A lipid metabolism-related genes prognosis biomarker associated with the tumor immune microenvironment in colorectal carcinoma

Abstract

Background and aim Lipid metabolic reprogramming is considered to be a new hallmark of malignant tumors. The purpose of this study was to explore the expression profiles of lipid metabolism-related genes (LMRG) in colorectal cancer (CRC). Methods The lipid metabolism statuses of 500 CRC patients from the Cancer Genome Atlas (TCGA) and 523 from the Gene Expression Omnibus (GEO GSE39582) database were analyzed. The risk signature was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression. Results A novel four-LMRG signature (PROCA1, CCKBR, CPT2, and FDFT1) was constructed to predict clinical outcomes in CRC patients. The risk signature was shown to be an independent prognostic factor for CRC and was associated with tumour malignancy. Principal components analysis demonstrated that the risk signature could distinguish between low- and high-risk patients. There were significantly differences in abundances of tumor-infiltrating immune cells and mutational landscape between the two risk groups. Patients in the low-risk group were more likely to have higher tumor mutational burden, stem cell characteristics, and higher PD-L1 expression levels. Furthermore, a genomic-clinicopathologic nomogram was established and shown to be a more effective risk stratification tool than any clinical parameter alone. Conclusions This study demonstrated the prognostic value of LMRG and showed that they may be partially involved in the suppressive immune microenvironment formation.

Comprehensive analysis of transient receptor potential channels-related signature for prognosis, tumor immune microenvironment, and treatment response of colorectal cancer

“…The current TRPC score exhibited excellent prognosis predictive ability in the TCGA, meta-GEO, GSE17537, GSE87211, and FJCH cohorts, and was identified as an independent risk factor of OS (P< 0.05). Furthermore, a nomogram based on the current TRPC score showed higher Cindex and AUC of prognosis prediction compared with published risk scores of previous studies by Yang et al (32), Liu et al (33), and Cao et al (34), and improved net benefits. Moreover, the current TRPC score correlated with clinicopathological characteristics, including TNM stages and microsatellite status.…”

“…Good calibrations were observed in the 1-year, 3-year, and 5-year predicted vs. observed survival rates ( Figure 6B ). The RMS of the TRPC nomogram was higher than that of the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) (P< 0.05, Figure 6C ). The C-index of the TRPC nomogram was 0.779, which was higher than that of the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) ( Figure 6D ).…”

“…The RMS of the TRPC nomogram was higher than that of the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) (P< 0.05, Figure 6C ). The C-index of the TRPC nomogram was 0.779, which was higher than that of the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) ( Figure 6D ). ROC curves revealed that the TRPC nomogram predicted the 1-year, 3-year, and 5-year OS more efficiently than the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) ( Figures 6E–G ).…”

“…ROC curves revealed that the TRPC nomogram predicted the 1-year, 3-year, and 5-year OS more efficiently than the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ) ( Figures 6E–G ). As shown in Figures 6H–J , DCA curves showed that the TRPC nomogram had better 1-year, 3-year, and 5-year OS net benefit than the TRPC score and published models of Yang ( 32 ), Liu ( 33 ), and Cao ( 34 ).…”

A Prognostic Ferroptosis-Related lncRNA Model Associated With Immune Infiltration in Colon Cancer

“…Therefore, early diagnosis is essential for improving the prognosis of CC patients. However, the survival of CC patients is poor because of the complexity of the disease, late disease detection, and lack of reliable risk-assessment biomarkers ( Lin et al, 2020 ; Yang C. et al, 2021 ). Even after treatment, the risk of recurrence and metastasis in CC patients is still high ( Chang et al, 2020 ; Jin et al, 2020 ).…”