ArticleFrontiers in pharmacology2025
New prognostic features and personalized treatment strategies of mitochondrial related genes in colorectal cancer patients.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Mitochondrial gene expression-based model for the prediction of thyroid cancer prognosis.Endocrine connections · 2026Article
- TRP channel expression patterns define molecular subtypes, prognosis, and therapeutic targets in gastric cancer.Frontiers in immunology · 2026Article
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Authors and funding
6 authors.
Funding
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Abstract
Colorectal cancer (CRC) is a common and aggressive malignancy with the complex and varied molecular landscape. Mitochondria play a pivotal role in the metabolic reprogramming of cancer cells, and their function can profoundly influence tumor progression. Therefore, identifying mitochondrial genes with immune-related features may offer a promising new approach for prognosis in CRC. Mitochondrial-associated genes were retrieved from the MITOCARTA 3.0 dataset. The LASSO regression method was applied to identify prognostic genes, while the area under the ROC curve and nomograms were used to assess the robustness of the model. Single-sample genomic enrichment analysis (ssGSEA) was utilized to explore the relationship between model genes and immune infiltration, and drug sensitivity analysis was conducted to identify potential therapeutic agents. Cellular assays were performed to validate the effectiveness of identified drugs. Key mitochondrial genes, including SUCLG2, ACACB, OSBPL1A, and TRAP1, have been identified as significant prognostic markers in CRC. The expression of ACACB and OSBPL1A progressively increased, while SUCLG2 and TRAP1 expression decreased in patients. ROC curve analysis of the TCGA dataset showed an area under the curve (AUC) greater than 0.6 for 1-, 2-, and 3-year survival predictions, demonstrating the strong prognostic potential of this model. Additionally, the model was strongly correlated with immune cells, particularly CD8
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