Overexpression of COX7A1 Promotes the Resistance of Gastric Cancer to Oxaliplatin and Weakens the Efficacy of Immunotherapy.

Gastric cancer (GC) is one of the most common clinical malignant tumors worldwide, with high morbidity and mortality. Presently, the overall response rate to immunotherapy is low, and current methods for predicting the prognosis of GC are not optimal. Therefore, novel biomarkers with accuracy, efficiency, stability, performance ratio, and wide clinical application are needed. Based on public data sets, the chemotherapy cohort and immunotherapy cohort from Sun Yat-sen University Cancer Center, a series of bioinformatics analyses, such as differential expression analysis, survival analysis, drug sensitivity prediction, enrichment analysis, tumor immune dysfunction and exclusion analysis, single-sample gene set enrichment analysis, stemness index calculation, and immune cell infiltration analysis, were performed for screening and preliminary exploration. Immunohistochemical staining and in vitro experiments were performed for further verification. Overexpression of COX7A1 promoted the resistance of GC cells to Oxaliplatin. COX7A1 may induce immune escape by regulating the number of fibroblasts and their cellular communication with immune cells. In summary, measuring the expression levels of COX7A1 in the clinic may be useful in predicting the prognosis of GC patients, the degree of chemotherapy resistance, and the efficacy of immunotherapy.

Construction of a gene model related to the prognosis of patients with gastric cancer receiving immunotherapy and exploration of COX7A1 gene function.

BACKGROUND: GC is a highly heterogeneous tumor with different responses to immunotherapy, and the positive response depends on the unique interaction between the tumor and the tumor microenvironment (TME). However, the currently available methods for prognostic prediction are not satisfactory. Therefore, this study aims to construct a novel model that integrates relevant gene sets to predict the clinical efficacy of immunotherapy and the prognosis of GC patients based on machine learning. METHODS: Seven GC datasets were collected from the Gene Expression Omnibus (GEO) database, The Cancer Genome Atlas (TCGA) database and literature sources. Based on the immunotherapy cohort, we first obtained a list of immunotherapy related genes through differential expression analysis. Then, Cox regression analysis was applied to divide these genes with prognostic significancy into protective and risky types. Then, the Single Sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to score the two categories of gene sets separately, and the scores differences between the two gene sets were used as the basis for constructing the prognostic model. Subsequently, Weighted Correlation Network Analysis (WGCNA) and Cytoscape were applied to further screen the gene sets of the constructed model, and finally COX7A1 was selected for the exploration and prediction of the relationship between the clinical efficacy of immunotherapy for GC. The correlation between COX7A1 and immune cell infiltration, drug sensitivity scoring, and immunohistochemical staining were performed to initially understand the potential role of COX7A1 in the development and progression of GC. Finally, the differential expression of COX7A1 was verified in those GC patients receiving immunotherapy. RESULTS: First, 47 protective genes and 408 risky genes were obtained, and the ssGSEA algorithm was applied for model construction, showing good prognostic discrimination ability. In addition, the patients with high model scores showed higher TMB and MSI levels, and lower tumor heterogeneity scores. Then, it is found that the COX7A1 expressions in GC tissues were significantly lower than those in their corresponding paracancerous tissues. Meanwhile, the patients with high COX7A1 expression showed higher probability of cancer invasion, worse clinical efficacy of immunotherapy, worse overall survival (OS) and worse disease-free survival (DFS). CONCLUSIONS: The ssGSEA score we constructed can serve as a biomarker for GC patients and provide important guidance for individualized treatment. In addition, the COX7A1 gene can accurately distinguish the prognosis of GC patients and predict the clinical efficacy of immunotherapy for GC patients.

Dual-color silver-enhanced in-situ hybridization and fluorescence in-situ hybridization for determination of HER2 gene status in gastric carcinoma / 中华病理学杂志

<p><b>OBJECTIVE</b>To investigate the advantages and disadvantages of dual-color silver-enhanced in-situ hybridization (DSISH) and fluorescence in-situ hybridization (FISH) for determination of HER2 gene status in gastric carcinoma and to evaluate the feasibility of DSISH.</p><p><b>METHODS</b>Eighty cases of primary gastric or gastroesophageal junction adenocarcinomas diagnosed and treated surgically from January to March, 2009 at the West China Hospital were enrolled in the study. Automated immunohistochemistry (IHC) staining, FISH and automated DSISH were carried out to detect the HER2 status, respectively, and the concordance of the three techniques was then evaluated.</p><p><b>RESULTS</b>DSISH and FISH failed initially, but repeated detection was successful in 5 cases. Gene amplification was detected in 12/13 IHC 3+ cases in DSISH and in 11/13 IHC 3+ cases in FISH. In 6 IHC 2+ cases, the amplification rate was both 1/6; in 18 IHC 1+ cases, the amplification rate was both 2/18. No amplification was observed in 43 IHC 0 cases. Only one of the 80 cases showed discrepancy, and therefore the overall concordance between FISH and DSISH was 98.8% (κ = 0.958, P < 0.01).</p><p><b>CONCLUSIONS</b>DSISH represents a novel approach for the determination of HER2 status in gastric carcinoma, and the overall concordance between DSISH and FISH is excellent. Despite their advantages and disadvantages, DSISH is more feasible and practical for routine application in surgical pathology.</p>

[Association between urinary neutrophil gelatinase-associated lipocalin and acute kidney injury after cardiac surgery].

OBJECTIVE: To test the hypothesis that Neutrophil gelatinase-associated lipocalin (NGAL) is an early biomarker for acute kidney injury (AKI) in patients after cardiac surgery. METHODS: 33 cases undergoing cardiac surgery were divided into AKI group and Non-AKI group according to the AKI criteria. The concentration of urine NGAL at different time points were measured. RESULTS: (1) Nine of 33 cases (27%) developed postoperative AKI, but diagnosis with serum creatinine was only 12-48 hours after cardiac surgery. (2)Urinary concentrations of NGAL at 2 h after cardiac surgery in patients who did not developed AKI were significantly higher compared with those of preoperative (P < 0.001). Urinary concentrations of NGAL at 2 h and 4 h after cardiac surgery in patients who developed AKI were significantly higher compared with those of preoperative (P < 0.001). (3) The mean urinary NGAL concentrations in patients who developed AKI were significantly higher after surgery compared with patients who did not develop AKI (P < 0.01). (4) Urinary concentrations of NGAL/Ucr at 2 h and 4 h after cardiac surgery in patients who did not developed AKI were significantly higher compared with those of preoperative (P < 0.05). Urinary concentrations of NGAL/Ucr at 2 h and 4 h after cardiac surgery in patients who developed AKI were significantly higher compared with those of preoperative (P < 0.01). (The mean urinary concentrations of NGAL/Ucr in patients who developed AKI were significantly higher after surgery compared with patients who did not develop AKI (P < 0.01). (6) For concentrations in urine of NGAL at 2 h after surgery, sensitivity was 0.7125, and specificity was 0.7307 for a cutoff value of 250 microg/L. For concentrations in urine of NGAL/Ucr at 2 h after surgery, sensitivity was 0.8127, and specificity was 0.7839 for a cutoff value of 250 microg/mmol. (7) Urinary concentrations of NGAL at 2 h after cardiac surgery was significantly associated with serum creatinine 12 h postoperative (R = 0.638, P < 0.05). CONCLUSIONS: The incidence of AKI in patients after cardiac surgery is high, which accounted for 27%. The amount of NGAL and NGAL/Ucr in urine at 2 h after cardiac surgery were the powerful independent predictor of acute renal injury and urine concentrations of NGAL/Ucr is more sensitive.