Short-term and long-term clinical outcomes of combined major vessel resection for hilar cholangiocarcinoma: a propensity score analysis

Purpose@#In the treatment of hilar cholangiocarcinoma (HCCA), combined resection of important hepatic vessels remains controversial. The purpose of this study was to compare the postoperative complications and prognosis of combined and non-combined major vessel resections in patients undergoing radical resection for HCCA. @*Methods@#In this study, patients with HCCA who underwent curative resection between January 2007 and December 2018 were retrospectively enrolled. Postoperative complications and prognosis between the groups were compared using propensity score-matching (PSM) analysis. @*Results@#There were 310 patients included in this study. The portal vein resection (PVR) and hepatic artery resection (HAR) groups had a higher incidence of postoperative complications than the control group. Patients in the HAR group had an increased risk of abdominal and pleural effusion after surgery. Patients who underwent combined PVR had better overall survival (OS; P = 0.020) and disease-free survival (DFS; P = 0.020). After curative-intent resection, patients in the HAR group had improved OS (P = 0.027) and DFS (P = 0.023). The postoperative complications of combined vascular resection (VR) did not worsen long-term survival for patients. @*Conclusion@#In patients with HCCA, combined VR improved prognosis. The postoperative complications of combined VR do not worsen patient survival. Therefore, radical surgical resection is recommended.

Application of weighted gene co-expression network analysis technology in human tumor research / 肿瘤

Weighted gene co-expression network analysis (WGCNA) technology is a high-throughput gene expression data mining algorithm, which uses the idea of system biology to find the correlation of gene expression and to construct gene modules, so as to further discovery a high-throughput data mining algorithm with biological significance modules. In recent years, with the deep understanding of human diseases to gene level, WGCNA has been used increasingly in the researches of various diseases, especially in mining the highthroughput data about tumor-related genes. Moreover, with the continuous improvement of this technology, the research of this technology in disease pathogenesis, development and treatment etc has been developed from a single co-expression network analysis to the multiple technologies [such as genome-wide association study (GWAS) and support vector machine (SVM)] combined WGCNA or the innovative applicated WGCNA. As a high-throughput research method based on gene level, WGCNA is playing an important role.