Patient reported outcomes and patient experiences of immune checkpoint modulators for advanced or recurrent melanoma: a mixed methods study.

PURPOSE: Little is known about late and long-term patient-reported outcomes (PROs) of immune checkpoint modulators (ICMs) outside clinical trials. We conducted a cross-sectional, mixed-methods study to describe long-term PROs among advanced melanoma patients who began standard of care treatment with ICMs at least 1 year previously. METHODS: All participants completed the Functional Assessment of Cancer Therapy-Immune Checkpoint Modulator (FACT-ICM), assessing 46 immune-related side effects on a 5-point Likert scale, and a subset completed individual interviews. Descriptive statistics were computed for quantitative data and applied thematic analysis was used to examine qualitative data. RESULTS: Participants (N = 80) had a mean age of 67 years, and the majority were male (66%), non-Hispanic White (96%), and college graduates (61%). Single-agent nivolumab was the most common first (47%) and current/recent ICM (64%). On the FACT-ICM, 98% of participants reported at least one side effect, and 78% reported moderate or severe side effects. The most common moderate or severe side effects were aching joints (43%) and fatigue (38%). In interviews (n = 20), we identified five themes regarding patients' longer-term experiences after ICMs: lasting fatigue or decline in functioning, minimal side effects, manageable thyroid and pituitary dysfunction, skin conditions can be difficult to manage, and treating the cancer is worth the side effects. CONCLUSIONS: Nearly all patients reported side effects of ICMs at least 1 year after starting treatment. Our findings suggest that ICM side effect screening and management-especially for aching joints and fatigue-are indicated during long-term care of people living with advanced melanoma.

First-in-human stage III/IV melanoma​ clinical trial of immune priming agent IFx-Hu2.0.

IFx-Hu2.0 was designed to encode part of the Emm55 protein contained within a plasmid in a formulation intended for transfection into mammalian cells. IFx-Hu2.0 promotes both adaptive and innate immune responses in animal studies. Furthermore, previous studies have demonstrated safety/efficacy in equine, canine, and murine species. We present the first-in-human study of IFx-Hu2.0, administered by intralesional injection into melanoma tumors of seven patients with stage III/IV unresectable melanoma. No dose-limiting toxicities attributable to IFx-Hu2.0 were observed. Grade 1/2 injection site reactions were observed in five of seven patients. IgG and IgM responses were seen in the peripheral blood to Emm55 peptides and known melanoma antigens, suggesting that IFx-Hu2.0 acts as an individualized "in-situ vaccine." Three of four patients previously refractory to anti-PD1 experienced clinical benefit upon subsequent anti-PD1-based treatment. Therefore, this approach is feasible, and clinical/correlative outcomes warrant further investigation for treating metastatic melanoma patients as an immune priming agent.

Jagged2 targeting in lung cancer activates anti-tumor immunity via Notch-induced functional reprogramming of tumor-associated macrophages.

Signaling through Notch receptors intrinsically regulates tumor cell development and growth. Here, we studied the role of the Notch ligand Jagged2 on immune evasion in non-small cell lung cancer (NSCLC). Higher expression of JAG2 in NSCLC negatively correlated with survival. In NSCLC pre-clinical models, deletion of Jag2, but not Jag1, in cancer cells attenuated tumor growth and activated protective anti-tumor T cell responses. Jag2-/- lung tumors exhibited higher frequencies of macrophages that expressed immunostimulatory mediators and triggered T cell-dependent anti-tumor immunity. Mechanistically, Jag2 ablation promoted Nr4a-mediated induction of Notch ligands DLL1/4 on cancer cells. DLL1/4-initiated Notch1/2 signaling in macrophages induced the expression of transcription factor IRF4 and macrophage immunostimulatory functionality. IRF4 expression was required for the anti-tumor effects of Jag2 deletion in lung tumors. Antibody targeting of Jagged2 inhibited tumor growth and activated IRF4-driven macrophage-mediated anti-tumor immunity. Thus, Jagged2 orchestrates immunosuppressive systems in NSCLC that can be overcome to incite macrophage-mediated anti-tumor immunity.

Treatment of Stage III Resectable Melanoma-Adjuvant and Neoadjuvant Approaches.

ABSTRACT: Patients with stage III resectable melanoma carry a high risk of melanoma recurrence that ranges from approximately 40% to 90% at 5 years following surgical management alone. Postoperative systemic adjuvant therapy targets residual micrometastatic disease that could be the source of future recurrence and death from melanoma. Randomized phase III adjuvant trials reported significant improvements in overall survival with high-dose interferon α in 2 of 3 studies (compared with observation and GMK ganglioside vaccine) and with anti-cytotoxic T-lymphocyte antigen 4 ipilimumab at 10 mg/kg compared with placebo and ipilimumab 3 mg/kg compared with high-dose interferon α. In the modern era, more recent phase III trials demonstrated significant recurrence-free survival improvements with anti-programmed cell death protein 1, pembrolizumab, and BRAF-MEK inhibitor combination dabrafenib-trametinib (for BRAF mutant melanoma) versus placebo. Furthermore, anti-programmed cell death protein 1, nivolumab and pembrolizumab have both been shown to significantly improve recurrence-free survival as compared with ipilimumab 10 mg/kg. For melanoma patients with clinically or radiologically detectable locoregionally advanced disease, emerging data support an important role for preoperative systemic neoadjuvant therapy. Importantly, a recent cooperative group trial (S1801) reported superior event-free survival rates with neoadjuvant versus adjuvant therapy. Collectively, current data from neoadjuvant immunotherapy and targeted therapy trials support a future change in clinical practice in favor of neoadjuvant therapy for eligible melanoma patients.

Comparing the rate of immunotherapy treatment change due to toxicity by sex.

BACKGROUND: Immuno-oncology therapy (IO) is associated with a variety of treatment-related toxicities. However, the impact of toxicity on the treatment discontinuation rate between males and females is unknown. We hypothesized that immune-related adverse events would lead to more frequent treatment changes in females since autoimmune diseases occur more frequently in females. AIMS: Our aim was to determine if there was a difference in the rate of immunotherapy treatment change due to toxicity between males and females. METHODS AND RESULTS: The Oncology Research Information Exchange Network Avatar Database collected clinical data from 10 United States cancer centers. Of 1035 patients receiving IO, 447 were analyzed, excluding those who did not have documentation noting if a patient changed treatment (n = 573). Fifteen patients with unknown or gender-specific cancer were excluded. All cancer types and stages were included. The primary endpoint was documented treatment change due to toxicity. Four hundred and forty-seven patients (281 males and 166 females) received IO treatment. The most common cancers treated were kidney, skin, and lung for 99, 84, and 54 patients, respectively. Females had a shorter IO course than males (median 3.7 vs. 5.1 months, respectively, p = .02). Fifty-four patients changed treatment due to toxicity. There was no significant difference between females and males on chi-square test (11.4% vs. 12.5%, respectively, p = 0.75) and multivariable logistic regression (OR 0.924, 95% CI 0.453-1.885, p = .827). Significantly more patients with chronic obstructive pulmonary disease (COPD) changed therapy due to toxicity (OR 2.491, 95% CI 1.025-6.054, p = .044). CONCLUSION: Females received a shorter course of IO than males. However, there was no significant difference in the treatment discontinuation rate due to toxicity between males and females receiving IO. Toxicity-related treatment change was associated with COPD.

A Bioinformatics Tool for Identifying Intratumoral Microbes from the ORIEN Dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10%-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, microbial graph attention (MEGA), to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of nine cancer centers in the Oncology Research Information Exchange Network. This package has three unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2,704 tumor RNA sequencing samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors. SIGNIFICANCE: Studying the tumor microbiome in high-throughput sequencing data is challenging because of the extremely sparse data matrices, heterogeneity, and high likelihood of contamination. We present a new deep learning tool, MEGA, to refine the organisms that interact with tumors.

The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors.

BACKGROUND: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. METHODS: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan-Meier curves. The OS predictions were assessed using Harrell's concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. RESULTS: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate-high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. CONCLUSIONS: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Translation of AI into oncology clinical practice.

Artificial intelligence (AI) is a transformative technology that is capturing popular imagination and can revolutionize biomedicine. AI and machine learning (ML) algorithms have the potential to break through existing barriers in oncology research and practice such as automating workflow processes, personalizing care, and reducing healthcare disparities. Emerging applications of AI/ML in the literature include screening and early detection of cancer, disease diagnosis, response prediction, prognosis, and accelerated drug discovery. Despite this excitement, only few AI/ML models have been properly validated and fewer have become regulated products for routine clinical use. In this review, we highlight the main challenges impeding AI/ML clinical translation. We present different clinical use cases from the domains of radiology, radiation oncology, immunotherapy, and drug discovery in oncology. We dissect the unique challenges and opportunities associated with each of these cases. Finally, we summarize the general requirements for successful AI/ML implementation in the clinic, highlighting specific examples and points of emphasis including the importance of multidisciplinary collaboration of stakeholders, role of domain experts in AI augmentation, transparency of AI/ML models, and the establishment of a comprehensive quality assurance program to mitigate risks of training bias and data drifts, all culminating toward safer and more beneficial AI/ML applications in oncology labs and clinics.

Adjuvant Therapy for High-Risk Melanoma: An In-Depth Examination of the State of the Field.

The consideration of systemic adjuvant therapy is recommended for patients with stage IIB-IV melanoma who have undergone surgical resection due to a heightened risk of experiencing melanoma relapse and mortality from melanoma. Adjuvant therapy options tested over the past three decades include high-dose interferon-α, immune checkpoint inhibitors (pembrolizumab, nivolumab), targeted therapy (dabrafenib-trametinib for BRAF mutant melanoma), radiotherapy and chemotherapy. Most of these therapies have been demonstrated to enhance relapse-free survival (RFS) but with limited to no impact on overall survival (OS), as reported in randomized trials. In contemporary clinical practice, the adjuvant treatment approach for surgically resected stage III-IV melanoma has undergone a notable shift towards the utilization of nivolumab, pembrolizumab, and BRAF-MEK inhibitors, such as dabrafenib plus trametinib (specifically for BRAF mutant melanoma) due to the significant enhancements in RFS observed with these treatments. Pembrolizumab has obtained regulatory approval in the United States to treat resected stage IIB-IIC melanoma, while nivolumab is currently under review for the same indication. This review comprehensively analyzes completed phase III adjuvant therapy trials in adjuvant therapy. Additionally, it provides a summary of ongoing trials and an overview of the main challenges and future directions with adjuvant therapy.

Clinical updates in neoadjuvant immunotherapy for melanoma before surgery.

INTRODUCTION: Locoregionally advanced melanoma represents a large group of high-risk melanoma patients at presentation and poses major challenges in relation to management and the risks of relapse and death. AREAS COVERED: Melanoma systemic therapy has undergone substantial advancements with the advent of immune checkpoint inhibitors and molecularly targeted therapies, which have been translated to the neoadjuvant setting for the management of locoregionally advanced disease. Notably, PD1 blockade as monotherapy, in combination with CTLA4 blockade or LAG3 inhibition, has demonstrated significant progress in reducing the risk of relapse and mortality, attributed to high pathologic response rates. Likewise, BRAF-MEK inhibition for BRAF mutant melanoma has yielded comparable outcomes, albeit with lower response durability than immunotherapy. Localized intralesional therapies such as Talimogene laherparepvec (T-VEC) and Tavokinogene Telseplasmid (TAVO) electro-gene-transfer combined with anti-PD1 have demonstrated favorable pathologic responses and increased immune activation. Most importantly, the S1801 randomized trial has demonstrated for the first time the advantage of the neoadjuvant approach over standard surgery followed by adjuvant therapy. EXPERT OPINION: Current evidence supports neoadjuvant therapy as a standard of care for locoregionally advanced melanoma. Ongoing research will define the optimal regimens and the biomarkers of therapeutic predictive and prognostic value.

Cetuximab for Immunotherapy-Refractory/Ineligible Cutaneous Squamous Cell Carcinoma.

Anti-PD1 therapy demonstrated impressive, prolonged responses in advanced cutaneous squamous cell carcinoma (CSCC). Therapy for ICI-refractory/ineligible disease remains unclear. We performed a retrospective analysis in locally-advanced/metastatic CSCC using cetuximab across three cohorts: immediately after ICI failure (A), not immediately following ICI failure (B), or without prior ICI (C). The primary endpoint was the overall response rate (ORR). Secondary endpoints included disease-control rate (DCR), progression-free survival (PFS), overall survival (OS), time-to-response (TTR) and toxicity. Twenty-three patients were included. In cohort A (n = 11), the ORR was 64% and DCR was 91%, with six ongoing responses at data cutoff. In cohort B (n = 2), all patients had progression as the best response. At a median follow-up of 21 months for A and B, TTR and PFS were 2.0 and 17.3 months, respectively. The median OS was not reached. In cohort C (n = 10), the ORR and DCR were 80%, including five ongoing responses at the data cutoff. At a median follow-up of 22.4 months, the TTR, PFS and OS were 2.5, 7.3 and 23.1 months, respectively. Cetuximab was well tolerated in all cohorts. In summary, cetuximab is effective in patients with failure/contraindications to ICI. Cetuximab immediately after ICI failure yielded particularly fast, durable responses. If confirmed, this could be the preferred therapy following ICI failure.

The tumor microbiome as a predictor of outcomes in patients with metastatic melanoma treated with immune checkpoint inhibitors.

Emerging evidence supports the important role of the tumor microbiome in oncogenesis, cancer immune phenotype, cancer progression, and treatment outcomes in many malignancies. In this study, we investigated the metastatic melanoma tumor microbiome and potential roles in association with clinical outcomes, such as survival, in patients with metastatic disease treated with immune checkpoint inhibitors (ICIs). Baseline tumor samples were collected from 71 patients with metastatic melanoma before treatment with ICIs. Bulk RNA-seq was conducted on the formalin-fixed paraffin-embedded (FFPE) tumor samples. Durable clinical benefit (primary clinical endpoint) following ICIs was defined as overall survival ≥24 months and no change to the primary drug regimen (responders). We processed RNA-seq reads to carefully identify exogenous sequences using the {exotic} tool. The 71 patients with metastatic melanoma ranged in age from 24 to 83 years, 59% were male, and 55% survived >24 months following the initiation of ICI treatment. Exogenous taxa were identified in the tumor RNA-seq, including bacteria, fungi, and viruses. We found differences in gene expression and microbe abundances in immunotherapy responsive versus non-responsive tumors. Responders showed significant enrichment of several microbes including Fusobacterium nucleatum, and non-responders showed enrichment of fungi, as well as several bacteria. These microbes correlated with immune-related gene expression signatures. Finally, we found that models for predicting prolonged survival with immunotherapy using both microbe abundances and gene expression outperformed models using either dataset alone. Our findings warrant further investigation and potentially support therapeutic strategies to modify the tumor microbiome in order to improve treatment outcomes with ICIs.

A bioinformatics tool for identifying intratumoral microbes from the ORIEN dataset.

Evidence supports significant interactions among microbes, immune cells, and tumor cells in at least 10-20% of human cancers, emphasizing the importance of further investigating these complex relationships. However, the implications and significance of tumor-related microbes remain largely unknown. Studies have demonstrated the critical roles of host microbes in cancer prevention and treatment responses. Understanding interactions between host microbes and cancer can drive cancer diagnosis and microbial therapeutics (bugs as drugs). Computational identification of cancer-specific microbes and their associations is still challenging due to the high dimensionality and high sparsity of intratumoral microbiome data, which requires large datasets containing sufficient event observations to identify relationships, and the interactions within microbial communities, the heterogeneity in microbial composition, and other confounding effects that can lead to spurious associations. To solve these issues, we present a bioinformatics tool, MEGA, to identify the microbes most strongly associated with 12 cancer types. We demonstrate its utility on a dataset from a consortium of 9 cancer centers in the Oncology Research Information Exchange Network (ORIEN). This package has 3 unique features: species-sample relations are represented in a heterogeneous graph and learned by a graph attention network; it incorporates metabolic and phylogenetic information to reflect intricate relationships within microbial communities; and it provides multiple functionalities for association interpretations and visualizations. We analyzed 2704 tumor RNA-seq samples and MEGA interpreted the tissue-resident microbial signatures of each of 12 cancer types. MEGA can effectively identify cancer-associated microbial signatures and refine their interactions with tumors.

A Tumor and Immune-Related Micro-RNA Signature Predicts Relapse-Free Survival of Melanoma Patients Treated with Ipilimumab.

Despite the unprecedented advances in the treatment of melanoma with immunotherapy, there continues to be a major need for biomarkers of clinical benefits and immune resistance associated with immune checkpoint inhibitors; microRNA could play a vital role in these efforts. This study planned to identify differentially expressed miRNA molecules that may have prognostic value for clinical benefits. Patients with surgically operable regionally advanced melanoma were treated with neoadjuvant ipilimumab (10 mg/kg intravenously every 3 weeks × two doses) bracketing surgery. Tumor biospecimens were obtained at baseline and surgery, and microRNA (miRNA) expression profiling was performed on the tumor biopsies. We found that an expression profile consisting of a 4-miRNA signature was significantly associated with improved relapse-free survival (RFS). The signature consisted of biologically relevant molecules previously reported to have prognostic value in melanoma and other malignancies, including miR-34c, miR-711, miR-641, and miR-22. Functional annotation analysis of target genes for the 4-miRNA signature was significantly enriched for various cancer-related pathways, including cell proliferation regulation, apoptosis, the MAPK signaling pathway, and the positive regulation of T cell activation. Our results presented miRNAs as potential biomarkers that can guide the treatment of melanoma with immune checkpoint inhibitors. These findings warrant further investigation in relation to CTLA4 blockade and other immune checkpoint inhibitors. ClinicalTrials.gov NCT00972933.

Granulomatous and Sarcoid-like Immune-Related Adverse Events following CTLA4 and PD1 Blockade Adjuvant Therapy of Melanoma: A Combined Analysis of ECOG-ACRIN E1609 and SWOG S1404 Phase III Trials and a Literature Review.

BACKGROUND: Treatment with immune checkpoint inhibitors (ICIs) has been linked to granulomatous and sarcoid-like lesions (GSLs) affecting different organs. This study sought to evaluate GSL incidence in patients with high-risk melanoma treated with cytotoxic T-lymphocyte antigen 4 (CTLA4) or programmed cell death 1 (PD1) blockade adjuvant therapy in two clinical trials: ECOG-ACRIN E1609 and SWOG S1404. Descriptions and GSL severity ratings were recorded. METHODS: Data were collected from ECOG-ACRIN E1609 and SWOG S1404. Descriptive statistics along with GSL severity grades were reported. Additionally, a literature review for such cases was summarized. RESULTS: A total of 11 GSL cases were reported among 2878 patients treated with either ICI or with High-Dose Interferon Alfa-2b (HDI) in ECOG-ACRIN E1609 and SWOG S1404 trials. Cases were numerically more commonly reported with ipi10, followed by pembrolizumab, ipi3, and HDI, respectively. Most of the cases were grade III. Further, organs involved included lung, mediastinal lymph nodes, skin and subcutaneous tissue, and eye. Furthermore, a summary of 62 reports in the literature was described. CONCLUSIONS: GSLs following anti-CTLA4 and anti-PD1 antibody therapy in patients with melanoma were reported unusually. Reported cases ranged in grade from I to III and appeared manageable. Careful attention to these events and their reporting will be essential to better guide practice and management guidelines.

Circulating tumor DNA-based molecular residual disease detection for treatment monitoring in advanced melanoma patients.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have substantially improved overall survival in patients with advanced melanoma; however, the lack of biomarkers to monitor treatment response and relapse remains an important clinical challenge. Thus, a reliable biomarker is needed that can risk-stratify patients for disease recurrence and predict response to treatment. METHODS: A retrospective analysis using a personalized, tumor-informed circulating tumor DNA (ctDNA) assay on prospectively collected plasma samples (n = 555) from 69 patients with advanced melanoma was performed. Patients were divided into three cohorts: cohort A (N = 30), stage III patients receiving adjuvant ICI/observation; cohort B (N = 29), unresectable stage III/IV patients receiving ICI therapy; and cohort C (N = 10), stage III/IV patients on surveillance after planned completion of ICI therapy for metastatic disease. RESULTS: In cohort A, compared to molecular residual disease (MRD)-negative patients, MRD-positivity was associated with significantly shorter distant metastasis-free survival (DMFS; hazard ratio [HR], 10.77; p = .01). Increasing ctDNA levels from the post-surgical or pre-treatment time point to after 6 weeks of ICI were predictive of shorter DMFS in cohort A (HR, 34.54; p < .0001) and shorter progression-free survival (PFS) in cohort B (HR, 22; p = .006). In cohort C, all ctDNA-negative patients remained progression-free for a median follow-up of 14.67 months, whereas ctDNA-positive patients experienced disease progression. CONCLUSION: Personalized and tumor-informed longitudinal ctDNA monitoring is a valuable prognostic and predictive tool that may be used throughout the clinical course of patients with advanced melanoma.

Leptomeningeal Disease (LMD) in Patients with Melanoma Metastases.

Leptomeningeal disease (LMD) is a devastating complication caused by seeding malignant cells to the cerebrospinal fluid (CSF) and the leptomeningeal membrane. LMD is diagnosed in 5-15% of patients with systemic malignancy. Management of LMD is challenging due to the biological and metabolic tumor microenvironment of LMD being largely unknown. Patients with LMD can present with a wide variety of signs and/or symptoms that could be multifocal and include headache, nausea, vomiting, diplopia, and weakness, among others. The median survival time for patients with LMD is measured in weeks and up to 3-6 months with aggressive management, and death usually occurs due to progressive neurologic dysfunction. In melanoma, LMD is associated with a suppressive immune microenvironment characterized by a high number of apoptotic and exhausted CD4+ T-cells, myeloid-derived suppressor cells, and a low number of CD8+ T-cells. Proteomics analysis revealed enrichment of complement cascade, which may disrupt the blood-CSF barrier. Clinical management of melanoma LMD consists primarily of radiation therapy, BRAF/MEK inhibitors as targeted therapy, and immunotherapy with anti-PD-1, anti-CTLA-4, and anti-LAG-3 immune checkpoint inhibitors. This review summarizes the biology and anatomic features of melanoma LMD, as well as the current therapeutic approaches.

Neoadjuvant Therapy in Melanoma: Where Are We Now?

PURPOSEOF REVIEW: This review summarizes the current state of neoadjuvant immunotherapy and targeted therapy for locoregionally advanced melanoma. RECENT FINDINGS: Melanoma systemic therapy has witnessed major advances with the development of immune checkpoint inhibitors and molecularly targeted therapy that have been translated into the neoadjuvant setting in managing locoregionally advanced disease. PD1 blockade as monotherapy and combined with CTLA4 blockade or LAG3 inhibition has demonstrated major improvements in reducing the risk of relapse and death that were associated with high pathologic response rates. Similar results were reported with BRAF-MEK inhibition for BRAF mutant melanoma with high pathologic response rates that appear to be less durable compared to immunotherapy. More importantly, in a recent randomized trial, event-free survival was significantly improved with neoadjuvant pembrolizumab compared to standard surgery and adjuvant therapy. Neoadjuvant therapy has become the standard of care for locoregionally advanced melanoma. Ongoing studies will define the most optimal combination regimens.

Systematic evaluation of the predictive gene expression signatures of immune checkpoint inhibitors in metastatic melanoma.

Advances in immunotherapy, including immune checkpoint inhibitors (ICIs), have transformed the standard of care for many types of cancer including melanoma. ICIs have improved the overall outcome of melanoma patients; however, a significant proportion of patients suffer from primary or secondary tumor resistance. Therefore, there is an urgent need to develop predictive biomarkers to better select patients for ICI therapy. Numerous biomarkers that predict the response of melanoma to ICIs have been investigated, including biomarker signatures based on genomics or transcriptomics. Most of these predictive biomarkers have not been systematically evaluated across different cohorts to determine the reproducibility of these signatures in metastatic melanoma. We evaluated 28 previously published predictive biomarkers of ICIs based on gene expression signatures in eight previously published studies with available RNA-sequencing data in public repositories. We found that signatures related to IFN-γ-responsive genes, T and B cell markers, and chemokines in the tumor immune microenvironment are generally predictive of response to ICIs in these patients. In addition, we identified that these predictive biomarkers have higher predictive values in on-treatment samples as compared to pretreatment samples in metastatic melanoma. The most frequently overlapping genes among the top 18 predictive signatures were CXCL10, CXCL9, PRF1, RANTES, IFNG, HLA-DRA, GZMB, and CD8A. From gene set enrichment analysis and cell type deconvolution, we estimated that the tumors of responders were enriched with infiltrating cytotoxic T-cells and other immune cells and the upregulation of genes related to interferon-γ signaling. Conversely, the tumors of non-responders were enriched with stromal-related cell types such as fibroblasts and myofibroblasts, as well as enrichment with T helper 17 cell types across all cohorts. In summary, our approach of validating and integrating multi-omics data can help guide future biomarker development in the field of ICIs and serve the quest for a more personalized therapeutic approach for melanoma patients.

Patient-reported tolerability of adjuvant ipilimumab (3 or 10 mg/kg) versus high-dose interferon alfa-2b for resected high-risk stage III-IV melanoma in phase III trial E1609.

PURPOSE: Trial E1609 demonstrated superior overall survival with ipilimumab 3 mg/kg (ipi3) compared to high-dose interferon (HDI) for patients with resected high-risk melanoma. To inform treatment tolerability, we compared health-related quality of life (HRQoL), gastrointestinal (GI), and treatment-specific physical and cognitive/emotional symptoms. We also compared treatment-specific concerns between all arms. METHODS: We assessed HRQoL using the Functional Assessment of Cancer Therapy-General, physical and cognitive/emotional concerns using the FACT-Biologic Response Modifier subscale, and GI symptoms with the Functional Assessment of Chronic Illness Therapy-Diarrhea subscale pre-treatment and every 3 months. The primary outcome was the difference in HRQoL at 3 months between ipi3/ipi10 vs. HDI. RESULTS: 549 patients (n = 158 ipi3; n = 191 ipi10; n = 200 HDI) were analyzed. 3-month completion was 58.7%. Compared to HDI, ipilimumab patients reported better HRQoL (ipi3 = 87.5 ± 14.6 vs. HDI = 74.7 ± 15.4, p < .001; ipi10 = 84.9 ± 16.5 vs. HDI, p < .001) and fewer physical (ipi3 = 22.3 ± 4.6 vs. HDI = 17.1 ± 5.4, p < .001; ipi10 = 21.8 ± 5.0 vs. HDI p < .001) and cognitive/emotional (ipi3 = 18.6 ± 4.4 vs. HDI = 15.0 ± 5.3, p < .001; ipi10 = 17.7 ± 4.8 vs. HDI p < .001) concerns, but worse GI symptoms (ipi3 = 40.8 ± 5.0 vs. HDI = 42.2 ± 2.9, p = .011; ipi10 = 39.5 ± 7.0 vs. HDI, p < .001). Fewer ipilimumab patients reported worsening treatment-specific concerns (e.g., 52% of ipi3 and 58% of ipi10 reported worsening fatigue vs. 82% HDI, p's < .001). CONCLUSION: PROs demonstrated less toxicity of ipi3 compared to HDI and ipi10. Priorities for symptom management among patients receiving ipilimumab include GI toxicities, fatigue, weakness, appetite loss, arthralgia, and depression. TRIAL REGISTRATION: NCT01274338, January 11, 2011 (first posted date) https://clinicaltrials.gov/ct2/show/NCT01274338?term=NCT01274338&draw=2&rank=1 .