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 两种一般类型的遗传改变推动了癌症的进展。突变和拷贝数更改 （CNA）。对这种ABL融合和BRAF的突变的研究产生了有力的靶向治疗剂。 但是，并非所有癌症都在靶向基因中突变。 48％的浆液卵巢癌（OV）没有 p53以外的致癌突变。对于这些低女人的肿瘤和癌症类型，最可能是罪魁祸首 对于肿瘤发生和耐药性，CNA中。 OV基因组非常不稳定。平均 肿瘤，2/3的基因显示拷贝数更改：删除了大约1/3，基因中有1/3增加 剂量。卵巢癌中的一个已知CNA驱动器是BRCA1/2基因的纯合损失。 患者;但是，SOC中99％的缺失是杂合的，而不是纯合缺失。这还剩下99％ 缺失的缺失必须包含抑制肿瘤，这些肿瘤抑制因子仅用杂合而导致癌症进展 损失，沿单个路径积累。我们开发了新颖的“ haptrig”途径分析 整个基因组数据集中的损失事件具有在OV等高度变化的背景中工作的能力 一次执行多个途径的计算。我们发现细胞回收途径 自噬是普遍的（占肿瘤的98％），冗余（在平均肿瘤中删除了至少4个基因），并且 在浆液卵巢癌中缺失所抑制的独特（比其他任何其他肿瘤类型）。最多 有影响力的自噬基因是BECN1和LC3B。我们发现BECN1和LC3B损失将有助于OV 在小鼠模型中加速OV肿瘤发生的非整倍性和单链状BECN1损失。我们建议 通过[1]分析> 3,000中的途径中断的每个肿瘤，从而发展我们对肿瘤CNA的理解 使用自动HAPTRIG生物信息学工具的已知分子途径[2]得分最大 每个途径/肿瘤对中的基因以鉴定癌症的新型CNA驱动因素，[3]在用户中释放工具 - 友好的门户网站供任何肿瘤科医生对任何肿瘤队列进行CNA途径分析。自从我们的顶部 对CNA网络的预测进行了验证，以影响基因组拷​​贝数的变异性，肿瘤发生， 和OV中的治疗靶向，我们建议通过[1]提供对CNA损失的进一步机械理解。 分析由BECN1和LC3B耗竭引起的CNA的类型和异质性，[2]代谢， BECN1 +/-鼠OV肿瘤中存在的CNA和干细胞变化，[3]分析自噬通量和 氯喹疗法的代谢改变，有选择地杀死BECN1和LC3B耗尽的OV细胞。