Colorectal Tumors in Diverse Patient Populations Feature a Spectrum of Somatic Mutational Profiles

不同患者群体中的结直肠肿瘤具有一系列体细胞突变谱。

阅读:3

Abstract

Admixed populations, including the Hispanic/Latino/a community, are underrepresented in cancer genetic/genomic studies. Leveraging the Latino Colorectal Cancer Consortium (LC3) and other existing datasets, we analyzed whole-exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer to map somatic mutational features by ethnicity and genetic similarity. Global proportions of African, Asian, European, and Native American genetic ancestries were estimated using ADMIXTURE. Associations between these proportions and somatic mutational features were examined using logistic regression. APC, TP53, and KRAS were the top three mutated genes across all participants and in the subset of Latino individuals in LC3. In analyses examining recurrently mutated genes, tumors from patients of Latino ethnicity had fewer KRAS and PIK3CA mutations compared with tumors from non-Latino patients. Genetic ancestry overall was associated with CDC27 mutation status, and African genetic ancestry was associated with SMAD2 mutation status. In exome-wide analyses, African genetic ancestry was significantly associated with higher odds of mutation in KNCN and TMEM184B. Native American genetic ancestry was associated with a lower frequency of microsatellite instability-high tumors. The SBS11 mutational signature was associated with Native American genetic ancestry as well as Latino ethnicity. In an independent replication dataset, MSK-IMPACT, estimates of association were largely consistent in direction but nonsignificant. A meta-analysis of LC3 and MSK-IMPACT showed that African genetic ancestry was significantly associated with KRAS mutation status and MSI status. This work facilitates precision medicine initiatives by providing insights into the contribution of genetic ancestry to molecular features of colorectal tumors. Significance: Analysis of tumors from various populations can broadly characterize genomic landscapes and enhance precision medicine strategies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。