Faculty Bibliography

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 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)

Melanoma, the deadliest skin cancer, remains largely incurable at advanced stages. Currently, there is a lack of animal models that resemble human melanoma initiation and progression. Recent studies using a Tyr-CreER driven mouse model have drawn contradictory conclusions about the potential of melanocyte stem cells (McSCs) to form melanoma. Here, we employ a c-Kit-CreER-driven model that specifically targets McSCs to show that oncogenic McSCs are a bona fide source of melanoma that expand in the niche, and then establish epidermal melanomas that invade into the underlying dermis. Further, normal Wnt and Endothelin niche signals during hair anagen onset are hijacked to promote McSC malignant transformation during melanoma induction. Finally, molecular profiling reveals strong resemblance of murine McSC-derived melanoma to human melanoma in heterogeneity and gene signatures. These findings provide experimental validation of the human melanoma progression model and key insights into the transformation and heterogeneity of McSC-derived melanoma.

BACKGROUND:Recent evidence suggests that immunotherapy efficacy in melanoma is modulated by gut microbiota. Few studies have examined this phenomenon in humans, and none have incorporated metatranscriptomics, important for determining expression of metagenomic functions in the microbial community. METHODS:In melanoma patients undergoing immunotherapy, gut microbiome was characterized in pre-treatment stool using 16S rRNA gene and shotgun metagenome sequencing (n = 27). Transcriptional expression of metagenomic pathways was confirmed with metatranscriptome sequencing in a subset of 17. We examined associations of taxa and metagenomic pathways with progression-free survival (PFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression. RESULTS:Higher microbial community richness was associated with longer PFS in 16S and shotgun data (p < 0.05). Clustering based on overall microbiome composition divided patients into three groups with differing PFS; the low-risk group had 99% lower risk of progression than the high-risk group at any time during follow-up (p = 0.002). Among the species selected in regression, abundance of Bacteroides ovatus, Bacteroides dorei, Bacteroides massiliensis, Ruminococcus gnavus, and Blautia producta were related to shorter PFS, and Faecalibacterium prausnitzii, Coprococcus eutactus, Prevotella stercorea, Streptococcus sanguinis, Streptococcus anginosus, and Lachnospiraceae bacterium 3 1 46FAA to longer PFS. Metagenomic functions related to PFS that had correlated metatranscriptomic expression included risk-associated pathways of L-rhamnose degradation, guanosine nucleotide biosynthesis, and B vitamin biosynthesis. CONCLUSIONS:This work adds to the growing evidence that gut microbiota are related to immunotherapy outcomes, and identifies, for the first time, transcriptionally expressed metagenomic pathways related to PFS. Further research is warranted on microbial therapeutic targets to improve immunotherapy outcomes.

Despite major improvements in combatting metastatic melanoma since the advent of immunotherapy, the overall survival for patients with advanced disease remains low. Recently, there is a growing number of reports supporting an "obesity paradox," in which patients who are overweight or mildly obese may exhibit a survival benefit in patients who received immune checkpoint inhibitors. We studied the relationship between body mass index and progression-free survival and overall survival in a cohort of 423 metastatic melanoma patients receiving immunotherapy, enrolled and prospectively followed up in the NYU Interdisciplinary Melanoma Cooperative Group database. We analyzed this association stratified by first vs. second or greater-line of treatment and treatment type adjusting for age, gender, stage, lactate dehydrogenase, Eastern Cooperative Oncology Group performance status, number of metastatic sites, and body mass index classification changes. In our cohort, the patients who were overweight or obese did not have different progression-free survival than patients with normal body mass index. Stratifying this cohort by first vs. non-first line immunotherapy revealed a moderate but insignificant association between being overweight or obese and better progression-free survival in patients who received first line. Conversely, an association with worse progression-free survival was observed in patients who received non-first line immune checkpoint inhibitors. Specifically, overweight and obese patients receiving combination immunotherapy had a statistically significant survival benefit, whereas patients receiving the other treatment types showed heterogeneous trends. We caution the scientific community to consider several important points prior to drawing conclusions that could potentially influence patient care, including preclinical data associating obesity with aggressive tumor biology, the lack of congruence amongst several investigations, and the limited reproduced comprehensiveness of these studies.

Background: Banking of human biospecimens linked to prospective, well-annotated clinical information is critical for advancing biomedical research. However, the establishment of an efficient biobank encompasses many issues including adherence to federal regulations, institutional policies and governance of the relationship between the biobank, investigators and funding agents. Here we report on the efforts of the Center for Biospecimen Research and Development (CBRD) at NYULH to establish a state-of-the-art biobank. Method(s): In 2015, we identified the need to establish a centralized infrastructure to facilitate research collaborations and support clinical trial studies. The four main considerations were: 1) creating a centralized mechanism to consent, collect and bank human biospecimens 2) Organizing, de-identifying, and annotating subjects' samples linked to their clinical data 3) Establishing multidisciplinary involvement of pathology departments 4) Enhancing quality control measures to achieve CAP and NYS DOH accreditation. To address these considerations, we created a Universal Consent (UC) form; developed a Laboratory Information Management System that assists in specimen organization and links subject samples to clinical data in their electronic medical record and fostered a partnership between the pathology department, individual researchers and the CBRD to develop best practices in biobanking. Result(s): Since June 2016, using the UC, 18,906 of 27,355 (70%) subjects agreed to use their specimens and data for research. 9,054 patients had specimens collected using the UC and additional specific consent if needed. We collected 4,178 unique samples (tissue, blood and fluids)-13,969 aliquots by the UC method and 7,713 samples from fresh and archival collections for specific research studies or clinical trials. The CBRD supported 93 research projects and 251 clinical trials. Conclusion(s): Establishment of the CBRD permitted the increase in absolute number of patients approached for research; enhancement of specimen quality and organization and introduction of the electronic crosslink to minimize the time and overhead needed for clinical data retrieval. Building on this success, we are upgrading our IT infrastructure to expand upon the data collected, digitalizing tissue slides to improve quality control and building an automated molecular genotyping database using existing NGS data to increase the number of trans-lational research projects

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.

Patients diagnosed with metastatic melanoma have varied clinical courses, even in patients with similar disease characteristics. We examine the impact of initial stage of melanoma diagnosis, BRAF status of primary melanoma, and receiving adjuvant therapy on postmetastatic overall survival (pmOS). We studied melanoma patients presenting to Perlmutter Cancer Center at New York University and prospectively enrolled in New York University melanoma biospecimen database and followed up on protocol-driven schedule. Patients were stratified by stage at initial melanoma diagnosis as per AJCC 7th ed. guidelines. pmOS was determined using the Kaplan-Meier method and Cox's proportional hazards models were used to assess hazard ratios (HRs). Three hundred and four out of 3204 patients developed metastatic disease over the time of follow-up (median follow-up 2.2 years, range: 0.08-35.2 years). Patients diagnosed with stage I (n=96) melanoma had longer pmOS (29.5 months) than those diagnosed with stage II (n=99, pmOS 14.9 months) or stage III (n=109, pmOS 15.1 months) melanoma (P=0.036). Initial stage of diagnosis remained significant in multivariate analysis when controlling for lactate dehydrogenase and site of metastases [primary diagnosis stage II (HR 1.44, P=0.046), stage III (HR 1.5, P=0.019)]. Adjuvant treatment was associated with better survival but BRAF mutation status did not show an association. Our data challenge the general assumption that primary melanomas converge upon diagnosis of metastatic disease and behave uniformly. Primary stage of melanoma at the time of diagnosis may be prognostic of outcome, similar to lactate dehydrogenase and metastatic disease sites.