Faculty Bibliography

BACKGROUND:Genetic and transcriptional alterations in cancer cells shape their interactions with immune and stromal compartments, thereby influencing tumor progression, immune evasion, and response to immune checkpoint inhibitors (ICIs). Yet, how these interactions are spatially organized within melanoma and how they relate to clinical outcome remains incompletely understood. METHODS:We used spatial multi-omic profiling on melanoma tissues from patients, compared those with loss-of-function mutations in the Neurofibromin 1 (NF1) tumor suppressor gene to those with intact NF1, and integrated these results with functional studies and subsequent gene expression changes observed in patient-derived melanoma models and an immunotherapy-resistant syngeneic mouse model. RESULTS:T cell infiltration. Mechanistically, EGFR signaling emerged as a prominent feature of NF1-deficient melanoma ecosystems and correlated with reduced expression of antigen-presentation genes and T cell exclusion. EGFR inhibition restored the expression of antigen-presentation programs and enhanced antitumor immune responses in a syngeneic Nf1 knockdown model resistant to ICIs. CONCLUSIONS:These findings define spatially organized, functionally distinct meta-niches enriched in NF1-mutant melanoma that may contribute to their aggressive disease features and poor ICI response. Our study links an understudied melanoma driver to specific immune-evasion mechanisms and identifies EGFR inhibition as a candidate strategy to improve outcomes in patients with NF1-mutant melanoma resistant to immunotherapy.

We present MelOD (Melanoma Omics Dashboard), a free, web-based interactive platform integrating preprocessed data from 16 melanoma studies, including eight bulk transcriptomics, six single-cell RNA-seq, and two proteomics datasets. MelOD provides user-friendly visualization and analysis tools, differential expression, dimensionality reduction, clustering, correlation, and survival analysis without requiring local computational resources. Several datasets include annotations for immunotherapy response, facilitating exploration of resistance and response signatures. Built on RShiny with optimized handling of large datasets, MelOD supports real-time hypothesis generation, cross-study validation, and community dataset contributions. Freely accessible online, MelOD lowers barriers to multi-omics research in melanoma and related fields.

The protein activating molecule in Beclin1-regulated autophagy1 (AMBRA1), discovered in 2007, is crucial for autophagy and plays roles in nervous system development, cell survival, and proliferation. Here, we investigated AMBRA1's involvement in various cellular processes using a systems-based "omics" approach, focusing on melanoma. Transcriptomic analysis of AMBRA1 overexpression or knock-down was shown to result in significant dysregulation of several transcripts. We identified several novel roles for AMBRA1 in a range of cellular pathways including cancer signaling pathways such as MAPK, angiogenesis, tissue growth factor signaling, axon guidance, and Wnt signaling. Furthermore, using yeast two-hybrid assays, we identified novel binding partners which provide evidence of new roles for AMBRA1 in different cellular processes. Ultimately, we conclude that AMBRA1 loss upregulates metastatic genes/proteins highlighting AMBRA1 as a tumor suppressor gene in melanoma.

Patients with resected, high-risk melanoma receive adjuvant immune checkpoint blockade (ICB), yet clinical benefit remains unpredictable, with 25%-40% of patients experiencing recurrence. To evaluate whether pre-treatment gut microbiome (GMB) features predict recurrence, we analyzed stool samples from 674 patients enrolled in a phase 3 clinical trial, CheckMate 915, which investigated the combination of nivolumab plus ipilimumab versus nivolumab as a single agent across five geographic regions. Region-specific and cross-region meta-analyses identified pre-treatment taxa associated with recurrence, including Eubacterium, Ruminococcus, Firmicutes, and Clostridium. Recurrence prediction was strongest when the validation cohort exhibited GMB profiles similar to those in the discovery cohort. Among closely matched individuals (Jensen-Shannon divergence [JSD] ≤ 0.11), the area under the curve (AUC) for recurrence prediction ranged from 0.78 to 0.94 across regions. GMB composition remained largely stable following treatment. These findings suggest that gut bacterial markers can predict recurrence after adjuvant ICB treatment in melanoma, supporting their potential as clinically actionable biomarkers to guide personalized therapy.

Ultraviolet (UV)-induced DNA mutations generate genetic drivers of cutaneous melanoma and numerous neoantigens that can trigger anti-tumor immunity. Melanoma cells must therefore rapidly evade immune detection by modulating cell-autonomous epigenetic mechanisms and tumor-microenvironment interactions. Although angiogenesis typically facilitates immune infiltration, solid tumors increase vascularization while limiting immune cell entry. By comparing transcription factor (TF) expression across early-stage melanoma, naevi, and other cancers, we found that the homeodomain TF HOXD13 drives a melanoblast-like program upregulated in melanoma and strongly correlated with angiogenesis and immune cell exclusion. Using transcriptomics, 3D chromatin profiling, and in vivo models, we show that HOXD13 promotes tumor growth by enhancing angiogenesis and suppressing T-cell infiltration. HOXD13 orchestrates 3D enhancer-promoter contacts activating VEGFA, SEMA3A, and CD73, which remodel vasculature and elevate immunosuppressive adenosine. Consistently, HOXD13-induced tumor growth is reversed by combined VEGFR and adenosine receptor (AdR) inhibition, revealing a dual pro-angiogenic and immunosuppressive HOXD13 axis with therapeutic relevance.

Lymphatic vessels activate anti-tumor immune surveillance and support metastasis. Whether there are distinct lymphatic phenotypes that govern immunity and metastasis remains unclear. Here we reveal that cytotoxic immunity normalizes lymphatic function and uncouples immune and metastatic potential. We demonstrate that intratumoral lymphatic vessel density negatively correlates with cytotoxic immunity and that IFNγ reprograms the intratumoral lymphatic state. Lymphatic deletion of Ifngr1 expanded the intratumoral lymphatic network and drove the emergence of a tip-like state that promotes lymph node metastasis but not dendritic cell migration or response to immune checkpoint blockade (ICB). Mechanistically, IFNγ restrains proliferation and cell state programs through inhibition of mitochondrial respiration. Lymphatic-specific inhibition of mitochondrial complex III restrained the intratumoral tip-like state, blocked metastasis, and enhanced the response to ICB. Our data reveal that IFNγ induces a metabolic and phenotypic switch in tumor-associated lymphatic vessels that blocks regional metastasis and reinforces immune surveillance.

PURPOSE/OBJECTIVE:Patients with stage II and resected stage III melanomas have variable clinical outcomes, evidence of underlying biological differences in tumors and/or the patients themselves, beyond stage. The approval of adjuvant immunotherapy for stage IIB/C and resected stage III/IV disease (and adjuvant targeted therapy for resected stage III disease), has created a pressing need to develop biomarkers to accurately distinguish patients at low- versus high-risk for recurrence and death from melanoma. MicroRNAs (miRNAs) are promising biomarkers because of their stability in tissues/fluids and their demonstrated functional and prognostic roles in melanoma. We hypothesized that miRNA expression could be integrated into prognostic models that would more accurately classify 5-year survival outcomes than clinical factors alone. PATIENTS AND METHODS/METHODS:Using a Nanostring miRNA Expression Assay, we analyzed 715 primary melanomas from patients with stage II or stage III disease within the InterMEL consortium, and examined associations between miRNA expression and melanoma-specific death. RESULTS:When integrated into clinical prognostic models for 5-year melanoma-specific survival, miRNA signatures improved the area under the receiver operating characteristic curve (AUC) for stage II patients from 0.71 for a 'clinical factors-only' model to 0.81 for a 'clinical plus miRNA' model in an independent test set, an improvement of 0.10 with 95% CI (0.03, 0.19). The improvement was more modest for stage III patients that were included in the analysis. CONCLUSIONS:Incorporating miRNA expression in primary melanomas may enhance the accuracy of clinical prognostic models, and potentially aid the selection of melanoma patients for adjuvant treatment and clinical trials.

PURPOSE/UNASSIGNED:Cancer treatment has been revolutionized by immune checkpoint inhibitors (ICI). However, a subset of patients do not respond and/or they experience significant adverse events. Attempts to integrate reliable biomarkers of ICI response as part of standard care have been hampered by limited generalizability. We previously reported our supervised machine learning (ML) model in a retrospective cohort of metastatic melanoma. EXPERIMENTAL DESIGN/UNASSIGNED:In this study, we expanded our testing to include larger cohorts of patients with melanoma accrued at several sites, including patients enrolled in clinical trials in both adjuvant and metastatic settings. We examined pretreatment hematoxylin and eosin slides from 639 patients with stage III/IV melanoma treated with ICIs [anti-cytotoxic T-lymphocyte-associated protein 4 (n = 212), anti-programmed death 1 (n = 271), or the combination (n = 156)]. We tested the generalizability of our supervised ML algorithm to predict response to ICIs in the metastatic melanoma cohort and then developed a self-supervised ML model to identify the histologic morphologies associated with patients' survival following ICI use in adjuvant and metastatic melanoma cohorts. RESULTS/UNASSIGNED:We predicted the response to ICI treatment with an AUC of 0.72. The deep convolutional neural network classified patients into high and low risk based on their likelihood of progression-free survival (P < 0.0001). We uncovered a novel association of specific histomorphologic tumor features-epithelioid histology and a low tumor-stroma ratio-with survival following ICI treatment. CONCLUSIONS/UNASSIGNED:Our data support the generalizability of our developed ML algorithm in predicting response to ICI treatment in patients with metastatic unresectable melanoma. We also showed, for the first time, tumor features associated with patients' overall survival.

UNLABELLED:Melanoma being one of the most common and deadliest skin cancers has been increasing since the past decade. Patients at advanced stages of the disease have very poor prognoses, as opposed to at the earlier stages. Nowadays, the standard of care of advanced melanoma is resection, followed by immune checkpoint inhibition-based immunotherapy. However, a substantial proportion of patients either do not respond or develop resistance. This underscores a need for novel approaches and therapeutic targets as well as a better understanding of the mechanisms of melanoma pathogenesis. Long noncoding RNAs (lncRNA) comprise a poorly characterized class of functional players and promising targets in promoting malignancy. Certain lncRNAs have been identified to play integral roles in melanoma progression and drug resistance; however, systematic screens to uncover novel functional lncRNAs are scarce. In this study, we profile differentially expressed lncRNAs in patient-derived short-term metastatic cultures and BRAF-MEK inhibition-resistant cells. We conduct a focused growth-related CRISPR inhibition screen of overexpressed lncRNAs, validate, and functionally characterize lncRNA hits with respect to cellular growth, invasive capacities, and apoptosis in vitro as well as the transcriptomic impact of our lead candidate the novel lncRNA XLOC_030781. In sum, we extend the current knowledge of ncRNAs and their potential relevance in melanoma. SIGNIFICANCE/UNASSIGNED:LncRNAs have emerged as novel players in regulating many cellular aspects also in melanoma. The number of functional significances of most lncRNAs remains elusive. We provide a comprehensive strategy to identify functionally relevant lncRNAs in melanoma by combining expression profiling with CRISPR inhibition growths screens. Our results broaden the characterized lncRNAs as potential targets for future therapeutic applications.