Impact of cancer predisposition on oncogenic process, microenvironment, and treatment

癌症易感性对致癌过程、微环境和治疗的影响

• 批准号: 10544995
• 负责人: FENG CHEN
• 金额: $ 46.89万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2026-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10544995
• 关键词: ATAC-seq; Address; Biological; Breast Cancer Cell; Breast Cancer Model; Cells; Characteristics; Clinical; Clonality; Computer Analysis; Data; Development; Event; Genes; Genetic Counseling; Genetic Models; Genetic Models for Cancer; Genetic Transcription; Germ-Line Mutation; Human; Image; Immune; Incidence; Malignant Neoplasms; Modeling; Molecular; Mutation; Nature; Oncogene Activation; Oncogenes; Oncogenic; Patient-derived xenograft models of breast cancer; Patients; Pattern; Phenotype; Predisposition; Process; Prognosis; Proteins; Proteomics; Renal Cell Carcinoma; Renal carcinoma; Resolution; Role; Sampling; Signal Transduction; Somatic Mutation; Susceptibility Gene; Testing; Tissue-Specific Gene Expression; Tissues; Transcend; Tumor Suppressor Proteins; Variant; brca gene; cancer cell; cancer predisposition; cancer type; cell stroma; differential expression; experience; human imaging; improved; mouse genetics; mouse model; multiple omics; multiplexed imaging; neoplastic cell; patient derived xenograft model; personalized cancer therapy; pressure; response; single cell analysis; single nucleus RNA-sequencing; transcriptomics; translational impact; treatment choice; treatment response; tumor; tumor initiation; tumor microenvironment; tumor progression; tumorigenesis

Our previous study of more than 10 thousand tumors across 33 cancer types identified over 800 germline predisposition variants in both tumor suppressors and oncogenes. Although the impact of some of these variants on cancer onset, incidence rate, and clonality have been documented, the effects of these variants (especially when compared to somatic mutations) on molecular characteristics of cancer cells, contributions of non-cancer cells having germline variants, and treatment responses, are far less studied. Our recent single cell(sc) /single nucleus(sn) RNA-seq analyses of cancer samples provided comprehensive expression profiles at a single cell resolution and revealed the expression of key cancer predisposition genes, such as BRCA 112, VHL, BAP1, and c-MET in many non-cancer stromal and immune cells in the tumor microenvironment (TME). Our pilot analyses also revealed significant differential gene expression in cancer and non-cancer cells based on the nature of the driver event being germline or somatic. We hypothesize that tumors with certain germline predisposition variants in tumor suppressors and oncogenes may show differences in tumor progression and treatment responses from those tumors with somatic mutations in the same genes due to differential influence on mutational, transcriptomic, and proteomic profiles of the cancer cells and potentially distinctive contributions from non-cancer cells having those germline changes. To take advantage of the considerable progress over the last few years, namely newly accumulated cancer sequencing data, advances in single cell omics, patient-derived xenografts (PDX), and tumor genetic models, we propose to test these hypotheses by performing the following: compare germline predisposition variants and somatic mutations to dissect their differential biological impacts and interactions using computational analysis (Aim 1); perform single nucleus RNA-seq/ATAC-seq, spatial transcriptomics, and multiplex imaging analysis of human cancer samples to reveal the differential roles of germline predisposition variants and somatic mutations in tumor cells and the TME (Aim 2); use PDX and genetic cancer models to investigate potential functional differences between germline predisposition variants and somatic mutations in tumor cells, TME, and treatment responses (Aim 3). Results from this study will advance our understanding of the unique contributions of germline variants to cancer cells and TME alike, improve genetic counseling and prognosis, and provide guidance for differential treatment of tumors carrying germline variants vs somatic mutations in key cancer driver genes.

我们先前对33种癌症类型的10,000多个肿瘤的研究鉴定出了800多种种系 肿瘤抑制剂和癌基因的倾向变体。虽然其中一些的影响 已经记录了癌症发作，发病率和克隆性的变体，这些变体的影响 （尤其是与体细胞突变相比）关于癌细胞的分子特征的贡献 研究的非癌细胞和治疗反应的研究要小得多。我们最近的单曲 细胞（SC） /单核（SN）癌症样品的RNA-seq分析提供了全面的表达曲线 在单个细胞分辨率下，揭示了关键癌症易感基因的表达，例如BRCA 112， 肿瘤微环境（TME）中许多非癌基质和免疫细胞中的VHL，BAP1和C-MET。 我们的试点分析还显示了癌症和非癌细胞中的显着差异基因表达 关于驾驶员事件的性质是种系或躯体。我们假设具有某些种系的肿瘤 肿瘤抑制剂和癌基因中的倾向变异可能显示出肿瘤进展的差异和 由于差异而导致相同基因中具有体细胞突变的肿瘤的治疗反应 对癌细胞的突变，转录组和蛋白质组学特征的影响以及潜在的独特性 具有这些种系变化的非癌细胞的贡献。利用可观的 在过去几年中的进展，即新累积的癌症测序数据，单细胞的进步 OMICS，患者衍生的异种移植（PDX）和肿瘤遗传模型，我们建议通过 执行以下操作：比较种系倾向变体和躯体突变以剖析其 使用计算分析的差异生物学影响和相互作用（AIM 1）；执行单个 核RNA-SEQ/ATAC-SEQ，空间转录组学和人类癌的多重成像分析 样品揭示了种系倾向变体和肿瘤中体细胞突变的差异作用 细胞和TME（AIM 2）；使用PDX和遗传癌模型研究潜在的功能 肿瘤细胞，TME和 治疗反应（目标3）。这项研究的结果将提高我们对独特的理解 种系变体对癌细胞和TME的贡献，改善遗传咨询和预后， 并为携带种系变异的肿瘤的差异治疗提供指导 癌症驱动基因。