Whole-exome sequencing identifies prognostic mutational signatures in gastric cancer

Zhu, Zhenxin; Fu, Hongbing; Wang, Shengzhou; Yu, Xinxin; You, Qi; Shi, Mengyao; Dai, Chun; Wang, Guan; Cha, Wei; Wang, Weimin

doi:10.21037/atm-20-6620

Cited by 13 publications

(15 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pseudogene UBE2MP1 was found to have a significant expression-methylation-correlation difference between normal and cancerous breast tissue [53]. UBE2MP1 was also found to be amplified in gastric cancers with amplified copy number variations in the 16p11.2 region, a mutation found to be associated with shorter overall survival [57], and was predicted to be a driver of lung adenocarcinoma [56].…”

Section: Novel Findings By Tigarmentioning

confidence: 98%

“…TIGAR identified 3 novel independent TWAS risk genes (KLHL25, UBE2MP1, and FRG1EP ) for breast cancer. Gene KLHL25 has known biological functions involved in carcinogenesis, while genes UBE2MP1 and FRG1EP are near such a gene [53][54][55][56][57].…”

Section: Novel Findings By Tigarmentioning

confidence: 99%

“…Novel findings by TIGAR TIGAR identified 3 novel independent TWAS risk genes (KLHL25, UBE2MP1, and FRG1EP) for breast cancer. Gene KLHL25 has known biological functions involved in carcinogenesis, while genes UBE2MP1 and FRG1EP are near such a gene [62][63][64][65][66] . Interestingly, genes UBE2MP1 and FRG1EP were also identified for ovarian cancer by TIGAR (Table 2), and all three genes are involved with biological functions in carcinogenesis, either directly or indirectly.…”

Section: Twas Of Breast and Ovarian Cancermentioning

confidence: 99%

See 2 more Smart Citations

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

Parrish

Gibson

Epstein

et al. 2021

Preprint

View full text Add to dashboard Cite

Standard Transcriptome-Wide Association Study (TWAS) methods first train gene expression prediction models using reference transcriptomic data, and then test the association between the predicted genetically regulated gene expression and phenotype of interest. Most existing TWAS tools require cumbersome preparation of genotype input files and extra coding to enable parallel computation. To improve the efficiency of TWAS tools, we develop TIGAR-V2, which directly reads VCF files, enables parallel computation, and reduces up to 90% computation cost compared to the original version. TIGAR-V2 can train gene expression imputation models using either nonparametric Bayesian Dirichlet Process Regression (DPR) or Elastic-Net (as used by PrediXcan), perform TWAS using either individual-level or summary-level GWAS data, and implements both burden and variance-component test statistics for inference. We trained gene expression prediction models by DPR for 49 tissues using GTEx V8 by TIGAR-V2 and illustrated the usefulness of these nonparametric Bayesian DPR eQTL weights through TWAS of breast and ovarian cancer utilizing public GWAS summary statistics. We identified 88 and 37 risk genes respectively for breast and ovarian cancer, most of which are either known or near previously identified GWAS (~95%) or TWAS (~40%) risk genes of the corresponding phenotype and three novel independent TWAS risk genes with known functions in carcinogenesis. These findings suggest that TWAS can provide biological insight into the transcriptional regulation of complex diseases. TIGAR-V2 tool, trained Bayesian cis-eQTL weights, and LD information from GTEX V8 are publicly available, providing a useful resource for mapping risk genes of complex diseases.

show abstract

Section: Novel Findings By Tigarmentioning

confidence: 98%

Section: Novel Findings By Tigarmentioning

confidence: 99%

Section: Twas Of Breast and Ovarian Cancermentioning

confidence: 99%

See 1 more Smart Citation

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

Parrish

Gibson

Epstein

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Hereditary stomach cancer is associated with mutations in the CDH1 gene and it is also manifested in Lynch (hereditary nonpolyposis colorectal cancer) syndrome related to mutations in mismatch repair genes [45][46][47][48]. Next-generation sequencing studies have identified rare germline variants in several other genes, including BRCA2 and other DNA repair genes [49][50][51]. In kidney cancer, the contribution of von Hippel-Lindau syndrome is a likely explanation for the early onset risk component [52].…”

Section: Genetic Implicationsmentioning

confidence: 99%

Familial Risks and Proportions Describing Population Landscape of Familial Cancer

Hemminki

Sundquist

et al. 2021

Cancers

View full text Add to dashboard Cite

Background: Familial cancer can be defined through the occurrence of the same cancer in two or more family members. We describe a nationwide landscape of familial cancer, including its frequency and the risk that it conveys, by using the largest family database in the world with complete family structures and medically confirmed cancers. Patients/methods: We employed standardized incidence ratios (SIRs) to estimate familial risks for concordant cancer among first-degree relatives using the Swedish Cancer Registry from years 1958 through 2016. Results: Cancer risks in a 20–84 year old population conferred by affected parents or siblings were about two-fold compared to the risk for individuals with unaffected relatives. For small intestinal, testicular, thyroid and bone cancers and Hodgkin disease, risks were higher, five-to-eight-fold. Novel familial associations included adult bone, lip, pharyngeal, and connective tissue cancers. Familial cancers were found in 13.2% of families with cancer; for prostate cancer, the proportion was 26.4%. High-risk families accounted for 6.6% of all cancer families. Discussion/Conclusion: High-risk family history should be exceedingly considered for management, including targeted genetic testing. For the major proportion of familial clustering, where genetic testing may not be feasible, medical and behavioral intervention should be indicated for the patient and their family members, including screening recommendations and avoidance of carcinogenic exposure.

show abstract

“… 11–14 Next-generation sequencing studies have identified rare germline variants in several other genes, including BRCA2 and many other DNA repair genes. 15–17 …”

Section: Introductionmentioning

confidence: 99%

Second Primary Cancers After Gastric Cancer, and Gastric Cancer as Second Primary Cancer

Zheng

Sundquist

Sundquist³

et al. 2021

CLEP

View full text Add to dashboard Cite

Background Second primary cancers (SPCs) are increasing, which may negatively influence patient survival. Gastric cancer (GC) has poor survival and when it is diagnosed as SPC it is often the cause of death. We wanted to analyze the risk of SPCs after GC and the risk of GC as SPC after any cancer. Such bidirectional analysis is important in relation to fatal cancers because SPCs may be under-reported in the short-term survival period. Methods Cancers were obtained from the Swedish Cancer Registry from years 1990 through 2015. Standardized incidence ratios (SIRs) were used to estimate bidirectional relative. Results We identified 23,137 GC patients who developed 1042 SPCs (4.5%); 2158 patients had GC as SPC. While the risk for three SPCs was increased after GC, seven first primary cancers were followed by an increased risk of GC as SPC, including esophageal, colorectal, bladder, squamous cell skin and breast cancers and non-Hodgkin lymphoma. Breast cancer, which was followed by a diagnosis of second GC, showed an excess of lobular histology. Conclusion Multiple primary cancers in the same individuals may signal genetic predisposition. Accordingly, the association of GC with breast cancer may be related to mutations in the CDH1 gene, and clustering of colorectal, small intestinal and bladder cancers could be related to Lynch syndrome. The third line of findings supports a contribution of immune dysfunction on the increased risk of GC as SPC after skin cancer and non-Hodgkin lymphoma. Early detection of GC in the risk groups could save lives.

show abstract

Whole-exome sequencing identifies prognostic mutational signatures in gastric cancer

Cited by 13 publications

References 44 publications

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

TIGAR-V2: Efficient TWAS Tool with Nonparametric Bayesian eQTL Weights of 49 Tissue Types from GTEx V8

Familial Risks and Proportions Describing Population Landscape of Familial Cancer

Second Primary Cancers After Gastric Cancer, and Gastric Cancer as Second Primary Cancer

Contact Info

Product

Resources

About