Protein expression of the gp78 E3 ligase predicts poor breast cancer outcome based on race.

Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER- tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.

A Phase I Study of the Combination of Pexidartinib and Sirolimus to Target Tumor-Associated Macrophages in Unresectable Sarcoma and Malignant Peripheral Nerve Sheath Tumors.

PURPOSE: To evaluate the safety and tolerability in phase I first-in-human combination therapy with pexidartinib, an inhibitor of colony-stimulating factor-1 receptor, and sirolimus, an mTOR inhibitor, to target tumor-associated macrophage (TAM) polarization in soft tissue sarcomas (STS). PATIENTS AND METHODS: This multicenter phase I study used the time-to-event continual reassessment method (TITE-CRM) to study the combination of sirolimus, doses ranging from 2 to 6 mg, with pexidartinib, doses ranging from 600 to 1,000 mg, both provided continuously on a 28-day cycle, in patients with advanced sarcoma. A total of 24 patients [8 malignant peripheral nerve sheath tumor, 3 tenosynovial giant cell tumor (TGCT), 5 leiomyosarcoma, and 8 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 II dose was 2 mg of sirolimus combined with 1,000 mg of pexidartinib daily. Of the 18 evaluable subjects, 5 experienced dose-limiting toxicities (2 elevated aspartate aminotransferase/alanine aminotransferase, 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 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.

Genomic and neoantigen evolution from primary tumor to first metastases in head and neck squamous cell carcinoma.

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.

Transcriptomic analysis identifies differences in gene expression in actinic keratoses after treatment with imiquimod and between responders and non responders.

The presence of actinic keratoses (AKs) increases a patient's risk of developing squamous cell carcinoma by greater than six-fold. We evaluated the effect of topical treatment with imiquimod on the tumor microenvironment by measuring transcriptomic differences in AKs before and after treatment with imiquimod 3.75%. Biopsies were collected prospectively from 21 patients and examined histologically. RNA was extracted and transcriptomic analyses of 788 genes were performed using the nanoString assay. Imiquimod decreased number of AKs by study endpoint at week 14 (p < 0.0001). Post-imiquimod therapy, levels of CDK1, CXCL13, IL1B, GADPH, TTK, ILF3, EWSR1, BIRC5, PLAUR, ISG20, and C1QBP were significantly lower (adjusted p < 0.05). Complete responders (CR) exhibited a distinct pattern of inflammatory gene expression pre-treatment relative to incomplete responders (IR), with alterations in 15 inflammatory pathways (p < 0.05) reflecting differential expression of 103 genes (p < 0.05). Presence of adverse effects was associated with improved treatment response. Differences in gene expression were found between pre-treatment samples in CR versus IR, suggesting that higher levels of inflammation pre-treament may play a part in regression of AKs. Further characterization of the immune micro-environment in AKs may help develop biomarkers predictive of response to topical immune modulators and may guide therapy.

Distinguishing melanophages from tumor in melanoma patients treated with talimogene laherparepvec.

Response to talimogene laherparepvec (T-Vec) is difficult to assess as pigmented macrophages that have ingested melanoma cells ('melanophages') persist after injection, mimicking melanoma. We used quantitative immunofluorescence (qIF) to (1) distinguish melanophages from melanoma in biopsies from two patients treated with T-Vec and (2) evaluate the tumor microenvironment pretreatment and posttreatment. Tissues were stained with 4',6-diamidino-2-phenylindole, cluster of differentiation (CD) 3, CD8, CD68, human leukocyte antigen-DR isotype (HLA-DR), and SRY-Box Transcription Factor 10 (SOX10), and multispectral images were analyzed. Post-T-Vec samples showed melanophages with cytoplasmic costaining of CD68, SOX10, and HLA-DR, without nuclear SOX10 expression. qIF revealed a dense immune infiltrate of CD3, CD8, and CD68 cells in post-T-Vec samples. Melanophages from tumors post-T-Vec stain the nuclear melanoma marker SOX10 in their cytoplasms as compared to melanoma cells that stain nuclear SOX10. This novel finding highlights the phagocytosis of melanoma cell components by macrophages after treatment with T-Vec. qIF may assist pathologists in determining whether lesions treated with immunotherapy contain residual viable melanoma.

Deep Learning Based on Standard H&E Images of Primary Melanoma Tumors Identifies Patients at Risk for Visceral Recurrence and Death.

PURPOSE: Biomarkers for disease-specific survival (DSS) in early-stage 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.

An open source automated tumor infiltrating lymphocyte algorithm for prognosis in melanoma.

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.

Correction to: The Role of Oncolytic Viruses in the Treatment of Melanoma.

A correction was made to a sentence in the original article to provide additional clarification in the "Other Oncolytic Viruses" section.

The Role of Oncolytic Viruses in the Treatment of Melanoma.

PURPOSE OF REVIEW: Oncolytic virotherapy is a new approach to the treatment of cancer and its success in the treatment of melanoma represents a breakthrough in cancer therapeutics. This paper provides a review of the current literature on the use of oncolytic viruses (OVs) in the treatment of melanoma. RECENT FINDINGS: 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.