Your browser doesn't support javascript.
loading
Index of Cancer-Associated Fibroblasts Is Superior to the Epithelial-Mesenchymal Transition Score in Prognosis Prediction.
Ko, Ying-Chieh; Lai, Ting-Yu; Hsu, Shu-Ching; Wang, Fu-Hui; Su, Sheng-Yao; Chen, Yu-Lian; Tsai, Min-Lung; Wu, Chung-Chun; Hsiao, Jenn-Ren; Chang, Jang-Yang; Wu, Yi-Mi; Robinson, Dan R; Lin, Chung-Yen; Lin, Su-Fang.
Afiliação
  • Ko YC; National Institute of Cancer Research, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Lai TY; Institute of Bioinformatics and Structural Biology, National Tsing-Hua University, Hsinchu 30013, Taiwan.
  • Hsu SC; National Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Wang FH; Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City 80708, Taiwan.
  • Su SY; PhD Program in Tissue Engineering and Regenerative Medicine, National Chung Hsing University, Taichung City 40227, Taiwan.
  • Chen YL; National Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Tsai ML; Institute of Information Science, Academia Sinica, Taipei 11529, Taiwan.
  • Wu CC; National Institute of Cancer Research, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Hsiao JR; National Institute of Cancer Research, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Chang JY; National Institute of Cancer Research, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Wu YM; Translational Cell Therapy Center, Department of Medical Research, China Medical University Hospital, Taichung City 40447, Taiwan.
  • Robinson DR; Department of Otolaryngology, Head and Neck Collaborative Oncology Group, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan.
  • Lin CY; National Institute of Cancer Research, National Health Research Institutes, Miaoli County 35053, Taiwan.
  • Lin SF; Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan.
Cancers (Basel) ; 12(7)2020 Jun 28.
Article em En | MEDLINE | ID: mdl-32605311
In many solid tumors, tissue of the mesenchymal subtype is frequently associated with epithelial-mesenchymal transition (EMT), strong stromal infiltration, and poor prognosis. Emerging evidence from tumor ecosystem studies has revealed that the two main components of tumor stroma, namely, infiltrated immune cells and cancer-associated fibroblasts (CAFs), also express certain typical EMT genes and are not distinguishable from intrinsic tumor EMT, where bulk tissue is concerned. Transcriptomic analysis of xenograft tissues provides a unique advantage in dissecting genes of tumor (human) or stroma (murine) origins. By transcriptomic analysis of xenograft tissues, we found that oral squamous cell carcinoma (OSCC) tumor cells with a high EMT score, the computed mesenchymal likelihood based on the expression signature of canonical EMT markers, are associated with elevated stromal contents featured with fibronectin 1 (Fn1) and transforming growth factor-ß (Tgfß) axis gene expression. In conjugation with meta-analysis of these genes in clinical OSCC datasets, we further extracted a four-gene index, comprising FN1, TGFB2, TGFBR2, and TGFBI, as an indicator of CAF abundance. The CAF index is more powerful than the EMT score in predicting survival outcomes, not only for oral cancer but also for the cancer genome atlas (TCGA) pan-cancer cohort comprising 9356 patients from 32 cancer subtypes. Collectively, our results suggest that a further distinction and integration of the EMT score with the CAF index will enhance prognosis prediction, thus paving the way for curative medicine in clinical oncology.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Ano de publicação: 2020 Tipo de documento: Article