1. Cancer Biology

eIF4E S209 phosphorylation licenses myc- and stress-driven oncogenesis

  1. Hang Ruan
  2. Xiangyun Li
  3. Xiang Xu
  4. Brian J Leibowitz
  5. Jingshan Tong
  6. Lujia Chen
  7. Luoquan Ao
  8. Wei Xing
  9. Jianhua Luo
  10. Yanping Yu
  11. Robert E Schoen
  12. Nahum Sonenberg
  13. Xinghua Lu
  14. Lin Zhang
  15. Jian Yu  Is a corresponding author
  1. Department of Pathology, University of Pittsburgh School of Medicine, United States
  2. UPMC Hillman Cancer Center, United States
  3. Department of Stem cell and regenerative medicine, Daping Hospital, Army Medical University, China
  4. Central laboratory, State key laboratory of trauma, burn and combined Injury, Daping Hospital, China
  5. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, United States
  6. Department of Biomedical informatics, University of Pittsburgh School of Medicine, United States
  7. Departments of Medicine and Epidemiology, University of Pittsburgh, United States
  8. Department of Biochemistry, Goodman Cancer Research Centre, McGill University, Canada
https://doi.org/10.7554/eLife.60151
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Cite this article
  1. Hang Ruan
  2. Xiangyun Li
  3. Xiang Xu
  4. Brian J Leibowitz
  5. Jingshan Tong
  6. Lujia Chen
  7. Luoquan Ao
  8. Wei Xing
  9. Jianhua Luo
  10. Yanping Yu
  11. Robert E Schoen
  12. Nahum Sonenberg
  13. Xinghua Lu
  14. Lin Zhang
  15. Jian Yu
(2020)
eIF4E S209 phosphorylation licenses myc- and stress-driven oncogenesis
eLife 9:e60151.
https://doi.org/10.7554/eLife.60151
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Abstract

To better understand a role of eIF4E S209 in oncogenic translation, we generated EIF4ES209A/+ heterozygous knockin (4EKI) HCT 116 human colorectal cancer (CRC) cells. 4EKI had little impact on total eIF4E levels, cap binding or global translation, but markedly reduced HCT 116 cell growth in spheroids and mice, and CRC organoid growth. 4EKI strongly inhibited Myc and ATF4 translation, the integrated stress response (ISR)-dependent glutamine metabolic signature, AKT activation and proliferation in vivo. 4EKI inhibited polyposis in ApcMin/+ mice by suppressing Myc protein and AKT activation. Furthermore, p-eIF4E was highly elevated in CRC precursor lesions in mouse and human. p-eIF4E cooperated with mutant KRAS to promote Myc and ISR-dependent glutamine addiction in various CRC cell lines, characterized by increased cell death, transcriptomic heterogeneity and immune suppression upon deprivation. These findings demonstrate a critical role of eIF4E S209-dependent translation in Myc and stress-driven oncogenesis and as a potential therapeutic vulnerability.

Introduction

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide (Siegel et al., 2019). The gatekeeper tumor suppressor APC is mutated in 85% of CRCs and leads to increased Wnt/Myc signaling which cooperates with mutational activation of RAS/RAF/ERK (50–80%) and PI3K/AKT/mTOR pathways (10–15%) to promote CRC initiation and progression (Vogelstein et al., 2013). Emerging evidence suggests that oncogenic drivers such as Myc do not simply increase ‘physiologic’ proliferation (Dang, 2016), but engender ‘oncogenic’ growth and hallmarks such as altered metabolism, resistance to cell death, metastasis, and immune evasion (Hanahan and Weinberg, 2011). Since direct targeting Myc (Dang et al., 2017) or mutant KRAS (Vogelstein et al., 2013) has not been successful in the clinic, intense interest remains to identify potential druggable targets in their regulatory circuitry.

mRNA translation is a highly energy-consuming and regulated process, and a converging target of oncogenic drivers (Pelletier et al., 2015; Truitt and Ruggero, 2016). The assembly of cap-binding complex eIF4F, consisting of the eukaryotic translation initiation factor 4E (eIF4E), RNA helicase eIF4A and scaffold eIF4G, is the rate-limiting step in translation initiation, which entails the unwinding of the secondary structure in the mRNA 5’UTR to facilitate recruitment of the 43S pre-initiation complex (PIC) containing the 40S ribosome and the eIF2α-GTP-Met-tRNA ternary complex for AUG codon recognition. Phosphorylation of eIF4E (S209) (p-4E, thereafter) and its inhibitor 4E-BP1 (i.e. T37/T46, S65/T70) is elevated in a variety of cancers due to activated RAS/RAF/ERK and PI3K/AKT/mTOR signaling (Martineau et al., 2013). Map kinase-interacting kinase 1 and 2 (Mnk1 and Mnk2) are activated by ERK or p38 MAPKs in response to a variety of extracellular stimuli to phosphorylate eIF4E (Wang et al., 1998). Constitutive or inducible p-4E is mediated by Mnk1/2 that are dispensable for normal development (Ueda et al., 2004; Ueda et al., 2010). p-4E is required for cellular transformation (Topisirovic et al., 2004) but dispensable for normal development in mice (Furic et al., 2010). 4E-BP1 and 4E-BP2 in their un- or hypo-phosphorylated forms are believed to inhibit eIF4E-eIF4G binding and even p-4E levels (Martineau et al., 2013). Genetic ablation of either or both Eif4ebp1 and Eif4ebp2 in mice leads to metabolic defects not spontaneous tumorigenesis (Le Bacquer et al., 2007). Genetic alterations in EIF4E or EIF4E4EBP1 and 2 are extremely rare or absent in human cancer. The oncogenic function of p-4E and its regulation remain to be better defined and likely go far beyond increased cap binding or global mRNA translation (Martineau et al., 2013).

Phosphorylation of eIF2α (S51, p-eIF2α, thereafter) is the core of evolutionally conserved ‘integrated stress response’ (ISR) (Hetz et al., 2013; Tabas and Ron, 2011; Tameire et al., 2015; Cubillos-Ruiz et al., 2017) and elevated in many cancers including CRC (Schmidt et al., 2019; Schmidt et al., 2020). In mammals, four eIF2α kinases are activated by distinct stresses such as nutrient deficiency, misfolded proteins, viral infection, or oxidative stress, and GCN2 is activated by amino acid starvation and conserved from yeast to human (Castilho et al., 2014). Elevated p-eIF2α inhibits global cap-dependent translation, while facilitates translation of stress-related proteins such as ATF4 and CHOP to regulate adaptation and recovery through widespread changes in transcription, translation, and metabolism. Failure to adapt leads to unresolved ISR, persistent CHOP elevation, and apoptosis via the induction of DR5 and BH3-only proteins (Tabas and Ron, 2011; Harding et al., 2003).

In the current study, we sought to better understand the oncogenic role of p-4E. Using EIF4E S209A/+ knockin (4EKI) human colon cancer cells and mice, human CRC organoids and adenoma samples, we uncovered a key role of p-4E in Myc and ATF4 translation, which promotes ISR-dependent glutamine metabolism, AKT signaling and oncogenic proliferation. Mutant KRAS cooperated with Myc to promote p-4E and ISR-dependent glutamine addiction and transcriptomic heterogeneity upon deprivation. Our findings support a critical role of eIF4E S209-dependent translation in Myc- and stress- driven CRC initiation and progression.

Results

eIF4E S209 regulates colon cancer cell growth and Myc translation

p-4E and p-4E-BP1 (S65/T70) are highly elevated in many types of cancers including CRC (Truitt and Ruggero, 2016; Martineau et al., 2013; Fan et al., 2009), while their mRNA or total protein levels do not increase significantly in the Cancer Genome Atlas (TCGA) CRC cohort (n = 640) (Figure 1—figure supplement 1A). To understand the oncogenic function of p-4E, we created EIF4ES209A/+ KI (4EKI thereafter) HCT 116 colon cancer cells using AAV-mediated gene editing (Figure 1A–B, Figure 1—figure supplement 1B–C). Compared to HCT 116 parental (WT) cells under normal growth conditions, 4EKI cells showed a strong reduction in p-4E and unexpectedly in p-4E-BP1 (S65/T70), p-AKT(S473), with no change in total eIF4E, 4E-BP1, p-4E-BP1(T37/46), p-mTOR (2448), p-S6 or p-ERK (Figure 1A). 4EKI slightly reduced 2D growth after day 5, as well as steady-state ATP levels (by 40%) and proliferation (by 20%) (Figure 1C, Figure 1—figure supplement 1D–F). 4EKI modestly reduced clonogenic and anchorage-independent growth, and severely impaired 3D spheroid growth (by 80%) (Figure 1D–F). We were unable to expand or obtain any homozygous 4EKI/KI HCT 116 clone, or heterozygous 4EKI clone in RKO or HT29 cells despite repeated attempts.

Figure 1 with 1 supplement see all
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eIF4E S209 regulates CRC cell growth.

Isogenic HCT116 WT and two independent EIF4ES209A knockin (S209A/+, 4EKI1, and 4EKI2) clones were analyzed for growth. (A) The indicated proteins in log-phase cells were analyzed by western blotting. Actin is the loading control. (B) Genomic DNA sequencing confirmed T to G (S209A) change in 4EKI cells. (C) Cell growth monitored for 7 days by counting. (D–F) Representative images and quantification (bottom) of cell growth in clonogenic assay, soft agar, and spheroids on day 10, day 14, and day 7, respectively. (F) Scale bar: 10 μM. WT values were set at 100%. C, D, E, F, values are mean+s.d. (n = 3). *p<0.05, **p<0.01, ***p<0.001 (Student’s t-test, two tailed). WT vs. KI.

We next examined the effects of 4EKI on translation in unstressed HCT 116 cells. 4EKI slightly reduced global mRNA translation, as measured by polysome profiling and activities of cap-dependent Luciferase and GFP reporters (by ~20%) (Figure 2A–C, Figure 2—figure supplement 1). eIF4G and 4E-BP1 bind to eIF4E competitively. In untransformed cells such as mouse fibroblast cells (MEFs), serum or growth factor stimulates cap (m7GTP) binding of eIF4G with 4E-BP1 dissociation (Martineau et al., 2013). In HCT 116 cells, serum enhanced eIF4G binding without 4E-BP1 dissociation. 4EKI reduced serum-induced eIF4G binding and increased 4EBP1 dissociation. eIF4E-cap binding was not affected by either serum or 4EKI (Figure 2D). We then analyzed several well-established eIF4E targets (Pelletier et al., 2015), and found a strong reduction of Myc and MMP7 protein in 4EKI cells, correlated with preferential reduction in the polysomal over total cellular mRNAs. Other known 4E targets (Cyclin D, Bcl-xL) or 4E itself, a Myc target, showed little difference in either protein or mRNA (Figure 2E–H). eFT508 is a highly selective Mnk1/2 inhibitor and reduces p-4E (Xu et al., 2019). eFT508 treatment impaired the growth of three CRC organoids at 48 hr, and abrogated p-4E and reduced levels of p-4EBP1(S65/T70) and Myc at 24 hr, without affecting total eIF4E (Figure 2I–J). These data demonstrate that p-4E promotes optimal growth of CRC cells by maintaining p-4E-BP1, AKT signaling and translation of oncogenic targets such as Myc and MMP7.

Figure 2 with 1 supplement see all
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eIF4E S209 regulates Myc translation in CRC.

WT and 4EKI cells were analyzed for translation. (A) Polysome profiling of log-phase cells. (B) Cap-dependent luciferase reporter activities were measured 24 hr after transfection with pcDNA-LUC reporter. (C) Translation of a bi-cistronic construct pYIC encoding cap-dependent and -independent reporters was analyzed by western blotting 24 hr after transfection. (D) The cells were subjected to serum starvation for 48 hr then stimulated with 10% FBS (+) for 4 hr. Binding of indicated eIF4F components (E, G, and 4E-BP1) to a synthetic cap analog (m7GTP) or their levels in the total lysate (input) were analyzed by western blotting. (E) The indicated eIF4E targets were analyzed by western blotting. Actin is the loading control. (F) The indicated transcripts in total cellular and (G) in polysomal RNAs were analyzed by RT-PCR. (H) The ratio of mRNA in polysome and total RNA normalized to WT (100%). N = 3. (B, F-H), values are mean+s.d. (n = 3). *p<0.05, **p<0.01 (Student’s t-test, two tailed). WT vs. KI. (I) Representative images of three CRC organoids treated with eFT508 (10 μM) for 48 hr. Scale bar: 100 µM. (J) The indicated proteins in CRC organoids treated with eFT508 at 24 hr were analyzed by western blotting.

eIF4E S209 promotes colon cancer growth in vivo through Myc and the ISR. c-Myc is the critical CRC driver and essential for cell proliferation, and controls transcription of up to 14% of the genome and virtually every aspect of metabolism (Dang, 2016). Myc regulates gene expression via target-specific and more general and target-independent mechanisms (Baluapuri et al., 2020). This presents a challenge and critical need to uncover p-4E-dependent Myc transcriptional programs in CRC. We compared transcriptomes in WT and 4EKI cells using cDNA microarrays (Figure 3—figure supplement 1A). Significantly downregulated genes in 4EKI cells (89, 3-fold or more) were mapped to the ISR, including upstream regulators (ATF4, CHOP, ATF3, GADD34/45B), and effectors in translation (tRNA synthetases), amino acid and glutamine (Gln) metabolism, and apoptosis (Figure 3A, Figure 3—figure supplement 1B, Supplementary file 1A). Significantly upregulated genes in 4EKI cells (70, 3-fold or more) were mapped to DNA replication and collagen formation, in addition to stress (Figure 3—figure supplement 1C–D). We detected mRNAs of ATF4, DDIT3 (encoding CHOP) and several Gln metabolic genes (SLC1A5 (ASCT2), ASNS, GLS, GOT1, SLC7A5) in total cellular and polysomal RNAs (Figure 3B–C, Figure 3—figure supplement 1E–F). Reduction of ATF4 and DDIT3 in 4EKI cells was more significant in polysomal RNAs, compared to ISR effectors. SiRNA of MYC, ATF4, or DDIT3 significantly reduced the expression of Gln metabolic genes in WT cells (Figure 3D). Established Myc targets involved in glycolysis, lipid, or nucleotide metabolism were not significantly affected by 4EKI (Figure 3—figure supplement 1G, Supplementary file 1B).

Figure 3 with 1 supplement see all
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eIF4E S209 regulates CRC growth and the ISR in vivo.

Paired HCT116 WT and 4EKI cells were characterized in vitro and in vivo. (A) Reactome Pathway analysis of genes elevated in WT cells (3-fold or more) visualized by ClueGO. (B) RT-PCR of indicated transcripts in total and (C) in polysomal RNAs. (D) The indicated transcripts were analyzed by RT-PCR in HCT116 cells transfected with the indicated siRNAs for 24 hr. N = 3. (E–K) Xenograft tumors. (E) The growth curve of WT and KI (KI1 and KI2) cells (four million) injected s.c. into different flanks of nude mice by day 23. (F) Representative images of WT and KI (KI1) xenografts on day 23. (G) Representative IF/IHC of the indicated makers in randomly chosen WT and KI tumors. Scale bar: 50 µm and (H) quantification of markers in (G) using 400x fields. (H) Representative PLA of eIF4E-4E-BP1 binding, scale bar: 25 µm, and (J) quantification (dots/cell). (K) The indicated transcripts were detected by RT-PCR. WT values were set at 100%. (B-D, F, H, J-K), values represent mean+s.d. (n = 3 or as indicated). *p<0.05, **p<0.01, ***p<0.001 (Student’s t-test, two tailed). WT vs. KI. +p<0.05, ++p<0.01, (one-way ANOVA with TUKEY post-hoc test), or scrambled vs. specific siRNAs.

We next compared the growth of 4EKI and parental cells in vivo. 4EKI clones showed marked reduction in engraftment efficiency (30–50%) and growth rate (over 90%) in nude mice (Figure 3E–F). 4EKI tumors were very small and showed near complete loss of p-4E, p-4E-BP1 (S65/T70), with drastic reduction in Myc, proliferation (Ki-67), ISR (p-GCN2, p-eIF2a) and AKT (S473) (Figure 3G–H), but marked stabilization of eIF4E and 4E-BP1 interaction (over 1000-fold) as measured by PLA (Figure 3I–J). p-GCN2 and p-eIF2a staining was punctate in xenograft tumors (Figure 3—figure supplement 1H). The expression of EIF4E was unchanged in 4EKI tumors, while that of ATF4, DDIT3, MYC was moderately reduced. The expression of Gln metabolic and translational targets was more severely reduced (by 60–90%) (Figure 3K). Among them, glutaminase (GLS) and leucine transporter SLC7A5 are key regulators of glutamine-dependent biosynthesis and mTOR activation (Palm and Thompson, 2017). Cell death (TUNEL), p-S6, or EIF4E was unchanged in 4EKI tumors with a minor reduction in several apoptotic targets such as TNFRSF10B (DR5) and PMAIP1 (NOXA) (Figure 3G, Figure 3—figure supplement 1I–J). The expression of Gln metabolic and apoptotic targets (SLC1A5, SLC7A5, BBC3, TRIB3 and PMAIP1) is also elevated in TCGA CRC cohorts (Figure 3—figure supplement 1K). These data support that p-4E promotes Myc- and ATF4-driven CRC growth through chronic exploitation of the most ancient arm of ISR (GCN2) to maintain constitutive AKT/4E-BP1 signaling.

eIF4E S209 promotes Myc- and ISR-driven tumor initiation and progression

ApcMin/+ mice are a widely used model for Myc-driven cancer initiation and polyposis (Qiu et al., 2010; Leibowitz et al., 2014). Polyps developed in ApcMin/+ mice showed highly elevated p-4E, p-4E-BP1 (S65/T70), Myc, p-AKT (S473) and p-eIF2α, compared to highly proliferative (Ki-67+) adjacent ‘normal’ crypts (Figure 4A). p-eIF2α and p-AKT (S473) staining was punctate in the polyps and largely absent in the crypts (Figure 4A). Mice homozygous for the Eif4eS209A allele (4EKI/KI) develop normally (Furic et al., 2010). Crossing 4EKI (S209A) allele onto ApcMin/+ mice significantly reduced tumor burden in a dose-dependent manner (Figure 4B–C, Figure 4—figure supplement 1A–B). Intestinal analysis revealed uniform p-4E staining in the proliferating zone (Ki-67+) of the crypts in WT but not 4EKI ApcMin/+ mice (Figure 4—figure supplement 1C). However, 4EKI had no effect on intestinal proliferation (Ki-67), or the expression of Eif4e, Myc, or Atf4, while significantly reduced the expression of Ddit3, and several metabolic, translational, and apoptotic ISR targets (Figure 4—figure supplement 1D–F). In contrast, 4EKI polyps showed no p-4E staining, reduced p-4E-BP1, Myc and p-AKT (Figure 4D–E), with little effect on Myc mRNA, Ki-67, or p-S6 compared to WT polyps at similar sizes (Figure 4F, Figure 4—figure supplement 1G–H). However, a potential role of p-4E in non-epithelial compartments or p-4E-independent mechanisms cannot be ruled not. We also found that p-4E, not total eIF4E, is highly elevated in human adenomas (Figure 4G), consistent with highly elevated Myc protein in these precursor lesions and modestly elevated mRNA (He et al., 1998). These data establish that p-4E is a rate-limiting factor in Myc- and ISR-dependent AKT signaling and oncogenic proliferation.

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eIF4E S209 promotes Myc-driven oncogenesis in mice and human.

(A) Representative IF of indicated markers in polyps and adjacent ‘normal’ crypts in ApcMin/+ mice. Scale bar: 100 µm. (B) Representative images of polyps and (C) quantification in the small intestine of 3-month-old ApcMin/+ (4E+/+) (n = 5), ApcMin/+;4EKI/+ (n = 8), and ApcMin/+;4EKI/KI (n = 4) mice. ++p<0.01, +++p<0.001 (One-Way ANOVA with TUKEY Post-hoc test). (D) Representative IF of indicated markers and (E) quantitation in the polyps in indicated mice. Scale bar: 100 µM. (F) Myc mRNA levels in the polyps from indicated mice. (G) p-4E (S209) and total eIF4E in human adenomas and normal colon analyzed by western blotting. Actin is a loading control.

eIF4E S209 promotes Myc- and ISR-dependent glutamine addiction

The above and the effects of Mnki on CRC organoids (Figure 2I–J) suggest that p-4E-dependent increase in Myc and glutamine metabolism might serve as a druggable vulnerability. Both glucose and Gln were required for the growth of HCT116 cells in culture, while 4EKI reduced cell loss and apoptosis upon deprivation of Gln, not glucose (Figure 5A–C). In WT cells, cell death and caspase-3 cleavage from 24 to 48 hr followed a rapid loss of p-4E/4E-BP1 (S65/T70) and Myc, and increased activation of ISR (p-GCN2/p-eIF2a and ATF4/CHOP) by 4 hr. The levels of apoptotic targets (DR5 and PUMA) decreased transiently by 4 hr and strongly increased by 24 hr (Figure 5D), indicative of failed recovery with increased cell death. In contrast, 4EKI cells showed reduced basal levels of Myc, ISR and p-AKT, transient ISR induction. Reduced or abrogated induction of ATF4, CHOP and apoptotic targets by 24 hr was consistent with a more successful recovery (Figure 5D). The kinetics or levels of p-4E-BP1 (T37/46), p-ERK, p-mTOR (S2448), p-S6, p-PERK, cyclin D1 were not significantly affected by 4EKI, while feedback AKT activation at 24 hr was observed in both cell lines and higher in WT cells (Figure 5D).

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p-4E promotes ISR-dependent glutamine addiction.

Isogenic HCT 116 WT and 4E KI cells were subjected to glutamine deprivation (2 to 0 mM), glucose deprivation (4 to 0 mM) or GLS inhibitor (CB-839, 40 µM) treatment, and analyzed at indicated times (0–48 hr). (A) Attached cells were stained with crystal violet at 48 hr. (B) Cell death were analyzed at 48 hr by flow cytometry and (C) quantification of AnnexinV+ cells. Representative flow cytometry plots and results are shown. (D) The indicated proteins were analyzed by western blotting at indicated times after Gln deprivation. (E) Heatmap of indicated transcripts in polysomes at 24 hr were analyzed by RT-PCR, normalized to WT 0 hr (Siegel et al., 2019). (F–G) WT cells were transfected the indicated siRNAs for 24 hr, followed by 24 hr recovery, and subjected to glutamine deprivation. (F) Heatmaps of indicated transcripts in total RNA at 24 hr were analyzed by RT-PCR, normalized to WT 0 hr (Siegel et al., 2019). (G) Cell death at 48 hr was quantitated by Annexin V+ cells. (H) 4EKI cells were transfected with control, Myc or ATF4 expression construct and subjected to glutamine deprivation. Cell death at 48 hr was quantitated by Annexin V+ cells. (I) Cell death 48 hr after GLSi was quantitated by Annexin V+ cells.

RT-PCR analysis using polysomal and total cellular RNAs further revealed coordinated transcription and translation during the ISR. MYC loss and ATF4 induction was rapid and primarily in polysomal fractions, while increases in CHOP and downstream effectors (metabolic and apoptotic) were in both fractions (Figure 5E–F). Knockdown of MYC, ATF4, and to lesser extent, DDIT3, SLC1A5, or ASNS, reduced cell death along with the basal and ISR induction in WT cells upon Gln deprivation (Figure 5F–G, Figure 5—figure supplement 1A). Compared to the increase in ISR effectors, the reduction of MYC was minimal in the total RNAs by Gln deprivation, 4EKI, or knockdown of ATF4 or DDIT3, confirming a key role of its posttranslational regulation (Figure 5F). Conversely, overexpression of MYC or ATF4 increased the ISR and apoptosis in 4EKI cells (Figure 5H, Figure 5—figure supplement 1B). The sensitivity to Gln deprivation was dose-dependent in parental cells (Figure 5—figure supplement 1C–D) and blunted in the independent 4EKI2 clone (Figure 5—figure supplement 1E–G). In addition, 4EKI cells were less sensitive than parental cells to GLS inhibitor CB-839 with reduced apoptosis and ISR induction (Figure 5I, Figure 5—figure supplement 1H–I). Together, these findings establish p-4E/Myc in promoting glutamine addiction in CRC cells via ISR hyperactivation and failed recovery upon withdraw.

Mutant KRAS cooperates with p-4E/Myc to promote glutamine addiction and immune suppression

KRAS mutations are frequently found after APC inactivation in large colonic adenomas (Vogelstein et al., 2013). Established CRC lines including HCT 116 often harbor mutant KRAS or BRAF (Supplementary file 2), which leads to constitutive ERK/MAPK signaling and elevated p-4E (Ueda et al., 2004; Ueda et al., 2010). We then determined if mutant KRAS contributes to glutamine addiction via p-4E/Myc and the ISR. Isogenic CRC cells (HCT116, Lim1215 and SW48) harboring mutant KRAS (G13D or G12V) showed higher basal levels of p-ERK, p-4E/4E-BP1, p-eIF2α and Myc, and are more sensitive to Gln deprivation, compared to their KRAS wildtype counterparts (Figure 6A–B). The increased sensitivity was associated with elevated apoptosis and ISR, and reduced Myc, p-4E but not p-ERK (Figure 6C–E, Figure 6—figure supplement 1A–C).

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Mutant KRAS and Myc promotes p-4E-dependent glutamine addiction.

Indicated WT and mutant KRAS isogenic CRC lines were subject to glutamine deprivation and analyzed. (A) The basal levels of indicated proteins were analyzed by western blotting. (B) Attached cells at 48 hr were stained with crystal violet. (C) Cell death at 48 hr was quantitated by flow cytometry. Representative results were shown. (D) The indicated proteins at 24 hr in two pairs of cell lines were analyzed by western blotting. *, non-specific band. (E) Heat map of indicated transcripts at 24 hr were detected by RT-PCR and normalized to the control (WT, Gln+, 1). (F) Numbers of differential genes upon Gln deprivation in the isogenic HCT 116 pair, 2-fold or more, *p<0.05. (G) Venn diagram of induced genes from (F). (H–J) Reactome pathway analysis of (H) shared, WT (I), and 4EKI-specific upregulated genes(J). Top five enriched pathways are shown.

We further analyzed transcriptomic landscapes to better understand the role of p-4E in the response of mutant KRAS to Gln deprivation. 4EKI significantly reduced the overall transcriptional response induced at either direction by nearly 50%, and drastically altered target selection (2-fold or more, Figure 6F–G, Figure 6—figure supplement 1D). Only a minor fraction of induced genes (117) (22% and 35%, respectively) was shared and mapped to stress and ATF4-related pathways (Top five non-overlapping) (Figure 6H). WT-specific induced genes (409,~78%) were mapped to transcription, cell cycle and cell death (Figure 6I), while 4EKI-specfic ones (217,~65%) were mapped to immune pathways (Figure 6J). These data support that p-4E critically controls the ISR level and outcomes such as cell death, transcriptional targets, and immune suppression in mutant KRAS CRC cells upon glutamine deprivation.

p-4E controls cell death and transcriptomic heterogeneity upon metabolic stress

We used a panel of CRC lines with diverse driver mutations (DLD1, RKO, SW480, and HT29) (Supplementary file 2), to further determine if elevated p-4E is associated with Gln addiction and transcriptional heterogeneity. The increased sensitivity was associated with higher basal p-4E/p-4E-BP1 and Myc, and enhanced ISR induction and reduced p-4EBP1 and Myc reduction upon deprivation, with little or no effect on the levels of p-ERK, p-4E, or p-S6 (Figure 7A–C). Cell death was correlated with the induction of p-GCN2/p-eIF2a, ATF4/CHOP and cleaved caspase-3 in RKO and H29 cells (Figure 7—figure supplement 1). We then analyzed induced genes in three CRC lines (HCT 116, RKO, and HT29 (MSI or MSS with mutant KRAS or BRAF)) sensitive to Gln deprivation. Among nearly 2000 induced genes (2-fold or higher), 100–200 (5–10%) were shared by any two cell lines. Only 53 genes (~4%) were shared by all three cell lines and mapped to ATF4, stress and angiogenesis (VEGF) (Figure 7D–E). Together, our data support that metabolic stress selectively triggers ISR-dependent cell death in p-4E/Myc high cells, which is associated with marked transcriptional heterogeneity (Figure 7F).

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p-4E controls metabolic stress-induced cell death and transcriptomic heterogeneity.

Indicated CRC lines were subject to glutamine deprivation and analyzed. (A) Attached cells at 48 hr were visualized by crystal violet. (B) The indicated proteins were analyzed by western blotting. (C) Transcripts at 24 hr were analyzed by RT-PCR and normalized to respective cell line controls (Gln+, 1). (D) Venn diagram of Gln deprivation induced genes in three sensitive cell lines. Two fold or more, *p<0.05. (E) Reactome Pathway analysis of shared genes (Silva-Almeida et al., 2020) in (D). (F) A model of p-4E in CRC development. CRC drivers converge on increased p-4E (S209) and p-4E-BP1(S65/T70) to promote Myc- and ISR (p-eIF2a/ATF4)-dependent adaptation and AKT activation via increased glutamine (Gln) metabolism. Acute metabolic stress (i.e. Gln deprivation) disrupts adaptation and triggers crisis in such cells due to rapid loss of p-4E/4E-BP1 and Myc and hyperactivation of ISR and p-AKT, leading to increased cell death and transcriptional heterogeneity.

Discussion

Translational reprogramming has emerged as a key regulator of cancer development, and the underlying mechanisms remain not fully resolved (Truitt and Ruggero, 2016; Robichaud et al., 2015; Robichaud et al., 2018). Our study demonstrates that p-4E-mediated Myc and ATF4 translation cooperates with mutant KRAS to promote CRC cell growth through ISR-dependent glutamine metabolism and AKT/p-4E-BP1 signaling (Figure 7F). High levels of p-4E and p-4E-BP1 (S65/70) are likely required to sustain Myc and ATF4 translation in cancers such as CRC with rare MYC gene rearrangements or amplifications (Vogelstein et al., 2013; Fan et al., 2009; He et al., 1998) and prominent increase in ribosomal biogenesis (Truitt and Ruggero, 2016; Zhang et al., 1997). These findings reveal fundamental differences between normal and oncogenic translation and proliferation. p-4E serves as an early and rate-limiting step in Myc- and stress-driven oncogenesis through GCN2-selective amino acid sensing and AKT activation. p-4E-dependent increase in Myc or AKT signaling is largely dispensable for rapid intestinal proliferation under homeostatic conditions.

Our data support a powerful and translational mechanism in shaping driver and TME interactions and evolution under metabolic stress (Figure 7F; Robichaud and Sonenberg, 2017). This finding is consistent with the lack of metastasis-specific mutations or driver heterogeneity in treatment-naïve CRCs (Jones et al., 2008; Reiter et al., 2018). The ISR is intrinsically redundant, heterogeneous, and crosstalk with mTOR signaling (Hetz et al., 2013; Tabas and Ron, 2011; Appenzeller-Herzog and Hall, 2012), which is increasingly recognized as an engine of ‘non-oncogenic addiction’ (Tameire et al., 2015; Cubillos-Ruiz et al., 2017; Luo et al., 2009). The levels of p-4E/4E-BP, p-eIF2α, and p-AKT are heterogenous in the TME (Figure 4; Le Bacquer et al., 2007). Our data showed that mutant KRAS cooperates with p-4E and Myc to promote ISR-dependent Gln addiction, which is characterized by increased cell death, transcriptional heterogeneity, and surprisingly immune suppression upon deprivation. Hyperactivation of Wnt/Myc and mutant RAS/RAF are strongly associated with cancer aggressiveness including immunosuppressive TME, absence of TILs, and resistance to immune checkpoint inhibitors (Ruan et al., 2020). Our data provide direct evidence that p-4E rewired translation and stress response is involved in this process through increased entropy or chaos (Tarabichi et al., 2013; Hanselmann and Welter, 2016) and target selection during chronic metabolic adaptation and competition within tumor cells and with the TME (Palm and Thompson, 2017; Andrejeva and Rathmell, 2017). Our findings are consistent with the notion that p-4E is linked to increased aggressiveness through the translation of immune checkpoint PD-L1 (24) and metastasis targets such as SNAIL and MMP3 (30) in Myc, mutant KRAS or PI3K-driven cancer models. ISR-dependent and sustained metabolic (Gln) and translation (tRNA synthetases) (Han et al., 2013) pressure can lead to cell death, while transient pressure likely permits better cell survival and Myc recovery (Dejure et al., 2017). Therefore, nutrient- and p-4E-sensitive translation is predicted to dynamically regulate the extent and heterogeneity of tumor intrinsic ISR, TME interaction and outcomes, which is worth further explorating (Figure 7F).

Our study helps shed some light on the biochemical nature of oncogenic translation and supports a ‘coded’ model, in which elevated p-eIF4E/4E-BP and p-eIF2α chronically ‘stress’ translation toward targets such as Myc, ATF4 and MMP7. This ‘coded’ model is supported by dynamic changes in their phosphorylation and binding under stress, target selection coupled with transcription, and dynamic 4F and target interactions (Costello et al., 2017). This model is also in line with the notion that ‘reprogrammed’ translation serves specialized roles including immunity (Pelletier et al., 2015; Truitt and Ruggero, 2016; Xu et al., 2019; Harding et al., 2000), and regulatory roles of extensive phosphorylation sites in 4E-BP1 (T37/T46, S65/T70, S83, S101, and S112) and family members (Martineau et al., 2013). Punctate staining of p-GCN2 and p-eIF2a and 4E-4EBP1 interaction in xenografts also supports transient and localized GCN2-eIF2a regulation (Castilho et al., 2014) with dynamic translation control during tumor evolution (Figure 7F). High p-4E levels render 4E-BP1 and Cap binding insensitive to serum or growth factors (Figure 2D). It will be interesting to determine whether and how these ‘trans’ codes might work with various ‘cis’ elements in mRNAs to control the extent and levels of inducible translation in the context of oncogenic drivers. Careful dissection of site-specific and conditional 4E/4E-BP mutants using appropriate in vivo models will help better understand how stress maladaptation leads to cancer and other chronic diseases (Tameire et al., 2015; Cubillos-Ruiz et al., 2017; Luo et al., 2009) at the systems level.

Myc, mutant RAS/RAF, or PIK3CA fuels abnormal growth by altering nutritional needs, including increased glutamine utilization. However, direct targeting a single driver, a single metabolic step, p-4E, or p-4E-BP1 has limited success in the clinic so far, due to complex resistance mechanisms encompassing compensatory pathway activation, metabolic bypasses, apoptosis resistance and immune suppression (Dang et al., 2017; Pelletier et al., 2015; Truitt and Ruggero, 2016; Palm and Thompson, 2017; Ruan et al., 2020; Lito et al., 2013; Zhang and Yu, 2013). Our model supports that Myc-driven metabolic addiction likely goes beyond Gln to other nutrients and reducing agents such as arginine, cystine, and glutathione necessary to support increased biosynthesis (Figure 7F). Elevated ISR in such tumors might therefore offer a therapeutic vulnerability. In fact, CRCs harboring mutant RAS/RAF or SPOP can be more effectively killed by drug combinations through catastrophic ISR associated with features of immunogenic cell death (He et al., 2013; He et al., 2016a; He et al., 2016b; Li et al., 2017; Tan et al., 2019), which is believed to help achieve more durable cancer control in patients (Ruan et al., 2020). The use of in-treatment and patient-derived models (Silva-Almeida et al., 2020) will likely be important to capture dynamic transcriptional responses and biomarkers for tailoring therapeutic inventions.

In summary, we demonstrate that p-4E-rewired translation is essential for Myc- and stress-driven oncogenesis. These findings provide a more unified mechanism to explain how cancer hallmarks are continuously shaped by drivers and the TME. Elevated p-4E and ISR is a potential therapeutic vulnerability in CRCs that are dependent on high levels of Myc and mutant KRAS.

Materials and methods

Cell culture and treatment

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The human CRC cell lines, including HCT116, DLD1, RKO, SW480, and HT29 were obtained from the American Type Culture Collection (Manassas, VA, USA). Isogenic KRAS pairs HCT116 (WT, G13D), Lim 1215 (WT, G13D, G12V), and SW48 (WT, G13D, G12V) cell lines were obtained from Bert Vogelstein at Johns Hopkins University as described (Yun et al., 2009). Information on major drivers or isogenic cell lines are found in (Supplementary file 2).

Authentication of purchased cell lines was provided by ATCC. Genetically modified cell line pairs were additionally verified by published biomarkers compared with parental (unmodified ATCC parental lines) as well as DNA sequencing and western analysis. Cell lines were regularly monitored and confirmed to be absence of Mycoplasma. All cell lines were used for less than 2 months (10 or fewer passages) in culture upon thawing from LN tank. All cell lines were cultured in McCoy’s 5A modified medium (Invitrogen, Carlsbad, CA, USA, Cat# 16600–082) supplemented with 10% defined fetal bovine serum (Hyclone, Logan, UT, USA, Cat # SH3007103), 100 units/ml penicillin, and 100 µg/ml streptomycin (Invitrogen) unless noted otherwise. Cells were maintained in a 37°C incubator at 5% CO2. mRNA or protein was analyzed at 24 hr while cell growth or death at 48 hr, unless noted otherwise.

EIF4ES209/+ knockin human CRC cells

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The EIF4ES209A (4EKI) targeting vector was constructed using the pUSER-rAAV (recombinant adeno associated virus) System (Zhang et al., 2008). Briefly, 2 0.8 kb homologous arms flanking the seventh intron of eIF4E were inserted between 2 USER sites in the AAV shuttle vector pTK-Neo-USER. The coding sequence for eIF4E single mutant (S209A) was introduced into the right arm using the QuickChange XL Site-Directed Mutagenesis Kit (Agilent Technologies, Cat# 200516). For gene targeting, HCT116 cells were infected with the targeting rAAV and selected by G418 (0.5 mg/ml; Mediatech) for 3 weeks. G418-resistant clones were pooled and screened by PCR for targeting events. To target the second allele, Neo flanked by 2 LoxP sites was excised from a heterozygous clone (209S/209A) by infection with an adenovirus expressing Cre recombinase (Ad-Cre) followed by isolation of single clones. The same targeting construct was used in the second round of gene targeting. The 4EKI targeting in independent HCT 116 clones was verified by sequencing of genomic DNA and Western blotting. We were unable to obtain or recover any homozygous 4E KI (209A/209A) HCT 116 cells after three rounds (3–4 T75s/each round, ~1 billion cells in total) with only retargeting events of the ‘Cred’ 4E KI allele. We were unable to obtain or expand any 4E KI (209S/A) heterozygous RKO or HT29 clones (p-4E high) from multiple PCR positive pools identified initially in 96-well plates. Details on screening and validation primers are found in (Supplementary file 3A).

Colony formation assay. 600 cells were plated in 6-well tissue culture plates. Cells were maintained at 37°C/5% CO2 and allowed to grow for 10 days with media changed every other day. At the conclusion of 10 days, cells were washed once with HBSS before staining with Crystal violet dye for 10 min. Cells were then washed three times with HBSS and photographed. All conditions were performed in triplicate.

Soft agar assay. Agar plates were prepared in 6-well petri dishes by first applying a 1.5 ml base layer of 1.6% agar (Invitrogen, Cat# 16500500) in Dulbecco's modified Eagle's medium containing 10% fetal bovine serum. Over this basal layer, an additional 1.5 ml layer of 0.8% agar in the same medium/fetal bovine serum mixture, and 1,000 cells were added. The cells were incubated at 37°C in a humidified atmosphere of 5% CO2 in air and gently layer 2 ml of 1x media over top agarose containing cells next day. 2 weeks later, colonies were measured unfixed and unstained by using a microscope with a calibrated grid. Clones with greater than 50 cells were scored as positive.

Spheroid (3D) culture. Cells were plated into 96-well round–bottom ultralow attachment plates (Greiner Bio-one #650970) at densities of 100–3000 cells/well in 200 µl/well McCoy’s 5A modified medium (Invitrogen, Carlsbad, CA, USA, Cat# 16600–082) supplemented with 10% defined fetal bovine serum (Hyclone, Logan, UT, USA, Cat# SH3007103), 100 Penicillin-Streptomycin (10,000 U/ml) (Invitrogen #15140–122). Plates were briefly centrifuged at 250 g for 5 min and then incubated at 37°C and 5% CO2. Spheroids formed within approximately 24 hr. Cells were re-fed every 72 hr by carefully removing 100 µl of medium from each well and replenishing with 100 µl of fresh growth medium. The growth of spheroids was imaged at indicated times (3–7 days) using an Olympus BX51 system microscope equipped with SPOT camera and SPOT Advanced 5.1 software.

Analyses of cell viability, proliferation and cell death

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Cell counts. 50, 000 cells were plated in triplicate in each of a 12-well tissue culture plate. Following plating, cells were harvested at day 1, day 3, day 5, and day 7. Cells were trypsinized and counted using a hemacytometer.

Cell viability was measured by CellTiter 96 AQueous One Solution Cell Proliferation Assay (MTS) (Promega G3580), and ATP-based CellTiter-Glo Luminescent Cell Viability Assay Kit (Promega, G7570) was performed in 96-wells according to the manufacturer’s instructions. The absorbance at 490 nm and Luminescence was measured with a Wallac Victor 1420 Multilabel Counter (PerkinElmer, SKU#: 8381-30-1005). Following various treatments, attached cells or clones were stained and with crystal violet (Sigma, St. Louis, MO, Cat# C0775) (3.7% Paraformaldehyde, 0.05% crystal violet in distilled water and filtered at 0.45 um before use) (Yu et al., 2003).

Bromodeoxyuridine (BrdU) incorporation was analyzed in cells following 15 min BrdU (10 μM) pulse. Cells were washed three times with Hank’s following fixation with methanol: acetone (1:1) at −20°C for 15 min, and staining with a monoclonal Alexa Fluor 594 anti-BrdU conjugated antibody (Invitrogen, Cat# B35132) and DAPI, and scored under a fluorescence microscopy as described (Wang et al., 2009).

Cell death and apoptosis were analyzed by nuclear staining with cells harvested from 12-well plates and Hoechst 33258 (Invitrogen, Cat# 40045), and Annexin V/propidium iodide (PI) followed by flow cytometry as described (Yu et al., 2006). Experiments were repeated on two or more occasions (different days) with similar results. Flow cytometry plots and quantitation were based on the analysis of 20,000 cells for each condition. Results from one representative experiment are shown with fraction (%) of indicated population.

Glutamine deprivation. Cells were plated overnight in complete DMEM (10% FBS, 2 mM glutamine) briefly washed with phosphate-buffered saline (PBS) (Gibco #14175–095) and then transferred into glutamine-free medium (glutamine- and pyruvate-free DMEM (Corning Cellgro Cat# 15–017-CV)) supplemented with 10% dialyzed FBS (Gibco A3382001) and 1 mM sodium pyruvate (Gibco #11360070). The corresponding glutamine-replete medium was prepared by addition of 2 mM glutamine (Corning Cellgro #25–005 CI) to glutamine-free medium. In some experiments, cells were first transfected with siRNA or expression constructs for 24 hr and replated in complete medium 24 hr to reach 30 to 40% density before the treatment.

Drug treatment. Cells were plated in 12-well plates 24 hr before and reached 30 to 40% density at treatment. The chemicals used include 40 μM CB839 (MCE, HY-12248), All chemicals used were dissolved with DMSO (Sigma-Aldrich Cat # 276855) in the stock and diluted by culture medium with final DMSO concentration at or below 0.5%.

Real-time Reverse Transcriptase (RT) PCR

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Total RNA was isolated from cells using the Mini RNA Isolation II Kit (Zymo Research, Orange, CA) according to the manufacturer’s protocol. One μg of total RNA was used to generate cDNA using Superscript III reverse transcriptase (Invitrogen, Carlsbad, CA, USA). Real-time PCR was carried out as described with triplicates normalized to WT or untreated (He et al., 2013). Details on primers are found in the supplementary materials (Supplementary file 3B-C). Representative results are shown, and similar results were obtained in at least three independent experiments. cDNA was synthesized from RNA prepare from cells, or RNA pooled from 2 to 3 randomly chosen tumors in each group.

Western blotting

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Western blotting was performed as previously described (Yu et al., 2001). Details on antibodies were found in the supplemental materials (Supplementary file 3D).

Polysome fractionation

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HCT116 parental and 4EKI cells were maintained in high-glucose (4.5 g/L) DMEM media with 10% FBS, 100 μg/ml penicillin and 100 μg/ml streptomycin. Early passage cells (within four after thawing) were plated at 30–40% and allow to grow to approximately 80% confluence within two days, cells were treated with 100 μg/ml cyclohexamide (Sigma CAS:66-81-9) in fresh cell culture medium at 37°C for 10 min. Cells from two 10 cm-plate were scraped and incubated in 600 µl lysis buffer (20 mM Tris-HCl pH8, 140 mM NaCl, 1.5 mM MgCl2, 0.25% NP-40, 1% Triton-X 100, 10 mM DTT, 200 μg/ml cyclohexamide and 200 U/ml Rnasin) for 30 min on ice. Lysates were centrifugated at 12000 rpm for 10 min at 4°C and supernatants were loaded onto a 10–50% sucrose gradient with 1 mM DTT, 100 μg/ml cyclohexamide and 40 U/ml Rnasin. Samples were centrifugated at 40,000 rpm for 2.5 hr at 4°C (Beckman coulter, SW41 Ti rotor) and then separated on a BIOCOMP gradient fractionation system (Canada, BIOCOMP, Model 251) to evaluate polysome profiles and collect polysome fractions. RNA was isolated from polysome fractions using TRIpure LS Reagent (aidlab Cat# RN0202). Three sets of experiments were performed independently.

m7GTP Pull-down assay

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HCT116 parental and 4EKI cells were plated at 30–40% in T75s and allow to grow to 80% confluence within two days. Then cells were starved for 24 hr with Mycoy’s 5A alone without FBS. After that replaced the cell media with fresh Mycoy’s 5A without FBS for the control group or with 10% FBS for the stimulation group for another 4 hr. Immobilized gamma-Aminophenyl-7-methyl GTP (C10-spacer7-Methyl-GTP agarose beads from Amersham (Jena Bioscience, Germany, Cat# AC-155L)) was used for the pull-down assay using the method described previously with minor modifications (Xu et al., 2010a). In brief, 20 µl of m7 GTP agarose beads were washed with 500 µl of PBS three times, added to 300 μg of total protein from the cell lysates in 1 ml IP (RIPA buffer) lysis buffer and rotated overnight at 4°C. Cap-bound eIF4E and precipitates were washed 3 times with 500 µl IP lysis buffer and eluted using 100 µl protein sample buffer (1 M Tris pH6.8, 4% SDS, 20% Glycerol, 50% NaOH, and 10% β-Mercaptoethanol). The eluted proteins (20 µl) were analyzed by immunoblotting with 10% amount of input.

Transfection

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Transfection was performed using Lipofectamine 2000 (Invitorgen, Cat#11668019) according to the manufacturer’s instructions and described (He et al., 2016b). The human pRK-ATF4 and pcDNA3.3-c-MYC constructs were obtained from ADDGENE. Cells were transfected with 0.4 μg of Plasmids/well in 12-well plates for 4 hr. MYC, ATF4, DDIT3, SLC1A5 or ASNS small-interfering RNA (siRNA) duplexes were synthesized by Dharmacon (Lafayette, CO, USA). Cells were transfected with 400 pmols of siRNA duplexes/well in 12-well plates for 4 hr. Transfected cells after 4 hr were incubated in medium containing 5% FBS for 20 hr, replated in 10% FBS normal growth medium for 24 hr before treatment. Details for siRNA sequence and expression plasmids are found in (Supplementary file 3E-F) respectively.

Reporter assays. Cap-dependent luciferase reporter construct pcDNA-LUC (Yang et al., 2004) and bicistronic PIYC (Nie and Htun, 2006) were previously described. Cells in 12-well plate were transfected with 0.4 μg of the reporter and 2 µl of lipofectamine 2000 (Invitrogen, Cat#11668019). Cell lysates were collected 24 hr after transfections. Luciferase activities were measured and normalized to total protein level. All reporter experiments were performed in triplicate and repeated three times with similar results. HA- or Myc-tag reporters encoded by PIYC were analyzed by western blotting as described (Xu et al., 2010b).

Animal studies

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All animal experiments were approved by the University of Pittsburgh Institutional Animal Care and Use Committee. All methods were performed in accordance with the relevant guidelines and regulations. The protocols for the use of recombinant DNA and animals included IBC201700136, IACUC# 19085635 and 18063020.

Xenograft studies

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Female 5–6 week-old Nu/Nu mice (Charles River, Wilmington, MA) were housed in a sterile environment with micro isolator cages and allowed access to water and chow ad libitum. Mice were injected subcutaneously with 4 × 106 WT and 4EKI (KI1 or KI2) HCT116 cells on the opposite flanks of the same animal. Tumor growth was monitored by calipers, and tumor volumes were calculated according to the formula 0.5 × length × width2. Mice were euthanized when tumors reached 1.0 cm3 in size in WT group, approximately 9 days after palpable WT tumors. Tumors were harvested at the end of experiments for analysis as described (Yu et al., 2006). Tumors were dissected and fixed in 10% formalin and embedded in paraffin or saved frozen for RNA extraction.

Immunohistochemistry (IHC) and immunofluorescence (IF). Rehydrated sections were treated with 3% hydrogen peroxide (IHC only), followed by antigen retrieval for 10 min in boiling 0.1 M citrate buffer (pH 6.0) with 1 mM EDTA. Apoptosis was analyzed by TUNEL staining with the ApopTag Peroxidase In Situ Apoptosis Detection Kit (Chemicon International, Temecula, CA) according to the manufacturer’s instructions. Immunostaining was performed on 5 mm paraffin-embedded tumor sections using an Alexa Fluor 488- or Alexa Fluor 594-conjugated secondary antibody (Invitrogen) for detection. The details on the primary antibodies were found in (Supplementary file 3D).

Proximity ligation assay (PLA). Interactions of eIF4E and 4E-BP1 were detected by in situ PLA in paraffin-embedded sections. PLA was performed using the Duolink In Situ Redstarter Kit (Sigma Sigma-Aldrich Cat#DUO92101-1KT) according to the manufacturers’ instructions and with minor modifications (Chen et al., 2018). Incubation with primary antibodies (Supplementary file 3D) was performed at 4°C overnight. The stained sections were mounted with VECTASHIELD Mounting Medium (Vector Laboratories) with DAPI for nuclear counter staining. The results were visualized by fluorescence microscopy (OlympusBX51 system), and the number of PLA signals per field was counted and plotted (more than three fields).

ApcMin/+ and Eif4eS209A mice

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C57BL/6J Eif4eS209A homozygous (4EKI/KI) mice (Furic et al., 2010) were crossed with ApcMin/+ mice (Jackson Laboratory) to generate ApcMin/+ mice with different 4ES209 (209 S/S, 209S/A, or 209A/A) genotypes. Genotypes were verified by genomic PCR. For polyposis promotion, 4-wk-old mice were fed AIN-93G diets (Dyets) for two wks (~6 wk of age) for intestinal gene expression or two mo (12–13 wk of age) for tumor phenotype analysis. Following sacrifice, the small intestine and colon were harvested for gene expression analysis and photographing and numeration of the adenoma burden as described (Leibowitz et al., 2014; Qiu et al., 2009). All measures were quantified from three randomly chosen mice. The RNA was pooled from three intestinal preps to produce cDNA for real-time PCR. In some cases, multiple adenomas were snipped and pooled from the same mouse to prepare total RNA. Details on primers and antibodies as well as staining for cell proliferation, cell death and various markers are included in supplemental material (Supplementary file 3C and D).

Quantitative real-time polymerase chain reaction

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For gene expression analysis, fresh mucosal scrapings from 10 cm of jejunum were washed in cold PBS, resuspended in 700 µl of RNA lysis buffer, and homogenized in a Dounce homogenizer. RNA was isolated using the Quick-RNA MiniPrep kit (Zymo Research, Orange, CA, USA) according to the manufacturer’s instructions. cDNA was generated from 2 to 4 μg of total RNA pooled from three mice using SuperScript III reverse transcriptase (Invitrogen) and random primers. The expression was normalized to the house keeping gene GAPDH. WT values were set 1.

Tissue processing and staining

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The intestines were dissected immediately upon sacrifice, rinsed with cold saline, opened longitudinally and tacked to a foam board for fixation in 10% (vol/vol) formalin. Adenomas were counted under a dissecting microscope, after which tissues were rolled up into ‘swiss rolls’ for paraffin embedding and histological analysis. Histological analysis was performed by hematoxylin and eosin (H and E) staining.

Immunohistochemistry (IHC) and immunofluorescence (IF). All measures were quantified from swiss rolls of each mouse from three mice per group. Paraffin-embedded sections were subjected to deparaffinization and antigen retrieval (boiling for 10 min in 0.1 M citrate buffer, pH 6.0, with 1 mM EDTA), followed by staining. An Olympus BX51 microscope equipped with SPOT camera and SPOT Advanced 5.1 software was used to acquire the images.

Phospho-eIF4E: Sections were deparaffinized and rehydrated through graded ethanols. Antigen retrieval was performed by boiling for 10 min in 0.1 M citrate buffer (pH 6.0) with 1 mM EDTA. Non-specific antibody binding was blocked using 20% goat serum (Invitrogen) at room temperature for 30 min. Sections were incubated overnight at 4°C in a humidified chamber with 1:100 diluted rabbit anti-phospho-eIF4E (S209) (76256; Abcam). Sections were then incubated with AlexaFluor 594-conjugated goat anti-rabbit secondary antibodies (1:200; AA11012; Invitrogen) for 1 hr at room temperature (Yu et al., 2006). Sections were then washed in PBS and mounted with VectaShield + DAPI (Vector Labs).

Phospho-4E-BP1: Sections were prepared as described above. Non-specific antibody binding was blocked using 20% goat serum (Invitrogen) at room temperature for 30 min. Sections were washed in PBS and incubated overnight at 4°C in a humidified chamber with 1:100 diluted rabbit anti-4E-BP1 (S65/70) (9451; Cell Signaling). Sections were then incubated with AlexaFluor 594- conjugated goat anti-rabbit secondary antibodies (1:200; AA11012; Invitrogen) for 1 hr at room temperature. Sections were then washed in PBS and mounted with VectaShield + DAPI (Vector Labs) for visualization.

Phospho-S6: Sections were prepared as described above. Non-specific antibody binding was blocked using 20% goat serum (Invitrogen) at room temperature for 30 min. Sections were washed in PBS and incubated overnight at 4°C in a humidified chamber with 1:100 diluted rabbit anti-phospho-S6 (S235/236) (2211; Cell Signaling). Sections were then incubated with AlexaFluor 594- conjugated goat anti-rabbit secondary antibodies (1:200; AA11012; Invitrogen) for 1 hr at room temperature. Sections were then washed in PBS and mounted with VectaShield + DAPI (Vector Labs).

Ki67: Sections were prepared as described above. Non-specific antibody binding was blocked using 20% goat serum (Invitrogen) at room temperature for 30 min. Sections were washed in PBS and incubated overnight at 4°C in a humidified chamber with 1:100 diluted rat anti-Ki67 (M7249; DAKO). Sections were then incubated with AlexaFluor 594- conjugated goat anti-rat secondary antibodies (1:200; AA11007; Invitrogen) for 1 hr at room temperature. Sections were then washed in PBS and mounted with VectaShield + DAPI (Vector Labs).

Myc: Sections were prepared as described above. Non-specific antibody binding was blocked using 20% goat serum (Invitrogen) at room temperature for 30 min. Sections were washed in PBS and incubated overnight at 4°C in a humidified chamber with 1:100 diluted rabbit anti-Myc (Abcam 39688). Sections were then incubated with AlexaFluor 594- conjugated goat anti-rabbit secondary antibodies (1:200; AA11012; Invitrogen) for 1 hr at room temperature. Sections were then washed in PBS and mounted with VectaShield + DAPI (Vector Labs).

Human tissue samples

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De-identified Frozen specimens of normal colon and colonic adenomas (Wang et al., 1998) were obtained from the University of Pittsburgh Biospecimen CORE with tissue collection under informed consent and usage approved by the Institutional Review Board at the University of Pittsburgh under the protocol of REN11110076/IRB0411047.

Lysates were prepared and used for western blotting as described (Leibowitz et al., 2014). In brief, minced pieces of human normal colon and polyp tissue were washed in 1 ml of ice-cold PBS and pelleted at 400 g. Pellets were resuspended in 700 µl of homogenization buffer (0.25 M sucrose, 10 mM Hepes, and 1 mM EGTA) supplemented with protease inhibitors (cOmplete EDTAfree mini, Roche) and homogenized in a Dounce homogenizer with 50 strokes of the pestle. After clearing by centrifugation at 16,000 g, protein concentrations in the supernatant were determined by a spectrophotometer (NanoDrop 2000, Thermo Fisher Scientific). Proteins (20 μg) were separated by the NuPAGE system (Invitrogen) and transferred to polyvinylidene difluoride membranes (Immobilon-P, Millipore). Antibodies used are listed in (Supplementary file 3D).

Human colon organoids

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Patient derived CRC organoids were established using surgically resected and de-identified CRC tissues from the Pitt Biospecimen Core (PBC) at University of Pittsburgh. Human colon organoids were developed and cultured as previously described (Fujii et al., 2015; Leibowitz et al., 2018) and passaged twice a week with a split ratio of 1:3 with minor modifications. In brief, the complete culture medium for human colon organoids contained advanced DMEM/F12 (12634–010; Invitrogen) supplemented with 1x penicillin/streptomycin (15140–122; Invitrogen), 2 mM GlutaMAX (35050–061; Invitrogen), 10 mM HEPES (15630–106; Invitrogen), 1xB27 (17504–044; Invitrogen), 1xN2 (17502–048; Invitrogen), 1 mM N-Acetylcysteine (A0737; Sigma), 10 nM [leu-15]-Gastrin (G9145; Sigma), 10 mM nicotinamide (N0636; Sigma), 10 μM SB202190 (S7067; Sigma), 0.5 μM A83-01(TGFβ inhibitor) (2939; Tocris Bioscience), 20% (vol/vol) FBS (S11150; ATLANTA Biologicals) and WRN-conditioned medium (50%, vol/vol) derived from L-WRN cells (ATCC CRL-3276). Freshly developed organoids were cultured with the complete medium plus 10 μM Y-27632 (Y0503 Sigma) and 100 μg/ml Primocin (ant-pm-1, InvivoGen) before the first passage. Key reagents are listed in (Supplementary file 3F).

Organoids were feed every 2–3 days with fresh complete medium and passaged approximately 1:3 every week (7–10 days). To passage, organoids in the Matrigel were mechanically disrupted with the growth media by pipetting up and down 10 times. The entire mixture including the pooling of 3–10 wells was transferred to a 15 ml conical tube and centrifuged at 400 x g for 5 min at room temperature. After removal of the top layer of media and second thin layer of Matrigel, organoids at the bottom were digested with 1 ml TryPLE at 37°C for 5 min and centrifuged as above. The pellet was then resuspended in Matrigel 50 µl/well (on ice) and seeding to a new 24-well plate prewarmed to 37°C in the incubator. The plate was put into the incubator for 10 min to solidify the Matrigel followed by addition of 500 µl/well of complete medium. To freeze down, organoids were harvested as above, and resuspended in growth media containing 10% DMSO and 10% FBS, at one well into 1 ml/vial. The vials were stored in liquid nitrogen.

To treat, freshly passaged organoids were seeded into 24-well plates at appropriate density and cultured for 2 days to around 30–50% confluency. The medium was replaced with 500 µl/well of growth medium with or without 10 μM eFT508 (S8275; Selleckchem). After treatment, organoids in triplicate wells of each group were observed and photographed till 48 hr. In addition, organoids from 8 wells of each group were pooled and harvested into100-150 µl protein lysis buffer for western blotting.

Transcriptomics and bioinformatics

Microarray analysis

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Total RNA was isolated from 2 million cells cultured in T75 flasks with or without treatment for 24 hr. Replica cell pellets were frozen in liquid nitrogen and used later for RNA isolation and RT-PCR analysis for candidate genes. Microarray analysis was performed using Affymetrix Human Genome U133 Plus 2.0 array by Core Facility at the University of Pittsburgh School of Medicine as described (Wang et al., 2009).

Pathway analysis

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Differentially expressed genes were identified with fold change (Vogelstein et al., 2013; Dang, 2016) in various conditions and p-value (equal or less than 0.05). Shared or intersected differentially expressed genes among groups were depicted by Venn Diagram R package (Chen and Boutros, 2011). Scatter plot was applied to visualize differentials in selected cell lines or treatment conditions. Log2 of the expression fold change was used as input for the plot.

Reactome pathway analysis (https://reactome.org/) was applied to discover biological functions of the gene set of interest (Croft et al., 2014). The input is the genes of interest and the output is the enriched pathways with the significant p-values (≤0.05). The display was limited to top five non overlapping pathways with the most significant p-values.

ClueGO plugin in Cytoscape (http://apps.cytoscape.org/apps/cluego) was additionally used to visualize Reactome Pathway analysis results, and the significance of the terms and groups is automatically calculated with kappa statistics (Bindea et al., 2009).

TCGA data mining eIF4E and 4E-BP1 of mRNA and protein expression were analyzed at cBioprotal (https://www.cbioportal.org/) using the TCGA provisional cohort (n = 640).

Expression of ISR targets was analyzed at Gene expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/). Two cohorts were used, colon adenocarcinoma (COAD, T, n = 275) and rectum adenocarcinoma (READ, T, n = 92) with matched TCGA normal and GTEx data (N, n = 349).

Data deposit

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Gene expression data were generated via cDNA microarray using Affymetrix Human Genome U133 Plus 2.0 array. Microarray data have been deposited at DRYAD (https://orcid.org/0000-0002-4021-1000) and will be released to the public upon publication of manuscript.

Statistical analysis

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Statistical analyses were carried out using GraphPad Prism software (VIII, GraphPad Software, Inc, La Jolla, CA). Multiple comparisons were analyzed by one-way analysis of variance (ANOVA) followed by Tukey’s post-hoc test, whereas those between two groups were made by two-tailed, unpaired t test. Differences were considered significant if the probability of the difference occurring by chance was less than 5 in 100 (p<0.05). The means ± one standard deviation (s.d.) were displayed in the figures. Sample size was determined using a combination of published work and power calculations. For ANOVA, we have computed the power for a test of interaction in a two-way factorial design applied by constructing mixed linear growth models to calculate the needed sample size. We estimated that usually 5 to 10 per group will provide 80% power to detect a standardized interaction of 1.5 SDs, and fewer mice with bigger difference (Leibowitz et al., 2018).

Data availability

Microarray data is deposited in Dryad under https://doi.org/10.5061/dryad.tb2rbnzxm. All data generated or analyzed during this study are included in the manuscript and supporting files.

The following data sets were generated

References

  11. Conference
    1. Dang CV
    (2016)
    A time for MYC: metabolism and therapy
    Cold Spring Harbor Symposia on Quantitative Biology. pp. 79–83.

Decision letter

  1. Maureen E Murphy
    Senior Editor; The Wistar Institute, United States
  2. Wafik S El-Deiry
    Reviewing Editor; Brown University, United States
  3. Zhenghe J Wang
    Reviewer

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

This study uncovers a novel mechanism by which Myc is up-regulated in colorectal cancers to drive glutamine addiction of these tumors. The data are novel, compelling and clinically-relevant.

Decision letter after peer review:

Thank you for submitting your article "eIF4E S209 phosphorylation licenses Myc-and stress-driven oncogenesis" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Maureen Murphy as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Zhenghe J Wang (Reviewer #2).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

Summary:

Overall two of three reviewers found the study to be outstanding with high quality data and convincing conclusions. These two reviewers recommended essentially minor revisions that involve some clarifications and additional discussion material to elaborate further on the study's limitations and future directions. The second reviewer found a number of additional points that require clarification and discussion. Please consider all of the reviewers' comments in revising your manuscript and in your point-by-point response. If you have any further data that address points raised, please include them. If you need extra time to repeat any experiments as suggested please do so to improve the quality of the manuscript.

Reviewer #1:

eIF4E regulates translation initiation and S209 is often phosphorylated in cancers with deregulated RAS-MAPK or PI3k-mTOR signaling. The authors generated eIF4ES209A knock-in (4EKI) in HCT116 (heterozygous knock-in) and mice (heterozygous knock-in, and 4EKI/KI). They report with 4EKI (S209A/+) in HCT116 reduced Myc and ATF4 translation, inhibition of ISR-dependent glutamine signature, Akt activation and tumor growth. In the min mouse background, 4EKI/KI inhibited polyposis, Myc and Akt activation. They further uncover an interaction between p-eIF4E, Myc and KRAS leading to glutamine addiction that may be a therapeutic vulnerability upon deprivation. The paper unravels important signaling mechanisms involving protein translation reprogramming that are relevant to cellular transformation and which may be exploited therapeutically in cancer.

Overall the paper is well-written and adds important information for a poorly understood cancer progression mechanism involving Myc, Ras, ATF4, p-4E, glutamine, and regulation of protein translation. The data is solid including multiple in vivo models.

The model of S209A results in blockade of phosphorylation of eIF4E. A phosphomimic mutant (S209D or S209E) would have been of interest even just in HCT116 with overexpression and could have provided additional important support for the author's findings.

Please elaborate more in the Discussion on the potential significance of MMP7. The authors could also explain better the underlying mechanism of ISR-dependent glutamine addiction and molecular basis for therapeutic vulnerability. This includes more discussion of how KRAS cooperates with Myc to feed into the glutamine addiction. It should be more clear in the paper that the underlying mechanism for the cooperativity has not been dissected, and neither have the reasons for heterogeneity among KRAS mutant colorectal cancer cell lines. As a start, how does KRAS knockdown or ablation impact on the results in Figure 6 in the different cell lines, including the impact on glutamine deprivation-mediated cell death phenotype.

Abstract: should say glutamine addiction (not glutamine addition)?

Figure 7F should be more clear regarding outcomes of tumor growth, cell death or survival, etc

Reviewer #2:

Xuan et al. report here that eIF4E S209 phosphorylation drives high levels of Myc and ATF4 translation, thereby rendering CRC cells dependent on glutamine and promoting tumor growth. Moreover, they further showed that mutant KRAS makes CRC dependent on glutamine through this mechanism. This study uncovers a novel mechanism by which Myc is up-regulated in CRCs to drive glutamine addiction of CRCs. The study is very comprehensive and convincing. Data presented are of high quality. However, the following concerns need to be addressed:

1) They generated two eIF4E S209 mutant knockin clones. In Figure 3, they only performed xenograft study of one knockin clone. To enhance the scientific rigor, they should grow the other knockin clone to show that it also forms small tumors.

2) Figure 6 shows that mutant KRAS cells express high levels of pS209 eIF4E. However, it is not clear what is the molecular mechanism by which mutant KRAS up-regulates pS209 eIF4E.

3) Throughout the manuscript, eIF4E S209 is spelled as eIF4ES209, which may cause confusion to readers outside of the field.

4) In the sentence "Expression of Gln metabolic and translational targets (60-90%) was markedly reduced in 4EKI tumors (Figure 3J)," I believe that they should refer Figure 3K.

5) They state in the sentence "Cell death (TUNEL), p-S6, or expression in ATF4, CHOP, Myc, 4E or apoptotic targets was not significantly different between WT and 4EKI tumors (Figure 3K and Figure 3—figure supplement 1H-I)." However, Figure 3K shows that mRNA levels of ATF4, CHOP and c-MYC are significantly reduced in the knockin clone.

6) The transition to mutant KRAS studies is a bit abrupt. The authors should come up with a better transition.

7) Statistical analyses are missing for some of the quantitative data, e.g., Figure 5 C, G, H and I, and Figure 6C.

8) I assume Figure 5E shown polysome transcripts in WT and KI cells 4 hour and 24 hour after glutamine deprivation and normalized to WT with Gln. If so, please clarify in the figure legend.

9) To be clear, Figure 5F should be labeled as total RNA instead of T-RNA.

10) The schematics shown in Figure 7F does not clearly express the point that glutamine deprivation down-regulates c-MYC. The authors should modify it to make the point come across clearly. They should integrate mutant KRAS into the diagram as well.

Reviewer #3:

The manuscript by Ruan and colleagues addresses the yet unresolved important question of the role of eIF4E S209 phosphorylation in colorectal tumorigenesis. Using non-phosphorylatable mutant (eIF4E S209A) knockin CRC cells and mouse models, they uncover a mechanism of p-eIF4E inducing ISR-dependent MYC and ATF4 translation leading to changes in glutamine metabolism and oncogenic proliferation. They suggest an oncogenic function of p-eIF4E S209 in CRC initiation and progression. Although the manuscript provides new data and insight on the importance of eIF4E phosphorylation for CRC tumorigenesis, which is of relevance as potential therapeutic target, there are substantial discrepancies between the data and the proposed links to stress signaling, cell death and immune evasion. Furthermore, parts of the data linking metabolic stress by glutamine deprivation to p-4E and cell death are opposing to already published mechanisms, and this is not discussed.

1) Subsection “eIF4E S209 regulates colon cancer cell growth and Myc translation”, Figure 1A. Only later it is shown that AKT activity is reduced, so signaling proteins upstream of 4EBP1 should be analysed also here in both clones for their phosphorylation status. Furthermore, 4EBP T37/46 phosphorylation is known as priming event for S65/70 phosphorylation meaning it would be counterintuitive that the latter is not affected.

2) Although introducing 4E S209 mutation is an elegant system to explore its role in tumorigenesis, neither homozygous 4EKI HCT116 clones could be obtained nor heterozygous RKO or HT29 4EKI clones, as explained by the authors. Expansion of data to more cell lines would have been important, of course, especially as RKO and HT29 are also used in later experiments. Likewise, as 4E is only heterozygously mutated, observed affects are hard to control. The authors could use a more physiological system as intestinal organoids to extend and support their findings. Furthermore, the kinases MNK1 and MNK2 are the only characterized kinases that phosphorylate 4E S209. As there are efficient MNK1/2 inhibitors available, which can also be used in vivo, the authors could use those to validate their most important findings.

3) To analyse changes in global translation efficiency in 4EKI cells the authors used polysome profiling (Figure 2A) and luciferase reporter assays (Figure 2B,C, Figure 2—figure supplement 1). It looks like that the whole polysome profile of 4EKI cells is shifted down in comparison to the profile of wt cells making interpretation difficult. In addition, using exogenously expressed luciferase reporters is a very artificial system to study endogenous protein synthesis. It is recommended to analyse global protein synthesis via S35-Methionine incorporation or Puromycin labelling, especially as observed translation changes are very subtle. Furthermore, if bicistronic reporter vectors are used to distinguish between cap- and IRES-dependent translation, a hairpin structure should be introduced in front of the IRES sequence. This can inhibit potential read-through of ribosomes, which can affect interpretation of results.

4) Figure 2E-H. The authors show reduced translation of MYC/MMP7 in 4EKI cells. Although polysomal mRNA is indeed more reduced than total RNA (at least shown for clone 1), also transcription is affected. Ribosomal profiling experiments would help to clearly distinguish between transcriptional and translational effects and to analyse whether a global oncogenic translational program is regulated by 4E S209 phosphorylation.

5) Subsection “eIF4E S209 promotes colon cancer growth in vivo through Myc and the ISR”, Figure 3D. The authors performed siRNA-mediated knockdown of MYC/ATF4/CHOP and show downregulation of Gln genes. It is not obvious, what is the claim behind that experiment. That knockdown of those proteins has similar effects as observed in 4EKI cells that show decreased expression of Gln genes and, therefore, these effects are MYC-/stress-dependent? This link is not directly shown by this experimental setting. Instead, the effects in 4EKI vs. wt cells should be analyzed upon MYC/ATF4 overexpression (as performed in Figure 5H and Figure 5—figure supplement 1B) and whether downregulation of Gln genes can be rescued by this.

6) Figure 3G. The immunofluorescence staining is not convincing, especially p-GCN2/p-eIF2 stainings that only show some single spots rather than broad cytoplasmic staining. A positive control should be used to validate a specific signal (e.g. tunicamycin treatment for p-eIF2a). Also, stainings of total GCN2/eIF2a/AKT levels should be performed. Please provide H&E stainings.

7) The authors state "Cell death (TUNEL), p-S6, or expression in ATF4, CHOP, Myc, 4E or apoptotic targets was not significantly different between WT and 4EKI tumors (Figure 3K and Figure 3—figure supplement 1H-I). The expression of ISR Gln metabolic and apoptotic targets (ASCT2, SLC7A5, PUMA, TRIB, and NOXA) is also elevated in TCGA CRC cohorts".

This description is not correct, as transcript levels of ATF4/CHOP/MYC (Figure 3K) and also some apoptotic genes (DR5, NOXA Figure 3—figure supplement 1I) are obviously significantly downregulated in 4EKI vs. wt tumors. The description and relevance of apoptosis between wt and 4EKI samples is not clear/confusing, especially as highly significant downregulation of apoptotic genes in 4EKI vs. wt cells is not described at all (Figure3—figure supplement 1F).

Please adjust description and explain in more detail.

8) The authors conclude "These data support that p-4E promotes Myc- and ATF4-driven CRC growth through chronic exploitation of the most ancient arm of ISR (GCN2) to maintain constitutive AKT/4E-BP1 signaling."

The conclusion that p-4E promotes the ISR and AKT/4EBP signaling via p-eIF2a/p-pGCN2 is mainly based on the not convincing tumor stainings (Figure 3G), see also comment 6. How do levels of p-eIF2a/pGCN2/pAKT levels react in 4EKI vs. wt HCT116 cells? Immunoblots should be shown. The authors could induce GCN2 activation (e.g. amino acid starvation, RNA Pol III inhibitor) to test whether active GCN2 rescues the phenotype in 4EKI cells/tumors. Furthermore, the authors argue that this MYC/ATF4/ISR-driven AKT/4EBP signaling fuels enhanced protein synthesis and, subsequently, tumor growth. Although enhanced protein synthesis is an essential factor for MYC-driven tumorigenesis, several recent publications have shown that this needs to be tightly balanced by several mechanisms. It would help for understanding, if the author's findings would be discussed more in the context of those publications.

9) Figure 4A/Figure 4—figure supplement 1A. The authors state “Uniform p-4E staining was detected in the bottom of proliferating (Ki-67+) crypts in normal mice". There is no overlay or co-staining (p-4E and Ki67) from the same section shown, making it impossible to interpret whether p-4E is found in Ki67+ crypts. Additionally, higher magnification of p-4E staining should be shown (as in Figure 4—figure supplement 1A). Please provide H&E stainings.

10) Figure 4D/E. The authors state "Compared to polyps formed in the control mice at similar sizes, ones formed in 4EKI mice showed strongly reduced levels of c-Myc, p-AKT, p-4E-BP1". This raises the question: If tumor formation is driven by elevated p-4E/MYC/pAKT/p-4EBP levels, why do those polyps form despite reduced levels of those proteins? Are those polyps smaller, although it does not look like in Figure 4B? How do p-4E levels in these APCmin 4EKI/KI tumors behave, stainings should be shown. It is recommended to show all stainings for total proteins (4EBP/eIF2a/AKT).

11) The authors state “Both glucose and Gln were required for the growth of HCT116 cells in culture… (Figure 5A-C)." This metabolic link has been published before, specifically in HCT116 wt cells, please cite properly (Dejure et al., 2017). In this previous publication, a mechanism has been well established that Gln starvation induces only moderate apoptosis but rather S phase arrest which is dependent on the MYC 3'UTR. Please comment on this. The authors should include BrdU π cell cycle FACS analysis to evaluate these contradictory results.

12) Please include p values for FACS analyses in complete Figure 5 and Figure 5—figure supplement 1.

13) The authors state “Apoptotic targets (DR5, PUMA and NOXA) showed transient suppression of translation at 4 hours followed by strong increase by 24 hours (Figure 5D, middle)." NOXA is clearly downregulated after 24h, please correct.

14) The authors state “In contrast, 4EKI cells showed reduced basal levels of Myc, ISR and p-AKT, and transient ISR induction… The kinetics or levels of p-4E-BP1 (T37/46), p-ERK, p-mTOR (S2448), p-S6, p-PERK, cyclin D1 were not significantly affected by 4EKI (Figure 5D)". Although I appreciate that p-eIF2a basal levels are lower in 4EKI cells, the other ISR markers (ATF4 and CHOP) seem to be not expressed at all in Figure 5D (middle panel) in both wt and 4EKI, so the claim that ISR basal levels are reduced in 4EKI cells is questionable. Also, it does not fit with Figure 3B where it is shown that ATF4 and CHOP total and polysomal mRNA levels are reduced in 4EKI vs. wt cells. Additionally, quantification of immunoblots, especially right panel, would make it easier to judge changes in kinetics of pmTOR/ERK/S6/AKT. Changes in p-PERK levels upon Gln deprivation are clearly not the same (more stable in wt than in 4EKI), in contrast to what is stated by the authors. Loading control is missing in Figure 5D, middle panel.

15) Subsection “eIF4E S209 promotes Myc- and ISR-dependent glutamine addiction”. Figure 5E-H are displayed in a confusing way and important controls are missing. Figure 5E needs to be shown for total RNA in the same way, otherwise described kinetics in changes of gene expression are not comprehensible (-GLN only shown for 24h for total RNA in F). MYC is not shown at all in total RNA, although it is stated that "Myc loss and ATF4 induction was rapid and primarily in polysomal fractions". What is lane labelled with "GLN+" in Figure 5F, wt cells? If yes, 4EKI cells GLN+ also have to be shown as comparison as zero time points. This discrepancy would be avoided if same heatmap of total RNA is shown.

siRNA experiments and MYC/ATF4 overexpression experiments in Figure 5F/G/H and Figure 5—figure supplement 1A/B should be shown in both wt and 4EKI cells side-by-side. In Figure 5G, the authors claim that siCHOP/ASCT2/ASNS reduces apoptosis to a lesser extent upon GLN deprivation. Nevertheless, the fold induction of apoptosis (GLN+ vs. GLN-) seems to be similar to siCTR cells. Same is true for Figure 5H where fold induction of apoptosis looks similar between CTR and MYC overexpressing cells. ATF4 immunoblot is missing in Figure 5—figure supplement 1B.

16) Subsection “Mutant KRAS cooperates with p-4E/Myc to promote glutamine addiction and immune suppression”, Figure 6A. Total eIF4E levels are also elevated in Lim1215 cells with KRAS mutations, arguing against increased p-4E levels in this cell line. Quantification of immunoblot could help clarifying this.

17) Subsection “Mutant KRAS cooperates with p-4E/Myc to promote glutamine addiction and immune suppression”, Figure 6C,D. The apoptotic response in HCT116 wt cells is much lower than in previous assays in HCT116 (26% in Figure 6B vs. over 50% in Figure 5) and no apoptosis induction at all in Lim1215 wt cells upon GLN deprivation (also no or only weak induction of ISR, and no cl. Casp 3, Figure 6D). This raises the question to which extent this phenotype/mechanism can be generalized to CRC or whether the mutational landscape of different CRC cells affect the response. The number of analysed cell lines could be extended or a more physiological, genetically defined system with specific mutations such as intestinal organoids could be used.

18) The authors state “The sensitivity was associated with elevated apoptosis and p-GCN2/ISR response, and reduction in Myc but p-ERK (Figure 6C-E, Figure 6—figure supplement 1A-C)." MYC levels are not shown in any of the given figures. Why should MYC levels be reduced in KRASmut cells upon GLN deprivation if they are more sensitive to deprivation and if this is mediated via MYC induction?

19) The authors state “These data establish that p-4E/Myc cooperates with mutant KRAS to promote glutamine addiction with elevated ISR and immune suppression". Are transcriptome analyses in Figure 6F-J performed in KRASwt cells? This is not completely obvious from the description. If yes, then the claim that cooperation with KRAS promotes immune suppression is not reflected by the data. Global gene expression changes are then only shown for KRASwt cells, same analyses need to be performed in KRASmut cells (-/+GLN, wt/4EKI).

20) Figure 7B. Total eIF4E and 4EBP levels are also elevated in RKO and HT29 cells, arguing against increased p-4E/p-4EBP levels. Quantification of immunoblot would help clarifying this.

21) The authors state “Together, our data support that p-4E controls cell death upon metabolic stress". This conclusion is only partially reflected by the data. I appreciate that HCT116 cells show reduced p-4E levels upon metabolic stress (GLN deprivation) associated with enhanced stress signaling (Figure 5). Instead, neither HT29 nor RKO cells that are sensitive to GLN deprivation with enhanced stress signaling, show changes in p-4E levels (Figure 7B). Therefore, it is questionable whether the proposed mechanism, p-4E regulating the response to metabolic stress, is a general feature of CRC. On the same line, a clear mechanism of the response to GLN deprivation in CRC cells has been described previously, that is associated with reduced nucleotide and MYC levels and, subsequently, slowed elongation of RNA Pol II and cell cycle arrest instead of apoptosis. This is not at all discussed in the manuscript.

22) The depicted model in Figure 7F is not comprehensible.

https://doi.org/10.7554/eLife.60151.sa1

Author response

Reviewer #1:

eIF4E regulates translation initiation and S209 is often phosphorylated in cancers with deregulated RAS-MAPK or PI3k-mTOR signaling. The authors generated eIF4ES209A knock-in (4EKI) in HCT116 (heterozygous knock-in) and mice (heterozygous knock-in, and 4EKI/KI). They report with 4EKI (S209A/+) in HCT116 reduced Myc and ATF4 translation, inhibition of ISR-dependent glutamine signature, Akt activation and tumor growth. In the min mouse background, 4EKI/KI inhibited polyposis, Myc and Akt activation. They further uncover an interaction between p-eIF4E, Myc and KRAS leading to glutamine addiction that may be a therapeutic vulnerability upon deprivation. The paper unravels important signaling mechanisms involving protein translation reprogramming that are relevant to cellular transformation and which may be exploited therapeutically in cancer.

Overall the paper is well-written and adds important information for a poorly understood cancer progression mechanism involving Myc, Ras, ATF4, p-4E, glutamine, and regulation of protein translation. The data is solid including multiple in vivo models.

The model of S209A results in blockade of phosphorylation of eIF4E. A phosphomimic mutant (S209D or S209E) would have been of interest even just in HCT116 with overexpression and could have provided additional important support for the author's findings.

p-4E (and mTOR/AKT) is highly elevated in CRC, we envision that it would be difficult to predict or explain the effects of S209D (E) in CRC. The loss of (hypo) function mutant (hypo phosphorylation) is therefore more informative on dissect its role in Myc and ISR-dependent CRC growth. We discussed the punctate signals and dynamic and local nature of GCN2-eIF2a and 4E-4EBP1 interaction. See Results (subsection “eIF4E S209 promotes colon cancer growth in vivo through Myc and the ISR”) and Discussion.

Please elaborate more in the Discussion on the potential significance of MMP7. The authors could also explain better the underlying mechanism of ISR-dependent glutamine addiction and molecular basis for therapeutic vulnerability. This includes more discussion of how KRAS cooperates with Myc to feed into the glutamine addiction. It should be more clear in the paper that the underlying mechanism for the cooperativity has not been dissected, and neither have the reasons for heterogeneity among KRAS mutant colorectal cancer cell lines. As a start, how does KRAS knockdown or ablation impact on the results in Figure 6 in the different cell lines, including the impact on glutamine deprivation-mediated cell death phenotype.

Our data suggest that MMP7 expression is regulated by transcription and translation in p-4E high cells, much like other ISR effectors. We elaborated the rationale with background on mutant KRAS/BRAF, Mnk1/2 and elevated p-4E, as well p-4E-dependent translation of other oncogenic targets (i.e. PD-L1, SNAIL and MMP-3). Our new data showed that a selective Mnk inhibitor reduces the growth of CRC organoids along with reduced p-4E/p-4E-BP1 and Myc. See new Figure 2I-J, revised Abstract, Introduction, Results and Discussion.

Abstract: should say glutamine addiction (not glutamine addition)?

Corrected.

Figure 7F should be more clear regarding outcomes of tumor growth, cell death or survival, etc

We simplified the model to propose the p-4E drives Myc and Gln-dependent metabolic adaption, which is disrupted by Gln withdraw, leading to Myc reduction and ISR hyperactivation. Nutrient- and p-4E sensitive ISR therefore dynamically regulates CRC outcomes during evolution and therapy. See revised Figure 7F and Discussion.

Reviewer #2:

Xuan et al. report here that eIF4E S209 phosphorylation drives high levels of Myc and ATF4 translation, thereby rendering CRC cells dependent on glutamine and promoting tumor growth. Moreover, they further showed that mutant KRAS makes CRC dependent on glutamine through this mechanism. This study uncovers a novel mechanism by which Myc is up-regulated in CRCs to drive glutamine addiction of CRCs. The study is very comprehensive and convincing. Data presented are of high quality. However, the following concerns need to be addressed:

1) They generated two eIF4E S209 mutant knockin clones. In Figure 3, they only performed xenograft study of one knockin clone. To enhance the scientific rigor, they should grow the other knockin clone to show that it also forms small tumors.

We performed new experiments. KI2 cells showed even more reduced engraftment and growth rate compared to WT cells (on the opposite flank of same mice). See revised Figure 3E and Results section.

2) Figure 6 shows that mutant KRAS cells express high levels of pS209 eIF4E. However, it is not clear what is the molecular mechanism by which mutant KRAS up-regulates pS209 eIF4E.

See reviewer 1 (point 2). We elaborated the rationale on mutant KRAS/BRAF, Mnk1/2 and increased p-4E. Our new data showed that a selective Mnk inhibitor reduces the growth of CRC organoids, p-4E/p-4E-BP1 and Myc. See new Figure 2I-J, Revised model Figure 7F, Abstract, Introduction, Results and Discussion sections.

3) Throughout the manuscript, eIF4E S209 is spelled as eIF4ES209, which may cause confusion to readers outside of the field.

We now use eIF4E S209 throughout the manuscript.

4) In the sentence "Expression of Gln metabolic and translational targets (60-90%) was markedly reduced in 4EKI tumors (Figure 3J)," I believe that they should refer Figure 3K.

Corrected.

5) They state in the sentence "Cell death (TUNEL), p-S6, or expression in ATF4, CHOP, Myc, 4E or apoptotic targets was not significantly different between WT and 4EKI tumors (Figure 3K and Figure 3—figure supplement 1H-I)." However, Figure 3K shows that mRNA levels of ATF4, CHOP and c-MYC are significantly reduced in the knockin clone.

Corrected in the revised Results.

6) The transition to mutant KRAS studies is a bit abrupt. The authors should come up with a better transition.

Please see point 2.

7) Statistical analyses are missing for some of the quantitative data, e.g., Figure 5 C, G, H and I, and Figure 6C.

Flow cytometry was repeated on two or more different occasions (days) with similar results. Plots and quantitation from one representative experiment are shown with fraction (%) of given population per convention. Revised MandM and Legends.

8) I assume Figure 5E shown polysome transcripts in WT and KI cells 4 hour and 24 hour after glutamine deprivation and normalized to WT with Gln. If so, please clarify in the figure legend.

Yes. The value of WT with Gln was set as 1 or control for each maker. Revised Legends.

9) To be clear, Figure 5F should be labeled as total RNA instead of T-RNA.

See above. We used Total-RNA to replace T-RNA in any figure as applicable. Values were normalized to WT cell with Gln (+) as one similarly as 5E. Myc was added to total-RNA panel. See revised Figure 5F and Results section.

10) The schematics shown in Figure 7F does not clearly express the point that glutamine deprivation down-regulates c-MYC. The authors should modify it to make the point come across clearly. They should integrate mutant KRAS into the diagram as well.

Please see reviewer 1 (point 4). Simplified model with drivers (KRAS), p-4E/p-4E-BP1, Myc/ISR and outcomes. See revised Figure 7F.

Reviewer #3:

The manuscript by Ruan and colleagues addresses the yet unresolved important question of the role of eIF4E S209 phosphorylation in colorectal tumorigenesis. Using non-phosphorylatable mutant (eIF4E S209A) knockin CRC cells and mouse models, they uncover a mechanism of p-eIF4E inducing ISR-dependent MYC and ATF4 translation leading to changes in glutamine metabolism and oncogenic proliferation. They suggest an oncogenic function of p-eIF4E S209 in CRC initiation and progression. Although the manuscript provides new data and insight on the importance of eIF4E phosphorylation for CRC tumorigenesis, which is of relevance as potential therapeutic target, there are substantial discrepancies between the data and the proposed links to stress signaling, cell death and immune evasion. Furthermore, parts of the data linking metabolic stress by glutamine deprivation to p-4E and cell death are opposing to already published mechanisms, and this is not discussed.

Thank you for commenting on the significance of our work. Our data supports a critical role of p-4E in coordinating Myc and mutant KRAS in control CRC growth, death and transcriptional heterogeneity depending on the nutrient availability (i.e. Gln). These oncogenic properties as well as “Stress” are strongly reduced in 4EKI (KI/+) CRC cells containing a complex mix of driver mutations such KRAS, b-Catenin, PIK3CA, TGFBR2.

Importantly, ISR-dependent transcriptional heterogeneity and outcomes (arrest vs cell death) is consistent with our model through Gln and Myc-dependent recovery vs. crisis. Revised Figure 7F, Results and Discussion as detailed below.

1) Subsection “eIF4E S209 regulates colon cancer cell growth and Myc translation”, Figure 1A. Only later it is shown that AKT activity is reduced, so signaling proteins upstream of 4EBP1 should be analysed also here in both clones for their phosphorylation status. Furthermore, 4EBP T37/46 phosphorylation is known as priming event for S65/70 phosphorylation meaning it would be counterintuitive that the latter is not affected.

Added p-AKT, p-mTOR and p-ERK. See revised Figure 1A and Results section.

2) Although introducing 4E S209 mutation is an elegant system to explore its role in tumorigenesis, neither homozygous 4EKI HCT116 clones could be obtained nor heterozygous RKO or HT29 4EKI clones, as explained by the authors. Expansion of data to more cell lines would have been important, of course, especially as RKO and HT29 are also used in later experiments. Likewise, as 4E is only heterozygously mutated, observed affects are hard to control. The authors could use a more physiological system as intestinal organoids to extend and support their findings. Furthermore, the kinases MNK1 and MNK2 are the only characterized kinases that phosphorylate 4E S209. As there are efficient MNK1/2 inhibitors available, which can also be used in vivo, the authors could use those to validate their most important findings.

See reviewer 1 (point 2). We elaborated on mutant KRAS/BRAF, Mnk, and added new data on Mnki in CRC organoids. See new Figure 2I-J, revised Introduction and Results section.

3) To analyse changes in global translation efficiency in 4EKI cells the authors used polysome profiling (Figure 2A) and luciferase reporter assays (Figure 2B,C, Figure 2—figure supplement 1). It looks like that the whole polysome profile of 4EKI cells is shifted down in comparison to the profile of wt cells making interpretation difficult. In addition, using exogenously expressed luciferase reporters is a very artificial system to study endogenous protein synthesis. It is recommended to analyse global protein synthesis via S35-Methionine incorporation or Puromycin labelling, especially as observed translation changes are very subtle. Furthermore, if bicistronic reporter vectors are used to distinguish between cap- and IRES-dependent translation, a hairpin structure should be introduced in front of the IRES sequence. This can inhibit potential read-through of ribosomes, which can affect interpretation of results.

This is a valid point worth studying. However, we chose to focus on oncogenic targets such as Myc, MMP7, and ISR-dependent regulation of Gln metabolism, and validation in multiple CRC cell line and mouse models. See below 4 as well. See revised model Figure 7F and Discussion section.

4) Figure 2E-H. The authors show reduced translation of MYC/MMP7 in 4EKI cells. Although polysomal mRNA is indeed more reduced than total RNA (at least shown for clone 1), also transcription is affected. Ribosomal profiling experiments would help to clearly distinguish between transcriptional and translational effects and to analyse whether a global oncogenic translational program is regulated by 4E S209 phosphorylation.

We focused on Myc and ISR targets in the context of Gln-dependent growth in CRC. The implication of heterogeneity, the use of systematic approach and appropriate models have been discussed. See revised Discussion section.

5) Subsection “eIF4E S209 promotes colon cancer growth in vivo through Myc and the ISR”, Figure 3D. The authors performed siRNA-mediated knockdown of MYC/ATF4/CHOP and show downregulation of Gln genes. It is not obvious, what is the claim behind that experiment. That knockdown of those proteins has similar effects as observed in 4EKI cells that show decreased expression of Gln genes and, therefore, these effects are MYC-/stress-dependent? This link is not directly shown by this experimental setting. Instead, the effects in 4EKI vs. wt cells should be analyzed upon MYC/ATF4 overexpression (as performed in Figure 5H and Figure 5—figure supplement 1B) and whether downregulation of Gln genes can be rescued by this.

We agree and clarified this point. p-4E/Myc/ISR(p-eIF2a/ATF4) are upstream events driving glutamine-biased metabolism and addiction. siRNA of downstream effectors (CHOP, ASNS or ASCT2) has more modest effects Gln addiction. This is consistent with prior studies on ISR level-dependent outcomes, including cell death in MEFs with uncontrolled translational load (1), or survival in HCT 116 cells with Myc recovery (2). See revised Figure 7F and Discussion section.

6) Figure 3G. The immunofluorescence staining is not convincing, especially p-GCN2/p-eIF2 stainings that only show some single spots rather than broad cytoplasmic staining. A positive control should be used to validate a specific signal (e.g. tunicamycin treatment for p-eIF2a). Also, stainings of total GCN2/eIF2a/AKT levels should be performed. Please provide H&E stainings.

We included higher magnification images p-GCN2 and p-eIF2a while keeping the originals with other markers at the same magnification. The punctate p-GCN2 and/or p-eIF2a staining was observed in the polyps of APCMin mice (Figure 4A). These findings are consistent with moderate increase in ISR and transient and localized GCN2-eIF2a regulation during cell growth (3). In contrast, acute metabolic stress (i.e., mTORi) or ER stressors induce high levels of p-eIF2a (ISR) and cell death in HCT 116 xenografts as we have shown (4). Total GCN2/eIF2a/AKT levels were not affected by acute metabolic stress in various CRC lines examined. See revised Figure 3—figure supplement 1H, Results and Discussion sections.

7) The authors state "Cell death (TUNEL), p-S6, or expression in ATF4, CHOP, Myc, 4E or apoptotic targets was not significantly different between WT and 4EKI tumors (Figure 3K and Figure 3—figure supplement 1H-I). The expression of ISR Gln metabolic and apoptotic targets (ASCT2, SLC7A5, PUMA, TRIB, and NOXA) is also elevated in TCGA CRC cohorts".

This description is not correct, as transcript levels of ATF4/CHOP/MYC (Figure 3K) and also some apoptotic genes (DR5, NOXA Figure 3—figure supplement 1I) are obviously significantly downregulated in 4EKI vs. wt tumors. The description and relevance of apoptosis between wt and 4EKI samples is not clear/confusing, especially as highly significant downregulation of apoptotic genes in 4EKI vs. wt cells is not described at all (Figure 3—figure supplement 1F).

Please adjust description and explain in more detail.

Sorry for the oversight. More details are added. The expression of metabolic and translational targets is reduced more significantly compared to apoptotic targets in 4EKI xenografts. The proliferation, p-GCN2/p-eIF2a, and p-AKT but not apoptosis, are reduced in 4EKI xenografts, supporting Gln-dependent metabolic adaptation and growth. See revised Results section.

8) The authors conclude "These data support that p-4E promotes Myc- and ATF4-driven CRC growth through chronic exploitation of the most ancient arm of ISR (GCN2) to maintain constitutive AKT/4E-BP1 signaling."

The conclusion that p-4E promotes the ISR and AKT/4EBP signaling via p-eIF2a/p-pGCN2 is mainly based on the not convincing tumor stainings (Figure 3G), see also comment 6. How do levels of p-eIF2a/pGCN2/pAKT levels react in 4EKI vs. wt HCT116 cells? Immunoblots should be shown. The authors could induce GCN2 activation (e.g. amino acid starvation, RNA Pol III inhibitor) to test whether active GCN2 rescues the phenotype in 4EKI cells/tumors. Furthermore, the authors argue that this MYC/ATF4/ISR-driven AKT/4EBP signaling fuels enhanced protein synthesis and, subsequently, tumor growth. Although enhanced protein synthesis is an essential factor for MYC-driven tumorigenesis, several recent publications have shown that this needs to be tightly balanced by several mechanisms. It would help for understanding, if the author's findings would be discussed more in the context of those publications.

See point 6 on punctate staining of p-eIF2a/p-GCN2, which is further supported by data from Apcmin mice and human adenomas (Figure 4 and Figure 4—figure supplement 1). p-4E-depedent increase in Myc/p-eIF2a/p-AKT is clearly not required for the rapid proliferation of “Normal” crypts but polyposis driven by oncogenic proliferation.

Gln-dependent adaptation in mutant KRAS, p-4E/Myc high tumors is the very cause of their Gln addiction and transcriptional heterogeneity (Figures 5-7). The findings are consistent with the degree and extent of ISR in relation to transcriptional heterogeneity and outcomes. See revised Figure 7F and Discussion section.

9) Figure 4A/Figure 4—figure supplement 1A. The authors state “Uniform p-4E staining was detected in the bottom of proliferating (Ki-67+) crypts in normal mice". There is no overlay or co-staining (p-4E and Ki67) from the same section shown, making it impossible to interpret whether p-4E is found in Ki67+ crypts. Additionally, higher magnification of p-4E staining should be shown (as in Figure 4—figure supplement 1A). Please provide H&E stainings.

It is well established (including by us) that intestinal proliferation is confined in the progenitors and the lower half of the (ALL/every) crypt. We added roomed in Ki-67 and p-4E IF in different crypts, and H&E stained polyps from both WT and 4EKI APCMin mice. See revised Figure 4—figure supplement 1C-D and Results section.

10) Figure 4D/E. The authors state "Compared to polyps formed in the control mice at similar sizes, ones formed in 4EKI mice showed strongly reduced levels of c-Myc, p-AKT, p-4E-BP1". This raises the question: If tumor formation is driven by elevated p-4E/MYC/pAKT/p-4EBP levels, why do those polyps form despite reduced levels of those proteins? Are those polyps smaller, although it does not look like in Figure 4B? How do p-4E levels in these APCmin 4EKI/KI tumors behave, stainings should be shown. It is recommended to show all stainings for total proteins (4EBP/eIF2a/AKT).

4EKI reduced the incidence of polyps by over 60%, and lost ones can be studied. We selected polyps at similar sizes (large) to control for growth or metabolic pressure. The residual 4EKI tumors are negative for p-4E with reduced Myc (still elevated compared to normal crypts). A potential role of p-4E in non-epithelial compartments or p-4E-independent mechanisms cannot be ruled out. See revised Results section.

11) The authors state “Both glucose and Gln were required for the growth of HCT116 cells in culture… (Figure 5A-C)." This metabolic link has been published before, specifically in HCT116 wt cells, please cite properly (Dejure et al., 2017). In this previous publication, a mechanism has been well established that Gln starvation induces only moderate apoptosis but rather S phase arrest which is dependent on the MYC 3'UTR. Please comment on this. The authors should include BrdU π cell cycle FACS analysis to evaluate these contradictory results.

See point 5. Our data showed dose-dependent induction of cell death with growth inhibition upon Gln starvation in HCT 116 (Figure 5—figure supplement 1C-D), supporting ISR-dependent outcomes. See revised Figure 7F and Discussion section.

12) Please include p values for FACS analyses in complete Figure 5 and Figure 5—figure supplement 1.

Please see reviewer #2 (point 7). See Materials and methods section and figure legends.

13) The authors state “Apoptotic targets (DR5, PUMA and NOXA) showed transient suppression of translation at 4 hours followed by strong increase by 24 hours (Figure 5D, middle)." NOXA is clearly downregulated after 24h, please correct.

Sorry for the oversight. Corrected. See Results section.

14) The authors state “In contrast, 4EKI cells showed reduced basal levels of Myc, ISR and p-AKT, and transient ISR induction… The kinetics or levels of p-4E-BP1 (T37/46), p-ERK, p-mTOR (S2448), p-S6, p-PERK, cyclin D1 were not significantly affected by 4EKI (Figure 5D)". Although I appreciate that p-eIF2a basal levels are lower in 4EKI cells, the other ISR markers (ATF4 and CHOP) seem to be not expressed at all in Figure 5D (middle panel) in both wt and 4EKI, so the claim that ISR basal levels are reduced in 4EKI cells is questionable. Also, it does not fit with Figure 3B where it is shown that ATF4 and CHOP total and polysomal mRNA levels are reduced in 4EKI vs. wt cells. Additionally, quantification of immunoblots, especially right panel, would make it easier to judge changes in kinetics of pmTOR/ERK/S6/AKT. Changes in p-PERK levels upon Gln deprivation are clearly not the same (more stable in wt than in 4EKI), in contrast to what is stated by the authors. Loading control is missing in Figure 5D, middle panel.

The same set of samples are used for the entire sets with action done on two separate blots (after stripping) for Figure 5D. Additional controls include total eIF2a, GCN2 and cyclin D, which did not change in response to Gln- in either WT or KI cells (or other CRCs).

p-eIF2a/ATF4/CHOP as well as ISR targets assessed by RT-PCR and/or micro array support that the basal ISR is lower in 4E KI HCT 116 cells and xenografts (with Gln) and some are punctate. Basal p-ERK, p-S6 and p-mTOR were similar in WT and 4EKI cells. See revised Figure 1A and Results section.

15) Subsection “eIF4E S209 promotes Myc- and ISR-dependent glutamine addiction”. Figure 5E-H are displayed in a confusing way and important controls are missing. Figure 5E needs to be shown for total RNA in the same way, otherwise described kinetics in changes of gene expression are not comprehensible (-GLN only shown for 24h for total RNA in F). MYC is not shown at all in total RNA, although it is stated that "Myc loss and ATF4 induction was rapid and primarily in polysomal fractions". What is lane labelled with "GLN+" in Figure 5F, wt cells? If yes, 4EKI cells GLN+ also have to be shown as comparison as zero time points. This discrepancy would be avoided if same heatmap of total RNA is shown.

siRNA experiments and MYC/ATF4 overexpression experiments in Figure 5F/G/H and Figure 5—figure supplement 1A/B should be shown in both wt and 4EKI cells side-by-side. In Figure 5G, the authors claim that siCHOP/ASCT2/ASNS reduces apoptosis to a lesser extent upon GLN deprivation. Nevertheless, the fold induction of apoptosis (GLN+ vs. GLN-) seems to be similar to siCTR cells. Same is true for Figure 5H where fold induction of apoptosis looks similar between CTR and MYC overexpressing cells. ATF4 immunoblot is missing in Figure 5—figure supplement 1B.

Figures 5E-I and Figure 5—figure supplement 1 examined the role of Myc/ATF4/CHOP in basal and induction of ISR upon Gln- using loss of function and gain of function in WT and 4E KI cells, respectively. These experiments support that the (inducible) expression of ISR targets and death upon persistent ISR, expression of apoptotic targets and failed recovery. Upstream regulators such as Myc (loss), ATF4 and CHOP are (more rapidly) controlled by translation (within 4 hours) (Figure 3A-D, Figure 5D).

5E-F,we clarified in legends on qRT-PCR normalization. Each marker is normalized to parental HCT 116 cells with Gln (1, black) in either sets (reviewer 2/point 8). Revised Figure 5F.

5H. Overexpression of Myc induces apoptosis in p53 WT cells (5), and caused a further increase with Gln- in 4EKI cells. Myc siRNA reduced cell death with Gln+ and Gln- in WT cells (Figure 5G). ATF4 overexpression did not increase cell death with Gln while strongly increased cell death upon Gln-. We’d like to argue that absolute levels of ISR effectors are important for cell fate. For example, expression from 0.2 to 1 vs 2-10 (same 5-fold) is likely to cause a different outcome. By analogy, cell death increased from 5-15% vs. 15-45% (3-fold) is not the same on tumor outcome or p-eIF2a levels. p-4E controls the ISR range.

16) Subsection “Mutant KRAS cooperates with p-4E/Myc to promote glutamine addiction and immune suppression”, Figure 6A. Total eIF4E levels are also elevated in Lim1215 cells with KRAS mutations, arguing against increased p-4E levels in this cell line. Quantification of immunoblot could help clarifying this.

Upon Gln- (by 24 hours), total GCN2, eIF4E or eIF2a did not change in any cell line examined. Myc reduction and ISR induction is more selective in mutant KRAS mutant cells (with higher basal levels). This is consistent with our model mutant KRAS cooperates with Myc via p-4E to promote Gln-dependent adaptation and addiction. See revised Figure 6D, Figure 6—figure supplement 1C, Figure 7F, and Results section.

17) Subsection “Mutant KRAS cooperates with p-4E/Myc to promote glutamine addiction and immune suppression”, Figure 6C,D. The apoptotic response in HCT116 wt cells is much lower than in previous assays in HCT116 (26% in Figure 6B vs. over 50% in Figure 5) and no apoptosis induction at all in Lim1215 wt cells upon GLN deprivation (also no or only weak induction of ISR, and no cl. Casp 3, Figure 6D). This raises the question to which extent this phenotype/mechanism can be generalized to CRC or whether the mutational landscape of different CRC cells affect the response. The number of analysed cell lines could be extended or a more physiological, genetically defined system with specific mutations such as intestinal organoids could be used.

Figure 5C. 4E WT vs. 4E KI HCT 116 cells (mutant KRAS). Figure 6C, WT and mutant refer to KRAS (not 4E S209), the death was 50-60% in G13D cells. Therefore, apoptosis was reduced in 4EKI or WT KRAS HCT 116 cells similarly.

Between Figures 6 and 7, we have used over 10 different CRC lines, supporting Gln addiction is correlated with higher basal p-4E/p-4EBP1, Myc, ISR and transcriptional heterogeneity. Pharmacological Mnki reduced the growth of CRC organoids, p-4E and Myc levels. Gln is not used in organoid culture, and Myc-driven metabolic/Gln addiction can be compensated by alternative fuels. See new Figure 2I-J, revised Results and Discussion section.

18) The authors state “The sensitivity was associated with elevated apoptosis and p-GCN2/ISR response, and reduction in Myc but p-ERK (Figure 6C-E, Figure 6—figure supplement 1A-C)." MYC levels are not shown in any of the given figures. Why should MYC levels be reduced in KRASmut cells upon GLN deprivation if they are more sensitive to deprivation and if this is mediated via MYC induction?

Gln- induced more cell death and Myc reduction in HCT 116 cells (vs 4EKI or WT KRAS), Lim 1215 (mutant KRAS vs WT), and RKO, HT29 (vs. DLD1 and SW480). As depicted in revised model (Figure 7F), higher basal Myc and p-4E/p-4EBP1 leads to oncogenic addiction, i.e. the dependence on Myc and Gln for adaptation and growth. Their loss (acute) leads to increased stress (ISR) and cell death.

19) The authors state “These data establish that p-4E/Myc cooperates with mutant KRAS to promote glutamine addiction with elevated ISR and immune suppression". Are transcriptome analyses in Figure 6F-J performed in KRASwt cells? This is not completely obvious from the description. If yes, then the claim that cooperation with KRAS promotes immune suppression is not reflected by the data. Global gene expression changes are then only shown for KRASwt cells, same analyses need to be performed in KRASmut cells (-/+GLN, wt/4EKI).

Our focus is to understand the role of p-4E in shaping the response of mutant KRAS to metabolic stress. See revised Results section.

20) Figure 7B. Total eIF4E and 4EBP levels are also elevated in RKO and HT29 cells, arguing against increased p-4E/p-4EBP levels. Quantification of immunoblot would help clarifying this.

We agree. However, total eIF4E and 4E-BP1 (eIF2a or GCN2) in these cells were unaffected by Gln-. SW480 cells have eIF4E but no detectable 4EBP1, supporting the heterogeneity of CRC, compared to more uniform p-4E in mouse polyps or human adenomas. This is also the very reason for us to examine these markers, ISR levels, and transcriptional response in a panel of CRCs including isogenic pairs.

21) The authors state “Together, our data support that p-4E controls cell death upon metabolic stress". This conclusion is only partially reflected by the data. I appreciate that HCT116 cells show reduced p-4E levels upon metabolic stress (GLN deprivation) associated with enhanced stress signaling (Figure 5). Instead, neither HT29 nor RKO cells that are sensitive to GLN deprivation with enhanced stress signaling, show changes in p-4E levels (Figure 7B). Therefore, it is questionable whether the proposed mechanism, p-4E regulating the response to metabolic stress, is a general feature of CRC. On the same line, a clear mechanism of the response to GLN deprivation in CRC cells has been described previously, that is associated with reduced nucleotide and MYC levels and, subsequently, slowed elongation of RNA Pol II and cell cycle arrest instead of apoptosis. This is not at all discussed in the manuscript.

See above and 11) too. This model helps explain that Myc-driven metabolic addiction likely goes beyond Gln to support increased biosynthesis. Metabolic stress (Gln-) leads to Myc loss and hyperactivation of ISR, with increased cell death and other oncogenic features. Therefore, the levels and duration of ISR dictates transcriptional response, TME interaction (i.e., immune signals) and outcome. See revised Figure 7F and Discussion section (2017 Embo paper and more papers cited).

22) The depicted model in Figure 7F is not comprehensible.

See 18, 20 and 21 too. We simplified the model to show how mutant KRAS (and other drivers) increases p-4E/p-4EBP1 and Myc/ISR and Gln-dependent growth. Gln deprivation reduced Myc and elevated ISR and cell death with other outcomes (transcriptional heterogeneity including immune suppression). Revised Figure 7F.

https://doi.org/10.7554/eLife.60151.sa2

Article and author information

Author details

  1. Hang Ruan

    1. Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. UPMC Hillman Cancer Center, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Xiangyun Li
    Competing interests
    No competing interests declared

  2. Xiangyun Li

    1. Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. UPMC Hillman Cancer Center, Pittsburgh, United States
    3. Department of Stem cell and regenerative medicine, Daping Hospital, Army Medical University, Chongqing, China
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Hang Ruan
    Competing interests
    No competing interests declared

  3. Xiang Xu

    1. Department of Stem cell and regenerative medicine, Daping Hospital, Army Medical University, Chongqing, China
    2. Central laboratory, State key laboratory of trauma, burn and combined Injury, Daping Hospital, Chongqing, China
    Contribution
    Resources, Data curation, Formal analysis, Supervision, Funding acquisition, Methodology, Writing - original draft
    Competing interests
    No competing interests declared

  4. Brian J Leibowitz

    1. Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. UPMC Hillman Cancer Center, Pittsburgh, United States
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared

  5. Jingshan Tong

    1. UPMC Hillman Cancer Center, Pittsburgh, United States
    2. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Methodology
    Competing interests
    No competing interests declared

  6. Lujia Chen

    1. UPMC Hillman Cancer Center, Pittsburgh, United States
    2. Department of Biomedical informatics, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Software, Formal analysis, Visualization, Writing - original draft
    Competing interests
    No competing interests declared

  7. Luoquan Ao

    1. Department of Stem cell and regenerative medicine, Daping Hospital, Army Medical University, Chongqing, China
    2. Central laboratory, State key laboratory of trauma, burn and combined Injury, Daping Hospital, Chongqing, China
    Contribution
    Data curation, Investigation, Methodology
    Competing interests
    No competing interests declared

  8. Wei Xing

    1. Department of Stem cell and regenerative medicine, Daping Hospital, Army Medical University, Chongqing, China
    2. Central laboratory, State key laboratory of trauma, burn and combined Injury, Daping Hospital, Chongqing, China
    Contribution
    Data curation, Investigation, Methodology
    Competing interests
    No competing interests declared

  9. Jianhua Luo

    Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared

  10. Yanping Yu

    Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Resources, Data curation
    Competing interests
    No competing interests declared

  11. Robert E Schoen

    Departments of Medicine and Epidemiology, University of Pittsburgh, Pittsburgh, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared

  12. Nahum Sonenberg

    Department of Biochemistry, Goodman Cancer Research Centre, McGill University, Montreal, Canada
    Contribution
    Methodology, Writing - original draft
    Competing interests
    Reviewing editor, eLife
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4707-8759

  13. Xinghua Lu

    1. UPMC Hillman Cancer Center, Pittsburgh, United States
    2. Department of Biomedical informatics, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Resources, Software, Supervision, Funding acquisition, Methodology
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8599-2269

  14. Lin Zhang

    1. UPMC Hillman Cancer Center, Pittsburgh, United States
    2. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    Contribution
    Resources, Supervision, Funding acquisition, Methodology
    Competing interests
    No competing interests declared

  15. Jian Yu

    1. Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, United States
    2. UPMC Hillman Cancer Center, Pittsburgh, United States
    Contribution
    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    yuj2@upmc.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4021-1000

Funding

NIH (R01CA215481)

  • Jian Yu

NIH (R01CA172136)

  • Lin Zhang

NIH (R01CA203028)

  • Lin Zhang

NIH (R01LM012011)

  • Xinghua Lu

National Key R and D Program of China (2018YFC1313400)

  • Xiang Xu

UPMC HCC (Institutional funds)

  • Jian Yu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

Funding: This work is supported in part by NIH grant R01CA215481 and institutional funds (JY), National Key R and D Program of China (2018YFC1313400) (XX), NIH grants R01LM012011 (XL), and R01CA172136 and R01CA203028(LZ). This project used the UPMC Hillman Cancer Center shared glassware, animal, and cell and tissue imaging facilities that were supported, in part, by National Cancer Institute award P30CA047904.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (# 19085635 and 18063020) of the University of Pittsburgh. All animal experiments were approved by the University of Pittsburgh Institutional Animal Care and Use Committee under Animal welfare assurance number A-3187-01. No surgery or invasive procedure was performed and every effort was made to minimize suffering with humane sacrifice.

Senior Editor

  1. Maureen E Murphy, The Wistar Institute, United States

Reviewing Editor

  1. Wafik S El-Deiry, Brown University, United States

Reviewer

  1. Zhenghe J Wang

Version history

  1. Received: June 17, 2020
  2. Accepted: October 31, 2020
  3. Accepted Manuscript published: November 2, 2020 (version 1)
  4. Version of Record published: November 13, 2020 (version 2)

Copyright

© 2020, Ruan et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Hang Ruan
  2. Xiangyun Li
  3. Xiang Xu
  4. Brian J Leibowitz
  5. Jingshan Tong
  6. Lujia Chen
  7. Luoquan Ao
  8. Wei Xing
  9. Jianhua Luo
  10. Yanping Yu
  11. Robert E Schoen
  12. Nahum Sonenberg
  13. Xinghua Lu
  14. Lin Zhang
  15. Jian Yu
(2020)
eIF4E S209 phosphorylation licenses myc- and stress-driven oncogenesis
eLife 9:e60151.
https://doi.org/10.7554/eLife.60151

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