Characterization of the metabolic alteration-modulated tumor microenvironment mediated by TP53 mutation and hypoxia

Kunpeng Luo; Zhipeng Qian; Yanan Jiang; Dongxu Lv; Kaibin Zhu; Jing Shao; Ying Hu; Chengqian Lv; Qianqian Huang; Yang Gao; Shizhu Jin; Desi Shang

doi:10.1016/j.compbiomed.2023.107078

Characterization of the metabolic alteration-modulated tumor microenvironment mediated by TP53 mutation and hypoxia

Comput Biol Med. 2023 Sep:163:107078. doi: 10.1016/j.compbiomed.2023.107078. Epub 2023 May 29.

Authors

Kunpeng Luo¹, Zhipeng Qian², Yanan Jiang³, Dongxu Lv⁴, Kaibin Zhu⁵, Jing Shao⁶, Ying Hu⁶, Chengqian Lv⁶, Qianqian Huang⁶, Yang Gao⁶, Shizhu Jin⁷, Desi Shang⁸

Affiliations

¹ The First Affiliated Hospital, Cardiovascular Lab of Big Data and lmaging Artificial Intelligence, Hengyang Medical School, University of South China Hengyang, Hunan, 421001, China; School of Computer, University of South China, Hengyang, Hunan, 421001, China; Department of Gastroenterology and Hepatology, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150081, China. Electronic address: kunpeng_luo@163.com.
² The First Affiliated Hospital, Cardiovascular Lab of Big Data and lmaging Artificial Intelligence, Hengyang Medical School, University of South China Hengyang, Hunan, 421001, China; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.
³ Department of Pharmacology (State-Province Key Laboratories of Biomedicine- Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin, Heilongjiang, 150081, China; Translational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin, Heilongjiang, 150081, China.
⁴ College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China.
⁵ Department of Thoracic Surgery, Harbin Medical University Cancer Hospital, No. 150, Haping Road, Harbin, Heilongjiang, 150081, China.
⁶ Department of Gastroenterology and Hepatology, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150081, China.
⁷ Department of Gastroenterology and Hepatology, Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, 150081, China. Electronic address: drshizhujin@hrbmu.edu.cn.
⁸ The First Affiliated Hospital, Cardiovascular Lab of Big Data and lmaging Artificial Intelligence, Hengyang Medical School, University of South China Hengyang, Hunan, 421001, China; School of Computer, University of South China, Hengyang, Hunan, 421001, China; College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, 150081, China. Electronic address: sds_46@163.com.

PMID: 37356294
DOI: 10.1016/j.compbiomed.2023.107078

Abstract

Background: TP53 mutation and hypoxia play an essential role in cancer progression. However, the metabolic reprogramming and tumor microenvironment (TME) heterogeneity mediated by them are still not fully understood.

Methods: The multi-omics data of 32 cancer types and immunotherapy cohorts were acquired to comprehensively characterize the metabolic reprogramming pattern and the TME across cancer types and explore immunotherapy candidates. An assessment model for metabolic reprogramming was established by integration of multiple machine learning methods, including lasso regression, neural network, elastic network, and survival support vector machine (SVM). Pharmacogenomics analysis and in vitro assay were conducted to identify potential therapeutic drugs.

Results: First, we identified metabolic subtype A (hypoxia-TP53 mutation subtype) and metabolic subtype B (non-hypoxia-TP53 wildtype subtype) in hepatocellular carcinoma (HCC) and showed that metabolic subtype A had an "immune inflamed" microenvironment. Next, we established an assessment model for metabolic reprogramming, which was more effective compared to the traditional prognostic indicators. Then, we identified a potential targeting drug, teniposide. Finally, we performed the pan-cancer analysis to illustrate the role of metabolic reprogramming in cancer and found that the metabolic alteration (MA) score was positively correlated with tumor mutational burden (TMB), neoantigen load, and homologous recombination deficiency (HRD) across cancer types. Meanwhile, we demonstrated that metabolic reprogramming mediated a potential immunotherapy-sensitive microenvironment in bladder cancer and validated it in an immunotherapy cohort.

Conclusion: Metabolic alteration mediated by hypoxia and TP53 mutation is associated with TME modulation and tumor progression across cancer types. In this study, we analyzed the role of metabolic alteration in cancer and propose a predictive model for cancer prognosis and immunotherapy responsiveness. We also explored a potential therapeutic drug, teniposide.

Keywords: Hypoxia; Metabolic alteration; Precise oncology; TP53 mutation; Tumor microenvironment.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinoma, Hepatocellular*
Humans
Hypoxia / genetics
Liver Neoplasms*
Mutation
Teniposide
Tumor Microenvironment
Tumor Suppressor Protein p53 / genetics

Substances

Teniposide
TP53 protein, human
Tumor Suppressor Protein p53