Dataset Information

Validation of a Blood Biomarker for Identification of Individuals at High Risk for Gastric Cancer.

ABSTRACT: BACKGROUND:Helicobacter pylori is the leading cause of gastric cancer, yet the majority of infected individuals will not develop neoplasia. Previously, we developed and replicated serologic H. pylori biomarkers for gastric cancer risk among prospective cohorts in East Asia and now seek to validate the performance of these biomarkers in identifying individuals with premalignant lesions. METHODS:This cross-sectional study included 1,402 individuals from Linqu County screened by upper endoscopy. H. pylori protein-specific antibody levels were assessed using multiplex serology. Multivariable-adjusted logistic regression models were used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for prevalent intestinal metaplasia, indefinite dysplasia, or dysplasia, compared with superficial or mild atrophic gastritis. RESULTS:Compared with individuals seronegative to Omp and HP0305, individuals seropositive to both were seven times more likely to have precancerous lesions (OR, 7.43; 95% CI, 5.59-9.88). A classification model for precancerous lesions that includes age, smoking, and seropositivity to H. pylori, Omp, and HP0305 resulted in an area under the curve (AUC) of 0.751 (95% CI, 0.725-0.777), which is significantly better than the same model, including the established gastric cancer risk factor CagA (AUC, 0.718; 95% CI, 0.691-0.746, P difference = 0.0002). CONCLUSIONS:The present study of prevalent precancerous gastric lesions provides support for two new serum biomarkers of gastric cancer risk, Omp and HP 0305. IMPACT:Our results support further research into the serological biomarkers Omp and HP0305 as possible improvements over the established virulence marker CagA for identifying individuals with precancerous lesions in East Asia.

SUBMITTER: Epplein M

PROVIDER: S-EPMC6279536 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Validation of a Blood Biomarker for Identification of Individuals at High Risk for Gastric Cancer.

Epplein Meira M Butt Julia J Zhang Yang Y Hendrix Laura H LH Abnet Christian C CC Murphy Gwen G Zheng Wei W Shu Xiao-Ou XO Tsugane Shoichiro S Qiao You-Lin YL Taylor Philip R PR Shimazu Taichi T Yoo Keun-Young KY Park Sue K SK Kim Jeongseon J Jee Sun Ha SH Waterboer Tim T Pawlita Michael M You Wei-Cheng WC Pan Kai-Feng KF

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20180829 12

<h4>Background</h4><i>Helicobacter pylori</i> is the leading cause of gastric cancer, yet the majority of infected individuals will not develop neoplasia. Previously, we developed and replicated serologic <i>H. pylori</i> biomarkers for gastric cancer risk among prospective cohorts in East Asia and now seek to validate the performance of these biomarkers in identifying individuals with premalignant lesions.<h4>Methods</h4>This cross-sectional study included 1,402 individuals from Linqu County sc ...[more]

PMID: 30158280

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Project description:ObjectiveTo screen and characterize germline variants for E-cadherin (CDH1) in non-hereditary gastric cancer (GC) patients and in subjects at risk of GC.Methods59 GCs, 59 first degree relatives (FDRs) of GC, 20 autoimmune metaplastic atrophic gastritis (AMAGs) and 52 blood donors (BDs) were analyzed for CDH1 by direct sequencing, structural modelling and bioinformatics. Functional impact on splicing was assessed for intronic mutations. E-cadherin/β-catenin immunohistochemical staining and E-cadherin mRNA quantification using RT-PCR were performed.ResultsIn GCs, 4 missense variants (p.G274S; p.A298T; p.T470I; p.A592T), 1 mutation in the 5'UTR (-71C>G) and 1 mutation in the intronic IVS12 (c.1937-13T>C) region were found. First pathogenic effect of p.A298T mutation was predicted by protein 3D modelling. The novel p.G274S mutation showed a no clear functional significance. Moreover, first, intronic IVS12 (c.1937-13T>C) mutation was demonstrated to lead to an aberrant CDH1 transcript with exon 11 deletion. This mutation was found in 2 GCs and in 1 BD. In FDRs, we identified 4 variants: the polymorphic (p.A592T) and 3 mutations in untranslated regions with unidentified functional role except for the 5'UTR (-54G>C) that had been found to decrease CDH1 transcription. In AMAGs, we detected 2 alterations: 1 missense (p.A592T) and 1 novel variant (IVS1 (c.48+7C>T)) without effect on CDH1 splicing. Several silent and polymorphic substitutions were found in all the groups studied.ConclusionsOverall our study improves upon the current characterization of CDH1 mutations and their functional role in GC and in individuals at risk of GC. Mutations found in untranslated regions and data on splicing effects deserve a particular attention like associated with a reduced E-cadherin amount. The utility of CDH1 screening, in addition to the identification of other risk factors, could be useful for the early detection of GC in subjects at risk (i.e. FDRs and AMAGs), and warrants further study.

Project description:BackgroundThe number of individuals meeting criteria for genetic counseling and testing for hereditary cancer syndromes (HCS) is far less than the number that actually receive it. To facilitate identification of patients at risk for HCS, Counsyl developed a digital identification tool (digital ID tool) to match personal and family cancer history to National Comprehensive Cancer Network (NCCN) BRCA-related Hereditary Breast and Ovarian Cancer (HBOC), Lynch syndrome, and polyposis testing criteria in one-to-one, automated fashion. The purpose of this study was to validate the ability of the digital ID tool to accurately identify histories that do and do not meet NCCN testing criteria.MethodsThird-party recorded three-generation pedigrees were retrospectively reviewed by a certified genetic counselor (CGC) to determine if independent events included in pedigree histories met NCCN guidelines, and were then sorted into groups: high risk events (meets criteria) and low risk events (does not meet criteria). Events were entered into the digital ID tool to determine the extent of its concordance with events sorted by CGC review. Statistical tests of accuracy were calculated at a 95% confidence interval (CI).ResultsOne hundred ninety-seven pedigrees were reviewed consecutively representing 765 independent events for analysis across groups. 382/382 (100%) high risk events identified by the digital ID tool and 381/383 (99.47%) low risk events identified by the digital ID tool were concordant with CGC sorting. The digital ID tool had a sensitivity of 100% (99.04-100% CI) and specificity of 99.48% (98.13-99.94% CI). The overall accuracy of the digital ID tool was estimated to be 99.74% (99.06-99.97% CI), reflecting the rate at which the digital ID tool reached the same conclusion as that of CGC review of pedigree events for the recommendation of genetic testing for individuals at risk for HCS.ConclusionsThe digital ID tool accurately matches NCCN criteria in one-to-one fashion to identify at-risk individuals for HCS and may be useful in clinical practice, specifically for BRCA-related HBOC and Lynch Syndrome.

Project description:BackgroundOver the last few years, great progress has been made in the development of key technologies to detect peripheral blood-based, tumor-specific biomarkers, such as circulating tumor cells (CTCs) and circulating cell free tumor DNA (ctDNA). Despite the considerable advances and their multiple clinical values, liquid biopsies are challenged by the very low concentrations of CTCs and ctDNA in blood samples. Additionally, blood biomarkers which were found using data-driven methods may only be effective in few datasets.MethodsWe firstly collected the genes which have expression correlations between blood and the other tissues/organs using Genotype-Tissue Expression (GTEx). Survival hazard genes and differential expression genes of each cancer type in The Cancer Genome Atlas (TCGA) were then selected by Cox regression model and Wilcoxon rank sum test, respectively. By combining the P values of two steps, several blood biomarkers can be inferred for each cancer type. After applying these potential blood biomarker sets to 13 datasets of blood samples from solid tumor patients using single sample gene set enrichment analyses (ssGSEA), we got an enrichment score (ES) for each sample.ResultsThe inferred blood biomarker (BB infer) genes showed reliable predictive value in various malignancies. In all the blood samples that were analyzed, the ESs of positive BB Infer genes in cancer patients are higher than healthy people. Conversely, the ESs of negative BB Infer genes in cancer patients are lower than healthy people. Furthermore, lower ES of negative BB infer genes signify the dismal outcome of patients.ConclusionsWe developed a novel solid tumor blood biomarker inference workflow for cancer screening and diagnosis. Moreover, we demonstrated the utility of this inference method in a series of blood sample datasets of solid tumor patients. These results suggested the potential value of this method in the screening, diagnosis and prognosis of cancers.

Dataset Information

Validation of a Blood Biomarker for Identification of Individuals at High Risk for Gastric Cancer.

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Validation of a Blood Biomarker for Identification of Individuals at High Risk for Gastric Cancer.

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