An interim exploratory proteomics biomarker analysis of a phase 2 clinical trial to assess the impact of CT1812 in Alzheimer's disease.

CT1812 is a novel, brain penetrant small molecule modulator of the sigma-2 receptor (S2R) that is currently in clinical development for the treatment of Alzheimer's disease (AD). Preclinical and early clinical data show that, through S2R, CT1812 selectively prevents and displaces binding of amyloid beta (Aß) oligomers from neuronal synapses and improves cognitive function in animal models of AD. SHINE is an ongoing phase 2 randomized, double-blind, placebo-controlled clinical trial (COG0201) in participants with mild to moderate AD, designed to assess the safety and efficacy of 6 months of CT1812 treatment. To elucidate the mechanism of action in AD patients and pharmacodynamic biomarkers of CT1812, the present study reports exploratory cerebrospinal fluid (CSF) biomarker data from 18 participants in an interim analysis of the first set of patients in SHINE (part A). Untargeted mass spectrometry-based discovery proteomics detects >2000 proteins in patient CSF and has documented utility in accelerating the identification of novel AD biomarkers reflective of diverse pathophysiologies beyond amyloid and tau, and enabling identification of pharmacodynamic biomarkers in longitudinal interventional trials. We leveraged this technique to analyze CSF samples taken at baseline and after 6 months of CT1812 treatment. Proteome-wide protein levels were detected using tandem mass tag-mass spectrometry (TMT-MS), change from baseline was calculated for each participant, and differential abundance analysis by treatment group was performed. This analysis revealed a set of proteins significantly impacted by CT1812, including pathway engagement biomarkers (i.e., biomarkers tied to S2R biology) and disease modification biomarkers (i.e., biomarkers with altered levels in AD vs. healthy control CSF but normalized by CT1812, and biomarkers correlated with favorable trends in ADAS-Cog11 scores). Brain network mapping, Gene Ontology, and pathway analyses revealed an impact of CT1812 on synapses, lipoprotein and amyloid beta biology, and neuroinflammation. Collectively, the findings highlight the utility of this method in pharmacodynamic biomarker identification and providing mechanistic insights for CT1812, which may facilitate the clinical development of CT1812 and enable appropriate pre-specification of biomarkers in upcoming clinical trials of CT1812.

CT1812 biomarker signature from a meta-analysis of CSF proteomic findings from two Phase 2 clinical trials in Alzheimer's disease.

INTRODUCTION: CT1812 is in clinical development for the treatment of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) exploratory proteomics was employed to identify pharmacodynamic biomarkers of CT1812 in mild to moderate AD from two independent clinical trials. METHODS: Unbiased analysis of tandem-mass tag mass spectrometry (TMT-MS) quantitative proteomics, pathway analysis and correlation analyses with volumetric magnetic resonance imaging (vMRI) were performed for the SPARC cohort (NCT03493282). Comparative analyses and a meta-analysis with the interim SHINE cohort (NCT03507790; SHINE-A) followed by network analysis (weighted gene co-expression network analysis [WGCNA]) were used to understand the biological impact of CT1812. RESULTS: CT1812 pharmacodynamic biomarkers and biological pathways were identified that replicate across two clinical cohorts. The meta-analysis revealed novel candidate biomarkers linked to S2R biology and AD, and network analysis revealed treatment-associated networks driven by S2R.  DISCUSSION: Early clinical validation of CT1812 candidate biomarkers replicating in independent cohorts strengthens the understanding of the biological impact of CT1812 in patients with AD, and supports CT1812's synaptoprotective mechanism of action and its continued clinical development. HIGHLIGHTS: This exploratory proteomics study identified candidate biomarkers of CT1812 in SPARC (NCT03493282) Comparative analyses identified biomarkers replicating across trials/cohorts Two independent Ph2 trial cohorts (SPARC and interim SHINE [NCT03507790; SHINE-A]) were used in a meta-analysis Amyloid beta (Aß) & synaptic biology impacted by CT1812 and volumetric magnetic resonance imaging (vMRI) treatment-related correlates emerge Network analyses revealed sigma-2 receptor (S2R)-interacting proteins that may be "drivers" of changes.

Combination of naproxen and a chemically-stable eicosapentaenoic acid analog provide additive tumor protection in Pirc rats.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Patients with the genetic disorder Familial Adenomatous Polyposis (FAP) develop hundreds to thousands of polyps that unless removed by prophylactic colectomy will progress to CRC at an early age. Nonsteroidal anti-inflammatory drugs (NSAIDs) and the ω-3 polyunsaturated fatty acid (PUFA) eicosapentaenoic acid (EPA), have been evaluated for their chemopreventive potential in delaying CRC onset in high-risk patients. In our study, we determined whether the NSAID, naproxen, alone or in combination with a chemically-stable EPA analog (TP-252), affects tumor formation in the ApcPirc rat model. When compared to control diet, animals fed naproxen or HD TP-252 had 66% and 82% fewer tumors, respectively. However, animals fed a combination of naproxen and HD TP-252, exhibited a 95% reduction in tumor formation and a 98% reduction in tumor volume, respectively. To elucidate potential mechanisms of tumor protection, a comprehensive, targeted lipidomic analysis was performed on colonic mucosa to determine changes in eicosanoid metabolism. Animals receiving TP-252 alone or in combination with naproxen had significantly reduced mucosal levels of proinflammatory ω-6 eicosanoids (PGE2 , 5-HETE and 14,15-DiHETrE), along with a simultaneous increase in anti-inflammatory EPA-derived ω-3 eicosanoids. A comprehensive lipidomic analysis also uncovered several potential pharmacodynamic (PD) lipid biomarkers, including resolvin E2, 9-HEPE, 12-HEPE and 18-HEPE, that were significantly correlated with tumor protection. Further studies with this drug combination should be focused on dose optimization and the role of EPA-derived lipid mediators in CRC initiation and progression.

Blood biomarkers in ALS: challenges, applications and novel frontiers.

Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disease among adults. With diagnosis reached relatively late into the disease process, extensive motor cell loss narrows the window for therapeutic opportunities. Clinical heterogeneity in ALS and the lack of disease-specific biomarkers have so far led to large-sized clinical trials with long follow-up needed to define clinical outcomes. In advanced ALS patients, there is presently limited scope to use imaging or invasive cerebrospinal fluid (CSF) collection as a source of disease biomarkers. The development of more patient-friendly and accessible blood biomarker assays is hampered by analytical hurdles like the matrix effect of blood components. However, blood also provides the opportunity to identify disease-specific adaptive changes of the stoichiometry and conformation of target proteins and the endogenous immunological response to low-abundance brain peptides, such as neurofilaments (Nf). Among those biomarkers under investigation in ALS, the change in concentration before or after diagnosis of Nf has been shown to aid prognostication and to allow the a priori stratification of ALS patients into smaller sized and clinically more homogeneous cohorts, supporting more affordable clinical trials. Here, we discuss the technical hurdles affecting reproducible and sensitive biomarker measurement in blood. We also summarize the state of the art of non-CSF biomarkers in the study of prognosis, disease progression, and treatment response. We will then address the potential as disease-specific biomarkers of the newly discovered cryptic peptides which are formed down-stream of TDP-43 loss of function, the hallmark of ALS pathobiology.

Clinical utility of serum biomarkers in Duchenne muscular dystrophy.

Assessments of disease progression and response to therapies in Duchenne muscular dystrophy (DMD) patients remain challenging. Current DMD patient assessments include complex physical tests and invasive procedures such as muscle biopsies, which are not suitable for young children. Defining alternative, less invasive and objective outcome measures to assess disease progression and response to therapy will aid drug development and clinical trials in DMD. In this review we highlight advances in development of non-invasive blood circulating biomarkers as a means to assess disease progression and response to therapies in DMD.

The FDA's New Guideline "Generally Accepted Scientific Knowledge" (GASK): An Opportunity to Expedite the Approval of Biosimilars.

The US FDA's new guideline suggests using "Generally Accepted Science Knowledge" (GASK) to develop nonclinical testing protocols for developing drugs and biologicals to remove unnecessary testing. Interpreting acceptable scientific knowledge as a rational approach has motivated the author to suggest substantial changes to the development of biosimilars, as demonstrated in this paper. The FDA can accept these suggestions without requiring any legislative change to the Act that defines such requirements. Suggested here is the waiving of clinical efficacy testing due to its lower sensitivity compared to analytical and functional testing and pharmacokinetic profiling. Also questioned is the need to test pharmacodynamic markers that do not correlate with clinical response and find new biomarkers requiring extensive testing to validate their use. Should the FDA accept these scientifically rational suggestions, it will significantly reduce the time and cost of approving biosimilars without safety or efficacy risk, as justified based on acceptable scientific knowledge and rationality.

A Critical Analysis of the FDA's Omics-Driven Pharmacodynamic Biomarkers to Establish Biosimilarity.

Demonstrating biosimilarity entails comprehensive analytical assessment, clinical pharmacology profiling, and efficacy testing in patients for at least one medical indication, as required by the U.S. Biologics Price Competition and Innovation Act (BPCIA). The efficacy testing can be waived if the drug has known pharmacodynamic (PD) markers, leaving most therapeutic proteins out of this concession. To overcome this, the FDA suggests that biosimilar developers discover PD biomarkers using omics technologies such as proteomics, glycomics, transcriptomics, genomics, epigenomics, and metabolomics. This approach is redundant since the mode-action-action biomarkers of approved therapeutic proteins are already available, as compiled in this paper for the first time. Other potential biomarkers are receptor binding and pharmacokinetic profiling, which can be made more relevant to ensure biosimilarity without requiring biosimilar developers to conduct extensive research, for which they are rarely qualified.

Evaluation of serum cytokines and acute phase proteins as possible pharmacodynamic biomarkers to monitor endoscopic remission during ustekinumab therapy in patients with Crohn's disease.

Background: Since not all Crohn's disease (CD) patients respond adequately to ustekinumab therapy, biomarkers could aid to monitor treatment response and optimize therapeutic outcomes. Objectives: To explore the dynamics of serum biomarker concentrations to monitor the response to ustekinumab treatment in CD patients. Design: Retrospective, exploratory study to evaluate concentrations of serum cytokines and acute phase proteins and their relation to endoscopic remission in CD patients during ustekinumab treatment. Methods: Serum concentrations of 16 proteins including cytokines and acute phase proteins were measured using the Mesoscale Discovery Platform in serum of healthy controls (n = 13), and CD patients (n = 61) at baseline (week 0), week 8 and week 24 during ustekinumab treatment. Endoscopic remission was defined as simple endoscopic score for CD (SES-CD) <3 after 6 months of therapy. Results: Absolute concentrations of serum amyloid A protein (SAA; week 8), IL-6 (week 24), AGP (weeks 8 and 24), interferon (IFN)-γ (weeks 8 and 24), lipopolysaccharide binding protein (LBP; weeks 8 and 24) and IL-22 (weeks 8 and 24) were significantly lower in endoscopic remitters compared to non-responders (p-values ranging between <0.001 and <0.05). SAA (week 8) and AGP (week 24) were the biomarkers with the highest area under the ROC curve (AUROC; 0.761 and 0.760, respectively) for identifying patients in endoscopic remission, though their performance was not superior to C-reactive protein (CRP) or faecal calprotectin. AUROCs of the predictive probability of biomarker combinations showed superiority in discriminating endoscopic remitters from non-responders in comparison to single biomarker measurements, but not as compared to faecal calprotectin. Conclusion: Although not superior to faecal calprotectin, measurement of AGP, SAA, LBF, IFN-γ, IL-6 and IL-22 concentrations, and combinations thereof with or without CRP and faecal calprotectin, during ustekinumab therapy might contribute to adequate monitoring of treatment response in CD patients.

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review.

OBJECTIVE: The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. METHODS: A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included. RESULTS: A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis." CONCLUSIONS: There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

A highly efficient protein corona-based proteomic analysis strategy for the discovery of pharmacodynamic biomarkers.

The composition of serum is extremely complex, which complicates the discovery of new pharmacodynamic biomarkers via serum proteome for disease prediction and diagnosis. Recently, nanoparticles have been reported to efficiently reduce the proportion of high-abundance proteins and enrich low-abundance proteins in serum. Here, we synthesized a silica-coated iron oxide nanoparticle and developed a highly efficient and reproducible protein corona (PC)-based proteomic analysis strategy to improve the range of serum proteomic analysis. We identified 1,070 proteins with a median coefficient of variation of 12.56% using PC-based proteomic analysis, which was twice the number of proteins identified by direct digestion. There were also more biological processes enriched with these proteins. We applied this strategy to identify more pharmacodynamic biomarkers on collagen-induced arthritis (CIA) rat model treated with methotrexate (MTX). The bioinformatic results indicated that 485 differentially expressed proteins (DEPs) were found in CIA rats, of which 323 DEPs recovered to near normal levels after treatment with MTX. This strategy can not only help enhance our understanding of the mechanisms of disease and drug action through serum proteomics studies, but also provide more pharmacodynamic biomarkers for disease prediction, diagnosis, and treatment.

Acute serum protein and cytokine response of single dose of prednisone in adult volunteers.

Pharmacological glucocorticoids are the most prescribed anti-inflammatory medications, and are chemical variants of cortisol, the circadian and stress hormone. Both endogenous and pharmacological glucocorticoids bind the glucocorticoid receptor (NR3C1) with high affinity, and both then bind downstream gene promoter elements (GRE) to drive positive gene transcription of many proteins. Glucocorticoid/GR complexes also bind distinct negative gene promoter elements (nGRE) to inhibit expression of genes involved in NF-κB innate immunity signaling. We sought to define the acute response of a single dose of prednisone (0.2 mg/kg) in young adult volunteers, with blood samples taken at baseline, 2, 3, 4 and 6 h post-oral dose. To control for circadian morning cortisol hitting the same molecular pathways, a day of blood draws was done without oral prednisone (same time of day), one day prior to drug day. Serum samples were processed for steroid hormone profiles (mass spectrometry; 9 steroidal hormones), proteomics (SOMAscan aptamer panels, 1,305 proteins), and inflammatory markers (Meso Scale Discovery; 10 pro-inflammatory cytokines). The pharmacological effect of the prednisone dose was shown by significant declines of adrenal steroids by 3 h after dosing. IL-10 showed drug-related increase to 4 hrs, then decrease to 6 hrs. IL-8 showed drug-related decrease in serum by 4 h, consistent with direct negative action of GR/ligand on IL-8 gene promoter. Proteomics data showed beta-2 microglobulin, TNFSF15, TSH, CST3, NBL1 to show time-related decreases with prednisone, while CXCL13 showed increases, although these require validation. In summary, a single low dose of prednisone leads to broad suppression of the adrenal axis within 3 h, and down-regulation of inflammatory serum proteins by 6 h.

Pharmacodynamic biomarkers for quantifying the mycobacterial effect of high doses of rifampin in patients with rifampin-susceptible pulmonary tuberculosis.

Background: Suboptimal drug exposure in patients with drug-susceptible tuberculosis (DS-TB) can drive treatment failure. Pharmacodynamics (PD) biomarkers such as the plasma TB drug-activity (TDA) assay may guide dose finding studies and predict microbiological outcomes differently than conventional indices. Methods: A study was nested from phase 2b randomized double-blind controlled trial of Tanzanian patients who received a 600 mg, 900 mg, or 1200 mg with a standard dose for DS-TB. Serum at 6 weeks collected over 24-h at 2-h intervals was collected for rifampin area under the concentration-time curve relative to minimum inhibitory concentration (AUC0-24/MIC) or peak concentration and MIC (Cmax/MIC). TDA was the ratio of time-to-positive growth of the patient's Mycobacterium tuberculosis isolates with and without coculture of patient's plasma collected at Cmax. Spearman's rank correlation (r) between PD parameters and culture convention on both liquid and solid culture media. Results: Among 10 patients, 600 mg (3), 900 mg (3), and 1200 mg (4) of rifampin dosages. The mean ± standard deviation (SD) of AUC0-24/MIC for patients on 600 mg was 168 ± 159 mg·h/L, on 900 mg was 169 ± 166 mg·h/L, and on 1200 mg was 308 ± 238 mg·h/L. The mean-TDA (SD) was 2.56 (±0.75), 1.5 (±0.59), and 2.29 (±1.08) for patients on 600 mg, 900 mg, and 1200 mg rifampin doses, respectively. Higher TDA values correlated with faster time to culture convention on both liquid (r = -0.55, P = 0.099) and solid media (r = -0.65, P = 0.04). Conclusions: TDA and rifampin AUC0-24/MIC did not trend as expected with rifampin dose, but TDA better predicted the time to sputum culture conversion. TDA may provide additional discrimination in predicting treatment response for some regimens distinct from plasma exposure relative to MIC or mg/kg dose.

Serum protein biomarkers for juvenile dermatomyositis: a pilot study.

BACKGROUND: Blood accessible biomarkers to assess disease activity and their response to therapies in Juvenile Dermatomyositis (JDM) are urgently needed. This pilot study aims to identify serum protein biomarkers associated with clinical disease activity in untreated JDM and their response to medical therapy. METHODS: SomaScan® technology screened JDM patients for 1305 proteins at three points: 1) before start of treatment, 2) while on therapy, and 3) after treatment tapering when patients were clinically inactive. To define disease associated biomarkers, SomaScan® data from untreated JDM patients (n = 8) were compared to SomaScan® data from an independent age-matched healthy control group (n = 12). Longitudinal analysis defined treatment responsive proteins at three time points: untreated (7 samples), treated (7 samples), and clinically inactive (6 samples). To confirm the SomaScan® data, a subset of nine candidate proteins (CXCL11, IL-17B, IL-17D, IL-22, CXCL10, MCP-1, ANGPT2, MIF, IL-23) were tested by ELISA after adding 2 JDM (one untreated, one clinically inactive) serum samples to the same group of JDM girls (8 untreated, 7 treated; 7 clinically inactive) as well as with 17 age, gender, matched healthy controls. RESULTS: Comparison of untreated JDM versus healthy controls identified 202 elevated and 49 decreased serum proteins in JDM patients with an adjusted p-value < 0.001. Only 82 out of 251 identified biomarker candidates responded to treatment while 12 out of these 82 proteins returned to their original untreated disease levels upon therapy tapering. The ELISA testing of the untreated samples for nine candidate proteins confirmed previously known biomarkers (CXCL10 or IP-10, CXCL11 or I-TAC and MCP-1) and identified novel biomarkers including IL-22, Angiopoetin-2, and IL-17B in a cross-sectional analysis comparing 8 untreated JDM and 17 age/gender matched controls. The subsequent longitudinal data by ELISA were not concordant for some biomarkers (IL-22 and IL-17B), but the other biomarkers either normalized or rebounded concordantly. CONCLUSIONS: Blood accessible protein biomarkers reflecting JDM pathophysiology were identified; some of them rebounded after therapy was tapered. Further studies bridging these biomarkers to specific clinical features of JDM are required to confirm the clinical utility of these serum protein biomarkers.

Comparison of Serum Pharmacodynamic Biomarkers in Prednisone-Versus Deflazacort-Treated Duchenne Muscular Dystrophy Boys.

Prednisone (Pred) and Deflazacort (Dfz) are commonly used glucocorticoids (GCs) for Duchenne muscular dystrophy (DMD) treatment and management. While GCs are known to delay the loss of ambulation and motor abilities, chronic use can result in onerous side effects, e.g., weight gain, growth stunting, loss of bone density, etc. Here, we use the CINRG Duchenne natural history study to gain insight into comparative safety of Pred versus Dfz treatment through GC-responsive pharmacodynamic (PD) biomarkers. Longitudinal trajectories of SOMAscan® protein data obtained on serum of DMD boys aged 4 to 10 (Pred: n = 7; Dfz: n = 8) were analyzed after accounting for age and time on treatment. Out of the pre-specified biomarkers, seventeen candidate proteins were differentially altered between the two drugs (p < 0.05). These include IGFBP-2 and AGER associated with diabetes complications, and MMP-3 associated with extracellular remodeling. As a follow-up, IGFBP-2, MMP-3, and IGF-I were quantified with an ELISA using a larger sample size of DMD biosamples (Dfz: n = 17, Pred: n = 12; up to 76 sera samples) over a longer treatment duration. MMP-3 and IGFBP-2 validated the SOMAscan® signal, however, IGF-I did not. This study identified GC-responsive biomarkers, some associated with safety, that highlight differential PD response between Dfz and Pred.

Identification of pharmacodynamic biomarkers and common molecular mechanisms of response to genotoxic agents in cancer cell lines.

PURPOSE: Genotoxic agents (GAs) including cisplatin, doxorubicin, gemcitabine, and topotecan are often used in cancer treatment. However, the response to GAs is variable among patients and predictive biomarkers are inadequate to select patients for treatment. Accurate and rapid pharmacodynamics measures of response can, thus, be useful for monitoring therapy and improve clinical outcomes. METHODS: This study focuses on integrating a database of genome-wide response to treatment (The NCI Transcriptional Pharmacodynamics Workbench) with a database of baseline gene expression (GSE32474) for the NCI-60 cell lines to identify mechanisms of response and pharmacodynamic (PD) biomarkers. RESULTS AND CONCLUSIONS: Our analysis suggests that GA-induced endoplasmic reticulum (ER) stress may signal for GA-induced cell death. Reducing the uptake of GA, activating DNA repair, and blocking ER-stress induction cooperate to prevent GA-induced cell death in the GA-resistant cells. ATF3, DDIT3, CARS, and PPP1R15A appear as possible candidate PD biomarkers for monitoring the progress of GA treatment. Further validation studies on the proposed intrinsic drug-resistant mechanism and candidate genes are needed using in vivo data from either patient-derived xenograft models or clinical chemotherapy trials.

Exosomal miRNAs as Novel Pharmacodynamic Biomarkers for Cancer Chemopreventive Agent Early Stage Treatments in Chemically Induced Mouse Model of Lung Squamous Cell Carcinoma.

BACKGROUND: Chemopreventive agent (CPA) treatment is one of the main preventive options for lung cancer. However, few studies have been done on pharmacodynamic biomarkers of known CPAs for lung cancer. MATERIALS AND METHODS: In this study, we treated mouse models of lung squamous cell carcinoma with three different CPAs (MEK inhibitor: AZD6244, PI-3K inhibitor: XL-147 and glucocorticoid: Budesonide) and examined circulating exosomal miRNAs in the plasma of each mouse before and after treatment. RESULTS: Compared to baselines, we found differentially expressed exosomal miRNAs after AZD6244 treatment (n = 8, FDR < 0.05; n = 55, raw p-values < 0.05), after XL-147 treatment (n = 4, FDR < 0.05; n = 26, raw p-values < 0.05) and after Budesonide treatment (n = 1, FDR < 0.05; n = 36, raw p-values < 0.05). In co-expression analysis, we found that modules of exosomal miRNAs reacted to CPA treatments differently. By variable selection, we identified 11, 9 and nine exosomal miRNAs as predictors for AZD6244, XL-147 and Budesonide treatment, respectively. Integrating all the results, we highlighted 4 miRNAs (mmu-miR-215-5p, mmu-miR-204-5p, mmu-miR-708-3p and mmu-miR-1298-5p) as the key for AZD6244 treatment, mmu-miR-23a-3p as key for XL-147 treatment, and mmu-miR-125a-5p and mmu-miR-16-5p as key for Budesonide treatment. CONCLUSIONS: This is the first study to use circulating exosomal miRNAs as pharmacodynamic biomarkers for CPA treatment in lung cancer.

1H NMR-based metabonomic revealed protective effect of Moutan Cortex charcoal on blood-heat and hemorrhage rats.

Moutan Cortex charcoal (MCC), the processed root bark of Paeonia suff ;ruticosa Andrews (Paeoniaceae), is a kind of traditional Chinese medicine (TCM) and has been used for treating blood-heat and hemorrhage(BHH)syndrome in China for thousands of years. In order to explore potential metabolic mechanism, 1H NMR-based metabonomics technique was applied to evaluate the effect of MCC on metabolic changes in plasma and urine of BHH rat models. Serum and urine samples were obtained from male SD rats with normal group, model group and MCC group for study. Based on 1H NMR spectra obtained from plasma and urine samples, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing the three group. And the 13 pharmacodynamic biomarkers of MCC were identified in the plasma and urine. The results showed that BHH induced great metabolic disorders in plasma and urine metabolisms. However, MCC could reverse the imbalanced metabolites by alanine, aspartate and glutamate metabolism and citrate cycle (TCA cycle) pathway, and its effect was also confirmed by the general signs and pharmacodynamics assessments. The results indicated that NMR-based metabolomic profiling method is sensitive and specific enough to evaluate the MCC efficacy and mechanism of action on BHH syndromes.

Biomarkers of Duchenne muscular dystrophy: current findings.

Numerous biomarkers have been unveiled in the rapidly evolving biomarker discovery field, with an aim to improve the clinical management of disorders. In rare diseases, such as Duchenne muscular dystrophy, this endeavor has created a wealth of knowledge that, if effectively exploited, will benefit affected individuals, with respect to health care, therapy, improved quality of life and increased life expectancy. The most promising findings and molecular biomarkers are inspected in this review, with an aim to provide an overview of currently known biomarkers and the technological developments used. Biomarkers as cells, genetic variations, miRNAs, proteins, lipids and/or metabolites indicative of disease severity, progression and treatment response have the potential to improve development and approval of therapies, clinical management of DMD and patients' life quality. We highlight the complexity of translating research results to clinical use, emphasizing the need for biomarkers, fit for purpose and describe the challenges associated with qualifying biomarkers for clinical applications.

Pan-Cancer Metabolic Signature Predicts Co-Dependency on Glutaminase and De Novo Glutathione Synthesis Linked to a High-Mesenchymal Cell State.

The enzyme glutaminase (GLS1) is currently in clinical trials for oncology, yet there are no clear diagnostic criteria to identify responders. The evaluation of 25 basal breast lines expressing GLS1, predominantly through its splice isoform GAC, demonstrated that only GLS1-dependent basal B lines required it for maintaining de novo glutathione synthesis in addition to mitochondrial bioenergetics. Drug sensitivity profiling of 407 tumor lines with GLS1 and gamma-glutamylcysteine synthetase (GCS) inhibitors revealed a high degree of co-dependency on both enzymes across indications, suggesting that redox balance is a key function of GLS1 in tumors. To leverage these findings, we derived a pan-cancer metabolic signature predictive of GLS1/GCS co-dependency and validated it in vivo using four lung patient-derived xenograft models, revealing the additional requirement for expression of GAC above a threshold (log2RPKM + 1 ≥ 4.5, where RPKM is reads per kilobase per million mapped reads). Analysis of the pan-TCGA dataset with our signature identified multiple indications, including mesenchymal tumors, as putative responders to GLS1 inhibitors.

Immuno-pharmacodynamics for evaluating mechanism of action and developing immunotherapy combinations.

Immunotherapy has become a major modality of cancer treatment, with multiple new classes of immunotherapeutics recently entering the clinic and obtaining market approval from regulatory agencies. While the promise of these therapies is great, so is the number of possible combinations not only with each other but also with small molecule therapeutics. Furthermore, the observation of unusual dose-response relationships suggests a critical dependency of drug effectiveness on the dosage regimen (dose and schedule). Clinical pharmacodynamic (PD) biomarkers will be useful endpoints for confirming drug mechanism of action, evaluating combination therapies for synergy or antagonism, and identifying optimal dosage regimens. In contrast to conventional PD in which drug action occurs entirely within a single target cell (ie, is self-contained within the malignant cell), immunotherapy involves a complex mechanism of action with sequential steps that propagate through multiple cell types, both normal and malignant. Its intercellular pharmacology begins with molecular target engagement either on an immune effector cell or a malignant cell, followed by stimulatory biochemical and biological signals in immune effector cells, and then finally ends with activation of cell death mechanisms in malignant cells lying within a certain distance from the activated effector cells (immune cell-tumor cell proximity). Evaluating such "trans-cellular pharmacology," in which different steps of drug action are distributed across multiple cell types, requires novel microscopy and image analysis tools capable of quantifying PD-biomarker responses, mapping the responses onto the cellular geography of the tumor using phenotypic biomarkers to identify specific cell types, and finally analyzing the spatial relationships between biomarkers in the context of each cell's biological role. We have termed this form of nearest neighbor image analysis of drug action "proximity PD microscopy," to indicate the importance of the location of the PD-biomarker response within the cellular landscape of a tumor specimen. We discuss herein the major modes of immunotherapy, and lay out a blueprint for using PD assessment to optimize dosage regimens of single agents and guide development of combination immunotherapy regimens, using PD1/PD-L1 immune checkpoint inhibition as a case study.