Breast carcinoma (BRCA) is the most common carcinoma among women worldwide. Despite the great progress achieved in early detection and treatment, morbidity and mortality rates remain high. In the present study, we make a systematic analysis of BRCA using TCGA database by applying CIBERSORT and ESTIMATE computational methods, uncovered CD3D as a prognostic biomarker by intersection analysis of univariate COX and protein–protein interaction (PPI). It revealed that high CD3D expression was strongly associated with poor survival of BRCA, based on The Cancer Genome Atlas (TCGA) database and online websites. Gene Set Enrichment Analysis (GSEA) revealed that the high CD3D expression group was mainly enriched for the immune-related pathways and the low CD3D expression group was mainly enriched for metabolic-related activities. Based on CIBERSORT analysis, the difference test and correlation test suggested that CD3D had a strong correlation with T cells, particularly CD8 + T cells, which indicated that CD3D up-regulation may increase T cell immune infiltration in the TME and induce antitumor immunity by activating T lymphocytes. Furthermore, the correlation analysis showed that CD3D expression had a strongly positive correlation with immune checkpoints, which indicating that the underlying mechanism involves CD3D mediated regulation of T cell functions in BRCA, and single cell RNA-seq analysis revealed that CD3D correlate with CD8 + T cells and it is itself highly expressed in CD8 + T cells. In summary, we identified a prognostic biomarker CD3D in BRCA, which was associated with lymphocyte infiltration, immune checkpoints and could be developed for innovative therapeutics of BRCA.

Purpose: Using the gastric cancer cell line SGC7901 and gastric cancer stem cell (CSC-G), we conducted this study to investigate the role of cancer stem cells in invasion, metastasis and tumor angiogenesis. Methods: Stem cell markers (OCT4, SOX2, C-Myc and Klf4) expression was detected by RT-PCR and Western blotting. The proliferation, migration, invasion abilities, L-OHP and 5-FU resistance, angiogenesis were assessed using in vitro spherical clone formation assays, plate cloning experiments, transwell migration, transwell invasion, drug resistance, scratch-wound migration, ring formation assay, and their tumorigenic and ability were assessed using a tumor formation experiment in mice. Results: Compared with the SGC7901, the expression of Oct4, Sox2, Klf4 and CD44 mRNA was significantly higher in CSC-G, the mRNA relative expression of E-cadherin in CSC-G was lower than SGC7901, while the expression of c-Myc did not significantly change. The proliferation, drug resistance, migration, and invasion abilities were significantly higher in CSC-G, and the tumorigenic ability in mice was also significantly higher. Conclusion: The proliferation, drug resistance, migration, invasion, and tumorigenic abilities of CSC-G significantly were higher than SGC7901. CSC-G plays important roles in proliferation, migration, invasion, and tumorigenicity.

Background Additional studies comparing laparoscopic gastrectomy (LG) versus open gastrectomy (OG) for advanced gastric cancer (AGC) have been published, and it is necessary to update the systematic review of this subject. Objective We conducted the meta-analysis to find some proof for the use of LG in AGC and evaluate whether LG is an alternative treatment for AGC. Method Randomized controlled trials (RCT) and high-quality retrospective studies (NRCT) compared LG and OG for AGC, which were published in English between January 2010 and May 2019, were search in PubMed, Embase, and Web of Knowledge by three authors independently and thoroughly. Some primary endpoints were compared between the two groups, including intraoperative time, intraoperative blood loss, harvested lymph nodes, first flatus, first oral intake, first out of bed, post-operative hospital stay, postoperative morbidity and mortality, rate of disease recurrence, and 5-year over survival (5-y OS). Besides, considering for this 10-year dramatical surgical material development between 2010 and 2019, we furtherly make the same analysis based on recent studies published between 2016 and 2019. Result Thirty-six studies were enrolled in this systematic review and meta-analysis, including 5714 cases in LAG and 6094 cases in OG. LG showed longer intraoperative time, less intraoperative blood loss, and quicker recovery after operations. The number of harvested lymph nodes, hospital mortality, and tumor recurrence were similar. Postoperative morbidity and 5-y OS favored LG. Furthermore, the systemic analysis of recent studies published between 2016 and 2019 revealed similar result. Conclusion A positive trend was indicated towards LG. LG can be performed as an alternative to OG for AGC.

Background Due to the complicated molecular and cellular heterogeneity in hepatocellular carcinoma (HCC), the morbidity and mortality still remains high level in the world. However, the number of novel metabolic biomarkers and prognostic models could be applied to predict the survival of HCC patients is still small. In this study, we constructed a metabolic gene signature by systematically analyzing the data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC). Methods Differentially expressed genes (DEGs) between tumors and paired non-tumor samples of 50 patients from TCGA dataset were calculated for subsequent analysis. Univariate cox proportional hazard regression and LASSO analysis were performed to construct a gene signature. The Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC), Univariate and Multivariate Cox regression analysis, stratification analysis were used to assess the prognostic value of the gene signature. Furthermore, the reliability and validity were validated in four types of testing cohorts. Moreover, the diagnostic capability of the gene signature was investigated to further explore the clinical significance. Finally, Go enrichment analysis and Gene Set Enrichment Analysis (GSEA) have been performed to reveal the different biological processes and signaling pathways which were active in high risk or low risk group. Results Ten prognostic genes were identified and a gene signature were constructed to predict overall survival (OS). The gene signature has demonstrated an excellent ability for predicting survival prognosis. Univariate and Multivariate analysis revealed the gene signature was an independent prognostic factor. Furthermore, stratification analysis indicated the model was a clinically and statistically significant for all subgroups. Moreover, the gene signature demonstrated a high diagnostic capability in differentiating normal tissue and HCC. Finally, several significant biological processes and pathways have been identified to provide new insights into the development of HCC. Conclusion The study have identified ten metabolic prognostic genes and developed a prognostic gene signature to provide more powerful prognostic information and improve the survival prediction for HCC.

Background Gastric cancer (GC) is one of the most common malignant diseases worldwide, the incidence and mortality for GC is still high, thus it is urgently important to identify the effective and reliable biomarkers to evaluate GC and the underlying molecular events. Methods The study integrated four Gene Expression Omnibus (GEO) profile datasets and The Cancer Genome Atlas (TCGA) dataset to screen differentially expressed genes (DEGs), screened key genes by performing the Kaplan-Meier analysis, univariate and multivariate-cox analysis. Further analysis were performed to evaluate and validate the prognostic value of the key genes based on TCGA database and online websites. In addition, mechanism analysis of the key genes was performed thought biological processes and KEGG pathway analysis. Results In the study, 192 DEGs (92 up-regulated and 100 down-regulated) were identified from the GEO and TCGA datasets. Next, gene ontology (GO) for DEGs focused primarily on cell adhesion, extracellular region and extracellular matrix structural constituent. Then four significant key genes were screened by performed the Kaplan-Meier analysis, univariate and multivariate-cox analysis. By using Kaplan-Meier plotter and OncoLnc, the expression level was associated with a worse prognosis. In addition, the area under curve (AUC) for time-dependent receiver operating characteristic (ROC) indicated a moderate diagnostic value. Furthermore, the expression of collagen triple helix repeat containing 1 ( CTHRC1 ), serpin family E member 1 ( SERPINE1 ), Versican ( VCAN ) was associated with tumor size, Uroplakin 1B ( UPK1B ) expression was associated with distant metastasis. Finally, multiple biological processes and signaling pathway associated with key genes revealed the underlying mechanism in GC. Conclusions Taken together, CTHRC1 , SERPINE1 , VCAN , UPK1B were novel potential prognostic molecular markers for GC, which acted as oncogene to promote the development of GC.