Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons.

IF 1.8 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Cold Spring Harbor Molecular Case Studies Pub Date : 2024-01-10 Print Date: 2023-12-01 DOI:10.1101/mcs.a006298
Kyle M Hernandez, Aarti Venkat, Danne C Elbers, John R Bihn, Mary T Brophy, Nhan V Do, Jennifer La, Qiong Liu, Andrew Prokhorenkov, Noah Metoki-Shlubsky, Feng-Chi Sung, Channing J Paller, Nathanael R Fillmore, Robert L Grossman
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引用次数: 0

Abstract

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.

退伍军人精确肿瘤数据共享中前列腺癌患者的分子标记分层。
与普通人群相比,退伍军人患前列腺癌的风险更高,前列腺癌具有非同寻常的临床和分子异质性。然而,对退伍军人群体中潜在的分子异质性及其对患者管理和治疗的影响知之甚少。利用美国退伍军人事务卫生系统的临床和靶向肿瘤测序数据,我们在退伍军人精确肿瘤数据共享(VPODC)中对45例晚期前列腺癌患者进行了回顾性队列研究,其中大多数患者具有转移性去势抵抗性。我们在这个队列中描述了突变负担,并进行了无监督聚类分析,通过分子改变对患者进行分层。患有前列腺癌的退伍军人表现出与先前研究大致相似的突变景观,包括与神经内分泌前列腺癌表型相关的KMT2A和NOTCH1突变,先前报道在退伍军人中富集。我们还在PTEN、MSH6、VHL、SMO和ABL1中发现了几个潜在的新突变。分层聚类分析揭示了两个亚组包含治疗可靶向的分子特征,具有不同于癌症数据库中体细胞突变目录中报道的新突变特征。本研究中提出的聚类方法可以潜在地用于根据患者不同的突变谱对患者进行临床分层,并确定精确肿瘤学中可操作的体细胞突变。
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来源期刊
Cold Spring Harbor Molecular Case Studies
Cold Spring Harbor Molecular Case Studies MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
3.20
自引率
0.00%
发文量
54
期刊介绍: Cold Spring Harbor Molecular Case Studies is an open-access, peer-reviewed, international journal in the field of precision medicine. Articles in the journal present genomic and molecular analyses of individuals or cohorts alongside their clinical presentations and phenotypic information. The journal''s purpose is to rapidly share insights into disease development and treatment gained by application of genomics, proteomics, metabolomics, biomarker analysis, and other approaches. The journal covers the fields of cancer, complex diseases, monogenic disorders, neurological conditions, orphan diseases, infectious disease, gene therapy, and pharmacogenomics. It has a rapid peer-review process that is based on technical evaluation of the analyses performed, not the novelty of findings, and offers a swift, clear path to publication. The journal publishes: Research Reports presenting detailed case studies of individuals and small cohorts, Research Articles describing more extensive work using larger cohorts and/or functional analyses, Rapid Communications presenting the discovery of a novel variant and/or novel phenotype associated with a known disease gene, Rapid Cancer Communications presenting the discovery of a novel variant or combination of variants in a cancer type, Variant Discrepancy Resolution describing efforts to resolve differences or update variant interpretations in ClinVar through case-level data sharing, Follow-up Reports linked to previous observations, Plus Review Articles, Editorials, and Position Statements on best practices for research in precision medicine.
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