Copy Number Alterations in Low Mutation Cancer

低突变癌症中的拷贝数改变

• 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
• 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

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% 的缺失是杂合的，而不是纯合的。这剩下的99% 的缺失必须含有肿瘤抑制因子，这些肿瘤抑制因子仅在杂合子的情况下才有助于癌症进展 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 生物信息学工具对已知的分子途径进行评估，[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。