Abstract
BackgroundMetabolic reprograming have been associated with cancer occurrence and progression within the tumor immune microenvironment. However, the prognostic potential of metabolism-related genes in colorectal cancer (CRC) has not been comprehensively studied. Here, we investigated metabolic transcript-related CRC subtypes and relevant immune landscapes, and developed a metabolic risk score (MRS) for survival prediction.MethodsMetabolism-related genes were collected from the Molecular Signatures Database and metabolic subtypes were identified using an unsupervised clustering algorithm based on the expression profiles of survival-related metabolic genes in GSE39582. The ssGSEA and ESTIMATE methods were applied to estimate the immune infiltration among subtypes. The MRS model was developed using LASSO Cox regression in the GSE39582 dataset and independently validated in the TCGA CRC and GSE17537 datasets.ResultsWe identified two metabolism-related subtypes (cluster-A and cluster-B) of CRC based on the expression profiles of 539 survival-related metabolic genes with distinct immune profiles and notably different prognoses. The cluster-B subtype had a shorter OS and RFS than the cluster-A subtype. Eighteen metabolism-related genes that were mostly involved in lipid metabolism pathways were used to build the MRS in GSE39582. Patients with higher MRS had worse prognosis than those with lower MRS (HR 3.45, P < 0.001). The prognostic role of MRS was validated in the TCGA CRC (HR 2.12, P = 0.00017) and GSE17537 datasets (HR 2.67, P = 0.039). Time-dependent receiver operating characteristic curve and stratified analyses revealed the robust predictive ability of the MRS in each dataset. Multivariate Cox regression analysis indicted that the MRS could predict OS independent of TNM stage and age.ConclusionsOur study provides novel insight into metabolic heterogeneity and its relationship with immune landscape in CRC. The MRS was identified as a robust prognostic marker and may facilitate individualized therapy for CRC patients.
Highlights
Metabolic reprograming have been associated with cancer occurrence and progression within the tumor immune microenvironment
The metabolic risk score (MRS) was identified as a robust prognostic marker and may facilitate individualized therapy for colorectal cancer (CRC) patients
The TNM stages for GSE39582 and The Cancer Genome Atlas (TCGA) datasets were redefined according to the America Joint Committee on Cancer (AJCC) 8th classification system and the following criteria: first, samples with any uncertain pathological T, N, and M stages were classified as samples with unknown stages; second, samples that showed clear T, N, and M stages separately but lacked an available summarized stage were reclassified
Summary
Metabolic reprograming have been associated with cancer occurrence and progression within the tumor immune microenvironment. The prognostic potential of metabolism-related genes in colorectal cancer (CRC) has not been comprehensively studied. We investigated metabolic transcript-related CRC subtypes and relevant immune landscapes, and developed a metabolic risk score (MRS) for survival prediction. Colorectal cancer (CRC) is one of the most common malignancies, ranking as the second leading cause of cancer-related death worldwide [1]. In the past few decades, the occurrence and mortality of CRC have decreased steadily due to advanced screening programs comprising fecal occult blood testing, direct colonic visualization, and noninvasive imaging techniques [1, 2]. The 5-year survival rate of CRC remains dismal [1, 3]. Novel prognostic factors to identify CRC patients’ risk more accurately are urgently needed
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
