Proceedings of the National Academy of SciencesPharmacology & ToxicologyPeer-reviewed journal article
Key Regulatory Elements of the TGFbeta-LRRC15 Axis Predict Disease Progression and Immunotherapy Resistance Across Cancer Types
Michael ChengiD, Claire M. StoreyiD, Mohamed AltaiiD, Julie E. ParkiD, Julie TraniD, Smiths S. Lueong, Daniel L.J. ThorekiD, Liqun MaoiD, Wahed ZedaniD, Constance YueniD, Alexander Ridley, Marija Trajkovic-Arsic, Ken HerrmanniD, Sumit Kumar SubudhiiD, Bilal Ahmed SiddiquiiD, Katharina Lückerath, Jens Thomas SivekeiD, Robert D. DamoiseauxiD, Xia YangiD, David UlmertiD
Abstract
Transforming growth factor-beta (TGF{beta}) has dual roles in cancer, initially suppressing tumors but later promoting metastasis and immune evasion. Efforts to inhibit TGF{beta} have been largely unsuccessful due to significant toxicity and indiscriminate immunosuppression. Leucine-rich repeat-containing protein 15 (LRRC15) is a TGF{beta}-regulated antigen expressed by mesenchymal-derived cancer cells and cancer-associated fibroblasts (CAFs). In preclinical studies, ablation of TGF{beta}-driven LRRC15+ CAFs increased tumor infiltration of CD8+ T cells. However, the underlying pathobiological mechanisms prompting TGF{beta}s upregulation of LRRC15 expression are unclear. Using an integrated approach combining functional compound screening with single-cell RNA sequencing, we reveal key genomic features regulating TGF{beta}s ability to increase LRRC15 expression on cancer cells. Construction of gene regulatory networks converged our analyses on four key genes--MMP2, SPARC, TGF{beta}R2, and WNT5B--central to TGF{beta}-induced LRRC15 pathobiology. Validation of these genes in cell models and their use in predicting immunotherapy responses highlight their potential in refining immunotherapy strategies and personalizing co-treatment options.
- organism: human
- assay: scRNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 5
- FWCI
- 0.00
- Field percentile
- top 40%
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