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.

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.

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.

Tumor interferon signaling and suppressive myeloid cells are associated with CAR T-cell failure in large B-cell lymphoma.

Axicabtagene ciloleucel (axi-cel) is a chimeric antigen receptor (CAR) T-cell therapy for relapsed or refractory large B-cell lymphoma (LBCL). This study evaluated whether immune dysregulation, present before CAR T-cell therapy, was associated with treatment failure. Tumor expression of interferon (IFN) signaling, high blood levels of monocytic myeloid-derived suppressor cells (M-MDSCs), and high blood interleukin-6 and ferritin levels were each associated with a lack of durable response. Similar to other cancers, we found that in LBCL tumors, IFN signaling is associated with the expression of multiple checkpoint ligands, including programmed cell death-ligand 1, and these were higher in patients who lacked durable responses to CAR-T therapy. Moreover, tumor IFN signaling and blood M-MDSCs associated with decreased axi-cel expansion. Finally, patients with high tumor burden had higher immune dysregulation with increased serum inflammatory markers and tumor IFN signaling. These data support that immune dysregulation in LBCL promotes axi-cel resistance via multiple mechanistic programs: insufficient axi-cel expansion associated with both circulating M-MDSC and tumor IFN signaling, which also gives rise to expression of immune checkpoint ligands.

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.

Phase 2 study of copanlisib in combination with gemcitabine and cisplatin in advanced biliary tract cancers.

BACKGROUND: Biliary tract cancer (BTC) has a poor prognosis despite treatment with first-line gemcitabine and cisplatin. In BTC, PI3K/AKT pathway activation has been shown to increase resistance to chemotherapy, which may be overcome with PI3K inhibition. This phase 2 study evaluated the safety and efficacy of copanlisib, a PI3K inhibitor, with gemcitabine and cisplatin in advanced BTCs. The role of PTEN expression in outcomes was also explored. METHODS: Patients with advanced/unresectable BTC received gemcitabine, cisplatin, and copanlisib as their first-line treatment. The primary endpoint was progression-free survival (PFS) at 6 months. Secondary endpoints were the response rate (RR), median overall survival (OS)/PFS, and safety profile. An assessment of PTEN expression by immunohistochemistry was also performed along with molecular profiling. RESULTS: Twenty-four patients received at least 1 dose of the study drug. The PFS rate at 6 months was 51%; the median OS was 13.7 months (95% CI, 6.8-18.0 months), and the median PFS was 6.2 months (95% CI, 2.9-10.1 months). Nineteen patients were evaluable for RR: 6 patients achieved a partial response (31.6%), and 11 (57.9%) had stable disease. The most common grade 3/4 adverse events were a decreased neutrophil count (45.83%), anemia (25%), increased lipase (25%), and hypertension (20.8%). Twenty patients had tissue evaluable for the PTEN status. The PFS for low (n = 9) and high PTEN expression (n = 11) was 8.5 and 4.6 months, respectively (P = .19). The median OS for low and high PTEN expression groups was 17.9 and 7.0 months, respectively (P = .19). CONCLUSIONS: The addition of copanlisib to gemcitabine and cisplatin does not improve PFS at 6 months. However, future studies using PTEN as a potential biomarker should be considered. LAY SUMMARY: The addition of copanlisib, a PI3K inhibitor, to standard chemotherapy for advanced biliary tract cancers was assessed for efficacy and safety. Twenty-four patients with advanced biliary tract cancer received treatment in this study. There was no difference in survival with the addition of copanlisib in comparison with standard chemotherapy. Copanlisib may be more effective and increase survival in patients with low PTEN expression levels. Further studies are needed to confirm this. No unexpected adverse events occurred.

Pathological and Survival Outcomes Associated with Variant Histology Bladder Cancers Managed by Cystectomy with or without Neoadjuvant Chemotherapy.

PURPOSE: Although neoadjuvant chemotherapy is associated with a survival advantage in pure urothelial, muscle invasive bladder cancer, the role of neoadjuvant chemotherapy is less clear in variant histology or urothelial carcinoma with divergent differentiation. We compared chemotherapy response and survival outcomes of patients with nonpure urothelial carcinoma histology who were managed with neoadjuvant chemotherapy followed by cystectomy vs cystectomy alone. MATERIALS AND METHODS: We analyzed 768 patients with clinical muscle invasive bladder cancer (cT2-4N0M0) who were treated with cystectomy at a tertiary care center from 2007 to 2017. Patients were stratified by histology and treatment strategy. Adjusted logistic and Cox regression models were used to evaluate pathological downstaging, cancer specific survival and overall survival. RESULTS: The cohort consisted of 410 patients (53%) with pure urothelial carcinoma, 185 (24%) with urothelial carcinoma with divergent differentiation and 173 (23%) with variant histology. Overall, 314 patients (41%) received neoadjuvant chemotherapy prior to cystectomy. There were similar rates of complete (18% to 30%) and partial (37% to 46%) pathological downstaging with neoadjuvant chemotherapy across all histological subgroups (p=0.30 and p=0.40, respectively). However, while patients with pure urothelial carcinoma experienced an overall survival benefit (HR 0.71, 95% CI 0.51-0.98, p=0.0013) and those with variant histology experienced a cancer specific survival benefit (HR 0.55, 95% CI 0.30-0.99, p=0.0495) with neoadjuvant chemotherapy, patients with urothelial carcinoma with divergent differentiation did not experience overall or cancer specific survival benefits with the use of neoadjuvant chemotherapy prior to cystectomy. CONCLUSIONS: Among patients with muscle invasive bladder cancer those with nonpure urothelial carcinoma histology with variant histology achieved nearly equivalent response rates and survival benefits with the use of neoadjuvant chemotherapy as those with pure urothelial carcinoma, while patients with urothelial carcinoma with divergent differentiation experienced significantly worse survival outcomes regardless of the use of neoadjuvant chemotherapy prior to cystectomy.

Immune reconstitution and associated infections following axicabtagene ciloleucel in relapsed or refractory large B-cell lymphoma.

CD19 CAR T-cell therapy with axicabtagene ciloleucel (axi-cel) for relapsed or refractory (R/R) large B cell lymphoma (LBCL) may lead to durable remissions, however, prolonged cytopenias and infections may occur. In this single center retrospective study of 85 patients, we characterized immune reconstitution and infections for patients remaining in remission after axi-cel for LBCL. Prolonged cytopenias (those occurring at or after day 30 following infusion) were common with >= grade 3 neutropenia seen in 21/70 (30-0%) patients at day 30 and persisting in 3/31 (9-7%) patients at 1 year. B cells were undetectable in 30/34 (88-2%) patients at day 30, but were detected in 11/19 (57-9%) at 1 year. Median IgG levels reached a nadir at day 180. By contrast, CD4 T cells decreased from baseline and were persistently low with a median CD4 count of 155 cells/µl at 1 year after axi-cel (n=19, range 33 - 269). In total, 23/85 (27-1%) patients received IVIG after axi-cel, and 34/85 (40-0%) received G-CSF. Infections in the first 30 days occurred in 31/85 (36-5%) patients, of which 11/85 (12-9%) required intravenous antibiotics or hospitalization ("severe") and were associated with cytokine release syndrome (CRS), neurotoxicity, tocilizumab use, corticosteroid use, and bridging therapy on univariate analyses. After day 30, 7 severe infections occurred, with no late deaths due to infection. Prolonged cytopenias are common following axi-cel therapy for LBCL and typically recover with time. Most patients experience profound and prolonged CD4 T cell immunosuppression without severe infection.

PDXGEM: patient-derived tumor xenograft-based gene expression model for predicting clinical response to anticancer therapy in cancer patients.

BACKGROUND: Cancer is a highly heterogeneous disease with varying responses to anti-cancer drugs. Although several attempts have been made to predict the anti-cancer therapeutic responses, there remains a great need to develop highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward a personalized medicine. Patient derived xenografts (PDXs) are preclinical cancer models in which the tissue or cells from a patient's tumor are implanted into an immunodeficient or humanized mouse. In the present study, we develop a bioinformatics analysis pipeline to build a predictive gene expression model (GEM) for cancer patients' drug responses based on gene expression and drug activity data from PDX models. RESULTS: Drug sensitivity biomarkers were identified by performing an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. We built a drug response prediction model (called PDXGEM) in a random-forest algorithm by using a subset of the drug sensitvity biomarkers with concordant co-expression patterns between the PDXs and pretreatment cancer patient tumors. We applied the PDXGEM to several cytotoxic chemotherapies as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological response or survival outcomes were observed in extensive independent validations on multiple cancer patient datasets obtained from retrospective observational studies and prospective clinical trials. CONCLUSION: Our results demonstrated the strong potential of using molecular profiles and drug activity data of PDX tumors in developing a clinically translatable predictive cancer biomarkers for cancer patients. The PDXGEM web application is publicly available at http://pdxgem.moffitt.org .

A Phase I Trial of Trametinib in Combination with Sorafenib in Patients with Advanced Hepatocellular Cancer.

LESSONS LEARNED: The combination of trametinib and sorafenib has an acceptable safety profile, albeit at doses lower than approved for monotherapy. Maximum tolerated dose is trametinib 1.5 mg daily and sorafenib 200 mg twice daily. The limited anticancer activity observed in this unselected patient population does not support further exploration of trametinib plus sorafenib in patients with hepatocellular carcinoma. BACKGROUND: The RAS/RAF/MEK/ERK signaling pathway is associated with proliferation and progression of hepatocellular carcinoma (HCC). Preclinical data suggest that paradoxical activation of the MAPK pathway may be one of the resistance mechanisms of sorafenib; therefore, we evaluated trametinib plus sorafenib in HCC. METHODS: This was a phase I study with a 3+3 design in patients with treatment-naïve advanced HCC. The primary objective was safety and tolerability. The secondary objective was clinical efficacy. RESULTS: A total of 17 patients were treated with three different doses of trametinib and sorafenib. Two patients experienced dose-limiting toxicity, including grade 4 hypertension and grade 3 elevation of aspartate aminotransferase (AST)/alanine aminotransferase (ALT)/bilirubin over 7 days. Maximum tolerated dose was trametinib 1.5 mg daily and sorafenib 200 mg twice a day. The most common grade 3/4 treatment-related adverse events were elevated AST (37%) and hypertension (24%). Among 11 evaluable patients, 7 (63.6%) had stable disease with no objective response. The median progression-free survival (PFS) and overall survival (OS) were 3.7 and 7.8 months, respectively. Phosphorylated-ERK was evaluated as a pharmacodynamic marker, and sorafenib plus trametinib inhibited phosphorylated-ERK up to 98.1% (median: 81.2%) in peripheral blood mononuclear cells. CONCLUSION: Trametinib and sorafenib can be safely administered up to trametinib 1.5 mg daily and sorafenib 200 mg twice a day with limited anticancer activity in advanced HCC.

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.

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.

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-SCT) as a consolidation strategy following initial chemotherapy response remains uncertain. 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. 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-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. Patients undergoing auto-SCT 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-SCT at first response and younger age at diagnosis were favorable prognostic factors. 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.

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.

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.

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.

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.

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.