Dissecting the treatment-naive ecosystem of human melanoma brain metastasis.

Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma; yet, our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBMs and 10 extracranial melanoma metastases (ECMs) and matched spatial single-cell transcriptomics and T cell receptor (TCR)-seq. Cancer cells from MBM were more chromosomally unstable, adopted a neuronal-like cell state, and enriched for spatially variably expressed metabolic pathways. Key observations were validated in independent patient cohorts, patient-derived MBM/ECM xenograft models, RNA/ATAC-seq, proteomics, and multiplexed imaging. Integrated spatial analyses revealed distinct geography of putative cancer immune evasion and evidence for more abundant intra-tumoral B to plasma cell differentiation in lymphoid aggregates in MBM. MBM harbored larger fractions of monocyte-derived macrophages and dysfunctional TOX+CD8+ T cells with distinct expression of immune checkpoints. This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

Combination immunotherapy including OncoVEXmGMCSF creates a favorable tumor immune micro-environment in transgenic BRAF murine melanoma.

Talimogene Laherparepvec (OncoVEXmGMCSF), an oncolytic virus, immune checkpoint inhibitor anti-programmed cell death protein 1 (anti-PD1), and BRAF inhibition (BRAFi), are all clinically approved for treatment of melanoma patients and are effective through diverse mechanisms of action. Individually, these therapies also have an effect on the tumor immune microenvironment (TIME). Evaluating the combination effect of these three therapies on the TIME can help determine when combination therapy is most appropriate for further study. In this study, we use a transgenic murine melanoma model (Tyr::CreER; BRAFCA/+; PTENflox/flox), to evaluate the TIME in response to combinations of BRAFi, anti-PD1, and OncoVEXmGMCSF. We find that mice treated with the triple combination BRAFi + anti-PD1 + OncoVEXmGMCSF have decreased tumor growth compared to BRAFi alone and prolonged survival compared to control. Flow cytometry shows an increase in percent CD8 + /CD3 + cytotoxic T Lymphocytes (CTLs) and a decrease in percent FOXP3 + /CD4 + T regulatory cells (Tregs) in tumors treated with OncoVEXmGMCSF compared to mice not treated with OncoVEXmGMCSF. Immunogenomic analysis at 30d post-treatment shows an increase in Th1 and interferon-related genes in mice receiving OncoVEXmGMCSF + BRAFi. In summary, treatment with combination BRAFi + anti-PD1 + OncoVEXmGMCSF is more effective than any single treatment in controlling tumor growth, and groups receiving OncoVEXmGMCSF had more tumoral infiltration of CTLs and less intratumoral Tregs in the TIME. This study provides rational basis to combine targeted agents, oncolytic viral therapy, and checkpoint inhibitors in the treatment of melanoma.

The CD58-CD2 axis is co-regulated with PD-L1 via CMTM6 and shapes anti-tumor immunity.

The cell-autonomous balance of immune-inhibitory and -stimulatory signals is a critical process in cancer immune evasion. Using patient-derived co-cultures, humanized mouse models, and single-cell RNA-sequencing of patient melanomas biopsied before and on immune checkpoint blockade, we find that intact cancer cell-intrinsic expression of CD58 and ligation to CD2 is required for anti-tumor immunity and is predictive of treatment response. Defects in this axis promote immune evasion through diminished T cell activation, impaired intratumoral T cell infiltration and proliferation, and concurrently increased PD-L1 protein stabilization. Through CRISPR-Cas9 and proteomics screens, we identify and validate CMTM6 as critical for CD58 stability and upregulation of PD-L1 upon CD58 loss. Competition between CD58 and PD-L1 for CMTM6 binding determines their rate of endosomal recycling over lysosomal degradation. Overall, we describe an underappreciated yet critical axis of cancer immunity and provide a molecular basis for how cancer cells balance immune inhibitory and stimulatory cues.

Neoadjuvant chemoradiation alters the immune microenvironment in pancreatic ductal adenocarcinoma.

Patients with pancreatic ductal adenocarcinoma (PDAC) have a grim prognosis despite complete surgical resection and intense systemic therapies. While immunotherapies have been beneficial with many different types of solid tumors, they have almost uniformly failed in the treatment of PDAC. Understanding how therapies affect the tumor immune microenvironment (TIME) can provide insights for the development of strategies to treat PDAC. We used quantitative multiplexed immunofluorescence (qmIF) quantitative spatial analysis (qSA), and immunogenomic (IG) analysis to analyze formalin-fixed paraffin embedded (FFPE) primary tumor specimens from 44 patients with PDAC including 18 treated with neoadjuvant chemoradiation (CRT) and 26 patients receiving no treatment (NT) and compared them with tissues from 40 treatment-naïve melanoma patients. We find that relative to NT tumors, CD3+ T cell infiltration was increased in CRT treated tumors (p = .0006), including increases in CD3+CD8+ cytotoxic T cells (CTLs, p = .0079), CD3+CD4+FOXP3- T helper cells (Th, p = .0010), and CD3+CD4+FOXP3+ regulatory T cells (Tregs, p = .0089) with no difference in CD68+ macrophages. IG analysis from micro-dissected tissues indicated overexpression of genes involved in antigen presentation, T cell activation, and inflammation in CRT treated tumors. Among treated patients, a higher ratio of Tregs to total T cells was associated with shorter survival time (p = .0121). Despite comparable levels of infiltrating T cells in CRT PDACs to melanoma, PDACs displayed distinct spatial profiles with less T cell clustering as defined by nearest neighbor analysis (p < .001). These findings demonstrate that, while CRT can achieve high T cell densities in PDAC compared to melanoma, phenotype and spatial organization of T cells may limit benefit of T cell infiltration in this immunotherapy-resistant tumor.

Etiologies of Melanoma Development and Prevention Measures: A Review of the Current Evidence.

(1) Melanoma is the most aggressive dermatologic malignancy, with an estimated 106,110 new cases to be diagnosed in 2021. The annual incidence rates continue to climb, which underscores the critical importance of improving the methods to prevent this disease. The interventions to assist with melanoma prevention vary and typically include measures such as UV avoidance and the use of protective clothing, sunscreen, and other chemopreventive agents. However, the evidence is mixed surrounding the use of these and other interventions. This review discusses the heritable etiologies underlying melanoma development before delving into the data surrounding the preventive methods highlighted above. (2) A comprehensive literature review was performed to identify the clinical trials, observational studies, and meta-analyses pertinent to melanoma prevention and incidence. Online resources were queried to identify epidemiologic and clinical trial information. (3) Evidence exists to support population-wide screening programs, the proper use of sunscreen, and community-targeted measures in the prevention of melanoma. Clinical evidence for the majority of the proposed preventive chemotherapeutics is presently minimal but continues to evolve. (4) Further study of these chemotherapeutics, as well as improvement of techniques in artificial intelligence and imaging techniques for melanoma screening, is warranted for continued improvement of melanoma prevention.

Transcriptomic analysis identifies differences in gene expression in actinic keratoses after treatment with imiquimod and between responders and non responders.

The presence of actinic keratoses (AKs) increases a patient's risk of developing squamous cell carcinoma by greater than six-fold. We evaluated the effect of topical treatment with imiquimod on the tumor microenvironment by measuring transcriptomic differences in AKs before and after treatment with imiquimod 3.75%. Biopsies were collected prospectively from 21 patients and examined histologically. RNA was extracted and transcriptomic analyses of 788 genes were performed using the nanoString assay. Imiquimod decreased number of AKs by study endpoint at week 14 (p < 0.0001). Post-imiquimod therapy, levels of CDK1, CXCL13, IL1B, GADPH, TTK, ILF3, EWSR1, BIRC5, PLAUR, ISG20, and C1QBP were significantly lower (adjusted p < 0.05). Complete responders (CR) exhibited a distinct pattern of inflammatory gene expression pre-treatment relative to incomplete responders (IR), with alterations in 15 inflammatory pathways (p < 0.05) reflecting differential expression of 103 genes (p < 0.05). Presence of adverse effects was associated with improved treatment response. Differences in gene expression were found between pre-treatment samples in CR versus IR, suggesting that higher levels of inflammation pre-treament may play a part in regression of AKs. Further characterization of the immune micro-environment in AKs may help develop biomarkers predictive of response to topical immune modulators and may guide therapy.

Automated digital TIL analysis (ADTA) adds prognostic value to standard assessment of depth and ulceration in primary melanoma.

Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied to a training cohort (n = 80) and a cutoff value was defined based on a Receiver Operating Curve. ADTA was then applied to a validation cohort (n = 145) and the previously determined cutoff value was used to stratify high and low risk patients, as demonstrated by Kaplan-Meier analysis (p ≤ 0.001). Multivariable Cox proportional hazards analysis was performed using ADTA, depth, and ulceration as co-variables and showed that ADTA contributed to DSS prediction (HR: 4.18, CI 1.51-11.58, p = 0.006). ADTA provides an effective and attainable assessment of TILs and should be further evaluated in larger studies for inclusion in staging algorithms.