Faculty Bibliography

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.

Nearly 10% of patients with high-risk early-stage melanoma will develop satellite or in-transit metastases (ITM), classified as stage III disease similar to lymph node metastases. The pivotal registration trials of the CTLA-4 antibody ipilimumab, and the PD-1 antibodies nivolumab and pembrolizumab, also included patients with unresectable stage III disease. However, there has been no analysis of patients with ITM, and anecdotal retrospective small series have indicated a potential lesser effect. This study aimed to identify patients with unresectable ITM within the randomized trials, and to determine response, progression-free survival and overall survival. The pivotal phase III randomized intervention trials that included melanoma patients with ITM, with or without nodal metastasis, and were treated with ipilimumab, nivolumab or pembrolizumab was identified. The datasets from each trial were then searched to identify the specific details of the investigated patient population for a pooled analysis. The primary endpoint was complete response rate. Seven trials that included stage III patients, and with accessible datasets, were identified. There was a total of 4711 patients, however, no patients with ITM could be identified, as this data was not captured by the case report forms. Evidence from prospective clinical trials on the use of immunotherapy in patients with ITM is lacking. We recommend pooling data from multiple institutions to examine efficacy of available drug therapies in this patient population, but more importantly, prospective clinical trials of locoregional treatments with or without systemic drug therapies are required.

BACKGROUND:Tumor mutation burden (TMB) has been associated with melanoma immunotherapy (IT) outcomes, including survival. We explored whether combining TMB with immunogenomic signatures recently identified by The Cancer Genome Atlas (TCGA) can refine melanoma prognostic models of overall survival (OS) in patients not treated by IT. METHODS:Cox proportional-hazards (Cox PH) analysis was performed on 278 metastatic melanomas from TCGA not treated by IT. In a discovery and two validation cohorts Cox PH models assessed the interaction between TMB and 53 melanoma immunogenomic features to refine prediction of melanoma OS. RESULTS:Interferon-γ response (IFNγRes) and macrophage regulation gene signatures (MacReg) combined with TMB significantly associated with OS (p = 8.80E-14). We observed that patients with high TMB, high IFNγRes and high MacReg had significantly better OS compared to high TMB, low IFNγRes and low MacReg (HR = 2.8, p = 3.55E-08). This association was not observed in low TMB patients. CONCLUSIONS:We report a model combining TMB and tumor immune features that significantly improves prediction of melanoma OS, independent of IT. Our analysis revealed that patients with high TMB, high levels of IFNγRes and MacReg had significantly more favorable OS compared to high TMB patients with low IFNγRes and low MacReg. These findings may substantially improve current melanoma prognostic models.

PURPOSE/OBJECTIVE:Several biomarkers of response to immune checkpoint inhibitors (ICI) show potential but are not yet scalable to the clinic. We developed a pipeline that integrates deep learning on histology specimens with clinical data to predict ICI response in advanced melanoma. EXPERIMENTAL DESIGN/METHODS:We used a training cohort from New York University (New York, NY) and a validation cohort from Vanderbilt University (Nashville, TN). We built a multivariable classifier that integrates neural network predictions with clinical data. A ROC curve was generated and the optimal threshold was used to stratify patients as high versus low risk for progression. Kaplan-Meier curves compared progression-free survival (PFS) between the groups. The classifier was validated on two slide scanners (Aperio AT2 and Leica SCN400). RESULTS:= 0.03 for the Leica SCN400). CONCLUSIONS:Histology slides and patients' clinicodemographic characteristics are readily available through standard of care and have the potential to predict ICI treatment outcomes. With prospective validation, we believe our approach has potential for integration into clinical practice.

INTRODUCTION/BACKGROUND:Immune checkpoint inhibitors (ICIs) are increasingly used to treat advanced cancer. Rheumatoid arthritis (RA) is associated with an increased risk of malignancies; however, patients with RA have been excluded from ICI trials. In this study, we evaluated risk of toxicity after initiation of ICI treatment in RA patients. METHODS:We conducted a single-institution, medical records review analysis to assess the incidence of immune-related adverse events (irAEs) and autoimmune disease (AID) flares among patients with AIDs treated with ICIs from 2011 to 2018. A subgroup analysis for RA patients was performed with frequencies of irAEs and AID flares reported. RESULTS:Twenty-two patients with RA who were treated with ICI for malignancy were identified. At the time of ICI initiation, 86% had inactive RA disease activity. Immune-related adverse events occurred in 7 (32%) of patients, with 2 (9%) developing grade 3 (i.e., severe) irAEs. Immune checkpoint inhibitors were temporarily discontinued because of irAEs in 5 patients (23%), and permanently in 1 patient. Rheumatoid arthritis flares occurred in 12 patients (55%). Of those, 10 (83%) received oral corticosteroids with an adequate treatment response. CONCLUSIONS:Our analysis suggests that irAEs following ICI treatment are not increased among RA patients compared with other cancer patients. Heightened RA disease activity during ICI treatment is common, but most adverse events are manageable with oral corticosteroids, and few require permanent ICI discontinuation. A close collaboration between the oncologist and rheumatologist is advisable when considering ICIs in patients with RA.

Introduction/UNASSIGNED:Most diseases involve a complex interplay between multiple biological processes at the cellular, tissue, organ, and systemic levels. Clinical tests and biomarkers based on the measurement of a single or few analytes may not be able to capture the complexity of a patient's disease. Novel approaches for comprehensively assessing biological processes from easily obtained samples could help in the monitoring, treatment, and understanding of many conditions. Objectives/UNASSIGNED:We propose a method of creating scores associated with specific biological processes from mass spectral analysis of serum samples. Methods/UNASSIGNED:A score for a process of interest is created by: (i) identifying mass spectral features associated with the process using set enrichment analysis methods, and (ii) combining these features into a score using a principal component analysis-based approach. We investigate the creation of scores using cohorts of patients with non-small cell lung cancer, melanoma, and ovarian cancer. Since the circulating proteome is amenable to the study of immune responses, which play a critical role in cancer development and progression, we focus on functions related to the host response to disease. Results/UNASSIGNED:We demonstrate the feasibility of generating scores, their reproducibility, and their associations with clinical outcomes. Once the scores are constructed, only 3 µL of serum is required for the assessment of multiple biological functions from the circulating proteome. Conclusion/UNASSIGNED:These mass spectrometry-based scores could be useful for future multivariate biomarker or test development studies for informing treatment, disease monitoring and improving understanding of the roles of various biological functions in multiple disease settings.

Background Several studies suggest the gut microbiome may be a novel, modifiable biomarker for clinical efficacy of immune checkpoint inhibitors (ICIs). Microbiome profiling of pre-treatment samples demonstrated that high alpha-diversity and enrichment of specific bacterial species are associated with improved tumor responses in melanoma, renal cell cancer (RCC), and non-small cell lung cancer (NSCLC). Despite these reports, the specific bacteria or communities helpful or harmful have been inconsistent across study populations, and further correlation with immune and mutational biomarkers are limited or lacking. We hypothesize that, by use of a larger sample size and a consistent computational approach, we would derive a clearer microbial profile that correlated with immunotherapeutic outcomes. Methods We re-analyzed the available raw 16S rRNA amplicon and metagenomic sequencing data across five recently published ICI studies (n=303 unique patients) of responder (R) and nonresponse (NR) using a consistent computational approaches (Resphera Insight and MetaPhlAn2). Using novel microbiota signatures, we identified Re-analysis Indices for Rand NR-associated bacteria and validated the result in three addition cohorts with available raw sequencing data in patients with melanoma, hepatocellular cancer (HCC), and NSCLC (n=105). Results Our results confirm signals reported in each study, though some bacteria reported initially were not statistically significant after correction for false discovery rate. Likely, in part, because our analysis allows for comparison of individual species across cohorts, we were able to identify new bacterial signatures, such as Oxalobacter formigenes, Roseburia hominis and Veillonella parvula, Clostridium hathewayi, enriched in R and NR respectively. When our Re-analysis Index was compared to an index assembled from the literature, we noted improvement occurred in a sensitivity and specificity analysis, especially in NR-associated signals. Moreover, we found that alpha-diversity was not consistently predictive of response or nonresponse to ICIs. Our Re-analysis Index also validated in melanoma patients and HCC but did not perform as well in the NSCLC cohort, suggesting the need for further refinement based on tumor type. Conclusions In summary, this bioinformatics platform improves on existing pipelines by standardizing critical preprocessing and downstream analysis tools, enabling comprehensive evaluations of taxonomic and functional signals across sequencing datasets. Notably, the NR-associated Re-analysis Index shows the strongest and most consistent signal using a random effects model and in a sensitivity and specificity analysis (p < 0.01). Our integrated analyses suggest an approach to identify patients who would benefit from microbiome-based interventions targeted to improve response rates by using a biomarker for nonresponse

OBJECTIVE:Long-term safety of pembrolizumab in melanoma was analyzed in KEYNOTE-001, KEYNOTE-002, and KEYNOTE-006. PATIENTS AND METHODS/METHODS:Analysis involved patients who received ≥1 pembrolizumab dose. Lead-time bias was addressed via landmark analyses in patients who were progression-free before day 147. RESULTS:Adverse events (AEs) were analyzed for 1567 patients (median follow-up, 42.4 months). Most AEs were mild/moderate; grade 3/4 treatment-related AEs occurred in 17.7% of patients. Two pembrolizumab-related deaths occurred. Any-grade immune-mediated AEs (imAEs) occurred in 23.0%, most commonly hypothyroidism (9.1%), pneumonitis (3.3%), and hyperthyroidism (3.0%); grade 3/4 imAEs occurred in 6.9% of patients. Most imAEs occurred within 16 weeks of treatment. In landmark analysis, patients who did (n = 79) versus did not (n = 384) develop imAEs had similar objective response rates (ORRs) (64.6% versus 63.0%); median time to response (TTR), 5.6 months for both; median duration of response (DOR), 20.0 versus 25.3 months; median progression-free survival (PFS), 17.0 versus 17.7 months; median overall survival (OS), not reached (NR) versus 43 months (p = 0.1104). Patients who did (n = 17) versus did not (n = 62) receive systemic corticosteroids had similar ORRs (70.6% vs. 62.9%) and median TTR (6.4 vs. 5.6 months) but numerically shorter median PFS (9.9 vs. 17.0 months); median DOR, 14.2 months versus NR; median OS, NR for both. CONCLUSIONS:These results enhance the knowledge base for pembrolizumab in advanced melanoma, with no new toxicity signals after lengthy follow-up of a large population. In landmark analyses, pembrolizumab efficacy was similar regardless of imAEs or systemic corticosteroid use. CLINICAL TRIAL REGISTRY/UNASSIGNED:NCT01295827, NCT01704287, NCT01866319.