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Divergent Resistance Mechanisms to Immunotherapy Explain Responses in Different Skin Cancers.
Dollinger, Emmanuel; Bergman, Daniel; Zhou, Peijie; Atwood, Scott X; Nie, Qing.
Affiliation
  • Dollinger E; Department of Mathematics, University of California, Irvine, CA 92697, USA.
  • Bergman D; Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA.
  • Zhou P; NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA.
  • Atwood SX; Center for Complex Biological Systems, University of California, Irvine, CA 92697, USA.
  • Nie Q; Department of Mathematics, University of California, Irvine, CA 92697, USA.
Cancers (Basel) ; 12(10)2020 Oct 13.
Article in En | MEDLINE | ID: mdl-33065980
The advent of immune checkpoint therapy for metastatic skin cancer has greatly improved patient survival. However, most skin cancer patients are refractory to checkpoint therapy, and furthermore, the intra-immune cell signaling driving response to checkpoint therapy remains uncharacterized. When comparing the immune transcriptome in the tumor microenvironment of melanoma and basal cell carcinoma (BCC), we found that the presence of memory B cells and macrophages negatively correlate in both cancers when stratifying patients by their response, with memory B cells more present in responders. Moreover, inhibitory immune signaling mostly decreases in melanoma responders and increases in BCC responders. We further explored the relationships between macrophages, B cells and response to checkpoint therapy by developing a stochastic differential equation model which qualitatively agrees with the data analysis. Our model predicts BCC to be more refractory to checkpoint therapy than melanoma and predicts the best qualitative ratio of memory B cells and macrophages for successful treatment.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Cancers (Basel) Year: 2020 Document type: Article Affiliation country: United States Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Cancers (Basel) Year: 2020 Document type: Article Affiliation country: United States Country of publication: Switzerland