SEARCH · Search bioRxiv

Results for “clinical trials”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43Linked to original sources

bioRxiv2021

Hepatoblastomas with carcinoma features (HBCs) represent a biological spectrum of aggressive neoplasms in children and young adults

Malignant hepatocellular cancers are the most common primary liver malignancies in children, and hepatoblastomas (HBs) account for more than two-thirds of these cases. While most HBs respond to chemotherapy and have favorable outcomes, the 3-year overall survival rate for high-risk HBs is below 50% and guidelines for their classification and treatment are still evolving. HB risk-stratification efforts using clinical, histological, and molecular parameters have been reported to help identify patients that require more or less aggressive therapies in retrospective studies, and are being validated in clinical trials. However, risk assessment is particularly challenging for cancers with certain histologies, including tumors in the recently proposed provisional hepatocellular neoplasm not otherwise specified (HCN NOS) category. HCN NOSs exhibit either intermediate or combined HB and hepatocellular carcinoma (HCC) histological features, and while neoplasms with such features were observed over a decade ago, only a handful have been characterized and little is known about their biology and clinical features. Here, we molecularly characterized a series of clinically annotated HCN NOSs that demonstrated either intermediate HB/HCC histology or distinct coexisting areas with HB and HCC histological features. In addition, molecular profiling of HBs demonstrating focal pleomorphism or anaplasia (HB FPA) revealed underlying biological features previously observed in HCCs. Our study suggested that HCN NOSs and HB FPAs are aggressive tumors, irrespective of patient age or resectability. Consequently, we designated them collectively as HBs with carcinoma features (HBCs) and outlined histological and molecular characteristics for their diagnosis and treatment. In our single-institution study, transplanted HBC patients were significantly and more than twice as likely to have good outcomes, highlighting the importance of molecular testing and aggressive early intervention.

cancer biology↗

bioRxiv2023

Aminobisphosphonates reactivate the latent reservoir in people living with HIV-1

Antiretroviral therapy (ART) is not curative due to the existence of cellular reservoirs of latent HIV-1 that persist during therapy. Current research efforts to cure HIV-1 infection include "shock and kill" strategies to disrupt latency using small molecules or latency-reversing agents (LRAs) to induce expression of HIV-1 enabling cytotoxic immune cells to eliminate infected cells. The modest success of current LRAs urges the field to identify novel drugs with increased clinical efficacy. Aminobisphosphonates (N-BPs) that include pamidronate, zoledronate, or alendronate, are the first-line treatment of bone-related diseases including osteoporosis and bone malignancies. Here, we show the use of N-BPs as a novel class of LRA: we found in ex vivo assays using primary cells from ART-suppressed people living with HIV-1 that N-BPs induce HIV-1 from latency to levels that are comparable to the T cell activator phytohemagglutinin (PHA). RNA sequencing and mechanistic data suggested that reactivation may occur through activation of the activator protein 1 signaling pathway. Stored samples from a prior clinical trial aimed at analyzing the effect of alendronate on bone mineral density, provided further evidence of alendronate-mediated latency reversal and activation of immune effector cells. Decay of the reservoir measured by IPDA was however not detected. Our results demonstrate the novel use of N-BPs to reverse HIV-1 latency while inducing immune effector functions. This preliminary evidence merits further investigation in a controlled clinical setting possibly in combination with therapeutic vaccination.

microbiology↗

bioRxiv2019

Deep phenotyping of a healthy human HAO1 knockout informs therapeutic development for primary hyperoxaluria type 1.

Primary Hyperoxaluria Type 1 (PH1) is a rare autosomal recessive metabolic disorder of oxalate metabolism leading to kidney failure as well as multi-organ damage. Overproduction of oxalate occurs in the liver due to an inherited genetic defect in the enzyme alanine-glyoxylate aminotransferase (AGXT), causing pathology due to the insolubility of calcium oxalate crystals in body fluids. The main current therapy is dual liver-kidney transplant, which incurs high morbidity and has poor availability in some health systems where PH1 is more prevalent. One approach currently in active clinical investigation targets HAO1 (hydroxyacid oxidase 1), encoding glycolate oxidase, to reduce substrate levels for oxalate production. To inform drug development, we sought individuals with reduced HAO1 function due to naturally occurring genetic variation.\n\nAnalysis of loss of function variants in 141,456 sequenced individuals suggested individuals with complete HAO1 knockout would only be observed in 1 in 30 million outbred people. However in a large sequencing and health records program (Genes & Health), in populations with substantial autozygosity, we identified a healthy adult individual predicted to have complete knockout of HAO1 due to an ultra rare homozygous frameshift variant (rs1186715161, ENSP00000368066.3:p.Leu333SerfsTer4). Primary care and hospital health records confirmed no apparently related clinical phenotype. At recall, urine and plasma oxalate levels were normal, however plasma glycolate levels (171 nmol/mL) were 12 times the upper limit of normal in healthy, reference individuals (mean+2sd=14 nmol/mL, n=67) while her urinary glycolate levels were 6 times the upper limit of normal. Comparison with preclinical and phase 1 clinical trial data of an RNAi therapeutic targeting HAO1 (lumasiran) suggests the individual likely retains <2% residual glycolate oxidase activity.\n\nThese results provide important data to support the safety of HAO1 inhibition as a potential chronic therapy for a devastating metabolic disease (PH1). We also suggest that the effect of glycolate oxidase suppression in any potential other roles in humans beyond glycolate oxidation do not lead to clinical phenotypes, at least in this specific individual. This demonstrates the value of studying the lifelong complete knockdown of a target protein in a living human to aid development of a potential therapeutic, both in de-risking the approach and providing potential hypotheses to optimize its development. Furthermore, therapy for PH1 is likely to be required lifelong, in contrast to data from chronicity studies in non-human species or relatively short-term therapeutic studies in people. Our approach demonstrates the potential for improved drug discovery through unlocking relevant evidence hiding in the diversity of human genetic variation.

genetics↗

bioRxiv2025

Eg5 Inhibitor SB743921 Causes p53-Dependent Cell Cycle Arrest, Senescence and Death in Tumor Cells

Mitotic inhibitors, such as Vinca alkaloids and taxanes, are one of the most effective chemotherapeutic agents used in the clinic. Despite their advantages, there are drawbacks to their use - primarily development of resistance and a high rate of side-effects, including damage to non-proliferating tissues. A range of new inhibitors targeting mitosis, whose activity does not depend on the binding to tubulin, are currently tested in clinical trials. Among such agents, inhibitors of Eg5 kinesin are highly promising due to their high activity and specificity. Here we show that compared to other drugs that target mitosis, an Eg5 inhibitor, SB743921, preferentially eliminates TP53-mutated cells and induces irreversible senescence, even after the drug washout, regardless of the p53 status. These effects are not defined by the immediate block of mitosis where SB743921 and a clinically used mitotic inhibitor Ixabepilone induce similar rates of mitotic arrest, apoptosis and induction of p53 and p21, but rather a long-term reaction, with absence of proteins required for replication, such as Cyclin A, E2F1, pRB. While after the washout Ixabepilone-treated cells can exit senescence and resume proliferation, cells treated with SB743921 did not exit the senescent state and did not resume proliferation as based on SA-{beta}-galactosidase staining and EdU incorporation. The remaining senescent cells were effectively eliminated by Bcl2/Bcl-xL/Bcl- w inhibitor ABT-263, showing a potential of the combinational therapy with senolytic drugs. In total, we show the capacity of Eg5-targeting drugs for therapy of high-risk TP53-mutated tumors, which are potentially resistant to clinically approved mitotic inhibitors.

cancer biology↗

bioRxiv2025

Identifiability-Guided Assessment of Digital Twins in Alzheimer's Disease Clinical Research and Care

Digital twins - personalized, data-driven computational models - are emerging as a powerful paradigm for representing and predicting disease trajectories at the individual level. These models have the potential to support diagnosis, monitor disease evolution, and evaluate therapeutic interventions in virtual settings in the context of clinical trials and patient care. Rigorous model assessment is thus critical for its implementation, but medical data are often sparse, noisy, and vary significantly across individuals, making it challenging to determine whether a digital twin optimized on such data is valid. In such settings, identifiability analysis becomes essential for evaluating whether model parameters can be reliably estimated and interpreted. To address this, we investigate how identifiability can support the clinical application of a computational causal digital twin model for Alzheimers Disease (AD), where data sparsity and variability are particularly pronounced. Our results show that the magnitude and distribution of biomarker data influence the parameter practical identifiability, and that constraints on the model structure and parameters can significantly affect identifiability. We also observe differences in identifiability across diagnostic groups, with several parameters showing significantly different values between individuals with AD, mild cognitive impairment (MCI), and cognitively normal (CN) subjects. Uncertainty quantification for identifiable parameters and their corresponding model trajectories provides visual insight into variability in disease progression and reveals mild trends related to biomarker data spread. This study represents a first step toward incorporating identifiability techniques into clinical digital twin frameworks, using a data-driven, interpretable example based on a previously published AD model.

neuroscience↗

bioRxiv2019

Physical activity interventions for major chronic disease: a matched-pair analysis of Cochrane and non-Cochrane systematic reviews

ObjectiveTo assess the degree of concordance between Cochrane and non-Cochrane systematic reviews with meta-analyses of physical activity interventions.\n\nStudy Design and SettingWe conducted a matched-pair analysis with individual meta-analyses as the unit of analysis, comparing Cochrane reviews of randomised controlled trials of physical activity interventions with non-Cochrane reviews. Meta-analyses were matched based on the intervention, condition, outcome and publication year. Matched pairs were contrasted statistically in terms of differences between effect estimates, their precision, and number of citations using Wilcoxon two-sample test and agreement using Bland-Altman plots.\n\nResultsOur search yielded 24 matched meta-analyses. Matched pairs were similar in terms of the number of included studies, sample sizes and publication year but only half (51.7%) of 545 individual clinical trials were included in both the Cochrane and non-Cochrane paired reviews. Effect estimates from non-Cochrane reviews were larger for 15 (62.5%) pairs, smaller for 8 (33.3%) and equal to Cochrane reviews for one (4.2%) pair. On average, effect estimates from non-Cochrane reviews were 0.12 log units (or 13%) higher compared with matched Cochrane reviews (z-score -2.312, P=0.012). We observed discrepancies with regard to the statistical (n=6) and clinical interpretation (n=4) of effect estimates, with non-Cochrane reviews reporting more often a statistically significant result (4/6) and effect sizes favouring intervention of greater than a two-fold (4/4) compared with Cochrane matches. Non-Cochrane reviews were also more frequently cited irrespective of whether the results agree or disagree in their statistical conclusion but this finding did not reach statistical significance at the traditional 0.05 threshold.\n\nConclusionOn average, meta-analyses from non-Cochrane reviews reported higher effect estimates and were more likely to show significant effects favouring the intervention compared with meta-analyses from Cochrane reviews. Though differences were small, they were sufficient to result in important discrepancies in statistical and clinical interpretations between a number of reviews.\n\nWhat is new?Key findings:\n\nO_LIFindings demonstrate non-Cochrane reviews on average report larger effect estimates and have discrepancies in statistical and clinical interpretation more likely to favour physical activity interventions. Potential sources underpinning discrepant review findings are explored in an accompanying sister paper.\nC_LI\n\nWhat this adds to what was known?\n\nO_LIThe first assessment of systematic differences between paired Cochrane and non-Cochrane meta-analyses examining the role of physical activity interventions for preventing and treating major chronic disease\nC_LI\n\nWhat is the implication and what should change now?\n\nO_LIAuthors should be aware of the need of protocol registration to minimise unnecessary duplication and be mindful of potential discrepant findings depending on the source of review evidence.\nC_LI

epidemiology↗

bioRxiv2022

Assessment of pre-clinical liver models based on their ability to predict the liver-tropism of AAV vectors

The liver is a prime target for in vivo gene therapies using recombinant adeno-associated viral vectors (rAAV). Multiple clinical trials have been undertaken for this target in the past 15 years, however we are still to see market approval of the first liver-targeted AAV-based gene therapy. Inefficient expression of the therapeutic transgene, vector-induced liver toxicity and capsid, and/or transgene-mediated immune responses reported at high vector doses are the main challenges to date. One of the contributing factors to the insufficient clinical outcomes, despite highly encouraging preclinical data, is the lack of robust, biologically- and clinically-predictive preclinical models. To this end, this study reports findings of a functional evaluation of six AAV vectors in twelve preclinical models of the human liver, with the aim to uncover which model is the most relevant for the selection of AAV capsid variant for safe and efficient transgene delivery to primary human hepatocytes. The results, generated by studies in models ranging from immortalized cells, iPSC-derived and primary hepatocytes, and primary human hepatic organoids to in vivo models, increased our understanding of the strengths and weaknesses of each system. This should allow the development of novel gene therapies targeting the human liver.

bioengineering↗

bioRxiv2025

Juvenile reinstatement of TCF4 in Pitt-Hopkins syndrome model mice reveals a critical window for genetic intervention

Pitt-Hopkins syndrome (PTHS) is a neurodevelopmental disorder caused by haploinsufficiency of TCF4 which encodes transcription factor 4. As PTHS therapeutics advance toward clinical trials, identifying the optimal timing for treatment is crucial. Our previous research demonstrated that restoring TCF4 during embryonic or neonatal stages, corresponding to prenatal or neonatal periods in humans, improved phenotypes in a PTHS mouse model (Kim et al., 2022). However, PTHS diagnosis generally occurs much later, when infants fail to reach developmental milestones and undergo genetic testing. This raises an essential question: can genetic therapeutics initiated at more clinically relevant time points retain effectiveness? Here, we examined whether reinstating TCF4 in juvenile PTHS model mice could reverse behavioral phenotypes, simulating a gene therapy. Our findings indicate that this delayed intervention largely fails to correct most phenotypes, except for a measure of cognitive function. These results reveal phenotype-specific plasticity and underscore a narrow, early critical window for effective treatment in PTHS. Our study also identifies the hippocampus as a potential target for PTHS therapeutics and suggests that while some cognitive functions may still retain therapeutic plasticity, reversing most core PTHS symptoms may require intervention during the very early postnatal, or potentially prenatal periods, in humans.

neuroscience↗

bioRxiv2021

A spatially resolved mechanistic growth law for cancer drug development.

Mathematical models used in pre-clinical drug discovery tend to be empirical growth laws. Such models are well suited to fitting the data available, mostly longitudinal studies of tumour volume, however, they typically have little connection with the underlying physiological processes. This lack of a mechanistic underpinning restricts their flexibility and inhibits their direct translation across studies including from animal to human. Here we present a mathematical model describing tumour growth for the evaluation of single agent cytotoxic compounds that is based on mechanistic principles. The model can predict spatial distributions of cell subpopulations and account for spatial drug distribution effects within tumours. Importantly, we demonstrate the model can be reduced to a growth law similar in form to the ones currently implemented in pharmaceutical drug development for pre-clinical trials so that it can integrated into the current workflow. We validate this approach for both cell-derived xenograft (CDX) and patient-derived xenograft (PDX) data. This shows that our theoretical model fits as well as the best performing and most widely used models. However, in addition the model is also able to accurately predict the observed growing fraction of tumours. Our work opens up current pre-clinical modelling studies to also incorporating spatially resolved and multi-modal data without significant added complexity and creates the opportunity to improve translation and tumour response predictions.

pharmacology and toxicology↗

bioRxiv2025

AI-Driven and 3D-Bioprinted New Approach Methodology (NAM) Identifies NEO100 as Potent Ultrasound-Activated Therapeutic for Primary and Metastatic Brain Tumors

Primary and metastatic brain tumors are among the deadliest and treatment-resistant cancers, mainly because of their inherent resistance to chemoradiation and limited drug delivery across the blood-brain barrier (BBB). Identifying molecules that can cross the BBB and serve as sonosensitizers is crucial for developing noninvasive, targeted therapies such as sonodynamic therapy (SDT). To overcome the limitations of traditional low-throughput screening, a New Approach Methodology (NAM) was developed, starting with AI-driven molecular discovery. A positive-unlabeled neural network, trained on over 200 molecular descriptors, was used to predict compounds likely to respond to focused ultrasound (FUS), penetrate the BBB, and mediate therapeutic sonodynamic activity. While AI helps prioritize potent candidates, effective SDT also depends on clinically scalable FUS delivery. Low-intensity FUS enables noninvasive activation of small molecules in the brain and has been validated in several clinical settings. Therefore, AI-guided predictions were combined with ultrasound-based sonodynamic testing using parameters relevant to human therapy. A major challenge in SDT development is the lack of rapid, physiologically relevant tumor models, as traditional 3D organoids take weeks to mature, delaying validation. To address this, a magnetic bioprinting platform was used to produce uniform 3D tumor spheroids within hours, enabling high-throughput screening of SDT. These spheroids replicate key microenvironmental gradients, supporting reliable ultrasound-driven cytotoxicity testing. Through this combined NAM pipeline, AI identified NEO100--an ultrapure, pharmaceutical-grade perillyl alcohol currently in Phase 2a clinical trials--as a promising sonosensitizer candidate. These predictions were validated in rapidly 3D bioprinted tumor models representing glioblastoma, Group 3 pediatric medulloblastoma, meningioma, and breast-to-brain and lung-to-brain metastases. In all tumor types, ultrasound activation significantly increased NEO100s cytotoxicity. Given its established safety profile in humans and ability to cross the BBB, NEO100 demonstrates how integrating AI-based molecular discovery, accelerated 3D bioprinting, and clinically relevant ultrasound parameters can rapidly advance precision sonodynamic therapies for various primary and metastatic brain cancers.

cancer biology↗

bioRxiv2024

ComputAgeBench: Epigenetic Aging Clocks Benchmark

The success of clinical trials of longevity drugs relies heavily on identifying integrative health and aging biomarkers, such as biological age. Epigenetic aging clocks predict the biological age of an individual using their DNA methylation profiles, commonly retrieved from blood samples. However, there is no standardized methodology to validate and compare epigenetic clock models as yet. We propose ComputAgeBench, a unifying framework that comprises such a methodology and a dataset for comprehensive benchmarking of different clinically relevant aging clocks. Our methodology exploits the core idea that reliable aging clocks must be able to distinguish between healthy individuals and those with aging-accelerating conditions. Specifically, we collected and harmonized 66 public datasets of blood DNA methylation, covering 19 such conditions across different ages, and tested 13 published clock models. Additionally, we compiled 46 separate datasets to facilitate the training of new aging clocks. We believe our work will bring the fields of aging biology and machine learning closer together for the research on reliable biomarkers of health and aging. Codehttps://github.com/ComputationalAgingLab/ComputAge Datasethttps://huggingface.co/datasets/computage/computage_bench

bioinformatics↗

bioRxiv2021

Immunogenicity and efficacy of the COVID-19 candidate vector vaccine MVA SARS 2 S in preclinical vaccination

The severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) has emerged as the infectious agent causing the pandemic coronavirus disease 2019 (COVID-19) with dramatic consequences for global human health and economics. Previously, we reached clinical evaluation with our vector vaccine based on vaccinia virus MVA against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes an infection in humans similar to SARS and COVID-19. Here, we describe the construction and preclinical characterization of a recombinant MVA expressing full-length SARS-CoV-2 spike (S) protein (MVA-SARS-2-S). Genetic stability and growth characteristics of MVA-SARS-2-S, plus its robust synthesis of S antigen, make it a suitable candidate vaccine for industrial scale production. Vaccinated mice produced S antigen-specific CD8+ T cells and serum antibodies binding to S glycoprotein that neutralized SARS-CoV-2. Prime-boost vaccination with MVA-SARS-2-S protected mice sensitized with a human ACE2-expressing adenovirus from SARS-CoV-2 infection. MVA-SARS-2-S is currently being investigated in a phase I clinical trial as aspirant for developing a safe and efficacious vaccine against COVID-19. Significance StatementThe highly attenuated vaccinia virus MVA is licensed as smallpox vaccine, and as vector it is a component of the approved Adenovirus-MVA-based prime-boost vaccine against Ebola virus disease. Here we provide results from testing the COVID-19 candidate vaccine MVA-SARS-2-S, a poxvirus-based vector vaccine that proceeded to clinical evaluation. When administered by intramuscular inoculation, MVA-SARS-2-S expresses and safely delivers the full-length SARS-CoV-2 spike (S) protein, inducing balanced SARS-CoV-2-specific cellular and humoral immunity, and protective efficacy in vaccinated mice. Substantial clinical experience has already been gained with MVA vectors using homologous and heterologous prime-boost applications, including the immunization of children and immunocompromised individuals. Thus, MVA-SARS-2-S represents an important resource for developing further optimized COVID-19 vaccines.

microbiology↗

bioRxiv2023

Large Scale Comparative Deconvolution Analysis of the Canine and Human Osteosarcoma Tumor Microenvironment Uncovers Conserved Clinically Relevant Subtypes

Osteosarcoma is a relatively rare but aggressive cancer of the bones with a shortage of effective biomarkers. Although less common in humans, Osteosarcomas are fairly common in adult pet dogs and have been shown to share many similarities with their human analogs. In this work, we analyze bulk transcriptomic data of 213 primary and 100 metastatic Osteosarcoma samples from 210 pet dogs enrolled in nation-wide clinical trials to uncover three Tumor Microenvironment (TME)-based subtypes: Immune Enriched (IE), Immune Enriched Dense Extra-Cellular Matrix-like (IE-ECM) and Immune Desert (ID) with distinct cell type compositions, oncogenic pathway activity and chromosomal instability. Furthermore, leveraging bulk transcriptomic data of canine primary tumors and their matched metastases from different sites, we characterize how the Osteosarcoma TME evolves from primary to metastatic disease in a standard of care clinical setting and assess its overall impact on clinical outcomes of canines. Most importantly, we find that TME-based subtypes of canine Osteosarcomas are conserved in humans and predictive of progression free survival outcomes of human patients, independently of known prognostic biomarkers such as presence of metastatic disease at diagnosis and percent necrosis following chemotherapy. In summary, these results demonstrate the power of using canines to model the human Osteosarcoma TME and discover novel biomarkers for clinical translation.

cancer biology↗

bioRxiv2024

Elucidation and Pharmacologic Targeting of Master Regulator Dependencies in Coexisting Diffuse Midline Glioma Subpopulations

Diffuse Midline Gliomas (DMGs) are universally fatal, primarily pediatric malignancies affecting the midline structures of the central nervous system. Despite decades of clinical trials, treatment remains limited to palliative radiation therapy. A major challenge is the coexistence of molecularly distinct malignant cell states with potentially orthogonal drug sensitivities. To address this challenge, we leveraged established network-based methodologies to elucidate Master Regulator (MR) proteins representing mechanistic, non-oncogene dependencies of seven coexisting subpopulations identified by single-cell analysis--whose enrichment in essential genes was validated by pooled CRISPR/Cas9 screens. Perturbational profiles of 372 clinically relevant drugs helped identify those able to invert the activity of subpopulation-specific MRs for follow-up in vivo validation. While individual drugs predicted to target individual subpopulations--including avapritinib, larotrectinib, and ruxolitinib--produced only modest tumor growth reduction in orthotopic models, systemic co-administration induced significant survival extension, making this approach a valuable contribution to the rational design of combination therapy.

systems biology↗

bioRxiv2019

Computed Tomography Measures of Inter-site tumor Heterogeneity for Classifying Outcomes in High-Grade Serous Ovarian Carcinoma: a Retrospective Study

AbstractO_ST_ABSBackgroundC_ST_ABSHigh grade serous ovarian carcinoma shows marked intra-tumoral heterogeneity which is associated with decreased survival and resistance to platinum-based chemotherapy. Pre-treatment quantification of spatial tumor heterogeneity by multiple tissue sampling is not clinically feasible. Using standard-of-care CT imaging to non-invasively quantify heterogeneity could have high clinical utility and would be highly cost-effective. Texture analysis measures local variations in computed tomography (CT) image intensity. Haralick texture methods are typically used to capture the heterogeneity of entire lesions; however, this neglects the possible presence of texture habitats within the lesion, and the differences between metastatic sites. The primary aim of this study was to develop texture analysis of intra-site and inter-site spatial heterogeneity from standard-of-care CT images and to correlate these measures with clinical and genomic features in patients with HGSOC. Methods and findingsWe analyzed the data from a retrospective cohort of 84 patients with HGSOC consisting of 46 patients from Memorial Sloan Kettering Cancer Center (MSKCC) and 38 non-MSKCC cases selected from The Cancer Imaging Archive (TCIA). Inclusion criteria consisted of FIGO stage II-IV HGSOC, attempted primary cytoreductive surgery, intravenous contrast-enhanced CT of abdomen and pelvis performed prior to surgery and availability of molecular tumor data analysed as per the Cancer Genome Atlas (TCGA) Research Network ovarian cancer project. Manual segmentation and image analysis was performed on 463 metastatic tumor sites from 84 patients. In the MSKCC cohort the median number of tumor sites was 7 (interquartile range 5-9) and 4 (interquartile range 3-4) in the TCIA patients. Sub-regions were produced within each tumor site by grouping voxels with similar Haralick texture using the Kernel K-means method. We derived statistical measures of intra- and inter-site tumor heterogeneity (IISTH) including cluster sites entropy (cSE), cluster sites standard deviation (cluDev) and cluster sites dissimilarity (cluDiss) from sub-regions identified within and between individual tumor sites. Unsupervised clustering was used to group patient IISTH measures into low, medium, high, and ultra-high heterogeneity clusters from each cohort. The IISTH measure cluDiss was an independent predictor of progression-free survival (PFS) in multivariable analysis in both datasets (MSKCC hazard ratio [HR] 1.04, 95% CI 1.01-1.06, P = 0.002; TCIA HR 1.05, 95% CI 1.00-1.10, P = 0.049). Low and medium IISTH clusters were associated with longer PFS in multivariable analysis (MSKCC HR 2.94, 90% CI 1.29-6.70, P = 0.009, TCIA HR 5.94, 95% CI 1.05-33.6, P = 0.044). IISTH measures were robust to differences in the CT imaging systems. Average Haralick textures contrast (TCIA HR 1.08, 95% CI 1.01-1.10, P = 0.019) and homogeneity (TCIA HR 1.09, 95% CI 1.02-1.16, P = 0.008) were associated with PFS in mutivariate analysis only in the TCIA dataset. All other average Haralick textures and total tumor volume were not associated with PFS in either dataset. ConclusionsTexture measures of intra- and inter-site tumor heterogeneity from standard of care CT images are correlated with shorter PFS in HGSOC patients. These quantitative methods are independent of the CT imaging system and can thus be applied in clinical practice. The methodology proposed here enables the non-invasive quantification of intra-tumoral heterogeneity and disease stratification for future experimental medicine studies and clinical trials, particularly in cases where total tumour volume and averaged textures have low predictive power. Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LITumor heterogeneity is a feature of many solid malignancies including ovarian cancer. C_LIO_LIRecent genomic research suggests that intra-site tumor heterogeneity (heterogeneity within a single tumor site) and inter-site tumor heterogeneity (heterogeneity between different metastatic sites in the same patient) correlate with clinical outcome in HGSOC. C_LI What did the researchers do and find?O_LIWe developed quantitative and non-invasive image-analysis based measures for predicting outcome in HGSOC patients by combining image-based information from within and between multiple tumor sites. C_LIO_LIUsing datasets from two sources, we demonstrate that these image-based tumor heterogeneity measures predict progression free survival in patients with HGSOC. C_LI What do these findings mean?O_LINon-invasive measures of CT image heterogeneity may predict outcomes in HGSOC patients. C_LIO_LIWider application of these CT image heterogeneity measures could prove useful for stratifying patients to different therapies given that total tumour volume and averaged textures have low predictive power. C_LI

bioinformatics↗

bioRxiv2019

Cross Trial Meta and Time Series Pharmacodynamic Analyses of Apremilast Effects

Finding biomarkers that provide shared link between disease severity, drug-induced pharmacodynamic effects and response status in human trials can provide number of values for patient benefits: elucidating current therapeutic mechanism-of-action, and, back-translating to fast-track development of next-generation therapeutics. Both opportunities are predicated on proactive generation of human molecular profiles that capture longitudinal trajectories before and after pharmacological intervention. Here, we present the largest plasma proteomic biomarker dataset available to-date and the corresponding analyses from placebo-controlled Phase III clinical trials of the phosphodiesterase type 4 inhibitor apremilast in psoriasis (PSOR), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) from 526 subjects overall. Using approximately 150 plasma analytes tracked across three time points, we identified IL-17A and KLK-7 as biomarkers for disease severity and apremilast pharmacodynamic effect in psoriasis patients. Combined decline rate of KLK-7, PEDF, MDC and ANGPTL4 by Week 16 represented biomarkers for the responder subgroup, shedding insights into therapeutic mechanisms. In ankylosing spondylitis patients, IL-6 and LRG-1 were identified as biomarkers with concordance to disease severity. Apremilast-induced LRG-1 increase was consistent with the overall lack of efficacy in ankylosing spondylitis. Taken together, these findings expanded the mechanistic knowledge base of apremilast and provided translational foundations to accelerate future efforts including compound differentiation, combination, and repurposing.

bioinformatics↗

bioRxiv2022

Inhibition of DNA-PKcs impairs the activation and cytotoxicity of CD4+ helper and CD8+ effector T cells

Modulation of T cell activity is an effective strategy for the treatment of autoimmune diseases, immune-related disorders and cancer. This highlights a critical need for continued investigation of proteins that regulate T cell function. The kinase DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is emerging as a potent regulator of the immune system spurring interest in its use as a therapeutic target for immune-related diseases. In murine models of autoimmune disease including asthma and rheumatoid arthritis, treatment with small molecule DNA-PKcs inhibitors, which are in clinical trials for cancer therapy, decreased disease severity. Additionally, DNA-PKcs inhibitors reduced T cell-mediated graft rejection and extended graft survival in a murine allogenic skin graft rejection model. These in vivo studies suggest the therapeutic use of DNA-PKcs inhibitors for autoimmune and T cell-mediated disorders. In this study, we sought to further characterize the effects of DNA-PKcs inhibitors on T cells to better understand their clinical potential. We determined that pharmacological inhibition of DNA-PKcs abrogated activation of murine and human CD4+ and CD8+ T cells as evident by reduced expression of the activation markers CD69 and CD25. Furthermore, inhibition of DNA-PKcs impeded metabolic pathways and proliferation of anti-CD3/CD28 activated CD4+ and CD8+ T cells as well as peptide-stimulated OTI-CD8+ T cells. This reduced the ability of OTI-CD8+ T cells to kill cancer cells and the expression of IFN{gamma} and the cytotoxic genes eomes, perforin and granzyme B. These results suggest a novel role for DNA-PKcs in early T cell activation. Furthermore, our data support the therapeutic potential of DNA-PKcs inhibitors on diseases of immune dysregulation.

immunology↗

bioRxiv2025

A synbiotic medical food improves gut barrier function, reduces immune responses, and inhibits osteoclast activity in models of postmenopausal bone loss aligned with clinical outcomes

Over half of women above age 50 are affected by osteopenia or osteoporosis, boneloss conditions influenced by estrogen decline, inflammation, and the intestinal microbiota. Probiotic-based interventions have shown promise in preclinical osteoporosis models. In a recent randomized, double-blind, placebo-controlled clinical trial of postmenopausal women, dietary intervention with SBD111, a synbiotic medical food combining plant-derived probiotics and prebiotic fibers, reduced bone loss in women with osteopenia, elevated body mass index (BMI), and/or elevated body fat. To investigate potential mechanisms underlying these outcomes, we examined intestinal epithelial, immune, and osteoclast responses to SBD111 in vitro. SBD111 administration improved intestinal barrier integrity, reduced immune cell cytokine secretion, and inhibited osteoclast activity. These effects align with clinically observed reductions in severe gastrointestinal symptoms and bone resorption markers. Together, these findings suggest that SBD111 modulates the gut-bone axis via barrier, immune, and antiresorptive pathways, supporting its role in maintaining skeletal health in postmenopausal women. IRB StatementsThe study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of MaineHealth under protocol 1689738-1 (approved 12/29/2020) and 958914 (approved 05/31/2005). Human peripheral blood mononuclear cells (PBMCs) were purchased from Charles River Laboratories and collected under their IRB-approved protocol with informed consent for commercial research use. Informed Consent Statements Informed consent was obtained from all participants involved in the study. HighlightsO_LISBD111 synbiotic medical food improves intestinal barrier function C_LIO_LISBD111 reduces cytokine release from inflamed immune cells C_LIO_LIThis synbiotic medical food inhibits osteoclast activity in vitro C_LIO_LIIn vitro SBD111 effects align with clinical reductions in bone loss and CTX-1 C_LI Graphical Abstract. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/669142v1_ufig1.gif" ALT="Figure 1000"> View larger version (30K): org.highwire.dtl.DTLVardef@13b16dcorg.highwire.dtl.DTLVardef@59dfcaorg.highwire.dtl.DTLVardef@737e59org.highwire.dtl.DTLVardef@6c054a_HPS_FORMAT_FIGEXP M_FIG SBD111 synbiotic medical food reduces bone loss via barrier improvement, anti-inflammation, and osteoclast inhibition. (A) SBD111 improves barrier integrity in vitro. Visualized in the left panel, inflammation reduces intestinal epithelial barrier function, resulting in the influx of inflammatory mediators, thereby activating the immune system. The addition of SBD111, shown in purple (right), improves barrier function, reducing the ability of inflammatory mediators to cross the epithelial barrier. (B) SBD111 reduces inflammatory responses of inflamed immune cells in a concentration-dependent manner. Low concentrations of SBD111 induce inflammatory responses. At higher concentrations, fewer inflammatory cytokines are secreted. (C) SBD111-derived components/metabolites inhibit the activity of bone-resorbing osteoclasts and reduce their ability to degrade bone. Image created in https://BioRender.com C_FIG

immunology↗