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Multiomics-based molecular subtyping based on the commensal microbiome predicts molecular characteristics and the therapeutic response in breast cancer.
Qin, Wenxing; Li, Jia; Gao, Na; Kong, Xiuyan; Guo, Liting; Chen, Yang; Huang, Liang; Chen, Xiaobing; Qi, Feng.
Affiliation
  • Qin W; Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, PR China. qinwenxingqwx@163.com.
  • Li J; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, PR China. qinwenxingqwx@163.com.
  • Gao N; Department of Thoracic Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, PR China.
  • Kong X; Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, PR China.
  • Guo L; Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325035, PR China.
  • Chen Y; Department of Oncology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, PR China.
  • Huang L; Department of Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, PR China.
  • Chen X; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, PR China.
  • Qi F; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, PR China. fdhlyx@163.com.
Mol Cancer ; 23(1): 99, 2024 May 10.
Article in En | MEDLINE | ID: mdl-38730464
ABSTRACT
The gut microbiota has been demonstrated to be correlated with the clinical phenotypes of diseases, including cancers. However, there are few studies on clinical subtyping based on the gut microbiota, especially in breast cancer (BC) patients. Here, using machine learning methods, we analysed the gut microbiota of BC, colorectal cancer (CRC), and gastric cancer (GC) patients to identify their shared metabolic pathways and the importance of these pathways in cancer development. Based on the gut microbiota-related metabolic pathways, human gene expression profile and patient prognosis, we established a novel BC subtyping system and identified a subtype called "challenging BC". Tumours with this subtype have more genetic mutations and a more complex immune environment than those of other subtypes. A score index was proposed for in-depth analysis and showed a significant negative correlation with patient prognosis. Notably, activation of the TPK1-FOXP3-mediated Hedgehog signalling pathway and TPK1-ITGAE-mediated mTOR signalling pathway was linked to poor prognosis in "challenging BC" patients with high scores, as validated in a patient-derived xenograft (PDX) model. Furthermore, our subtyping system and score index are effective predictors of the response to current neoadjuvant therapy regimens, with the score index significantly negatively correlated with both treatment efficacy and the number of immune cells. Therefore, our findings provide valuable insights into predicting molecular characteristics and treatment responses in "challenging BC" patients.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Gastrointestinal Microbiome Limits: Animals / Female / Humans Language: En Journal: Mol Cancer Journal subject: NEOPLASIAS Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Gastrointestinal Microbiome Limits: Animals / Female / Humans Language: En Journal: Mol Cancer Journal subject: NEOPLASIAS Year: 2024 Document type: Article