Faculty Bibliography

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.

Chemotherapy-induced alopecia and radiation-induced alopecia, the thinning or loss of hair due to cytotoxic chemotherapy and radiation therapy, respectively, are distressing adverse effects of cancer treatment. Chemotherapy, targeted therapies, and radiation therapy used in pediatric oncology often lead to alopecia by damaging hair follicles, with varying degrees of severity depending on the specific treatment type, mechanism of action, and damage-response pathway involved. Pediatric chemotherapy-induced alopecia, radiation-induced alopecia, and permanent alopecia, defined as hair regrowth that remains incomplete 6 months or more after treatment, have significant negative impacts on mental health, self-esteem, and social interactions, highlighting the need for further research into supportive care strategies. There are currently no standard interventions for chemotherapy-induced alopecia or radiation-induced alopecia in children, with most recommendations limited to gentle hair care and camouflaging techniques during treatment. Scalp cooling has demonstrated safety and efficacy in reducing chemotherapy-induced alopecia in adults and is currently under investigation in children and adolescents. Topical and low-dose oral minoxidil have been studied in children for other hair loss disorders and may improve hair regrowth after chemotherapy or radiation. Increased awareness and continued research into management strategies for pediatric chemotherapy-induced alopecia and radiation-induced alopecia are necessary to help mitigate its significant negative impact on quality of life.

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.

IMPORTANCE/UNASSIGNED:There exists substantial heterogeneity in outcomes within T stages for patients with cutaneous squamous cell carcinoma (cSCC). OBJECTIVE/UNASSIGNED:To determine whether a customized generative pretrained transformer model, trained on a comprehensive dataset with more than 1 trillion parameters and equipped with relevant focused context and retrieval augmented generation (RAG), could excel in aggregating and interpreting vast quantities of data to develop a novel class-based risk stratification system that outperforms the current standards. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:To build the RAG knowledge base, a systematic review of the literature was conducted that addressed risk factors for poor outcomes in cSCC. Using the RAG-enabled generative pretrained transformer (GPT) model, we developed a novel class-based risk stratification system that assigned point values for risk factors, culminating in a GPT-based prognostication system called the artificial intelligence-derived risk score (AIRIS). The system's performance was validated on a combined prospective and retrospective cohort of 2379 primary cSCC tumors (1996-2023) with at least 36 months of follow-up, against Brigham and Women's Hospital (BWH) and American Joint Committee on Cancer Staging Manual, eighth edition (AJCC8) systems in stratifying risk for locoregional recurrence (LR), nodal metastasis (NM), distant metastasis (DM), and disease-specific death (DSD). MAIN OUTCOMES AND MEASURES/UNASSIGNED:Performance metrics evaluated included distinctiveness, homogeneity, and monotonicity, as defined by the AJCC8, as well as sensitivity, specificity, positive predictive value, negative predictive value, accuracy, the area under the receiver operating characteristic curve, and concordance. RESULTS/UNASSIGNED:The median age at diagnosis was 73 (IQR, 64-81) years, with 38.5% female patients and 61.5% male patients. The AIRIS prognostication system demonstrated superior sensitivity across all outcomes (LR, 49.1%; NM, 73.7%; DM, 82.5%; and DSD, 72.2%) and the highest area under the receiver operating characteristic curve values (LR, 0.69; NM, 0.81; DM, 0.85; and DSD, 0.80), indicating significantly enhanced discriminative capability compared with the BWH and AJCC8 systems. While all systems were comparably distinctive, the AIRIS prognostication system consistently demonstrated the lowest proportion of tumors exhibiting poor outcomes in low-risk categories, suggesting its improved homogeneity and monotonicity. CONCLUSIONS AND RELEVANCE/UNASSIGNED:The results of this diagnostic study suggest that the AIRIS system outperforms the existing BWH and AJCC8 prognostication systems, potentially providing a more effective tool for predicting poor outcomes in cSCC. This study illustrates the potential of large language models in refining prognostic tools, offering implications for treating patients with cancer.

BACKGROUND:Lymphovascular invasion (LVI) is regarded as a high-risk feature of cutaneous squamous cell carcinoma (CSCC) but is currently absent from CSCC staging systems. OBJECTIVE:To assess whether LVI serves as an independent predictor of major poor outcomes in CSCC. METHODS:Twelve centers contributed to a multinational CSCC database. Clinical and pathologic risk factors, treatment, and patient outcomes were retrospectively collected. CSCCs were stratified based on LVI status. Tumors that developed major poor outcomes defined as nodal metastasis, in-transit metastasis, distant metastasis, and disease-specific death were identified. RESULTS:A total of 23,166 CSCCs were identified, 179 were LVI+ tumors (0.8%). LVI+ tumors had a higher cumulative incidence of major poor outcomes than those without LVI (33.5% vs. 3.2% at 3 years; overall cumulative incidence function p < 0.001). In an adjusted analysis, LVI+ tumors had an 82% increase in the rate of developing major poor outcomes when compared to LVI- tumors (subdistribution hazard ratio (SHR) = 1.82; p = 0.002). Notably, LVI+ low-stage BWH tumors (T1 or T2a) had a greater cumulative incidence of major poor outcomes compared to LVI- BWH low-stage tumors (20.7% vs. 1.61% at 3 years, overall cumulative incidence function p < 0.001). LIMITATIONS/CONCLUSIONS:Retrospective study design CONCLUSION: The presence of LVI in CSCC is a high-risk feature that is an independent predictor of metastasis and disease-specific death in both low and high BWH stage tumors.