Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3

Chunli Kong; Liyun Zheng; Shiji Fang; Minjiang Chen; Guihan Lin; Rongfang Qiu; Zhongwei Zhao; Weiqian Chen; Jingjing Song; Yang Yang; Jiansong Ji

doi:10.1177/15330338231195494

Predictive Models for Colon Adenocarcinoma Diagnosis, Prognosis, and Immune Microenvironment Based on 2 Hypoxia-Related Genes: KDM3A and ENO3

Technol Cancer Res Treat. 2023 Jan-Dec:22:15330338231195494. doi: 10.1177/15330338231195494.

Authors

Chunli Kong^{1

2

3}, Liyun Zheng^{1

2

3}, Shiji Fang^{1

2

3}, Minjiang Chen^{1

2

3}, Guihan Lin^{1

2

3}, Rongfang Qiu^{1

2

3}, Zhongwei Zhao^{1

2

3}, Weiqian Chen^{1

2

3}, Jingjing Song^{1

2

3}, Yang Yang^{1

2

3}, Jiansong Ji^{1

2

3}

Affiliations

¹ Department of Radiology, Clinical College of The Affiliated Central Hospital, Lishui University, Lishui, China.
² Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, China.
³ Department of Radiology, Lishui Hospital of Zhejiang University, Lishui, China.

Abstract

Background: Hypoxia is known to play a critical role in tumor occurrence, progression, prognosis, and therapy resistance. However, few studies have investigated hypoxia markers for diagnosing and predicting prognosis in colon adenocarcinoma (COAD). This study aims to identify a hypoxia genes-based biomarker for predicting COAD patients' prognosis and response to immunotherapy on an individual basis. Methods: Hypoxia-related genes were extracted from the Molecular Signatures Database. Gene expression, clinical data, and mutation data of COAD were collected retrospectively from the Cancer Genome Atlas, the Gene Expression Omnibus, and the International Cancer Genome Consortium databases. Univariate and multivariate cox regression, and the least absolute shrinkage and selection operator method were used to select the genes most associated with the prognosis of COAD patients. Kaplan-Meier survival analysis, receiver operating characteristic curves, calibration curves, and decision curve analyses were performed to validate the efficacy of the signature in predicting the prognosis of COAD patients. EdU incorporation assays, cell survival assays, western blot assays, and trans-well invasion assays were performed to further confirm the function of the screened genes in tumorigenesis. Results: ENO3 and KDM3A were identified as key genes for constructing prognostic and diagnostic signatures, which were found to be independent risk factors for predicting the prognosis and diagnosis of COAD patients. Using these signatures, COAD patients could be stratified into high-risk and low-risk groups, with the latter exhibiting better overall survival outcomes. Moreover, the high-risk group displayed elevated levels of immune checkpoint genes and tumor mutation burden, indicating that these patients may benefit from immune checkpoint inhibitor therapy. Conclusion: The signature developed in this study demonstrates excellent efficacy in prognosticating the outcomes of COAD patients. Moreover, it can serve as a valuable tool for clinicians to identify COAD patients who are suitable for ICI therapy.

Keywords: ENO3; KDM3A; colon adenocarcinoma; hypoxia; immune checkpoint inhibitor.

MeSH terms

Adenocarcinoma* / diagnosis
Adenocarcinoma* / genetics
Colonic Neoplasms* / diagnosis
Colonic Neoplasms* / genetics
Humans
Hypoxia
Jumonji Domain-Containing Histone Demethylases
Prognosis
Retrospective Studies
Tumor Microenvironment / genetics

Substances

KDM3A protein, human
Jumonji Domain-Containing Histone Demethylases