CT‐detected extramural venous invasion‐related gene signature for the overall survival prediction in patients with gastric cancer
| Autor: | Caizhen Feng, Yi Wang, Yingjiang Ye, Bo Gao, Nan Hong, Fan Chai, Shengcai Wei, Jin Cheng |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Oncology
Male Cancer Research medicine.medical_specialty Epithelial-Mesenchymal Transition Metal ion transport Bioinformatics radiogenomics Radiogenomics Risk Assessment Stomach Neoplasms Internal medicine x‐ray tomography medicine Cell Adhesion Humans Imaging Genomics Radiology Nuclear Medicine and imaging Neoplasm Invasiveness Gene extramural venous invasion Research Articles RC254-282 Aged Cell Proliferation Proportional Hazards Models Aged 80 and over Framingham Risk Score Ion Transport business.industry Proportional hazards model Sequence Analysis RNA gastric cancer Cancer Neoplasms. Tumors. Oncology. Including cancer and carcinogens Genomic signature Middle Aged medicine.disease Metals Cohort Female business Tomography X-Ray Computed Research Article |
| Zdroj: | Cancer Medicine, Vol 10, Iss 21, Pp 7816-7830 (2021) Cancer Medicine |
| ISSN: | 2045-7634 |
| Popis: | Background Computed tomography (CT)‐detected extramural venous invasion (EMVI) has been identified as an independent factor that can be used for risk stratification and prediction of prognosis in patients with gastric cancer (GC). Overall survival (OS) is identified as the most important prognostic indicator for GC patients. However, the molecular mechanism of EMVI development and its potential relationship with OS in GC are not fully understood. In this radiogenomics‐based study, we sought to investigate the molecular mechanism underlying CT‐detected EMVI in patients with GC, and aimed to construct a genomic signature based on EMVI‐related genes with the goal of using this signature to predict the OS. Materials and Methods Whole mRNA genome sequencing of frozen tumor samples from 13 locally advanced GC patients was performed to identify EMVI‐related genes. EMVI‐prognostic hub genes were selected based on overlapping EMVI‐related differentially expressed genes and OS‐related genes, using a training cohort of 176 GC patients who were included in The Cancer Genome Atlas database. Another 174 GC patients from this database comprised the external validation cohort. A risk stratification model using a seven‐gene signature was constructed through the use of a least absolute shrinkage and selection operator Cox regression model. Results Patients with high risk score showed significantly reduced OS (training cohort, p = 1.143e‐04; validation cohort, p = 2.429e‐02). Risk score was an independent predictor of OS in multivariate Cox regression analyses (training cohort, HR = 2.758; 95% CI: 1.825–4.169; validation cohort, HR = 2.173; 95% CI: 1.347–3.505; p Imaging feature of computed tomography‐detected extramural venous invasion (EMVI) has been identified as an independent risk factor of gastric cancer (GC). We aimed to investigate the molecular mechanism of EMVI based on whole mRNA genome sequencing of frozen cancerous samples from 13 locally advanced GC. Then using TCGA database, we constructed an EMVI‐related gene model and found it could predict the prognosis in patients with GC. |
| Databáze: | OpenAIRE |
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