CGPA: multi-context insights from the cancer gene prognosis atlas.

Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes. Recognizing the complexity of revealing multifaceted prognostic implications, especially when extending the analysis to include various covariates and thresholds, we present the Cancer Gene Prognosis Atlas (CGPA). This platform greatly enhances gene-centric biomarker research across cancer types by offering an interactive and user-friendly interface for highly customized, in-depth prognostic analysis. CGPA notably supports data-driven exploration of gene pairs and gene-hallmark relationships, elucidating key composite biological mechanisms like synthetic lethality and immunosuppression. It further expands its capabilities to assess multi-gene panels using both public and user-provided data, facilitating a seamless mechanism-to-machine analysis. Additionally, CGPA features a designated portal for discovering prognostic gene modules using curated cancer immunotherapy data. Ultimately, CGPA's comprehensive, accessible tools allow cancer researchers, including those without statistical expertise, to precisely investigate the prognostic landscape of genes, customizing the model to fit specific research hypotheses and enhancing biomarker discovery and validation through a synergy of mechanistic and data-driven strategies.

A pan-cancer gamma delta T cell repertoire.

This report presents the largest collection of gamma-delta T cell receptor (γδ TCR) reads in human cancer to date, analyzing about 11,000 patient tumor samples across 33 cancer types using the TRUST4 algorithm. Despite γδ T cells being a small fraction of the T cell population, they play a key role in both innate and adaptive immunity. Our comprehensive analysis reveals their significant presence across all cancer types, specifically highlighting the diverse spectrum and clonality patterns of their γδ receptors. This research highlights the complex roles of γδ T cells in tumor tissues and their potential as prognostic biomarkers. We also demonstrate the utility of T cell receptor gamma (TRG) and delta (TRD) gene expression values from standard RNA-seq data. Ultimately, our work establishes a fundamental resource for future tumor-infiltrating γδ T cell research and may facilitate the development of novel γδ-T-cell-based therapeutic strategies. Together, we demonstrate the strong diversity and prognostic potential of γδ T cells in multiple cancer types.

JAK2/mTOR Inhibition Fails to Prevent Acute GVHD Despite Reduced Th1/Th17 cells: Final Phase II Trial Results.

Our phase I graft-versus-host disease (GVHD) prevention trial of JAK2 inhibitor, pacritinib, (recommended phase II dose: 100mg po BID day 0 to +70) plus sirolimus and tacrolimus (PAC/SIR/TAC) demonstrated the regimen was safe and free of pan-JAK myelosuppression after allogeneic hematopoietic cell transplantation (alloHCT). PAC inhibits IL-6 receptor activity and pathogenic Th1/Th17 differentiation in preclinical models and the phase I trial. Herein we report on our completed phase II trial of PAC/SIR/TAC after 8/8-HLA matched alloHCT. This single-arm phase II trial (NCT02891603) was powered to determine if PAC/SIR/TAC suppressed %pSTAT3+ CD4+ T cells at day +21 (primary endpoint: %pSTAT3+ CD4+ T cells ≤ 35%) and estimated grade II-IV acute GVHD by day +100. The impact of PAC/SIR/TAC on T cell subsets, CD28 (pS6 and pH3ser10), and IL-2 receptor (pSTAT5) signal transduction was also evaluated. Eligible patients (n=28) received alloHCT for hematologic malignancies or myeloproliferative neoplasms. Reduced or myeloablative intensity conditioning was permitted. PAC/SIR/TAC met the primary endpoint, reducing %pSTAT3+ CD4+ T cells to 9.62% at day +21. Th1/Th17 cells were decreased at day +21, increasing the ratio of Tregs to Th1 and Th17 cells with PAC/SIR/TAC at RP2D PAC compared to dose level 1 PAC. The cumulative incidence of grade II-IV acute GVHD by day +100 with PAC/SIR/TAC was similar to historic SIR/TAC values (46 v 43%). While PAC/SIR/TAC suppressed pSTAT3 and Th1/Th17 cells, the regimen did not improve acute GVHD prevention.

Autologous Hematopoietic Cell Transplantation Consolidation for First Response is Associated With Longer Survival Among Patients With Nodal Peripheral T Cell Lymphoma.

Nodal peripheral T cell lymphomas (PTCLs) are challenging subsets of non-Hodgkin lymphomas characterized by their heterogeneity and aggressive clinical behavior. Given the mixed outcomes reported in previous studies, the efficacy of autologous hematopoietic cell transplantation (auto-HCT) as a consolidation strategy following initial chemotherapy response remains uncertain. This study aims to evaluate the impact of upfront auto-HCT consolidation on overall survival (OS) and event-free survival (EFS) among patients with nodal PTCL who achieved a complete or partial response to initial chemotherapy. A retrospective cohort study was conducted at Moffitt Cancer Center, involving 123 patients with nodal PTCL treated between February 2005 and February 2021. Patients were stratified into 2 groups based on whether they received auto-HCT as part of their initial treatment strategy. Kaplan-Meier method and Cox proportional hazard models were used for statistical analysis to compare OS and EFS between groups. Patients undergoing auto-HCT after first response demonstrated significantly longer median OS (12.3 versus 4.3 yr; P = .035) and EFS (6.2 versus 2.2 yr; P = .003) compared to those who did not. Multivariate analyses indicated that auto-HCT at first response and younger age at diagnosis were favorable prognostic factors. The findings suggest that upfront auto-HCT consolidation can significantly improve long-term outcomes in patients with nodal PTCL, supporting the strategy of early auto-HCT consideration and referral following initial chemotherapy response. These results underscore the importance of integrating upfront auto-HCT into the treatment paradigm for nodal PTCL, emphasizing early referral to transplantation services to optimize patient outcomes.

Breaking the silence of sharing data in medical research.

Data sharing is highly advocated in the scientific community, with numerous organizations, funding agencies, and journals promoting transparency and collaboration. However, limited research exists on actual data sharing practices. We conducted a comprehensive analysis of the intent to share individual participant data (IPD) in a total of 313,990 studies encompassing clinical trials and observational studies obtained from ClinicalTrials.gov, spanning the period from 2000 to 2023. Our study found that only 10.3% of principal investigators (PIs) expressed intent to share IPD. Clinical trials were more likely to share data than observational studies (odds ratio, OR = 1.98, 95% CI: 1.92-2.04). Large sample size studies were 1.69 times more likely to share data than small ones (95% CI: 1.65-1.73). Studies registered after 2018 were 1.6 times more likely to share data (95% CI: 1.57-1.64) than before 2019. NIH and other US Federal agency-funded studies had 1.49 times higher odds of sharing data (95% CI: 1.43-1.55) than other funders. USA-based studies were 1.53 times more likely to share data (95% CI: 1.49-1.57) than out of USA. Biological trials were 1.58 times more likely to share data than drug and other trials (95% CI: 1.51-1.66). Phase III trials had the highest odds, 2.47 times, of sharing data (95% CI: 2.38-2.56) than non-Phase III trials.

Troponin Elevation in Patients Undergoing Percutaneous Hepatic Perfusion for Metastatic Uveal Melanoma.

BACKGROUND: Percutaneous Hepatic Perfusion (PHP) is a liver directed regional therapy recently FDA approved for metastatic uveal melanoma to the liver involving percutaneous isolation of liver, saturation of the entire liver with high-dose chemotherapy and filtration extracorporeally though in line filters and veno-venous bypass. The procedure is associated with hemodynamic shifts requiring hemodynamic support and blood product resuscitation due to coagulopathy. OBJECTIVE: To assess the cardiac safety and subsequent clinically significant sequalae of this therapy. METHODS: Consecutive PHP procedures done at our center between 2010-2022 were assessed retrospectively. Cardiac risk factors, post procedural cardiac enzymes, electrocardiograms, and transthoracic echocardiograms along with 90-day cardiac outcomes were reviewed. All data were reviewed by cardio-oncologists at our institution. RESULTS: Of 37 patients reviewed, mean age was 63 years and 57% were women. 132 procedures were performed with an average of 3.57 procedures per patient. 68.6% of patients had elevated troponin during at least 1 procedure. No patients were found to have acute coronary syndrome, heart failure, unstable arrhythmias, or cardiac death. No patients had notable echocardiographic changes. 10.8% of patients with positive troponin had asymptomatic transient electrocardiographic changes not meeting criteria for myocardial infarction. One patient had non-sustained ventricular tachycardiac intra-operatively which did not recur subsequently. Three patients died from non-cardiac causes within 90-days. There was no oncology treatment interruption, even in those with troponin elevation. In multivariable analysis, a history of hyperlipidemia was a predictor of postoperative troponin elevation. (P = .042). CONCLUSION: Percutaneous Hepatic Perfusion is safe and associated with a transient, asymptomatic troponin elevation peri-operatively without major adverse cardiac events at 90 days. The observed troponin elevation is likely secondary to coronary demand-supply mismatch related to procedural hemodynamic shifts, hypotension, and anemia.

Percutaneous hepatic perfusion using melphalan in patients with uveal melanoma and liver metastases carries no significant cardiac adverse events.

Factors associated with overall survival in breast cancer patients with leptomeningeal disease (LMD): a single institutional retrospective review.

BACKGROUND: Breast cancer-related leptomeningeal disease (BC-LMD) is a dire diagnosis for 5-8% of patients with breast cancer (BC). We conducted a retrospective review of BC-LMD patients diagnosed at Moffitt Cancer Center from 2011 to 2020, to determine the changing incidence of BC-LMD, factors which are associated with the progression of BC CNS metastasis to BC-LMD, and factors which are associated with OS for patients with BC-LMD. METHODS: Patients with BC and brain/spinal metastatic disease were identified. For those who eventually developed BC-LMD, we used Kaplan-Meier survival curve, log-rank test, univariable, and multivariate Cox proportional hazards regression model to identify factors affecting time from CNS metastasis to BC-LMD and OS. RESULTS: 128 cases of BC-LMD were identified. The proportion of BC-LMD to total BC patients was higher between 2016 and 2020 when compared to 2011-2015. Patients with HR+ or HER2 + BC experienced longer times between CNS metastasis and LMD than patients with triple-negative breast cancer (TNBC). Systemic therapy and whole-brain radiation therapy (WBRT) was associated with prolonged progression to LMD in all patients. Hormone therapy in patients with HR + BC were associated with a delayed BC-CNS metastasis to LMD progression. Lapatinib treatment was associated with a delayed progression to LMD in patients with HER2 + BC. Patients with TNBC-LMD had shorter OS compared to those with HR + and HER2 + BC-LMD. Systemic therapy, intrathecal (IT) therapy, and WBRT was associated with prolonged survival for all patients. Lapatinib and trastuzumab therapy was associated with improved OS in patients with HER2 + BC-LMD. CONCLUSIONS: Increasing rates of BC-LMD provide treatment challenges and opportunities for clinical trials. Prospective trials testing lapatinib and/or similar tyrosine kinase inhibitors, IT therapies, and combination treatments are urgently needed.

A data-driven approach to choosing privacy parameters for clinical trial data sharing under differential privacy.

OBJECTIVES: Clinical trial data sharing is crucial for promoting transparency and collaborative efforts in medical research. Differential privacy (DP) is a formal statistical technique for anonymizing shared data that balances privacy of individual records and accuracy of replicated results through a "privacy budget" parameter, ε. DP is considered the state of the art in privacy-protected data publication and is underutilized in clinical trial data sharing. This study is focused on identifying ε values for the sharing of clinical trial data. MATERIALS AND METHODS: We analyzed 2 clinical trial datasets with privacy budget ε ranging from 0.01 to 10. Smaller values of ε entail adding greater amounts of random noise, with better privacy as a result. Comparison of rates, odds ratios, means, and mean differences between the original clinical trial datasets and the empirical distribution of the DP estimator was performed. RESULTS: The DP rate closely approximated the original rate of 6.5% when ε > 1. The DP odds ratio closely aligned with the original odds ratio of 0.689 when ε ≥ 3. The DP mean closely approximated the original mean of 164.64 when ε ≥ 1. As ε increased to 5, both the minimum and maximum DP means converged toward the original mean. DISCUSSION: There is no consensus on how to choose the privacy budget ε. The definition of DP does not specify the required level of privacy, and there is no established formula for determining ε. CONCLUSION: Our findings suggest that the application of DP holds promise in the context of sharing clinical trial data.

Baseline Serum Inflammatory Proteins Predict Poor CAR T Outcomes in Diffuse Large B-cell Lymphoma.

A subset of patients with diffuse large B-cell lymphoma (DLBCL) treated with CD19 chimeric antigen receptor (CAR) T-cell therapy have poor clinical outcomes. We report serum proteins associated with severe immune-mediated toxicities and inferior clinical responses in 146 patients with DLBCL treated with axicabtagene ciloleucel. We develop a simple stratification based on pre-lymphodepletion C reactive protein (CRP) and ferritin to classify patients into low-, intermediate-, and high-risk groups. We observe that patients in the high-risk category were more likely to develop grade ≥3 toxicities and had inferior overall and progression-free survival. We sought to validate our findings with two independent international cohorts demonstrating that patients classified as low-risk have excellent efficacy and safety outcomes. Based on routine and readily available laboratory tests that can be obtained prior to lymphodepleting chemotherapy, this simple risk stratification can inform patient selection for CAR T-cell therapy. SIGNIFICANCE: CAR T-cell therapy has changed the treatment paradigm for patients with relapsed/refractory hematologic malignancies. Despite encouraging efficacy, a subset of patients have poor clinical outcomes. We show that a simple clinically applicable model using pre-lymphodepletion CRP and ferritin can identify patients at high risk of poor outcomes. This article is featured in Selected Articles from This Issue, p. 80.

Enhanced Efficacy of Chemotherapy by Addition of Immune Checkpoint Inhibitors in Stage IV Large Cell Neuroendocrine Carcinoma of the Lung: A Real-World Analysis.

Background: Large Cell Neuroendocrine Carcinoma (LCNEC) is a high-grade malignancy with limited treatment options. Despite promising results of immunotherapy in non-small cell and small cell lung cancers, its benefit in LCNEC remains elusive. Methods: We included 24 patients diagnosed with stage IV LCNEC from the Moffitt Cancer Center database who received systemic therapy between January 2016 and May 2021. Group A comprised patients who received first-line CT and ICI (anti-PD-1 or anti-PD-L1 therapy for ICI, n = 11), and Group B received first-line CT only (n = 13). The collected data encompassed overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and toxicities since treatment initiation. Results: Kaplan-Meier survival analysis revealed median OS was 56 weeks (95%CI = 22.2-89.8) and 28 weeks (95% CI=16.3-39.7) in groups A and B, respectively. Log-rank test showed the difference was statistically significant (p=0.029). Median PFS was 32 weeks (95%CI=14.7-49.3) in group A and 20 weeks (95% CI=13.8-26.2) in groups B, but the difference was not statistically significant (p= 0.136). Univariate Cox analysis confirmed that the addition of ICI to CT significantly improved OS in patients with stage IV LCNEC (HR=0.35, 95% CI=0.13-0.95, p = 0.039). The ORR (63.6% vs 45.4%, p= 0.670) and DCR (81.8% vs 63.6%, p= 0.635) tended to be higher in group A than in group B but the difference was not statistically significant. Importantly, the combined treatment demonstrated a satisfactory safety profile, with only two patients reporting grade 2 or higher adverse events. Conclusions: Our results suggest that the combination of immunotherapy with chemotherapy holds potential for improving outcomes in stage IV LCNEC. Despite the retrospective nature and limited sample size of our study, these preliminary findings provide a valuable insight into the potential of immunotherapy in LCNEC treatment and encourage further research through larger, prospective trials.

The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease.

Background: Parkinson's disease is a neurological disorder that can cause gait disturbance, leading to mobility issues and falls. Early diagnosis and prediction of freeze episodes are essential for mitigating symptoms and monitoring the disease. Objective: This review aims to evaluate the use of artificial intelligence (AI)-based gait evaluation in diagnosing and managing Parkinson's disease, and to explore the potential benefits of this technology for clinical decision-making and treatment support. Methods: A thorough review of published literature was conducted to identify studies, articles, and research related to AI-based gait evaluation in Parkinson's disease. Results: AI-based gait evaluation has shown promise in preventing freeze episodes, improving diagnosis, and increasing motor independence in patients with Parkinson's disease. Its advantages include higher diagnostic accuracy, continuous monitoring, and personalized therapeutic interventions. Conclusion: AI-based gait evaluation systems hold great promise for managing Parkinson's disease and improving patient outcomes. They offer the potential to transform clinical decision-making and inform personalized therapies, but further research is needed to determine their effectiveness and refine their use.

Prediction-oriented prognostic biomarker discovery with survival machine learning methods.

Identifying novel and reliable prognostic biomarkers for predicting patient survival outcomes is essential for deciding personalized treatment strategies for diseases such as cancer. Numerous feature selection techniques have been proposed to address the high-dimensional problem in constructing prediction models. Not only does feature selection lower the data dimension, but it also improves the prediction accuracy of the resulted models by mitigating overfitting. The performances of these feature selection methods when applied to survival models, on the other hand, deserve further investigation. In this paper, we construct and compare a series of prediction-oriented biomarker selection frameworks by leveraging recent machine learning algorithms, including random survival forests, extreme gradient boosting, light gradient boosting and deep learning-based survival models. Additionally, we adapt the recently proposed prediction-oriented marker selection (PROMISE) to a survival model (PROMISE-Cox) as a benchmark approach. Our simulation studies indicate that boosting-based approaches tend to provide superior accuracy with better true positive rate and false positive rate in more complicated scenarios. For demonstration purpose, we applied the proposed biomarker selection strategies to identify prognostic biomarkers in different modalities of head and neck cancer data.

Factors improving overall survival in breast cancer patients with leptomeningeal disease (LMD): A single institutional retrospective review.

Background: Breast cancer-related leptomeningeal disease (BC-LMD) is a dire diagnosis for 5-8% of patients with breast cancer (BC). We conducted a retrospective review of BC-LMD patients diagnosed at Moffitt Cancer Center (MCC) from 2011-2020, to determine the changing incidence of BC-LMD, which factors impact progression of BC CNS metastasis to BC-LMD, and which factors affect OS for patients with BC-LMD. Methods: Patients with BC and brain/spinal metastatic disease were identified. For those who eventually developed BC-LMD, we used Kaplan-Meier survival curve, log-rank test, univariable, and multivariate Cox proportional hazards regression model to identify factors affecting time from CNS metastasis to BC-LMD and OS. Results: 128 cases of BC-LMD were identified. The proportion of BC-LMD to total BC patients was higher between 2016-2020 when compared to 2011-2015. Patients with HR + or HER2 + BC experienced longer times between CNS metastasis and LMD than patients with triple-negative breast cancer (TNBC). Systemic therapy and whole-brain radiation therapy (WBRT) prolonged progression to LMD in all patients. Hormone therapy in patients with HR + BC delayed BC-CNS metastasis to LMD progression. Lapatinib delayed progression to LMD in patients with HER2 + BC. Patients with TNBC-LMD had shorter OS compared to those with HR + and HER2 + BC-LMD. Systemic therapy, intrathecal (IT) therapy, and WBRT prolonged survival for all patients. Lapatinib and trastuzumab improved OS in patients with HER2 + BC-LMD. Conclusions: Increasing rates of BC-LMD provide treatment challenges and opportunities for clinical trials. Trials testing lapatinib and/or similar tyrosine kinase inhibitors, IT therapies, and combination treatments are urgently needed.

Risk factors associated with amyotrophic lateral sclerosis based on the observational study: a systematic review and meta-analysis.

Objective: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder affecting the upper and lower motor neurons. Though the pathogenesis of ALS is still unclear, exploring the associations between risk factors and ALS can provide reliable evidence to find the pathogenesis. This meta-analysis aims to synthesize all related risk factors of ALS to understand this disease comprehensively. Methods: We searched the following databases: PubMed, EMBASE, Cochrane library, Web of Science, and Scopus. Moreover, observational studies, including cohort studies, and case-control studies, were included in this meta-analysis. Results: A total of 36 eligible observational studies were included, and 10 of them were cohort studies and the rest were case-control studies. We found six factors exacerbated the progression of disease: head trauma (OR = 1.26, 95% CI = 1.13, 1.40), physical activity (OR = 1.06, 95% CI = 1.04, 1.09), electric shock (OR = 2.72, 95% CI = 1.62, 4.56), military service (OR = 1.34, 95% CI = 1.11, 1.61), pesticides (OR = 1.96, 95% CI = 1.7, 2.26), and lead exposure (OR = 2.31, 95% CI = 1.44, 3.71). Of note, type 2 diabetes mellitus was a protective factor for ALS. However, cerebrovascular disease (OR = 0.99, 95% CI = 0.75, 1.29), agriculture (OR = 1.22, 95% CI = 0.74, 1.99), industry (OR = 1.24, 95% CI = 0.81, 1.91), service (OR = 0.47, 95% CI = 0.19, 1.17), smoking (OR = 1.25, 95% CI = 0.5, 3.09), chemicals (OR = 2.45, 95% CI = 0.89, 6.77), and heavy metal (OR = 1.5, 95% CI = 0.47, 4.84) were not risk factors for ALS based on meta-analyses. Conclusions: Head trauma, physical activity, electric shock, military service, pesticides, and lead were risk factors for ALS onset and progression. But DM was a protective factor. This finding provides a better understanding of ALS risk factors with strong evidence for clinicians to rationalize clinical intervention strategies. INPLSY registration number: https://inplasy.com/inplasy-2022-9-0118/, INPLASY202290118.

Telemedicine Adoption in an NCI-Designated Cancer Center During the COVID-19 Pandemic: A Report on Patient Experience of Care.

BACKGROUND: Patients with cancer require timely access to care so that healthcare providers can prepare an optimal treatment plan with significant implications for quality of life and mortality. The COVID-19 pandemic spurred rapid adoption of telemedicine in oncology, but study of patient experience of care with telemedicine in this population has been limited. We assessed overall patient experience of care with telemedicine at an NCI-designated Comprehensive Cancer Center during the COVID-19 pandemic and examined changes in patient experience over time. PATIENTS AND METHODS: This was a retrospective study of outpatient oncology patients who received treatment at Moffitt Cancer Center. Press Ganey surveys were used to assess patient experience. Data from patients with appointments between April 1, 2020, and June 30, 2021, were analyzed. Patient experience was compared between telemedicine and in-person visits, and patient experience with telemedicine over time was described. RESULTS: A total of 33,318 patients reported Press Ganey data for in-person visits, and 5,950 reported Press Ganey data for telemedicine visits. Relative to patients with in-person visits, more patients with telemedicine visits gave higher satisfaction ratings for access (62.5% vs 75.8%, respectively) and care provider concern (84.2% vs 90.7%, respectively) (P<.001). When adjusted for age, race/ethnicity, sex, insurance, and clinic type, telemedicine visits consistently outperformed in-person visits over time regarding access and care provider concern (P<.001). There were no significant changes over time in satisfaction with telemedicine visits regarding access, care provider concern, telemedicine technology, or overall assessment (P>.05). CONCLUSIONS: In this study, a large oncology dataset showed that telemedicine resulted in better patient experience of care in terms of access and care provider concern compared with in-person visits. Patient experience of care with telemedicine visits did not change over time, suggesting that implementing telemedicine was effective.

A subnetwork-based framework for prioritizing and evaluating prognostic gene modules from cancer transcriptome data.

Cancer prognosis prediction is critical to the clinical decision-making process. Currently, the high availability of transcriptome datasets allows us to extract the gene modules with promising prognostic values. However, the biomarker identification is greatly challenged by tumor and patient heterogeneity. In this study, a framework of three subnetwork-based strategies is presented, incorporating hypothesis-driven, data-driven, and literature-based methods with informative visualization to prioritize candidate genes. By applying the proposed approaches to a head and neck squamous cell cancer (HNSCC) transcriptome dataset, we successfully identified multiple HNSCC-specific gene modules with improved prognostic values and mechanism information compared with the standard gene panel selection methods. The proposed framework is general and can be applied to any type of omics data. Overall, the study demonstrates and supports the use of the subnetwork-based approach for distilling reliable and biologically meaningful prognostic factors.

Fucosylation of HLA-DRB1 regulates CD4+ T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy.

Immunotherapy efficacy is limited in melanoma, and combinations of immunotherapies with other modalities have yielded limited improvements but also adverse events requiring cessation of treatment. In addition to ineffective patient stratification, efficacy is impaired by paucity of intratumoral immune cells (itICs); thus, effective strategies to safely increase itICs are needed. We report that dietary administration of L-fucose induces fucosylation and cell surface enrichment of the major histocompatibility complex (MHC)-II protein HLA-DRB1 in melanoma cells, triggering CD4+ T cell-mediated increases in itICs and anti-tumor immunity, enhancing immune checkpoint blockade responses. Melanoma fucosylation and fucosylated HLA-DRB1 associate with intratumoral T cell abundance and anti-programmed cell death protein 1 (PD1) responder status in patient melanoma specimens, suggesting the potential use of melanoma fucosylation as a strategy for stratifying patients for immunotherapies. Our findings demonstrate that fucosylation is a key mediator of anti-tumor immunity and, importantly, suggest that L-fucose is a powerful agent for safely increasing itICs and immunotherapy efficacy in melanoma.

Phase II clinical and immune correlate study of adjuvant nivolumab plus ipilimumab for high-risk resected melanoma.

BACKGROUND: Adjuvant therapy for high-risk resected melanoma with programmed cell-death 1 blockade results in a median relapse-free survival (RFS) of 5 years. The addition of low dose ipilimumab (IPI) to a regimen of adjuvant nivolumab (NIVO) in CheckMate-915 did not result in increased RFS. A pilot phase II adjuvant study of either standard dose or low dose IPI with NIVO was conducted at two centers to evaluate RFS with correlative biomarker studies. METHODS: Patients with resected stages IIIB/IIIC/IV melanoma received either IPI 3 mg/kg and NIVO 1 mg/kg (cohort 4) or IPI 1 mg/kg and NIVO 3 mg/kg (cohorts 5 and 6) induction therapy every 3 weeks for 12 weeks, followed by maintenance NIVO. In an amalgamated subset of patients across cohorts, peripheral T cells at baseline and on-treatment were assessed by flow cytometry and RNA sequencing for exploratory biomarkers. RESULTS: High rates of grade 3-4 adverse events precluded completion of induction therapy in 50%, 35% and 7% of the patients in cohorts 4, 5 and 6, respectively. At a median of 63.9 months of follow-up, 16/56 patients (29%) relapsed. For all patients, at 5 years, RFS was 71% (95% CI: 60 to 84), and overall survival was 94% (95% CI: 88 to 100). Expansion of CD3+CD4+CD38+CD127-GARP- T cells, an on-treatment increase in CD39 expression in CD8+ T cells, and T-cell expression of phosphorylated signal-transducer-and-activator-of-transcription (STAT)2 and STAT5 were associated with relapse. CONCLUSIONS: Adjuvant IPI/NIVO at the induction doses used resulted in promising relapse-free and overall survival, although with a high rate of grade 3-4 adverse events. Biomarker analyses highlight an association of ectoenzyme-expressing T cells and STAT signaling pathways with relapse, warranting future validation. TRIAL REGISTRATION NUMBER: NCT01176474 and NCT02970981.

The Impact of the Affordable Care Act on Insurance Coverage and Stage Among Head and Neck Squamous Cell Carcinoma Patients.

The purpose was to examine the change in percent uninsured and if there is change in T-stage, N-stage and overall-stage among nonelderly patients with newly diagnosed head and neck squamous cell carcinoma after the Affordable Care Act (ACA). The National Cancer Database was used for this study. Patients were divided between pre-ACA and post-ACA implementation with stratification between areas of ACA expansion versus non-expansion. A quasi-experimental difference-in-difference study design was undertaken. A total of 15,037 patients met the inclusion criteria. Between the pre-ACA and post-ACA periods, there was increase in proportion of percent insured with Medicaid coverage in patients residing in expansion region. There was a decrease in the proportion of patients who had advanced Tumor stage and Nodal stage decreased after implementation of ACA. With the implementation of ACA expansion, there is increased Medicaid coverage, corresponding to a decreased proportion of patients presenting with advanced T-stage and N-stage.