Exploring the relationship between lactate metabolism and immunological function in colorectal cancer through genes identification and analysis

Enkui Zhang; Xueliang Zhou; Xiaodong Fan; Shuchun Li; Chengsheng Ding; Hiju Hong; Batuer Aikemu; Guang Yang; Galiya Yesseyeva; Xiao Yang; Junjun Ma; Minhua Zheng

doi:10.3389/fcell.2023.1173803

Exploring the relationship between lactate metabolism and immunological function in colorectal cancer through genes identification and analysis

Front Cell Dev Biol. 2023 Aug 24:11:1173803. doi: 10.3389/fcell.2023.1173803. eCollection 2023.

Authors

Enkui Zhang^{1

2

3}, Xueliang Zhou^{1

2}, Xiaodong Fan^{1

2}, Shuchun Li^{1

2}, Chengsheng Ding^{1

2}, Hiju Hong^{1

2}, Batuer Aikemu^{1

2}, Guang Yang^{1

2}, Galiya Yesseyeva^{1

2}, Xiao Yang^{1

2

4}, Junjun Ma^{1

2

4}, Minhua Zheng^{1

2

4}

Affiliations

¹ Department of General Surgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
² Shanghai Minimally Invasive Surgery Center, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
³ Department of General Surgery, Peking University First Hospital, Beijing, China.
⁴ Department of General Surgery and Carson International Cancer Research Center, Shenzhen University General Hospital and Shenzhen University Clinical Medical Academy, Shenzhen, China.

Abstract

Introduction: Metabolic dysregulation is a widely acknowledged contributor for the development and tumorigenesis of colorectal cancer (CRC), highlighting the need for reliable prognostic biomarkers in this malignancy. Methods: Herein, we identified key genes relevant to CRC metabolism through a comprehensive analysis of lactate metabolism-related genes from GSEA MsigDB, employing univariate Cox regression analysis and random forest algorithms. Clinical prognostic analysis was performed following identification of three key genes, and consistent clustering enabled the classification of public datasets into three patterns with significant prognostic differences. The molecular pathways and tumor microenvironment (TME) of these patterns were then investigated through correlation analyses. Quantitative PCR was employed to quantify the mRNA expression levels of the three pivotal genes in CRC tissue. Single-cell RNA sequencing data and fluorescent multiplex immunohistochemistry were utilized to analyze relevant T cells and validate the correlation between key genes and CD4⁺ T cells. Results: Our analysis revealed that MPC1, COQ2, and ADAMTS13 significantly stratify the cohort into three patterns with distinct prognoses. Additionally, the immune infiltration and molecular pathways were significantly different for each pattern. Among the key genes, MPC1 and COQ2 were positively associated with good prognosis, whereas ADAMTS13 was negatively associated with good prognosis. Single-cell RNA sequencing (scRNA-seq) data illustrated that the relationship between three key genes and T cells, which was further confirmed by the results of fluorescent multiplex immunohistochemistry demonstrating a positive correlation between MPC1 and COQ2 with CD4⁺ T cells and a negative correlation between ADAMTS13 and CD4⁺ T cells. Discussion: These findings suggest that the three key lactate metabolism genes, MPC1, COQ2, and ADAMTS13, may serve as effective prognostic biomarkers and support the link between lactate metabolism and the immune microenvironment in CRC.

Keywords: colorectal cancer; immune infiltration; lactate metabolism; prognosis; validation.

Grants and funding

This study was supported by the National Natural Science Foundation of China (No. 82072614 to MZ, No. 81802933 to XY), Shanghai Municipal Key Clinical Specialty (shslczdzk00102 to MZ), Science and Technology Commission of Shanghai Municipality under Grant (22ZR1439700 to XY), and Guangci Distinguished Young Scholars Training Program under Grant (GCQN-2019-A07 to XY) and Shanghai Sailing Program (23YF1424900 to BA).