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Wenbin Guan

Researcher at Shanghai Jiao Tong University

Publications -  12
Citations -  200

Wenbin Guan is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Medicine & Cancer. The author has an hindex of 6, co-authored 9 publications receiving 127 citations.

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Journal ArticleDOI

Downregulation of miRNA-214 in cancer-associated fibroblasts contributes to migration and invasion of gastric cancer cells through targeting FGF9 and inducing EMT

TL;DR: This study showed that miR-214 inhibited the tumor-promoting effect of CAFs on GC through targeting FGF9 in CAFs and regulating the EMT process in GC cells, suggesting miRNA-214/FGF9In CAFs as a potential target for therapeutic approaches in GC.
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Cancer associated fibroblasts tailored tumor microenvironment of therapy resistance in gastrointestinal cancers.

TL;DR: Predictably, targeting therapy‐resistant CAFs is a promising adjunctive treatment to benefit GI patients and some key problems about distinguishing CAFs subpopulations and controversial issues on pleiotropic CAFs in medication need to be solved for subsequent clinical application.
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The Better Survival of MSI Subtype Is Associated With the Oxidative Stress Related Pathways in Gastric Cancer.

TL;DR: More opportunities to induce apoptosis of cancer cells, led by the unbalance between antioxidant system and ROS accumulation, lay foundations for unveiling the better prognosis in MSI phenotype through the bioinformatics analysis.
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Roles of microRNAs in cancer associated fibroblasts of gastric cancer.

TL;DR: The miRNAs biogenesis is introduced and an overview of the mechanisms and emerging roles of CAFs-related miRNas are provided to bring better treatment effect on GC and other diseases.
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Integrated assessment of PD-L1 expression and molecular classification facilitates therapy selection and prognosis prediction in gastric cancer

TL;DR: Different molecular subtypes in GC may have a tendency to react differently to anti-PD-L1/PD-1 immunotherapy or anti-Her2 therapy, and this cost-effective classification strategy would be helpful for predicting prognosis and promoting personalized therapy in clinical practice.