Proteogenomics-driven therapeutic discovery in hepatocellular carcinoma

蛋白质基因组学驱动的肝细胞癌治疗发现

• 批准号: 10594466
• 负责人: Bing Zhang
• 金额: $ 19.99万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594466
• 关键词: Animal Model; Antigens; Automobile Driving; Biological Assay; Biological Markers; Biology; Cancer Etiology; Cell Line; Cells; Cessation of life; China; Chinese; Classification; Clinical; Collaborations; Colon Carcinoma; Complement; Computer Analysis; Computing Methodologies; DNA Sequence Alteration; Data; Data Analyses; Data Set; Development; Disease; Drug Targeting; Funding; Generations; Genetic; Genome; Genomics; Growth; Hepatitis B Virus; Immune; Immune Evasion; Immunofluorescence Immunologic; Immunophenotyping; Immunotherapy; International; Knowledge; Machine Learning; Malignant Neoplasms; Malignant neoplasm of liver; Maps; Mass Spectrum Analysis; Messenger RNA; Modeling; Molecular; Monitor; Multiomic Data; National Cancer Institute; Oncology; Outcome; Pathogenesis; Pathway interactions; Patients; Pharmaceutical Preparations; Phase I Clinical Trials; Phenotype; Primary carcinoma of the liver cells; Prognosis; Prospective cohort; Proteins; Proteomics; Publishing; RNA analysis; Reaction; Recommendation; Research; Research Personnel; Resources; Specimen; Techniques; Technology; Testing; Therapeutic; Therapeutic Agents; Therapeutic Intervention; Training; Translating; Validation; biomarker selection; biomarker validation; cancer type; cohort; forging; genomic platform; immunogenicity; in silico; mouse model; multiple omics; neoantigens; next generation sequencing; novel therapeutics; patient derived xenograft model; phosphoproteomics; prognostic; prognostic model; programs; protein biomarkers; proteogenomics; small molecule; targeted agent; transcriptome sequencing; transcriptomics; treatment strategy; tumor; tumor microenvironment

Project Summary Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide, and therapeutic options are limited. There is a pressing need to fully understand the molecular mechanisms underlying the disease in order to identify new effective biomarkers, drug targets, and therapeutic agents for the prognosis and treatment of HCC. Proteins are the functional molecules of the cell, and many clinically validated biomarkers and most drug targets are proteins; however, cancer omics studies have relied primarily on genomic platforms. By melding genomics with mass spectrometry (MS)-based proteomics, the new field of proteogenomics provides an opportunity to more completely understand how somatic genomes activate aberrant protein networks that drive cancer pathogenesis. A major National Cancer Institute (NCI)-funded initiative, the Clinical Proteomics Tumor Analysis Consortium (CPTAC), and the more recently established International Cancer Proteogenome Consortium (ICPC), are promoting an integrated proteogenomics approach that is postulated to produce sounder therapeutic hypotheses and a new generation of protein biomarkers. The central purpose of this application is to forge a collaboration between a CPTAC team in the US and an ICPC team in China to enable proteogenomics-driven therapeutic discoveries in hepatitis B virus-related (HBV+) HCC, which attributes to 85% of HCC cases in China. The two teams bring complementary expertise required for a successful proteogenomic study of HCC. The China team has already generated the most comprehensive multi-omics dataset yet produced for liver cancer by applying proteogenomic profiling to a Chinese HBV+ HCC cohort (CHCC-HBV) with 159 cases, and the data has been preliminarily analyzed through collaborative efforts between the two teams. In this application, the US team will perform deep computational analyses of the proteogenomics data to generate prognostic models and therapeutic hypotheses, which will be experimentally validated in cell lines, animal models, and clinical specimens by the China team. Our specific Aims are: Aim 1) To develop and validate a protein-based prognostic model; Aim 2) To identify and validate subtype-specific causal drivers and therapeutic strategies; and Aim 3) To characterize the immune landscape of HBV+ HCC. Successful completion of this project will lead to new knowledge on HCC biology as well as new prognostic and treatment strategies for HBV+ HCC. Meanwhile, experimentally validated computational methods developed in this project will have wide application to the study of other cancers and other non-cancer diseases.

项目摘要 肝细胞癌是全球癌症相关死亡的第三大原因， 治疗选择是有限的。迫切需要充分了解分子机制。 以确定新的有效的生物标记物、药物靶点和治疗药物 肝细胞癌的预后和治疗蛋白质是细胞的功能分子，有许多临床验证。 生物标记物和大多数药物靶标都是蛋白质；然而，癌症组学研究主要依靠基因组学。 站台。通过将基因组学与基于质谱学(MS)的蛋白质组学相结合， 蛋白质组学为更全面地了解体细胞基因组如何激活异常提供了机会 驱动癌症发病机制的蛋白质网络。国家癌症研究所(NCI)资助的一项重大倡议， 临床蛋白质组学肿瘤分析联盟(CPTAC)和最近成立的国际 癌症蛋白质组联盟(ICPC)正在推动一种集成的蛋白质组学方法，即 假设产生更合理的治疗假说和新一代蛋白质生物标记物。中环 此应用程序的目的是在美国的CPTAC团队和ICPC之间建立合作 中国的团队使蛋白质组学驱动的乙肝相关治疗发现成为可能 (乙肝病毒阳性)肝细胞癌，中国85%的肝细胞癌病例。两个团队带来了互补的专业知识 这是成功的肝细胞癌蛋白质基因组研究所必需的。中国团队已经产生了最多的 通过将蛋白质组学图谱应用于肝癌而为肝癌产生的综合多组学数据集 中国人乙肝病毒+肝癌队列(CHCC-HBV159例)，并对资料进行了初步分析。 两个团队之间的合作努力。在这一应用中，美国团队将执行深度计算 对蛋白质组学数据进行分析，以生成预后模型和治疗假设，这将是 中国团队在细胞系、动物模型和临床标本中进行了实验验证。我们的特定 目标是：目标1)开发和验证基于蛋白质的预后模型；目标2)识别和验证 亚型特定的原因驱动因素和治疗策略；以及目标3)表征脑炎的免疫环境 乙肝病毒+肝细胞癌。该项目的成功完成将带来对肝细胞癌生物学的新知识以及新的 乙肝病毒阳性肝细胞癌的预后和治疗策略。同时，经过实验验证的计算方法 本项目的开发将对其他癌症和其他非癌症疾病的研究具有广泛的应用价值。