Abstract
Background
Triple-negative breast cancer (TNBC) is resistant to targeted therapy with HER2 monoclonal antibodies and endocrine therapy, because it lacks the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC is a subtype of breast cancer with the worst prognosis and the highest mortality rate compared to other subtypes. N6-methyladenosine (m6A) modification is significant in cancer and metastasis, because it can alter gene expression and function at numerous levels, such as RNA splicing, stability, translocation, and translation. There are limited investigations into the connection between TNBC and m6A.
Materials and methods
Breast cancer-related data were retrieved from the Cancer Genome Atlas (TCGA) database, and 116 triple-negative breast cancer cases were identified from the data. The GSE31519 data set, which included 68 cases of TNBC, was obtained from the Gene Expression Omnibus (GEO) database. Survival analysis was used to determine the prognosis of distinct m6A types based on their m6A group, gene group, and m6A score. To investigate the potential mechanism, GO and KEGG analyses were performed on the differentially expressed genes.
Results
The expression of m6A-related genes and their impact on prognosis in TNBC patients were studied. According to the findings, m6A was crucial in determining the prognosis of TNBC patients, and the major m6A-linked genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. YTHDF2, RBM15B and IGFBP3 are associated with poor prognosis, while WTAP is associated with good prognosis. By cluster analysis, the gene cluster and the m6A cluster were beneficial in predicting the prognosis of TNBC patients. The m6A score based on m6A and gene clusters was more effective in predicting the prognosis of TNBC patients. Furthermore, the tumor microenvironment may play an important role in the process of m6A, influencing TNBC prognosis.
Conclusions
N6-adenylic acid methylation (m6A) was important in altering the prognosis of TNBC patients, and the key m6A-associated genes in this process were YTHDF2, RBM15B, IGFBP3, and WTAP. Furthermore, the comprehensive typing based on m6A and gene clusters was useful in predicting TNBC patients' prognosis, showing potential as valuable evaluating tools for TNBC.
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References
Accornero F, Ross RL, Alfonzo JD (2020) From canonical to modified nucleotides: balancing translation and metabolism. Crit Rev Biochem Mol Biol 55(6):525–540. https://doi.org/10.1080/10409238.2020.1818685
Auer F, Hammoud Z, Ishkin A, Pratt D, Ideker T, Kramer F (2018) ndexr-an R package to interface with the network data exchange. Bioinformatics 34(4):716–717. https://doi.org/10.1093/bioinformatics/btx683
Carrera-Lasfuentes P, Lanas A, Bujanda L, Strunk M, Quintero E, Santolaria S, Benito R, Sopeña F, Piazuelo E, Thomson C, Pérez-Aisa A, Nicolás-Pérez D, Hijona E, Espinel J, Campo R, Manzano M, Geijo F, Pellise M, Zaballa M, González-Huix F, Espinós J, Titó L, Barranco L, D’Amato M, García-González MA (2017) Relevance of DNA repair gene polymorphisms to gastric cancer risk and phenotype. Oncotarget 8(22):35848–35862. https://doi.org/10.18632/oncotarget.16261
Chang G, Shi L, Ye Y, Shi H, Zeng L, Tiwary S, Huse JT, Huo L, Ma L, Ma Y, Zhang S, Zhu J, Xie V, Li P, Han L, He C, Huang S (2020) YTHDF3 induces the translation of m(6)A-enriched gene transcripts to promote breast cancer brain metastasis. Cancer Cell 38(6):857–871. https://doi.org/10.1016/j.ccell.2020.10.004
Chen M, Wong CM (2020) The emerging roles of N6-methyladenosine (m6A) deregulation in liver carcinogenesis. Mol Cancer 19(1):44. https://doi.org/10.1186/s12943-020-01172-y
Chen L, Zhang YH, Lu G, Huang T, Cai YD (2017) Analysis of cancer-related lncRNAs using gene ontology and KEGG pathways. Artif Intell Med 76:27–36. https://doi.org/10.1016/j.artmed.2017.02.001
Cui ZJ, Zhou XH, Zhang HY (2019) DNA methylation module network-based prognosis and molecular typing of cancer. Genes (basel) 10(8):571. https://doi.org/10.3390/genes10080571
de Silva HC, Lin MZ, Phillips L, Martin JL, Baxter RC (2019) IGFBP-3 interacts with NONO and SFPQ in PARP-dependent DNA damage repair in triple-negative breast cancer. Cell Mol Life Sci 76(10):2015–2030. https://doi.org/10.1007/s00018-019-03033-4
Dixit D, Prager BC, Gimple RC, Poh HX, Wang Y, Wu Q, Qiu Z, Kidwell RL, Kim L, Xie Q, Vitting-Seerup K, Bhargava S, Dong Z, Jiang L, Zhu Z, Hamerlik P, Jaffrey SR, Zhao JC, Wang X, Rich JN (2021) The RNA m6A reader YTHDF2 maintains oncogene expression and is a targetable dependency in glioblastoma stem cells. Cancer Discov 11(2):480–499. https://doi.org/10.1158/2159-8290.CD-20-0331
Einstein JM, Perelis M, Chaim IA, Meena JK, Nussbacher JK, Tankka AT, Yee BA, Li H, Madrigal AA, Neill NJ, Shankar A, Tyagi S, Westbrook TF, Yeo GW (2021) Inhibition of YTHDF2 triggers proteotoxic cell death in MYC-driven breast cancer. Mol Cell 81(15):3048–3064. https://doi.org/10.1016/j.molcel.2021.06.014
Fan X, Wang Y, Jiang T, Cai W, Jin Y, Niu Y, Zhu H, Bu Y (2018) B-Myb mediates proliferation and migration of non-small-cell lung cancer via suppressing IGFBP3. Int J Mol Sci 19(5):1479. https://doi.org/10.3390/ijms19051479
Fang R, Chen X, Zhang S, Shi H, Ye Y, Shi H, Zou Z, Li P, Guo Q, Ma L, He C, Huang S (2021) EGFR/SRC/ERK-stabilized YTHDF2 promotes cholesterol dysregulation and invasive growth of glioblastoma. Nat Commun 12(1):177. https://doi.org/10.1038/s41467-020-20379-7
Funakoshi Y, Wang Y, Semba T, Masuda H, Hout D, Ueno NT, Wang X (2019) Comparison of molecular profile in triple-negative inflammatory and non-inflammatory breast cancer not of mesenchymal stem-like subtype. PLoS ONE 14(9):e222336. https://doi.org/10.1371/journal.pone.0222336
Gabani P, Merfeld E, Srivastava AJ, Weiner AA, Ochoa LL, Mullen D, Thomas MA, Margenthaler JA, Cyr AE, Peterson LL, Naughton MJ, Ma C, Zoberi I (2019) Predictors of locoregional recurrence after failure to achieve pathologic complete response to neoadjuvant chemotherapy in triple-negative breast cancer. J Natl Compr Canc Netw 17(4):348–356. https://doi.org/10.6004/jnccn.2018.7103
Guan K, Liu X, Li J, Ding Y, Li J, Cui G, Cui X, Sun R (2020) Expression status and prognostic value of M6A-associated genes in gastric cancer. J Cancer 11(10):3027–3040. https://doi.org/10.7150/jca.40866
Guo X, Li K, Jiang W, Hu Y, Xiao W, Huang Y, Feng Y, Pan Q, Wan R (2020) RNA demethylase ALKBH5 prevents pancreatic cancer progression by posttranscriptional activation of PER1 in an m6A-YTHDF2-dependent manner. Mol Cancer 19(1):91. https://doi.org/10.1186/s12943-020-01158-w
He L, Li H, Wu A, Peng Y, Shu G, Yin G (2019) Functions of N6-methyladenosine and its role in cancer. Mol Cancer 18(1):176. https://doi.org/10.1186/s12943-019-1109-9
Julovi SM, Martin JL, Baxter RC (2018) Nuclear insulin-like growth factor binding protein-3 as a biomarker in triple-negative breast cancer xenograft tumors: effect of targeted therapy and comparison with chemotherapy. Front Endocrinol (lausanne) 9:120. https://doi.org/10.3389/fendo.2018.00120
Liu L, Bai X, Wang J, Tang XR, Wu DH, Du SS, Du XJ, Zhang YW, Zhu HB, Fang Y, Guo ZQ, Zeng Q, Guo XJ, Liu Z, Dong ZY (2019a) Combination of TMB and CNA stratifies prognostic and predictive responses to immunotherapy across metastatic cancer. Clin Cancer Res 25(24):7413–7423. https://doi.org/10.1158/1078-0432.CCR-19-0558
Liu X, Liu L, Dong Z, Li J, Yu Y, Chen X, Ren F, Cui G, Sun R (2019b) Expression patterns and prognostic value of m(6)A-related genes in colorectal cancer. Am J Transl Res 11(7):3972–3991
Loyer P, Busson A, Trembley JH, Hyle J, Grenet J, Zhao W, Ribault C, Montier T, Kidd VJ, Lahti JM (2011) The RNA binding motif protein 15B (RBM15B/OTT3) is a functional competitor of serine-arginine (SR) proteins and antagonizes the positive effect of the CDK11p110-cyclin L2α complex on splicing. J Biol Chem 286(1):147–159. https://doi.org/10.1074/jbc.M110.192518
Ma X, Kang H, Dai Z, Ma L, Jin Y, Wang X (2015) Impact of the IGFBP3 A-202C polymorphism on susceptibility and clinicopathologic features of breast cancer. Biomed Pharmacother 71:108–111. https://doi.org/10.1016/j.biopha.2015.02.018
Ma S, Chen C, Ji X, Liu J, Zhou Q, Wang G, Yuan W, Kan Q, Sun Z (2019) The interplay between m6A RNA methylation and noncoding RNA in cancer. J Hematol Oncol 12(1):121. https://doi.org/10.1186/s13045-019-0805-7
Mapperley C, van de Lagemaat LN, Lawson H, Tavosanis A, Paris J, Campos J, Wotherspoon D, Durko J, Sarapuu A, Choe J, Ivanova I, Krause DS, von Kriegsheim A, Much C, Morgan M, Gregory RI, Mead AJ, O'Carroll D, Kranc KR (2021) The mRNA m6A reader YTHDF2 suppresses proinflammatory pathways and sustains hematopoietic stem cell function. J Exp Med 218(3). https://doi.org/10.1084/jem.20200829
Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP (2018) Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res 28(11):1747–1756. https://doi.org/10.1101/gr.239244.118
Murphy N, Carreras-Torres R, Song M, Chan AT, Martin RM, Papadimitriou N, Dimou N, Tsilidis KK, Banbury B, Bradbury KE, Besevic J, Rinaldi S, Riboli E, Cross AJ, Travis RC, Agnoli C, Albanes D, Berndt SI, Bézieau S, Bishop DT, Brenner H, Buchanan DD, Onland-Moret NC, Burnett-Hartman A, Campbell PT, Casey G, Castellví-Bel S, Chang-Claude J, Chirlaque MD, de la Chapelle A, English D, Figueiredo JC, Gallinger SJ, Giles GG, Gruber SB, Gsur A, Hampe J, Hampel H, Harrison TA, Hoffmeister M, Hsu L, Huang WY, Huyghe JR, Jenkins MA, Keku TO, Kühn T, Kweon SS, Le Marchand L, Li CI, Li L, Lindblom A, Martín V, Milne RL, Moreno V, Newcomb PA, Offit K, Ogino S, Ose J, Perduca V, Phipps AI, Platz EA, Potter JD, Qu C, Rennert G, Sakoda LC, Schafmayer C, Schoen RE, Slattery ML, Tangen CM, Ulrich CM, van Duijnhoven F, Van Guelpen B, Visvanathan K, Vodicka P, Vodickova L, Vymetalkova V, Wang H, White E, Wolk A, Woods MO, Wu AH, Zheng W, Peters U, Gunter MJ (2020) Circulating levels of insulin-like growth factor 1 and insulin-like growth factor binding protein 3 associate with risk of colorectal cancer based on serologic and mendelian randomization analyses. Gastroenterology 158(5):1300–1312. https://doi.org/10.1053/j.gastro.2019.12.020
Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh AA (2015) Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12(5):453–457. https://doi.org/10.1038/nmeth.3337
Relvas M, Regueira-Iglesias A, Balsa-Castro C, Salazar F, Pacheco JJ, Cabral C, Henriques C, Tomás I (2021) Relationship between dental and periodontal health status and the salivary microbiome: bacterial diversity, co-occurrence networks and predictive models. Sci Rep 11(1):929. https://doi.org/10.1038/s41598-020-79875-x
Rizvi AA, Karaesmen E, Morgan M, Preus L, Wang J, Sovic M, Hahn T, Sucheston-Campbell LE (2019) gwasurvivr: an R package for genome-wide survival analysis. Bioinformatics 35(11):1968–1970. https://doi.org/10.1093/bioinformatics/bty920
Rong B, Zhang Q, Wan J, Xing S, Dai R, Li Y, Cai J, Xie J, Song Y, Chen J, Zhang L, Yan G, Zhang W, Gao H, Han JJ, Qu Q, Ma H, Tian Y, Lan F (2020) Ribosome 18S m(6)A methyltransferase METTL5 promotes translation initiation and breast cancer cell growth. Cell Rep 33(12):108544. https://doi.org/10.1016/j.celrep.2020.108544
Ruan HG, Gu WC, Xia W, Gong Y, Zhou XL, Chen WY, Xiong J (2021) METTL3 is suppressed by circular RNA circMETTL3/miR-34c-3p signaling and limits the tumor growth and metastasis in triple negative breast cancer. Front Oncol 11:778132. https://doi.org/10.3389/fonc.2021.778132
Shi Y, Zheng C, Jin Y, Bao B, Wang D, Hou K, Feng J, Tang S, Qu X, Liu Y, Che X, Teng Y (2020) Reduced expression of METTL3 promotes metastasis of triple-negative breast cancer by m6A methylation-mediated COL3A1 up-regulation. Front Oncol 10:1126. https://doi.org/10.3389/fonc.2020.01126
Song P, Feng L, Li J, Dai D, Zhu L, Wang C, Li J, Li L, Zhou Q, Shi R, Wang X, Jin H (2020) β-catenin represses miR455-3p to stimulate m6A modification of HSF1 mRNA and promote its translation in colorectal cancer. Mol Cancer 19(1):129. https://doi.org/10.1186/s12943-020-01244-z
Sun YS, Zhao Z, Yang ZN, Xu F, Lu HJ, Zhu ZY, Shi W, Jiang J, Yao PP, Zhu HP (2017) Risk factors and preventions of breast cancer. Int J Biol Sci 13(11):1387–1397. https://doi.org/10.7150/ijbs.21635
Sun T, Wu R, Ming L (2019) The role of m6A RNA methylation in cancer. Biomed Pharmacother 112:108613. https://doi.org/10.1016/j.biopha.2019.108613
Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71(3):209–249. https://doi.org/10.3322/caac.21660
Tan B, Zhou K, Liu W, Prince E, Qing Y, Li Y, Han L, Qin X, Su R, Pokharel SP, Yang L, Zhao Z, Shen C, Li W, Chen Z, Zhang Z, Deng X, Small A, Wang K, Leung K, Chen CW, Shen B, Chen J (2022) RNA N(6) -methyladenosine reader YTHDC1 is essential for TGF-beta-mediated metastasis of triple negative breast cancer. Theranostics 12(13):5727–5743. https://doi.org/10.7150/thno.71872
Terry KL, Tworoger SS, Gates MA, Cramer DW, Hankinson SE (2009) Common genetic variation in IGF1, IGFBP1 and IGFBP3 and ovarian cancer risk. Carcinogenesis 30(12):2042–2046. https://doi.org/10.1093/carcin/bgp257
von Minckwitz G, Martin M (2012) Neoadjuvant treatments for triple-negative breast cancer (TNBC). Ann Oncol 23(Suppl 6):i35–i39. https://doi.org/10.1093/annonc/mds193
Wan W, Ao X, Chen Q, Yu Y, Ao L, Xing W, Guo W, Wu X, Pu C, Hu X, Li Z, Yao M, Luo D, Xu X (2022) METTL3/IGF2BP3 axis inhibits tumor immune surveillance by upregulating N(6)-methyladenosine modification of PD-L1 mRNA in breast cancer. Mol Cancer 21(1):60. https://doi.org/10.1186/s12943-021-01447-y
Wang S, Su W, Zhong C, Yang T, Chen W, Chen G, Liu Z, Wu K, Zhong W, Li B, Mao X, Lu J (2020a) An eight-CircRNA assessment model for predicting biochemical recurrence in prostate cancer. Front Cell Dev Biol 8:599494. https://doi.org/10.3389/fcell.2020.599494
Wang S, Zou X, Chen Y, Cho WC, Zhou X (2020b) Effect of N6-methyladenosine regulators on progression and prognosis of triple-negative breast cancer. Front Genet 11:580036. https://doi.org/10.3389/fgene.2020.580036
Wei W, Sun J, Zhang H, Xiao X, Huang C, Wang L, Zhong H, Jiang Y, Zhang X, Jiang G (2021) Circ0008399 interaction with WTAP promotes assembly and activity of the m(6)A methyltransferase complex and promotes cisplatin resistance in bladder cancer. Cancer Res 81(24):6142–6156. https://doi.org/10.1158/0008-5472.CAN-21-1518
Wen S, Wei Y, Zen C, Xiong W, Niu Y, Zhao Y (2020) Long non-coding RNA NEAT1 promotes bone metastasis of prostate cancer through N6-methyladenosine. Mol Cancer 19(1):171. https://doi.org/10.1186/s12943-020-01293-4
Yu Y, Ouyang Y, Yao W (2018) shinyCircos: an R/Shiny application for interactive creation of Circos plot. Bioinformatics 34(7):1229–1231. https://doi.org/10.1093/bioinformatics/btx763
Yu HL, Ma XD, Tong JF, Li JQ, Guan XJ, Yang JH (2019) WTAP is a prognostic marker of high-grade serous ovarian cancer and regulates the progression of ovarian cancer cells. Onco Targets Ther 12:6191–6201. https://doi.org/10.2147/OTT.S205730
Zaccara S, Ries RJ, Jaffrey SR (2019) Reading, writing and erasing mRNA methylation. Nat Rev Mol Cell Biol 20(10):608–624. https://doi.org/10.1038/s41580-019-0168-5
Zhang C, Samanta D, Lu H, Bullen JW, Zhang H, Chen I, He X, Semenza GL (2016) Hypoxia induces the breast cancer stem cell phenotype by HIF-dependent and ALKBH5-mediated m6A-demethylation of NANOG mRNA. Proc Natl Acad Sci U S A 113(14):E2047–E2056. https://doi.org/10.1073/pnas.1602883113
Zhang B, Wu Q, Li B, Wang D, Wang L, Zhou YL (2020a) m(6)A regulator-mediated methylation modification patterns and tumor microenvironment infiltration characterization in gastric cancer. Mol Cancer 19(1):53. https://doi.org/10.1186/s12943-020-01170-0
Zhang C, Huang S, Zhuang H, Ruan S, Zhou Z, Huang K, Ji F, Ma Z, Hou B, He X (2020b) YTHDF2 promotes the liver cancer stem cell phenotype and cancer metastasis by regulating OCT4 expression via m6A RNA methylation. Oncogene 39(23):4507–4518. https://doi.org/10.1038/s41388-020-1303-7
Zhang Z, Zhang C, Luo Y, Wu P, Zhang G, Zeng Q, Wang L, Yang Z, Xue L, Zheng B, Zeng H, Tan F, Xue Q, Gao S, Sun N, He J (2021) m(6)A regulator expression profile predicts the prognosis, benefit of adjuvant chemotherapy, and response to anti-PD-1 immunotherapy in patients with small-cell lung cancer. BMC Med 19(1):284. https://doi.org/10.1186/s12916-021-02148-5
Zheng ZQ, Li ZX, Zhou GQ, Lin L, Zhang LL, Lv JW, Huang XD, Liu RQ, Chen F, He XJ, Kou J, Zhang J, Wen X, Li YQ, Ma J, Liu N, Sun Y (2019) Long noncoding RNA FAM225A promotes nasopharyngeal carcinoma tumorigenesis and metastasis by acting as ceRNA to sponge miR-590-3p/miR-1275 and upregulate ITGB3. Cancer Res 79(18):4612–4626. https://doi.org/10.1158/0008-5472.CAN-19-0799
Zhong Q, Fan J, Chu H, Pang M, Li J, Fan Y, Liu P, Wu C, Qiao J, Li R, Hang J (2020) Integrative analysis of genomic and epigenetic regulation of endometrial cancer. Aging (albany NY) 12(10):9260–9274. https://doi.org/10.18632/aging.103202
Zuo X, Chen Z, Gao W, Zhang Y, Wang J, Wang J, Cao M, Cai J, Wu J, Wang X (2020) M6A-mediated upregulation of LINC00958 increases lipogenesis and acts as a nanotherapeutic target in hepatocellular carcinoma. J Hematol Oncol 13(1):5. https://doi.org/10.1186/s13045-019-0839-x
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Jiarong Yi and Xi Wang designed the study. Haoming Wu, Jundong Wu and Jikun Feng finished the main work and wrote the manuscript. Xinjian Huang, Jundong Wu and Wenjing Zhong revised and polished the manuscript. Xiazi Zouxu and Weiling Huang performed the statistical analysis of the data. All authors reviewed the manuscript.
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Jiarong Yi and Xi Wang designed the study. Haoming Wu, Jundong Wu and Jikun Feng finished the main work and wrote the manuscript. Xinjian Huang, Jundong Wu and Wenjing Zhong revised and polished the manuscript. Xiazi Zouxu and Weiling Huang performed the statistical analysis of the data. All authors reviewed the manuscript.
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Wu, H., Feng, J., Wu, J. et al. Prognostic value of comprehensive typing based on m6A and gene cluster in TNBC. J Cancer Res Clin Oncol 149, 4367–4380 (2023). https://doi.org/10.1007/s00432-022-04345-y
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DOI: https://doi.org/10.1007/s00432-022-04345-y