Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival-related microRNA and then constructed a microRNA signature-based prognostic model. The accuracy of the model was evaluated and validated through Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six-microRNA (miRNA-100, miRNA-374a, miRNA-509-3, miRNA-668, miRNA-549, and miRNA-653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high-risk and low-risk patients and predict 3-year and 5-year survival. The six-microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six-microRNA signature can be used to accurately predict the prognosis of GC patients.
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http://dx.doi.org/10.1002/2211-5463.12593 | DOI Listing |
JCO Precis Oncol
May 2023
Division of Medical Oncology, Department of Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Purpose: MicroRNAs (miRNAs) have been evaluated as biomarkers in cancers. Therefore, we aimed to identify a prognostic miRNA signature from The Cancer Genome Atlas (TCGA) database and validate it in the Ramathibodi (RA) locally advanced head and neck squamous cell carcinoma (LA-HNSCC) cohort.
Methods: The correlation between candidate miRNAs and the survival of patients with LA-HNSCC in TCGA database was analyzed.
Cancer Genomics Proteomics
January 2023
Department of Neurosurgery, University Hospital Brno, Brno, Czech Republic;
Background/aim: Brain metastases (BMs) are the most frequent intracranial tumors in adults and one of the greatest challenges for modern oncology. Most are derived from lung, breast, renal cell, and colorectal carcinomas and melanomas. Up to 14% of patients are diagnosed with BMs of unknown primary, which are commonly characterized by an early and aggressive metastatic spread.
View Article and Find Full Text PDFJ Ovarian Res
May 2022
Department of Gynecologic Cancer, Shaanxi Provincial Cancer Hospital, No. 309 Yanta West Road, Shaanxi, 710061, Xi'an, People's Republic of China.
Background: Ovarian cancer (OVC) is a devastating disease worldwide; therefore the identification of prognostic biomarkers is urgently needed. We aimed to determine a robust microRNA signature-based risk score system that could predict the overall survival (OS) of patients with OVC.
Methods: We extracted the microRNA expression profiles and corresponding clinical data of 467 OVC patients from The Cancer Genome Atlas (TCGA) database and further divided this data into training, validation and complete cohorts.
Int J Gen Med
January 2022
Department of General Surgery, Xiangya Hospital, Central South University, Changsha, Hunan, People's Republic of China.
Purpose: Tumor deposits (TDs) are acknowledged negative prognostic factors in colorectal cancer (CRC), and their pathogenesis remains a puzzle. This study aimed to construct and validate a nomogram available for preoperative TDs prediction in CRC patients.
Patients And Methods: Patients from the Surveillance, Epidemiology, and End Results (SEER) and the cancer genome atlas (TCGA) databases were randomly divided into training and validation sets according to the sample size ratio of 7:3.
J Clin Lab Anal
November 2021
Department of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
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