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Tumor mutation burden as a marker for molecularly matched therapy: more evidence needed

    Xiang-Yu Meng

    *Author for correspondence:

    E-mail Address: mengxy_whu@163.com

    Health Science Center, Hubei Minzu University, Enshi, 445000, China

    Hubei Provincial Key Laboratory of Occurrence and Intervention of Rheumatic Diseases, Hubei Minzu University, Enshi, 445000, China

    &
    Qiu-Ji Wu

    **Author for correspondence:

    E-mail Address: wuqiuji@126.com

    Department of Radiation and Medical Oncology, Hubei Key Laboratory of Tumour Biological Behaviors, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China

    Published Online:https://doi.org/10.2217/epi-2023-0354
    Free first page

    References

    • 1. Litchfield K, Reading JL, Puttick C et al. Meta-analysis of tumor- and T cell-intrinsic mechanisms of sensitization to checkpoint inhibition. Cell 184(3), 596–614; e514 (2021).
    • 2. Mcgrail DJ, Pilie PG, Rashid NU et al. High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann. Oncol. 32(5), 661–672 (2021).
    • 3. De Bortoli T, Benary M, Horak P et al. Tumour mutational burden and survival with molecularly matched therapy. Eur. J. Cancer 190, 112925 (2023).
    • 4. Offin M, Rizvi H, Tenet M et al. Tumor mutation burden and efficacy of EGFR-tyrosine kinase inhibitors in patients with EGFR-mutant lung cancers. Clin. Cancer Res. 25(3), 1063–1069 (2019).
    • 5. Lin C, Shi X, Zhao J et al. Tumor mutation burden correlates with efficacy of chemotherapy/targeted therapy in advanced non-small cell lung cancer. Front Oncol. 10, 480 (2020).
    • 6. Smith AE, Ferraro E, Safonov A et al. HER2+ breast cancers evade anti-HER2 therapy via a switch in driver pathway. Nat. Commun. 12(1), 6667 (2021).
    • 7. Hyman DM, Piha-Paul SA, Won H et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature 554(7691), 189–194 (2018).
    • 8. Taber A, Christensen E, Lamy P et al. Molecular correlates of cisplatin-based chemotherapy response in muscle invasive bladder cancer by integrated multi-omics analysis. Nat. Commun. 11(1), 4858 (2020).
    • 9. Lengel HB, Mastrogiacomo B, Connolly JG et al. Genomic mapping of metastatic organotropism in lung adenocarcinoma. Cancer Cell 41(5), 970–985; e973 (2023).
    • 10. Tsang ES, Csizmok V, Williamson LM et al. Homologous recombination deficiency signatures in gastrointestinal and thoracic cancers correlate with platinum therapy duration. NPJ Precis. Oncol. 7(1), 31 (2023).
    • 11. Batalini F, Gulhan DC, Mao V et al. Mutational Signature 3 Detected from Clinical Panel Sequencing is Associated with Responses to Olaparib in Breast and Ovarian Cancers. Clin. Cancer Res. 28(21), 4714–4723 (2022).
    • 12. Hanahan D. Hallmarks of Cancer: New Dimensions. Cancer Discov. 12(1), 31–46 (2022).
    • 13. Neyret-Kahn H, Fontugne J, Meng XY et al. Epigenomic mapping identifies an enhancer repertoire that regulates cell identity in bladder cancer through distinct transcription factor networks. Oncogene 42(19), 1524–1542 (2023).
    • 14. Labrie M, Brugge JS, Mills GB, Zervantonakis IK. Therapy resistance: opportunities created by adaptive responses to targeted therapies in cancer. Nat. Rev. Cancer 22(6), 323–339 (2022).
    • 15. Zhou Q, Zhang XC, Chen ZH et al. Relative abundance of EGFR mutations predicts benefit from gefitinib treatment for advanced non-small-cell lung cancer. J. Clin. Oncol. 29(24), 3316–3321 (2011).