TICRR as a potential prognostic biomarker for lung adenocarcinoma: A comprehensive analysis using TCGA database.

To investigate the role of TopBP1-interacting checkpoint and replication regulator (TICRR) in the tumorigenesis and prognosis of lung adenocarcinoma (LUAD) patients. Wilcoxon signed-rank test and logistic regression were utilized to analyze the relationship between clinical characteristics and TICRR expression in LUAD from TCGA dataset. Kaplan-Meier plots and Cox regressions were used to assess the impact of TICRR impact on prognosis.

Influence of metabolic syndrome on prognosis of patients with surgically treated esophageal cancer: a meta-analysis.

Background: Metabolic syndrome (MetS) has been related to the increased incidence of esophageal cancer (EC). The aim of the study was to evaluate the influence of MetS on prognosis of patients with surgically treated EC in a systematic review and meta-analysis.

Methods: An extensive search was conducted on PubMed, Embase, Web of Science, Wanfang, and CNKI to identify relevant cohort studies.

Association Between Metabolic Syndrome and the Risk of Lung Cancer: A Meta-Analysis.

Previous studies showed conflicting results regarding the association between metabolic syndrome (MetS) and risk of lung cancer. We performed a systemic review and meta-analysis to determine the relationship between MetS and lung cancer incidence and mortality in adults. Longitudinal follow-up studies were identified by search of Medline, Embase, Cochrane Library, and Web of Science.

The circular RNA hsa_circ_000780 as a potential molecular diagnostic target for gastric cancer.

Background: The present study aimed to identify a specific circular RNA (circRNA) for early diagnosis of gastric cancer (GC).

Methods: Totally 82 patients with GC, 30 with chronic nonatrophic gastritis and 30 with chronic atrophic gastritis were included in this study. Four of the 82 GC patients were selected for screening.

A subregion-based positron emission tomography/computed tomography (PET/CT) radiomics model for the classification of non-small cell lung cancer histopathological subtypes.

Background: This study classifies lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using subregion-based radiomics features extracted from positron emission tomography/computed tomography (PET/CT) images.

Methods: In this study, the standard F-fluorodeoxyglucose (FDG) PET/CT images of 150 patients with lung ADC and 100 patients with SCC were retrospectively collected from the PET Center of the First Affiliated Hospital, College of Medicine, Zhejiang University. First, the 3D feature vector of each tumor voxel (whose basis is PET value, CT value, and CT local dominant orientation) was extracted.