UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

PhISCS-BnB: a fast branch and bound algorithm for the perfect tumor phylogeny reconstruction problem.

MOTIVATION: Recent advances in single-cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program, or a constraint satisfaction program, which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology. RESULTS: We introduce PhISCS-BnB (phylogeny inference using SCS via branch and bound), a branch and bound algorithm to compute the most likely perfect phylogeny on an input genotype matrix extracted from an SCS dataset. PhISCS-BnB not only offers an optimality guarantee, but is also 10-100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a recently published large melanoma dataset derived from the sublineages of a cell line involving 20 clones with 2367 mutations, which returned the optimal tumor phylogeny in <4 h. The resulting phylogeny agrees with and extends the published results by providing a more detailed picture on the clonal evolution of the tumor. AVAILABILITY AND IMPLEMENTATION: https://github.com/algo-cancer/PhISCS-BnB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetically engineered mouse models of melanoma.

Melanoma is a complex disease that exhibits highly heterogeneous etiological, histopathological, and genetic features, as well as therapeutic responses. Genetically engineered mouse (GEM) models provide powerful tools to unravel the molecular mechanisms critical for melanoma development and drug resistance. Here, we expound briefly the basis of the mouse modeling design, the available technology for genetic engineering, and the aspects influencing the use of GEMs to model melanoma. Furthermore, we describe in detail the currently available GEM models of melanoma. Cancer 2017;123:2089-103. © 2017 American Cancer Society.

A role for insulator elements in the regulation of gene expression response to hypoxia.

Hypoxia inducible factor (HIF) up-regulates the transcription of a few hundred genes required for the adaptation to hypoxia. This restricted set of targets is in sharp contrast with the widespread distribution of the HIF binding motif throughout the genome. Here, we investigated the transcriptional response of GYS1 and RUVBL2 genes to hypoxia to understand the mechanisms that restrict HIF activity toward specific genes. GYS1 and RUVBL2 genes are encoded by opposite DNA strands and separated by a short intergenic region (~1 kb) that contains a functional hypoxia response element equidistant to both genes. However, hypoxia induced the expression of GYS1 gene only. Analysis of the transcriptional response of chimeric constructs derived from the intergenic region revealed an inhibitory sequence whose deletion allowed RUVBL2 induction by HIF. Enhancer blocking assays, performed in cell culture and transgenic zebrafish, confirmed the existence of an insulator element within this inhibitory region that could explain the differential regulation of GYS1 and RUVBL2 by hypoxia. Hence, in this model, the selective response to HIF is achieved with the aid of insulator elements. This is the first report suggesting a role for insulators in the regulation of differential gene expression in response to environmental signals.

Stochastic modelling of single-cell gene expression adaptation reveals non-genomic contribution to evolution of tumor subclones.

Cancer progression is an evolutionary process driven by the selection of cells adapted to gain growth advantage. We present the first formal study on the adaptation of gene expression in subclonal evolution. We model evolutionary changes in gene expression as stochastic Ornstein-Uhlenbeck processes, jointly leveraging the evolutionary history of subclones and single-cell expression data. Applying our model to sublines derived from single cells of a mouse melanoma revealed that sublines with distinct phenotypes are underlined by different patterns of gene expression adaptation, indicating non-genetic mechanisms of cancer evolution. Interestingly, sublines previously observed to be resistant to anti-CTLA-4 treatment showed adaptive expression of genes related to invasion and non-canonical Wnt signaling, whereas sublines that responded to treatment showed adaptive expression of genes related to proliferation and canonical Wnt signaling. Our results suggest that clonal phenotypes emerge as the result of specific adaptivity patterns of gene expression.

Melanoma clonal subline analysis uncovers heterogeneity-driven immunotherapy resistance mechanisms.

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.

Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response.

With the continued promise of immunotherapy for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer screening and treatment strategies. Here, we study 1084 eQTLs affecting the TIME found through analysis of The Cancer Genome Atlas and literature curation. These TIME eQTLs are enriched in areas of active transcription, and associate with gene expression in specific immune cell subsets, such as macrophages and dendritic cells. Polygenic score models built with TIME eQTLs reproducibly stratify cancer risk, survival and immune checkpoint blockade (ICB) response across independent cohorts. To assess whether an eQTL-informed approach could reveal potential cancer immunotherapy targets, we inhibit CTSS, a gene implicated by cancer risk and ICB response-associated polygenic models; CTSS inhibition results in slowed tumor growth and extended survival in vivo. These results validate the potential of integrating germline variation and TIME characteristics for uncovering potential targets for immunotherapy.

Fast intratumor heterogeneity inference from single-cell sequencing data.

We introduce HUNTRESS, a computational method for mutational intratumor heterogeneity inference from noisy genotype matrices derived from single-cell sequencing data, the running time of which is linear with the number of cells and quadratic with the number of mutations. We prove that, under reasonable conditions, HUNTRESS computes the true progression history of a tumor with high probability. On simulated and real tumor sequencing data, HUNTRESS is demonstrated to be faster than available alternatives with comparable or better accuracy. Additionally, the progression histories of tumors inferred by HUNTRESS on real single-cell sequencing datasets agree with the best known evolution scenarios for the associated tumors.

Melanoma central nervous system metastases: An update to approaches, challenges, and opportunities.

Brain metastases are the most common brain malignancy. This review discusses the studies presented at the third annual meeting of the Melanoma Research Foundation in the context of other recent reports on the biology and treatment of melanoma brain metastases (MBM). Although symptomatic MBM patients were historically excluded from immunotherapy trials, efforts from clinicians and patient advocates have resulted in more inclusive and even dedicated clinical trials for MBM patients. The results of checkpoint inhibitor trials were discussed in conversation with current standards of care for MBM patients, including steroids, radiotherapy, and targeted therapy. Advances in the basic scientific understanding of MBM, including the role of astrocytes and metabolic adaptations to the brain microenvironment, are exposing new vulnerabilities which could be exploited for therapeutic purposes. Technical advances including single-cell omics and multiplex imaging are expanding our understanding of the MBM ecosystem and its response to therapy. This unprecedented level of spatial and temporal resolution is expected to dramatically advance the field in the coming years and render novel treatment approaches that might improve MBM patient outcomes.

Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response.

Gut bacteria modulate the response to immune checkpoint blockade (ICB) treatment in cancer, but the effect of diet and supplements on this interaction is not well studied. We assessed fecal microbiota profiles, dietary habits, and commercially available probiotic supplement use in melanoma patients and performed parallel preclinical studies. Higher dietary fiber was associated with significantly improved progression-free survival in 128 patients on ICB, with the most pronounced benefit observed in patients with sufficient dietary fiber intake and no probiotic use. Findings were recapitulated in preclinical models, which demonstrated impaired treatment response to anti­programmed cell death 1 (anti­PD-1)­based therapy in mice receiving a low-fiber diet or probiotics, with a lower frequency of interferon-γ­positive cytotoxic T cells in the tumor microenvironment. Together, these data have clinical implications for patients receiving ICB for cancer.

Melanoblast transcriptome analysis reveals pathways promoting melanoma metastasis.

Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posit that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover metastatic melanoma biology. Using a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, we identify melanoblast-specific genes whose expression contribute to metastatic competence and derive a 43-gene signature that predicts patient survival. We identify a melanoblast gene, KDELR3, whose loss impairs experimental metastasis. In contrast, KDELR1 deficiency enhances metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover targetable pathways for melanoma therapy.

Multimodel preclinical platform predicts clinical response of melanoma to immunotherapy.

Although immunotherapy has revolutionized cancer treatment, only a subset of patients demonstrate durable clinical benefit. Definitive predictive biomarkers and targets to overcome resistance remain unidentified, underscoring the urgency to develop reliable immunocompetent models for mechanistic assessment. Here we characterize a panel of syngeneic mouse models, representing a variety of molecular and phenotypic subtypes of human melanomas and exhibiting their diverse range of responses to immune checkpoint blockade (ICB). Comparative analysis of genomic, transcriptomic and tumor-infiltrating immune cell profiles demonstrated alignment with clinical observations and validated the correlation of T cell dysfunction and exclusion programs with resistance. Notably, genome-wide expression analysis uncovered a melanocytic plasticity signature predictive of patient outcome in response to ICB, suggesting that the multipotency and differentiation status of melanoma can determine ICB benefit. Our comparative preclinical platform recapitulates melanoma clinical behavior and can be employed to identify mechanisms and treatment strategies to improve patient care.

p62/SQSTM1 Fuels Melanoma Progression by Opposing mRNA Decay of a Selective Set of Pro-metastatic Factors.

Modulators of mRNA stability are not well understood in melanoma, an aggressive tumor with complex changes in the transcriptome. Here we report the ability of p62/SQSTM1 to extend mRNA half-life of a spectrum of pro-metastatic factors. These include FERMT2 and other transcripts with no previous links to melanoma. Transcriptomic, proteomic, and interactomic analyses, combined with validation in clinical biopsies and mouse models, identified a selected set of RNA-binding proteins (RBPs) recruited by p62, with IGF2BP1 as a key partner. This p62-RBP interaction distinguishes melanoma from other tumors where p62 controls autophagy or oxidative stress. The relevance of these data is emphasized by follow-up analyses of patient prognosis revealing p62 and FERMT2 as adverse determinants of disease-free survival.

Lineage-specific roles of the cytoplasmic polyadenylation factor CPEB4 in the regulation of melanoma drivers.

Nuclear 3'-end-polyadenylation is essential for the transport, stability and translation of virtually all eukaryotic mRNAs. Poly(A) tail extension can also occur in the cytoplasm, but the transcripts involved are incompletely understood, particularly in cancer. Here we identify a lineage-specific requirement of the cytoplasmic polyadenylation binding protein 4 (CPEB4) in malignant melanoma. CPEB4 is upregulated early in melanoma progression, as defined by computational and histological analyses. Melanoma cells are distinct from other tumour cell types in their dependency on CPEB4, not only to prevent mitotic aberrations, but to progress through G1/S cell cycle checkpoints. RNA immunoprecipitation, sequencing of bound transcripts and poly(A) length tests link the melanoma-specific functions of CPEB4 to signalling hubs specifically enriched in this disease. Essential in these CPEB4-controlled networks are the melanoma drivers MITF and RAB7A, a feature validated in clinical biopsies. These results provide new mechanistic links between cytoplasmic polyadenylation and lineage specification in melanoma.

RAB7 controls melanoma progression by exploiting a lineage-specific wiring of the endolysosomal pathway.

Although common cancer hallmarks are well established, lineage-restricted oncogenes remain less understood. Here, we report an inherent dependency of melanoma cells on the small GTPase RAB7, identified within a lysosomal gene cluster that distinguishes this malignancy from over 35 tumor types. Analyses in human cells, clinical specimens, and mouse models demonstrated that RAB7 is an early-induced melanoma driver whose levels can be tuned to favor tumor invasion, ultimately defining metastatic risk. Importantly, RAB7 levels and function were independent of MITF, the best-characterized melanocyte lineage-specific transcription factor. Instead, we describe the neuroectodermal master modulator SOX10 and the oncogene MYC as RAB7 regulators. These results reveal a unique wiring of the lysosomal pathway that melanomas exploit to foster tumor progression.

Targeted activation of innate immunity for therapeutic induction of autophagy and apoptosis in melanoma cells.

Inappropriate drug delivery, secondary toxicities, and persistent chemo- and immunoresistance have traditionally compromised treatment response in melanoma. Using cellular systems and genetically engineered mouse models, we show that melanoma cells retain an innate ability to recognize cytosolic double-stranded RNA (dsRNA) and mount persistent stress response programs able to block tumor growth, even in highly immunosuppressed backgrounds. The dsRNA mimic polyinosine-polycytidylic acid, coadministered with polyethyleneimine as carrier, was identified as an unanticipated inducer of autophagy downstream of an exacerbated endosomal maturation program. A concurrent activity of the dsRNA helicase MDA-5 driving the proapoptotic protein NOXA resulted in an efficient autodigestion of melanoma cells. These results reveal tractable links for therapeutic intervention among dsRNA helicases, endo/lysosomes, and apoptotic factors.