Abstract 3535: Multi-omics analysis of longitudinal melanoma samples reveals evolutionary transitions and therapy-associated cell-state switching

Abstract Background: In-transit metastasis (ITM) in melanoma is associated with poor prognosis, yet patients show widely variable clinical outcomes from rapid progression to durable responses. To investigate the mechanisms underlying these variations, we performed multi-omics profiling of sequential tumor biopsies from an ITM melanoma patient who progressed to stage IV over 4 years. Methods: Whole-exome sequencing (WES) from 14 tumors was analyzed using ABSOLUTE for purity-adjusted variant and CNA calling. Pyclone and PhylogicNDT defined mutational clusters based on cancer cell fraction (CCF) and inferred tumor lineages. The phylogenetic map was then integrated with clinical metadata. Gene set enrichment analysis (GSEA) on bulk RNA-seq assessed lineage- and time-associated melanoma signatures and transcriptional programs. Results: Phylogenetic reconstruction captured 3 major lineages (L1: ITM; L2: ITM + distant subcutaneous metastases; L3: distant skin metastases) from a common ancestral clone. Combination of anti-PD1 and intralesional T-VEC therapy reshaped the genomic landscape of tumor clones, selectively favoring L3, which expanded into clonality while L1 became undetectable, consistent with therapy-associated selection. L2, branched off L1, also exhibited persistent survival and immune resistance. RNA-seq showed evidence for a coordinated shift from a highly differentiated state towards an AXL-high state following clinical immune intervention. Transcriptional tumor state heterogeneity increased over time, independent of lineages. Both ITM (L2) and distant (L3) lineages initially displayed more invasive, mesenchymal-like cell state profiles immediately following the clone formation, but transitioned towards more differentiated tumor states, benefiting cell proliferation and clonal expansion. By the end of the clinical course, all distant lesions across anatomical sites converged on an MITF-driven, melanocytic-like proliferative state. Conclusion: This study reconstructed a phylogenetic map for tumor evolution through multi-omics, longitudinal data from an ITM patient to reveal key pathways and tumor state changes associated with metastatic events and heterogeneity in clinical responses. In the next step, the individual phylogenetic trees will be compared with other patients in the cohort to explore intra-tumoral, inter-tumoral, and inter-patient heterogeneity in tumor progression, metastasis sites, and resistance to therapy. Citation Format: Yourong Bao, Anne Zaremba, Giuseppe Tarantino, Tuulia Vallius, Mark Woodnorth, Mariana Lopez Leon, Yingxiao Shi, Zoltan Maliga, Samira Makhzami, Tyler Aprati, Bojan Karlas, Valerie Glutsch, Bastian Schilling, Jessica Cecile Hassel, Carola Berking, Jochen Utikal, Friedegund Meier, Frank Meiss, Lucie Heinzerling, Katharina Kähler, Jiajia Chen, Lisa Zimmer, Antje Sucker, Elisabeth Livingstone, Eva Hadaschik, Christine G. Lian, George F. Murphy, Yevgeniy R. Semenov, Genevieve Boland, Peter Karl Sorger, Florian Rambow, David Liu, Dirk Schadendorf. Multi-omics analysis of longitudinal melanoma samples reveals evolutionary transitions and therapy-associated cell-state switching abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3535.