Research Paper Volume 12, Issue 20 pp 20835—20861
SMARCD3 is a potential prognostic marker and therapeutic target in CAFs
- 1 Department of General Surgery, People’s Hospital of Quzhou, Quzhou, Zhejiang, China
- 2 Clinical Research Institute, Zhejiang Provincial People’s Hospital, Zhejiang, China. People’s Hospital of Hangzhou Medical College, Zhejiang, China. Key Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang Province, Zhejiang, China
- 3 Department of Stomatology, Zhejiang Provincial People's Hospital, Hangzhou, China
Received: May 13, 2020 Accepted: September 5, 2020 Published: October 28, 2020https://doi.org/10.18632/aging.104102
How to Cite
Copyright: © 2020 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Objective: Screening for novel prognostic biomarkers and potential therapeutic targets from colorectal cancer microenvironment.
Results: 372 genes were overexpressed in colorectal cancer microenvironment, five of which that had the most prognostic powers were enriched in Epithelial-Mesenchymal Transition and cell cycle pathways. For the first time, we showed that SMARCD3 was mainly expressed in CAFs and could be a novel prognostic marker and potential therapeutic target. Function analyses indicated that MSARCD3 might promote CAFs activation and colorectal cancer metastasis through SMARCD3-WNT5A/TGF-β-MAPK14-SMARCD3 positive feedback loop. Signaling map of SMARCD3 was constructed and several potential drugs that could regulate SMARCD3 were also presented.
Conclusions: SMARCD3 is a novel prognostic biomarker and potential therapeutic target of colorectal cancer, which may promote cancer metastasis through activation of CAFs.
Methods: Colorectal cancer microenvironment related genes were screened based on immune and stromal scores. Function enrichment analyses were performed to show the underlying mechanistic insights of these tumor microenvironment related genes. Kaplan-Meier survival analysis was used for evaluating the prognostic power. Gene-Pathway interaction network analysis and cellular heterogeneity analysis of tumor microenvironment were also performed. Gene set enrichment analysis was performed for signal gene pathway analysis. Protein data from The Cancer Genome Atlas were used for validation.