Autologous hematopoietic cell transplantation consolidation for first response is associated with longer survival among patients with nodal peripheral T-cell lymphoma.

BACKGROUND: 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-SCT) as a consolidation strategy following initial chemotherapy response remains uncertain. OBJECTIVE: This study aims to evaluate the impact of upfront auto-SCT 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. STUDY DESIGN: 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 two groups based on whether they received auto-SCT 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. RESULTS: Patients undergoing auto-SCT after first response demonstrated significantly longer median OS (12.3 vs. 4.3 years; P = .035) and EFS (6.2 vs. 2.2 years; P = .003) compared to those who did not. Multivariate analyses indicated that auto-SCT at first response and younger age at diagnosis were favorable prognostic factors. CONCLUSION: The findings suggest that upfront auto-SCT consolidation can significantly improve long-term outcomes in patients with nodal PTCL, supporting the strategy of early auto-SCT consideration and referral following initial chemotherapy response. These results underscore the importance of integrating upfront auto-SCT into the treatment paradigm for nodal PTCL, emphasizing early referral to transplantation services to optimize patient outcomes.

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.

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.

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.

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.

Prognostic features of endometrial cancer metastasis to the central nervous system.

OBJECTIVES: Central nervous system metastases (CNSm) secondary to endometrial cancer (EC) are rare. As a result, prognostic factors for this patient population are not well described. METHODS: EC patients with CNSm were identified retrospectively from two academic centers. EC patients without CNSm (non-CNSm) were used as controls. Chi-square and Fisher's exact tests were used for analysis of categorial variables. Wilcoxon tests were used for quantitative measures. Overall survival (OS) was compared with Log-rank test. Cox proportional hazard models were used to estimate hazard ratios for OS. RESULTS: 22 EC patients with CNSm and 354 non-CNSm patients were included. Compared to non-CNSm EC, the CNSm cohort was younger (58.5 vs 62.0 years, p = 0.018) with lower BMI (27.7 vs. 33.7 kg/m2, p = 0.005), and had more advanced stages (p = ≤ 0.001), grade 3 tumors (81.8% CNSm vs 25.1% non CNSm, p≤0.001) and serous histology (22.7% vs 8.5%, p = 0.010). Median survival after CNSm diagnosis was 9 months (95% CI 4, NA). CNSm was a strong poor prognostic factor (HR death 4.96, p = 0.022). Improved OS was seen with CNS as the only disease site (83m CNSm only vs 30m additional sites, p = 0.007) and less than five CNSm (49m <5 vs. 23m ≥5, p = 0.004). Surgical resection of CNSm (OS 83m surgery vs 33m no surgery, p = 0.003) or multimodal therapy (83m multimodal vs 33m single therapy, p = 0.027) resulted in longer OS. CONCLUSIONS: CNSm is a poor prognostic factor in EC, however, low volume disease with aggressive treatment may result in more favorable survival outcomes.

Transcriptomic analysis reveal the responses of dendritic cells to VDBP.

BACKGROUND: Vitamin D binding protein (VDBP) is an essential plasma carrier protein, which plays possible roles in reproductive health, disease and so on. However, the effects of VDBP on immunity have not been fully studied and the pertinent literatures remain very limited. OBJECTIVE: In this study, we introduced the exogenous VDBP into DC2.4 and established a stable DC2.4/VDBP cell line to explore the role of this gene in immunity. METHODS: Dendritic cells (DCs), as the most effective antigen presenting cells (APC) found so far, are directly involved in regulating some innate immunity. In order to evaluate the biological role of VDBP in DCs, we stably overexpressed VDBP in DCs, and conducted Cell Counting Kit­8 (CCK-8 kit) and flow cytometry to detect changes in cell function. CCK-8 kit was used to monitor the viability of DCs after gene overexpression, and flow cytometry was used to detect changes in cell cycle distribution and apoptosis. Subsequently, in order to reveal the mechanism of VDBP regulating DCs, we adopted RNA sequencing (RNA-seq). RESULTS: CCK-8 results revealed VDBP successfully inhibited viability of DCs. Besides, we found that overexpression of this gene greatly promoted apoptosis and obviously altered the cell cycle distribution of DCs in G1 and G2 phases. Moreover, RNA-seq was carried out and 151 differently expression genes (DEGs) were obtained. In addition, gene differential expression analysis showed that most of them were uniformly enriched in immunity-related pathways. CONCLUSION: These results indicated that VDBP greatly repressed proliferation, facilitated apoptosis and changed cell cycle in DCs via altering the expression levels of gene associated with their cellular immunity.

Expression of epigenetic pathway related genes in association with PD-L1, ER/PgR and MLH1 in endometrial carcinoma.

The distribution of Endometrial Cancer (EC)-related deaths is uneven among the morphologic subtypes of EC. Serous Cancer (SC) makes 10% of all EC and accounts for 40% of EC-related deaths. We investigated expression of selected genes involved in epigenetic pathways by immunohistochemistry in a cohort of 106 EC patients and analyzed mRNA-based expression levels for the same set of genes in EC samples from The Cancer Genome Atlas (TCGA) dataset. A tissue microarray was constructed using low-grade (n = 30) and high-grade (n = 28) endometrioid, serous (n = 31) and clear cell carcinoma (n = 17) samples. Epigenetic marker levels were associated with PD-L1, ER/PgR, and MLH1 expression. Epigenetic markers were evaluated by H-score and PD-L1 expression was recorded by using Combined Positive Score. Results were correlated with disease stage and survival outcome. BRD4, KAT6a and HDAC9 levels were higher in SC compared to other histologic subtypes (p<0.001-0.038). After adjusting for multiple comparisons, DNMT3b expression was higher in SC compared to endometrioid-type but not between SC and CCC. The expression levels of BRD4 (p = 0.021) and KAT6a (p = 0.0027) were positively associated with PD-L abundance, while PgR (p = 0.029) and PD-L1 expression were negatively associated. In addition, BRD4 expression was low in specimens with loss of MLH1 expression (p = 0.02). More importantly, BRD4 abundance had a negative impact on disease outcome (p = 0.02). Transcriptionally, BRD4, KAT6a and DNMT3b expression levels were higher in SC in TCGA dataset. The median PD-L1 expression was marginally associated with BRD4, a transcriptional activator of CD274/PD-L1 (p = 0.069) and positively with KAT6a (p = 0.0095). In conclusion, the protein expression levels of epigenetic markers involved in cancer pathogenesis are increased by immunohistochemistry in SC. PD-L1 levels are associated with BRD4 and KAT6a in EC samples. A combination therapy with BRD4/PD-L1 or KAT6a/PD-L1 inhibitors might have a potential use in EC, in particular serous-type carcinoma.

Efficient gradient boosting for prognostic biomarker discovery.

MOTIVATION: A gradient boosting decision tree (GBDT) is a powerful ensemble machine-learning method that has the potential to accelerate biomarker discovery from high-dimensional molecular data. Recent algorithmic advances, such as extreme gradient boosting (XGB) and light gradient boosting (LGB), have rendered the GBDT training more efficient, scalable and accurate. However, these modern techniques have not yet been widely adopted in discovering biomarkers for censored survival outcomes, which are key clinical outcomes or endpoints in cancer studies. RESULTS: In this paper, we present a new R package 'Xsurv' as an integrated solution that applies two modern GBDT training frameworks namely, XGB and LGB, for the modeling of right-censored survival outcomes. Based on our simulations, we benchmark the new approaches against traditional methods including the stepwise Cox regression model and the original gradient boosting function implemented in the package 'gbm'. We also demonstrate the application of Xsurv in analyzing a melanoma methylation dataset. Together, these results suggest that Xsurv is a useful and computationally viable tool for screening a large number of prognostic candidate biomarkers, which may facilitate future translational and clinical research. AVAILABILITY AND IMPLEMENTATION: 'Xsurv' is freely available as an R package at: https://github.com/topycyao/Xsurv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.