Copy Number Alterations in Low Mutation Cancer

低突变癌症中的拷贝数改变

基本信息

批准号：
9814814
负责人：
Joe R Delaney
金额：
$ 23.66万
依托单位：
MEDICAL UNIVERSITY OF SOUTH CAROLINA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-12-01 至 2021-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9814814
关键词：
Algorithms Alleles Aneuploidy Autophagocytosis BRAF gene BRCA1 gene Bioinformatics Biological Biological Assay Cancer Biology Cells Chloroquine Chromosome Arm Clinical DNA Data Data Set Drug Targeting Drug resistance Event Gene Dosage Genes Genetic Genome Genomics Genotype Heterogeneity Immunotherapy In Vitro Individual International Investigation Maintenance Malignant Neoplasms Malignant neoplasm of ovary Maps Mediating Mentorship Metabolic Metabolism Minority Modeling Molecular Molecular Biology Mus Mutate Mutation Noise Oncogenes Oncogenic Oncologist Ovarian Serous Tumor Pathway Analysis Pathway interactions Patients Phase Phenotype Process Recycling Research Research Personnel Resources Serous Stem cells TP53 gene Testing The Cancer Genome Atlas Training Tumor Suppressor Genes Tumor Suppressor Proteins Work addiction bioinformatics tool cancer genome cancer type cohort computerized tools drug sensitivity improved in vivo knock-down mouse model neoantigens novel targeted treatment tool tumor tumor progression tumorigenesis user-friendly whole genome

项目摘要

Abstract Two general types of genetic alterations drive cancer progression; mutations and copy number alterations (CNAs). Research into mutations such ABL fusions and BRAF have yielded powerful targeted therapeutics. However, not all cancers are mutated in targetable genes; 48% of serous ovarian cancers (OV) have no oncogenic mutation other than in p53. For these low-mutation tumors and cancer types, the most likely culprit for tumorigenesis and drug resistance lies in CNAs. The OV genome is remarkably unstable; in the average tumor, 2/3 of genes display a copy number change: roughly 1/3 are deleted and 1/3 are increased in gene dosage. One known CNA driver in ovarian cancer is a homozygous loss in BRCA1/2 genes in ~10% of patients; however 99% of deletions in SOC are heterozygous, not homozygous deletions. This remaining 99% of deletions must contain tumor suppressors which contribute to cancer progression with only heterozygous losses, which accumulate along individual pathways. We developed novel "HAPTRIG" pathway analysis of loss events in whole genome datasets with the ability to work in highly altered backgrounds like OV and can perform calculations of multiple pathways at once. We discovered that the cellular recycling pathway of autophagy is universally (98% of tumors), redundantly (at least 4 genes are deleted in the average tumor), and uniquely (more than any other tumor type) suppressed by deletions in serous ovarian cancer. The most impactful lost autophagy genes are BECN1 and LC3B. We found BECN1 and LC3B loss is to contribute to OV aneuploidy and monoallelic BECN1 loss to accelerate OV tumorigenesis in a mouse model. We propose to develop our understanding of tumor CNAs by [1] analyzing every tumor for pathway disruptions in >3,000 known molecular pathways using an automated HAPTRIG bioinformatics tool, [2] scoring the most impactful genes in each pathway/tumor pair to identify novel CNA drivers of cancer, and [3] release the tool in a user- friendly portal for any oncologist to perform CNA pathway analysis on any cohort of tumors. Since our top predictions from the CNA networks were validated to impact genomic copy number variability, oncogenesis, and therapy targeting in OV, we propose to provide further mechanistic understanding of CNA losses by [1] analyzing the types and heterogeneity of CNAs caused by BECN1 and LC3B depletion, [2] the metabolic, CNA, and stem cell changes present in BECN1+/- murine OV tumors, and [3] assaying autophagic flux and metabolic alterations for chloroquine therapy, which selectively kills BECN1 and LC3B depleted OV cells.

抽象的两种一般类型的基因改变会导致癌症进展；突变和拷贝数改变（CNA）。对 ABL 融合和 BRAF 等突变的研究已经产生了强大的靶向治疗方法。然而，并非所有癌症都会发生靶向基因突变。 48% 的浆液性卵巢癌 (OV) 没有 p53 以外的致癌突变。对于这些低突变肿瘤和癌症类型，最有可能的罪魁祸首是肿瘤发生和耐药性的关键在于CNA。 OV基因组非常不稳定；平均而言肿瘤，2/3的基因显示拷贝数变化：基因中大约1/3被删除，1/3被增加剂量。卵巢癌中一个已知的 CNA 驱动因素是约 10% 的卵巢癌患者中 BRCA1/2 基因纯合性缺失。患者;然而，SOC 中 99% 的缺失是杂合性缺失，而不是纯合性缺失。这剩下的99% 的缺失必须含有肿瘤抑制因子，仅杂合子就有助于癌症进展损失，沿着各个路径累积。我们开发了新颖的“HAPTRIG”通路分析全基因组数据集中的丢失事件，能够在 OV 等高度改变的背景下工作，并且可以一次执行多个路径的计算。我们发现细胞循环途径自噬是普遍存在的（98%的肿瘤）、冗余的（平均肿瘤中至少有 4 个基因被删除），并且浆液性卵巢癌中的缺失独特地（比任何其他肿瘤类型都更能）被抑制。最有影响的丢失自噬基因是 BECN1 和 LC3B。我们发现BECN1和LC3B的损失对OV有贡献非整倍体和单等位基因 BECN1 缺失加速小鼠模型中 OV 肿瘤的发生。我们建议通过 [1] 分析超过 3,000 个肿瘤中的每个肿瘤的通路中断情况，加深我们对肿瘤 CNA 的理解使用自动化 HAPTRIG 生物信息学工具的已知分子途径，[2] 得分最具影响力每个通路/肿瘤对中的基因，以识别癌症的新 CNA 驱动因素，并 [3] 在用户中发布该工具任何肿瘤学家都可以对任何肿瘤队列进行 CNA 通路分析的友好门户。自从我们的顶来自 CNA 网络的预测经过验证可以影响基因组拷贝数变异性、肿瘤发生、和针对 OV 的治疗，我们建议通过 [1] 提供对 CNA 损失的进一步机制理解分析 BECN1 和 LC3B 缺失引起的 CNA 的类型和异质性，[2] 代谢、 BECN1+/- 鼠 OV 肿瘤中存在 CNA 和干细胞变化，以及 [3] 测定自噬通量和氯喹治疗的代谢改变，选择性杀死 BECN1 和 LC3B 耗尽的 OV 细胞。