Faculty Bibliography

PURPOSE/UNASSIGNED:Cancer treatment has been revolutionized by immune checkpoint inhibitors (ICI). However, a subset of patients do not respond and/or they experience significant adverse events. Attempts to integrate reliable biomarkers of ICI response as part of standard care have been hampered by limited generalizability. We previously reported our supervised machine learning (ML) model in a retrospective cohort of metastatic melanoma. EXPERIMENTAL DESIGN/UNASSIGNED:In this study, we expanded our testing to include larger cohorts of patients with melanoma accrued at several sites, including patients enrolled in clinical trials in both adjuvant and metastatic settings. We examined pretreatment hematoxylin and eosin slides from 639 patients with stage III/IV melanoma treated with ICIs [anti-cytotoxic T-lymphocyte-associated protein 4 (n = 212), anti-programmed death 1 (n = 271), or the combination (n = 156)]. We tested the generalizability of our supervised ML algorithm to predict response to ICIs in the metastatic melanoma cohort and then developed a self-supervised ML model to identify the histologic morphologies associated with patients' survival following ICI use in adjuvant and metastatic melanoma cohorts. RESULTS/UNASSIGNED:We predicted the response to ICI treatment with an AUC of 0.72. The deep convolutional neural network classified patients into high and low risk based on their likelihood of progression-free survival (P < 0.0001). We uncovered a novel association of specific histomorphologic tumor features-epithelioid histology and a low tumor-stroma ratio-with survival following ICI treatment. CONCLUSIONS/UNASSIGNED:Our data support the generalizability of our developed ML algorithm in predicting response to ICI treatment in patients with metastatic unresectable melanoma. We also showed, for the first time, tumor features associated with patients' overall survival.

Targeted therapies and immunotherapy have improved treatment outcomes for many melanoma patients. However, patients whose melanomas harbor driver mutations in the neurofibromin 1 (NF1) tumor suppressor gene often lack effective targeted treatment options when their tumors do not respond to immunotherapy. In this study, we utilized patient-derived short-term cultures (STCs) and multiomics approaches to identify molecular features that could inform the development of therapies for patients with NF1 mutant melanoma. Differential gene expression analysis revealed that the epidermal growth factor receptor (EGFR) is highly expressed and active in NF1 mutant melanoma cells, where it hyper-activates ERK and AKT, leading to increased tumor cell proliferation, survival, and growth. In contrast, genetic or pharmacological inhibition of EGFR hindered cell proliferation and survival and suppressed tumor growth in patient-derived NF1 mutant melanoma models but not in NF1 wild-type models. These results reveal a connection between NF1 loss and increased EGFR expression that is critical for the survival and growth of NF1 mutant melanoma cells in patient-derived culture and xenograft models, irrespective of their BRAF and NRAS mutation status.

Benign peripheral nerve sheath tumors (PNSTs) represent a heterogeneous group of neoplasms with varying histological and molecular characteristics. While traditional classifications categorize these tumors based on predominant cell types, recent advances in molecular pathology have revealed the presence of hybrid tumors featuring elements from at least two nerve sheath tumors (hPNST). We herein studied 20 cases of hPNST involving 15 female and 5 male patients (median age: 29.5 years; range: 3 weeks - 71 years). Tumors occurred on the upper extremity (6), scalp (3), trunk (3), face (3), lower extremity (2), right lateral neck (1), nasal sinus (1) and retroperitoneum (1). Follow-up information was available in 9 of 20 cases (45%; median: 10 months; range: 2 weeks - 144 months) and documented local recurrence in 2 of 9 patients (22%) at 10 and 144 months after incomplete excision. Next-generation sequencing demonstrated VGLL3 fusions in 14 cases, fused with CHD7 (10 tumors), CHD9 (3 tumors), and MAMLD1 (1 tumor), an alternate TEAD1::NCOA2 (1 tumor) fusion and several novel fusions including TOX::TEAD1 (2 tumors), RREB1::LPP (1 tumor), SRF::MYOCD (1 tumor) and KANK1::CDK5RAP2 (1 tumor). Most tumors with VGLL3 fusions showed morphologically and immunophenotypically classic features of hybrid schwannoma-perineurioma, while rare cases showed unusual microscopic features such as prominent myxoid stroma, pseudolipoblasts, prominent schwannian nodules, or solely schwannomatous morphology. The RREB1::LPP -driven tumor showed features of hybrid schwannoma-neurofibroma. Lastly, one tumor with a novel SRF::MYOCD fusion displayed morphologic features reminiscent of desmoplastic melanoma while exhibiting a combined neural and smooth muscle phenotype. Our data expands on the morphologic and molecular spectrum of fusion-driven hybrid peripheral nerve sheath tumors, including 5 previously undescribed fusions, and further expands on non-CNS schwannomas with VGLL3 fusions.

Chromosomal structural variants (SVs) are major contributors to cancer development. Although multiple methods exist for detecting SVs, they are limited in throughput, such as fluorescent in situ hybridization and targeted panels, and use RNA, which degrades in formalin-fixed, paraffin-embedded (FFPE) blocks and is unable to detect SVs that do not produce a fusion transcript. High-throughput chromosome conformation capture (Hi-C) is a DNA-based next-generation sequencing (NGS) method that preserves the spatial conformation of the genome, capturing long-range genetic interactions and SVs. Herein, a retrospective study analyzing 71 FFPE specimens from 10 different solid tumors was performed. Results showed high concordance (98%) with clinical fluorescent in situ hybridization and RNA NGS in detecting known SVs. Furthermore, Hi-C provided insight into the mechanism of SV formation, including chromothripsis and extrachromosomal DNA, and detected rearrangements between genes and regulatory regions, all of which are undetectable by RNA NGS. Lastly, SVs were detected in 71% of cases in which previous clinical methods failed to identify a driver. Of these, 14% were clinically actionable based on current medical guidelines, and an additional 14% were not in medical guidelines but involve targetable biomarkers. Current data suggest that Hi-C is a robust and accurate method for genome-wide SV analyses from FFPE tissue and can be incorporated into current clinical NGS workflows.

Soft tissue sarcomas (STSs) are a diverse group of malignant tumors derived from mesenchymal tissues [...].

BACKGROUND:Digital papillary adenocarcinoma (DPAC) is a rare but aggressive cutaneous malignant sweat gland neoplasm that occurs on acral sites. Despite its clinical significance, the cellular and genetic characteristics of DPAC remain incompletely understood. METHODS:We conducted a comprehensive genomic and transcriptomic analysis of DPAC (n = 14) using targeted next-generation DNA and RNA sequencing, along with gene expression profiling employing the Nanostring Technologies nCounter IO 360 Panel. Gene expression in DPAC was compared to that in hidradenoma (n = 10). Immunohistochemistry was employed to validate gene expression. RESULTS:Two out of eight DPACs showed fusion gene rearrangements (CRTC3::MAML2 and TRPS1::PLAG1). No uniform mutational signature was detected in DPAC. Comparative gene expression analysis revealed an enrichment of genes related to matrix remodeling, metabolism, and DNA damage repair. Hallmark pathway analysis demonstrated significant upregulation of E2F target genes in DPAC compared to hidradenoma (p = 0.00710). Human papillomavirus-42 was found to be positive in all of our tested DPAC cases. Immunohistochemistry confirmed increased protein expression of CD56, CDC20, and SOX10 in DPAC. Notably, most DPAC tumors also exhibited B-cell infiltration, as indicated by CD20 staining. CONCLUSIONS:Our findings reveal novel fusions and validate altered replication pathways related to HPV42 in DPAC.

PURPOSE/OBJECTIVE:Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep learning strategies on histology samples to predict outcome for OSA in the neoadjuvant setting. EXPERIMENTAL DESIGN/METHODS:Our study relies on a training cohort from New York University (New York, NY) and an external cohort from Charles university (Prague, Czechia). We trained and validated the performance of a supervised approach that integrates neural network predictions of necrosis/tumor content, and compared predicted overall survival (OS) using Kaplan-Meier curves. Furthermore, we explored morphology-based supervised and self-supervised approaches to determine whether intrinsic histomorphological features could serve as a potential marker for OS in the setting of neoadjuvant. RESULTS:Excellent correlation between the trained network and the pathologists was obtained for the quantification of necrosis content (R2=0.899, r=0.949, p < 0.0001). OS prediction cutoffs were consistent between pathologists and the neural network (22% and 30% of necrosis, respectively). Morphology-based supervised approach predicted OS with p-value=0.0028, HR=2.43 [1.10-5.38]. The self-supervised approach corroborated the findings with clusters enriched in necrosis, fibroblastic stroma, and osteoblastic morphology associating with better OS (lg2HR; -2.366; -1.164; -1.175; 95% CI=[-2.996; -0.514]). Viable/partially viable tumor and fat necrosis were associated with worse OS (lg2HR;1.287;0.822;0.828; 95% CI=[0.38-1.974]). CONCLUSIONS:Neural networks can be used to automatically estimate the necrosis to tumor ratio, a quantitative metric predictive of survival. Furthermore, we identified alternate histomorphological biomarkers specific to the necrotic and tumor regions themselves which can be used as predictors.

Gene fusions involving JAZF1 are a recurrent event in low grade endometrial stromal sarcoma, and have been more recently described in few instances of endometrial stromal sarcoma-like tumors in the genitourinary tract of men. In this article, we describe a previously unreported spindle cell sarcoma harboring an in-frame JAZF1::NUDT5 gene fusion, arising in the chest wall of a 51-year-old man. The tumor had unique morphologic features resembling both endometrial stromal sarcoma and endometrial stromal sarcoma-like tumors, consisting of a mixture of cytologically bland and pleomorphic spindle cells with brisk mitotic activity, within an alternating myxoid and fibrous stroma. It had diffuse immunohistochemical expression of CD10, CD34 and CD56, and variable expression of androgen receptor. To our knowledge, neoplasms with these clinico-pathologic characteristics and novel gene fusion have not been previously reported in the English language literature.