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Updated: Jul 25, 2025
Induction and Testing of Hypoxia in Cell Culture
Published on: August 12, 2011
Characterization of the metabolic alteration-modulated tumor microenvironment mediated by TP53 mutation and hypoxia
Kunpeng Luo1, Zhipeng Qian2, Yanan Jiang3
1The 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.
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.
Insights
Metabolic reprogramming driven by TP53 mutations and hypoxia influences tumor microenvironment and cancer progression. This study developed a model to predict prognosis and immunotherapy response, identifying teniposide as a potential drug.
Area of Science:
- Oncology
- Cancer Metabolism
- Tumor Microenvironment
Background:
- TP53 mutations and hypoxia are key drivers of cancer progression.
- Metabolic reprogramming and tumor microenvironment (TME) heterogeneity in cancer remain incompletely understood.
Purpose of the Study:
- To comprehensively analyze metabolic reprogramming patterns and TME characteristics across diverse cancer types.
- To develop a predictive model for cancer prognosis and immunotherapy responsiveness.
- To identify potential therapeutic targets for cancer treatment.
Main Methods:
- Utilized multi-omics data from 32 cancer types and immunotherapy cohorts.
- Developed a metabolic reprogramming assessment model using machine learning (lasso regression, neural network, elastic net, survival SVM).
- Performed pharmacogenomics analysis and in vitro assays to identify therapeutic drugs.
Main Results:
- Identified distinct metabolic subtypes in hepatocellular carcinoma (HCC) linked to TME characteristics.
- The developed metabolic reprogramming model outperformed traditional prognostic indicators.
- A metabolic alteration (MA) score correlated positively with tumor mutational burden (TMB), neoantigen load, and homologous recombination deficiency (HRD) across cancers.
- Metabolic reprogramming was linked to immunotherapy sensitivity in bladder cancer.
Conclusions:
- Metabolic alterations driven by hypoxia and TP53 mutations modulate the TME and impact cancer progression.
- A predictive model for cancer prognosis and immunotherapy response was established.
- Teniposide was identified as a potential therapeutic drug for targeting metabolic alterations in cancer.
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