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IER5, a DNA damage response gene, is required for Notch-mediated induction of squamous cell differentiation

  1. Li Pan
  2. Madeleine E Lemieux
  3. Tom Thomas
  4. Julia M Rogers
  5. Colin H Lipper
  6. Winston Lee
  7. Carl Johnson
  8. Lynette M Sholl
  9. Andrew P South
  10. Jarrod A Marto
  11. Guillaume O Adelmant
  12. Stephen C Blacklow
  13. Jon C Aster  Is a corresponding author
  1. Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, United States
  2. Bioinfo, Canada
  3. Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, United States
  4. Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College, Thomas Jefferson University, United States
  5. Departmentof Oncologic Pathology and Blais Proteomics Center, Dana FarberCancer Institute, HarvardMedical School, United States
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Cite this article as: eLife 2020;9:e58081 doi: 10.7554/eLife.58081

Abstract

Notch signaling regulates squamous cell proliferation and differentiation and is frequently disrupted in squamous cell carcinomas, in which Notch is tumor suppressive. Here, we show that conditional activation of Notch in squamous cells activates a context-specific gene expression program through lineage-specific regulatory elements. Among direct Notch target genes are multiple DNA damage response genes, including IER5, which we show is required for Notch-induced differentiation of squamous carcinoma cells and TERT-immortalized keratinocytes. IER5 is epistatic to PPP2R2A, a gene that encodes the PP2A B55α subunit, which we show interacts with IER5 in cells and in purified systems. Thus, Notch and DNA-damage response pathways converge in squamous cells on common genes that promote differentiation, which may serve to eliminate damaged cells from the proliferative pool. We further propose that crosstalk involving Notch and PP2A enables tuning and integration of Notch signaling with other pathways that regulate squamous differentiation.

Introduction

Notch receptors participate in a conserved signaling pathway in which successive ligand-mediated proteolytic cleavages by ADAM10 and γ-secretase permit intracellular Notch (ICN) to translocate to the nucleus and form a Notch transcription complex (NTC) with the DNA-binding factor RBPJ and co-activators of the Mastermind-like (MAML) family (for review, see Bray, 2016). Outcomes of Notch activation are dose and cell-context-dependent, in part because most Notch response elements lie within lineage-specific enhancers (Castel et al., 2013; Ryan et al., 2017; Skalska et al., 2015; Wang et al., 2014). As a result, Notch-dependent transcriptional programs vary widely across cell types.

The context-dependency of outcomes produced by Notch signaling is reflected in the varied patterns of Notch mutations that are found in different cancers (for review, see Aster et al., 2017). In some cancers oncogenic gain-of-function Notch mutations predominate, but in human cutaneous squamous cell carcinoma (SCC) (South et al., 2014; Wang et al., 2011) loss-of-function mutations are common, early driver events, observations presaged by work showing that loss of Notch function promotes skin cancer development in mouse models (Nicolas et al., 2003; Proweller et al., 2006). The mechanism underlying the tumor suppressive effect of Notch appears to involve its ability to promote squamous differentiation at the expense of self-renewal, a function that is operative in other squamous epithelia (Alcolea et al., 2014), where Notch also has tumor suppressive activities (Agrawal et al., 2011; Agrawal et al., 2012; Loganathan et al., 2020). In line with this idea, conditional ablation of Notch1 in postnatal mice results in epidermal hyperplasia and expansion of proliferating basal-like cells (Nicolas et al., 2003; Rangarajan et al., 2001). Moreover, murine and human β-papilloma viruses express E6 proteins that target MAML1 and inhibit Notch function (Meyers et al., 2017; Tan et al., 2012), thereby causing epidermal hyperplasia and delayed differentiation of infected keratinocytes. Conversely, constitutively active forms of Notch enhance keratinocyte differentiation in vitro and in vivo (Nickoloff et al., 2002; Rangarajan et al., 2001; Uyttendaele et al., 2004).

While these studies delineate a pro-differentiation, tumor suppressive role for Notch in squamous cells, little is known about the Notch target genes that confer this phenotype. Work to date has focused on candidate genes chosen for their known activities in keratinocytes or their roles as Notch target genes in other cell types. These include CDKN1A/p21 (Rangarajan et al., 2001), which has been linked to cell cycle arrest and differentiation (Missero et al., 1996); HES1, which represses basal fate/self-renewal (Blanpain et al., 2006); and IRF6, expression of which positively correlates with Notch activation in keratinocytes (Restivo et al., 2011). However, dose- and time-controlled genome-wide studies to determine the immediate, direct effects of Notch activation in squamous-lineage cells have yet to be performed.

To this end, we developed and validated 2D and 3D culture models of malignant and non-transformed human squamous epithelial cells in which tightly regulated Notch activation produces growth arrest and squamous differentiation. We find that immediate, direct Notch target genes are largely keratinocyte-specific and are associated with lineage-specific NTC-binding enhancers enriched for the motifs of transcription factors linked to regulation of keratinocyte differentiation, particularly AP1. Among these targets are multiple genes previously shown to be upregulated by DNA damage and cell stress, including IER5, a member of the AP1-regulated immediate early response gene family (Williams et al., 1999). Here, we show that IER5 is required for Notch-induced differentiation of human SCC cells and TERT-immortalized human keratinocytes, and that this requirement is abolished by knockout of the B55α regulatory subunit of PP2A, to which IER5 directly binds. Our studies provide the first genome-wide view of the effects of Notch on gene expression in cutaneous squamous carcinoma cells, highlight previously unrecognized crosstalk between Notch and DNA response genes, and point to the existence of a Notch-IER5-PP2A signaling axis that coordinates keratinocyte differentiation.

Establishment of a conditional Notch-on SCC model

Determination of the immediate, direct effects of Notch in a model system requires tightly timed, switch-like Notch activation. This is difficult to achieve with ligands because simple addition of soluble Notch ligands does not induce signaling (Sun and Artavanis-Tsakonas, 1997). Methods of triggering Notch activation include plating of cells on immobilized ligands (Varnum-Finney et al., 2000); treatment with EDTA, which renders Notch susceptible to activating cleavages by chelating Ca2+ and thereby destabilizing the Notch negative regulatory region (Rand et al., 2000); and γ-secretase inhibitor (GSI) washout, which reliably delivers a pulse of ICN in 15–30 min to the nuclei of cells expressing mutated or truncated forms of membrane-tethered Notch (Petrovic et al., 2019; Ryan et al., 2017; Wang et al., 2014; Weng et al., 2006). Plating of adherent cells on substrate coated with immobilized ligand is confounded by the need to first produce cell suspensions with trypsin and/or EDTA, which activates Notch in cells expressing Notch receptors. EDTA treatment also suffers from several limitations: (i) Notch activation is confined to a period of several minutes immediately following EDTA addition and is therefore limited in degree and duration, possibly because chelation of Zn2+ also rapidly inactivates ADAM metalloproteases and (ii) off-target effects of EDTA, including on surface proteins that mediate cell adhesion. GSI washout is open to criticism because γ-secretase has numerous substrates in addition to Notch receptors, raising questions about specificity. However, major phenotypes induced by treatment of flies (Micchelli et al., 2003), mice (van Es et al., 2005), and humans (Aster and Blacklow, 2012) with GSI are all related to Notch inhibition, strongly suggesting that Notch is the dominant GSI substrate at the organismal level. In line with these observations, in prior work we have noted that cells lacking ongoing Notch signaling show little or no change in phenotype when treated with GSI, and we therefore selected GSI washout to produce timed activation of Notch in cells of squamous lineage.

To create a squamous cell model in which GSI washout activates NOTCH1 (Figure 1A), we first engineered a cDNA encoding a mutated truncated form of NOTCH1, ΔEGF-L1596H, that cannot respond to ligand and that has a point substitution in its negative regulatory region that produces ligand-independent, γ-secretase-dependent Notch activation (Gordon et al., 2009; Malecki et al., 2006). Notably, when expressed from retroviruses NOTCH1 alleles bearing negative regulatory region mutations like L1596H generate Notch signals that are sufficient to produce physiologic effects in hematopoietic stem cells (induction of T cell differentiation) without causing pathophysiologic effects (induction of T cell acute lymphoblastic leukemia) (Chiang et al., 2008). Because Notch transcription complexes appear to largely act through ‘poised’ enhancers primed by lineage-specific ‘pioneer’ transcription factors (Falo-Sanjuan et al., 2019), we reasoned that squamous cell carcinoma lines with loss-of-function Notch mutations and little/no ongoing Notch signaling would be an ideal context in which to identify direct downstream targets of Notch. We therefore transduced ΔEGF-L1596H into two human SCC cell lines, IC8 and SCCT2, that have biallelic inactivating mutations in NOTCH1 and TP53 (Inman et al., 2018), lesions that were confirmed by resequencing on a clinical-grade targeted exome NGS platform (summarized in Tables 1 and 2).

Figure 1 with 3 supplements see all
Notch activation induces growth arrest and differentiation of squamous carcinoma cells.

(A) Strategy used to activate Notch in a tightly regulated fashion. (B) Notch-induced suppression of SC2 cell growth in standard cultures is abrogated by DN-MAML, a specific inhibitor of canonical Notch signaling. SC2 cells were transduced with empty MigRI virus (EV) or with MigRI virus encoding DN-MAML. Cell numbers at various times post-GSI washout (DMSO vehicle alone) or sham GSI-washout (GSI) were assessed using Cell Titer-Blue on biological replicates performed in quadruplicate. Error bars represent standard deviations. Timepoints with significantly different cell growth between Notch-on cells (DMSO, empty vector) and Notch-off cells (GSI, empty vector; DMSO, DN-MAML1; and GSI, DN-MAML1) are denoted with *** (p<0.005) or **** (p<0.0005) (two-tailed student t test). (C) Western blot showing the kinetics of activated intracellular NOTCH1 (ICN1) generation and increases in involucrin (IVL) following GSI washout in SC2 cells in standard cultures. (D) Notch-induced differentiation of SC2 cells is abrogated by DN-MAML. Transcripts for involucrin (IVL) and keratin1 (KRT1) were measured in the presence of GSI and 3 days after GSI washout in SC2 cells transduced with empty virus or with DN-MAML. Transcript abundance in biological replicates performed in triplicate was measured by RT-PCR and normalized against GAPDH. Error bars represent standard deviations of the mean. **, p<0.005; *, p<0.05; two-tailed student t-test. (E) Indirect immunofluorescence microscopy showing staining for involucrin (IVL, green) and plakophilin-1 (PKP1, red) in SC2 cells at time 0 and 6 and 8 days after GSI washout. Nuclei in each image were counterstained with DAPI. (F) Immunohistochemical staining of SC2 cells grown in skin raft cultures for 14 days in the presence and absence of GSI.

Table 1
Sequence variants, IC8* and SCCT2** squamous cell carcinoma cell lines.
GeneVariantVariant allele frequency
IC8 cell
CASP8c.971T > C(p.M324T)66% of 411 reads
FBXW7c.1633T > C(p.Y545H)33% of 195 reads
KMT2Dc.7412G > A(p.R2471Q)42% of 255 reads
MGAc.5599G > A(p.V1867I)39% of 710 reads
MTORc.4828G > A(p.E1610K)56% of 280 reads
NOTCH1c.5059C > T (p.Q1687*)100% of 412 reads
PAXIP1c.2023C > T(p.H675Y)17% of 384 reads
PMS1c.566_567delTCinsAT(p.V189D)36% of 108 reads
RIF1c.658G > A(p.E220K)62% of 251 reads
ROS1c.1144T > G(p.Y382D)87% of 169 reads
ROS1c.1164+2_1164+8delTTAGTCC ()19% of 191 reads
SDHAc.1627T > C(p.Y543H)56% of 668 reads
SF3B1c.2549T > C(p.I850T)31% of 246 reads
TERTCC242-243TT promoter mutation50% of 26 reads
TP53c.451C > T(p.P151S)100% of 366 reads
WHSC1c.2185C > T(p.R729C)66% of 410 reads
WWTR1c.551T > G (p.V184G)64% of 256 reads
ZNF217c.2590C > T(p.L864F)39% of 835 reads
ZNF217c.1162delC(p.H388Tfs*77)55% of 822 reads
SCCT2 Cell
ALKc.2854G > A (p.G952R)50% of 441 reads
ASXL1c.3959C > T (p.A1320V)31% of 930 reads
BRD3c.533C > T (p.S178F)49% of 281 reads
BRD4c.3915_3917dupTGC (p.A1306dup)45% of 170 reads
CDH4c.1801C > T (p.L601F)30% of 447 reads
CDKN2Ac.*151–1G > A ()100% of 172 reads
CDKN2Ac.212A > T (p.N71I)100% of 184 reads
CREBBPc.5842C > T (p.P1948S)74% of 77 reads
CREBBPc.2116G > A (p.G706R)45% of 172 reads
DDB1c.327+6G > A ()47% of 451 reads
DICER1c.775C > T (p.P259S)42% of 301 reads
DOCK8c.185T > A (p.V62E)100% of 597 reads
EGFRc.1955G > A (p.G652E)48% of 518 reads
EGFRc.298C > T (p.P100S)49% of 595 reads
ERCC2c.886A > T (p.S296C)48% of 165 reads
ERCC5c.264+1G > A ()50% of 442 reads
ETV4c.1298C > G (p.P433R)45% of 302 reads
FANCFc.494C > T (p.T165I)50% of 644 reads
FANCLc.155+1G > A ()51% of 220 reads
FAT1c.9076–1G > A ()49% of 367 reads
FHc.681G > T (p.Q227H)4% of 756 reads
FLT4c.2224G > A (p.D742N)49% of 346 reads
GALNT12c.1035+5G > A ()52% of 523 reads
GLI2c.1859C > A (p.T620K)45% of 351 reads
HNF1Ac.1640C > T (p.T547I)54% of 392 reads
JAZF1c.477C > T (p.I159I)47% of 606 reads
JAZF1c.328C > T (p.P110S)44% of 211 reads
KMT2Dc.10355+1G > A ()49% of 622 reads
LIG4c.1271_1275delAAAGA (p.K424Rfs*20)40% of 659 reads
MAP2K1c.568+1G > A ()53% of 239 reads
MED12c.2080G > A (p.E694K)100% of 269 reads
MYBc.1461+5G > A ()41% of 430 reads
NF1c.2608G > A (p.V870I)50% of 615 reads
NF2c.813T > G (p.F271L)48% of 168 reads
NOTCH1c.1226G > T (p.C409F)44% of 519 reads
NOTCH1c.1406A > G (p.D469G)50% of 912 reads
NOTCH1c.1245G > T (p.E415D)42% of 495 reads
NOTCH2c.5252G > A (p.G1751D)44% of 459 reads
NOTCH2c.1298G > A (p.C433Y)50% of 484 reads
NOTCH2c.1108+1G > A ()53% of 305 reads
NSD1c.7669G > A (p.G2557R)49% of 743 reads
PDGFRBc.2586+2T > A ()43% of 380 reads
PHOX2Bc.181A > T (p.T61S)52% of 222 reads
POLQc.6565G > A (p.A2189T)27% of 462 reads
POLQc.1634G > A (p.S545N)33% of 667 reads
PPARGc.819+6T > C ()100% of 134 reads
PRKDCc.6436G > A (p.A2146T)42% of 471 reads
RAD51Cc.996G > A (p.Q332Q)45% of 302 reads
RHEBc.443C > T (p.S148F)46% of 120 reads
ROS1c.6871C > T (p.P2291S)45% of 605 reads
ROS1c.3342A > T (p.Q1114H)48% of 274 reads
ROS1c.137A > T (p.D46V)42% of 215 reads
RPTORc.2992G > A (p.V998I)48% of 352 reads
RUNX1T1c.1039G > A (p.D347N)45% of 715 reads
SDHAc.1151C > T (p.S384L)53% of 446 reads
SLC34A2c.1700T > A (p.I567N)50% of 460 reads
SMARCA4c.3947T > G (p.F1316C)55% of 431 reads
SMARCE1c.395C > T (p.A132V)51% of 587 reads
STAT3c.1852G > A (p.G618S)47% of 527 reads
TDGc.166+4G > A ()48% of 329 reads
TP53c.375+1G > T47% of 173 reads
TP53c.832_833delCCinsTT (p.P278F)46% of 418 reads
UIMC1c.971T > C (p.V324A)48% of 745 reads
XPCc.571C > T (p.R191W)100% of 219 reads
  1. *Based on analysis of 16,131,317 unique, high-quality sequencing reads (mean, 406 reads per targeted exon, with 98% of exons having more than 30 reads).

    Based on analysis of 20,972,158 unique, high-quality sequencing reads (mean, 413 reads per targeted exon, with 99% of exons having more than 30 reads).

Table 2
Copy number variants, squamous cell carcinoma cell lines.
ChromosomeTypeGenes affected
IC8 cell line
1qGainMCL1, GBA, RIT1, NTRK1, DDR2, PVRL4, SDHC, CDC73, MDM4, PIK3C2B, UBE2T, PTPN14, H3F3A, EGLN1, AKT3, EXO1, FH
2LossXPO1, FANCL, REL, MSH6, EPCAM, MSH2, SOS1, ALK, BRE, DNMT3A, GEN1, MYCN, TMEM127, GLI2, ERCC3, CXCR4, RIF1, ACVR1, ABCB11, NFE2L2, PMS1, CASP8, SF3B1, CTLA4, ERBB4, IDH1, BARD1, XRCC5, DIS3L2
3pLossMITF, BAP1, PBRM1, COL7A1, RHOA, SETD2, CTNNB1, MLH1, MYD88, XPC, PPARG, RAF1, FANCD2, OGG1, VHL
3qGainNFKBIZ, CBLB, POLQ, GATA2, MBD4, TOPBP1, FOXL2, ATR, MECOM, PRKCI, TERC, PIK3CA, SOX2, ETV5, BCL6
4LossPHOX2B, RHOH, SLC34A2, FGFR3, WHSC1, KDR, KIT, PDGFRA, FAM175A, HELQ, TET2, FBXW7, NEIL3, FAT1
5GainRICTOR, IL7R, SDHA, TERT, MAP3K1, PIK3R1, XRCC4, RASA1, APC, RAD50, CTNNA1, PDGFRB, ITK, NPM1, TLX3, FGFR4, NSD1, UIMC1, FLT4
6GainCCND3, NFKBIE, POLH, VEGFA, CDKN1A, PIM1, RNF8, FANCE, DAXX, HFE, HIST1H3B, HIST1H3C, ID4, PRDM1, ROS1, RSPO3, MYB, TNFAIP3, ESR1, ARID1B, PARK2, QKI
7GainEGFR, IKZF1, JAZF1, ETV1, PMS2, RAC1, CARD11, SBDS, CDK6, SLC25A13, CUX1, RINT1, MET, POT1, SMO, BRAF, PRSS1, EZH2, RHEB, XRCC2, PAXIP1
8pLossKAT6A, POLB, FGFR1, WHSC1L1, NRG1, WRN, NKX3-1, PTK2B, GATA4, NEIL2
8q11.21-q21.11LossPRKDC, MYBL1, TCEB1
8q21.3-q24.3GainNBN, RUNX1T1, RAD54B, RSPO2, EXT1, RAD21, MYC, RECQL4
9p13.2-p21.3LossPAX5, FANCG, RMRP, CDKN2A, CDKN2B, MTAP
9p24.1-p24.3GainCD274, JAK2, PDCD1LG2, DOCK8
11p11.2-p13GainEXT2, LMO2
13q33.1LossERCC5
15qGainFAN1, GREM1, BUB1B, MGA, RAD51, TP53BP1, B2M, USP8, MAP2K1, PML, NEIL1, FAH, NTRK3, BLM, FANCI, IDH2, IGF1R
16p13.3LossCREBBP, SLX4
19LossBABAM1, CRTC1, JAK3, KLF2, MEF2B, BRD4, NOTCH3, CALR, KEAP1, SMARCA4, ELANE, GNA11, MAP2K2, STK11, TCF3, CCNE1, C19orf40, CEBPA, AKT2, AXL, CIC, XRCC1, ARHGAP35, ERCC1, ERCC2, BCL2L12, PNKP, POLD1, PPP2R1A
20GainMCM8, ASXL1, BCL2L1, MAFB, AURKA, ZNF217, GNAS, CDH4
SCCT2 Cell Line
1q32.1LossUBE2T
1q42.12-q42.2GainH3F3A, EGLN1
1q43LossAKT3, EXO1
1q43GainFH
3 p Arm levelLossMITF, BAP1, PBRM1, COL7A1, RHOA, SETD2, CTNNB1, MLH1, MYD88, XPC, PPARG, RAF1, FANCD2, OGG1, VHL
3q Arm levelGainNFKBIZ, CBLB, POLQ, GATA2, MBD4, TOPBP1, FOXL2, ATR, MECOM, PRKCI, TERC, PIK3CA, SOX2, ETV5, BCL6
8q Arm levelGainPRKDC, MYBL1, TCEB1, NBN, RUNX1T1, RAD54B, RSPO2, EXT1, RAD21, MYC, RECQL4
9q Arm levelGainGNAQ, NTRK2, FANCC, PTCH1, GALNT12, XPA,
KLF4, TAL2, ENG, ABL1, TSC1, BRD3, NOTCH1
18q11.2GainGATA6, RBBP8
18q11.2-q21.33GainSS18, SETBP1, SMAD2, SMAD4, BCL2
20GainMCM8, ASXL1, BCL2L1, MAFB, AURKA, ZNF217,
GNAS, CDH4

In pilot studies, we observed that the growth of IC8 and SCCT2 cells transduced with empty virus was unaffected by the presence or absence of GSI, whereas the growth of lines transduced with ΔEGF-L1596H was reduced by GSI washout (Figure 1—figure supplement 1A, B). GSI washout was accompanied by rapid activation of NOTCH1 (ICN1) followed by upregulation of markers of differentiation, such as involucrin (Figure 1—figure supplement 1C, D). Of interest, ICN1 levels reproducibly peaked at around 4 hr and then declined, suggesting that sustained NOTCH1 activation and accompanying changes in cell state led to induction of feedback loops that negatively regulate ICN1. We also observed that IC8-ΔEGF-L1596H cells formed ‘skin-like’ epithelia when seeded onto organotypic 3D cultures, whereas SCCT2-ΔEGF-L1596H cells did not (data not shown); therefore, additional studies focused on IC8 cells and derivatives thereof.

To further characterize and validate our system, we performed single-cell cloning of IC8−ΔEGF-L1596H cells and observed that differentiation following GSI washout correlated with ICN1 accumulation (Figure 1—figure supplement 2A and B). The subclone SC2, which showed moderate accumulation of ICN1 and sharply reduced growth following GSI washout, was selected for further study. The ability of SC2 cells to form a multilayered epithelium in the Notch-on, growth suppressive state appears to stem from an unexpected property that emerged in 3D cultures, namely the self-organization of these cells into a proliferating, ICN1-low basal layer in contact with matrix and a non-proliferating, ICN1-high suprabasal layer (Figure 1—figure supplement 2C). The self-organization of Notch-on SC2 cells grown on collagen rafts into ICN1-low basal proliferating cells and ICN1-high suprabasal non-proliferating cells suggested that contact of SC2 cells with collagen reduces ICN1 levels. To test this idea, we plated SC2 cells on plastic or collagen, washed out GSI, and compared ICN1 levels by western blotting. As shown in Figure 1—figure supplement 2D, culture of SC2 cells on collagen sharply reduced ICN1 levels, whereas the level of total NOTCH1 polypeptides was unchanged or slightly increased in cells grown on collagen. These observations point to the existence of one or more matrix-dependent effects that decrease ICN1 levels and which may serve to reinforce the ‘Notch-low’ status of basal keratinocytes.

We also noted that the growth arrest induced by GSI washout in SC2 cells was blocked by dominant-negative MAML1 (DN-MAML), a specific inhibitor of Notch-dependent transcription (Figure 1BNam et al., 2007; Weng et al., 2003), confirming that the growth inhibitory effects of GSI washout are mediated through Notch activation. Growth arrest occurred several days after Notch activation (compare Figure 1B and C) and was accompanied by upregulation of multiple markers of squamous differentiation, such as involucrin, keratin1, and plakophilin1, in 2D (Figure 1C–E) and in 3D cultures (Figure 1F). In addition, we also noted that staining for keratin14, a prototypic marker of proliferating basal keratinocytes (Fuchs, 1995), became more sharply localized to basal cells in Notch-on SC2 cells (Figure 1F).

Although Notch activation in IC8 and SC2 cells clearly induced expression of squamous differentiation markers, the distribution of these markers in 3D cultures failed to precisely mimic that of normal epidermis, as staining for involucrin and plakophilin-1 was seen in proliferating keratin14-positive basal cells. The observed expression of spinous markers in ICN1-low proliferating basal cells may be explained by differing Notch dose requirements for growth arrest (relatively high) versus induction of spinous differentiation (relatively low). To further compare and contrast the effects of Notch activation in SC2 cells with normal keratinocyte differentiation, we performed staining for a series of additional markers (Figure 1—figure supplement 3). Similar to normal keratinocyte differentiation, Notch activation was associated with increased staining for BCL6, particularly in suprabasal SC2 cells. By contrast, p63 staining, which is normally confined to basal keratinocytes, was seen in suprabasal as well as basal SC2 cells, and keratin5 staining was observed throughout SC2 cell rafts, in contradistinction to keratin14 staining (Figure 1F). Notch activation also failed to induce staining for markers of terminal differentiation such as filaggrin (Figure 1—figure supplement 3) and loricrin (not shown). Thus, Notch activation in SC2 cells induces genes associated with spinous differentiation but is insufficient to down-regulate certain genes associated with basal cell fate, such as p63 and keratin5, or to push SC2 cells to terminally differentiate.

Identification of a squamous cell-specific Notch-induced program of gene expression

To determine early and delayed effects of Notch on gene expression, we performed RNA-seq on SC2 cells in 2D cultures in the Notch-off state and following Notch activation. Because γ-secretase has numerous substrates, as a control we performed RNA-seq on parental, non-transduced IC8 cells in the presence of GSI and following GSI washout, which revealed no significant GSI-dependent changes in gene expression in the absence of a Notch transgene (Figure 2—figure supplement 1). By contrast, Notch activation in SC2 cells produced significant changes in gene expression by 4 hr that became more pronounced by 24 hr and 72 hr (Figure 2A, see Supplementary files 13 for differentially expressed genes). Gene ontology (GO) analysis revealed enrichment among upregulated genes for those that are associated with keratinocyte differentiation and biology (Supplementary files 4 and 5, summarized in Figure 2B). Among the rapidly upregulated genes (genes that increase in expression by 4 hr) were several reported targets of Notch in keratinocytes (e.g, RHOV [Pomrey and Radtke, 2010], HES1 [Blanpain et al., 2006], and IRF6 [Restivo et al., 2011]), but most genes in this class were novel for keratinocytes and included: (1) direct targets of Notch in other lineages (e.g. NRARP, HES4, and HES5); (2) genes linked to keratinocyte differentiation (e.g. RIPK4 [Kwa et al., 2014], recently reported to be upregulated following treatment of keratinocytes with EDTA [Loganathan et al., 2020], and SMAD3 [Meyers et al., 2017]); (3) genes associated with DNA damage responses in keratinocytes and other cell types (e.g. GADD45A, CXCL8, IL1B, ID3, CYR61, BTG2, IER3, and IER5 [Kis et al., 2006; Kumar et al., 1998; Maeda et al., 2002; Rouault et al., 1996; Sesto et al., 2002; Simbulan-Rosenthal et al., 2006]); and (4) genes associated with growth arrest of keratinocytes and other cell types (e.g. HES1 [Blanpain et al., 2006], GADD45A [Maeda et al., 2002], and BTG2 [Rouault et al., 1996]).

Figure 2 with 2 supplements see all
Identification of Notch-induced genes in squamous carcinoma cells.

(A) Volcano plots showing changes in RNA transcript read counts induced by Notch activation in SC2 cells for 4, 24, and 72 hr as compared to control cells treated with sham GSI washout. RNA-seq for each treatment group was performed in triplicate on biological replicates. Vertical lines denote a twofold change in read count, while the horizontal line denotes a false discovery rate (FDR) of 5%. (B) Gene ontogeny (GO) annotation of differentially expressed genes in ‘Notch-on’ SC2 cells. The most highly associated GO terms are shown; other significant associated annotated gene sets (FDR < 5%) are listed in Supplementary file 7. (C-E) Transcriptional responses of selected ‘canonical’ Notch target genes (C), genes linked to keratinocyte differentiation (D), and genes associated with DNA damage responses (E), to Notch activation in IC8-ΔEGF-L1596H cells. Transcript abundance in technical replicates prepared in triplicate was measured by RT-PCR and normalized against GAPDH. Error bars represent standard deviations of the mean. (F) Western blots of cell lysates prepared from IC8-ΔEGF-L1596H cells transduced with empty virus (EV) or DN-MAML following sham GSI washout (-) or 24 hr post-GSI washout (+).

To confirm that these changes in gene expression are general features of Notch activation in IC8-ΔEGF-L1596H cells and to determine the kinetics of response, we performed RT-PCR analyses on a number of known and novel targets in pooled IC8-ΔEGF-L1596H transductants. This confirmed the Notch responsiveness of all genes tested, and also revealed variation in the kinetics of response, even among ‘canonical’ Notch target genes. For example, HES1 showed fast induction followed by rapid down-regulation, consistent with autoinhibition (Hirata et al., 2002), whereas HES4, HES5, and NRARP (a feedback inhibitor of NTC function [Jarrett et al., 2019]) showed more sustained increases in expression (Figure 2C). Genes encoding non-structural proteins known to be linked to squamous differentiation also were ‘early’ responders (Figure 2D), as were genes linked to DNA damage/cell stress response (Figure 2E). In the case of the latter novel targets, we confirmed that protein levels also rose in a Notch-dependent fashion (Figure 2F). By contrast, increased expression of genes encoding structural proteins associated with keratinocyte differentiation (e.g. IVL, KRT1, KRT13) was delayed, only emerging at 24–72 hr (Supplementary files 13). These findings suggest that Notch activation induces the expression of a core group of early direct target genes, setting in motion downstream events that lead to differentiation.

Notch activation also down-regulated a smaller set of genes (Figure 2A, summarized in Supplementary files 13), possibly via induction of transcriptional repressors of the Hes family. These include multiple genes expressed by basal epidermal stem cells, including genes encoding the Notch ligand DLL1 (Lowell et al., 2000); β1-integrin (Jones and Watt, 1993); LRIG1 (Jensen and Watt, 2006), a negative regulator of epidermal growth factor receptor signaling; and multiple WNT ligands (WNT7A, 7B, 9A, 10A, and 11), of interest because WNT signaling contributes to maintenance of epidermal stem cells (Lim et al., 2013).

To determine the overlap of Notch target genes in squamous cells with other cell lineages, we compared the list of Notch-responsive genes in SC2 cells with three other cell types in which GSI washout has been used to identify genes that are rapidly upregulated by Notch: triple-negative breast cancer cells (Petrovic et al., 2019); mantle cell lymphoma cells (Ryan et al., 2017); and T-cell acute lymphoblastic leukemia (T-ALL) cells. Using fairly stringent cutoffs for Notch-responsiveness (FDR < 0.05, log2 change >1; summarized in Supplementary file 6), we failed to identify any genes that were co-regulated by Notch in all of these cell types (Figure 2—figure supplement 2). Even in two epithelial cell types, SC2 squamous cells and MB157 triple negative breast cancer cells, only 10.8% of Notch-responsive genes in SC2 cells were also Notch-responsive in MB157 cells. As would be expected, the overlap between Notch-responsive genes in SC2 cells and B lineage REC1 cells (9/390, 2.3%) and T lineage DND41 cells (1/390, 0.3%) was even lower. These observations serve to again emphasize the remarkable context-specificity of Notch effects on gene expression.

Notch target genes are associated with lineage-specific NTC-binding enhancer elements

To identify sites of NTC-binding to Notch-responsive regulatory elements in IC8-ΔEGF-L1596H cells, we performed ChIP-seq for Notch transcription complex components (RBPJ and MAML1) 4 hr after Notch activation, as well as for RBPJ prior to Notch activation. The rationale for identifying RBPJ and MAML1-binding sites, rather than NOTCH1-binding sites, was several fold: (i) we wanted to identify binding of endogenous Notch transcription complex components with reliable commercially available monoclonal antibodies; (ii) based on our RNA-seq data sets, MAML1 is the most highly expressed member of the MAML family in IC8 cells (MAML1 log2 read counts per million = 6.66; MAML2 log2 read counts per million = 3.59; MAML3 log2 read counts per million = 0.70), and therefore was the logical member of the family to study; and (iii) we were intrigued by prior studies suggesting that MAML1 might associate with non-Notch transcription factor complexes (Jin et al., 2010; Quaranta et al., 2017; Shen et al., 2006; Zhao et al., 2007). In the Notch-on state, we found that most MAML1 binding sites also bound RBPJ (8533/9,187 sites, 93%; Figure 3A), in line with studies showing that MAML1 association with DNA requires both RBPJ and NICD (Nam et al., 2006). Approximately 92% of RBPJ/MAML1 co-binding sites (hereafter designated NTC binding sites) are in intergenic or intronic regions consistent with enhancers (Figure 3B). As predicted by past studies (Castel et al., 2013; Krejcí and Bray, 2007; Ryan et al., 2017; Wang et al., 2014), NTC binding was associated with increases in RBPJ ChIP-Seq signals and H3K27ac signals at promoter and enhancer sites (Figure 3C), features previously noted to characterize ‘dynamic’ functional Notch response elements. Motif analysis revealed that the most common motif lying within 300 bp of NTC ChIP-Seq signals is that of RBPJ (Figure 3D), and that the motif for AP1, a factor not associated with NTC binding sites in other cell types (Chatr-Aryamontri et al., 2017; Drier et al., 2016; Petrovic et al., 2019; Ryan et al., 2017; Wang et al., 2014), is also highly enriched in this 600 bp window. Based on the method of Severson et al., 2017, approximately 13% of NTC-binding sites in IC8 cells are predicted to be sequence paired sites (Figure 3E), a specialized type of response element that binds NTC dimers (Arnett et al., 2010). Finally, particularly at early time points, NTC-binding sites were spatially associated with genes that are upregulated by Notch, whereas genes that decreased in expression were no more likely to be associated with NTC binding sites than genes that did not change in expression (Figure 3F). Taken together, these studies show that NTCs mainly bind lineage-specific enhancers in SCC cells and that their loading leads to rapid ‘activation’ of Notch-responsive elements and upregulation of adjacent genes.

Characterization of Notch transcription complex (NTC) binding sites in IC8-ΔEGF-L1596H cells.

(A) Number and overlap of RBPJ and MAML1 binding sites determined by ChIP-Seq of chromatin prepared 4 hr after Notch activation. (B) Genomic distribution of RBPJ/MAML1 co-binding sites 4 hr after Notch activation. TTS, transcription termination sites; ncRNA, non-coding RNA. (C) Effect of NTC loading on histone3 lysine27 acetylation (H3K27ac), based on ChIP-Seq for H3K27ac in cells maintained in GSI and in cells 1, 2, and 4 hr after GSI washout. (D) Transcription factor motifs enriched within 300 bp of RBPJ/MAML1 ChIP-Seq signal peaks. (E) Protein-binding matrix (PBM) X PBM scores for NTC-binding sites. Sites with scores in the right-hand Gaussian distribution correspond to likely sequence paired sites. (F) Kolmogorov-Smirnov analysis showing spatial relationships between NTC-binding sites and transcriptional start sites (TSSs) of genes that increase, decrease, or are unchanged in expression following Notch activation. The gray zone denotes genes with TSSs within 2 kb of RBP/MAML1 peaks.

We also performed motif analysis on sites producing significant signals for only RBPJ or only MAML1. RBPJ ‘only’ sites also were enriched for RBPJ (E value 1.3e-124) and AP1 (E value 2.8e-71) motifs but had lower average ChIP-Seq signals, suggesting these may be weak RBPJ-binding sites. MAML1 ‘only’ sites also were enriched for AP1 motifs (E value 2.9e-181) but were not associated with RBPJ motifs. These sites were relatively few in number (N = 654) and the associated AP1 motifs were distributed broadly around MAML1 signal peaks, arguing against direct physical interaction between MAML1 and AP1 family members on chromatin. Thus, the significance of these ‘MAML1-only’ peaks is uncertain, and it is possible that the observed ChIP-seq signals are non-specific, stemming from over-representation of ‘open’ chromatin in ChIPs.

IER5 is a direct Notch target gene

We were intrigued by the convergence of Notch target genes, which presumably serve to promote and coordinate keratinocyte differentiation, and genes linked to DNA damage/cell stress responses. We selected one gene of this class, IER5, a member of the immediate early response gene family, for detailed analysis based on prior work implicating IER5 in cellular responses to DNA damaging agents and heat shock (Ding et al., 2009; Ishikawa and Sakurai, 2015; Kis et al., 2006), as well as functional studies suggesting that IER5 is a modulator of the serine/threonine kinase PP2A (Asano et al., 2016; Ishikawa et al., 2015; Kawabata et al., 2015) and might therefore serve as point of crosstalk between Notch and signaling pathways that depend on serine/threonine phosphorylation for signal transduction.

To confirm that IER5 is also upregulated by activation of endogenous Notch signaling in non-transformed keratinocytes, we studied TERT-immortalized NOK1 keratinocytes, which undergo squamous differentiation when moved to high Ca2+ medium (Piboonniyom et al., 2003). We observed that differentiation of NOK1 cells significantly increased the expression of IER5 as well as the canonical Notch target gene NRARP, effects that were blocked by GSI and by DN-MAML1, confirming that the observed changes in gene expression are Notch-dependent (Figure 4—figure supplement 1A and B). In line with the Notch-dependent increases in IER5 transcripts upon induction of differentiation, we also observed that IER5 protein levels increased in differentiation medium in a GSI- and DN-MAML1-sensitive fashion (Figure 4—figure supplement 1C and D). Differentiation was accompanied by activation of NOTCH2 and NOTCH3 (inferred from the accumulation of smaller polypeptides consistent with ADAM cleavage products under differentiation conditions in the presence of GSI; Figure 4—figure supplement 1C and D), as well as increased expression of NOTCH3, a known target of activated Notch. Suppression of IER5 transcript levels by GSI in some experiments was less pronounced than the abrogation of the accumulation of IER5 protein by Notch inhibitors, suggesting that additional pathways influence IER5 expression (consistent with the complex enhancer landscape around this gene) and that Notch signaling may regulate IER5 both transcriptionally and post-transcriptionally. Unexpectedly, we did not observe any activation of NOTCH1 in NOK1 cells in differentiation medium (data not shown), suggesting that differentiation in this model is directed by NOTCH2 instead of NOTCH1. Notably, given that germline swaps of the coding sequences of the intracellular domains of NOTCH1 and NOTCH2 yield apparently normal mice (Liu et al., 2015), it is likely that NOTCH1 and NOTCH2 activate the same sets of target genes, including IER5 in keratinocytes.

We next sought to confirm that IER5 is a direct Notch target gene. Inspection of chromatin landscapes around IER5 in IC8 cells revealed a series of flanking enhancers, two of which (D and E) showed the largest RBPJ/MAML1 signals and the greatest increase in H3K27ac following Notch activation (Figure 4A), a dynamic change that is strongly correlated with increased transcription of flanking genes (Wang et al., 2014). Notably, a similar enhancer landscape exists in non-transformed human keratinocytes (Figure 4—figure supplement 1E), and expression of IER5 transcripts is readily detectable in normal human skin (Figure 4—figure supplement 1F-H), consistent with the idea that the observed enhancers are involved in physiologic regulation of IER5 in keratinocytes. Reporter gene assays with enhancers D and E in IC8-ΔEGF-L1596H cells (Figure 4B and C, respectively) confirmed that the Notch responsiveness of these elements depend on RBPJ-binding sites and also showed, in the case of enhancer D, that a flanking AP1 consensus site is also required. To determine the contributions of enhancers D and E within the genomic IER5 locus, we used CRISPR/Cas9 targeting to delete the regions containing RBPJ-binding sites in these two enhancers in SC2 cells (Figure 4D). These deletions partially abrogated the Notch-dependent increase in IER5 transcription (Figure 4E) and suppressed the accumulation of IER5 protein following Notch activation (Figure 4F), confirming that IER5 is directly regulated by Notch through these elements.

Figure 4 with 1 supplement see all
IER5 is a direct Notch target gene.

(A) Chromatin landscapes around IER5 in IC8-ΔEGF-L1596H cells. ChIP-Seq signals for RBPJ, MAML1, and H3K27ac for cells maintained in and 4 hr after GSI washout (WO) are shown. (B, C) Activities of a WT IER5 enhancer E luciferase reporter gene and derivatives bearing mutations (μ) in two RBPJ consensus motifs (B) and a WT IER5 enhancer D luciferase reporter gene and derivatives bearing mutations in two RBPJ consensus motifs or in flanking AP1 consensus motifs (C). Reporter gene assays were performed in SC2 cells maintained in GSI or 24 hr after GSI washout (WO). Luciferase reporter gene activity was determined in biological replicates prepared in triplicate and normalized to the activity of a Renilla luciferase internal control gene. Error bars represent standard deviations. (D) Cartoon showing the CRISPR/Cas9 targeting strategy for IER5 enhancers D and E. (E) Relative IER5 transcript levels in SC2 cells targeted with control AAVS1 CRISPR/Cas9 plasmids (SC2/con) or with CRISPR/Cas9 plasmids that remove the RPBJ sites in enhancers D and E (SC2/ΔD+E). Cells were either maintained in GSI or were harvested 2 hr following GSI washout (WO). Transcript abundance was measured in experimental triplicates by RT-PCR and normalized against GAPDH. Error bars represent standard errors of the mean. (F) Western blots showing IER5 protein levels in SC2/con cells and SC2/ΔD+E cells that were either maintained in GSI or harvested 1, 2, or 4 hr following GSI washout (WO). In B, C, and E, *, p<0.05; **, p<0.005; ***, p<0.0005 (all two-tailed student t test); NS, not significant.

IER5 is required for ‘late’ Notch-dependent differentiation events in squamous cells

To systematically determine the contribution of IER5 to Notch-dependent changes in gene expression, we compared the transcriptional response to Notch activation in SC2 cells, SC2 cells in which IER5 was knocked out (I5 cells), and I5 cells to which IER5 expression was added back (I5AB cells, Figure 5A). Different doses of IER5 had no effect on gene expression in the absence of Notch signaling, or on the expression of genes that are induced by Notch within 4 hr (Figure 5B, denoted with a blue box); however, by 24 hr and 72 hr of Notch activation, I5 cells failed to upregulate a large group of Notch-responsive genes that were rescued by add-back of IER5 (Figure 5B, denoted with a red box). GO analysis revealed that IER5-dependent genes were associated with various aspects of keratinocyte differentiation and biology (Figure 5C; summarized in Supplementary files 7 and 8). An example of a differentiation-associated gene impacted by loss of IER5 is KRT1, a marker of spinous differentiation, expression of which is markedly impaired by IER5 knockout and restored by IER5 add-back (Figure 5D). Similarly, IER5 was required for Notch-dependent expression of the late marker involucrin in 3D cultures (Figure 5G). Thus, IER5 is necessary but not sufficient for expression of a group of genes that respond to Notch with delayed kinetics.

Effect of IER5 on Notch-dependent changes in gene expression in SC2 cells and NOK1 cells.

(A) Western blots showing IER5 and ICN1 protein levels in SC2 cells, a single-cell clone derived from SC2-IER5 knockout cells (I5KO), I5KO cells transduced with empty virus (I5/con), and pooled I5KO cells transduced with IER5 cDNA (I5AB) that were maintained in GSI (-) or harvested 48 hr post-GSI washout (+). (B) Heat map showing Notch-induced changes in gene expression in SC2 cells, I5KO cells, and I5AB cells. RNA-seq was performed in biological replicates in triplicate at time 0, 4 hr, 24 hr, and 72 hr after GSI washout. Samples were subjected to unsupervised clustering using a gene set containing all genes that were significantly upregulated at any time point after Notch activation in SC2 cells. The blue boxes highlight genes that are upregulated at 4, 24, and 72 hr after Notch activation, whereas the red box highlights genes that are under-expressed in IER5 knockout cells (I5KO) and rescued by re-expression of IER5 (I5AB) at later timepoints (24 and 72 hr). (C) Gene ontogeny (GO) terms associated with the set of under-expressed genes in I5KO cells following Notch activation. FDR = false discovery rate. (D) Diminished induction of KRT1 expression at 24 and 72 hr after GSI WO in I5KO cells is prevented by IER5 addback (I5AB cells). Transcript abundance in biological replicates prepared in triplicate was measured by RT-PCR and normalized against GAPDH. Error bars represent standard deviations of the mean. *, p<0.05; **, p<0.005; NS, not significant (two-tailed student t test). (E) Immunohistochemical staining for involucrin in SC2, I5KO, and I5AB cells in raft cultures grown in the absence of GSI. (F, G) Effect of CRISPR/Cas9 targeting of IER5 and enforced IER5 expression on differentiation-associated transcripts in NOK1 cells. In F, NOK1 cells were transduced with CRISPR/Cas9, GFP, and IER5 (I5KO) gRNA or AAVS1 control (con) gRNA and sorted for GFP positivity. In G, NOK1 cells were transduced with empty GFP-expressing retrovirus (con) or IER5 and GFP and sorted. In F and G, analyses were done on pooled GFP-positive transductants, which were moved to high Ca2+ medium for 3 days (F) or 5 days (G) prior to harvest. Inset western blots show the extent of IER5 loss (F) and IER5 overexpression (G) relative to control cells. In F and G, transcript abundance was measured in biological replicates prepared in triplicate by RT-PCR and normalized against GAPDH. Error bars represent standard deviations of the mean. *, p<0.05, student two-sided t test.

To extend these observations to non-transformed keratinocytes that rely on endogenous Notch signaling for differentiation, we targeted IER5 with CRISPR/Cas9 and also enforced expression of IER5 through retroviral transduction in NOK1 cells. Although CRISPR/Cas9 targeting of bulk NOK1 cells was only partially effective, it was sufficient to diminish the expression of multiple differentiation-associated genes (Figure 5F), whereas overexpression of IER5 increased expression of each of these markers (Figure 5G). Thus, IER5 is required for Notch-dependent differentiation of malignant and non-transformed keratinocytes.

IER5 binds B55α/PP2A complexes

IER5 encodes a 327 amino acid protein with a ~ 50 amino acid N-terminal IER domain and a C-terminal domain predicted to be unstructured, suggesting that it functions through protein-protein interactions. To identify interacting proteins in an unbiased way, we expressed a tagged form of IER5 in IER5 null I5 cells and performed affinity purification followed by mass spectrometry (Adelmant et al., 2019), which identified the B55α regulatory subunit of PP2A (encoded by the PPP2RA2 gene) and PP2A scaffolding and catalytic subunits as potential interactors (Figure 6A; summarized in Supplementary file 9). We confirmed these associations by expressing tagged IER5 in I5 cells and tagged B55α in SC2 cells (Figure 6B). Full-length IER5 and the N-terminal IER domain of IER5 co-precipitated endogenous B55α in Notch-independent fashion, whereas the C-terminal portion of IER5 did not (Figure 6C). Similarly, tagged B55α co-precipitated endogenous IER5 in a fashion that was augmented by Notch activation (Figure 6D), consistent with increased recovery of IER5 due to induction of IER5 expression by Notch. To confirm that IER5 binds B55α directly, we studied the interaction of purified recombinant proteins. IER5 exhibited saturable binding to B55α-coated beads (Figure 6E), and additional microscale thermophoresis studies showed that IER5 binds B55α with a Kd of approximately 100 nM (Figure 6F).

IER5 binds to B55α.

(A) Polypeptides identified by mass spectroscopy in immunoprecipitates prepared from I5 cells expressing tandem-tagged IER5. (B) Cartoon showing the structure of tandem-tagged IER5 polypeptides. FH, FLAG-HA tag. (C) Western blot analysis of immunoprecipitates prepared from I5 cells expressing the indicated forms of tagged IER5. WO, washout. (D) Western blot analysis of immunoprecipitates prepared from SC2 cells expressing FLAG-tagged B55α. (E) Western blot showing that IER5 binds His-Sumo-tagged B55α immobilized on beads. The upper two panels were stained for IER5, while the lower two panels were stained for SUMO. (F) Microscale thermophoresis showing saturable binding of IER5 to His-Sumo-tagged B55α.

IER5 is epistatic to PPP2R2A in SCC cells

To gain insight into the role of IER5-B55α interaction in the regulation of Notch- and IER5-sensitive genes, we prepared SCC cells that were knocked out for IER5, PPP2R2A, or both genes (Figure 7A). Knockout of PPP2R2A did not affect the levels of ICN1 following GSI washout (Figure 7A), but markedly increased the expression of the late differentiation gene KRT1 in 2D culture (Figure 7B) and the accumulation of involucrin in 3D cultures (Figure 7C), effects that were suppressed by add-back of B55α, suggesting a model in which IER5 suppresses a B55α-dependent activity. This was supported by assays performed with IER5/PPP2R2A double knockout cells (Figure 7A), in which expression of the late genes such as KRT1 was also restored (Figure 7D). These results suggest that Notch modulation of B55α-PP2A activity via IER5 is important in regulating the complex series of events downstream of Notch that lead to squamous cell differentiation.

PPP2R2A is epistatic to IER5.

(A) Western blot showing IER5 and B55α protein levels in single (KO) and double (DKO) PPP2R2A and IER5 knockout clones in the presence of GSI (-) and 4 hr after GSI washout (+). (B) PPP2R2A knockout enhances Notch-dependent expression of KRT1. RT-PCR analysis of KRT1 expression in SC2 cells transduced with an empty retrovirus (SC2/EV); PPP2R2A knockout cells (B55 KO) transduced with empty retrovirus (B55KO/EV); and PPP2R2A knockout cells transduced with B55α-expressing retrovirus (B55KO/B55AB). WO = GSI washout. *, p<0.05; **, p<0.005 (two-tailed student t test). (C) Immunohistochemical (IHC) staining for involucrin of SC2 control, B55KO, and B55KO/B55AB cells in raft cultures in GSI-free medium. (D) B55α knockout negates the requirement for IER5 for Notch-dependent upregulation of KRT1. Results are shown for SC2 control cells (SC2/EV); an IER5 knockout clone; a PPP2R2A knockout clone (B55KO); and three IER5/PPP2R2A double knockout (DKO) clones. Cells were maintained in GSI or harvested 72 hr following GSI washout (WO). KRT1 transcript abundance was measured in biological replicates prepared in triplicate by RT-PCR and normalized against GAPDH. Error bars represent standard errors of the mean. *, p<0.05; **, p<0.005; ***, p<0.0005; ****, p<0.00005 (all two-tailed student t test).

Discussion

Our work provides a genome-wide view of the direct effects of Notch in SCC cells, in which Notch activation induces growth arrest and differentiation. The phenotypic changes induced by Notch are mediated by a largely squamous-cell-specific transcriptional program that includes genes linked to keratinocyte differentiation and DNA damage responses, including IER5, which modulates the activity of B55α-containing PP2A complexes. Upregulation of these Notch-responsive genes are associated with binding of NTCs to RBPJ sites within lineage-specific enhancers, including a minority of sequence-paired sites, a specialized dimeric NTC binding element recently implicated in anti-parasite immune responses in mice (Kobia et al., 2020). The Notch target genes and elements identified here in malignant squamous cells are likely to be relevant for understanding Notch function in non-transformed squamous cells, as many of the NTC-binding enhancers found near Notch target genes in SCC cells are also active in normal human keratinocytes (based on review of ENCODE data for non-transformed human keratinocytes). These observations have a number of implications for understanding how Notch regulates the growth and differentiation of squamous cells and highlight the potential for Notch to influence the activity of diverse signaling pathways in keratinocytes through modulation of PP2A.

Prior work has suggested that p53-mediated upregulation of Notch expression and activity is a component of the DNA damage response in keratinocytes (Mandinova et al., 2008). Conversely, our work shows that Notch activation, even in a TP53 mutant background, induces the expression of genes that are components of the keratinocyte DNA damage/cell stress response, suggesting that these two pathways converge on a set of genes that induce the differentiation (and thus, the elimination) of damaged cells. Consistent with this idea, recent work has shown that low-dose radiation induces the differentiation of esophageal squamous cells at the expense of self-renewal in vivo (Fernandez-Antoran et al., 2019). The frequent co-mutation of TP53 and Notch genes in squamous carcinoma may also reflect, at least in part, the convergence of these pathways on a core set of genes with anti-oncogenic activities. Further work delineating the crosstalk between p53 and Notch signaling in well controlled model systems will be needed to test this idea.

Among the genes linked to Notch and p53 is IER5, an immediate early response gene that is a component of the DNA-damage response in a number of cell types (Ding et al., 2009; Kis et al., 2006; Kumar et al., 1998; Yang et al., 2016). Several lines of investigation suggest that IER5 modulates the function of PP2A complexes containing B55 (Asano et al., 2016; Ishikawa et al., 2015; Kawabata et al., 2015) regulatory subunits, and here we demonstrate that IER5 directly binds B55α protein in a purified system. However, the exact effect of IER5 on PP2A function is uncertain. One model suggests that IER5 augments the ability of B55/PP2A complexes to recognize and dephosphorylate specific substrates such as S6 kinase and HSF1 (Ishikawa et al., 2015; Kawabata et al., 2015), the latter leading to HSF1 activation as part of the heat shock response. However, our work with double knockout cells suggests IER5 inhibits at least some activities that are attributable to B55α-containing PP2A complexes. Work in purified systems, which is now feasible, may help to clarify how IER5 influences B55/PP2A function.

We also note that IER3, a putative regulator of B56/PP2A complexes, behaves as a direct Notch target in our SCC model system. Given the pleotropic role of PP2A isoforms and their myriad substrates, it appears likely that Notch-dependent modulation of PP2A regulators such as IER5 and IER3 will alter the activity of many factors that are regulated by serine/threonine phosphorylation. Because IER5 is required for expression of a large number of Notch-sensitive genes with delayed response kinetics, B55α/PP2A complexes are likely to regulate one or more transcription factors that coordinately induce squamous differentiation with Notch, another idea that is readily testable in our model system.

Finally, we note that our small screen of SCC cell lines suggests that squamous cell carcinomas retain the capacity to respond to Notch signals by undergoing growth arrest and differentiation. Although originally identified as an oncogene, sequencing of cancer genomes has revealed that Notch most commonly acts as a tumor suppressor, particularly in squamous cell carcinoma, which is difficult to treat when advanced in stage. While restoring the expression of defective Notch receptors is problematic, detailed analysis of crosstalk between Notch and other pathways may reveal druggable targets leading to reactivation of tumor suppressive signaling nodes downstream of Notch, which would constitute a new rational therapeutic approach for squamous cancers.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
AntibodyRabbit monoclonal anti-MAML1Cell Signaling TechnologyCat. #: 12166ChIP, 1 ml per1 × 106 cells
AntibodyRabbit monoclonal anti-RBPJCell Signaling TechnologyCat. #: 5313ChIP, 2.5 ml per1 × 106 cells
AntibodyRabbit polyclonal anti-histone H3 acetyl K27AbcamCat. #: ab4729ChIP, 9 ml per1 × 106 cells
AntibodyMouse monoclonal anti-involucrinSigmaCat. #: I9018IF, 1:500; IHC, 1:10,000
AntibodyRabbit polyclonal anti-plakophilin-1SigmaCat. #: HPA027221IF, 1:300; IHC, 1:500
AntibodyRabbit monoclonal anti-activated NOTCH1 (ICN1)Cell Signaling TechnologyCat. #: 4147IHC, 1:50; WB, 1:1000
AntibodyRabbit monoclonal anti-keratin-1AbcamCat. #: ab185628IHC, 1:1000
AntibodyRabbit monoclonal anti-Ki-67BiocareCat. #: CRM325IHC, 1:100
AntibodyMouse monoclonal anti-B55aCell Signaling TechnologyCat. #: 5689WB, 1:1000
AntibodyRabbit monoclonal anti-NOTCH2Cell Signaling TechnologyCat. #: 5732WB, 1:1000
AntibodyRabbit monoclonal anti-NOTCH3Cell Signaling TechnologyCat. #: 5276WB, 1:1000
AntibodyRabbit monoclonal anti-GADD45ACell Signaling TechnologyCat. #: 4632WB, 1:1000
AntibodyRabbit monoclonal anti-ID3Cell Signaling TechnologyCat. #: 9837WB, 1:1000
AntibodyHorse polyclonal anti-mouse Ig linked to HRPCell Signaling TechnologyCat. #: 7076WB, 1:1,000-1:20,000
AntibodyGoat polyclonal anti-rabbit Ig linked to HRPCell Signaling TechnologyCat. #: 7074WB, 1:1000
AntibodyMouse monoclonal anti-actinSigmaCat. #: A1978WB, 1:10,000
AntibodyMouse monoclonal anti-FLAGSigmaCat. #: F3165WB, 1:1000
AntibodyRabbit polyclonal anti-IER5SigmaCat. #: HPA029894WB, 1:1000
AntibodyMouse monoclonal anti-filaggrinSanta Cruz BiotechnologyCat. #: sc-66192IHC, 1:100
AntibodyMouse monoclonal anti-p63Biocare MedicalCat. #: CM163AIHC, 1:250
AntibodyRabbit polyclonal anti-loricrinBioLegendCat. #: 905103IHC, 1:800
AntibodyMouse monoclonal anti-BCL6Cell Marque Tissue DiagnosticsCat. #: 227 M-95IHC, 1:500
AntibodyRabbit monoclonal anti-keratin5Cell Signaling TechnologyCat. #: 71536IHC, 1:2000
AntibodyChicken polyclonal anti-keratin14BioLegendCat. #: 906004IHC, 1:800
AntibodyChicken polyclonal anti-SUMOLifesensorsCat. #: AB7002WB, 1:2000
AntibodySheep polyclonal anti-rabbit Ig linked to DynabeadsThermoFisher ScientificCat. #: 11203DChIP, 100 μl beads per 20 × 106 cells
AntibodyMouse monoclonal anti-FLAG epitope linked to magnetic beadsSigmaCat #: M8823Tandem purification,40 μl to 1 ml beads
Cell line (Homo sapiens)IC810.1038/s41467-018-06027-1Dr. Andrew South (Thomas Jefferson University)
Cell line (H. sapiens)SCCT210.1038/s41467-018-06027-1Dr. Andrew South (Thomas Jefferson University)
Cell line (H. sapiens)NOK1Piboonniyom et al., 2003; 63:476–83Dr. Karl Munger (Tufts University)
Commercial assay or kitCellTiter BluePromegaCat. #: G8080
Commercial assay or kitChIP Assay KitMilliporeCat. #: 17–295
Commercial assay or kitNext Ultra II DNA Library Prep KitNew England BioLabsCat. #: E7645
Commercial assay or kitNext Ultra II RNA Library Prep KitNew England BioLabsCat. #: E7775
Commercial assay or kitQuickChange II KitAgilent TechnologiesCat. #: 200523
Commercial assay or kitDual Luciferase KitPromegaCat. #: E1910
Chemical compound, drugCompound ETocrisCat. #: CAS 209986-17-4
Recombinant DNA reagentpL-CRISPR.
SFFV.GFP
AddgeneCat. #: #57827
Recombinant DNA reagentpL-CRISPR.SFFV.tRFPAddgeneCat. #: #57826
Recombinant DNA reagentlentiCRISPRv2 neoAddgeneCat. #: 98292
Recombinant DNA reagentlentiCRISPRv2 hygroAddgeneCat. #: 98291
Recombinant DNA reagentpVL1392Expression SystemsCat. #: 91–012

Cell lines and 2D cultures

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Cells were grown under 5% C02 at 37°C in media supplemented with glutamine and streptomycin/penicillin. IC8 cells (Wang et al., 2011) were cultured in Keratinocyte medium as described (Purdie et al., 2011). ΔEGF-L1596H cDNA cloned into pBABE-puro was packaged into pseudotyped retrovirus and used to transduce IC8 and SCCT2 cells, which were selected with puromycin (1 µg/ml). In some instances, cells were also transduced with pseudotyped MigRI retrovirus encoding dominant negative MAML1 fused to GFP (Weng et al., 2003). Single-cell IC8 cell clones were isolated by limiting dilution. NOK1 cells were grown in keratinocyte-SFM medium supplemented with human EGF and bovine pituitary extract (BPE) (Thermo Fisher Scientific) and induced to differentiate by transfer to Dulbcecco modified Eagle medium (DMEM) containing 10% fetal bovine serum. The identity of IC8 cells and SCCT2 cells was confirmed by detection of cell-line-specific ‘private’ driver mutations (Inman et al., 2018) by NextGen sequencing. The identity of NOK1 cells was confirmed by STR testing (Genetica Cell Line Testing, Case # CX4-007937). Culture cells were tested for mycoplasma periodically using the LookOut Mycoplasma PCR Detection Kit (Millipore Sigma, Cat. #MP0035).

To determine the effect of collagen matrix on ICN1 levels, 5 × 104 cells were plated in the presence of GSI in standard Corning six-well plates or Corning Biocoat Collagen 6-well plates coated with rat tail collagen 1. After 4 days, cells were subjected to GSI washout or sham GSI washout and cultured for an additional 24 hr.

Cell growth assays

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Cell numbers were estimated using CellTiter Blue (Promega) per the manufacturer’s recommendations. Fluorescence was measured using a SpectraMax M3 microplate reader (Molecular Devices).

Organotypic 3D cultures

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3D raft cultures were performed on a matrix containing 5 × 105 J2 3T3 fibroblast cells and rat collagen as described (Arnette et al., 2016). Briefly, rafts were allowed to mature for 6–7 days and then were seeded with 5 × 105 SCC cells in E-medium in the presence of GSI. After 2 days, rafts were raised to the fluid-air interface, and medium was refreshed + / - GSI every 2 days for a total of 12 additional days.

Targeted exon sequencing

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NGS was performed on IC8 and SCCT2 cell genomic DNA using the ‘oncopanel’ assay (Abo et al., 2015; Wagle et al., 2012), which covers 447 cancer genes. Briefly, DNA (200 ng) was enriched with the Agilent SureSelect hybrid capture kit and used for library preparation. Following sequencing (Illumina HiSeq 2500), reads were aligned to human genome GRCh37 (hg19) (Li and Durbin, 2009), sorted, duplicate marked, and indexed. Base-quality score calibration and alignments around indels was done with Genome Analysis Toolkit (DePristo et al., 2011; McKenna et al., 2010). Single-nucleotide variant calls were with MuTect (Cibulskis et al., 2013). Copy number alterations were determined using RobustCNV. Structural variants were detected using BreaKmer (Abo et al., 2015).

Preparation of ChIP-Seq and RNA-seq libraries

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Chromatin was prepared as described (Wang et al., 2014) and was immunoprecipitated with antibodies against MAML1 (clone D3K7B) or RBPJ (clone D10A11, both from Cell Signaling Technology) and Dynabeads bearing sheep anti-rabbit Ig (Thermo Fisher Scientific). H3K27ac ChIPs were prepared using the ChIP assay kit (Millipore) and H2K27ac antibody (ab4729, Abcam). ChIP-seq libraries were constructed using the NEBNext Ultra II DNA Library Prep Kit (New England BioLabs). Total RNA was prepared with Trizol (Life Technology) and RNeasy Mini columns (Qiagen). RNA libraries were constructed using the NEBNext Ultra II RNA Library Prep kit (New England BioLab). ChIP-seq and RNA-seq libraries were sequenced on an Illumina NextSeq 500 instrument. ChIP-seq and RNA-seq data sets are deposited in GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156488).

For Figure 2—figure supplement 1, IC8 cells were seeded at 6 × 105 cells per 10 cm dish. The next morning, media was changed to media containing GSI (Compound E, 1 μM) or an equivalent volume of DMSO. One day after the media change, cells were lifted from the dish with trypsin containing 1 μM GSI or an equivalent volume of DMSO and washed with PBS containing 1 μM GSI or vehicle (DMSO), and 106 cells were pelleted and resuspended in TRIzol (Thermo Fisher). Two biological replicates were collected per condition. RNA Spike-in standards (Invitrogen, 1 μL of 1:10 diluted ERCC) were added to each tube of RNA in TRIzol. Total RNA was extracted by phenol/chloroform with MaXtract tubes (Qiagen). RNA quality was assessed by HS RNA ScreenTape on an Agilent Tape Station. Libraries were constructed using the TruSeq Stranded Total RNA Library Prep Gold kit (Illumina) at the HMS Nascent Transcriptomics Core. Samples were sequenced for paired end reads on the Illumina NovaSeq at the Harvard Bauer Center Sequencing Core, using the S1 Flow Cell and the 100 Cycle Kit. RNA-seq data sets for IC8 cells treated with vehicle or GSI are available at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE156624.

ChIP-seq data analysis

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Reads were trimmed with Trim Galore (v.0.3.7 using cutadapt v.1.8), assessed for quality with FastQC (v.0.11.3), and aligned to GRCh38/hg38 with bowtie (v.2.0.0; Langmead and Salzberg, 2012). Peaks were identified using MACS2 (v.2.1.1; Zhang et al., 2008) and annotated using Homer (v3.12, 6-8-2012; Heinz et al., 2010). Peaks mapping to repeats (repeatMasker track, from UCSC) or ENCODE blacklisted regions were removed. Overlapping RBPJ and MAML1 peaks were identified with bedtools intersectBed (v2.23.0; Quinlan and Hall, 2010). Motif analysis was performed using MEME-ChIP (Machanick and Bailey, 2011). Average signal profiles were generated with ngsplot (Shen et al., 2014). RBPJ sequence-paired sites (SPSs) were identified as described (Severson et al., 2017). Mixed Gaussian curves were generated in R using the mixtools (v.1.1.0) function (Benaglia et al., 2009).

RNA-seq data analysis

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Reads were trimmed as described for DNA reads and aligned to human genome GRCh38/hg38 using gencode release 27 annotations and STAR (v.2.5.3a) (Dobin et al., 2013). Raw counts from two sequencing runs were loaded into R (R Development Core Team, 2014), summed, and filtered to exclude transcripts with <0.5 reads per million mapped before performing differential expression (DE) analysis with edgeR (v.3.16.5) and RUVSeq (v.1.8.0) (Risso et al., 2014). After first-pass DE analysis, a control set of 733 genes with FDR > 0.5 in all pairwise comparisons was used with RUVg (k = 1) to identify unwanted variation. Second-pass edgeR analysis included the RUVg weights in the model matrix. Genes with FDR < 5% and absolute logFC >1 were retained for further analysis. DAVID v.6.8 (Huang da, Huang et al., 2009) was used for gene ontology (GO) enrichment analysis of the DE gene lists. EdgeR cpm function with library size normalization and log2 conversion was used to generate expression values, which were displayed using pheatmap (R package version 1.0.8). Other plots were made using in-house R scripts (available upon request).

For Figure 2—figure supplement 1, sequencing reads were filtered to retain reads with an average quality score ≥20 and were then mapped to hg38 with Ensembl release 99 annotations using Star version 2.7.0 f. (Dobin et al., 2013). Duplicated reads were removed. ERCC spike-in reads were mapped using Bowtie version 1.2.2 (Langmead et al., 2009). The percentage of reads mapping to the spike-in was not significantly different between samples. To identify differentially expressed genes, the featureCounts function (Liao et al., 2014) in Rsubread version 2.0.1 (Liao et al., 2019) was used in R version 3.6.2 to assign reads to Ensembl release 99 gene annotations. Differential gene expression was performed with DESeq2 version 1.26.0 in R (Love et al., 2014), using the size factors calculated by DESeq2 to normalize. The cut-offs used to identify differentially expressed genes were an adjusted p-value<0.0001 and |log2 fold change| > 1.

Quantitative RT-PCR

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Total RNA was isolated using RNAeasy Mini Kit (Qiagen) and cDNA was prepared using an iScript cDNA synthesis kit (BioRad). qPCR was carried out using a CFX384 Real-Time PCR Detection System. Gene expression was normalized to GAPDH using the ΔΔ CT method. Primer sets used are available on request.

In situ hybridization

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In situ hybridization (ISH) reagents were from Advanced Cell Diagnostics. Deidentified normal human skin was obtained from the paraffin archives of the Department of Pathology at Brigham and Women’s Hospital under institutional review board protocol #2014P001256. Briefly, 4μ sections of skin were deparaffinized, processed using RNAscope 2.5 Universal Pretreatment Reagent, and hybridized to probes specific for human IER5, human PPIB (peptidylprolyl isomerase B), or bacterial DapB in a HybEZ II oven. ISH signal was developed using the RNAscope 2.5 HD Assay.

Immunostaining of cells and organotypic rafts

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Antibody sources and antibody dilutions are provided in the Key Resource Table. For indirect immunofluorescence microscopy, cells grown on chamber microscope slides were fixed in 4% paraformaldehyde and treated with immunofluorescence blocking buffer (catalog #12411, Cell Signaling Technology). Staining with primary antibodies against involucrin or plakophilin-1 in antibody dilution buffer (catalog #12378, Cell Signaling Technology) was developed by incubation with Alexa Fluor-conjugated secondary antibodies (Cell Signaling Technology, 1:1000). After counterstaining with DAPI (BioLegend, catalog #422801), slides were coverslipped with ProLong Gold Antifade Reagent (Cell Signaling Technology, catalog #9071) and imaged on a Nikon 80i immunofluorescence microscope. Rafts were fixed in 4% buffered formalin for 24 hr, processed, and paraffin-embedded. Sections (4μ) were placed on Superfrost Plus slides and baked at 60°C for 1 hr. Immunohistochemical staining was performed on a Leica Bond III instrument using the following primary antibodies and Leica antigen retrieval conditions: involucrin, retrieval H1 (30 min); plakophilin1, retrieval H1 (30 min); keratin1, H1 retrieval (30 min); keratin5, retrieval H2 (20 min); keratin14, retrieval H2 (20 min); BCL6, retrieval H2 (20 min); p63, retrieval H2 (40 min); filaggrin, retrieval H1 (30 min); loricrin, retrieval H1 (30 min); Ki67, retrieval H2 (20 min); or ICN1, retrieval H2 (40 min). Diaminobenzidine (DAB) staining was developed using the Bond Polymer Refine Detection Kit (Leica). Slides were counterstained with hematoxylin. Digital micrographs were captured with an Olympus BX40 microscope and Olympus cellSens Entry software.

Reporter gene assays

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Luciferase reporter genes containing IER5-associated enhancers were assembled in pGL3-TATA (Wang et al., 2014). Mutatagenesis was with the QuickChange II kit (Agilent Technologies). Luciferase assays were performed using Dual Luciferase Assay Kit (Promega) as described (Malecki et al., 2006) using lysates from cultured cells that were co-transfected with firefly luciferase and internal control Renilla luciferase plasmids using Lipofactamine 2000 (Thermo Fisher Scientific).

Western blotting and immunoprecipitation

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Antibody sources and dilutions are provided in the Key Resource Table. Whole cell lysates were prepared as described (Malecki et al., 2006). Protein concentration was measured by Bradford assay (Bio-Rad) prior to SDS-PAGE. Western blots staining was developed with Super Signal West Pico Chemiluminescent Substrate (Thermo Scientific). To prepare immunoprecipitates, cells were lysed in 50 mM Tris, pH 7.4, containing 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, and protease inhibitors (Sigma). Lysates were incubated overnight at 4°C with 20 µl anti-FLAG M2 magnetic beads (Sigma). After extensive washing, bound proteins were eluted with FLAG peptide (Sigma) and analyzed on western blots as above.

Affinity purification of IER5 complexes and mass spectrometry

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Mass spectroscopy was performed on tandem affinity purified IER5 complexes prepared from IE5 knockout (I5) cells expressing tandem tagged IER5 48 hr after GSI washout. Lysis of cells and subsequent tandem purification were as described (Adelmant et al., 2019). Tryptic peptides were analyzed by electrospray mass spectrometry (QExactive HF mass spectrometer, Thermo Fisher; Digital PicoView electrospray source platform, New Objective). Spectra were recalibrated using the background ion (Si(CH3)2O)six at m/z 445.12 + / - 0.03 and converted to a Mascot generic file format (.mgf) using multiplierz scripts (Askenazi et al., 2009; Parikh et al., 2009). Spectra were searched using Mascot (v2.6) against three databases: (i) human protein sequences (downloaded from RefSeq); (ii) common lab contaminants; and (iii) a decoy database generated by reversing the sequences from these two databases. Spectra matching peptides from the reverse database were used to calculate a global FDR and were discarded, as were matches to the forward database with FDR > 1.0% and those present in >1% of 108 negative tandem affinity purification controls (Rozenblatt-Rosen et al., 2012).

Recombinant protein expression and purification

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A cDNA encoding B55α with 6xHis-SUMO N-terminal tag was cloned into the baculovirus transfer vector pVL1392. High-titer baculovirus supernatants were used to infect insect Sf9 cells grown at a density of 4.0 × 106 cell/mL. After 72 hr of incubation at 27°C, conditioned media was isolated by centrifugation, supplemented with 20 mM Tris buffer, pH 7.5, containing 150 mM NaCl, 5 mM CaCl2, 1 mM NiCl2, and 0.01 mM ZnCl2, re-centrifuged to remove residual debris, and applied to a Ni-NTA column. After washing with 20 mM Tris buffer, pH 7.5, containing 150 mM NaCl and 5 mMCaCl2, B55α was eluted in the same buffer supplemented with 500 mM imidazole. This eluate was concentrated with a centrifugal filter and then subject to S200 size exclusion chromatography in 20 mM Na cacodylate, pH 6.0, containing 150 mM NaCl, and 5 mM CaCl2. Fractions containing B55α were further purified by ion exchange chromatography on a MonoQ column in 20 mM Na cacodylate, pH 6.0, using a linear NaCl gradient. The purified protein was buffer-exchanged into 20 mM HEPES buffer, pH 7.5, containing 150 mM NaCl, prior to flash freezing and storage at −80°C. A cDNA encoding IER5 with a N-terminal 6xHis-SUMO tag was cloned into pTD6 and used to transform Rosetta E. coli cells. Expression of IER5 was induced at 37°C for 4 hr with IPTG induction followed by inclusion body preparation. Lysates were centrifuged at 4°C for 20 min at 30,000 x g and pellets were resuspended in 10 mL wash buffer (50 mM Tris-HCl, pH 7.5, 150 mM NaCl, containing 1% Triton X-100 and 1M urea) per gram cell weight, and incubated at 23°C for 5 min. Following multiple washes, inclusion bodies were resuspended in extraction buffer (50 mM Tris-HCl, pH 7.5, 8M urea, 1 mM β-mercaptoethanol, 1 mM PMSF) and incubated at room temperature for 1 hr. The solubilized proteins were then dialyzed overnight against a 100-fold volume of wash buffer and cleared by centrifugation. 6x-his-IER5 was then concentrated on Ni-NTA beads, eluted with 500 mM imidazole, cleaved using SUMO protease (SUMOpro, Lifesensors), and passed back over Ni-NTA beads. Untagged IER5 was then purified by chromatography on S200 and MonoQ columns as described for B55α.

IER5/B55α-binding assays

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For bead pulldown assays, 5 μM purified His-SUMO-B55α bait was bound to 100 ul Ni-NTA beads, which were mixed with different concentrations of purified IER5 in 20 mM HEPES buffer, pH 7.5, containing 150 mM NaCl for 1 hr. Control binding assays were conducted with purified His-SUMO bound to Ni-NTA beads. Following extensive washing, proteins were eluted by boiling in SDS-PAGE loading buffer and analyzed on SDS-PAGE gels followed by western blotting. Microscale thermophoresis assays were performed on a NanoTemper Monolith NT.115 instrument with blue/red filters (NanoTemper Technologies GmbH, Munich, Germany). Samples were prepared in 20 mM Tris-HCl, pH 7.5, containing 150 mM NaCl, 1 mM β-mercaptoethanol, 1% glycerol, 0.05% Tween-20, and loaded into premium treated capillaries. Measurements were performed at 22° C using 20% MST power with laser off/on times of 5 s and 30 s, respectively. His-SUMO-B55α target labeled with red fluorescent detector as per the NanoTemper His-labeling kit was used at a concentration of 10 nM and mixed with 16 serial dilutions of purified IER5 ligand from 5 μM to 0.000153 μM. All experiments were repeated three times. Data analyses were performed using NanoTemper analysis software.

CRISPR/Cas9 targeting and site directed mutagenesis

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Guide RNAs (gRNAs) were designed using software available at http://crispr.mit.edu. To score the effects of gene editing in bulk cell populations, gRNAs were cloned into pL-CRISPR.SFFV.GFP and transiently transfected using Lipofactamine 2000 (Thermo Fisher Scientific). Cells sorted for GFP expression 48 hr post-transfection were used in downstream analyses. To create double knockout cells, single-cell clones bearing single-gene knockouts were transduced with pL-CRISPR.SFFV.GFP bearing gRNA. Lentivirus was packaged by co-transfection with psPAX2 and pMD2.G. To create deletions, pairs of gRNAs flanking genomic regions of interest were cloned into lentiCRISPRv2 neo and lentiCRISPRv2 hygro, or into pL-CRISPR.SFFV.GFP and pL-CRISPR.SFFV.RFP. Double deletants were isolated sequentially by selection for RFP/GFP double positivity and G418/hygromycin resistance. The sequences of gRNAs used are available on request.

Data availability

Sequencing data have been deposited in GEO under accession codes GSE156488 and GSE156624.

The following data sets were generated
    1. Pan L
    (2020) NCBI Gene Expression Omnibus
    ID GSE156488. Notch target genes in keratinocytes.
    1. Rogers JM
    (2020) NCBI Gene Expression Omnibus
    ID GSE156624. Gamma-secretase inhibition does not affect gene expression in squamous cell carcinoma cells that do not express Notch1.

References

    1. Bray SJ
    (2016) Notch signalling in context
    Nature Reviews Molecular Cell Biology 17:722–735.
    https://doi.org/10.1038/nrm.2016.94
    1. Fuchs E
    (1995) Keratins and the skin
    Annual Review of Cell and Developmental Biology 11:123–154.
    https://doi.org/10.1146/annurev.cb.11.110195.001011
    1. Piboonniyom SO
    2. Duensing S
    3. Swilling NW
    4. Hasskarl J
    5. Hinds PW
    6. Münger K
    (2003)
    Abrogation of the retinoblastoma tumor suppressor checkpoint during keratinocyte immortalization is not sufficient for induction of centrosome-mediated genomic instability
    Cancer Research 63:476–483.
  1. Report
    1. Pomrey AB
    2. Radtke F
    (2010)
    RhoV, a Potential Notch Target Gene in Murine Skin, Does Not Play an Essential Role in Epidermis Development and Homeostasis
    École Polytechnique Federale De Lausanne, Lausanne.
  2. Software
    1. R Development Core Team
    (2014) R: A language and environment for statistical computing
    R Foundation for Statistical Computing, Vienna, Austria.
    1. Sun X
    2. Artavanis-Tsakonas S
    (1997)
    Secreted forms of DELTA and SERRATE define antagonists of notch signaling in Drosophila
    Development 124:3439–3448.
    1. Varnum-Finney B
    2. Wu L
    3. Yu M
    4. Brashem-Stein C
    5. Staats S
    6. Flowers D
    7. Griffin JD
    8. Bernstein ID
    (2000)
    Immobilization of notch ligand, Delta-1, is required for induction of notch signaling
    Journal of Cell Science 113:4313–4318.

Decision letter

  1. Apurva Sarin
    Reviewing Editor; Institute for Stem Cell Science and Regenerative Medicine, India
  2. Anna Akhmanova
    Senior Editor; Utrecht University, Netherlands
  3. Daniel Schramek
    Reviewer; Mount Sinai Hospital, United States
  4. Freddy Radtke
    Reviewer; Ecole polytechnique fédérale de Lausanne, Switzerland

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

Acceptance summary:

The study combines an elegant approach to control Notch activation in 2D and 3D models of squamous cell differentiation and genome wide analysis of transcriptional programmes, to identify molecules implicated in the DNA damage response and keratinocyte differentiation as downstream targets of Notch signaling. The requirement of a hierarchical signaling cascade, comprising Notch, IER5 (a DNA damage response intermediate) and its association with PP2A, for the regulation of differentiation, is a major insight provided by this work. The study opens new avenues for exploring context dependent signaling of the Notch pathway in other systems.

Decision letter after peer review:

Thank you for submitting your article "IER5, a DNA-damage response gene, is required for Notch-mediated induction of squamous cell differentiation" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Anna Akhmanova as the Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: Daniel Schramek (Reviewer #1); Freddy Radtke (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.

As the editors have judged that your manuscript is of interest, but as described below that additional experiments are required before it is published, 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). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv (if it is not already there) along with this decision letter and a formal designation that the manuscript is "in revision at eLife". Please let us know if you would like to pursue this option. (If your work is more suitable for medRxiv, you will need to post the preprint yourself, as the mechanisms for us to do so are still in development.)

Summary:

In this study, the authors report that Notch signaling in squamous cell carcinomas, induces DNA damage genes, and their implication in keratinocyte differentiation as exemplified by IER5, is novel. The study employs a well-defined model that allows for precise and rapid activation of NOTCH signaling, which is not readily achieved with more conventional methods such as plate-bound ligands. The ChIP seq analysis adds new aspects to how NOTCH regulates differentiation in squamous cells. Overall, the study is interesting, the manuscript is well written and in general the conclusions are justified by the experiments.

Essential revisions:

1) It is unclear why the authors picked IER5 as Notch induced DNA response gene and not any other gene from the family of Notch induced upregulated DNA damage genes. A rationale may be provided.

2) It seems that in the presence of GSI (NOTCH off in all layers), these cells from a stratified epithelium with a basal layer that is negative of differentiation markers (Figure 1F) and suprabasal layers that show pronounced differentiation markers (Figure 1F) but also some proliferating cells (which is a-typical at least in squamous epithelia in vivo). This would indicate that differentiation occurs independent of NOTCH1 (and might be a function of NOTCH2/3). In NOTCH ON conditions (=WO), these cultures still form an epithelial sheet where ICN1 accumulates in the nucleus of suprabasal cells but not in the basal layer. Is this a result of a technical manipulation, or are the cells in contact with the basal lamina down-regulating ICN1 through some post-transcriptional mechanism? From the Materials and methods section, it sounds like that SCC cells where seeded with or without GSI, so 'washout' might be a little misleading. Albeit the highly proliferating nature of the basal layer and absence of ICN1, it seems that these cells at the same time express high levels of differentiation markers such as IVL, PKP1 and Keratin1, which is somehow counterintuitive? So, the major effect of ICN1 in these cultures is the block of proliferation in the suprabasal layers and induction of differentiation markers in the basal (albeit ICN1 negative) layer. An IHC with K5/14, p63, LOR/FLG would explain the observations in light of the known biology of basal versus suprabasal layers and explain/speculate why the basal layer upon WO does not accumulate ICN1, but shows signs of differentiation? K5/K14 staining would further document if the basal layer indeed expresses basal keratinocytes while LOR/FLG will allow assessment of terminal differentiation (which presumably should not overlap with proliferation).

This comment may be addressed including text, clarifying/comparing similarities and differences to epithelial stratification in vivo versus the in vitro system described in this study.

3) The induction of IER5 using an orthogonal approach for NOTCH activation such as EDTA treatment or plate bound ligands and/or short-term NOTCH inhibition in NOTCH1-proficient SCC cells or keratinocytes is critical. This analysis could include RT-PCR for some of newly identified NOTCH targets including IER5 and WB blot for IER5. This will allow the reader to gauge how general the NOTCH targets are over a panel of SCC cells and estimate the level of IER5 transactivation but also expression upon stimulation of endogenous NOTCH1. Figure 5—figure supplement 1A and B strongly suggests that IER5 expression is regulated also by other TF but also potentially post-translationally as the IER5 mRNA levels increase under GSI treatment but the IER5 protein levels do not. This analysis would also give functional insights about the levels of induction of target gene expression.

4) The authors performed ChIP-Seq for RBPJ, MAML1 and H3K27Ac in a system, in which they can express NOTCH1 in a timed control manner. Why have the authors not used antibodies specific for NOTCH1 instead of MAML1? There are several MAML proteins, whereas a ChIP-Seq for NOTCH1 as the authors have done in the past would have been more logical.

5) In Figure 4A ChIP-Seq analysis for RBPJ, MAML and H3K27Ac, within the wider IER5 gene locus is shown. This led to the identification of the putative Notch regulated D and E enhancer. The RBPJ and MAML1 peaks within the D and E region are prominent. Assuming wash out wash out conditions are shown, do these peaks decrease or disappear in the presence of GSI? Are these so called "dynamic" RBPJ sites?

6) The study has successfully identified keratinocyte-specific NOTCH target genes. However, on a global level, it is not entirely clear, which genes are really keratinocyte specifics versus genes that were also found in other systems to be NOTCH targets. As such, a meta-analysis with the few other sets of published NOTCH targets from other systems such as ES cells (Meier-Stiegen et al., 2010 Plos one), myogenic cells (Castel et al., 2013) etc. may be included.

7) To convince the reader that the identified enhancer landscape of the IER5 locus is not a specificity of one particular squamous cell derivative a similar enhancer landscape is shown for non-transformed human keratinocytes (Figure 1—figure supplement 1). The representation is a little odd, the peaks are cut off and could be shown completely.

8) Many graphs lack statistical analysis. For example, CRISPR-mediated deletion of the enhancer region D and E results only in a partial abrogation of NOTCH dependent increase of IER5 transcripts. Is this statistically significant? Similarly, there are no statistics for the luciferase reporter assays (Figure 4B and C) or bar graphs of Figure 5, i.e. in Figure 5—figure supplement 1B, is the Day 1 and Day 5 between DMSO and GSI significantly different?

9) Figure 5F shows apparently a KO of IER5 in NOK1 cells. The band for IER5 is still visible. The KO seems not to be complete. It is at best a knockdown, which is correctly mentioned in the figure legend. Have the authors sequenced the IER locus around the targeting guide RNA? Was only one allele targeted? or is this residual band due to a mixed population of targeted and non-targeted cells.

10) It might be helpful to the inexperienced reader to put PPP2RA2 and B55a in context and to mention that PPP2RA2 is the gene coding for the B55a regulatory subunit of PP2A.

11) Although the experiments showing a direct interaction between IER5 and B55a are convincing, the results of the subsequent genetic experiments, do not give any mechanistic insight to how IER5 might regulate squamous cell differentiation through B55a. This part of the story is somewhat confusing and may be better shown as a supplementary figure, concentrating on the identification of IER5 as DNA damage gene involved in regulating squamous cell differentiation.

https://doi.org/10.7554/eLife.58081.sa1

Author response

Essential revisions:

1) It is unclear why the authors picked IER5 as Notch induced DNA response gene and not any other gene from the family of Notch induced upregulated DNA damage genes. A rationale may be provided.

The decision to pursue IER5 as a target was several-fold: (i) it is a novel Notch target; (ii) it is an example of a DNA-damage response gene that is also regulated by Notch; (iii) based on previously published work, it appeared to represent a point of cross-talk between Notch signaling and PP2A, a regulator of many pathways that rely on phosphorylation for signal transmission. We have added these justifications to the subsection “IER5 is a direct Notch target gene”.

2) It seems that in the presence of GSI (NOTCH off in all layers), these cells from a stratified epithelium with a basal layer that is negative of differentiation markers (Figure 1F) and suprabasal layers that show pronounced differentiation markers (Figure 1F) but also some proliferating cells (which is a-typical at least in squamous epithelia in vivo). This would indicate that differentiation occurs independent of NOTCH1 (and might be a function of NOTCH2/3).

GSI inhibits activation of all four Notch receptors, and as shown later in Figure 5—figure supplement 1, inhibits NOTCH2 and NOTCH3 activation in NOK1 cells; thus, in 3D organotypic cultures when cells are grown at air-fluid interfaces, squamous cells retain some capacity for differentiation that is truly Notch independent (and also p53 independent, since these cells are TP53 null). We speculate that differentiation may be related to exposure of these cells to high O2 tension at the air interface, a condition that is essential to produce epidermis-like growth of normal and transformed keratinocytes in 3D cultures. The mechanism that underlies Notch-independent differentiation of IC8 cells in organotypic cultures is unknown and beyond the scope of the current study. (Parenthetically, our RNA-Seq data show that IC8 cells sharply upregulate NOTCH3 expression in response to GSI washout at 24hr and 72hr of washout, suggesting that as in T-ALL cells, NOTCH3 is a target of NOTCH1 in IC8 cells. By contrast, in IC8 cells NOTCH2 expression did not change significantly at any time point, and NOTCH4 expression was not detectable.)

In NOTCH ON conditions (=WO), these cultures still form an epithelial sheet where ICN1 accumulates in the nucleus of suprabasal cells but not in the basal layer. Is this a result of a technical manipulation, or are the cells in contact with the basal lamina down-regulating ICN1 through some post-transcriptional mechanism?

We also found this observation of great interest, as it suggested that contact of keratinocytes with collagen triggered a signal that destabilized NICD1. Consistent with this idea, in the revised manuscript we show that plating of IC8-DEGF-L1596H cells on collagen (relative to plastic) sharply decreases ICN1 levels without having any effect on total NOTCH1 protein levels. These findings suggest that the organization of IC8-DEGF-L1596H cells into a basal proliferating layer and a suprabasal non-cycling layer stems from a previously unrecognized matrix-dependent effect limits ICN1 accumulation. We show these data in revised Figure 1—figure supplement 1F. Determination of the mechanistic details underlying this effect of matrix clearly merits study but is beyond the scope of the current paper.

From the Materials and methods section, it sounds like that SCC cells where seeded with or without GSI, so 'washout' might be a little misleading.

IC8-DEGF-L1596H cells were indeed plated in the presence of GSI followed by washout or sham washout; the initial description in the Materials and methods was not well worded. We have clarified this point in the Materials and methods section.

Albeit the highly proliferating nature of the basal layer and absence of ICN1, it seems that these cells at the same time express high levels of differentiation markers such as IVL, PKP1 and Keratin1, which is somehow counterintuitive? So, the major effect of ICN1 in these cultures is the block of proliferation in the suprabasal layers and induction of differentiation markers in the basal (albeit ICN1 negative) layer. An IHC with K5/14, p63, LOR/FLG would explain the observations in light of the known biology of basal versus suprabasal layers and explain/speculate why the basal layer upon WO does not accumulate ICN1, but shows signs of differentiation? K5/K14 staining would further document if the basal layer indeed expresses basal keratinocytes while LOR/FLG will allow assessment of terminal differentiation (which presumably should not overlap with proliferation).

This comment may be addressed including text, clarifying/comparing similarities and differences to epithelial stratification in vivo versus the in vitro system described in this study.

In our revised paper, we address these comments as follows.

We agree that plakophilin-1 and involucrin staining is not excluded from the basal ICN-low cell layer in the Notch-on state, and as requested by the reviewers now provide a more extensive comparison of the Notch off and on states in IC8 cell rafts with respect to expression of markers that are commonly used to gauge keratinocyte differentiation. Specifically, we have performed staining for p63, K5, K14, BCL6, and FLG and provide representative images of these markers in Figure 1F and Figure 1—figure supplement 3. Notch activation has little/no effect on p63 transcripts (per RNA-seq data), and consistent with these data, in the rafts there is little change in p63 staining following Notch activation. Results with other makers is mixed. On the one hand, K14 staining becomes more sharply restricted to the basal ICN1-low proliferative cells in the Notch-on state (Figure 1F), and Notch activation increases BCL6 levels, particularly in suprabasal cells (Figure 1—figure supplement 3). On the other hand, K5 staining becomes more diffuse through the full thickness of Notch-on rafts, and there is no evidence of induction of markers of terminal differentiation (FLG; Figure 1—figure supplement 3) in the presence or absence of Notch activation. Thus, Notch activation principally alters markers associated with spinous differentiation (as made clear by subsequent RNA-seq analyses) but does not uniformly suppress markers associated with the basal cell state and cannot “push” cells through to terminally differentiate. Since the purpose of our work was to discover direct Notch target genes that may play a role in Notch-dependent progression of basal cells to the spinous cell state, not to determine if Notch activation is sufficient to normalize differentiation of squamous carcinoma cells, we do not think that these are serious discrepancies, although it does highlight the need to evaluate potential target genes and their functional consequences in other models.

3) The induction of IER5 using an orthogonal approach for NOTCH activation such as EDTA treatment or plate bound ligands and/or short-term NOTCH inhibition in NOTCH1-proficient SCC cells or keratinocytes is critical. This analysis could include RT-PCR for some of newly identified NOTCH targets including IER5 and WB blot for IER5. This will allow the reader to gauge how general the NOTCH targets are over a panel of SCC cells and estimate the level of IER5 transactivation but also expression upon stimulation of endogenous NOTCH1.

We have long thought about how best to acutely activate Notch in order to determine its direct effects in cells of various lineages, and for reasons described below, have come to the conclusion that GSI washout has important advantages over other methods. In past work have used GSI washout to identify direct target genes in T-ALL cells (Weng et al., 2006), triple negative breast cancer cells (Cancer Discov 2014; 4:1154-67), and B cell lymphoma cells (Ryan et al., 2017). To the best of our knowledge, because we have rigorously correlated changes in gene expression with the presence of Notch responsive elements that show dynamic changes following Notch activation, observations made in these well controlled systems have stood the test of time. For example, we were one of the first groups to identify MYC as a key Notch target in T-ALL cells using GSI washout (Weng et al., 2006), and subsequently identified the putative pre-T-cell-specific Notch-sensitive MYC enhancer ~1.9 MB 3’ of MYC, also by doing “dynamic ChIP-Seq” following GSI washout (Wang et al., 2014). In parallel, Adolfo Ferrando’s group did the bold experiment of knocking out this enhancer element and showed that loss of this element produces only two phenotypes in mice: (i) failure of T cell development; and (ii) resistance to Notch-induced T-ALL. Our approach, which identifies both targets and response elements, provides a roadmap for these types of physiologic investigations.

GSI washout coupled with expression of a GSI regulatable form of NOTCH1 to acutely activate Notch is open to two criticisms: (1) the possibility that GSI has off-Notch effects; and (2) that the dose of Notch that is delivered is supraphysiologic and thus may activate target genes that a physiologic dose of Notch would not. With respect to criticism #1, we would like to emphasize the following points. First, although it is certainly true that γ-secretase has many proteolytic targets, we took care to perform RNA-seq on IC8 cells with and without GSI treatment and observed that there were no genes that changed significantly in expression (defined as fold change of 2X and FDR <0.05) following exposure to GSI (Figure 2—figure supplement 1). This fits with the observation that GSI has no effect on the growth or morphology of IC8 cells, even in long term cultures. Second, as an additional new control, we show that the upregulation of IER5 during the differentiation of NOK1 cells is sensitive to DN-MAML, further implicating endogenous Notch signaling in IER5 regulation (revised Figure 4—figure supplement 1). Dominant negative MAML1 (DN-MAML) is a highly specific inhibitor of Notch (Weng et al., 2003; Nam et al., 2006) that acts downstream of γ-secretase. Notably, conditional activation of DN-MAML in mice reproduces a host of Notch loss of function phenotypes, including the development of squamous cell carcinoma (Proweller et al., 2006), and has not been observed to produce any off-Notch phenotypes. Taken together, the rapid response of IER5 to Notch activation (Figure 2E), the identification of Notch-sensitive enhancers flanking IER5 (Figure 4A), the responsiveness of these elements to Notch in reporter gene assays (Figure 4B, C), the abrogation of Notch-responsiveness following partial CRISPR targeting (Figure 4D-F), and the inhibition of IER5 upregulation by endogenous Notch signaling in NOK1 cells make a compelling case for IER5 being a direct Notch target in squamous cells.

By contrast to GSI washout coupled with DN-MAML as an additional control, if one focuses just on the issue of the direct effects of Notch, both EDTA activation of Notch receptors and activation with plated ligand suffer from several limitations. One of the present authors (J.C.A.) was the senior author on the paper that first described EDTA-mediated activation of NOTCH1 and performed many of the experiments in this paper (Rand et al., 2000), and we therefore have a good deal of experience with this approach. In our hands (in unpublished data), all of the Notch activation following EDTA exposure occurs within the first 2-5 minutes of treatment, meaning that this approach generates a relatively small, transient pulse of activated Notch. Shut-off of Notch activation likely stems from chelation of other metals, such as Zn2+, that are required for the activity of metalloproteases such as ADAM10 and ADAM17, which in turn act upstream of γ-secretase during Notch activation. That EDTA washout works at all is probably explained by the high affinity of ADAMs for Zn2+ relative to the weak binding of Ca2+ to the Notch negative regulatory region. Our observations are consistent with those recently published by the Schramek lab, which showed that nuclear NOTCH1 and NOTCH2 appear by 15 minutes following EDTA-treatment of WT murine keratinocytes but then return to near baseline levels by 60 minutes (Supplementary Figures 14 and 15, Loganathan et al., 2020). As a result, only genes that respond rapidly to low levels of activated Notch (and perhaps mainly genes that have low levels of expression prior to EDTA treatment, yielding larger fold changes) will “score” as being responsive in EDTA-treated cells. These limitations may explain why target genes such as Rhov (originally identified in the Radtke lab in experiments in normal murine keratinocytes) failed to score in the experiments done by Loganathan et al. Our past observations also highlight a second confounding aspect of EDTA treatment; it has effects on many cellular processes that depend on divalent metal ions, including adhesion to substrate, that undoubtedly affect gene expression independent of effects on Notch. Of the other possible approaches, in principle plated ligand is superior to GSI washout in terms of specificity but plating of adherent cells on ligand-coated substrate is confounded by the need to apply adherent cells that have been suspended following trypsin-EDTA treatment (which activates Notch); moreover, plated ligand lacks the switch-like behavior of GSI washout, which is essential to be able to tightly correlate changes in gene expression with Notch activation. Also, we would like to again highlight the important observation that in the parental cells lacking the Notch transgene, not a single gene shows a significant change in expression in the GSI treated state, using the criteria of FDR<0.05 and log2 change of >1 (Figure 2—figure supplement 1). This means that all of the changes that we see in gene expression can be confidently attributed, directly or indirectly, to Notch activation.

The second potential problem with our system is Notch dosage, which could be supraphysiologic and could therefore potentially activate target genes that would not respond to physiologic doses of Notch. Several of the authors (Blacklow and Aster) have in past work systemically compared the activity of various Notch mutations in cultured cells and in vivo. The NRR mutation in the Notch transgene, L1596H, is an example a gain of function mutation of a strength that drives a physiologic response to Notch in murine hematopoietic stem cells in vivo (T cell differentiation from bone marrow progenitors) without causing the development of T cell acute lymphoblastic leukemia (Chiang et al., 2008), a phenotype that does require supraphysiologic doses of Notch. We cannot exclude the possibility that the dose of Notch that we have chosen has non-physiologic effects, but by focusing on genes that respond rapidly we have hopefully kept these to a minimum. In the subsection “Establishment of a Conditional Notch-on SCC Model”, we provide the rationale for the choice of mutant and the use of GSI washout as a method for activating Notch.

We also wish to re-emphasize that we have rigorously shown that endogenous Notch signaling is sufficient to induce IER5 in immortalized NOK1 keratinocytes. Although IER5 upregulation in these cells appears to be mediated through NOTCH2 instead of NOTCH1, domain swap experiments in mice have shown that the intracellular domains of these receptors are functionally interchangeable (Liu et al., 2015), and thus all NOTCH1 targets must be regulatable by NOTCH2 as well. In new experiments (Figure 4—figure supplement 1), we show that DN-MAML is a potent inhibitor of IER5 induction via endogenous Notch activation in NOK1 cells, as are other novel targets such as ID3, building additional confidence that the targets that we have focused on are regulated by endogenous, ligand-mediated Notch signaling in keratinocytes.

Figure 5—figure supplement 1A and B strongly suggests that IER5 expression is regulated also by other TF but also potentially post-translationally as the IER5 mRNA levels increase under GSI treatment but the IER5 protein levels do not. This analysis would also give functional insights about the levels of induction of target gene expression.

We agree with the comment that IER5 regulation is likely to be complex, as Notch inhibition under conditions that induce NOK1 cell differentiation tends to have a greater effect on IER5 protein levels than on IER5 transcript levels (now shown in revised Figure 4—figure supplement 1). The complex enhancer landscape surrounding IER5, the known ability of TP53 to induce IER5, and the existence of multiple phosphorylation sites in IER5 (see https://www.phosphosite.org/proteinAction.action?id=5357431&showAllSites=true) suggest that IER5 is likely to be regulated by multiple factors at the transcriptional and post-transcriptional level. We have added a description of this complexity to the subsection “IER5 is a direct Notch target gene”, details of which are beyond the scope of this paper.

4) The authors performed ChIP-Seq for RBPJ, MAML1 and H3K27Ac in a system, in which they can express NOTCH1 in a timed control manner. Why have the authors not used antibodies specific for NOTCH1 instead of MAML1? There are several MAML proteins, whereas a ChIP-Seq for NOTCH1 as the authors have done in the past would have been more logical.

There are several logical reasons why we decided to do ChIP-Seq for MAML1 rather than NOTCH1, as we have done in the past, or other MAMLs. As for the choice of MAML1, RNA-seq data showed that it is the major member of the Mastermind family expressed in IC8 cells (MAML1 log2 read counts per million = 6.66; log2 MAML2 read counts per million = 3.59; MAML3 log2 read counts per million = 0.70). As for not doing ChIP-Seq for NOTCH1, we were driven by the desire to look at complexes containing endogenous Notch transcription complex components (rather than proteins driven from transgenes) and, for the sake of rigor and reproducibility, to perform our analyses with commercial monoclonal antibodies, instead of private polyclonal antibodies [the only NOTCH1 reagent that we have found to produce robust NOTCH1 ChIP-Seq results]. Moreover, given reports of MAML1 participation in transcription complexes other than Notch transcription complexes, we were curious to see if we would detect evidence of such complexes in squamous cells – we did not. We now provide our reasoning in the subsection “Notch target genes are associated with lineage-specific NTC-binding enhancer elements”.

5) In Figure 4A ChIP-Seq analysis for RBPJ, MAML and H3K27Ac, within the wider IER5 gene locus is shown. This led to the identification of the putative Notch regulated D and E enhancer. The RBPJ and MAML1 peaks within the D and E region are prominent. Assuming wash out wash out conditions are shown, do these peaks decrease or disappear in the presence of GSI? Are these so called "dynamic" RBPJ sites?

RBPJ peaks generally do not disappear in the presence of GSI/absence of Notch signals, but as shown in Figure 3C, do on average increase in size in the presence of active Notch. In our experience, the most sensitive measure of “dynamic sites” that are associated with increased transcription of flanking genes is increased H3K27ac, as shown in Figure 4. We now make this point in the subsection “IER5 is a direct Notch target gene”.

6) The study has successfully identified keratinocyte-specific NOTCH target genes. However, on a global level, it is not entirely clear, which genes are really keratinocyte specifics versus genes that were also found in other systems to be NOTCH targets. As such, a meta-analysis with the few other sets of published NOTCH targets from other systems such as ES cells (Meier-Stiegen et al., 2010 Plos one), myogenic cells (Castel et al., 2013) etc. may be included.

The data in the papers listed above were obtained at different time points under different conditions of Notch activation. A more apt comparison is the list of genes that are rapidly and significantly upregulated by Notch activation (defined as FDR<0.05 and log2 fold change >1) via GSI washout. We have compared this list of genes in squamous carcinoma cells, in which Notch behaves as a tumor suppressor, and in the triple negative breast cancer cell line MB157, the mantle cell lymphoma cell line REC1, and the T-cell acute lymphoblastic cell line DND41, all cell contexts in which Notch has oncogenic activities. In new Supplementary file 6 and Figure 2—figure supplement 2, we show that only around 10% of genes that are acutely regulated by Notch in squamous cells overlap with those that are upregulated in triple negative breast cancer cells, and that less than 2% of Notch responsive genes overlap between squamous cells and blood cancer cells. Moreover, across these four cell types, there are no target genes that are shared. These comparisons, now discussed in the subsection “Identification of a squamous cell-specific Notch-induced program of gene expression”, serve to emphasize the remarkable context specificity of Notch effects, which underlie its ability to produce widely varied cellular outcomes in different cell types.

7) To convince the reader that the identified enhancer landscape of the IER5 locus is not a specificity of one particular squamous cell derivative a similar enhancer landscape is shown for non-transformed human keratinocytes (Figure 1—figure supplement 1). The representation is a little odd, the peaks are cut off and could be shown completely.

We now show the tops of the peaks in revised Figure 4—figure supplement 1.

8) Many graphs lack statistical analysis. For example, CRISPR-mediated deletion of the enhancer region D and E results only in a partial abrogation of NOTCH dependent increase of IER5 transcripts. Is this statistically significant? Similarly, there are no statistics for the luciferase reporter assays (Figure 4B and C) or bar graphs of Figure 5, i.e. in Figure 5—figure supplement 1B, is the Day 1 and Day 5 between DMSO and GSI significantly different?

We now provide p-values in all of these figures.

9) Figure 5F shows apparently a KO of IER5 in NOK1 cells. The band for IER5 is still visible. The KO seems not to be complete. It is at best a knockdown, which is correctly mentioned in the figure legend. Have the authors sequenced the IER locus around the targeting guide RNA? Was only one allele targeted? or is this residual band due to a mixed population of targeted and non-targeted cells.

The latter is the case. This is a bulk population of CRISPR targeted cells and there is a subpopulation of cells that is not successfully targeted; hence, although the effect of IER5 targeting is clear, Figure 5F may underestimate the true size of this effect. We now describe this limitation more clearly in the subsection “IER5 is required for “late” Notch-dependent differentiation events in squamous cells” and in the figure legend.

10) It might be helpful to the inexperienced reader to put PPP2RA2 and B55a in context and to mention that PPP2RA2 is the gene coding for the B55a regulatory subunit of PP2A.

We have explained that B55a is encoded by the PPP2RA2 gene in the subsection “IER5 binds B55α/PP2A complexes”.

11) Although the experiments showing a direct interaction between IER5 and B55a are convincing, the results of the subsequent genetic experiments, do not give any mechanistic insight to how IER5 might regulate squamous cell differentiation through B55a. This part of the story is somewhat confusing and may be better shown as a supplementary figure, concentrating on the identification of IER5 as DNA damage gene involved in regulating squamous cell differentiation.

We appreciate the reviewer’s comments, but respectfully disagree about whether the results are confusing. Our data provide additional evidence that the functional effects of IER5 are linked to B55a, and moreover suggest that these effects are mediated through inhibition of B55a/PP2A complexes. Given uncertainty about the effects of IER5 on B55a/PP2A, we would prefer to retain these results as a figure rather than a supplementary figure.

https://doi.org/10.7554/eLife.58081.sa2

Article and author information

Author details

  1. Li Pan

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Contribution
    Investigation, Methodology, Writing - original draft, Writing - review and editing, Responsible for conduct of RNA-seq and ChIP-seq experiments, RT-PCR analyses, Western blot analyses, immunofluorescence microscopy, organotypic cultures
    Competing interests
    No competing interests declared
  2. Madeleine E Lemieux

    Bioinfo, Plantagenet, Canada
    Contribution
    Formal analysis, Methodology, Writing - original draft, Writing - review and editing, Responsible for design of RNA-seq experiments, responsible for statistical and bioinformatic analyses of RNA-Seq and ChIP-Seq experiments and generation of graphic displays of data (e.g., heat maps)
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6355-8691
  3. Tom Thomas

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Contribution
    Investigation, Methodology, Writing - original draft, Writing - review and editing, Responsible for purification of recombinant proteins and conduct of tandem affinity purification and immunoprecipitation studies
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1840-6776
  4. Julia M Rogers

    Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, United States
    Contribution
    Investigation, Writing - original draft, Writing - review and editing, Responsible for conducting RNA-seq experiments studying the effects of GSI on gene expression in parental IC8 cells
    Competing interests
    No competing interests declared
  5. Colin H Lipper

    Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, United States
    Contribution
    Investigation, Methodology, Writing - review and editing, Responsible for microscale thermophoresis experiments
    Competing interests
    No competing interests declared
  6. Winston Lee

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Present address
    Departmentof Pathology, University of Michigan Medical School, Ann Arbor, United States
    Contribution
    Investigation, Methodology, Writing - original draft, Writing - review and editing, Responsible for development of organotypic culture system, optimization of the GSI washout method for adherent cell lines
    Competing interests
    No competing interests declared
  7. Carl Johnson

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Contribution
    Investigation, Writing - original draft, Writing - review and editing, Responsible for western blot analyses, RT-PCR analyses, in situ hybridization studies
    Competing interests
    No competing interests declared
  8. Lynette M Sholl

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Contribution
    Data curation, Writing - original draft, Writing - review and editing, Responsible for curation of targeted exome sequencing data for the IC8 and SCCT2 cell lines
    Competing interests
    No competing interests declared
  9. Andrew P South

    Department of Dermatology and Cutaneous Biology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, United States
    Contribution
    Conceptualization, Data curation, Writing - original draft, Writing - review and editing, Assisted with development of organotypic cultures, provided key cell line reagents
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7650-0835
  10. Jarrod A Marto

    1. Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    2. Departmentof Oncologic Pathology and Blais Proteomics Center, Dana FarberCancer Institute, HarvardMedical School, Boston, United States
    Contribution
    Data curation, Investigation, Methodology, Writing - original draft, Writing - review and editing, Responsible for conduct of tandem mass spectroscopy, curation of data sets to remove non-specific IER5-interacting proteins
    Competing interests
    No competing interests declared
  11. Guillaume O Adelmant

    1. Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    2. Departmentof Oncologic Pathology and Blais Proteomics Center, Dana FarberCancer Institute, HarvardMedical School, Boston, United States
    Contribution
    Data curation, Formal analysis, Methodology, Writing - original draft, Writing - review and editing, Responsible for conduct of tandem mass spectroscopy, curation of data sets to remove non-specific IER5-interacting proteins
    Competing interests
    No competing interests declared
  12. Stephen C Blacklow

    Department of Biological Chemistry and Molecular Pharmacology, Blavatnik Institute, Harvard Medical School, Boston, United States
    Contribution
    Conceptualization, Writing - original draft, Writing - review and editing, Responsible for experimental conceptualization and design
    Competing interests
    SCB is on the SAB for Erasca, Inc, receives sponsored research funding from Novartis and Erasca, Inc, and is a consultant for IFM therapeutics and Ayala Pharmaceuticals.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6904-1981
  13. Jon C Aster

    Department of Pathology, Brigham and Women’s Hospital, and Harvard Medical School, Boston, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Methodology, Writing - original draft, Project administration, Writing - review and editing, Responsible for experimental conceptualization and design, documentation of organotypic culture results by light microscopy
    For correspondence
    jaster@rics.bwh.harvard.edu
    Competing interests
    JCA is a consultant for Ayala Pharmaceuticals and for Cellestia, Inc, There is no conflict of interest with the work described in this manuscript.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1957-9070

Funding

Ludwig Institute for Cancer Research

  • Jon C Aster

National Institutes of Health (R35 CA220340)

  • Stephen C Blacklow

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

Acknowledgements

Funding: JCA is supported by the Harvard Ludwig Institute and the Michael A Gimbrone Chair in Pathology at Brigham and Women’s Hospital and Harvard Medical School. SCB is supported by NIH award R35 CA220340. JMR is a fellow of the Leukemia and Lymphoma Society. Competing interests: SCB is on the SAB for Erasca, Inc, receives sponsored research funding from Novartis and Erasca, Inc, and is a consultant for IFM therapeutics and Ayala Pharmaceuticals. JCA is a consultant for Ayala Pharmaceuticals and Cellestia, Inc Data and materials availability: All genome-wide data sets are available through GEO. Cell lines, primer sequences, gRNA sequences, and other reagents/methodology will be made available on request.

Senior Editor

  1. Anna Akhmanova, Utrecht University, Netherlands

Reviewing Editor

  1. Apurva Sarin, Institute for Stem Cell Science and Regenerative Medicine, India

Reviewers

  1. Daniel Schramek, Mount Sinai Hospital, United States
  2. Freddy Radtke, Ecole polytechnique fédérale de Lausanne, Switzerland

Publication history

  1. Received: April 20, 2020
  2. Accepted: September 15, 2020
  3. Accepted Manuscript published: September 16, 2020 (version 1)
  4. Version of Record published: October 1, 2020 (version 2)

Copyright

© 2020, Pan 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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