Faculty Bibliography

Screening for therapeutic targets is standard of care in the management of advanced non-small cell lung cancer. However, most molecular assays utilize tumor tissue, which may not always be available. "Liquid biopsies" are plasma-based next generation sequencing (NGS) assays that use circulating tumor DNA to identify relevant targets. To compare the sensitivity, specificity, and accuracy of a plasma-based NGS assay to solid-tumor-based NGS we retrospectively analyzed sequencing results of 100 sequential patients with lung adenocarcinoma at our institution who had received concurrent testing with both a solid-tissue-based NGS assay and a commercially available plasma-based NGS assay. Patients represented both new diagnoses (79%) and disease progression on treatment (21%); the majority (83%) had stage IV disease. Tissue-NGS identified 74 clinically relevant mutations, including 52 therapeutic targets, a sensitivity of 94.8%, while plasma-NGS identified 41 clinically relevant mutations, a sensitivity of 52.6% (p < 0.001). Tissue-NGS showed significantly higher sensitivity and accuracy across multiple patient subgroups, both in newly diagnosed and treated patients, as well as in metastatic and nonmetastatic disease. Discrepant cases involved hotspot mutations and actionable fusions including those in EGFR, ALK, and NTRK1. In summary, tissue-NGS detects significantly more clinically relevant alterations and therapeutic targets compared to plasma-NGS, suggesting that tissue-NGS should be the preferred method for molecular testing of lung adenocarcinoma when tissue is available. Plasma-NGS can still play an important role when tissue testing is not possible. However, given its low sensitivity, a negative result should be confirmed with a tissue-based assay.

The Great Debate session at the 2020 Melanoma Bridge virtual congress (December 3rd-5th, Italy) featured counterpoint views from experts on five specific controversial issues in melanoma. The debates considered whether or not innate immunity is important in the response to cancer and immunotherapy, how useful are the revised American Joint Committee on Cancer (AJCC) classification for the staging of patients, the use of sentinel node biopsy for staging patients, the use of triplet combination of targeted therapy plus immunotherapy versus combined immunotherapy, and the respective benefits of neoadjuvant versus adjuvant therapy. As is usual with Bridge congresses, the debates were assigned by meeting Chairs and positions taken by experts during the debates may not have necessarily reflected their own personal opinion.
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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.

High levels of autoimmune antibodies are observed in COVID-19 patients but their specific contribution to disease severity and clinical manifestations remains poorly understood. We performed a retrospective study of 115 COVID-19 hospitalized patients with different degrees of severity to analyze the generation of autoimmune antibodies to common antigens: a lysate of erythrocytes, the lipid phosphatidylserine (PS) and DNA. High levels of IgG autoantibodies against erythrocyte lysates were observed in a large percentage (up to 36%) of patients. Anti-DNA and anti-PS antibodies determined upon hospital admission correlated strongly with later development of severe disease, showing a positive predictive value of 85.7% and 92.8%, respectively. Patients with positive values for at least one of the two autoantibodies accounted for 24% of total severe cases. Statistical analysis identified strong correlations between anti-DNA antibodies and markers of cell injury, coagulation, neutrophil levels and erythrocyte size. Anti-DNA and anti-PS autoantibodies may play an important role in the pathogenesis of COVID-19 and could be developed as predictive biomarkers for disease severity and specific clinical manifestations.

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.

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.

This overview of the 5^th edition of the WHO Classification of thymic epithelial tumors (TETs, including thymomas, thymic carcinomas (TCs) and thymic neuroendocrine tumors (NETs)), mediastinal germ cell tumors (GCTs) and mesenchymal neoplasms aims to 1) list established and new tumor entities and subtypes, and 2) focus on diagnostic, molecular and conceptual advances since publication of the 4^th edition in 2015. Diagnostic advances are best exemplified by the immunohistochemical characterization of adenocarcinomas, and the recognition of genetic translocations in metaplastic thymomas, rare B2 and B3 thymomas, and hyalinizing clear cell carcinomas. Advancements at the molecular and tumor biological level of utmost oncological relevance are the findings that thymomas and most TCs lack currently targetable mutations, have an extraordinarily low tumor mutational burden, but commonly show a programmed death-ligand 1 (PD-L1)^high phenotype. Finally, data underpinning a conceptual advance is illustrated for the future classification of thymic NETs that may fit into the classification scheme of extrathoracic NETs. Endowed with updated clinical information and state-of-the-art PET/CT images, the 5^th edition of the WHO classification of TETs, GCTs and mesenchymal neoplasms with its wealth of new diagnostic and molecular insights will be a valuable source for pathologists, radiologists, surgeons and oncologists alike. Therapeutic perspectives and research challenges will be addressed as well.

BACKGROUND:Immune checkpoint blockade (ICB) shows lasting benefits in advanced melanoma; however, not all patients respond to this treatment and many develop potentially life-threatening immune-related adverse events (irAEs). Identifying individuals who will develop irAEs is critical in order to improve the quality of care. Here, we prospectively demonstrate that the gut microbiome predicts irAEs in melanoma patients undergoing ICB. METHODS:Pre-, during, and post-treatment stool samples were collected from 27 patients with advanced stage melanoma treated with IPI (anti-CTLA-4) and NIVO (anti-PD1) ICB inhibitors at NYU Langone Health. We completed 16S rRNA gene amplicon sequencing, DNA deep shotgun metagenomic, and RNA-seq metatranscriptomic sequencing. The divisive amplicon denoising algorithm (DADA2) was used to process 16S data. Taxonomy for shotgun sequencing data was assigned using MetaPhlAn2, and gene pathways were assigned using HUMAnN 2.0. Compositionally aware differential expression analysis was performed using ANCOM. The Cox-proportional hazard model was used to assess the prospective role of the gut microbiome (GMB) in irAES, with adjustment for age, sex, BMI, immune ICB treatment type, and sequencing batch. RESULTS:= 0.88, p < 0.001). CONCLUSIONS:We identified two distinct fecal bacterial community clusters which are associated differentially with irAEs in ICB-treated advanced melanoma patients.

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