Screening ferroptosis related genes influencing prognosis of colon cancer through bioinformatics analysis

LI Xiao-Jun; ZHANG Ya-Min

doi:10.16098/j.issn.0529-1356.2023.04.010

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Acta Anatomica Sinica ›› 2023, Vol. 54 ›› Issue (4) : 445-452. DOI: 10.16098/j.issn.0529-1356.2023.04.010

Cancer Biology

Screening ferroptosis related genes influencing prognosis of colon cancer through bioinformatics analysis

LI Xiao-jun¹ ZHANG Ya-min2^*

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Abstract

Objective To explore ferroptosis-related long non-coding RNAs (lncRNAs) with prognostic significance in colon cancer (CC), and then construct a prognosis-related predictive scoring model. To search for ferroptosis-related differential expressed genes co-expressed with prognosis-related lncRNAs. Methods Ferroptosis-related genes (FGs) were downloaded from FerrDb database; The expression data of 41 adjacent normal tissues and 473 tumor tissues, and clinical data of 452 patients were successfully downloaded. Co-expression and differential expression analysis was performed to identify differentially expressed ferroptosis-related lncRNAs (DEFlncRNAs), and univariate Cox regression analysis was used to screen statistically significant prognosis-related DEFlncRNAs, and then multivariate Cox regression analysis was used to construct a prognostic model, calculate risk score among CC patients and divide patients by the median risk score. Kaplan-Meier curves, univariate and multivariate Cox regression analyses, and receiver operationg characteristic(ROC) curve were used to reveale great accuracy of the model. Then, a nomogram was drawed to predict the survival among CC patients. Finally, the differentially expressed ferroptosis-related genes regulating DEFlncRNAs were found by co-expression analysis, and the different expression was verified by immunohistochemical experiments. Result Expression and clinical data among colon cancer (CC) patients were downloaded from TCGA database. A risk prognostic model containing 28 lncRNAs to predict the prognosis among CC patients was successfully constructed. An effective clinical nomogram for predicting the overall survival of CC patients was successfully constructed. Finally, the co-expression analysis of DEFlncRNAs and differentially expressed ferroptosis-related genes (DEFGs) was preformed to obtain a co-expression network, including17 key DEFGs, with the correlation coefficient filter criteria (|corFilter|)>0.4 and P value filter criteria (P value filter)<0.05. Immunohistochemical experiments confirmed ANGPTL7 was highly expressed in the adjacent tissues among CC patients. Conclusion Successfully constructed a prognostic-related model among CC patients containing 28 DEFlncRNAs, and 17 DEFGs was finally obtained.

Key words

Ferroptosis / Coloncellular carcinoma / Prognostic model / Bioinformatics / Cox regression analysis / Human

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LI Xiao-jun ZHANG Ya-min. Screening ferroptosis related genes influencing prognosis of colon cancer through bioinformatics analysis[J]. Acta Anatomica Sinica. 2023, 54(4): 445-452 https://doi.org/10.16098/j.issn.0529-1356.2023.04.010

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