Dataset Information

A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling.

ABSTRACT: Numerous colon cancer cases are resistant to chemotherapy based on oxaliplatin and suffer from relapse. A number of survival- and prognosis-related biomarkers have been identified based on database mining for patients who develop drug resistance, but the single individual gene biomarker cannot attain high specificity and sensitivity in prognosis prediction. This work was conducted aiming to establish a new gene signature using oxaliplatin resistance-related genes to predict the prognosis for colon cancer. To this end, we downloaded gene expression profile data of cell lines that are resistant and not resistant to oxaliplatin from the Gene Expression Omnibus (GEO) database. Altogether, 495 oxaliplatin resistance-related genes were searched by weighted gene co-expression network analysis (WGCNA) and differential expression analysis. As suggested by functional analysis, the above genes were mostly enriched into cell adhesion and immune processes. Besides, a signature was built based on four oxaliplatin resistance-related genes selected from the training set to predict the overall survival (OS) by stepwise regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. Relative to the low risk score group, the high risk score group had dismal OS (P < 0.0001). Moreover, the area under the curve (AUC) value regarding the 5-year OS was 0.72, indicating that the risk score was accurate in the prediction of OS for colon cancer patients (AUC >0.7). Additionally, multivariate Cox regression suggested that the signature constructed based on four oxaliplatin resistance-related genes predicted the prognosis for colon cancer cases [hazard ratio (HR), 2.77; 95% CI, 2.03-3.78; P < 0.001]. Finally, external test sets were utilized to further validate the stability and accuracy of oxaliplatin resistance-related gene signature for prognosis of colon cancer patients. To sum up, this study establishes a signature based on four oxaliplatin resistance-related genes for predicting the survival of colon cancer patients, which sheds more light on the mechanisms of oxaliplatin resistance and helps identify colon cancer cases with a dismal prognostic outcome.

SUBMITTER: Lin Q

PROVIDER: S-EPMC8138443 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: Colon adenocarcinoma (COAD) is one of the most prevalent cancers worldwide and has become a leading cause of cancer death. Although many potential biomarkers of COAD have been screened with the bioinformatics method, it is necessary to explore novel markers for the diagnosis and appropriate individual treatments for COAD patients due to the high heterogeneity of this disease. Epithelial-to-mesenchymal transition (EMT)-mediated tumor metastasis suggests poor prognosis of cancers. Ferroptosis is involved in tumor development. EMT signaling can increase the cellular sensitivity to ferroptosis in tumors. The aim of our study is finding novel prognostic biomarkers to determine COAD patients for predicting efficiency of metastasis status and targeting precise ferroptosis-related therapy. Methods: A novel gene signature related to metastasis and ferroptosis was identified combing with risk model and WGCNA analysis with R software. The biological functions and predictive ability of the signature in COAD were explored through bioinformatics analysis. Results: We established a four-gene prognostic signature (MMP7, YAP1, PCOLCE, and HOXC11) based on EMT and ferroptosis related genes and validated the reliability and effectiveness of this model in COAD. This four-gene prognostic signature was closely connected with metastasis and ferroptosis sensitivity of COAD. Moreover, WGCNA analysis further confirmed the correlation between PCOLCE, HOXC11, and liver and lymphatic invasion of COAD. Conclusion: The four genes may become potential prognostic biomarkers to identify COAD patients with metastasis. Moreover, this four-gene signature may be able to determine the COAD suitable with ferroptosis induction therapy. Finally, PCOLCE2 and HOXC11 were selected individually because of their novelties and precise prediction ability. Overall, this signature provided novel possibilities for better prognostic evaluation of COAD patients and may be of great guiding significance for individualized treatment and clinical decision.

Dataset Information

A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets