Identification of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in alimentary tract malignancies

• Published in: BMC bioinformatics Vol. 24; no. 1; p. 184
• Main Authors: Xie, Yangyang, Song, Xue, Du, Danwei, Ni, Zhongkai, Huang, Hai
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 04.05.2023; BioMed Central; BMC
• Subjects: Alimentary tract malignancies; Analysis; Apoptosis; Calibration; Cancer; Cell Death; Copper; Correlation analysis; Cuproptosis; Databases, Factual; Digestive tract; Gastric cancer; Gene expression; Gene mutations; Genetic aspects; Genomes; Genomics; Health aspects; Health risk assessment; Humans; Immune checkpoint inhibitors; Immune infiltration; Immunology; Immunotherapy; Kinases; Long non-coding RNA; Malignancy; Medical prognosis; Metastases; Metastasis; Methods; Mutation; Neoplasms; Nomograms; Nomography (Mathematics); Non-coding RNA; Patient outcomes; Patients; Point mutation; Prognosis; Regression analysis; Risk; Risk groups; RNA; RNA, Long Noncoding - genetics; Survival; Survival analysis; Taiwan; China; Prognosis; Cuproptosis; Alimentary tract malignancies; Immune infiltration; Long non-coding RNA
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-023-05314-z

Alimentary tract malignancies (ATM) caused nearly one-third of all tumor-related death. Cuproptosis is a newly identified cell death pattern. The role of cuproptosis-associated lncRNAs in ATM is unknown. Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to identify prognostic lncRNAs by Cox regression and LASSO. Then a predictive nomogram was constructed based on seven prognostic lncRNAs. In addition, the prognostic potential of the seven-lncRNA signature was verified via survival analysis, the receiver operating characteristic (ROC) curve, calibration curve, and clinicopathologic characteristics correlation analysis. Furthermore, we explored the associations between the signature risk score and immune landscape, and somatic gene mutation. We identified 1211 cuproptosis-related lncRNAs and seven survival-related lncRNAs. Patients were categorized into high-risk and low-risk groups with significantly different prognoses. ROC and calibration curve confirmed the good prediction capability of the risk model and nomogram. Somatic mutations between the two groups were compared. We also found that patients in the two groups responded differently to immune checkpoint inhibitors and immunotherapy. The proposed novel seven lncRNAs nomogram could predict prognosis and guide treatment of ATM. Further research was required to validate the nomogram.