Purpose Gastric cancer is a commonly occurring cancer in Asia and one of the leading causes of cancer deaths. However, there is no reliable blood-based screening test for this cancer. Identifying proteins secreted from tumor cells could lead to the discovery of clinically useful biomarkers for early detection of gastric cancer. Experimental design A SILAC-based quantitative proteomic approach was employed to identify secreted proteins that were differentially expressed between neoplastic and non-neoplastic gastric epithelial cells. Proteins from the secretome were subjected to SDS-PAGE and SCX-based fractionation, followed by mass spectrometric analysis on an LTQ-Orbitrap Velos mass spectrometer. Immunohistochemical labeling was employed to validate a subset of candidates using tissue microarrays. Results We identified 2,205 proteins in the gastric cancer secretome of which 263 proteins were overexpressed >4-fold in gastric cancer-derived cell lines as compared to non-neoplastic gastric epithelial cells. Three candidate proteins, proprotein convertase subtilisin/kexin type 9 (PCSK9), lectin mannose binding 2 (LMAN2) and PDGFA associated protein 1 (PDAP1), were validated by immunohistochemical labeling. Conclusions and clinical relevance We report here the largest cancer secretome described to date. The novel biomarkers identified in the current study are excellent candidates for further testing as early detection biomarkers for gastric adenocarcinoma.

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Severe acute respiratory syndrome involving corona virus-2 (SARS-CoV-2) has been implied to cause COVID-19 disease, leading to an unprecedented health emergency across the globe with a staggering figure of mortality rate. Measures to control the pandemic are pushing the economy into a tailspin, putting burden not only on the individuals but also on the nations. Despite the widespread infection rates, young people have shown better recovery rate while COVID-19 symptoms are more pronounced in elderly and people with comorbid conditions such as diabetes, cardiac and respiratory diseases. Cancer is a highly prevalent disease affecting millions of individuals. In this study, we analyzed the expression status of genes that are required for SARS-CoV-2 infectivity and its propagation to assess the susceptibility of certain cancer patients to infection and subsequent complications. Our data indicate that patients with colon, rectum, cholangiocarcinoma, lung adenoma, kidney renal papillary cell carcinoma and kidney renal clear cell carcinoma are more at risk for COVID-19. Genes that are responsible for severe COVID-19 are also highly expressed in many cancer types. We also carried out the association rule mining analysis which is helpful in predicting the expression of proviral genes in various cancers.