Abstract 236: Identification of novel cancer target genes by combining data from the cancer genome-wide association studies (GWAS), regulatory DNA elements and The Cancer Genome Atlas (TCGA)

2018 ◽  
Author(s):  
Diptee A. Kulkarni ◽  
Karl Guo ◽  
Junping Jing ◽  
Mugdha Khaladkar ◽  
Kijoung Song ◽  
...  
Keyword(s):  
Target Genes ◽  
Association Studies ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Combining Data ◽  
Dna Elements ◽  
Cancer Genome Atlas ◽  
Regulatory Dna

scholarly journals Detecting oncogenic selection through biased allele retention in The Cancer Genome Atlas

2020 ◽  
Author(s):  
Juliet Luft ◽  
Robert S. Young ◽  
Alison M. Meynert ◽  
Martin S. Taylor
Keyword(s):  
Association Studies ◽  
Strand Break ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Germline Variants ◽  
A Genome ◽  
Cancer Genome Atlas ◽  
Genome Atlas

AbstractBackgroundThe loss of genetic diversity in segments over a genome (loss-of-heterozygosity, LOH) is a common occurrence in many types of cancer. By analysing patterns of preferential allelic retention during LOH in approximately 10,000 cancer samples from The Cancer Genome Atlas (TCGA), we sought to systematically identify genetic polymorphisms currently segregating in the human population that are preferentially selected for, or against during cancer development.ResultsExperimental batch effects and cross-sample contamination were found to be substantial confounders in this widely used and well studied dataset. To mitigate these we developed a generally applicable classifier (GenomeArtiFinder) to quantify contamination and other abnormalities. We provide these results as a resource to aid further analysis of TCGA whole exome sequencing data. In total, 1,678 pairs of samples (14.7%) were found to be contaminated or affected by systematic experimental error. After filtering, our analysis of LOH revealed an overall trend for biased retention of cancer-associated risk alleles previously identified by genome wide association studies. Analysis of predicted damaging germline variants identified highly significant oncogenic selection for recessive tumour suppressor alleles. These are enriched for biological pathways involved in genome maintenance and stability.ConclusionsOur results identified predicted damaging germline variants in genes responsible for the repair of DNA strand breaks and homologous repair as the most common targets of allele biased LOH. This suggests a ratchet-like process where heterozygous germline mutations in these genes reduce the efficacy of DNA double-strand break repair, increasing the likelihood of a second hit at the locus removing the wild-type allele and triggering an oncogenic mutator phenotype.

scholarly journals Trait-associated noncoding variant regions affect TBX3 regulation and cardiac conduction

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Jan Hendrik van Weerd ◽  
Rajiv A Mohan ◽  
Karel van Duijvenboden ◽  
Ingeborg B Hooijkaas ◽  
Vincent Wakker ◽  
...  
Keyword(s):  
Association Studies ◽  
Cardiac Conduction ◽  
Regulatory Function ◽  
Genome Wide Association Studies ◽  
Gene Desert ◽  
Reporter Mice ◽  
Genome Wide ◽  
Pr Interval ◽  
Dna Elements ◽  
Regulatory Dna

Genome-wide association studies have implicated common genomic variants in the gene desert upstream of TBX3 in cardiac conduction velocity. Whether these noncoding variants affect expression of TBX3 or neighboring genes and how they affect cardiac conduction is not understood. Here, we use high-throughput STARR-seq to test the entire 1.3 Mb human and mouse TBX3 locus, including two cardiac conduction-associated variant regions, for regulatory function. We identified multiple accessible and functional regulatory DNA elements that harbor variants affecting their activity. Both variant regions drove gene expression in the cardiac conduction tissue in transgenic reporter mice. Genomic deletion from the mouse genome of one of the regions caused increased cardiac expression of only Tbx3, PR interval shortening and increased QRS duration. Combined, our findings address the mechanistic link between trait-associated variants in the gene desert, TBX3 regulation and cardiac conduction.

scholarly journals Generalizability of Associations from Prostate Cancer Genome-Wide Association Studies in Multiple Populations

2009 ◽  
Vol 18 (4) ◽  
pp. 1285-1289 ◽  
Author(s):  
Kevin M. Waters ◽  
Loic Le Marchand ◽  
Laurence N. Kolonel ◽  
Kristine R. Monroe ◽  
Daniel O. Stram ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Association Studies ◽  
Cancer Genome ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Populations ◽  
Genome Wide

scholarly journals Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers

2013 ◽  
Vol 34 (7) ◽  
pp. 1520-1528 ◽  
Author(s):  
Y. Zheng ◽  
T. O. Ogundiran ◽  
A. G. Falusi ◽  
K. L. Nathanson ◽  
E. M. John ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fine Mapping ◽  
Association Studies ◽  
African Ancestry ◽  
Cancer Genome ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Addressing the Missing Heritability Problem With the Help of Regulatory Features

2019 ◽  
Vol 15 ◽  
pp. 117693431986086
Author(s):  
Shan-Shan Dong ◽  
Yan Guo ◽  
Tie-Lin Yang
Keyword(s):  
Target Genes ◽  
Association Studies ◽  
Complex Diseases ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Susceptibility Loci ◽  
Missing Heritability ◽  
Genome Wide ◽  
Missing Heritability Problem

Genome-wide association studies (GWASs) have successfully identified thousands of susceptibility loci for human complex diseases. However, missing heritability is still a challenging problem. Considering most GWAS loci are located in regulatory elements, we recently developed a pipeline named functional disease-associated single-nucleotide polymorphisms (SNPs) prediction (FDSP), to predict novel susceptibility loci for complex diseases based on the interpretation of regulatory features and published GWAS results with machine learning. When applied to type 2 diabetes and hypertension, the predicted susceptibility loci by FDSP were proved to be capable of explaining additional heritability. In addition, potential target genes of the predicted positive SNPs were significantly enriched in disease-related pathways. Our results suggested that taking regulatory features into consideration might be a useful way to address the missing heritability problem. We hope FDSP could offer help for the identification of novel susceptibility loci for complex diseases.

scholarly journals Challenges and progress in interpretation of non-coding genetic variants associated with human disease

2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Genome Wide ◽  
Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

scholarly journals Cross-cancer genome-wide association study of endometrial cancer and epithelial ovarian cancer identifies genetic risk regions associated with risk of both cancers

2020 ◽  
Author(s):  
Dylan M. Glubb ◽  
Deborah J. Thompson ◽  
Katja K.H. Aben ◽  
Ahmad Alsulimani ◽  
Frederic Amant ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Endometrial Cancer ◽  
Epithelial Ovarian Cancer ◽  
Genetic Correlation ◽  
Target Genes ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Molecular Features ◽  
Genome Wide

AbstractAccumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

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