1. Biochemistry and Chemical Biology
  2. Cell Biology

METTL3 promotes homologous recombination repair and modulates chemotherapeutic response in breast cancer by regulating the EGF/RAD51 axis

  1. Enjie Li
  2. Mingyue Xia
  3. Yu Du
  4. Kaili Long
  5. Feng Ji
  6. Feiyan Pan
  7. Lingfeng He
  8. Zhigang Hu  Is a corresponding author
  9. Zhigang Guo  Is a corresponding author
  1. Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, China
https://doi.org/10.7554/eLife.75231
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Cite this article
  1. Enjie Li
  2. Mingyue Xia
  3. Yu Du
  4. Kaili Long
  5. Feng Ji
  6. Feiyan Pan
  7. Lingfeng He
  8. Zhigang Hu
  9. Zhigang Guo
(2022)
METTL3 promotes homologous recombination repair and modulates chemotherapeutic response in breast cancer by regulating the EGF/RAD51 axis
eLife 11:e75231.
https://doi.org/10.7554/eLife.75231
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Abstract

Methyltransferase-like 3 (METTL3) and N6-methyladenosine (m6A) are involved in many types of biological and pathological processes, including DNA repair. However, the function and mechanism of METTL3 in DNA repair and chemotherapeutic response remain largely unknown. In present study, we identified that METTL3 participates in the regulation of homologous recombination repair (HR), which further influences chemotherapeutic response in both MCF-7 and MDA-MB-231 breast cancer (BC) cells. Knockdown of METTL3 sensitized these BC cells to Adriamycin (ADR; also named as doxorubicin) treatment and increased accumulation of DNA damage. Mechanically, we demonstrated that inhibition of METTL3 impaired HR efficiency and increased ADR-induced DNA damage by regulating m6A modification of EGF/RAD51 axis. METTL3 promoted EGF expression through m6A modification, which further upregulated RAD51 expression, resulting in enhanced HR activity. We further demonstrated that the m6A ‘reader,’ YTHDC1, bound to the m6A modified EGF transcript and promoted EGF synthesis, which enhanced HR and cell survival during ADR treatment in BC. Our findings reveal a pivotal mechanism of METTL3-mediated HR and chemotherapeutic drug response, which may contribute to cancer therapy.

Editor's evaluation

This paper identified a new mechanism by which N6-methyltransferase METTL3 modulates DNA repair and cellular resistance to DNA damaging chemotherapeutics. The mechanism involves upregulation of epidermal growth factor expression, which in turn regulates expression of RAD51 recombinase resulting in enhanced DNA repair by homologous recombination.

https://doi.org/10.7554/eLife.75231.sa0

Introduction

m6A modification of RNA has been reported to participate in regulating numerous cellular processes in eukaryotes (Wang et al., 2014; Wang et al., 2015; Xiang et al., 2017). METTL3 is a key member of the m6A methyltransferase complex, which also includes co-factors METTL14 and the Wilms tumor 1 associated protein (WTAP) (Liu et al., 2014; Wang et al., 2015). This RNA modification can be recognized by a set of m6A-binding proteins, including YTH domain containing family protein (YTHDF1/2/3), YTH domain containing 1/2 (YTHDC1/2), and insulin like growth factor 2 mRNA binding protein (IGF2BP1/2/3), which serve as m6A ‘readers’ and mediate specific functions of m6A-modified RNA (Deng et al., 2018; Wang et al., 2015). Furthermore, fat mass and obesity-associated protein (FTO) and RNA demethylase, ALKBH5, work as m6A ‘erasers’ to remove m6A modifications from RNA (Deng et al., 2018). Recent studies have indicated that the m6A modification and METTL3 play important roles in the progression and chemotherapy response of various cancers, including BC (Cai et al., 2018; Deng et al., 2018; Pan et al., 2021).

Chemotherapy is used in early-stage BC and locally advanced BC to provide an improved chance for breast-conserving surgery, reduce the risk of recurrence, and increase survival rates (Fisusi and Akala, 2019). The use of adjuvant chemotherapy remains an effective treatment for triple-negative BC and other types of invasive breast cancer (Hennigs et al., 2016). Several chemotherapeutic agents, including ADR, docetaxel, 5-fluorouracil, and cisplatin are used in combination chemotherapy for BC treatment (Fisusi and Akala, 2019). Since 1970s, ADR was considered as the most active chemotherapeutic agent for the treatment of BC, which was used in neoadjuvant chemotherapy or combination therapy (Chan et al., 1999; Fisher et al., 1998; Paridaens et al., 2000). Chemotherapeutic agents, such as ADR, induce apoptosis by causing DNA damage (He et al., 2016; Lu et al., 2020). Targeting the DNA damage response (DDR) may enhance the sensitization of cancer cells to chemotherapeutic drugs (Li et al., 2021; Lu et al., 2020). Moreover, elevated DNA repair activity contributes to the drug resistance of cancer cells treated with chemotherapy (Li et al., 2021; Lu et al., 2020).

Key proteins involved in DNA repair, such as BRCA1, RAD51, and RAD52 in HR, xeroderma pigmentosum group C (XPC) in nucleotide excision repair (NER), and flap endonuclease 1 (FEN1) in base excision repair (BER), influence the susceptibility of various cancers and may be suitable targets in cancer mono- and combination therapy (Ali et al., 2017; Grundy et al., 2020; Hengel et al., 2016; Huang et al., 2016; Li et al., 2021; Lu et al., 2020; Malik et al., 2020; Miki et al., 1994). In addition, mutations in several DDR proteins, such as BRCA1, BRCA2, PALB2, and RAD51 also contribute to hereditary breast and ovarian cancer (Hengel et al., 2017; Li et al., 2021; Lok et al., 2013). Mutations in these proteins incapacitates HR and results in synthetic lethality with inhibition of RAD52 or PARP1, suggesting a novel strategy for treating patients with BRCA1/2/PALB2-mutant tumors (Bryant et al., 2005; Farmer et al., 2005; Lok et al., 2013). However, targeting key DDR proteins to improve sensitization of cancer cells and circumvent cancer cell resistance remain significant challenges to achieving satisfactory therapeutic effects (Li et al., 2021; Pan et al., 2021). Therefore, exploring novel treatment strategies and mechanisms that affect DDR in cancer cells may contribute to improved treatment for these diseases.

Currently, METTL3 and m6A modification have been implicated in DDR (Xiang et al., 2017; Yu et al., 2021b; Zhang et al., 2020). However, the molecular mechanism of METTL3 and m6A modification in DDR, especially in the context of chemotherapeutic drug-induced DDR, remains unexplored. Here, we report that METTL3 is involved in the regulation of HR by regulating the EGF/RAD51 axis. Knockdown of METTL3 sensitizes both MCF-7 (estrogen receptor (ER)-positive BC cell) and MDA-MB-231 (MB-231, triple-negative BC cell) BC cells to ADR, impairs HR, and induces significant DNA damage. Moreover, YTHDC1 was identified as the reader that binds and protects m6A-modified EGF mRNA and regulates DNA repair and the response of BC cells to ADR. Overall, our findings provide insight into the function and mechanism of METTL3 in HR and the chemotherapeutic drug response in BC, and demonstrate the potential of targeting METTL3 as an antitumor treatment.

Results

METTL3 regulates chemotherapeutic response of BC cells

METTL3 has been reported to be involved in the progression of several types of cancers, including BC (Deng et al., 2018; Wang et al., 2020a). We wonder whether METTL3 regulates chemotherapeutic response of BC cells. First, we identified the elevated METTL3 and m6A levels in five types of BC cells, including MCF-7, MB-231, T47D, SKBR3, and BT474 cells (Figure 1—figure supplement 1A, B). Then, we investigated the role of METTL3 in regulating the sensitivity of both MCF-7 and MB-231 cells (ER-positive and triple-negative cells, respectively) to chemotherapeutic drugs with stable METTL3-OV or -KD cell lines (Figure 1—figure supplement 1C, D). Cell viability assays were performed using METTL3-KD and METTL3-OV MCF-7 stable cell lines treated with five first-line chemotherapeutic drugs including 5-FU, cisplatin (DDP), ADR, paclitaxel, and carboplatin. The results indicated that modification of METTL3 expression markedly attenuated the sensitivity of MCF-7 cells to ADR compared with the other drugs (Figure 1A and Figure 1—figure supplement 1E-I; Andreetta et al., 2010). Cell viability assays using METTL3-OV and -KD MB-231 stable cells verified the effect of METTL3 on ADR sensitivity (Figure 1B and Figure 1—figure supplement 1E). These results were further verified in a morphological analysis, which showed that silencing METTL3 enhanced chemotherapeutic drug sensitivity (Figure 1C), whereas overexpression of METTL3 decreased sensitivity in MCF-7 cells (Figure 1—figure supplement 1J). Furthermore, flow cytometry analysis demonstrated that treatment with ADR induced higher apoptosis rates in both METTL3-KD MCF-7 and MB231 cells compared with control cells (Figure 1D and Figure 1—figure supplement 1K). Accordingly, elevated pro-apoptotic Bax and caspase 3 were detected in METTL3-KD BC cells treated with ADR (Figure 1E). We then detected the effect of METTL3 on ADR-sensitivity using a human non-tumorigenic breast epithelial cell line MCF-10A. Our data showed that overexpression of METTL3 attenuated the sensitivity of MCF-10A cells to ADR (Figure 1—figure supplement 1L-N). As expected, silence of METTL3 reduced global m6A levels in MCF-7 and MB-231 BC cells, whereas overexpression of METTL3 increased m6A levels in these cells compared with control cells (Figure 1—figure supplement 1O, P).

Figure 1 with 1 supplement see all
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Knockdown of Methyltransferase-like 3 (METTL3) sensitizes both MCF-7 and MB-231 cells to Adriamycin (ADR).

(A, B) MTT assays were performed to determine the effect of METTL3 on ADR cytotoxicity in MCF-7 or MDA-MB231 cells. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (C) Morphological analysis of MCF-7 with different drug treatments. (D) Annexin V/PI staining and flow cytometry assay of control or METTL3-KD MCF-7 cells with different drug treatments. (E) Western blot (WB) analysis of METTL3, BAX, and Caspase 3 in control or METTL3-KD MCF-7 cells treated with various concentrations of ADR. All statistical data are presented as the mean ± SD. * p<0.05; ** p<0.01; *** p<0.001 (Student’s t-test).

Figure 1—source data 1

Source data for Figure 1E.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig1-data1-v2.zip

METTL3 promotes HR

ADR is normally described as a classic topoisomerase II poison that intercalates into DNA and forms DNA adducts, and subsequently induces DNA double strand breaks (DSBs) (Swift et al., 2006; Yang et al., 2014). We further addressed whether METTL3 was involved in DSB repair and affected ADR-induced DNA damage. To explore the role of METTL3 in the regulation of DNA repair, we treated METTL3-KD or –OV BC cells with ADR and subsequently released the cells into fresh medium lacking ADR and monitored the levels of γ-H2AX (an established marker of DNA damage) over time. Our data showed that knockdown of METTL3 maintained higher γ-H2AX levels in both MCF-7 and MB-231 cells compared with control cells (Figure 2A and B), whereas overexpression of METTL3 resulted in an earlier decline of γ-H2AX compared with control cells (Figure 2—figure supplement 1A, B). We further detected the effect of METTL3 on the regulation of DSB repair that was induced by etoposide (ETO; another inhibitor of topoisomerase II). Accordingly, our data showed that METTL3 promoted the repair of DSB induced by ETO in both MCF-7 and MB-231 cells (Figure 2C and D, Figure 2—figure supplement 1C, D). As showed in our data, the DNA damage was more rapid induced by etoposide than doxorubicin (Figure 2A–D), which was consistent with previous study in lung cancer cell lines (Binaschi et al., 1990). These results may due to a few differences among mechanisms of these two compounds poisoned DNA strands and cells, by which ADR induced cell death by trapping topoisomerase II, formation of ADR-DNA adducts, and generation of free radicals or ceramide production, whereas DNA damage secondary to topoisomerase II inhibition appears to be a major mechanism for etoposide-induced apoptosis (Yang et al., 2014; Yang et al., 2001). Consistently, an increased number of positive nuclei foci of γ-H2AX was detected in both METTL3-KD MCF-7 and MB-231 cells after ADR treatment and then released after 4 hr (Figure 2E), whereas experiments using METTL3-OV MCF-7 and MB-231 cells showed the opposite effects (Figure 2—figure supplement 1E). Since the phosphorylation and foci formation of γ-H2AX was the marker of both DNA damage and DNA replication stress, we also detected another DNA damage marker 53BP1 (tumor-suppressor p53-binding protein 1, a key regulator of DSB repair) foci (Gagou et al., 2010; Wang et al., 2002; Ward and Chen, 2001). Similar results were obtained for the foci of 53BP1 in both MCF-7 and MB-231 cells (Figure 2F and Figure 2—figure supplement 1F). DSBs are primarily repaired by either HR or non-homologous end joining (NHEJ) (Sonoda et al., 2006). Using two well-characterized green fluorescent protein (GFP)-based HR and NHEJ reporter systems, we determined the effect of METTL3 on HR and NHEJ efficiency (Mendez-Dorantes et al., 2020; Tsai et al., 2020). The results showed that overexpression of METTL3 significantly enhanced HR-mediated DSB repair, whereas knockdown of METTL3 decreased efficiency of HR (Figure 2G and H; and Figure 2—figure supplement 1G). No effect of METTL3 was observed on NHEJ-mediated DSB repair (Figure 2—figure supplement 1H, I). This is consistent with previous reports using the HR and NHEJ luciferase reporter system based on crisper-cas9-induced DSBs (Zhang et al., 2020).

Figure 2 with 1 supplement see all
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Knockdown of Methyltransferase-like 3 (METTL3) impairs homologous recombination repair (HR) efficacy.

(A, B) Western blot (WB) assay to determine γ-H2AX levels in control and METTL3-KD MCF-7 cells (A) or MB-231 cells (B) with ADR (0.5 μM) treatment for 1 hr following different recovery times. (C, D) WB to determine γ-H2AX levels in control and METTL3-KD MCF-7 cells (C) or MB-231 cells (D) with ETO (10 μM) treatment for 1 hr following different recovery times. The Quantification of relative WB band are represented as the mean ± SD of three biological repeats. n=3 per group. (E) Immunofluorescence staining of γ-H2AX foci in different labeled cells with ADR treatment for 1 hr following 8 hr of recovery. (F) Immunofluorescence staining of 53BP1 foci in different cells treated same in (E). The quantification of average foci numbers per cells were showed in right panel, 50 cells were calculated in each group. (G) Schematic of GFP-based HR reporter system. (H) The GFP+ frequency of HR-mediated DSB repair in control and METTL3-KD U2OS cells (n=3 per group). ** p<0.01; *** p<0.001 (Student’s t-test).

Figure 2—source data 1

Source data for Figure 2A.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig2-data1-v2.zip
Figure 2—source data 2

Source data for Figure 2B.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig2-data2-v2.zip
Figure 2—source data 3

Source data for Figure 2C.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig2-data3-v2.zip
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Source data for Figure 2D.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig2-data4-v2.zip

EGF is the target of METTL3 and is regulated by m6A modification

A comprehensive assay combined with RNA-seq, MeRIP-qPCR, bioinformatics analysis, and literature retrieval were designed to explore the putative target(s) of METTL3-mediated m6A modification, which is involved in the regulation of both DNA repair and BC sensitivity to ADR (Figure 3A). A total of 98 genes showed significant changes (p<0.05; 42 up-regulated; and 56 down-regulated) in METTL3-ovexpressing MCF-7 cells compared with control MCF-7 cells (Figure 3B). Among these genes, 52 were shown to be modified by m6A in the exonic, 5’UTR, or 3’UTR of mRNA region in the m6A-Atlas, a comprehensive knowledgebase for unraveling the m6A epitranscriptome (Table 1; Tang et al., 2021). Furthermore, literature retrieval identified 8 (Table 2) out of 52 genes that were reported to be involved in the regulation of DNA repair, among which EGF was highlighted because of its role in cancer progression, and DNA repair (Myllynen et al., 2011; Wilson et al., 2009; Yacoub et al., 2003). Next, we verified the expression of EGF regulated by METTL3. The mRNA levels of EGF increased in both METTL3-OV MCF-7 and MDA-MB231 cells compared with control cells (Figure 3C and D), whereas knockdown of METTL3 down-regulated EGF expression (Figure 3—figure supplement 1A, B). WB analysis of whole cell lysates further verified the up-regulation of EGF by METTL3 (Figure 3E and F, and Figure 3—figure supplement 1C, D). Moreover, secreted EGF in the culture supernatants were examined by ELISA. The results indicated increased EGF levels in the medium of METTL3-OV MCF-7 and MB-231 cells (Figure 3G and H), whereas down-regulated EGF was detected in the medium of METTL3-KD cells (Figure 3—figure supplement 1E, F ). Overexpression of METTL3 also enhanced the expression of EGF in MCF-10A cells (Figure 3—figure supplement 1G, H). Furthermore, to validate the m6A modification in EGF mRNA, we performed a methylated RNA immunoprecipitation (meRIP)-qPCR assay using an m6A antibody followed by qPCR for the predicted region of the m6A sites. EGF mRNA exhibited the highest score by the sequence-based RNA adenosine methylation site predictor algorithm (Zhou et al., 2016). Using specific primers designed for the predicted m6A-harboring regions of EGF, the qPCR data showed that overexpression of METTL3 upregulated the m6A modification of EGF mRNA (Figure 3I and Figure 3—figure supplement 1I), whereas knockdown of METTL3 significantly attenuated its m6A levels (Figure 3—figure supplement 1J). Our data indicated that EGF was the target of METTL3 and regulated by METTL3-mediated m6A modification in both BC cell line and non-tumorigenic breast cell line.

Figure 3 with 1 supplement see all
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Screening and Identification of EGF as the targets of Methyltransferase-like 3 (METTL3) in breast cancer (BC).

(A) Schematic of the screening progress of METTL3 targets in BC. (B) Heat map of RNA-seq to identify the genes regulated by METTL3 overexpression. The value presented Log2 (fold change). (C, D) qRT-PCR was performed in METTL3-overexpressing MCF-7 (C) and MB-231 cells (D) to detect EGF expression. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (E, F) Western blot (WB) analysis of EGF expression in METTL3-overexpressing MCF-7 (E) and MB-231 cells (F). (G, H) ELISA assay measuring secreted EGF in the medium of METTL3-overexpressing MCF-7 (G) and MB-231 cells. (H) Data are expressed as the mean ± standard deviation (SD), n=3 per group. (I) MeRIP-qPCR analysis was used to assess the m6A levels of EGF mRNA in METTL3-overexpressing MCF-7 cells. The enrichment of m6A in each group was calculated by m6A-IP/input and IgG-IP/input. Data are expressed as the mean ± standard deviation (SD), n=3 per group. * p<0.05; *** p<0.001 (Student’s t-test).

Figure 3—source data 1

Source data for Figure 3E.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig3-data1-v2.zip
Figure 3—source data 2

Source data for Figure 3F.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig3-data2-v2.zip
Table 1
52 genes were showed to be modified by m6A in the exonic in this study.
KCNG3DLG2SLC12A8PHOSPHO2AQP1ABCC6
RGS4C11orf91GATA3RORCSIRPACOL3A1
ASB9HIST1H3HIFI16KRT17BMF
ST8SIA5FBXO27RASL11ALAMC2BIK
METTL3SLIT2DTX4TMPRSS9SHH
ABCC9AOC3ANK3PLCH2NOMO3
APOECOL27A1KIF27BAIAP3NPIPA5
EGFOCLNENO2FMNL3MST1
IKZF2PI3PCSK1LRP4PMCH
DHRSXVEGFCTNS4PDK4CSF1R
Table 2
Eight genes were showed to be modified by m6A and be involved in DNA repair in this study.
EGFMETTL3DLG2VEGFC
GATA3KRT17IFI16MST1

EGF regulates RAD51 expression and enhances HR activity

The EGF/EGFR signaling pathway has been reported to regulate DSB repair in lung cancer cells following X-irradiation by promoting both the NHEJ and HR pathways (Kriegs et al., 2010; Myllynen et al., 2011). Thus, we wondered whether EGF/EGFR is involved in METTL3-mediated DSB repair in both MCF-7 and MB-231 cells treated with chemotherapeutic agents, such as ADR. First, we evaluated the effect of the EGF/EGFR signaling pathway on DSB repair in these BC cells. MCF-7 and MB-231 cells were treated with ADR or ETO, respectively, and then released for different times with EGF treatment. WB analysis showed that the γ-H2AX levels markedly decreased in both ADR- and ETO-treated cells following EGF treatment, indicating that EGF enhanced DSB repair (Figure 4A–D). Using a GFP-based HR reporter system, we detected the effect of the EGF/EGFR pathway on regulating HR activity. Our data showed that additional EGF enhanced HR activity in the reporter system (Figure 4E), whereas the EGFR inhibitors erlotinib and gefitinib could inhibited the HR activity with lower GFP-positive cells compared to vehicle treatment (Figure 4—figure supplement 1A, B). To explore the molecular mechanism of EGF-mediated HR, we determined whether EGF/EGFR regulated the expression of core genes involved in HR, including BRCA1, BRCA2, CtIP, and RAD51. Our data showed that both EGF and METTL3 exhibited a slight effect on the regulation of BRCA1, BRCA2, and CtIP expression (Figure 4—figure supplement 1C, D). In contrast, the expression of RAD51 was markedly regulated by the EGF/EGFR signaling pathway (Figure 4F and G, and Figure 4—figure supplement 1).

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Additional EGF promotes RAD51 expression and enhances homologous recombination repair (HR) activity.

(A, B) Western blot (WB) assay identified that EGF (10 ng/ml) enhanced DNA repair in MCF-7 (A) and MB-231 cells (B) treated with ADR (0.5 μM) (shown by lower γ-H2AX in EGF treated samples compare to PBS treated samples). (C, D) EGF (10 ng/ml) enhanced DNA repair in MCF-7 (C) and MB-231 cells (D) treated with ETO (10 μM). The Quantification of relative WB band are represented as the mean ± SD of three biological repeats. (E) The GFP+ frequency of HR reporter assay in the treatment with EGF (10 ng/ml for 4 hr) or vehicle. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (F, G) EGF augmented RAD51 mRNA (F) and protein (G) expression in MCF-7 cells. Data are expressed as the mean ± standard deviation (SD), n=2 per group. ** p<0.01 (Student’s t-test).

Figure 4—source data 1

Source data for Figure 4A.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig4-data1-v2.zip
Figure 4—source data 2

Source data for Figure 4B.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig4-data2-v2.zip
Figure 4—source data 3

Source data for Figure 4C.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig4-data3-v2.zip
Figure 4—source data 4

Source data for Figure 4D.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig4-data4-v2.zip
Figure 4—source data 5

Source data for Figure 4G.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig4-data5-v2.zip

METTL3-modification of DNA repair is EGF/ RAD51 dependent

We next explored the effect of EGF/EGFR signaling on METTL3-mediated HR in MCF-7 and MB-231 cells. WB analysis showed that knockdown of METTL3 down-regulated RAD51 expression, which was recovered by EGF treatment in both MCF-7 and MB-231 cells (Figure 5A and B). In contrast, overexpression of METTL3 up-regulated RAD51 expression, which was repressed by the EGFR inhibitors, erlotinib and gefitinib (Figure 5—figure supplement 1A, B ). Both EGF and RAD51 levels were down-regulated in xenograft tissues derived from METTL3-KD MCF-7 cells (Figure 5C). Accordingly, EGF treatment impeded METTL3-KD-mediated repression of DNA repair in both MCF-7 and MB-231 cells (Figure 5D and E). The EGFR inhibitor, erlotinib, repressed DNA repair activities that were up-regulated by overexpression of METTL3 in both BC cells (Figure 5—figure supplement 1C, D). These data indicate that the EGF/EGFR signaling pathway regulates RAD51 expression and participates in METTL3-mediated HR.

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Methyltransferase-like 3 (METTL3) promotes DNA repair via EGF/Rad51 axis.

(A, B) RAD51 protein levels in METTL3-KD MCF-7 (A) and MB-231 (B) cells treated with or without EGF. (C) Immunohistochemistry analysis of the expression of EGF and RAD51 in control and METTL3-KD tumor tissues. (D, E) WB analysis showing that treatment with 10 ng/ml EGF for 8 hr restores DNA repair activity in METTL3-KD MCF-7 (D) and MB-231 (E) cells. (F) WB analysis showing that knocking down RAD51 or EGFR inhibitor Gefitinib (10 nM for 8 hr) treatment in METTL3-OV cells decreases METTL3-enhanced DNA repair activity. The Quantification of relative WB band are represented as the mean ± SD of three biological repeats. (G) Immunofluorescence analysis of co-staining of γ-H2AX and cyclin A in METTL3-OV cells ±RAD51 shRNA or gefitinib (10 nM) during ADR treatment (0.5 μM for 1 hr and recovery for 8 hr without ADR). The quantitative assay is on the right. n=3 per group. (H) Immunofluorescence analysis of cyclin A and RAD51 foci in cells treated the same as in (G). The quantification of average foci numbers per cells were showed in right panel, 50 cells were calculated in each group. ** p<0.01; *** p<0.001 (Student’s t-test).

Figure 5—source data 1

Source data for Figure 5A.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig5-data1-v2.zip
Figure 5—source data 2

Source data for Figure 5B.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig5-data2-v2.zip
Figure 5—source data 3

Source data for Figure 5D.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig5-data3-v2.zip
Figure 5—source data 4

Source data for Figure 5E.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig5-data4-v2.zip
Figure 5—source data 5

Source data for Figure 5F.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig5-data5-v2.zip

We next investigated whether the effects of METTL3 on DNA repair were EGF/RAD51 dependent. We first confirmed the effect of RAD51 on HR activity in GFP-based HR reporter system as showed in Figure 2G. Our data showed that overexpression of RAD51 promoted HR activity, whereas knockdown of RAD51 repressed HR efficiency in the reporter system (Figure 5—figure supplement 1E, F), which were consistent with other current studies (Asan et al., 2019; Ouyang et al., 2021). Then, we knocked down of RAD51 in METTL3-OV MCF-7 cells. The METTL3-OV MCF-7 cells were transfected with shRAD51 (shRNA of RAD51) for 36 hr, then treated with ADR for 1 hr and released for 8 hr with or without gefitinib/erlotinib treatment. Overexpression of METTL3 resulted in elevated DNA repair activity (shown by γ-H2AX down-regulation) which was reversed by treatment with siRAD51 or gefitinib/erlotinib (Figure 5F, and Figure 5—figure supplement 1G). We further detected the γ-H2AX foci and RAD51 foci in different treated cells by immunofluorescence. We stained Cyclin A to represent S/G2 phase cells. Consistently, immunofluorescence analysis showed that the γ-H2AX foci were down-regulated by overexpression of METTL3, which were reversed by treatment with shRAD51 or gefitinib in both cyclin A positive cells and cyclin A negative cells (Figure 5G). The 53BP1 foci showed similar partners to γ-H2AX foci in these different treated cells (Figure 5—figure supplement 1H). The RAD51 foci were also augmented by overexpression of METTL3 and reversed with gefitinib treatment in both cyclin A positive cells and cyclin A negative cells (Figure 5H). Moreover, we detected RAD51 foci in cells with single inhibition of METTL3 by shRNA or single inhibition of EGF/EGFR by gefitinib or double treatments with shMETTL3 and gefitinib. We found that the RAD51 foci decreased to similar levels in cells in these three conditions compared to those in control cells, which indicated an epistatic effect of shMETTL3 and EGF/EGFR inhibition (Figure 5—figure supplement 1I). This epistatic effect was verified by cells survival assay (Figure 5—figure supplement 1J). Furthermore, we detected γ-H2AX levels in the ADR-treated MCF-7 and MB-231 cells with overexpression of METTL3 or EGF or RAD51. Our data showed that overexpression of METTL3/EGF/RAD51 all could alleviate DNA damage (shown by decreased γ-H2AX) in both MCF-7 and MB-231 cells with similar manner (Figure 5—figure supplement 1K, L). These results suggest that METTL3 augments HR in ADR-treated BC cells via the EGF/ RAD51 axis.

YTHDC1 enhances the METTL3/m6A-regulated EGF/Rad51 axis

There are two major families of m6A ‘readers’ that play a specific role in controlling the fate of methylated mRNA including the YTH family and the IGF2BP family (Deng et al., 2018; Wang et al., 2015; Xiao et al., 2016). To elucidate the specific m6A readers of EGF mRNA and to determine the m6A-dependent mechanism of EGF regulation, we performed qPCR assays to screen EGF-related m6A readers. Interestingly, knockdown of YTHDC1, but not other members of the YTH family or the IGF2BP family, down-regulated both EGF and RAD51 in MCF-7 cells (Figure 6A and Figure 6—figure supplement 1A-C). Furthermore, knockdown of YTHDC1 reversed the METTL3-mediated up-regulation of EGF and RAD51 (Figure 6B and C). The potential binding motif of YTHDC1 in EGF mRNA is UGG(m6A)CU, which is the preferentially binding motif of YTHDC1 (Xu et al., 2014). Using RIP-qPCR, we found that the direct interaction between YTHDC1 and EGF transcripts was enhanced in METTL3-OV cells compared with that in control cells (Figure 6D), whereas the interaction between YTHDC1 and EGF transcripts was down-regulated in the condition of shMETTL3 (Figure 6—figure supplement 1D). Furthermore, the YTHDC1 deficiency impaired the outcome of down-regulation of γ-H2AX foci in METTL3-OV MCF-7 cells (Figure 6E). An MTT assay revealed that YTHDC1 depletion rendered MCF-7 cells more sensitive to ADR and reversed METTL3-induced ADR resistance in METTL3-overexpressing cells (Figure 6F). These results were verified by morphological analysis (Figure 6G). Moreover, cell survival assay identified that double knockdown of METTL3 and YTHDC1 enhanced the sensitivity of MCF-7 to ADR, which is similar to those of single knockdown of METTL3 or YTHDC1 (Figure 6—figure supplement 1E). This result indicated an epistatic effect between shMETTL3 and shYTHDC1 on ADR response in MCF-7 cells. Taken together, our results suggest that YTHDC1 functions as an m6A ‘reader’ to enhance EGF mRNA stability and augment HR and cell survival in ADR-treated BC cells.

Figure 6 with 1 supplement see all
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YTHDC1 is the ‘reader’ of the METTL3/m6A-regulated EGF/RAD51 axis.

(A) The expression of EGF in YTHDC1-silenced MCF-7 cells was detected by qRT-PCR. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (B) The mRNA levels of EGF in control or METTL3-OV cells with or without knocking down YTHDC1. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (C) WB assay determining the effect of YTHDC1 knockdown on EGF and RAD51 expression in control and METTL3-OV MCF-7 cells. The Quantification of relative WB band are represented as the mean ± SD of three biological repeats. (D) RIP-qPCR assay showing the enrichment of the EGF transcript in METTL3-OV cells. Data are expressed as the mean ± SD, n=3 per group. (E) Immunofluorescence analysis of γ-H2AX and RAD51 foci in METTL3-OV cells with knocked-down YTHDC1. The quantification of average foci numbers per cell are shown in the right panel, 50 cells were calculated in each group. (F) MTT assays were performed to detect the effect of YTHDC1 knockdown on ADR sensitivity in control and METTL3-OV MCF-7 cells. Data are expressed as the mean ± standard deviation (SD), n=3 per group. (G) Morphological analysis of control or METTL3-OV MCF-7 cells with or without YTHDC1 knockdown. Cells were treated with 0.5 μM ADR for 24 hr. * p<0.05; ** p<0.01; *** p<0.001 (Student’s t-test).

Figure 6—source data 1

Source data for Figure 6C.

https://cdn.elifesciences.org/articles/75231/elife-75231-fig6-data1-v2.zip

Discussion

A deficiency of DNA repair proteins is associated with carcinogenesis and elevated DNA repair activity contributes to drug resistance in cancer (Li et al., 2021; Lu et al., 2020). MELLT3 and its regulated m6A modification have been reported to be involved in DNA repair (Xiang et al., 2017; Zhang et al., 2020). However, the potential mechanism of METTL3 in DNA repair and chemotherapeutic response is poorly defined. In the present study, we demonstrated that m6A RNA methylation levels and METTL3 expression were elevated in five different kinds of BC cells. Biochemical and cell biological analysis revealed that inhibition of METTL3 sensitizes both ER-positive and triple-negative BC cells to ADR treatment with elevated DNA damage. Knockdown of METTL3 impaired HR activity and increased ADR-induced DNA damage through modification of the EGF/RAD51 axis. METTL3 promoted HR through m6A-dependent upregulation of EGF expression, which further augmented RAD51 expression. The m6A ‘reader,’ YTHDC1, bound to the m6A-modified EGF transcript, protected EGF mRNA, and enhanced EGF expression (Figure 7). This result was consistent with other studies showing that YTHDC1 is recruited to sites of DNA damage, bound m6A RNA, and increased the activity of DSB repair (Yu et al., 2021a; Zhang et al., 2020).

Figure 7
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Proposed schematic diagram of the proposed mechanism elucidated in this study.

Methyltransferase-like 3 (METTL3) augments EGF transcript m6A modification, which was recognized by the reader YTHDC1, resulting increase of EGF expression. Elevated EGF promoted RAD51 expression, enhanced homologous recombination repair (HR) efficacy, and modified chemotherapeutic response of cancer cells.

Recently, RNA m6A modification and the core RNA methyltransferase, METTL3, were reported to play an important role in cancer chemotherapy (Deng et al., 2018). METTL3 was implicated in ADR resistance in MCF-7 cells by regulating the miR-221–3 p/HIPK2/Che-1 axis (Pan et al., 2021). Our data further demonstrated that METTL3 knockdown markedly sensitized both MCF-7 and MB-231 cells to ADR. ADR is one of the most effective antitumor agents for BC treatment, although it is limited by severe side effects. Various mechanisms have been proposed to explain ADR-induced cell death, including trapping topoisomerase II, formation of ADR-DNA adducts, and generation of free radicals that increase oxidative stress, which induce DNA damage and result in cell death (Yang et al., 2014). We also showed that a deficiency in METTL3 inhibits DNA repair and increases the accumulation of DNA damage in ADR-treated MCF-7 and MB-231 cells, which further leads to cell death.

A large number of studies have implicated dysfunctional DNA repair proteins, such as BRCA1, RAD51, FEN1, and Polβ, in BC initiation and progression (Li et al., 2021; Lu et al., 2020; Martin et al., 2007; Thacker, 2005; Wang et al., 2019; Wang et al., 2020b; Xia et al., 2021). Elevated DNA repair activity contributes to drug resistance and limits the efficacy of chemotherapeutic agents (Long et al., 2021; Lu et al., 2020). Thus, targeting the DDR key proteins such as BRCA1 and BRCA2 is a potential effective therapeutic strategy for mono- or combination therapy. In 2005, the synthetic lethality between PARP inhibition and BRCA1 or BRCA2 mutation was reported by two independent groups, suggesting a novel strategy for treating patients with BRCA-mutant tumors (Bryant et al., 2005; Farmer et al., 2005; Xia et al., 2021). Inhibition of PAPR1 causes failure of DNA single-stranded breaks repair, finally leading to DSBs in cells. HR-competent cells can repair DSBs for cell survival, whereas in cells with defects caused by mutations in BRCA1 or BRCA2 or other HR-associated proteins, the DNA damage remains unrepaired, causing cell death (Xia et al., 2021). In 2014, PARP inhibitor Olaparib was primary approved by the FDA to treat certain patients with ovarian cancer. The PARP inhibitors are now indicated for the treatment of patients with germline breast cancer susceptibility gene (BRCA) mutated, human epidermal growth factor receptor 2 (HER2)-negative metastatic BC, who have been previously treated with chemotherapy (Arora et al., 2021; Xia et al., 2021). Although PARPi has shown great efficacy, their widespread use is restricted by various factors, including drug resistance and the limited population. In recent years, there have been a number of studies and clinical trials evaluating the use of cytotoxic chemotherapy such as temozolomide, platinum salts, and topoisomerase inhibitors in combination with PARPi, and the evidence suggests that combination therapy may be of considerable use in many types of cancer (Palleschi et al., 2021). RNA m6A modification has been reported to be involved in the regulation of DNA repair. Xiang et al., 2017 reported that METTL3-mediated m6A RNA accumulates at UV-damaged sites in DNA, which further recruits DNA polymerase κ (Pol κ) to damaged sites to facilitate NER and cell survival (Xiang et al., 2017). Zhang et al., reported METTL3-m6A-YTHDC1 mediated HR in U2OS cells exposed to X-rays or treatment with Zeocin (Zhang et al., 2020). Another recent study found that METTL3-METTL14 is active in vitro on double-stranded DNA containing a cyclopyrimidine dimer, and the m6A reader, YTHDC1, is recruited to sites of DNA damage (Yu et al., 2021a). Our data demonstrated that silencing METTL3 inhibited the repair of DSBs induced by ADR. Nevertheless, the molecular mechanism of DNA repair regulation by METTL3/m6A remains undefined.

There are two major pathways to repair DSBs including error-free HR and error-prone NHEJ (Sonoda et al., 2006). Using a GFP-based reporter system, we found that METTL3 regulated HR, but not NHEJ in DSB repair, which is consistent with the study of Zhang et al., 2020. However, Gene Ontology (GO) analysis of METTL3-associated gene expression profiles based on RNA-seq in MCF-7 cells did not identify enriched ‘DNA damage’ or ‘DNA repair’ categories (data not shown). This data is supported by Xiang et al., showing that GO analysis of METTL3-dependent, UV-induced methylated transcripts only identified ‘DNA damage’ as weakly enriched (Xiang et al., 2017). Zhang et al., also reported that METTL3 does not change active RNA polymerase II binding to DNA lesions and has no effect on RNA transcription at DSBs. Another study showed that METTL3 catalyzes m6A modification of FEN1 mRNA, which is recognized and stabilized by IGF2BP2 in hepatocellular carcinoma cells (Pu et al., 2020). However, our RNA-seq data showed no change in FEN1 expression with METTL3 overexpression in MCF-7 cells, suggesting that METTL3-mediated FEN1 expression may be cell specific.

EGF/EGFR signaling is important to many biological processes, such as cell proliferation, cell division, and tissue development. Human cancer tissues express high levels of growth factors and their receptors, such as EGF/EGFR, which exhibit autocrine or paracrine regulation of cancer growth (Knowlden et al., 2003; Mendelsohn and Baselga, 2000; Singh and Harris, 2005). Aberrant activation of EGF/EGFR signaling contributes to cancer proliferation, epithelial-mesenchymal transition, and metastasis (Mendelsohn and Baselga, 2000). Therefore, targeting EGFR by antibodies or small molecule tyrosine kinase inhibitors has been used successfully to treat various malignancies, including BC (Barzegar et al., 2017; Ueno and Zhang, 2011). Based on RNA-seq, MeRIP-qPCR, and the screening strategy, we determined that EGF is regulated in a METTL3-m6A-YTHDC1-dependent manner in MCF-7 and MB-231 cells. Overexpression of METTL3 markedly increased EGF expression and secretion, whereas knockdown of METTL3 resulted in the opposite effect. Moreover, we detected the expression of EGFR in METTL3-OV MCF-7, MB-231, and MCF-10A cells. We found that overexpression of METTL3 enhanced the expression of EGFR in all these cells (Figure 6—figure supplement 1F-H), which is consistent to previous study (Lin et al., 2016). These data indicated METTL3 might have more global effect on EGR-RAD51 axis. We further demonstrated that EGF/EGFR axis plays an important role in METTL3-mediated HR in both ER-positive and triple-negative cells during ADR treatment. Our results are consistent with previous reports showing that EGF/EGFR signaling plays a role in DSB repair (Myllynen et al., 2011). Moreover, dysregulated EGF/EGFR signaling modulates the expression of several genes involved in DNA repair including ERCC1, XRCC1, RAD51, and RAD50 (Kryeziu et al., 2013; Yacoub et al., 2003). Accordingly, we found that EGF/EGFR signaling regulated RAD51 expression in both MCF-7 and MB-231 cells and the regulation of RAD51 expression by METTL3 was EGF-dependent. Furthermore, knockdown of RAD51 or inhibition of EGFR by gefitinib/erlotinib impaired the effect of METTL3 on the up-regulation of DNA repair activity. Although other studies and our RNA-seq data suggest that there may be other factors involved in the regulation of METTL3-mediated DNA repair and response to chemotherapy (Cai et al., 2018; Pan et al., 2021; Wang et al., 2020a). Our experiments demonstrate a role for EGF in the regulation of HR activity and ADR sensitivity in BC.

The m6A modification of EGF mRNA has been detected in human kidney and embryonic stem cells by different groups using m6A-REF-seq (GSE125240) and MAZTER-seq (GSE122961), respectively (Garcia-Campos et al., 2019; Zhang et al., 2019). Our MeRIP-qPCR assay identified that m6A modification of EGF mRNA was augmented in METTL3-expressing MCF-10A, MCF-7, and MB-231 cells compared with that in control cells. The m6A-modified EGF mRNA was recognized and bound by YTHDC1, which further promoted EGF synthesis and secretion. We demonstrated that the regulation of EGF expression by METTL3 was m6A-YTHDC1-dependent and knockdown of YTHDC1 impeded the up-regulation of EGF in METTL3-overexpressing cells, and restored the sensitivity of MCF-7 cells to ADR. Moreover, knockdown of YTHDC1 impeded METTL3-enhanced RAD51 expression and inhibited recruitment of RAD51 to damaged sites. Our data combined with the studies of Zhang et al., and Yu et al., demonstrate that YTHDC1 plays an important role in DNA repair (Yu et al., 2021a; Zhang et al., 2020). Our results further suggest the involvement of YTHDC1 in the regulation of EGF mRNA stability. Although YTHDC1 is primary known as a nuclear m6A reader, which regulates mRNA splicing through the recruitment and modulation of pre-mRNA splicing factors such as SRSF3 (Xiao et al., 2016). Our data suggest that YTHDC1 may contribute to the stability of cytosolic mRNA, including EGF, through m6A. Our hypothesis is supported by previous studies suggesting that YTHDC1 can shuttle between the nucleus and the cytoplasm (Rafalska et al., 2004), to process mature mRNAs, including MAT2A (Shima et al., 2017). Moreover, Roundtree et al., showed that YTHDC1 mediates the export of methylated mRNA from the nucleus to the cytoplasm, resulting in nuclear clearance of mRNAs and accompanying their resulting cytoplasmic abundance (Roundtree et al., 2017). These results suggest multiple processes through which YTHDC1 regulates the processing of mature mRNA, whereas the detailed molecular mechanism warrants further study.

Collectively, we showed an effect of METTL3 on HR via the m6A-YTHDC1-dependent regulation of the EGF/RAD51 axis, and demonstrated a role for METTL3 in the response of BC chemotherapy. Our results suggest that the development of METTL3 inhibitors or targeting its pathway may lead to promising treatments for cancer patients.

Materials and methods

Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (Mus. musculus)BALB/c-Nude (BALB/cNj-Foxn1nu/Gpt)GemPharmatech Co., Ltd., Nanjing, ChinaStrain NO.D000521
Cell line (Homo sapiens)MCF-7National Collection of Authenticated Cell Cultures, Chinese Academy of ScienceCSTR:19375.09.
3101HUMSCSP531
Cell line (Homo sapiens)MDA-MB-231National Collection of Authenticated Cell Cultures, Chinese Academy of ScienceCSTR:19375.09.
3101HUMSCSP5043
Antibodyanti-METTL3 (Mouse monoclonal)ABclonalCat# A19079
RRID: Addgene_101892		WB (1:1000)
Antibodyanti-γ-H2AX (Mouse monoclonal)Cell Signaling TechnologyCat#
80,312 S		WB (1:1000)
IF(1:300)
Antibodyanti-BAX (Rabbit polyclonal)ABclonalCat# A11550
RRID: AB_516294		WB (1:1000)
Antibodyanti-caspase3 (Rabbit polyclonal)ProteintechCat# 19677-I-AP
RRID: AB_590739		WB (1:1000)
Antibodyanti-EGF (Rabbit polyclonal)ProteintechCat# 27141–1-AP
RRID: AB_1066833		WB (1:1000)
Antibodyanti-RAD51
(Rabbit polyclonal)		ProteintechCat# 14961–1-AP
RRID: AB_10706869		WB (1:1000)
IF (1:300)
Antibodyanti-FLAG (Mouse monoclonal)bioworldCat# AP0007MH
RRID：AB_1537400		WB (1:1000)
Antibodyanti-EGFR (Rabbit polyclonal)ABclonalCat# A11577
RRID: AB_442085		WB (1:1000)
Antibodyanti-TBB5 (Mouse monoclonal)AbgentCat# AM1031A
RRID: AB_1554765		WB (1:1000)
Antibodyanti-Cyclin A (Mouse monoclonal)proteintechCat# 66391–1-IgIF(1:300)
Sequence-based reagentMETTL3_FThis paperqPCR primersAAGCTGCACTTCAGACGAAT
Sequence-based reagentMETTL3_RThis paperqPCR primersGGAATCACCTCCGACACTC
Sequence-based reagentEGF_FThis paperqPCR primersTGGATGTGCTTGATAAGCGG
Sequence-based reagentEGF_RThis paperqPCR primersACCATGTCCTTTCCAGTGTGT
Sequence-based reagentRAD51_FThis paperqPCR primersCAACCCATTTCACGGTTAGAGC
Sequence-based reagentRAD51_RThis paperqPCR primersTTCTTTGGCGCATAGGCAACA
Commercial assay or kitHuman EGF ELISA KitSenBeiJia Biological Technology Co.Cat# SBJ-H0212
Chemical compound, drugDoxorubicin (Adriamycin) HClSelleckCat# S1208
CAS No. 25316-40-9
Chemical compound, drugPaclitaxelSelleckCat# S1150
CAS No. 33069-62-4
Chemical compound, drugCisplatinSelleckCat# S1166
CAS No. 15663-27-1
Chemical compound, drug5-Fluorouracil, 5-FUSelleckCat# S1209
CAS No. 51-21-8
Chemical compound, drugRecombinant Human EGFBeyotimeCat# P5552
Chemical compound, drugErlotinibBeyotimeCat# SC0168
Chemical compound, drugGefitinibBeyotimeCat# SC0186
Software, algorithmGraphPad Prism softwareGraphPad Prism (https://graphpad.com)RRID: SCR_015807Version 8.0.0

Plasmid construction

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The oligonucleotide 5′-CAGGAGATCCTAGAGCTATTA-3′ was used for construction of METTL3-KD lentivirus vectors as previously described (Xiang et al., 2017). The lentivirus vectors were constructed and purified by the Corues Biotechnology Company (Nanjing, China). For knockdown of RAD51, YTHDC1 and other ‘readers,’ and the silencing plasmids containing shRNA sequences were constructed based on psilencer3.0-H1. The shRNA sequences are listed in Table 3. All plasmids were verified by sequencing.

Table 3
Sequences of the shRNA used in this study.
Gene nameshRNA sequences
sh-METTL35’-CAGGAGATCCTAGAGCTATTA-3’
sh-RAD515’-GACTGCCAGGATAAAGCTT-3’
sh-YTHDC15’-CCAGAGAGTGAACAAGATAAA-3’
sh-YTHDF15’-GGGGGTTGAGTGTTGCATCTT-3’
sh-YTHDF25’-AAGGCTAAGCAGGTGTTGAAA-3’
sh-YTHDF35’-TAAGTCAAAGAAGACGTATTACTC-3’
sh-YTHDC25’-GCCCACAGATTGGCTTATTTA-3’
sh-IGF2BP15’-TGCTATTCTTCCTAATCTATATC-3’
sh-IGF2BP25’-GTGAAGCTGGAAGCGCATATCTC-3’
sh-IGF2BP35’-CGGTGAATGAACTTCAGAATTCTC-3’

Cell culture and the development of stable cell lines

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MCF-7 and MB-231 were purchased from the National Collection of Authenticated Cell Cultures, Chinese Academy of Science. All cells were authenticated by STR profiling and tested for mycoplasma contamination. Cells were cultured in the recommended medium supplemented with 10% fetal bovine serum (FBS, Invigentech), 1% penicillin, and 1% streptomycin, and incubated in an incubator with 5% CO2 at 37℃. For METTL3-overexpressing (OV) or –knockdown (KD) MCF-7 and MB-231 stable cells, the cells were infected with specific lentivirus vectors for 48 hr and then selected with puromycin for two weeks. All cell lines were confirmed to be negative for mycoplasma contamination.

m6A dot blotting

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Total RNA was isolated using the Trizol method and mRNAs were isolated with the GenElute mRNA Miniprep Kit (Sigma). The concentration and purity of the mRNA were measured using a NanoDrop 2000. The mRNAs were denatured by heating to 95°C for 5 min, followed by chilling on ice. Next, the mRNAs (50∼100 ng) were spotted directly onto a positively-charged nylon membrane (GE Healthcare, USA) and air-dried at room temperature for 5 min. The membrane was then ultraviolet (UV) crosslinked using a Ultraviolet Crosslinker, washed with PBST for 5 min, blocked with 5% nonfat milk in TBST, and then incubated with anti-m6A antibody (A17924, ABclonal) overnight at 4°C. HRP-conjugated anti-rabbit IgG secondary antibody was added to the membrane for 1.5 hr at room temperature with gentle shaking, followed by development with enhanced chemiluminescence. Last, 0.02% methylene blue staining was used to verify that equal amounts of mRNA were spotted onto the membrane.

Drug sensitivity assay

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Cells were seeded into 96-well plates at 3000 cells per well for at least three parallel experiments. 24 hr later, cells were exposed to ADR at increasing concentrations (0, 0.01, 0.05, 0.1, 0.5, and 1 μΜ) for 48 hr; 5-FU at increasing concentrations (0, 0.1, 0.5, 1, 5 μΜ) for 48 hr; carboplatin at increasing concentrations (0, 10, 50, 100, 500 μΜ) for 48 hr; paclitaxel at increasing concentrations (0, 0.01, 0.1, 1 nΜ) for 48 hr; or DDP at increasing concentrations (0, 2, 4, 6, 8 μΜ) for 48 hr. Chemotherapeutic drug-treated cells were incubated with 10 μL 3-(4,5)-dimethylthiazol (-z-y1)–3,5-diphenyltetrazolium bromide (MTT) solution (5 mg/mL, Sigma-Aldrich, St Louis, MO, USA) for 4 hr. The media was replaced with 100 μL dimethyl sulfoxide (DMSO, Sigma-Aldrich) to dissolve the formazan crystals within 10 min. The absorbance of the formazan was read at 450 nm. The relative values were calculated based on the mean of control cells in the absence of ADR, which was showed as 100%. At least three replicates were performed for each drug treatment.

RNA-seq and analysis

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RNA-Seq was performed by oeBiotech Inc (Shanghai, China). For RNA sequencing, purified RNA from METTL3 overexpressing or control cells was used for library construction with the Illumina TruSeq RNA Sample Prep Kit (FC-122–1001) and then sequenced with an Illumina HiSeq 2000. Raw reads were aligned to the human genome, GRCh37/hg19, by Bowtie2. Differentially expressed genes (DEGs) between METTL3-OV and the control samples were identified using the limma-voom method. A heatmap clustered by k-means was used to show DEGs or transcripts. The raw sequencing data were deposited in the Gene Expression Omnibus database (accession to cite for these SRA data: PRJNA743152).

RNA immunoprecipitation (RIP)

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RNA immunoprecipitation (RIP) assays were conducted using the EZ-Magna RIP RNA-Binding Protein Immunoprecipitation Kit Merck Chemicals (Shanghai Co., Ltd). The anti-YTHDC1 antibody for RIP was purchased from Cell Signaling Technology, Inc (# 81,504 S).

m6A-RNA immunoprecipitation (MeRIP) and MeRIP-qPCR

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m6A enrichment followed by qRT-PCR was used to quantify the changes in m6A methylation of the target gene using the Magna MeRIP m6A Kit (Millipore, MA) following the manufacturer’s instructions. Briefly, 5 μg of fragmented mRNA extracted from MCF-7 stable cells was incubated with 5 μg of m6A antibody (A17924, ABclonal). Methylated mRNA was eluted by free m6A from the beads and purified with the GenElute mRNA Miniprep Kit (MRN70, Sigma). One tenth of the fragmented RNA was saved as an input control for standardization. The relevant enrichment of m6A from METTL3 in each sample was analyzed by RT-qPCR.

Immunofluorescence

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For immunofluorescence assays, cells were washed with PBS for three times then fixed with 4% formaldehyde for 10 min at room temperature. After permeabilization with 0.1% Triton X-100 for 10 min, cells were blocked with 3% BSA for 1 hr. Then, cells were incubated with indicated primary antibodies overnight at 4 °C. Following washed with PBST for three times, cells were incubated with fluorescent secondary antibodies for 2 hr at room temperature. Subsequently, cells were stained with DAPI and visualized under a fluorescence microscope (Nikon 80I 10–1500×).

Tumor analysis

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All animal experiments were performed according to the procedures approved by the Laboratory Animal Care Committee at Nanjing Normal University (Permit number IACUC—20210251) and followed National Institutes of Health guide for the care and use of Laboratory animals. Six-to-seven weeks old female nude mice were purchased from GemPharmatech Co., Ltd. (Nanjing, China), and were maintained under specific pathogen-free conditions for subcutaneous inoculation. Cells were trypsinized and resuspended in DMEM at a consistence of 1 × 107 cells/ml. A total of 1 × 106 cells were injected into flank of mice. 27 days after injection, tumors were removed for paraffin-embedded sections.

Immunohistochemistry

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Immunohistochemical staining was performed as previously described (Lu et al., 2020). Briefly, tumor tissues were fixed in 4% polysorbate. Paraffin-embedded sections from tissue specimens were deparaffinized and heated at 100 °C in 10 mM citrate buffer (pH 6.0) for 15 min for antigen retrieval. Slides were incubated with primary antibody at 4 °C overnight, followed by incubation with secondary antibody at room temperature and visualized using a DAB Kit (Bioworld). Then, it was redacted with hematoxylin. The expression levels of target proteins in tissue were examed according to the semiquantitative immunoreactivity score (IRS).

Apoptosis assay

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METTL3-KD or control MCF-7 or MB-231 cells were treated with doxorubicin for 24 hr and replaced with fresh media. After other 24 hr recovery, about 1 × 105 cells per well were collected and stained with both Annexin V and propidium iodide (PI). Apoptosis was analyzed by flow cytometry using the BD FACSverse.

ELISA

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The cell culture media were centrifuged at the speed of 5000 r.p.m for 5 min and supernatant were collected for EGF measurement using commercial kits (SenBeiJia Biological Technology Co., Nanjing, China) according to manufacturer’s instructions.

Statistical analysis

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Statistical analysis was performed with GraphPad Prism 8.0. Statistical significance was determined using a two-tailed Student’s t-test or analysis of variance in the case of comparisons among multiple groups. p<0.05 was considered statistically significant.

Data availability

The raw sequencing data were deposited in the Gene Expression Omnibus database (accession to cite for these SRA data: PRJNA743152).

The following data sets were generated
    1. Enjie L
    2. Zhigang H
    (2021) NCBI BioProject
    ID PRJNA743152. METTL3 Overexpressing MCF-7.
    https://www.ncbi.nlm.nih.gov/bioproject/PRJNA743152

References

    1. Yang XH
    2. Sladek TL
    3. Liu X
    4. Butler BR
    5. Froelich CJ
    6. Thor AD
    (2001)
    Reconstitution of caspase 3 sensitizes MCF-7 breast cancer cells to doxorubicin- and etoposide-induced apoptosis
    Cancer Research 61:348–354.

Decision letter

  1. Maria Spies
    Reviewing Editor; University of Iowa, United States
  2. Kevin Struhl
    Senior Editor; Harvard Medical School, United States
  3. Sarah R Hengel
    Reviewer; University of Pittsburgh School of Medicine, United States

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "METTL3 promotes homologous recombination repair and modulates chemotherapeutic response by regulating the EGF/Rad51 axis" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kevin Struhl as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Sarah R Hengel (Reviewer #1).

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

Essential revisions:

Please respond to the reviewers' critiques. Most importantly, address with the inclusion of necessary experiments.

1) How the cell cycle influences the outcomes of the reporter assays.

2) The effects of the RAD51 overexpression.

3) Monitor ADR resistance in response to METTL3 overexpression.

Additionally, please address all the questions regarding data quantification and analysis

Reviewer #1 (Recommendations for the authors):

1. Throughout the text the authors refer to responses in breast cancer (BC) cells. As different types of breast cancers (ER+, TNBC, HER2, BRCA1/2-/-) have different signaling pathways and genetic factors that play an important role, it is a standard in the field to explicitly list the types of breast cancers one is referring to throughout the text. Please address throughout the entire text and figure legends.

2. Each set of figures should have a concluding statement about the larger conclusion drawn from all the data presented in that figure. Some of the figures have this statement but not all. Please address.

3. There are not limitations on references cited for eLife. For example, several key references for paragraph (line 59-71) are lacking historical references from within the field with regard to chemotherapeutics, doxyrubicin, etc. Please amend.

4. While ADR is a chemical name used, the more well-known name for this compound is doxorubicin. I would suggest that the authors utilize this name throughout the text, but this is just a suggestion.

5. While topoisomerase inhjibitors were once the gold standard-breast cancers are more often readily treated with PARPi (ex Olaparib) in the clinic in the United States. I think it essential for mechanistic understanding of the interplay of historically important chemotherapeutics (doxyrubicin) and current standards are addressed in this manuscript (Olaparib).

6. Throughout the text there are western blots that should be quantified. This will allow the data to be quantitatively described and compared instead of using non-quantitative terms like "increased" etc.

8. Γ H2AX phosphorylation is a global marker of DSBs and stalled forks. The authors failed to note that H2AX phorylation is present and a marker of stalled replications forks.

a. PMID: 11673449, PMID: 20053681, doi:10.1101/gad.2053211, https://doi.org/10.1016/j.cell.2013.10.043 etc.

Reviewer #2 (Recommendations for the authors):

Overall, I found the study and individual experiments underdeveloped, with major points as follows.

1. Throughout the manuscript, cell cycle control should be assessed, which can affect RAD51 foci / HR frequencies. For example (Figure 5G, H), RAD51 foci should be performed with co-staining with either Cyclin A or EdU labeling. Alternatively, examining cell cycle profiles with π / BrdU labeling would be fine. Without such analysis, it is unclear whether all the findings are potentially due to increased proliferation vs. HR proficiency per se.

2. Figure 2/4 concerns

Overall concern: depletion of METTL3 is shown for panels A-F (gammaH2AX dynamics), and METTL3 over-expression for the HR reporter assay. The rationale for not showing data for both manipulations of METTL3 in both end point analysis is unclear.

i) Panels A-D (and Figure 4 A-D), A gammaH2AX time-course is shown only once, but should be repeated and quantified.

ii) Panels E-F. Only one time point of gammaH2AX foci is shown, and untreated cells are also not shown. gammaH2AX foci density can also mark apoptotic cells, and so DNA damage should also be tested with 53BP1 foci; while a single IF representative image is shown in supplemental, this should be quantified.

iii) Panel H (and Figure 4E). The raw GFP+ frequencies should be shown. Normalizing the +METTL3 to 100% is a somewhat confusing way to describe these experiments

3. The significance of elevated RAD51 causing higher HR / more RAD51 foci is underdeveloped. It is unclear whether elevating the levels of RAD51 is actually pro-HR, as the literature is mixed on this point. While the authors perform depletion of RAD51, the appropriate mimic for the +METTL3 or +EGF experiments is over-expression of RAD51. As in point #1, RAD51 levels should be assessed more rigorously with cell cycle phase experiments, and examination of RAD51 cytoplasmic levels.

Reviewer #3 (Recommendations for the authors):

1) Figure 1: in figure 1 A the authors mention that in the absence of ADR the viability is 100%. However, in the later blot panel E, it looks that there is some apoptosis even without the drug, which means that the shRNA is toxic. How were these data normalized? Accordingly, this information should be described in detail in material and methods or in figure legends.

2) Figure-1C: On the top of the images there are numbers but without any other information – For instance which drug is used. This information should be present to help future readers to understand the figure. Also, μm should read uM. I have the same comment for the other panels through all the paper ex:

– Figure S1-J- add the drug used at the top of the figure (1uM of what).

– Supplementary Figure 1L, M: please indicate in the figure the dose used for this experiment.

– Supp figure 2 -E and F, indicate the scale bar.

3) Figure S1-J- The authors should consider to overexpress METTL3 and monitor increase to ADR in MCF-10A. Do you increase m6A of the EGF mRNA and the binding of the reader? Do you increase the expression of the EGF? This should be tested to validate the model.

4) Figure 2-A-B. Therefore, it is difficult to make a conclusion without quantification. Please provide the relative quantification of triplicate experiments. This should be compared with the results of the IF.

5) Supplementary Figure S2E-F, the authors should provide the quantification of these figures.

6) Material and methods: Please provide the list of the antibodies used for this study especially for the IF experiments.

7) Figure 3-D: the heat map is not ready to understand. On top: please clarify the meaning of the group highlighted in red and the group highlighted in blue. Does each column represent replicates? I guess in red is represents METLL3? The scale indicates number but what is the value, is it Log10 or Ln2 scaled?

8) Figure 3I: a control is missing in the figure. What is the signal obtained in the condition of shMETTL3 or siRNA?

9) Figure 4E and Supplementary Figure S4A, B: In the text the authors did not describe what they did in these experiments. What is Gefitinib and erlotinib? We can find this information but only later.

10) Figure 5: What are the results of the epistatic test on the viability in the single and the double shRNA conditions shMETLL3 and shEGF in terms of growth and RAD51 foci?

11) Figure 6D: A control is missing, this interaction should be abrogated in the absence of MELLT3.

12) Figure 6F: A control is missing – what is the phenotype of shMETLL3 and shYTHDC1 double knockdown are their epistatic? They should.

13) Discussion: It has been showed previously that METTL3 Promotes EGF receptors translation in Human Cancer Cells. The authors should monitor the expression of the EGFR receptors. This is likely to also enhance the response of the EGR-RAD51 axis. Once the data obtained, this should be added to the discussion (PMID: 27117702).

https://doi.org/10.7554/eLife.75231.sa1

Author response

Essential revisions:

Please respond to the reviewers' critiques. Most importantly, address with the inclusion of necessary experiments.

1) How the cell cycle influences the outcomes of the reporter assays.

In this study, we identified that METTL3 mediated HR activity and regulated chemotherapeutic response in breast cancer cells. As HR primarily operates in the S and G2 phases of the cell cycle, cell cycle can affect HR frequencies. We also wonder if METTL3-mediated HR is a direct or indirect effect of the change in cell cycle profile. To address this question and per #2 reviewer’s suggestion, we stained Cyclin A to represent S/G2 phase cells and performed the co-staining of γ-H2AX and RAD51 foci with Cyclin A. We showed γ-H2AX were down-regulated by overexpression of METTL3 in both cyclin A positive cells and cyclin A negative cells (new Figure 5G). Furthermore, the RAD51 foci were augmented by overexpression of METTL3 and reversed with treatment of EGFR inhibitor gefitinib in both cyclin A positive cells and cyclin A negative cells (new Figure 5H). In contrast, the RAD51 foci decreased in cells inhibition of METTL3 by shRNA or inhibition of EGF/EGFR by gefitinib in both cyclin A positive cells and cyclin A negative cells (new Figure 5—figure supplement 1I).

2) The effects of the RAD51 overexpression.

To address this question, we overexpressed RAD51 or knocked down this protein in (GFP)-based HR reporter system to detect the effect of RAD51. Our data showed that knockdown of RAD51 repressed HR activity, whereas overexpression of RAD51 promoted HR efficiency (new Figure 5—figure supplement 1E and F), which were consistent with other current studies (Asan, 2019; Ouyang, 2021). Furthermore, we detectedγ-H2AX levels in the condition of overexpressed RAD51 to mimic +METTL3 or +EGF experiment. We found that overexpression of RAD51 could alleviate γ-H2AX levels, which is similar to the effect of overexpression of METTL3 and EGF (new Figure 5—figure supplement 1K, L).

3) Monitor ADR resistance in response to METTL3 overexpression.

To address this question, we overexpressed METTL3 in MCF-10A cells and detected their response to ADR. Using this cell model, we found that overexpression of METTL3 attenuated the sensitivity of MCF-10A cells to ADR (new Figure 1 —figure supplement 1L-N). Moreover, the m6A modification of EGF mRNA was upregulated in METTL3-OV MCF-10A cells, as well as the binding of EGF to YTHDC1 (new Figure 3 —figure supplement 3J).

Additionally, please address all the questions regarding data quantification and analysis

We quantified all WB and IF data as suggested and point-by-point responses to the comments are attached.

Reviewer #1 (Recommendations for the authors):

1. Throughout the text the authors refer to responses in breast cancer (BC) cells. As different types of breast cancers (ER+, TNBC, HER2, BRCA1/2-/-) have different signaling pathways and genetic factors that play an important role, it is a standard in the field to explicitly list the types of breast cancers one is referring to throughout the text. Please address throughout the entire text and figure legends.

In this study, we detected the effect of METTL3 on HR and chemotherapeutic response using both MCF-7 and MDA-MB-231 breast cancer cells. MCF-7 is a human breast cancer cell line with estrogen, progesterone and glucocorticoid receptors. The MCF-7 cell are useful in vitro breast studies because they retained several ideal characteristics particular to mammary epithelium (Camarillo et al., 2014). In contrast, the MDA-MB-231 cell line is ER, PR, and E-cadherin negative, which is a good model of triple-negative breast cancer (Welsh, 2013). We labeled these specific cell lines throughout the text and figure legends in our revised manuscript.

2. Each set of figures should have a concluding statement about the larger conclusion drawn from all the data presented in that figure. Some of the figures have this statement but not all. Please address.

We thank the reviewer for this suggestion. We modified the figure legends of our revised manuscript.

3. There are not limitations on references cited for eLife. For example, several key references for paragraph (line 59-71) are lacking historical references from within the field with regard to chemotherapeutics, doxyrubicin, etc. Please amend.

Thanks for this critique. We added some description and references in the revised version.

4. While ADR is a chemical name used, the more well-known name for this compound is doxorubicin. I would suggest that the authors utilize this name throughout the text, but this is just a suggestion.

Indeed, doxorubicin is the well-known name in the clinical treatment. As we most focus on the effect of ADR on HR and chemotherapeutic response of BC cells, we keep the name ADR in our text. We also indicated another name of ADR is doxorubicin in the revised abstract.

5. While topoisomerase inhibitors were once the gold standard-breast cancers are more often readily treated with PARPi (ex Olaparib) in the clinic in the United States. I think it essential for mechanistic understanding of the interplay of historically important chemotherapeutics (doxyrubicin) and current standards are addressed in this manuscript (Olaparib).

Doxorubicin was the first line chemotherapeutic agent for BC chemotherapy. Various mechanisms have been proposed to explain ADR-induced cell death, including trapping topoisomerase II, formation of ADR-DNA adducts, and generation of free radicals that increase oxidative stress, which induce DNA damage and result in cell death (Yang, 2014).

Targeting the DNA damage response (DDR) key proteins such as BRCA1 and BRCA2 is an effective therapeutic strategy for mono- or combination therapy. In 2005, two groups described the synthetic lethality (SL) interaction between PARP inhibition and BRCA1 or BRCA2 mutation, suggesting a novel strategy for treating patients with BRCA-mutant tumors (Farmer, 2005; Bryant, 2005; Xia, 2021). PARP inhibitors, originally used as chemo or radiosensitizing agents, are effective in the treatment of homologous recombination repair (HRR)-defective tumors. The PARP inhibitor, Olaparib was primary approved by the FDA in 2014 to treat certain patients with ovarian cancer and is now indicated for the treatment of patients with germline breast cancer susceptibility gene (BRCA) mutated, human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer, who have been previously treated with chemotherapy (Arora, 2021; Xia, 2021). Although PARPi has shown great efficacy, their widespread use is restricted by various factors, including drug resistance and the limited population. In recent years there have been a number of studies and clinical trials evaluating the use of cytotoxic chemotherapy such as temozolomide,platinum salts, and topoisomerase inhibitors in combination with PARPi, and the evidence suggests that combination therapy may be of considerable use in many types of cancer (Palleschi, 2021). In the revised version we added a description in the Discussion section.

6. Throughout the text there are western blots that should be quantified. This will allow the data to be quantitatively described and compared instead of using non-quantitative terms like "increased" etc.

We thank the comments from the reviewer. We quantified the densities of Western blotting bands and added the data in the revised figures.

8. Γ H2AX phosphorylation is a global marker of DSBs and stalled forks. The authors failed to note that H2AX phorylation is present and a marker of stalled replications forks.

a. PMID: 11673449, PMID: 20053681, doi:10.1101/gad.2053211, https://doi.org/10.1016/j.cell.2013.10.043 etc.

We agree with the Reviewer. Γ H2AX is the marker of both DNA damage and DNA replication stress. We apologize that we didn’t mention this in our initial manuscript, and we added the description in the revised version. We also detected and added another DNA damage marker 53BP1 foci in the revised Figure 2F to identify the effect of METTL3 in DNA damage response. In addition, we stained Cyclin A to represent S/G2 phase cells and we showed that γ-H2AX foci decreased in both cyclin A positive cells and cyclin A negative cells with overexpression of METTL3 (new Figure 5G).

Reviewer #2 (Recommendations for the authors):

Overall, I found the study and individual experiments underdeveloped, with major points as follows.

1. Throughout the manuscript, cell cycle control should be assessed, which can affect RAD51 foci / HR frequencies. For example (Figure 5G, H), RAD51 foci should be performed with co-staining with either Cyclin A or EdU labeling. Alternatively, examining cell cycle profiles with π / BrdU labeling would be fine. Without such analysis, it is unclear whether all the findings are potentially due to increased proliferation vs. HR proficiency per se.

We thank the reviewer for this important comment. As HR primarily operates in the S and G2 phases of the cell cycle, cell cycle can affect RAD51 foci / HR frequencies. Per the reviewer’s suggestion, we performed the co-staining of γ-H2AX and RAD51 foci with Cyclin A. The γ-H2AX foci were down-regulated by overexpression of METTL3, which were reversed by treatment with siRAD51 or EGFR inhibitors in both cyclin A positive cells and cyclin A negative cells (Figure 5G). Consistently, we also found that RAD51 foci were augmented by overexpression of METTL3 and reversed with treatment of EGFR inhibitor gefitinib in both cyclin A positive cells and cyclin A negative cells (new Figure 5H). In contrast, we found that the RAD51 foci decreased in cells inhibition of METTL3 by shRNA or inhibition of EGF/EGFR by gefitinib in both cyclin A positive cells and cyclin A negative cells (Figure 5—figure supplement 1I). We added these data in the revised version.

2. Figure 2/4 concerns

Overall concern: depletion of METTL3 is shown for panels A-F (gammaH2AX dynamics), and METTL3 over-expression for the HR reporter assay. The rationale for not showing data for both manipulations of METTL3 in both end point analysis is unclear.

Thanks for this comment. We detected the γ-H2AX levels in condition of both depletion of METTL3 and overexpression of METTL3 (as showed in Figure 2A-D and Figure 2—figure supplement 1A-D). Per the reviewer’s suggestion, we detected the HR activity with knockdown of METTL3 for HR reporter assay in revised Figure 2H. We found that overexpression of METTL3 enhanced HR activity, whereas knockdown of METTL3 decreased efficiency of HR (new Figure 2H; and Figure 2—figure supplement 1G).

i) Panels A-D (and Figure 4 A-D), A gammaH2AX time-course is shown only once, but should be repeated and quantified.

The experiments were repeated for three time and the typical images were selected to show in figures. As per the reviewer’s suggestion, the percentage of positive cell with γ-H2AX foci were quantified and presented in the new Figure 2A-D and Figure 4A-D.

ii) Panels E-F. Only one time point of gammaH2AX foci is shown, and untreated cells are also not shown. gammaH2AX foci density can also mark apoptotic cells, and so DNA damage should also be tested with 53BP1 foci; while a single IF representative image is shown in supplemental, this should be quantified.

We thank the reviewer for these suggestions. We agree that the γ-H2AX was not only a DNA damage marker. Per the reviewer’s suggestion, we tested the 53BP1 foci in the same condition of γ-H2AX detection (new Figure 2F). We also quantified all IF figures and added the data in the revised figures.

iii) Panel H (and Figure 4E). The raw GFP+ frequencies should be shown. Normalizing the +METTL3 to 100% is a somewhat confusing way to describe these experiments

As per the reviewer’s suggestion, we re-organized the data of HR reporter and quantified the data of the GFP signal following Dr Jeremy Stark's lab (Tsai 2020; Mendez-Dorantes, 2020).

3. The significance of elevated RAD51 causing higher HR / more RAD51 foci is underdeveloped. It is unclear whether elevating the levels of RAD51 is actually pro-HR, as the literature is mixed on this point. While the authors perform depletion of RAD51, the appropriate mimic for the +METTL3 or +EGF experiments is over-expression of RAD51. As in point #1, RAD51 levels should be assessed more rigorously with cell cycle phase experiments, and examination of RAD51 cytoplasmic levels.

We appreciate these comments and thank the reviewer for his/her good suggestion. Per the reviewer’s suggestion, we overexpressed and knocked down of RAD51 in (GFP)-based HR reporter system. We found that overexpression of RAD51 promoted HR activity, whereas knockdown of RAD51 repressed HR activity (Figure 5—figure supplement 1E, F), which were consistent with other current studies (Asan, 2019; Ouyang, 2021). Furthermore, we detectedγ-H2AX levels in the condition of overexpressed RAD51 following the reviewer’s suggestion to mimic +METTL3 or +EGF experiment. We found that overexpression of RAD51 could alleviate γ-H2AX levels, which are equal to the effect of overexpression of METTL3 and EGF (Figure 5—figure supplement 1K, L). We added all these supplementary data in revised version.

Reviewer #3 (Recommendations for the authors):

1) Figure 1: in figure 1 A the authors mention that in the absence of ADR the viability is 100%. However, in the later blot panel E, it looks that there is some apoptosis even without the drug, which means that the shRNA is toxic. How were these data normalized? Accordingly, this information should be described in detail in material and methods or in figure legends.

We thank these comments from the reviewer. We measured the cell survival by MTT assays and calculated the relative value based on the mean of cells in the absence of ADR, which was showed as 100% (Figure 1A, B). For apoptosis analysis in Figure 1E, the cells with different treatments were collected and stained with both Annexin V and propidium iodide (PI). Then, the apoptosis was analyzed normally by flow cytometry using the BD FACSverse. We have added the data normalization in the revised “Drug sensitivity assay” method.

2) Figure-1C: On the top of the images there are numbers but without any other information – For instance which drug is used. This information should be present to help future readers to understand the figure. Also, μm should read uM. I have the same comment for the other panels through all the paper ex:

– Figure S1-J- add the drug used at the top of the figure (1uM of what).

– Supplementary Figure 1L, M: please indicate in the figure the dose used for this experiment.

– Supp figure 2 -E and F, indicate the scale bar.

Thanks for these suggestions. All these figures were updated as suggested. For ‘Supplementary Figure 1L, M’, the ADR dose and treatment were showed in revised figure legends of new Figure 1 —figure supplement 1O and P.

3) Figure S1-J- The authors should consider to overexpress METTL3 and monitor increase to ADR in MCF-10A. Do you increase m6A of the EGF mRNA and the binding of the reader? Do you increase the expression of the EGF? This should be tested to validate the model.

These are important suggestions. Per the reviewer’s suggestions, we overexpressed METTL3 in MCF-10A cells and detected their response to ADR. Using this cell model, we confirmed that overexpression of METTL3 attenuated the sensitivity of MCF-10A cells to ADR (new Figure 1 —figure supplement 1L-N). Consistently, the m6A modification of EGF mRNA was upregulated in METTL3-overexpressing MCF-10A cells, as well as the binding of the reader (new Figure 3 —figure supplement 3J). We also found that overexpression of METTL3 promoted the expression of EGF in MCF-10A cells (new Figure3 —figure supplement 3G, H). Our supplementary data confirmed the effect of METTL3 on EGF expression and ADR response in MCF-10A cell model.

4) Figure 2-A-B. Therefore, it is difficult to make a conclusion without quantification. Please provide the relative quantification of triplicate experiments. This should be compared with the results of the IF.

As per the reviewer’s suggestion, we quantified the Western blotting band in the revised Figure 2 as well as in other figures.

5) Supplementary Figure S2E-F, the authors should provide the quantification of these figures.

We provided the quantification in these revised figures.

6) Material and methods: Please provide the list of the antibodies used for this study especially for the IF experiments.

We provided the antibodies list in the Key resources table.

7) Figure 3-D: the heat map is not ready to understand. On top: please clarify the meaning of the group highlighted in red and the group highlighted in blue. Does each column represent replicates? I guess in red is represents METLL3? The scale indicates number but what is the value, is it Log10 or Ln2 scaled?

We apologize for making this confusion. Yes, the red represents METTL3. We have modified this panel as suggested. The scale indicates the value of log2 (fold change) and we add the description in the revised figure legend of Figure 3.

8) Figure 3I: a control is missing in the figure. What is the signal obtained in the condition of shMETTL3 or siRNA?

We thank the reviewer for this critique. Per the reviewer’s suggestion, we detected the Me-RIP-qPCR of EGF in the condition of shMETTL3. While overexpression of METTL3 upregulated the m6A modification of EGF mRNA, knockdown of METTL3 significantly attenuated its m6A levels (new Figure 3 —figure supplement 1J).

9) Figure 4E and Supplementary Figure S4A, B: In the text the authors did not describe what they did in these experiments. What is Gefitinib and erlotinib? We can find this information but only later.

We apologize for making this confusion. We added some description of the experiments about Figure 4E and Supplementary Figure S4a, b. In these experiments, we tried to detect the effect of the EGF on regulating HR activity using a GFP-based HR reporter system as showed in Figure 2G. We added additional EGF (Figure 4E) or EGFR inhibitor Gefitinib and erlotinib (Supplementary Figure S4A, B) in the Reporter system, and showed that EGF promoted HR, whereas EGFR inhibitor repressed HR, showing by increased or reduced GFP-positive cells.

10) Figure 5: What are the results of the epistatic test on the viability in the single and the double shRNA conditions shMETLL3 and shEGF in terms of growth and RAD51 foci?

We appreciate these comments. We detected RAD51 foci and cell survival in cells with single inhibition of METTL3 by shRNA or inhibition of EGF/EGFR by gefitinib or double treatments with shMETTL3 and gefitinib. We found that the RAD51 foci decreased to similar levels in these three conditions, which indicated an epistatic effect of shMETTL3 and EGF/EGFR inhibition. This epistatic effect was verified by cells survival assay (Figure 5—figure supplement 1I, J). We added these data in the revised manuscript.

11) Figure 6D: A control is missing, this interaction should be abrogated in the absence of MELLT3.

As per the reviewer’s suggestion, we detected the EGF mRNA binding of reader in the cells with knockdown of METTL3. Indeed, our RIP-qPCR experiments showed that down-regulation of METTL3 markedly suppressed the binding of EGF mRNA to YTHDC1 (new Figure 6—figure supplement 1D). We added these data in the revised manuscript.

12) Figure 6F: A control is missing – what is the phenotype of shMETLL3 and shYTHDC1 double knockdown are their epistatic? They should.

As per the reviewer’s suggestion, we tested the cell survival in cells with double knockdown of METTL3 and YTHDC1. We found that cells showed similar sensitivity to ADR treatment in the condition of shYTHDC1 and shMETTL3, as well as in the condition of double knockdown of METTL3 and YTHDC1 (new Figure 6—figure supplement 1E).

13) Discussion: It has been showed previously that METTL3 Promotes EGF receptors translation in Human Cancer Cells. The authors should monitor the expression of the EGFR receptors. This is likely to also enhance the response of the EGR-RAD51 axis. Once the data obtained, this should be added to the discussion (PMID: 27117702).

As per the reviewer’s suggestion, we detected the expression of EGFR in METTL3-OV MCF-7, MB-231 and MCF-10A cells. We found that overexpression of METTL3 also enhanced the expression of EGFR (new Figure 6—figure supplement 1F-H), which is consistent to the data reported by Lin et al. (Lin, 2016). These data indicated METTL3 might has more global effect on EGR-RAD51 axis. We added a discussion in the revised version.

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Arora S, Balasubramaniam S, Zhang H, et al. FDA Approval Summary: Olaparib Monotherapy or in Combination with Bevacizumab for the Maintenance Treatment of Patients with Advanced Ovarian Cancer. Oncologist. 2021;26(1):e164-e172.

Binaschi M, Capranico G, De Isabella P, Mariani M, Supino R, Tinelli S, Zunino F. Comparison of DNA cleavage induced by etoposide and doxorubicin in two human small-cell lung cancer lines with different sensitivities to topoisomerase II inhibitors. Int J Cancer. 1990 Feb 15;45(2):347-52

Bryant HE, Schultz N, Thomas HD, Parker KM, Flower D, Lopez E, Kyle S, Meuth M, Curtin NJ, Helleday T. Specific killing of BRCA2-deficient tumours with inhibitors of poly(ADP-ribose) polymerase. Nature. 2005 Apr 14;434(7035):913-7.

Camarillo I G , Xiao F , Madhivanan S , et al. Low and high voltage electrochemotherapy for breast cancer: an in vitro model study. Electroporation-Based Therapies for Cancer, 2014:55-102.

Farmer H, McCabe N, Lord CJ, Tutt AN, Johnson DA, Richardson TB, Santarosa M, Dillon KJ, Hickson I, Knights C, Martin NM, Jackson SP, Smith GC, Ashworth A. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature. 2005 Apr 14;434(7035):917-21.

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Mendez-Dorantes C, Tsai LJ, Jahanshir E, Lopezcolorado FW, Stark JM. BLM has Contrary Effects on Repeat-Mediated Deletions, based on the Distance of DNA DSBs to a Repeat and Repeat Divergence. Cell Rep. 2020 Feb 4;30(5):1342-1357.e4.

Ouyang J, Yadav T, Zhang JM, Yang H, Rheinbay E, Guo H, Haber DA, Lan L, Zou L. RNA transcripts stimulate homologous recombination by forming DR-loops. Nature. 2021 Jun;594(7862):283-288. doi: 10.1038/s41586-021-03538-8.

Palleschi M, Tedaldi G, Sirico M, Virga A, Ulivi P, De Giorgi U. Moving beyond PARP Inhibition: Current State and Future Perspectives in Breast Cancer. Int J Mol Sci. 2021 Jul 23;22(15):7884

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https://doi.org/10.7554/eLife.75231.sa2

Article and author information

Author details

  1. Enjie Li

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Data curation, Formal analysis, Investigation, Methodology, Resources, Visualization, Writing - original draft
    Contributed equally with
    Mingyue Xia and Yu Du
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1113-4384

  2. Mingyue Xia

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Conceptualization, Data curation, Methodology, Visualization
    Contributed equally with
    Enjie Li and Yu Du
    Competing interests
    No competing interests declared

  3. Yu Du

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Data curation, Formal analysis, Investigation, Validation, Visualization
    Contributed equally with
    Enjie Li and Mingyue Xia
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1847-0743

  4. Kaili Long

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Data curation, Formal analysis, Methodology, Visualization, Writing - review and editing
    Competing interests
    No competing interests declared

  5. Feng Ji

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Methodology, Validation, Visualization
    Competing interests
    No competing interests declared

  6. Feiyan Pan

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Methodology, Resources, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3990-618X

  7. Lingfeng He

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Methodology, Resources, Writing - review and editing
    Competing interests
    No competing interests declared

  8. Zhigang Hu

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing - original draft, Writing - review and editing
    For correspondence
    huzg_2000@126.com
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5265-3535

  9. Zhigang Guo

    Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, China
    Contribution
    Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Writing - review and editing
    For correspondence
    guo@njnu.edu.cn
    Competing interests
    No competing interests declared

Funding

National Natural Science Foundation of China (32171407)

  • Zhigang Hu

National Natural Science Foundation of China (81872284)

  • Zhigang Guo

Natural Science Fund of Colleges and Universities in Jiangsu Province (19KJA180010)

  • Zhigang Hu

Priority Academic Program Development of Jiangsu Higher Education Institutions

  • Zhigang Guo

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

Ethics

All animal experiments were performed according to the procedures approved by the Laboratory Animal Care Committee at Nanjing Normal University (Permit number IACUC-20210251) and followed National Institutes of Health guide for the care and use of Laboratory animals.

Senior Editor

  1. Kevin Struhl, Harvard Medical School, United States

Reviewing Editor

  1. Maria Spies, University of Iowa, United States

Reviewer

  1. Sarah R Hengel, University of Pittsburgh School of Medicine, United States

Publication history

  1. Received: November 3, 2021
  2. Preprint posted: November 12, 2021 (view preprint)
  3. Accepted: April 29, 2022
  4. Accepted Manuscript published: May 3, 2022 (version 1)
  5. Version of Record published: May 11, 2022 (version 2)

Copyright

© 2022, Li et al.

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

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  1. Enjie Li
  2. Mingyue Xia
  3. Yu Du
  4. Kaili Long
  5. Feng Ji
  6. Feiyan Pan
  7. Lingfeng He
  8. Zhigang Hu
  9. Zhigang Guo
(2022)
METTL3 promotes homologous recombination repair and modulates chemotherapeutic response in breast cancer by regulating the EGF/RAD51 axis
eLife 11:e75231.
https://doi.org/10.7554/eLife.75231

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