Xiaodie Liu, Wenhui Wang, Xiaolei Zhang, Jing Liang, Dingqing Feng, Yuebo Li, Ming Xue, Bin Ling
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引用次数: 0
Abstract
Endometrial cancer (EC), the second most common malignancy in the female reproductive system, has garnered increasing attention for its genomic heterogeneity, but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in EC through comprehensive multi-omics analysis (RNA-seq datasets from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and GEO datasets; the Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy. Unsupervised consensus clustering was performed to categorize EC patients into three metabolism-pathways-based subgroups (MPS). These MPS subgroups had distinct clinical prognoses, transcriptomic and genomic alterations, immune microenvironment landscape, and unique patterns of chemotherapy sensitivity. Moreover, the MPS2 subgroup has a better response to immunotherapy. Finally, three machine learning algorithms (LASSO, random forest, and stepwise multivariate Cox regression) were used for developing a prognostic “Metagene” signature based on metabolic molecules. Thus, a thirteen-hub-gene-based classifier was constructed to predict patients’ MPS subtype offering a more accessible and practical approach. This metabolism-based classification system can potentially enhance prognostic predictions and guide clinical strategies for immunotherapy and metabolism-targeted therapy in EC.
期刊介绍:
Molecular Therapy Nucleic Acids is an international, open-access journal that publishes high-quality research in nucleic-acid-based therapeutics to treat and correct genetic and acquired diseases. It is the official journal of the American Society of Gene & Cell Therapy and is built upon the success of Molecular Therapy. The journal focuses on gene- and oligonucleotide-based therapies and publishes peer-reviewed research, reviews, and commentaries. Its impact factor for 2022 is 8.8. The subject areas covered include the development of therapeutics based on nucleic acids and their derivatives, vector development for RNA-based therapeutics delivery, utilization of gene-modifying agents like Zn finger nucleases and triplex-forming oligonucleotides, pre-clinical target validation, safety and efficacy studies, and clinical trials.