The vitamin D receptor gene as a determinant of survival in pancreatic cancer patients: Genomic analysis and experimental validation

Purpose: Advanced pancreatic cancer is a highly refractory disease almost always associated with survival of little more than a year. New interventions based on novel targets are needed. We aim to identify new genetic determinants of overall survival (OS) in patients after treatment with gemcitabine using genome-wide screens of germline DNA. We aim also to support these findings with in vitro functional analysis. Patients and methods: Genome-wide screens of germline DNA in two independent cohorts of pancreatic cancer patients (from the Cancer and Leukemia Group B (CALGB) 80303 and the Mayo Clinic) were used to select new genes associated with OS. The vitamin D receptor gene (VDR) was selected, and the interactions of genetic variation in VDR with circulating vitamin D levels and gemcitabine treatment were evaluated. Functional effects of common VDR variants were also evaluated in experimental assays in human cell lines. Results: The rs2853564 variant in VDR was associated with OS in patients from both the Mayo Clinic (HR 0.81, 95% CI 0.70–0.94, p = 0.0059) and CALGB 80303 (HR 0.74, 0.63–0.87, p = 0.0002). rs2853564 interacted with high pre-treatment levels of 25-hydroxyvitamin D (25(OH)D, a measure of endogenous vitamin D) (p = 0.0079 for interaction) and with gemcitabine treatment (p = 0.024 for interaction) to confer increased OS. rs2853564 increased transcriptional activity in luciferase assays and reduced the binding of the IRF4 transcription factor. Conclusion: Our findings propose VDR as a novel determinant of survival in advanced pancreatic cancer patients. Common functional variation in this gene might interact with endogenous vitamin D and gemcitabine treatment to determine improved patient survival. These results support evidence for a modulatory role of the vitamin D pathway for the survival of advanced pancreatic cancer patients.</p

Recent discoveries and applications involving small-molecule microarrays

High-throughput and unbiased binding assays have proven useful in probe discovery for a myriad of biomolecules, including targets of unknown structure or function and historically challenging target classes. Over the past decade, a number of novel formats for executing large-scale binding assays have been developed and used successfully in probe discovery campaigns. Here we review the use of one such format, the small-molecule microarray (SMM), as a tool for discovering protein-small molecule interactions. This review will briefly highlight selected recent probe discoveries using SMMs as well as novel uses of SMMs in profiling applications. © 2013 Elsevier Ltd

Derivation and validation of a risk classification tree for patients with synovial sarcoma

Abstract Background Synovial sarcoma (SS) accounts for 8%–10% of all soft‐tissue sarcomas. Clinical presentation and outcomes vary, yet discrete risk groups based on validated prognostic indices are not defined for the full spectrum of patients with SS. Methods We performed a retrospective cohort study using data from the SEER (surveillance, epidemiology, and end results program) database of SS patients who were <70 years of age at diagnosis. We constructed a recursive partitioning model of overall survival using a training cohort of 1063 patients with variables: Age at diagnosis, sex, race, ethnicity, primary site, tumor size, tumor grade, and stage. Based on this model, we grouped patients into three risk groups and estimated 5‐year overall survival for each group. We then applied these groups to a test cohort (n = 1063). Results Our model identified three prognostic groups with significantly different overall survival: low risk (local/regional stage with either <21 years of age OR tumor <7.5 cm and female sex), intermediate‐risk (local/regional stage, age ≥ 21 years with either male sex and tumor <7.5 cm OR any sex with appendicular anatomic location) and high risk (local/regional stage, age ≥ 21 years, tumor size ≥7.5 cm and non‐appendicular location OR distant stage). Prognostic groups were applied to the test cohort, showing significantly different survival between groups (p < 0.0001). Conclusions Our analysis yields an intuitive risk‐classification tree with discrete groups, which may provide useful information for researchers, patients, and clinicians. Prospective validation of this model may inform efforts at risk‐stratifying treatment

Pharmacotherapy for Amyotrophic Lateral Sclerosis: A Review of Approved and Upcoming Agents

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative disorder involving loss of upper and lower motor neurons, with most cases ending in death within 3-5 years of onset. Several molecular and cellular pathways have been identified to cause ALS; however, treatments to stop or reverse disease progression are yet to be found. Riluzole, a neuroprotective agent offering only a modest survival benefit, has long been the sole disease-modifying therapy for ALS. Edaravone, which demonstrated statistically significant slowing of ALS disease progression, is gaining approval in an increasing number of countries since its first approval in 2015. Sodium phenylbutyrate and taurursodiol (PB-TURSO) was conditionally approved in Canada in 2022, having shown significant slowing of disease progression and prolonged survival. Most clinical trials have focused on testing small molecules affecting common cellular pathways in ALS: targeting glutamatergic, apoptotic, inflammatory, and oxidative stress mechanisms among others. More recently, clinical trials utilizing stem cell transplantation and other biologics have emerged. This rich and ever-growing pipeline of investigational products, along with innovative clinical trial designs, collaborative trial networks, and an engaged ALS community', provide renewed hope to finding a cure for ALS. This article reviews existing ALS therapies and the current clinical drug development pipeline

Data-driven predictions of complex organic mixture permeation in polymer membranes

Abstract Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures

The vitamin D receptor gene as a determinant of survival in pancreatic cancer patients: Genomic analysis and experimental validation.

PURPOSE:Advanced pancreatic cancer is a highly refractory disease almost always associated with survival of little more than a year. New interventions based on novel targets are needed. We aim to identify new genetic determinants of overall survival (OS) in patients after treatment with gemcitabine using genome-wide screens of germline DNA. We aim also to support these findings with in vitro functional analysis. PATIENTS AND METHODS:Genome-wide screens of germline DNA in two independent cohorts of pancreatic cancer patients (from the Cancer and Leukemia Group B (CALGB) 80303 and the Mayo Clinic) were used to select new genes associated with OS. The vitamin D receptor gene (VDR) was selected, and the interactions of genetic variation in VDR with circulating vitamin D levels and gemcitabine treatment were evaluated. Functional effects of common VDR variants were also evaluated in experimental assays in human cell lines. RESULTS:The rs2853564 variant in VDR was associated with OS in patients from both the Mayo Clinic (HR 0.81, 95% CI 0.70-0.94, p = 0.0059) and CALGB 80303 (HR 0.74, 0.63-0.87, p = 0.0002). rs2853564 interacted with high pre-treatment levels of 25-hydroxyvitamin D (25(OH)D, a measure of endogenous vitamin D) (p = 0.0079 for interaction) and with gemcitabine treatment (p = 0.024 for interaction) to confer increased OS. rs2853564 increased transcriptional activity in luciferase assays and reduced the binding of the IRF4 transcription factor. CONCLUSION:Our findings propose VDR as a novel determinant of survival in advanced pancreatic cancer patients. Common functional variation in this gene might interact with endogenous vitamin D and gemcitabine treatment to determine improved patient survival. These results support evidence for a modulatory role of the vitamin D pathway for the survival of advanced pancreatic cancer patients

Stabilization of the Max Homodimer with a Small Molecule Attenuates Myc-Driven Transcription

The transcription factor Max is a basic-helix-loop-helix leucine zipper (bHLHLZ) protein that forms homodimers or interacts with other bHLHLZ proteins, including Myc and Mxd proteins. Among this dynamic network of interactions, the Myc/Max heterodimer has crucial roles in regulating normal cellular processes, but its transcriptional activity is deregulated in a majority of human cancers. Despite this significance, the arsenal of high-quality chemical probes to interrogate these proteins remains limited. We used small molecule microarrays to identify compounds that bind Max in a mechanistically unbiased manner. We discovered the asymmetric polycyclic lactam, KI-MS2-008, which stabilizes the Max homodimer while reducing Myc protein and Myc-regulated transcript levels. KI-MS2-008 also decreases viable cancer cell growth in a Myc-dependent manner and suppresses tumor growth in vivo. This approach demonstrates the feasibility of modulating Max with small molecules and supports altering Max dimerization as an alternative approach to targeting Myc.National Cancer Institute (Grant R01-CA160860)National Cancer Institute (Grant P30-CA14051)National Cancer Institute (Grant U01-CA176152)National Cancer Institute (Grant CA170378PQ2)National Institutes of Health (Grant CA170378PQ2