@article{bf4af1f22cb54b44917954ce922d6942,
title = "Index of cancer-associated fibroblasts is superior to the epithelial–mesenchymal transition score in prognosis prediction",
abstract = "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-β (Tgfβ) 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.",
keywords = "Cancer-associated fibroblasts, Epithelial–mesenchymal transition, Oral cancer, Prognosis prediction, Tumor stroma",
author = "Ko, {Ying Chieh} and Lai, {Ting Yu} and Hsu, {Shu Ching} and Wang, {Fu Hui} and Su, {Sheng Yao} and Chen, {Yu Lian} and Tsai, {Min Lung} and Wu, {Chung Chun} and Hsiao, {Jenn Ren} and Chang, {Jang Yang} and Wu, {Yi Mi} and Robinson, {Dan R.} and Lin, {Chung Yen} and Lin, {Su Fang}",
note = "Funding Information: This research was funded by the Ministry of Science and Technology, Taiwan (MOST 107-2314-B-400-029 and MOST 108-2320-B-400-019) and National Health Research Institutes, Taiwan (CA-109-PP-05). Acknowledgments: We are grateful to Mark Yen-Ping Kuo (National Taiwan University) and Shu-Chun Lin (National Yang-Ming University, Taiwan) for providing TW2.6 and OC3, respectively. The authors acknowledge Ming-Hwai Lin (Taipei Veterans General Hospital, Taiwan) and Jeffrey Shu-Ming Chang (National Health Research Institutes, Taiwan) for statistics analysis; the Clinical and Industrial Genomic Application Development Service Center of National Core Facility for Biopharmaceuticals, Taiwan (MOST 108-2319-B-010-001) and Genomics Core and Bioinformatics-Biology Service Core at the Institute of Molecular Biology of Academia Sinica for RNA-seq analyses. We are indebted to the Taiwan NHRI Microarray Core, Laboratory Animal Center and Pathology Core Laboratory for assistance with Partek Flow, animal studies, and the Masson{\textquoteright}s trichrome staining, respectively. Ting-Yu Lai carried out her thesis research under the auspices of the Graduate Program of Biotechnology in Medicine, National Tsing Hua University and National Health Research Institutes. Funding Information: Funding: This research was funded by the Ministry of Science and Technology, Taiwan (MOST 107-2314-B-400-029 and MOST 108-2320-B-400-019) and National Health Research Institutes, Taiwan (CA-109-PP-05). Publisher Copyright: {\textcopyright} 2020 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2020",
month = jul,
doi = "10.3390/cancers12071718",
language = "English",
volume = "12",
pages = "1--17",
journal = "Cancers",
issn = "2072-6694",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "7",
}
