Development and validation of an integrative pan-solid tumor predictor of PD-1/PD-L1 blockade benefit.

BACKGROUND: Anti-PD-1 and PD-L1 (collectively PD-[L]1) therapies are approved for many advanced solid tumors. Biomarkers beyond PD-L1 immunohistochemistry, microsatellite instability, and tumor mutation burden (TMB) may improve benefit prediction. METHODS: Using treatment data and genomic and transcriptomic tumor tissue profiling from an observational trial (NCT03061305), we developed Immunotherapy Response Score (IRS), a pan-tumor predictive model of PD-(L)1 benefit. IRS real-world progression free survival (rwPFS) and overall survival (OS) prediction was validated in an independent cohort of trial patients. RESULTS: Here, by Cox modeling, we develop IRS-which combines TMB with CD274, PDCD1, ADAM12 and TOP2A quantitative expression-to predict pembrolizumab rwPFS (648 patients; 26 tumor types; IRS-High or -Low groups). In the 248 patient validation cohort (248 patients; 24 tumor types; non-pembrolizumab PD-[L]1 monotherapy treatment), median rwPFS and OS are significantly longer in IRS-High vs. IRS-Low patients (rwPFS adjusted hazard ratio [aHR] 0.52, p = 0.003; OS aHR 0.49, p = 0.005); TMB alone does not significantly predict PD-(L)1 rwPFS nor OS. In 146 patients treated with systemic therapy prior to pembrolizumab monotherapy, pembrolizumab rwPFS is only significantly longer than immediately preceding therapy rwPFS in IRS-High patients (interaction test p = 0.001). In propensity matched lung cancer patients treated with first-line pembrolizumab monotherapy or pembrolizumab+chemotherapy, monotherapy rwPFS is significantly shorter in IRS-Low patients, but is not significantly different in IRS-High patients. Across 24,463 molecularly-evaluable trial patients, 7.6% of patients outside of monotherapy PD-(L)1 approved tumor types are IRS-High/TMB-Low. CONCLUSIONS: The validated, predictive, pan-tumor IRS model can expand PD-(L)1 monotherapy benefit outside currently approved indications.

Therapies activating the immune system (checkpoint inhibitors) have revolutionized the treatment of patients with advanced cancer, however new molecular tests may better identify patients who could benefit. Using treatment data and clinical molecular test results, we report the development and validation of Immunotherapy Response Score (IRS) to predict checkpoint inhibitor benefit. Across patients with more than 20 advanced cancer types, IRS better predicted checkpoint inhibitor benefit than currently available tests. Data from >20,000 patients showed that IRS identifies ~8% of patients with advanced cancer who may dramatically benefit from checkpoint inhibitors but would not receive them today based on currently available tests. Our approach may help clinicians to decide which patients should receive checkpoint inhibitors to treat their disease.

Nicotinamide riboside and pterostilbene reduces markers of hepatic inflammation in NAFLD: A double-blind, placebo-controlled clinical trial.

BACKGROUND AND AIMS: The prevalence of NAFLD is increasing globally and on a path to becoming the most frequent cause of chronic liver disease. Strategies for the prevention and treatment of NAFLD are urgently needed. APPROACH AND RESULTS: A 6-month prospective, randomized, double-blind, placebo-controlled clinical trial was conducted to assess the efficacy of daily NRPT (commercially known as Basis, a combination of nicotinamide riboside and pterostilbene) supplementation in 111 adults with NAFLD. The study consisted of three arms: placebo, recommended daily dose of NRPT (NRPT 1×), and a double dose of NRPT (NRPT 2×). NRPT appeared safe and well tolerated. At the end of the study, no significant change was seen in the primary endpoint of hepatic fat fraction with respect to placebo. However, among prespecified secondary outcomes, a time-dependent decrease in the circulating levels of the liver enzymes alanine aminotransferase (ALT) and gamma-glutamyltransferase (GGT) was observed in the NRPT 1× group, and this decrease was significant with respect to placebo. Furthermore, a significant decrease in the circulating levels of the toxic lipid ceramide 14:0 was also observed in the NRPT 1× group versus placebo, and this decrease was associated with a decrease in ALT in individuals of this group. A dose-dependent effect was not observed with respect to ALT, GGT, or ceramide 14:0 in the NRPT 2× group. CONCLUSIONS: This study demonstrates that NRPT at the recommended dose is safe and may hold promise in lowering markers of hepatic inflammation in patients with NAFLD.

A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking.

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.

Personalized reproductive medicine on the brink: progress, opportunities and challenges ahead.

Significant progress has been made in several fields of medicine towards personalizing treatment recommendations based on individual patient genotype. As the number of clinical and genetic biomarkers available to physicians has increased, predictive models able to integrate the contributions of multiple variables simultaneously have become valuable tools for medical decision making. Leveraging genotype information and multivariate predictive models holds the promise of bringing greater efficiency to, and reducing the costs of, fertility treatments. This work reviews the advances that have been made in genetic biomarker discovery and predictive modelling for fertility treatment outcomes. We also discuss some of the limitations of these studies for translation to clinical diagnostics and the challenges that remain.Personalized medicine holds the promise of allowing doctors to create 'bespoke' treatment recommendations for each patient based on multiple clinical variables such as age and hormone concentrations combined with the patient's genetic sequence information. A number of challenges remain for the field of reproductive medicine to make the research discoveries necessary to usher in this new era of personalized fertility care. Here, we discuss some of these challenges and make recommendations for overcoming them.