Thompson Joe Sneath, Madrid Laura, Hernando Barbara, Sauer Carolin M, Vias Maria, Escobar-Rey Maria, Leung Wing-Kit, Garcia-Lopez Diego, Huckstep Jamie, Sekowska Magdalena, Hosking Karen, Jimenez-Linan Mercedes, Reinius Marika A V, Roy Abhipsa, Abdulle Omar, Pangonyte Justina, Dobson Harry, Cullen Amy E, De Silva Dilrini, Gómez-Sánchez David, Torres Marina, Fernández-Sanromán Ángel, Sanders Deborah, Martins Filipe Correia, Funingana Ionut-Gabriel, Codacci-Pisanelli Giovanni, Quintela-Fandino Miguel, Markowetz Florian, Yip Jason, Brenton James D, Piskorz Anna M, Macintyre Geoff
Spanish National Cancer Research Centre (CNIO), Madrid, Spain.
Tailor Bio Ltd, Cambridge, UK.
Nat Genet. 2025 Jun 23. doi: 10.1038/s41588-025-02233-y.
Chemotherapies are often given without precision biomarkers, exposing patients to toxic side effects without guaranteed benefit. Here we present chromosomal instability signature biomarkers that identify resistance to platinum-, taxane- and anthracycline-based treatments using a single genomic test. In retrospectively emulated randomized-control biomarker clinical trials using real-world cohorts (n = 840), predicted resistant patients had elevated treatment failure risk for taxane (hazard ratio (HR) of 7.44) and anthracycline (HR of 1.88) in ovarian, taxane (HR of 3.98) and anthracycline (HR of 3.69) in metastatic breast and taxane (HR of 5.46) in metastatic prostate. Nonrandomized emulations showed predictive capacity for platinum resistance in ovarian (HR of 1.46) and anthracycline in sarcoma (HR of 3.59). We demonstrate feasibility using whole-genome sequencing, capture-panel sequencing and cell-free DNA. Our findings highlight the clinical value of chromosomal instability signatures in predicting resistance to chemotherapies across multiple cancer types, with the potential to transform the one-size-fits-all chemotherapy approach into precise, tailored treatment.
化疗通常在没有精确生物标志物的情况下进行,这使得患者在没有保证疗效的情况下遭受毒副作用。在此,我们展示了染色体不稳定特征生物标志物,这些标志物可通过单一基因组检测来识别对铂类、紫杉烷类和蒽环类治疗的耐药性。在使用真实世界队列(n = 840)进行的回顾性模拟随机对照生物标志物临床试验中,预测为耐药的患者在卵巢癌中接受紫杉烷治疗(风险比(HR)为7.44)和蒽环类治疗(HR为1.88)、在转移性乳腺癌中接受紫杉烷治疗(HR为3.98)和蒽环类治疗(HR为3.69)以及在转移性前列腺癌中接受紫杉烷治疗(HR为5.46)时,治疗失败风险升高。非随机模拟显示了对卵巢癌铂耐药(HR为1.46)和肉瘤蒽环类耐药(HR为3.59)的预测能力。我们通过全基因组测序、捕获-panel测序和游离DNA证明了其可行性。我们的研究结果突出了染色体不稳定特征在预测多种癌症类型化疗耐药性方面的临床价值,有可能将一刀切的化疗方法转变为精确的、量身定制的治疗方法。