Identification of prognostic genes through expression differentiation during metastatic process in lung adenocarcinoma

Abstract

Cancer is a highly complicated biological process due to large scale heterogeneity. Identification of differentially expressed genes between normal and cancer samples is widely utilized in the discovery of prognostic factors. In this study, based on RNA sequencing data of lung adenocarcinoma, we focused on the expression differentiation during confined (with neither lymph node invasion nor distant metastasis) primary tumors and lymphnode (with only lymph node invasion but not distant metastasis) primary tumors. The result indicated that differentially expressed genes during confined-lymphnode transition were more closely related to patient’s overall survival comparing with those identified from normal-cancer transition. With the aid of public curated biological network, we successfully retrieved the biggest connected module composed of 135 genes, of which the expression was significantly associated with patient’s overall survival, confirmed by 9 independent microarray datasets.

Role of Ultrasound Imaging in the Prediction of TRIM67 in Brain Metastases From Breast Cancer

“…The recent developments in bioinformatics have facilitated the diagnosis and treatment of the disease with the help of largescale biological data (19)(20)(21)(22). The considerable amount of RNA sequencing data and the increasing number of prognostic factors and therapeutic targets identified have considerably aided in the examination of the mechanisms related to cancer development and clinical treatment (23,24). One study used RNA sequencing to probe the cellular origin and evolution of breast cancer in BRCA1 mutant carriers (25).…”