首页|China-Japan Friendship Hospital Reports Findings in Endometrial Cancer (Metaboli sm pathway-based subtyping in endometrial cancer: An integrated study by multi-o mics analysis and machine learning algorithms)
China-Japan Friendship Hospital Reports Findings in Endometrial Cancer (Metaboli sm pathway-based subtyping in endometrial cancer: An integrated study by multi-o mics analysis and machine learning algorithms)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Oncology - Endometrial Cancer is the subject of a report. According to news reporting from Beijing,People's Repu blic of China,by NewsRx journalists,research stated,"Endometrial cancer (EC),the second most common malignancy in the female reproductive system,has garner ed increasing attention for its genomic heterogeneity,but understanding of its metabolic characteristics is still poor. We explored metabolic dysfunctions in E C through a comprehensive multi-omics analysis (RNAseq datasets from The Cancer Genome Atlas [TCGA],Cancer Cell Line Enc yclopedia [CCLE],and GEO datasets; the Cl inical Proteomic Tumor Analysis Consortium [CPTAC] proteomics; CCLE metabolomics) to develop useful molecular targets for precision therapy." The news correspondents obtained a quote from the research from China-Japan Frie ndship Hospital,"Unsupervised consensus clustering was performed to categorize EC patients into three metabolismpathway- based subgroups (MPSs). These MPS subg roups had distinct clinical prognoses,transcriptomic and genomic alterations,i mmune microenvironment landscape,and unique patterns of chemotherapy sensitivit y. Moreover,the MPS2 subgroup had a better response to immunotherapy. Finally,three machine learning algorithms (LASSO,random forest,and stepwise multivaria te Cox regression) were used for developing a prognostic metagene signature base d on metabolic molecules. Thus,a 13-hub gene-based classifier was constructed t o predict patients' MPS subtypes,offering a more accessible and practical appro ach."
BeijingPeople's Republic of ChinaAsi aAlgorithmsCancerCyborgsDrugs and TherapiesEmerging TechnologiesEndo metrial CancerGynecologyHealth and MedicineImmunotherapyMachine LearningOncologyWomen's Health
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