Faculty Bibliography

BACKGROUND:Tumor mutation burden (TMB) has been associated with melanoma immunotherapy (IT) outcomes, including survival. We explored whether combining TMB with immunogenomic signatures recently identified by The Cancer Genome Atlas (TCGA) can refine melanoma prognostic models of overall survival (OS) in patients not treated by IT. METHODS:Cox proportional-hazards (Cox PH) analysis was performed on 278 metastatic melanomas from TCGA not treated by IT. In a discovery and two validation cohorts Cox PH models assessed the interaction between TMB and 53 melanoma immunogenomic features to refine prediction of melanoma OS. RESULTS:Interferon-γ response (IFNγRes) and macrophage regulation gene signatures (MacReg) combined with TMB significantly associated with OS (p = 8.80E-14). We observed that patients with high TMB, high IFNγRes and high MacReg had significantly better OS compared to high TMB, low IFNγRes and low MacReg (HR = 2.8, p = 3.55E-08). This association was not observed in low TMB patients. CONCLUSIONS:We report a model combining TMB and tumor immune features that significantly improves prediction of melanoma OS, independent of IT. Our analysis revealed that patients with high TMB, high levels of IFNγRes and MacReg had significantly more favorable OS compared to high TMB patients with low IFNγRes and low MacReg. These findings may substantially improve current melanoma prognostic models.

Understanding the contribution of the host's genetic background to cancer immunity may lead to improved stratification for immunotherapy and to the identification of novel therapeutic targets. We investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA. High heritability was observed for estimates of NK cell and T cell subset infiltration and for interferon signaling. Common variants of IFIH1, TMEM173 (STING1), and TMEM108 were associated with differential interferon signaling and variants mapping to RBL1 correlated with T cell subset abundance. Pathogenic or likely pathogenic variants in BRCA1 and in genes involved in telomere stabilization and Wnt-β-catenin also acted as immune modulators. Our findings provide evidence for the impact of germline genetics on the composition and functional orientation of the tumor immune microenvironment. The curated datasets, variants, and genes identified provide a resource toward further understanding of tumor-immune interactions.

Over the last few years, numerous clinical trials and real-world experience have provided a large amount of evidence demonstrating the potential for long-term survival with immunotherapy agents across various malignancies, beginning with melanoma and extending to other tumours. The clinical success of immune checkpoint blockade has encouraged increasing development of other immunotherapies. It has been estimated that there are over 3000 immuno-oncology trials ongoing, targeting hundreds of disease and immune pathways. Evolving topics on cancer immunotherapy, including the state of the art of immunotherapy across various malignancies, were the focus of discussions at the Immunotherapy Bridge meeting (4-5 December, 2019, Naples, Italy), and are summarised in this report.

Next-generation sequencing has enabled genetic and genomic characterization of melanoma to an unprecedent depth. However, the high mutational background plus the limited deep-coverage whole-genome sequencing performed on cutaneous melanoma samples, make difficult the identification of novel driver mutations. We sought to explore the somatic mutation portfolio in exonic and gene regulatory regions in human melanoma samples, for which we performed targeted sequencing of tumors and matched germline DNA samples from 89 melanoma patients, identifying known and novel recurrent mutations. Two recurrent mutations found in the RPS27 promoter associated with decreased RPS27 mRNA levels in vitro. Data mining and IHC analyses revealed a bimodal pattern of RPS27 expression in melanoma, with RPS27-low patients displaying worse prognosis. In vitro characterization of RPS27-high and -low melanoma cell lines, as well as loss-of-function experiments, demonstrated that high RPS27 status provides increased proliferative and invasive capacities, while low RPS27 confers survival advantage in low-attachment and resistance to therapy. Additionally, we demonstrate that 10 other cancer types harbor bimodal RPS27 expression and in those, similarly to melanoma, RPS27-low expression associates with worse clinical outcomes. RPS27 promoter mutation could thus represent a mechanism of gene expression modulation in melanoma patients, which may have prognostic and predictive implications.

In immuno-oncology (IO), the baseline host factors attract significant clinical interest as promising predictive biomarker candidates primarily due to the feasibility of noninvasive testing and the personalized potential of IO outcome prediction catered to individual patients. Growing evidence from experimental or population-based studies suggests that the host genetic factors contribute to the immunological status of a patient as it plays out at the multiple rate-limiting steps of the cancer immunity cycle. Recent observations suggest that germline genetics may be associated with tumor microenvironment phenotypes, autoimmune toxicities, and/or efficacy of immunotherapy regimens and overall cancer survival. Despite these highly intriguing indications, the potential of germline genetic factors as personalized biomarkers of immune-checkpoint inhibition (ICI) remains vastly unexplored. In this chapter, we review the rationale for exploring the germline genetic factors as novel biomarkers predictive of IO outcomes, including ICI efficacy, toxicity, or survival, and discuss the approaches for the identification of such germline genetic surrogates. Specifically, we focus on strategies for mapping the germline genetic biomarkers of ICI using genome-wide scans (genome-wide association analyses, next-generation sequencing technologies), followed by targeted assays, to be applied in clinical use. As we discuss the limitations, we highlight a need for large collaborative consortia in these efforts and sketch possible avenues for incorporating germline genetic factors into emerging multifactorial approaches for more personalized prediction of ICI outcomes.

In immuno-oncology (IO), the baseline host factors attract significant clinical interest as promising predictive biomarker candidates. Growing evidence from experimental or population-based studies suggests that the host genetic factors contribute to the immunological status of a patient as it plays out at the multiple rate-limiting steps of the cancer immunity cycle. Recent observations suggest that germline genetics may be associated with tumor microenvironment phenotypes, autoimmune toxicities and/or efficacy of immunotherapy regimens and overall cancer survival. Despite these highly intriguing indications, the potential of germline genetic factors as personalized biomarkers of immune-checkpoint inhibition (ICI) remains vastly unexplored. Here, we review the rationale for exploring the germline genetic factors as novel biomarkers predictive of IO outcomes, including ICI efficacy, toxicity and survival, and discuss the comprehensive approaches for the identification of such germline genetic indicators. In addressing the current limitations, we highlight a need for large collaborative consortia in these efforts. We also outline possible avenues for incorporating germline genetic factors into emerging multifactorial tools for a more personalized prediction of ICI outcomes.

Background: Tumor-specific indicators, such as tumor mutation burden (TMB) have been shown to affect overall survival (OS) in melanoma. Recently, pan-cancer analyses from The Cancer Genome Atlas (TCGA) discovered specific tumor immune signatures predictive of overall survival (OS), yet it is unclear how these interact with other prognostic markers, independently of immunotherapy (IT). We aimed to combine the immune landscape signatures with TMB and other prognostic markers to improve melanoma OS prediction in patients, independent of IT.
Method(s): We examined the whole-exome data in conjunction with the molecular, clinical and immune features from 278 metastatic melanomas from TCGA, not treated by IT, to develop an improved prognostic model of melanoma OS. Using the discovery (N=139) and validation (N=139) design we performed multivariate Cox proportional hazards (Cox HR) models, adjusted for age and tumor stage at primary diagnosis, to identify interaction between TMB and melanoma immune features (n=59), refining the prediction of melanoma OS.
Result(s): We identified 4 immune features that were significantly associated with OS in both the discovery and validation cohorts. The multivariate Cox HR models revealed that IFN-c response (IFN-c R) and macrophage regulation (MR) signatures in combination with TMB were the most significantly associated with OS (p=8.80E-14). After further refinement, we observed that patients with high TMB, high IFN-c R and high MRhad significantly better OS compared to high TMB, low IFN-y R and low MR (HR=2.8, p=3.55E-08). This association was not observed in low TMB patients.
Conclusion(s): We show, for the first time, that TMB and tumor immune features are significantly associated with improved OS, independent of IT. Further analysis of patients revealed that high TMB associates with improved OS in patients with high IFN- c R and MR but not in low IFN- c R and MR. Hence, this data provides first evidence that patients with high TMB have distinct OS outcome depending on other tumor immune features. Beside biological link between TMB and IFN-y and MR, our data suggest that these associations may significantly improve the current melanoma prognostic models

Background Somatic genetic alterations have been associated with differential disposition of the intratumoral immune milieu. In contrast, the role of germline genetics remains largely unknown. The Cancer Genome Atlas (TCGA) Pan-Cancer Immune Response Working Group recently analyzed associations between immunological features of tumor microenvironment, prognosis, and tumor-intrinsic properties (including somatic mutations and copy number aberrations). The study generated a comprehensive set of per-sample immune response signatures, and identified distinct tumor immunological subtypes shared across multiple cancer types [1]. Here, we examined the germline genetic contribution to >100 such immune response signatures, considered as potential traits, in >9,000 study participants across 30 different cancer types in the TCGA. Methods We used SNP data from Affymetrix 6.0 arrays typed on normal tissue and blood. After stringent quality control, we imputed missing SNPs using the Haplotype Reference Consortium dataset and included SNPs with minor allele frequency >0.005 and imputation quality R2>0.5. We inferred genetic ancestry using principal components analysis. We estimated genome-wide heritability of the immune signatures using the genomic-relatedness-based restricted maximumlikelihood (GREML) approach implemented in genome-wide complex trait analysis (GCTA). We performed genome-wide association studies (GWAS) using linear regression models. All analyses were adjusted for cancer type, age at diagnosis, gender, and genetic ancestry using principal components 1-7. Linear regression was also applied to germline exome sequence data [2] to evaluate rare variant associations. Results Across different tumor types, we found significant heritability (FDR< 0.05) for estimates of innate and adaptive immune cell enrichment including natural killer cells, activated dendritic cells, eosinophils and neutrophils, and T-cell subsets (CD8 Cytotoxic, T-helper, T-follicular helper, T-effector memory, T-central memory, Th1 and Th17 cells) respectively, as well as for antigen-presenting machinery and interferon-related signatures. Furthermore, we found significant interactions between germline modifiers and distinct immune subtypes (FDR<0.05). Through GWAS analysis, we identified several polymorphisms associated with both immune cells and immunomodulatory signaling passing the genome-wide significance threshold (p<5E-8). Two SNPs previously associated with the risk of several auto-immune diseases [3], rs2111485 and rs1990760 mapping to Interferon Induced Helicase C Domain 1 (IFIH1) locus, were significantly correlated with interferon signaling in tumors (Figure 1). Moreover, suggestive associations between rare variants and immune response traits were found. Conclusions We demonstrated that intratumoral immune disposition is partially under germline control through systematic pan-cancer analysis. Germline variants associated with differential immune response might be used to stratify patients based on likelihood of treatment response and to prioritize targets for development of novel therapies. (Figure Preseted)

Background Autoantibody landscapes are very specific to the individual, can remain stable for many years, and contain unique features reported in association with cancer, autoimmunity, infection, neurologic conditions, CD8+ T cell behavior, and checkpoint blockade adverse events [1-11]. The goal of this work was to determine whether pre-existing antigenspecific features in melanoma patient autoantibody landscapes would associate with clinical outcomes following checkpoint blockade. Methods Pre-treatment serum samples were collected from 117 melanoma patients prior to checkpoint blockade with anti-CTLA4 (N=60), anti-PD1 (N=38), or both in combination (N=16). All data was collected with approval of the NYU Institutional Review Board at the NYU Perlmutter Cancer Center with informed consent [11]. Serum samples were run on HuProt Human Proteome Microarrays containing >19,000 human proteins by CDI Laboratories. Raw serum IgG signal intensities were processed across staining cohorts via interquartile range normalization. Pre-existing antibody responses were defined as patient-specific IgG signals >3.5 median absolute deviations above cohort median IgG background (modified Z-score). Group statistics were computed (GraphPad Prism), and gene ontology enrichment analysis was performed (Enrichr) [12]. Results Several pre-existing antigen-specific IgG autoantibody targets were observed to have associations with good outcomes (SD/PR) or objective clinical responses (PR/CR) versus patients with progressive disease (POD). While final determination of the most predictive subsets is ongoing, many targets represent genes in an axis surrounding immune signaling pathways, hereditary neurodegenerative disease, and the ubiquitin proteasome pathway (ie, UBQLN1, UBQLN2). An exemplary example was observed in the autoantibody responses shared by >10% of all patients regardless of clinical outcome. Gene ontology enrichment analysis of these shared melanoma-patient autoantibodies versus KEGG 2019 [12] demonstrates this set of proteins is strongly enriched for neurotrophin signaling-associated proteins after multi-sample correction (P=0.004) (Table 1). Several other associations were observed cohort-wide for ontologies with tissuespecific enrichment in the brain, neurons, and neuronal processes. Conclusions In this pilot study, we found strong associations across the cohort for autoantibodies against nerve-growth-inducing neurotrophins and genes like UBQLN1 and UBQLN2 which have strong associations with amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson's, and Alzheimer's - neurodegenerative diseases that are known to have incidences which correlate with melanoma [14-16]; this hints at a potential immunologic connection between the conditions, perhaps related to an antitumor / autoimmune axis involving the targets reported here. (Table Presented)

Multiple primary melanoma (MPM) has been associated with a higher 10-year mortality risk compared to patients with single primary melanoma (SPM). Given that 3-8% of patients with SPM develop additional primary melanomas, new markers predictive of MPM risk are needed. Based on the evidence that the immune system may regulate melanoma progression, we explored whether germline genetic variants controlling the expression of 41 immunomodulatory genes modulate the risk of MPM compared to patients with SPM or healthy controls. By genotyping these 41 variants in 977 melanoma patients, we found that rs2071304, linked to the expression of SPI1, was strongly associated with MPM risk reduction (OR = 0.60; 95% CI = 0.45-0.81; p = 0.0007) when compared to patients with SPM. Furthermore, we showed that rs6695772, a variant affecting expression of BATF3, is also associated with MPM-specific survival (HR = 3.42; 95% CI = 1.57-7.42; p = 0.0019). These findings provide evidence that the genetic variation in immunomodulatory pathways may contribute to the development of secondary primary melanomas and also associates with MPM survival. The study suggests that inherited host immunity may play an important role in MPM development.