Transcriptomic study of gastrointestinal stromal tumors with liver metastasis.

Introduction: GIST (gastrointestinal stromal tumor) is the most prominent mesenchymal neoplasms of the gastrointestinal tract, and liver is the most common metastasis site for GIST. The molecular mechanism leading to liver metastasis of GIST is currently unclear. Methods: With the goal of revealing the underlying mechanism, we performed whole-genome gene expression profiling on 18 pairs of RNA samples comprised of GIST tissues (with liver metastasis) and corresponding non-tumor tissues. After identifying differentially expressed gene, functional annotation and signal pathway analyses were conducted. GSE13861, datasets that compare GIST (without liver metastasis) with adjacent tissues, served as a comparison. Results: A total of 492 up-regulated genes and 629 down-regulated genes were identified as differentially expressed genes between liver metastasis tissues and non-tumor tissues. We characterized expression patterns of DEGs identified from our cohort and GSE13861 that show signatures of enrichment for functionality. In subsequent gene set enrichment analysis, differentially expressed genes were mainly enriched in Epithelial Mesenchymal Transition in both datasets. 493 genes were overlapped among our whole-genome gene expression profiling results and GSE13861, consisting 188 up-regulated genes and 305 down-regulated genes. By using CytoHubba plugin of Cytoscape, CDH1, CD34, KIT, PROM1, SOX9, FGF2, CD24, ALDH1A1, JAG1 and NES were identified as top ten hub genes in tumorigenesis and liver metastasis of GIST. higher expression levels of FGF2, JAG1, CD34, ALDH1A1 and the lower expression level of CDH1 were respectively associated with unfavorable overall survival. Meanwhile higher expression levels of CD34, FGF2, KIT, JAG1, ALDH1A were correlated with worse disease-free survival. Discussion: The present study may help to provide candidate pathways and targets for treatment of GIST and prevention methods to liver metastasis.

A nomogram to predict risk of lymph node metastasis in early gastric cancer.

Lymph node (LN) metastasis is known as one of the most important prognostic factors for early gastric cancer (EGC) patients. Patients without LNM normally have better prognosis. However, there is no evaluation criteria to accurately assess the possibility of LN metastasis. Therefore, this study aims to establish an effective nomogram for prognosis prediction. In this study, 285 EGC patients from January 2010 to December 2015 were enrolled. Pearson's Chi-Square (χ2) test (including continuity correction when appropriate) and logistics regression analyses was used to identify the risk factors for LN metastasis. The independent risk factors identified were then incorporated in a nomogram model. The predictive accuracy and discriminative ability of the nomogram were evaluated by receiver operating characteristic curve (ROC) and calibration curve. LN metastasis occurred in 59 (20.7%) EGC patients. And most of these patients were submucosal cancers (48/59). Chi-square test indicated lymphovascular emboli, carbohydrate antigen 19-9 (CA19-9), ulcer, tumor size, tumor infiltration and histological grade were the risk factors, and multivariate logistics analyses confirmed all these six factors were independent risk factors of LN metastasis, which were selected to construct the nomogram. The nomogram proved well calibrated and had good discriminative ability (C-index value: 0.842). The proposed nomogram could result in more-accurate risk prediction for EGC patients.

Comparison of a Tumor-Ratio-Metastasis Staging System and the 8th AJCC TNM Staging System for Gastric Cancer.

BACKGROUND: Despite the implementation of the 8th American Joint Committee on Cancer (AJCC) TNM staging system for gastric cancer (GC) in 2017, it still holds a significant level of stage migration which affects patients' proper classification and accurate prognosis. Here, to reduce this effect, we evaluated the prognostic value of a lymph node ratio (LNR) and established a novel tumor-ratio-metastasis (TRM) staging system. METHOD: The data of 15,206 GC patients from the Sun Yat-sen University Cancer Center (Training set; n=2,032) and the US Surveillance, Epidemiology, and End Results (SEER) database (Validation set; n=13,174) were analyzed. The training set was classified into 5 LNR categories, based on which the novel TRM staging system was constructed. The overall survival (OS) between the TRM and AJCC TNM systems was compared in the training set and validated in the validation set. The likelihood ratio x 2, liner trend x 2, C-index, and Akaike information criterion (AIC) values were used to measure the discriminatory ability between the two different staging systems. Decision curve analyses (DCAs) were conducted to test the clinical value of the two staging systems. RESULT: The patients were classified into the following categories: LNR0: 0%, LNR1: 0%60%. Univariate analyses demonstrated that the log-rank x 2 of the LNR stage (Training/Validation set: x 2 = 463.1/2880.8) was larger than the AJCC pN stage (Training/Validation set: x 2 = 281.5/2240.8). For both the training set and validation set, stratified analyses using the Kaplan-Meier method identified significantly heterogeneous OS in every pN category but only one using the LNR. The TRM staging system had higher likelihood ratio x 2, liner trend x 2, C-index and smaller AIC values than the TNM system. CONCLUSION: The TRM staging system demonstrated improved homogeneity and discriminatory ability in predicting the prognosis of GC patients compared with the AJCC TNM staging system.