Institute of Pathology, Philipps-University Marburg and University Hospital Marburg (UK-GM), Marburg, Germany; Charité - Universitätsmedizin Berlin, Institute of Pathology, Berlin, Germany.
Helios Klinikum Berlin-Buch, Department of Obstetrics and Gynaecology, Berlin, Germany.
Ann Oncol. 2021 Apr;32(4):500-511. doi: 10.1016/j.annonc.2020.12.016. Epub 2021 Jan 6.
Different endogenous and exogenous mutational processes act over the evolutionary history of a malignant tumor, driven by abnormal DNA editing, mutagens or age-related DNA alterations, among others, to generate the specific mutational landscape of each individual tumor. The signatures of these mutational processes can be identified in large genomic datasets. We investigated the hypothesis that genomic patterns of mutational signatures are associated with the clinical behavior of breast cancer, in particular chemotherapy response and survival, with a particular focus on therapy-resistant disease.
Whole exome sequencing was carried out in 405 pretherapeutic samples from the prospective neoadjuvant multicenter GeparSepto study. We analyzed 11 mutational signatures including biological processes such as APOBEC-mutagenesis, homologous recombination deficiency (HRD), mismatch repair deficiency and also age-related or tobacco-induced alterations.
Different subgroups of breast carcinomas were defined mainly by differences in HRD-related and APOBEC-related mutational signatures and significant differences between hormone-receptor (HR)-negative and HR-positive tumors as well as correlations with age, Ki-67 and immunological parameters were observed. We could identify mutational processes that were linked to increased pathological complete response rates to neoadjuvant chemotherapy with high significance. In univariate analyses for HR-positive tumors signatures, S3 (HRD, P < 0.001) and S13 (APOBEC, P = 0.001) as well as exonic mutation rate (P = 0.002) were significantly correlated with increased pathological complete response rates. The signatures S3 (HRD, P = 0.006) and S4 (tobacco, P = 0.011) were prognostic for reduced disease-free survival of patients with chemotherapy-resistant tumors.
The results of this investigation suggest that the clinical behavior of a tumor, in particular, response to neoadjuvant chemotherapy and disease-free survival of therapy-resistant tumors, could be predicted by the composition of mutational signatures as an indicator of the individual genomic history of a tumor. After additional validations, mutational signatures might be used to identify tumors with an increased response rate to neoadjuvant chemotherapy and to define therapy-resistant subgroups for future therapeutic interventions.
不同的内源性和外源性突变过程在恶性肿瘤的进化史中起作用,这些过程由异常的 DNA 编辑、诱变剂或与年龄相关的 DNA 改变等驱动,产生每个肿瘤的特定突变景观。这些突变过程的特征可以在大型基因组数据集中识别出来。我们研究了这样一个假设,即突变特征的基因组模式与乳腺癌的临床行为相关,特别是化疗反应和生存,特别关注治疗耐药性疾病。
对前瞻性新辅助多中心 GeparSepto 研究中的 405 个治疗前样本进行了全外显子组测序。我们分析了 11 种突变特征,包括 APOBEC 诱变、同源重组缺陷 (HRD)、错配修复缺陷等生物学过程,以及与年龄、烟草诱导相关的改变。
乳腺癌的不同亚组主要由 HRD 相关和 APOBEC 相关突变特征的差异以及激素受体 (HR) 阴性和 HR 阳性肿瘤之间的显著差异以及与年龄、Ki-67 和免疫参数的相关性来定义。我们可以确定与新辅助化疗的病理性完全缓解率增加相关的突变过程,具有很高的显著性。在 HR 阳性肿瘤的单因素分析中,S3(HRD,P < 0.001)和 S13(APOBEC,P = 0.001)以及外显子突变率(P = 0.002)与增加的病理性完全缓解率显著相关。S3(HRD,P = 0.006)和 S4(烟草,P = 0.011)的特征与化疗耐药肿瘤患者无病生存降低相关。
本研究结果表明,肿瘤的临床行为,特别是新辅助化疗的反应和治疗耐药肿瘤的无病生存,可以通过突变特征的组成来预测,作为肿瘤个体基因组史的指标。经过进一步验证,突变特征可用于识别对新辅助化疗反应率增加的肿瘤,并为未来的治疗干预确定治疗耐药亚组。