Comprehensive analysis of CPNE1 predicts prognosis and drug resistance in gastric adenocarcinoma.

BACKGROUND: Recent studies have confirmed that Copines-1 (CPNE1) is associated with many malignancies. However, the role of CPNE1 in stomach adenocarcinoma (STAD) is currently unclear. METHODS: TIMER2.0, TCGA, UALCAN databases were used to investigate the expression of CPNE1 in STAD and normal tissues. KM-plotter database was used to explore the relationship between CPNE1 expression and prognosis in STAD. Immunohistochemistry (IHC) was used to assess the protein levels of CPNE1 in both normal and cancer tissues, as well as to confirm the prognostic significance of CPNE1. In order to assess the viability of CPNE1 as a divider, the Recipient Operating Characteristics (ROC) curve was employed and the assessment based on the AUC score (below the curve). To investigate the potential function of CPNE1, correlation analysis and enrichment analysis were performed with the clusterProfiler package in R software. The CPNE1 binding protein network was constructed by STRING and GeneMANIA. The relationship between methylation and prognosis was explored by Methsurv database. The Genomics of Drug Sensitivity in Cancer (GDSC) was employed to predict drug responsiveness in STAD. Ultimately, CCK-8 assays and RT-qPCR were performed to confirm the correlation between CPNE1 expression and the IC50 of Axitinib in the AGS cell line. RESULT: CPNE1 is highly expressed in various cancers, including STAD. High expression of CPNE1 indicated poor overall survival (OS) of STAD (P < 0.05). The ROC curve suggested that CPNE1 was a potential diagnostic biomarker (AUC = 0.925). The functions of CPNE1 were enriched in DNA-acting catalytic activity, sulfur transferase activity, Ran GTPase binding, DNA helicase activity, helicase activity and eukaryotic ribosome biosynthesis. Hyper-methylated CPNE1 predicts better prognosis in STAD (P < 0.05). Additionally, STAD patients with high-expression CPNE1 seemed to be more resistant to the chemotherapeutic agents, including A-770041, WH-4-023, AZD-2281, AG-014699, AP-24534, Axitinib, AZD6244, RDEA119, AZD8055, Temsirolimus, Pazopanib and Roscovitine. In vitro experiments demonstrated the involvement of CPNE1 in Axitinib chemoresistance. CONCLUSION: CPNE1 could be a predictive biomarker and a potential target for biological therapy in STAD.

SLAMF8 can predict prognosis of pan-cancer and the immunotherapy response effectivity of gastric cancer.

SLAMF8, the eighth member of the Signaling Lymphocytic Activation Molecule Family (SLAMF), functions in the regulation of the development and activity of diverse immune cells as a costimulatory receptor within the SLAMF family. Studies had revealed that SLAMF8 is expressed higher in several autoimmune inflammation diseases and tumors. Nevertheless, the connection between SLAMF8 and pan-cancer remains undisclosed. The research investigated the correlation between SLAMF8 and various factors including the immune microenvironment, microsatellite instability, immune novel antigen, gene mutation, immune regulatory factors, immune blockade TMB, and immune or molecular subtypes of SLAMF8 in verse cancer types. Immunohistochemistry was ultimately employed to validate the presence of the SLAMF8 gene in various tumor types including hepatocellular carcinoma, prostate adenocarcinoma, and kidney renal clear cell carcinoma. Furthermore, the relationship between SLAMF8 expression and the therapeutic efficacy of the PD1 blockade agent, Sintilimab, treatment in gastric cancer was validated. The result of differential analysis suggested that SLAMF8 was over-expressed in pan-cancer compared with paracancerous tissues. The analysis of survival indicated a connection between SLAMF8 and the overall prognosis in different types of cancers, where higher levels of SLAMF8 were found to be significantly linked to unfavorable outcomes in patients but favorable outcome of immunotherapy in gastric cancer. Significant correlations were observed between SLAMF8 levels and pan-cancer tumorigenesis, tumor metabolism, and immunity. As a result, SLAMF8 may become an important prognostic biomarker in the majority of tumors and a hopeful gene target for immunotherapy against gastric cancer.

Establishment of the molecular subtypes and a risk model for stomach adenocarcinoma based on genes related to reactive oxygen species.

Background: Oxidative stress promotes the development of stomach adenocarcinoma (STAD) and resistance of STAD patients to chemotherapy. This study developed a risk classification and prognostic model for STAD based on genes related to oxidative stress. Methods: Univariate Cox regression and least absolute shrinkage and selection operator (Lasso) regression analysis were performed using transcriptome data of STAD from The Cancer Genome Atlas (TCGA) and reactive oxygen species (ROS)-related genes from Gene Set Enrichment Analysis (GSEA) website to develop a risk model. Genetic landscape, pathway characteristics and immune characteristics between the two risk groups were assessed to evaluate patients' response to anti-tumor therapy. Further, a nomogram was created to evaluate the clinical outcomes of STAD patients. The mRNA levels of genes were detected by reverse transcription quantitative PCR (RT-qPCR). Results: Two ROS-related molecular subtypes (subtype C1 and C2) were classified, with subtype C2 having unfavorable prognosis, higher immune score, and greater infiltration of macrophages, myeloid-derived suppressor cells (MDSCs), mast cells, regulatory T cells, and C-C chemokine receptor (CCR). Five ROS-related genes (ASCL2, COMP, NOX1, PEG10, and VPREB3) were screened to develop a prognostic model, the robustness of which was validated in TCGA and external cohorts. RT-qPCR analysis showed that ASCL2, COMP, NOX1, and PEG10 were upregulated, while the mRNA level of VPREB3 was downregulated in gastric cancer cells. The risk score showed a negative relation to tumor mutation burden (TMB). Low-risk patients exhibited higher mutation frequencies of TTN, SYNE1, and ARID1A, higher response rate to immunotherapy and were more sensitive to 32 traditional chemotherapeutic drugs, while high-risk patients were sensitive to 13 drugs. Calibration curve and DCA confirmed the accuracy and reliability of the nomogram. Conclusion: These findings provided novel understanding on the mechanism of ROS in STAD. The current study developed a ROS-related signature to help predict the prognosis of patients suffering from STAD and to guide personalized treatment.