Faculty Bibliography

Melanoma is a highly prevalent cancer with an increasing incidence worldwide and high metastatic potential. Brain metastasis is a major complication of the disease, as more than 50% of metastatic melanoma patients eventually develop intracranial disease. MicroRNAs (miRNAs) have been found to play an important role in the tumorigenicity of different cancers and have potential as markers of disease outcome. Identification of relevant miRNAs has generally stemmed from miRNA profiling studies of cells or tissues, but these approaches may have missed miRNAs with relevant functions that are expressed in subfractions of cancer cells. We performed an unbiased in vivo screen to identify miRNAs with potential functions as metastasis suppressors using a lentiviral library of miRNA decoys. Notably, we found that a significant fraction of melanomas that metastasized to the brain carried a decoy for miR-124a, a miRNA that is highly expressed in the brain/neurons. Additional loss- and gain-of-function in vivo validation studies confirmed miR-124a as a suppressor of melanoma metastasis and particularly of brain metastasis. miR-124a overexpression did not inhibit tumor growth in vivo, underscoring that miR-124a specifically controls processes required for melanoma metastatic growth, such as seeding and growth post-extravasation. Finally, we provide proof of principle of this miRNA as a promising therapeutic agent by showing its ability to impair metastatic growth of melanoma cells seeded in distal organs. Our efforts shed light on miR-124a as an antimetastatic agent, which could be leveraged therapeutically to impair metastatic growth and improve patient survival.

The Great Debate session at the 2021 Melanoma Bridge virtual congress (December 2-4) featured counterpoint views from experts on seven important issues in melanoma. The debates considered the use of adoptive cell therapy versus use of bispecific antibodies, mitogen-activated protein kinase (MAPK) inhibitors versus immunotherapy in the adjuvant setting, whether the use of corticosteroids for the management of side effects have an impact on outcomes, the choice of programmed death (PD)-1 combination therapy with cytotoxic T-lymphocyte-associated antigen (CTLA)-4 or lymphocyte-activation gene (LAG)-3, whether radiation is needed for brain metastases, when lymphadenectomy should be integrated into the treatment plan and then the last debate, telemedicine versus face-to-face. As with previous Bridge congresses, the debates were assigned by meeting Chairs and positions taken by experts during the debates may not have necessarily reflected their respective personal view. Audiences voted both before and after each debate.

Survival outcomes in melanoma, and their association with mutations in the telomerase reverse transcriptase (TERT) promoter, remain uncertain. In addition, few studies have examined whether these associations are affected by a nearby common germline polymorphism, or vary based on melanoma histopathological subtype. We analyzed 408 primary tumors from a prospective melanoma cohort for somatic TERT^-124[C>T] and TERT^-146[C>T] mutations, the germline polymorphism rs2853669, and BRAF^V600 and NRAS^Q61 mutations. We tested the associations between these variants and clinicopathologic factors and survival outcomes. TERT^-124[C>T] was associated with thicker tumors, ulceration, mitoses (>0/mm²), nodular histotype and CNS involvement. In a multivariable model controlling for AJCC stage, TERT^-124[C>T] was an independent predictor of shorter recurrence-free survival (RFS) (HR=2.58, p=0.001), and overall survival (HR=2.47, p=0.029). Patients with the germline variant and TERT^-124[C>T] mutant melanomas had significantly shorter RFS than those patients lacking either or both sequence variants (p<0.04). The impact of the germline variant appeared to be more pronounced in superficial spreading compared to nodular melanoma. No associations were found between survival and TERT^-146[C>T], BRAF or NRAS mutations. These findings strongly suggest that TERT^-124[C>T] mutation is a biomarker of aggressive primary melanomas, an effect that may be modulated by rs2853669.

Metastasis is a complex process, requiring cells to overcome barriers that are only incompletely modeled by in vitro assays. A systematic workflow was established using robust, reproducible in vivo models and standardized methods to identify novel players in melanoma metastasis. This approach allows for data inference at specific experimental stages to precisely characterize a gene's role in metastasis. Models are established by introducing genetically modified melanoma cells via intracardiac, intradermal, or subcutaneous injections into mice, followed by monitoring with serial in vivo imaging. Once preestablished endpoints are reached, primary tumors and/or metastases-bearing organs are harvested and processed for various analyses. Tumor cells can be sorted and subjected to any of several 'omics' platforms, including single-cell RNA sequencing. Organs undergo imaging and immunohistopathological analyses to quantify the overall burden of metastases and map their specific anatomic location. This optimized pipeline, including standardized protocols for engraftment, monitoring, tissue harvesting, processing, and analysis, can be adopted for patient-derived, short-term cultures and established human and murine cell lines of various solid cancer types.

Brain metastasis is a significant cause of morbidity and mortality in multiple cancer types and represents an unmet clinical need. The mechanisms that mediate metastatic cancer growth in the brain parenchyma are largely unknown. Melanoma, which has the highest rate of brain metastasis among common cancer types, is an ideal model to study how cancer cells adapt to the brain parenchyma. Our unbiased proteomics analysis of melanoma short-term cultures revealed that proteins implicated in neurodegenerative pathologies are differentially expressed in melanoma cells explanted from brain metastases compared to those derived from extracranial metastases. We showed that melanoma cells require amyloid beta (AB) for growth and survival in the brain parenchyma. Melanoma-secreted AB activates surrounding astrocytes to a pro-metastatic, anti-inflammatory phenotype and prevents phagocytosis of melanoma by microglia. Finally, we demonstrate that pharmacological inhibition of AB decreases brain metastatic burden.

The contribution of epigenetic dysregulation to metastasis remains understudied. Through a meta-analysis of gene expression datasets followed by a mini-screen, we identified Plant Homeodomain Finger protein 8 (PHF8), a histone demethylase of the Jumonji C protein family, as a previously unidentified prometastatic gene in melanoma. Loss- and gain-of-function approaches demonstrate that PHF8 promotes cell invasion without affecting proliferation in vitro and increases dissemination but not subcutaneous tumor growth in vivo, thus supporting its specific contribution to the acquisition of metastatic potential. PHF8 requires its histone demethylase activity to enhance melanoma cell invasion. Transcriptomic and epigenomic analyses revealed that PHF8 orchestrates a molecular program that directly controls the TGFβ signaling pathway and, as a consequence, melanoma invasion and metastasis. Our findings bring a mechanistic understanding of epigenetic regulation of metastatic fitness in cancer, which may pave the way for improved therapeutic interventions.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor tissue is limited or unavailable for direct testing. Here, we utilize two distinct and complementary machine learning methods of analyzing whole slide images (WSI) for predicting mutated BRAF. In the first method, WSI of melanomas from 256 patients were used to train a deep convolutional neural network (CNN) in order to develop a fully automated model that first selects for tumor-rich areas (Area Under the Curve AUC=0.96) then predicts for mutated BRAF (AUC=0.71). Saliency mapping was performed and revealed that pixels corresponding to nuclei were the most relevant to network learning. In the second method, WSI were analyzed using a pathomics pipeline that first annotates nuclei and then quantifies nuclear features, demonstrating that mutated BRAF nuclei were significantly larger and rounder nuclei compared to BRAF WT nuclei. Lastly, we developed a model that combines clinical information, deep learning, and pathomics that improves the predictive performance for mutated BRAF to AUC=0.89. Not only does this provide additional insights on how BRAF mutations affect tumor structural characteristics, machine learning-based analysis of WSI has the potential to be integrated into higher order models for understanding tumor biology.

BACKGROUND:Early reports on cancer patients with coronavirus disease 2019 (COVID-19) corroborated speculation that cancer patients are at increased risk for becoming infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19. However, cancer patients are a heterogeneous population and their corresponding risk may be different. AIM/OBJECTIVE:To compare COVID-19 presentation in patients with active malignancy to those with a history of cancer to determine the impact of cancer status on COVID-19 outcomes in the two groups. METHODS AND RESULTS/RESULTS:Of the 6724 patients who were hospitalized at NYU Langone Health (3/16/20-7/31/20) and tested positive for SARS-CoV-2, 580 had either active cancer (n = 221) or a history of cancer (n = 359). We compared the baseline clinicodemographic characteristics and hospital courses of the two groups. We studied the relationship between cancer status and the rate of admission to the intensive care unit (ICU), use of invasive mechanical ventilation (IMV), and all-cause mortality. The two groups had similar laboratory results associated with COVID-19 infection, incidence of venous thromboembolism, and incidence of severe COVID-19. Active cancer status was not associated with the rate of ICU admission (p = .307) or use of IMV (p = .236), but was significantly associated with worse all-cause mortality in both univariate and multivariate analysis with odds ratios of 1.48 (95% confidence interval [CI]: 1.04-2.09; p = .028) and 1.71 (95% CI: 1.12-2.63; p = .014), respectively. CONCLUSION/CONCLUSIONS:Active cancer patients had worse survival outcomes compared to patients with a history of cancer despite similar COVID-19 disease characteristics in the two groups. Our data suggest that cancer care should continue with minimal interruptions during the pandemic to bring about response and remission as soon as possible.

Substantial progress has been made in understanding how tumors escape immune surveillance. However, few measures to counteract tumor immune evasion have been developed. Suppression of tumor antigen expression is a common adaptive mechanism that cancers use to evade detection and destruction by the immune system. Epigenetic modifications play a critical role in various aspects of immune invasion, including the regulation of tumor antigen expression. To identify epigenetic regulators of tumor antigen expression, we established a transplantable syngeneic tumor model of immune escape with silenced antigen expression and used this system as a platform for a CRISPR-Cas9 suppressor screen for genes encoding epigenetic modifiers. We found that disruption of the genes encoding either of the chromatin modifiers activating transcription factor 7-interacting protein (Atf7ip) or its interacting partner SET domain bifurcated histone lysine methyltransferase 1 (Setdb1) in tumor cells restored tumor antigen expression. This resulted in augmented tumor immunogenicity concomitant with elevated endogenous retroviral (ERV) antigens and mRNA intron retention. ERV disinhibition was associated with a robust type I interferon response and increased T-cell infiltration, leading to rejection of cells lacking intact Atf7ip or Setdb1. ATF7IP or SETDB1 expression inversely correlated with antigen processing and presentation pathways, interferon signaling, and T-cell infiltration and cytotoxicity in human cancers. Our results provide a rationale for targeting Atf7ip or Setdb1 in cancer immunotherapy.

BACKGROUND:Immune-related adverse events (irAEs) are common, clinically significant autoinflammatory toxicities observed with immune checkpoint inhibitors (ICI). Preexisting immune-mediated inflammatory disease (pre-IMID) is considered a relative contraindication to ICI due to the risk of inciting flares. Improved understanding of the risks and benefits of treating pre-IMID patients with ICI is needed. METHODS:We studied melanoma patients treated with ICI and enrolled in a prospective clinicopathological database. We compiled a list of 23 immune-mediated inflammatory diseases and evaluated their presence prior to ICI. We tested the associations between pre-IMID and progression-free survival (PFS), overall survival (OS), and irAEs. RESULTS:In total, 483 melanoma patients were included in the study; 74 had pre-IMID and 409 did not. In patients receiving ICI as a standard of care (SoC), pre-IMID was significantly associated with irAEs (p = 0.04) as well as improved PFS (p = 0.024) and OS (p = 0.007). There was no significant association between pre-IMID and irAEs (p = 0.54), PFS (p = 0.197), or OS (p = 0.746) in patients treated through a clinical trial. Pre-IMID was significantly associated with improved OS in females (p = 0.012), but not in males (p = 0.35). CONCLUSIONS:The dichotomy of the impact of pre-IMID on survival and irAEs in SoC versus clinical trial patients may reflect the inherit selection bias in patients accrued in clinical trials. Future mechanistic work is required to better understand the differences in outcomes between female and male pre-IMID patients. Our data challenge the notion that clinicians should avoid ICI in pre-IMID patients, although close monitoring and prospective clinical trials evaluating ICI in this population are warranted.