Identification of Five Glycolysis-Related Gene Signature and Risk Score Model for Colorectal Cancer

Abstract

Metabolic changes, especially in glucose metabolism, are widely established during the occurrence and development of tumors and regarded as biological markers of pan-cancer. The well-known ‘Warburg effect’ demonstrates that cancer cells prefer aerobic glycolysis even if there is sufficient ambient oxygen. Accumulating evidence suggests that aerobic glycolysis plays a pivotal role in colorectal cancer (CRC) development. However, few studies have examined the relationship of glycolytic gene clusters with prognosis of CRC patients. Here, our aim is to build a glycolysis-associated gene signature as a biomarker for colorectal cancer. The mRNA sequencing and corresponding clinical data were downloaded from TCGA and GEO databases. Gene set enrichment analysis (GSEA) was performed, indicating that four gene clusters were significantly enriched, which revealed the inextricable relationship of CRC with glycolysis. By comparing gene expression of cancer and adjacent samples, 236 genes were identified. Univariate, multivariate, and LASSO Cox regression analyses screened out five prognostic-related genes (ENO3, GPC1, P4HA1, SPAG4, and STC2). Kaplan–Meier curves and receiver operating characteristic curves (ROC, AUC = 0.766) showed that the risk model could become an effective prognostic indicator (P < 0.001). Multivariate Cox analysis also revealed that this risk model is independent of age and TNM stages. We further validated this risk model in external cohorts (GES38832 and GSE39582), showing these five glycolytic genes could emerge as reliable predictors for CRC patients’ outcomes. Lastly, based on five genes and risk score, we construct a nomogram model assessed by C-index (0.7905) and calibration plot. In conclusion, we highlighted the clinical significance of glycolysis in CRC and constructed a glycolysis-related prognostic model, providing a promising target for glycolysis regulation in CRC.

Development of an Aging-Related Gene Signature for Predicting Prognosis, Immunotherapy, and Chemotherapy Benefits in Rectal Cancer

“…Our univariate Cox regression analysis results show that T, N, and M stages were all risk factors of rectal cancer prognosis. However, after including other prognostic variables, only the N stage could independently predict patients' prognosis, consistent with previous studies (Di et al, 2020;Zhu et al, 2021). Our data indicate that more reliable prognostic markers be included in the clinic.…”

Identification of a Ferroptosis-Related Long Noncoding RNA Prognostic Signature and Its Predictive Ability to Immunotherapy in Hepatocellular Carcinoma

“…The DEGs were validated using the following cutoffs: |log2FC| ≥ 1 and FDR <0.05. The linear models for microarray data (LIMMA) R package was performed for DEGs identified between paracancerous and cancer samples as we reported before ( Zhu et al, 2021 ). p values were adjusted using the Benjamini & Hochberg (BH) multiple testing correction.…”

ENO3 Inhibits Growth and Metastasis of Hepatocellular Carcinoma via Wnt/β-Catenin Signaling Pathway

“…Up till now, the effects of ENO3 on tumors remain controversial, and its effects might be different depending on a variety of cell types. For example, previous researches reported that ENO3 was highly expressed in STK11 mutant lung cancer, colorectal cancer, and its ectopic expression correlated with a worse outcome of patients by bioinformatic analysis ( Park et al, 2019 ; Zhu et al, 2021 ). However, the results were converse in pancreatic carcinoma and HCC ( Liu et al, 2019 ; Tan et al, 2020 ).…”

“…Apart from these, ENO3 has also been involved in various tumors, though the results are contradictory. For example, ENO3 is up-regulated in STK11 mutant pulmonary carcinoma ( Park et al, 2019 ) and colorectal carcinoma ( Xiaohang et al, 2020 ; Zhu et al, 2021 ), while down-regulated in pancreatic cancer ( Tan et al, 2020 ) and hepatocellular carcinomas ( Liu et al, 2019 ). Interestingly, down-regulation of ENO3 is also found in the activated human hepatic stellate cells, which can induce liver fibrosis and cirrhosis ( Zhong et al, 2015 ).…”