Assessment of tumor infiltrating lymphocytes (TILs) as a prognostic variable in melanoma has not seen broad adoption due to lack of standardization. Automation could represent a solution. Here, using open source software, we build an algorithm for image-based automated assessment of TILs on hematoxylin-eosin stained sections in melanoma. Using a retrospective collection of 641 melanoma patients comprising four independent cohorts; one training set (N = 227) and three validation cohorts (N = 137, N = 201, N = 76) from 2 institutions, we show that the automated TIL scoring algorithm separates patients into favorable and poor prognosis cohorts, where higher TILs scores were associated with favorable prognosis. In multivariable analyses, automated TIL scores show an independent association with disease-specific overall survival. Therefore, the open source, automated TIL scoring is an independent prognostic marker in melanoma. With further study, we believe that this algorithm could be useful to define a subset of patients that could potentially be spared immunotherapy.

Biomarkers for disease-specific survival (DSS) in earlystage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural network architecture for DSS prediction.Experimental Design: The model was trained on 108 patients from four institutions and tested on 104 patients from Yale School of Medicine (YSM, New Haven, CT). A receiver operating characteristic (ROC) curve was generated on the basis of vote aggregation of individual image sequences, an optimized cutoff was selected, and the computational model was tested on a third independent population of 51 patients from Geisinger Health Systems (GHS).Results: Area under the curve (AUC) in the YSM patients was 0.905 (P < 0.0001). AUC in the GHS patients was 0.880 (P < 0.0001). Using the cutoff selected in the YSM cohort, the computational model predicted DSS in the GHS cohort based on Kaplan-Meier (KM) analysis (P < 0.0001).Conclusions: The novel method presented is applicable to digital images, obviating the need for sample shipment and manipulation and representing a practical advance over current genetic and IHC-based methods.

PATIENTS AND METHODS.This multicenter phase 1 study used the time-to-event continual reassessment method (TITE-CRM) to study the combination of sirolimus, doses ranging from 2-6mg, with pexidartinib, doses ranging from 600-1000mg, both provided continuously on a 28 day cycle, in patients with advanced sarcoma. A total of 24 patients (eight MPNST, three tenosynovial giant cell tumor (TGCT), five leiomyosarcoma and eight with other sarcoma subtypes) were enrolled. The median age was 46 years, 56% were male, and 61% had >2 prior lines of therapy. RESULTS.The recommended phase 2 dose (RP2D) was 2mg of sirolimus combined with 1000mg of pexidartinib daily. Of the 18 evaluable subjects, five experienced dose-limiting toxicities (2 elevated AST/ALT, 2 elevated sirolimus trough levels, and 1 grade 5 dehydration).Most common grade 2 or higher treatment related adverse events included anemia, fatigue, neutropenia, and lymphopenia. Clinical benefit was observed in 12 out of 18 (67%) evaluable subjects with 3 partial responses (all in TGCT) and 9 stable disease. Tissue staining indicated a decreased proportion of activated M2 macrophages within tumor samples with treatment. CONCLUSIONS.Pexidartinib can be safely administered with sirolimus. These findings support further investigation of this combination to determine clinical efficacy. Clinicaltrials.gov identifier NCT02584647.Research.

Talimogene laherparepvec (T-VEC) is the first OV approved for the treatment of melanoma and presents new challenges as it enters the clinical setting. Several other OVs are at various stages of clinical and pre-clinical development for the treatment of melanoma. Reports from phase Ib-III clinical trials combining T-VEC with checkpoint blockade are encouraging and demonstrate potential added benefit of combination immunotherapy. OVs have recently emerged as a standard treatment option for patients with advanced melanoma. Several OVs and therapeutic combinations are in development. Immunooncolytic virotherapy combined with immune checkpoint inhibitors is promising for the treatment of advanced melanoma.

Head and neck cell squamous-cell carcinomas (HNSCC) are a group of common cancers typically associated with tobacco use and human papilloma virus infection. Up to half of all cases will suffer a recurrence after primary treatment. As such, new therapies are needed, including therapies which promote the anti-tumor immune response. Prior work has characterized changes in the mutation burden between primary and recurrent tumors; however, little work has characterized the changes in neoantigen evolution. We characterized genomic and neoantigen changes between 23 paired primary and recurrent HNSCC tumors. Twenty-three biopsies from patients originally diagnosed with locally advanced disease were identified from the Washington University tumor bank. Whole exosome sequencing, RNA-seq, and immunohistochemistry was performed on the primary and recurrent tumors. Within these tumors, we identified 6 genes which have predicted neoantigens in 4 or more patients. Interestingly, patients with neoantigens in these shared genes had increased CD3+ CD8+ T cell infiltration and duration of survival with disease. Within HNSCC tumors examined here, there are neoantigens in shared genes by a subset of patients. The presence of neoantigens in these shared genes may promote an anti-tumor immune response which controls tumor progression.