Infrapyloric (No. 206) and greater curvature (No. 204) lymph node metastasis in adenocarcinoma located in the right half of the transverse colon (InCLART Study): protocol for a multicentre prospective observational study.

INTRODUCTION: In the case of right-sided transverse colon cancer (RTCC) and hepatic flexure colon cancer (HFCC), there is a potential connection of lymph drainage between mesentery and greater omentum. However, most previous reports have been limited case series with No. 206 and No. 204 lymph node (LN) dissection for RTCC and HFCC. METHODS AND ANALYSIS: The InCLART Study is a prospective observational study aiming to enrol 427 patients with RTCC and HFCC treated at 21 high-volume institutions in China. The prevalence of infrapyloric (No. 206) and greater curvature (No. 204) LN metastasis and short-term outcomes will be investigated in a consecutive series of patients with T2 or deeper invasion RTCC or HFCC, following the principle of complete mesocolic excision with central vascular ligation. Primary endpoints were performed to identify the prevalence of No. 206 and No. 204 LN metastasis. Secondary analyses will be used to estimate prognostic outcomes, intraoperative and postoperative complications, the consistency of preoperative evaluation and postoperative pathological results of LN metastasis. ETHICS AND DISSEMINATION: Ethical approval for the study has been granted by the Ruijin Hospital Ethics Committee (approval number: 2019-081) and has been or will be approved successively by each participating centre's Research Ethics Board. The findings will be disseminated in peer-reviewed publications. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Registry (NCT03936530; https://clinicaltrials.gov/ct2/show/NCT03936530).

A Novel Glycolysis-Related Long Noncoding RNA Signature for Predicting Overall Survival in Gastric Cancer.

Background: The aim of this study was to construct a glycolysis-related long noncoding RNA (lncRNA) signature to predict the prognosis of patients with gastric cancer (GC). Methods: Glycolysis-related genes were obtained from the Molecular Signatures Database (MSigDB), lncRNA expression profiles and clinical data of GC patients were obtained from The Cancer Genome Atlas database (TCGA). Furthermore, univariate Cox regression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) and multivariate Cox regression analysis were used to construct prognostic glycolysis-related lncRNA signature. The specificity and sensitivity of the signature was verified by receiver operating characteristic (ROC) curves. We constructed a nomogram to predict the 1-year, 3-year, and 5-year survival rates of GC patients. Besides, the relationship between immune infiltration and the risk score was analyzed in the high and low risk groups. Multi Experiment Matrix (MEM) was used to analyze glycolysis-related lncRNA target genes. R "limma" package was used to analyze the mRNA expression levels of the glycolysis-related lncRNA target genes in TCGA. Gene set enrichment analysis (GSEA) was employed to further explore the biological pathways in the high-risk group and the glycolysis-related lncRNA target gene. Results: A prognostic signature was conducted based on nine glycolysis-related lncRNAs, which are AL391152.1, AL590705.3, RHOXF1-AS1, CFAP61-AS1, LINC00412, AC005165.1, AC110995.1, AL355574.1 and SCAT1. The area under the ROC curve (AUC) values at 1-year, 3-year, and 5-year were 0.765, 0.828 and 0.707 in the training set, and 0.669, 740 and 0.807 in the testing set, respectively. In addition, the nomogram could efficaciously predict the 1-year, 3-year, and 5-year survival rates of the GC patients. Then, we discovered that GC patients with high-risk scores were more likely to respond to immunotherapy. GSEA revealed that the signature was mainly associated with the calcium signaling pathway, extracellular matrix (ECM) receptor interaction, and focal adhesion in high-risk group, also indicated that SBSPON is related to aminoacyl-tRNA biosynthesis, citrate cycle, fructose and mannose metabolism, pentose phosphate pathway and pyrimidine metabolism. Conclusion: Our study shows that the signature can predict the prognosis of GC and may provide new insights into immunotherapeutic strategies.