Open Access

ARTICLE

Identification and validation of novel prognostic fatty acid metabolic gene signatures in colon adenocarcinoma through systematic approaches

HENG ZHANG^1,#, WENJING CHENG^2,#, HAIBO ZHAO², WEIDONG CHEN², QIUJIE ZHANG^2,*, QING-QING YU^2,*

1 Department of Laboratory, Shandong Daizhuang Hospital, Jining, 272051, China
2 Jining No.1 People’s Hospital, Shandong First Medical University, Jining, 272000, China

* Corresponding Authors: QIUJIE ZHANG. Email: ; QING-QING YU. Email:
# These authors contributed equally to this work

(This article belongs to the Special Issue: Transcriptome Analysis in Tumor Microenvironment and Tumor Heterogeneity)

Oncology Research 2024, 32(2), 297-308. https://doi.org/10.32604/or.2023.043138

Received 23 June 2023; Accepted 09 August 2023; Issue published 28 December 2023

Abstract

Background: Colorectal cancer (CRC) belongs to the class of significantly malignant tumors found in humans. Recently, dysregulated fatty acid metabolism (FAM) has been a topic of attention due to its modulation in cancer, specifically CRC. However, the regulatory FAM pathways in CRC require comprehensive elucidation. Methods: The clinical and gene expression data of 175 fatty acid metabolic genes (FAMGs) linked with colon adenocarcinoma (COAD) and normal cornerstone genes were gathered through The Cancer Genome Atlas (TCGA)-COAD corroborating with the Molecular Signature Database v7.2 (MSigDB). Initially, crucial prognostic genes were selected by uni- and multi-variate Cox proportional regression analyses; then, depending upon these identified signature genes and clinical variables, a nomogram was generated. Lastly, to assess tumor immune characteristics, concomitant evaluation of tumor immune evasion/risk scoring were elucidated. Results: A 8-gene signature, including ACBD4, ACOX1, CD36, CPT2, ELOVL3, ELOVL6, ENO3, and SUCLG2, was generated, and depending upon this, CRC patients were categorized within high-risk (H-R) and low-risk (L-R) cohorts. Furthermore, risk and age-based nomograms indicated moderate discrimination and good calibration. The data confirmed that the 8-gene model efficiently predicted CRC patients’ prognosis. Moreover, according to the conjoint analysis of tumor immune evasion and the risk scorings, the H-R cohort had an immunosuppressive tumor microenvironment, which caused a substandard prognosis. Conclusion: This investigation established a FAMGs-based prognostic model with substantially high predictive value, providing the possibility for improved individualized treatment for CRC individuals.

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Supplementary Material

Supplementary Material File

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