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Clinical molecular subtyping reveals intrinsic mesenchymal reprogramming in gastric cancer cells. | LitMetric

AI Article Synopsis

  • The study identifies specific gene signature-based subtypes of gastric cancer (GC) that are linked to treatment resistance and poor outcomes, analyzing data from 547 cases.
  • Researchers explored the relationship between these cancer subtypes and the tumor microenvironment using advanced techniques, revealing that some GC cells are in a partial epithelial-mesenchymal transition state.
  • By targeting TGF-β signaling, which they found to drive mesenchymal traits in cancer cells, the study suggests new therapeutic strategies that could reduce resistance to treatment in gastric cancer.

Article Abstract

The mesenchymal cancer phenotype is known to be clinically related to treatment resistance and a poor prognosis. We identified gene signature-based molecular subtypes of gastric cancer (GC, n = 547) based on transcriptome data and validated their prognostic and predictive utility in multiple external cohorts. We subsequently examined their associations with tumor microenvironment (TME) features by employing cellular deconvolution methods and sequencing isolated GC populations. We further performed spatial transcriptomics analysis and immunohistochemistry, demonstrating the presence of GC cells in a partial epithelial-mesenchymal transition state. We performed network and pharmacogenomic database analyses to identify TGF-β signaling as a driver pathway and, thus, a therapeutic target. We further validated its expression in tumor cells in preclinical models and a single-cell dataset. Finally, we demonstrated that inhibition of TGF-β signaling negated mesenchymal/stem-like behavior and therapy resistance in GC cell lines and mouse xenograft models. In summary, we show that the mesenchymal GC phenotype could be driven by epithelial cancer cell-intrinsic TGF-β signaling and propose therapeutic strategies based on targeting the tumor-intrinsic mesenchymal reprogramming of medically intractable GC.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10238377PMC
http://dx.doi.org/10.1038/s12276-023-00989-zDOI Listing

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