Bioinformatics analyses for the identification of tumor antigens and immune subtypes of gastric adenocarcinoma.

Background: Although mRNA vaccines have been effective against multiple cancers, their efficacy against stomach adenocarcinoma (STAD) remains undefined. Immunotyping can indicate the comprehensive immune status in tumors and their immune microenvironment, which is closely associated with therapeutic response and vaccination potential. The aim of this study was to identify potential antigens in STAD for mRNA vaccine development, and further distinguish immune subtypes of STAD to construct an immune landscape for selecting suitable patients for vaccination. Methods: The gene expression and clinicopathological features of patients with gastric cancer were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Program (GTEx). 729 samples from GSE66229 and GSE84437 were downloaded through GEO and were used as the validation cohorts. Differential gene expression, genetic alterations and prognosis were analyzed using the R package, cBioPortal program and Kaplan-Meier. The relationship between tumor antigens and immune cells was evaluated and plotted by TIMER. ConsensusClusterPlus was used for consistency matrix construction and data clustering, and graph learning-based dimensional reduction was used to depict immune landscape. WGCNA was used to estimate the relationship between the color modules and immune subtypes. Results: Two overexpressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in STAD, including RAI14 and NREP. The immune subtypes showed distinct molecular, cellular and clinical characteristics. IS1 and IS2 exhibited immune-activated phenotypes and correlated to better survival compared to IS3, while IS3 tumors was immunologically cold. Immunogenic cell death modulators, immune checkpoints, and CA125, and CEA were also differentially expressed among the three immune subtypes. Finally, the immune landscape of STAD showed a high degree of heterogeneity between individual patients. Conclusion: RAI14 and NREP are potential antigens for developing anti-STAD mRNA vaccine, and patients with IS1 and IS3 tumors may be suitable for vaccination.

Short-Term Outcomes of Tri-Staple Versus Universal Staple in Laparoscopic Anterior Resection of Rectal and Distal Sigmoid Colonic Cancer: A Matched-Pair Analysis.

BACKGROUND: Anastomotic leakage is a serious complication in laparoscopic colorectal surgeries. To resolve this problem, a new stapling technology (Tri-staple) is developed. In this study, we aim to compare the short-term outcomes of Tri-staple versus Universal staple in laparoscopic anterior resection of rectal and distal sigmoid colonic cancer. METHODS: A total of 446 patients were admitted to our hospital and received laparoscopic anterior resection for rectal and distal sigmoid colonic cancer between January 2016 and December 2020. Among them, Tri-staples were used in 202 patients, and the Universal staples were used in 244 patients. Propensity score matching was performed, followed by a comparison between the two groups (Tri-staple vs. Universal staple) in the incidences of anastomotic leakage, bleeding, and reoperation. RESULTS: In total, 270 patients were included in this retrospective cohort study by the propensity score matching, with each group having 135 patients. Tri-staple group had a significant lower incidence of anastomotic leakage compared with the Universal staple group (4.44% vs. 11.11%, P < 0.05). The reoperation rate was also lower in Tri-staple group than the Universal staple group (3.70% vs. 8.15%, P < 0.05). The anastomotic bleeding rates, average postoperative hospital stay, average drain indwelling period, and average fasting period had no statistical differences between the two groups. CONCLUSION: The usage of Tri-staple in laparoscopic anterior resection of rectal and distal sigmoid colonic cancer is associated with lower postoperative complications compared with Universal staple. Future high-quality randomized controlled trials are needed to confirm our findings.

Postoperative adjuvant TACE-associated nomogram for predicting the prognosis of resectable Hepatocellular Carcinoma with portal vein Tumor Thrombus after Liver Resection.

Background: To explore the effects of postoperative adjuvant transarterial chemoembolization (PA-TACE) on the prognosis of HCC patients with Portal Vein Tumor Thrombus (PVTT) undergoing resection, and to develop a PA-TACE-related nomogram for predicting survival individually. Patients and Methods: Two hundred and ninety-three consecutive HCC patients with PVTT under R0 hepatectomy were recruited. Forty-seven cases had recurrence within one month after surgery. The remaining 246 cases consisted of 90 PA-TACE and 156 non-PA-TACE cases. COX regression analysis was performed for overall survival (OS) or recurrence-free survival (RFS) of these 246 cases, allowing the derivation of independent factors that were integrated into the nomogram. C-index, calibration curves, and risk stratification were performed to evaluate the performance and discriminative power of the nomograms. Results: In 246 patients without recurrence within one month after surgery, the OS and RFS for the PA-TACE group were significantly better than those for the non-PA-TACE group (P<0.0001, P<0.0001, respectively). After Cox regression analysis of OS or RFS, PA-TACE-related nomogram models were constructed. The C-index of the PA-TACE-related nomogram for OS and RFS was 0.72 and 0.73, respectively. Calibration curves revealed a good agreement between predictions and observations for the nomograms. Based on the nomogram-related risk stratification, Kaplan-Meier curves showed powerful discriminative ability. Conclusions: PA-TACE therapy improved the survival of HCC patients with PVTT undergoing hepatectomy. Accurate nomogram models were developed for predicting the individual survival and recurrence of these patients.

Effect of menopausal status on the survival and recurrence of sex-classified hepatocellular carcinoma after liver resection: a case-matched study with propensity score matching.

OBJECTIVE: To investigate the impact of menopausal status on the prognosis for sex-classified Hepatocellular carcinoma (HCC) and to establish prognostic nomograms for patients after liver resection. RESULTS: After propensity score matching (PSM), statistically significant differences in both overall survival (OS) and recurrence-free survival (RFS) were found between men and women HCC patients. Based on Cox regression analysis, these differences were evident in the normal menstruation (N) group expanded with male patients, but not in either the expanded postmenopausal (P) or intermediate (I) groups. Sex disparity was also apparent in the recurrence-free survival (RFS) of the total HCC patients. Integrated with independent factors, nomograms for the OS and RFS of the expanded N group showed higher C-indices of 0.773 and 0.724, respectively, than those of nomograms for the total patients and BCLC stage (P<0.001). CONCLUSION: Sex disparity appears to affect both the survival and recurrence of HCC only in normal menstruation women and their matched men. For predicting survival, prognostic nomograms derived from the expanded N group of HCC patients were more accurate for patients with the same clinical conditions. METHODS: The patients (390 females and 1920 males), who underwent curative liver resection for HCC during 2008 to 2012, were screened. The 390 women were divided into three groups: normal menstruation, intermediate, and postmenopausal. To overcome selection bias, the three groups of females were matched with males at a ratio of 1:2, using propensity score matching. Based on further Cox regression analysis, independent factors were integrated into nomograms for OS and RFS by R rms. The accuracy and discrimination of the nomograms were evaluated by the C-index, calibration curve, and decision curve analysis.

Develop a circular RNA-related regulatory network associated with prognosis of gastric cancer.

BACKGROUND: In gastric cancer (GC), circular RNAs (circRNAs) mainly play an important role in miRNA sponge, which not only indicate long-term survival and prognosis but also increase resistance to the apoptosis. The purpose of the study is to explore new circRNAs and their underlying mechanisms in GC. METHOD: Through rigorous retrieval strategies, we used the sva package to analyze and identify differentially expressed circRNAs (DECs) from three Gene Expression Omnibus microarray datasets (GSE83521, GSE89143, and GSE78092). Online website CSCD and CircInteractome were used to reveal the binding sites between miRNAs and DECs. The possible target miRNAs of the DECs identified based on miRNAs, and Cytoscape was used to create a regulatory network of circRNA-miRNA-mRNA and identified the hub genes which were further validated using The Cancer Genome Atlas database and Human Protein Atlas. RESULTS: Twenty-eight DECs were obtained using the sva package. A regulatory network of circRNA-miRNA-mRNA (competing endogenous RNA) containing 15 circRNAs, 24 miRNAs, and 158 genes was identified. A protein-protein interaction network based on the 158 genes was established, and further determined that 10 hub genes (SKA1, ANLN, CHEK1, SKA3, TOP2A, BIRC5, RRM2, NCAPG2, FANCI, and RAD51) were associated with some cancer-related pathways based on the functional enrichment analysis. Finally, six hub genes (BIRC5, TOP2A, FANCI, NCAPG2, RAD51, and RRM2) were proven to influence the overall survival of GC. CONCLUSION: Our study established a circRNA-miRNA-mRNA regulatory network and defined six circRNA-related hub genes in GC, which could serve as potential therapeutic targets or prognostic biomarker for GC treatment.

Integrated Transcriptomic Analysis Reveals the Molecular Mechanism of Meningiomas by Weighted Gene Coexpression Network Analysis.

Meningiomas are the most common primary intracranial tumor in adults. However, to date, systemic coexpression analyses for meningiomas fail to explain its pathogenesis. The aim of the present study was to construct coexpression modules and identify potential biomarkers associated with meningioma progression. Weighted gene coexpression network analysis (WGCNA) was performed based on GSE43290, and module preservation was tested by GSE74385. Functional annotations were performed to analyze biological significance. Hub genes were selected for efficacy evaluations and correlation analyses using two independent cohorts. A total of 14 coexpression modules were identified, and module lightcyan was significantly associated with WHO grades. Functional enrichment analyses of module lightcyan were associated with tumor pathogenesis. The top 10 hub genes were extracted. Ten biomarkers, particularly AHCYL2, FGL2, and KCNMA1, were significantly related to grades and prognosis of meningioma. These findings not only construct coexpression modules leading to the better understanding of its pathogenesis but also provide potential biomarkers that represent specific on tumor grades and identify recurrence, predicting prognosis and progression of meningiomas.

A Gene-Related Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer.

Purpose: To develop and validate a gene-related nomogram for predicting the risk of lymph node (LN) metastasis preoperatively in patients with colorectal cancer (CRC). Methods: RNA-seq data of 581 CRC and 51 normal cases with clinical features were downloaded from TCGA database. In the evaluation cohort with 381 CRC cases, the LASSO regression was used to reduce dimensionality of gene signatures extracted to build gene score. A gene-related nomogram was performed based on the multivariable logistic regression analysis. The performance of the nomogram was assessed by the discrimination, calibration, and clinical usefulness not only in the evaluation, but also in the validation cohort with 200 CRC cases. Results: A total of 12,590 differentially expressed genes were selected, in which 59 candidates associated with LN metastasis in differentially expressed genes set were screened by LASSO to form the gene score. Based on the analysis of multivariate logistic regression, the gene-related nomogram showed good calibration and discrimination not only in the evaluation cohort (concordance-index 0.93; 95%CI 0.91-0.96), but also in the validation cohort (concordance-index 0.70; 95%CI 0.63-0.78). The decision curve analysis of the gene-related nomogram also provides constructive guidance for the design of operation plan, preoperatively. Conclusions: The presented genes nomogram may predict the LN metastasis in CRC patients, preoperatively. And 59 hub genes were defined related to LN metastasis of CRC, which can serve as treatment targets for the further study. Preoperative biopsy and gene analysis are needed to develop the operation plan in clinical practice.

Identification of hub genes and construction of transcriptional regulatory network for the progression of colon adenocarcinoma hub genes and TF regulatory network of colon adenocarcinoma.

The aim of this study was to identify key genes related to the progression of colon adenocarcinoma (COAD), and to investigate the regulatory network of hub genes and transcription factors (TFs). Dataset GSE20916 including 44 normal colon, 55 adenoma, and 36 adenocarcinoma tissue samples was used to construct co-expression networks via weighted gene co-expression network. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis for the objective module were performed using the online Database for Annotation, Visualization and Integrated Discovery. Hub genes were identified by taking the intersection of differentially expressed genes between dataset GSE20916 and GSE39582 and validated using The Cancer Genome Atlas (TCGA) database. The correlations between microRNA (miRNA) and hub genes were analyzed using the online website StarBase. Cytoscape was used to establish a regulatory network of TF-miRNA-target gene. We found that the orange module was a key module related to the tumor progression in COAD. In datasets GSE20916 and GSE39582, a total of eight genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) were selected, which were closely related with patients' survivals in TCGA database and dataset GSE20916. COAD patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. A regulatory network of TF-miRNA-target gene with 144 TFs, 26 miRNAs, and 7 hub genes was established, including model KLF11-miR149-BGN, TCEAL6-miR29B2-COL1A1, and TCEAL6-miR29B2-COL1A2. In conclusion, during the progression of COAD, eight core genes (BGN, SULF1, COL1A1, FAP, THBS2, CTHRC1, COL5A2, and COL1A2) play vital roles. Regulatory networks of TF-miRNA-target gene can help to understand the disease progression and optimize treatment strategy.