bioRxivCancer BiologyPreprint
Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms
C. Gruen, H. H. Yang, A. Sassano, E. Wu, V. Gopalan, K. L. Marie, A. Castro, F. R. Mehrabadi, C. H. Wu, I. Church, G. A. Needle, C. Smith, S. Chin, J. Ebersole, C. Marcelus, A. Fon, H. Liu, S. Malikic, C. Sahinalp, H. Carter, S. Hannenhalli, C.-P. Day, M. P. Lee, G. Merlino, E. Perez-Guijarro
Abstract
Intratumoral heterogeneity (ITH) can promote cancer progression and treatment failure, but the complexity of the regulatory programs and contextual factors involved complicates its study. To understand the specific contribution of ITH to immune checkpoint blockade (ICB) response, we generated single cell-derived clonal sublines from an ICB-sensitive and genetically and phenotypically heterogeneous mouse melanoma model, M4. Genomic and single cell transcriptomic analyses uncovered the diversity of the sublines and evidenced their plasticity. Moreover, a wide range of tumor growth kinetics were observed in vivo, in part associated with mutational profiles and dependent on T cell-response. Further inquiry into melanoma differentiation states and tumor microenvironment (TME) subtypes of untreated tumors from the clonal sublines demonstrated correlations between highly inflamed and differentiated phenotypes with the response to anti-CTLA-4 treatment. Our results demonstrate that M4 sublines generate intratumoral heterogeneity at both levels of intrinsic differentiation status and extrinsic TME profiles, thereby impacting tumor evolution during therapeutic treatment. These clonal sublines proved to be a valuable resource to study the complex determinants of response to ICB, and specifically the role of melanoma plasticity in immune evasion mechanisms.
- organism: mouse
- assay: scRNA-seq
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: statistical model
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