Disease spectrum of gastric cancer susceptibility genes

McKinley, Sophia K.; Singh, Preeti; Yin, Kanhua; Wang, Jin; Zhou, June; Bao, Yujia; Wu, Menghua; Pathak, Kush; Mullen, John; Braun, Danielle; Hughes, Kevin S.

doi:10.1007/s12032-021-01495-w

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…After surgery, patients typically undergo a variety of treatments, such as chemoradiation and chemotherapy, in an effort to delay or eliminate the likelihood of a cancer returning [ 5 , 6 ]. Despite the fact that these treatments have led to an increase in patient survival rates, the overall survival rate for patients diagnosed with GC remains at roughly 30 percent worldwide [ 7 , 8 ]. Therefore, the purpose of our research was to investigate potential biomarkers for the prognostic evaluation of GC patients.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer

Huang

Zheng

et al. 2022

Disease Markers

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The prognosis of gastric cancer (GC) is difficult to predict due to the disease’s complex genetic and phenotypic characteristics. MUC16 has been reported to be involved in the progression of several tumors. In this study, we aimed to explore whether MUC16 mutation had any impact on the prognosis or treatments of GC patients. Additionally, this analysis uncovered possible critical pathways related with these systems. On the cBioPortal, we were able to locate the pertinent data of patients with MUC16 mutations. And then, GSEA analysis identified differences in mRNA levels between mutant and wild-type MUC16 patients in terms of biological function annotation and pathways. The KEGG and GO analyses were also performed using the differentially expressed genes (DEGs). There were 139 individuals with GC who had the MUC16 mutation, which accounts for 32 percent, and the remaining patients had the MUC16 wild type. Survival assays revealed that patients with the MUC16 mutation had longer overall survival and disease-free survival. GSEA analysis revealed that cell cycle, cysteine and methionine metabolism, Huntington’s disease, one carbon pool by folate, pyrimidine metabolism, pyruvate metabolism, RNA degradation, spliceosome, and valine leucine and isoleucine degradation were distinctly enriched in patients with MUC16 mutation type. Moreover, we identified 323 DEGs. Among them, 162 genes were upregulated, and 161 genes were downregulated. GO and KEGG assays indicated DEGs as enriched in pancreatic secretion, neuroactive ligand-receptor interaction, protein digestion and absorption, fat digestion and absorption, and glycerolipid metabolism. Overall, our data revealed that the MUC16 mutation in GC may affect the development of patients by altering several genes and pathways, indicating the importance of MUC16 mutation in the treatments of GC on an individual basis.

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Section: Introductionmentioning

confidence: 99%

Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer

Huang

Zheng

et al. 2022

Disease Markers

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“…A similar study found a total of 17 germline SMAD4 mutations and six large deletions in a cohort of 80 JPS patients, among these 11 were predicted to generate a truncated protein (30). Moreover, a systematic analysis identified SMAD4 as a GC susceptibility gene (31). Besides germinal alterations, somatic SMAD4 mutations are common among poorly cohesive gastric carcinoma patients (32).…”

Section: Discussionmentioning

confidence: 86%

Proteogenomic analysis in an early onset diffuse gastric cancer patient revealed alterations in PIK3R1, TP53, SMAD4 and a potential role of the PI3K-AKT and EGFR pathways: a case report

Córdova-Delgado¹,

Pinto²,

Pizarro³

et al. 2022

J Gastrointest Oncol

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Background: Early-onset gastric cancers (EOGC) are poor prognosis hard-to treat malignancies that affect young individuals (<45 years old).Case Description: Herein we describe the case of a 26-year-old female EOGC patient that initially displayed stable disease after first-line CAPOX plus immunotherapy. However, patient eventually developed progressive disease and was consecutively switched to paclitaxel plus ramucirumab, and palliative irinotecan.In search for therapeutic alternatives a proteo-genomic analysis was performed in a tissue biopsy taken after the first progression. Our analyses found a total of 18 somatic mutations, including TP53 and PIK3R1, and a previously unreported germline alteration in the tumor suppressor SMAD4. Also, our proteomic analysis found 62 proteins previously documented as "enriched in stomach cancer" and AKT/mTOR and EGFR as pathways with therapeutic potential. Unfortunately, the clinical utility of AKT/mTOR inhibitors or EGFR targeted therapies could not be assessed. Conclusions:As explained above EOGC is a growing health concern that affects young individuals.Furthermore, the reported case displayed a poor response to standard therapy including checkpoint inhibitors and chemotherapy despite the presence of biomarkers that predict a favorable outcome. Future studies should adopt alternative approaches to find novel, more effective therapies.

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“…In addition, a framework of the systematic review and verification of gene-disease associations has been developed [20]. Using this framework, we have examined all genes listed in the Ask2Me.org tool, verified over 500 gene-disease associations, and reported the disease spectra for breast, thyroid, and gastric cancer susceptibility genes [20][21][22][23]. Since users are not only interested in the commonly tested genes such as BRCA1/2, we plan to expand the Ask2Me.org tool to cover a broader range of genes, especially those with relatively low prevalence.…”

Section: Xsl • Fomentioning

confidence: 99%

Search Behavior Regarding Cancer Susceptibility Genes Using a Clinical Decision Support Tool for Gene-Specific Penetrance: Content Analysis

Yin¹,

Zhou²,

Singh³

et al. 2021

JMIR Cancer

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Background Genetic testing for germline cancer susceptibility genes is widely available. The Ask2Me.org (All Syndromes Known to Man Evaluator) tool is a clinical decision support tool that provides evidence-based risk predictions for individuals with pathogenic variants in cancer susceptibility genes. Objective The aim of this study was to understand the search behavior of the Ask2Me.org tool users, identify the patterns of queries entered, and discuss how to further improve the tool. Methods We analyzed the Ask2Me.org user-generated queries collected between December 12, 2018, and October 8, 2019. The gene frequencies of the user-generated queries were compared with previously published panel testing data to assess the correspondence between usage and prevalence of pathogenic variants. The frequencies of prior cancer in the user-generated queries were compared with the most recent US population–based cancer incidence. Results A total of 10,085 search queries were evaluated. The average age submitted in the queries was 48.8 (SD 16.5) years, and 84.1% (8478/10,085) of the submitted queries were for females. BRCA2 (1671/10,085, 16.6%), BRCA1 (1627/10,085, 16.1%), CHEK2 (994/10,085, 9.9%), ATM (662/10,085, 6.6%), and APC (492/10,085, 4.9%) were the top 5 genes searched by users. There was a strong linear correlation between genes queried by users and the frequency of pathogenic variants reported in published panel testing data (r=0.95, r2=0.90, P<.001). Over half of the queries (5343/10,085, 53.0%) included a prior personal history of cancer. The frequencies of prior cancers in the queries on females were strongly correlated with US cancer incidences (r=0.97, r2=0.95, P<.001), while the same correlation was weaker among the queries on males (r=0.69, r2=0.47, P=.02). Conclusions The patients entered in the Ask2Me.org tool are a representative cohort of patients with pathogenic variants in cancer susceptibility genes in the United States. While a majority of the queries were on breast cancer susceptibility genes, users also queried susceptibility genes with lower prevalence, which may represent a transformation from single gene testing to multigene panel testing. Owing to these changing tides, more efforts are needed to improve evidence-based clinical decision support tools to better aid clinicians and their practice.

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Disease spectrum of gastric cancer susceptibility genes

Cited by 9 publications

References 31 publications

Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer

Bioinformatics Analysis Based on TCGA: MUC16 Mutation Correlates with Clinical Outcome in Gastric Cancer

Proteogenomic analysis in an early onset diffuse gastric cancer patient revealed alterations in PIK3R1, TP53, SMAD4 and a potential role of the PI3K-AKT and EGFR pathways: a case report

Search Behavior Regarding Cancer Susceptibility Genes Using a Clinical Decision Support Tool for Gene-Specific Penetrance: Content Analysis

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