No abstract

Mosaic loss of Chromosome Y (LOY) is a common acquired structural mutation in the leukocytes of aging men that is correlated with several age-related diseases including Alzheimer's disease (AD). The molecular basis of LOY in brain cells has not been systematically investigated. Here, we present a large-scale analysis of single-cell and single-nuclei RNA brain datasets, yielding 851,674 cells, to investigate the cell type–specific burden of LOY. LOY frequencies differed widely between donors and CNS cell types. Among five well-represented neural cell types, LOY was enriched in microglia and rare in neurons, astrocytes, and oligodendrocytes. In microglia, LOY was significantly enriched in AD subjects. Differential gene expression (DE) analysis in microglia found 172 autosomal genes, 3 X-linked genes, and 10 pseudoautosomal genes associated with LOY. To our knowledge, we provide the first evidence of LOY in the microglia, and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.

Summary Despite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants remains challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, genetic data, and allele-specific gene expression from TCGA, we identified 320 somatic non-coding mutations that affect gene expression in cis (FDR<0.25). These mutations cluster into 47 cis-regulatory elements that modulate expression of their subject genes through diverse molecular mechanisms. We further show that these mutations have hallmark features of non-coding drivers; namely, that they preferentially disrupt transcription factor binding motifs, are associated with a selective advantage, increased oncogene expression and decreased tumor suppressor expression.

39Despite the recent availability of complete genome sequences of tumors from thousands of 40 patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic 41 variants is notoriously challenging, and only a handful of validated examples exist. By integrating 42 whole-genome sequencing, gene expression, chromatin accessibility, and genetic data from 43 TCGA, we identified 301 non-coding somatic mutations that affect gene expression in cis. These 44 mutations cluster into 36 hotspot regions with diverse molecular mechanisms of gene expression 45 regulation. We further show that these mutations have hallmark features of noncoding drivers; 46

Cancer cell lines have numerous characteristics that make them favorable pre-clinical research models, yet they are notoriously poor at predicting drug response in the clinic. Here we sought to investigate the utility of synthetic lethality (SL) interactions discovered from large-scale CRISPR functional screens (i.e. the BROAD and Sanger Cancer Dependency Maps or "DepMap") as predictors of targets that validate in patients. Mutual exclusivity, the phenomenon where two genes are rarely mutated together in the same tumor, is a powerful clinical-stage readout that can be caused by synthetic lethality. We found that SL interactions discovered in DepMap are significantly more likely to be mutually exclusive in TCGA when they include a driver (tumor-suppressor/oncogene). These SL interactions represent high-value targeting opportunities with the advantage of clear patient selection criteria based on their driver mutation status. In an effort to identify drugs that target these proteins as potential repurposing opportunities, we found that pharmacogenomic inhibition rarely invokes the same target dependencies as a genetic deletion of the drug target. Nonetheless, we identified several dozen "clean" drugs with potential for repositioning and validated the top candidates in PDx. Although tumours are more heterogenous than cancer cell lines, we show that cell line viability readouts linked to single-gene/drug perturbations can yield accurate predictions of clinical efficacy when tied to tumor-driver biology. Citation Format: Tomas Babak, Michael Vermeulen, Doris Coto Villa, Andrew Craig. Driver-gene dependencies reveal clinically actionable drug repositioning opportunities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4035.

No abstract

No abstract

Mosaic loss of chromosome Y (LOY) is a particularly common acquired structural mutation in the leukocytes of aging men and it has been shown to correlate with several age-related diseases including Alzheimer’s disease (AD). To derive the molecular basis of LOY in brain cells, we create an integrated resource by aggregating data from 21 single-cell and single-nuclei RNA brain studies, yielding 763,410 cells to investigate the presence and cell-type specific burden of LOY. We created robust quantification metrics for assessing LOY, which were validated using a multi-modal dataset. Using this new resource and LOY-quantification approach, we found that LOY frequencies differed widely between CNS cell-types and individual donors. Among five common neural cell types, microglia were most affected by LOY (7.79%, n=41,949), while LOY in neurons was rare (0.48%, n=220,010). Differential gene expression analysis in microglia found 188 autosomal genes, 6 X-linked genes, and 11 pseudoautosomal genes, pointing to broad dysregulation in lipoprotein metabolism, inflammatory response, and antigen processing that coincides with loss of Y. To our knowledge, we provide the first evidence of LOY in the microglia, and highlight its potential roles in aging and the pathogenesis of neurodegenerative disorders such as AD.