Integrated analysis of single-cell and bulk RNA-seq establishes a novel signature for prediction in gastric cancer.

BACKGROUND: Single-cell sequencing technology provides the capability to analyze changes in specific cell types during the progression of disease. However, previous single-cell sequencing studies on gastric cancer (GC) have largely focused on immune cells and stromal cells, and further elucidation is required regarding the alterations that occur in gastric epithelial cells during the development of GC. AIM: To create a GC prediction model based on single-cell and bulk RNA sequencing (bulk RNA-seq) data. METHODS: In this study, we conducted a comprehensive analysis by integrating three single-cell RNA sequencing (scRNA-seq) datasets and ten bulk RNA-seq datasets. Our analysis mainly focused on determining cell proportions and identifying differentially expressed genes (DEGs). Specifically, we performed differential expression analysis among epithelial cells in GC tissues and normal gastric tissues (NAGs) and utilized both single-cell and bulk RNA-seq data to establish a prediction model for GC. We further validated the accuracy of the GC prediction model in bulk RNA-seq data. We also used Kaplan-Meier plots to verify the correlation between genes in the prediction model and the prognosis of GC. RESULTS: By analyzing scRNA-seq data from a total of 70707 cells from GC tissue, NAG, and chronic gastric tissue, 10 cell types were identified, and DEGs in GC and normal epithelial cells were screened. After determining the DEGs in GC and normal gastric samples identified by bulk RNA-seq data, a GC predictive classifier was constructed using the Least absolute shrinkage and selection operator (LASSO) and random forest methods. The LASSO classifier showed good performance in both validation and model verification using The Cancer Genome Atlas and Genotype-Tissue Expression (GTEx) datasets [area under the curve (AUC)_min = 0.988, AUC_1se = 0.994], and the random forest model also achieved good results with the validation set (AUC = 0.92). Genes TIMP1, PLOD3, CKS2, TYMP, TNFRSF10B, CPNE1, GDF15, BCAP31, and CLDN7 were identified to have high importance values in multiple GC predictive models, and KM-PLOTTER analysis showed their relevance to GC prognosis, suggesting their potential for use in GC diagnosis and treatment. CONCLUSION: A predictive classifier was established based on the analysis of RNA-seq data, and the genes in it are expected to serve as auxiliary markers in the clinical diagnosis of GC.

C1QTNF6 is overexpressed in gastric carcinoma and contributes to the proliferation and migration of gastric carcinoma cells.

In the present study, proteins differentially expressed between gastric cancer tissue and para­tumoral normal gastric tissues were screened, and the function of the highly expressed protein C1QTNF6 in gastric carcinoma was investigated. The differential expression of mRNAs extracted from the tumor and adjacent tissues was analyzed using GeneChip assay. An AGS si­C1QTNF6 cell line was constructed using shRNA­C1QTNF6 lentivirus. The cell invasion and migration ability of C1QTNF6­knockdown cells were determined by Transwell chamber migration and wound healing assays, respectively. The effects of C1QTNF6 on AGS cell cycle distribution and apoptosis were detected using a FACScan flow cytometer. The results demonstrated that the expression of 109 genes was increased and the expression of 129 was decreased in tumor tissues. Among these genes, the C1QTNF6 gene was highly expressed in tumor tissues and the AGS7901 cell line. C1QTNF6­knockdown decreased the cell growth, and the proliferative and migration ability, as well as increasing the apoptosis of gastric carcinoma cells. In addition, the number of AGS cells in the G2/M phase was significantly increased after 5 days of C1QTNF6­shRNA lentivirus infection. The results of the present study indicated that C1QTNF6 serves an important role in the development of gastric carcinoma. C1QTNF6 is involved in promoting the proliferation and migration, and in reducing the apoptosis of gastric carcinoma cells. These results provided a potential therapeutic target for the treatment of gastric carcinoma.

Clinicopathological and prognostic significance of programmed cell death ligand 1 (PD-L1) expression in patients with esophageal squamous cell carcinoma: a meta-analysis.

BACKGROUND: The clinicopathological and prognostic significance of programmed cell death ligand 1 (PD-L1) expression in patients with esophageal squamous cell carcinoma (ESCC) remains controversial. To investigate this question, we conducted a meta-analysis. METHODS: A comprehensive literature search of electronic databases (up to July 10, 2016) was performed for relevant studies using multiple search strategies. Correlation between PD-L1 expression and clinicopathological features/overall survival (OS) was analyzed. RESULTS: A total of 1,350 ESCC patients from eight studies were included. The pooled odds ratios (ORs) indicated that none of the clinicopathological characteristics was correlated with PD-L1 expression, including gender [OR =0.84; 95% confidence interval (CI): 0.59-1.18; P=0.31], histological differentiation (OR =1.33; 95% CI: 0.95-1.85; P=0.09), tumor depth (OR =0.66; 95% CI: 0.33-1.35; P=0.26), status of lymph node metastasis (OR =0.67; 95% CI: 0.30-1.52; P=0.34), distal metastasis (OR =0.66; 95% CI: 0.40-1.09; P=0.10) and tumor node metastasis (TNM) stage (OR =0.93; 95% CI: 0.49-1.75; P=0.82). The combined hazard ratio (HR) for OS showed a trend that overexpression of PD-L1 might be associated with the survival outcome of ESCC, though the difference was not statistically significant (HR =1.65; 95% CI 0.95-2.85; P=0.07). CONCLUSIONS: Based on the published studies, PD-L1 overexpression in ESCC was not associated with common clinicopathological characteristics. PD-L1 might be a poor prognostic biomarker for ESCC. Further large-scale research should be performed to reveal the precise clinicopathological and prognostic significance of PD-L1 in ESCC by unified testing standard.

Identification and differential expression of human carcinoma-associated antigens in hepatocellular carcinoma tissues.

This study was designed to identify and verify hepatocellular carcinoma (HCC)-associated human carcinoma antigens (HCAs) that may be useful as tumor markers for HCC. We found that BCE075 and BCD021 anti-HCA antibodies were immunostained in the liver tissue samples and showed specific staining. Their expression was increased in HCC compared with normal liver tissues (P = 0.008). Immunoprecipitation and mass spectrometry analyses of the proteins precipitated by these two antibodies were identified to be cytoskeleton-associated protein 4 (CLIMP63) and brain-type glycogen phosphorylase (PYGB). This study demonstrated that HCC tissues expressed specific HCA glycoproteins, suggesting that our mouse monoclonal anti-HCA antibodies could be useful for immunohistochemical analysis of HCA expression as potential biomarkers for HCC diagnosis.

Over-expression of human carcinoma-associated antigen in intrahepatic cholangiocellular carcinoma.

OBJECTIVE: To investigate the expression status of human carcinoma antigen (HCA) in human cholangiocellular carcinomas, and to determine the relationship between HCA and clinical features. METHODS: Tissues from 60 intrahepatic cholangiocellular carcinoma (ICC) patients, and normal liver tissues from 20 hepatic hemangioma patients selected randomly were assayed for the expression of HCA by immunohistochemistry, and Western blots. Areas of poorly differentiated (n=20), moderately-well differentiated (n=30), highly differentiated tumors (n=10) from different cases were evaluated. Results were recorded as positive (≥5% of cells staining and staining intensity 2+ or 3+) or negative (<5% of cells staining and staining intensity<2+) and analyzed using the χ2 test. RESULTS: BCE075 and BDD048 antibodies showed similar staining patterns. The positive immunostaining of BCE075 was mainly localized in the cytoplasm and cell secretions. The staining was positive in 15% of poorly differentiated ICC, 72% of moderately-well differentiated, 100% of highly differentiated tumors. But, staining was not detected in adjacent normal tissue. The differences in HCA expression among these tissues were statistically significant. Also, we found expression of HCA to be closely associated with the degree of differentiation of ICC and tumor cell morphology. There was a correlation between expression of HCA and serum CA19-9. CONCLUSION: The data suggest that HCA is a potential marker for the diagnosis of cholangiocellular carcinoma.

[Preparation and identification of monoclonal antibody against Homo sapiens hemoglobin alpha 2 (HBA2)].

This study was purposed to prepare and identify monoclonal antibodies (McAbs) against Homo sapiens hemoglobin alpha 2 (HBA2). Normal human fetal liver tissues were homogenized, and human liver nuclear proteins were isolated by centrifugation. The total human fetal liver nuclear proteins were used to immunize BALB/c mice for preparing McAbs by hybridoma technique. The McAbs specificity was identified by ELISA, Western blot, and immunohistochemistry. The antigen was identified by Uni-ZAP expression library screening. The results showed that one hybridoma cell line, AEE091, secreting specific McAb against HBA2 was established. The Ig subclass of this McAb was IgG1 (kappa). Data from immunohistochemistry assay showed that AEE091 could recognize human liver nuclear protein. Using AEE091 McAb, isolation of the protein antigen by IP revealed that AEE091 McAb could recognize 15 kD protein. Screening the Uni-ZAP XR pre-made liver cDNA library with AEE091 hybridoma cell supernatants demonstrated that AEE091 McAb specially reacted with HBA2. It is concluded that a hybridoma cell line stably secreting specific McAb against HBA2 is established. The specific McAb against HBA2 would be very useful for studying HBA2 function and screening thalassemia.