Biological subgroups in melanoma: A correlation of tumor genomic and transcriptomic analysis with spatial immunophenotyping.
Authors: Miles Piper, Griffin Caryotakis, Yoko DeRose, Qin Zhou, Magdalena Kovacsovics, Berit Gibson, Doug Grossman, David Nix, Aik-choon Tan, Siwen Hu-Lieskovan
Journal: Journal of Clinical Oncology (2024)

e14667 Background: A prominent challenge advancing immunotherapy is the heterogeneity of resistance mechanisms leading to drug development failure despite efficacy in subgroup of patients. To address these shortcomings, precision medicine platforms aimed at prospectively stratifying patients into treatment groups based on tumor mutational burden (TMB) and tumor inflammation scores by gene expression profiling (GEP) are now being explored. Whether these gene-based variables reflect the true immunologic state of the tumor remains an open question. Here, we sought to evaluate TMB and GEP as markers of intratumoral inflammatory state by single-cell spatial analysis. Methods: Under an IRB approved protocol through the Huntsman Cancer Institute, 25 melanoma tumors with available clinical, WES, and RNAseq data were stained with a multiplex immunofluorescence-based protocol using Opal dye and Leica Bond Rx (CD8, CD68, PD1, PD-L1, Ki67, SOX10, DAPI) and scanned with Akoya Polaris whole slide scanner. Images were analyzed using HALO. Results: Melanoma tumors were stratified into 4 subgroups based on TMB (&lt;10 vs ≥10 m/Mb) by WES, and inflammatory (Inflm) gene signature expression (GSEA &gt;0 vs ≤0) by RNAseq, denoted as S1 (TMB hi /Inflm hi ; n=4), S2 (TMB hi /Inflm lo ; n=4), S3 (TMB lo /Inflm hi ; n=8), and S4 (TMB lo /Inflm lo ; n=9). The rate of disease progression was 0% (S1), 25% (S2), 25% (S3), and 56% (S4). Infiltration analysis of CD8 T cells showed elevated intratumoral CD8 density in S1 (249/mm 2 ) and S3 (157/mm 2 ) vs S2 (65/mm 2 ) and S4 (65/mm 2 ; p=0.0002), consistent with GEP findings. Spatial analysis showed a similar pattern of CD8 distribution across subgroups with peak CD8 density in the tumor periphery. Proximity analyses showed average distance of CD8 T cell to the nearest tumor cell was not different across subgroups. Furthermore, we found Inflm hi tumors had a higher frequency of PD1+ CD8 T cells relative to Inflm lo tumors (12.9 vs 2.8 cells/HPF; p=0.0002), suggesting GEP also reflects CD8 activation and functional status. Increased frequency of PD1+ CD8 T cells was correlated with a much improved overall survival (HR=3.3; p=0.017). A similar analysis performed on CD68+ macrophages showed significantly increased peri-tumoral macrophage recruitment in S4 (445/mm 2 ) vs S1 (209/mm 2 ; p&lt;0.0001), S2 (91/mm 2 ; p&lt;0.0001), and S3 (267/mm 2 ; p=0.0003) subgroups. Interestingly, Inflm hi tumors were associated with an increased proportion of PDL1+ macrophages regardless of TMB status (43% vs 3%; p&lt;0.0001), suggestive of an upregulated adaptive immune response in tumors with active inflammation. Conclusions: Our findings illustrate that biological groupings based on TMB and GEP biomarkers correlate with CD8 spatial location and activation state. Each subgroup has unique tumor immune features that can be related to immune resistance and warrant further investigation.