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bioRxiv2021

A structured evaluation of cryopreservation in generating single cell transcriptomes from cerebrospinal fluid

ImportanceA robust cerebrospinal fluid (CSF) cell cryopreservation protocol using high resolution single-cell (sc) transcriptomic data would enable the deployment of this important modality in multi-center translational research studies and clinical trials in which many sites do not have the expertise or resources to produce data from fresh samples. It would also serve to reduce technical variability in larger projects. ObjectiveTo test a reliable cryopreservation protocol adapted for CSF cells, facilitating the characterization of these rare, fragile cells in moderate to large scale studies. DesignDiagnostic lumbar punctures were performed on twenty-one patients at two independent sites. Excess CSF was collected and cells were isolated. Each cell sample was split into two fractions for single cell analysis using one of two possible chemistries: 3 sc-RNA-Sequencing or 5sc-RNA-Sequencing. One cell fraction was processed fresh while the second sample was cryopreserved and profiled at a later time after thawing. SettingThe research protocol was deployed at two academic medical centers taking care of multiple sclerosis and other neurological conditions. Participants21 subjects (age 24 - 72) were recruited from individuals undergoing a diagnostic lumbar puncture for suspected neuroinflammatory disease or another neurologic illness; they donated excess CSF. FindingsOur comparison of fresh and cryopreserved data from the same individuals demonstrates highly efficient recovery of all known CSF cell types. The proportion of all cell types was similar between the fresh and the cryopreserved cells processed, and RNA expression was not significantly different. Results were comparable at both performance sites, and with different single cell sequencing chemistries. Cryopreservation also did not affect recovery of T and B cell clonotype diversity. Conclusion and relevanceOur cryopreservation protocol for CSF-cells provides an important alternative to fresh processing of fragile CSF cells: cryopreservation enables the involvement of sites with limited capacity for experimental manipulation and reduces technical variation by enabling batch processing and pooling of samples. Key pointsO_ST_ABSQuestionC_ST_ABSHow efficient is CSF cryopreservation for single-cell transcriptome analysis and can it be implemented in large multi-center translational and clinical trial settings? FindingsWe compared single-cell transcriptomes of paired fresh and cryopreserved CSF from 21 patients at two independent sites. We validate the efficacy of a simple and cost effective CSF cryopreservation method that preserves the composition and the transcriptomes of CSF cells stored for weeks-months. The protocol is deployed in a large multicenter Phase 4 MS clinical trial. MeaningA validated CSF cryopreservation method that would significantly advance basic science and biomarker research in neurological disorders by implementing single-cell transcriptome analyses in multi-center research and clinical trials.

genetics↗

bioRxiv2020

GNS561, a clinical-stage PPT1 inhibitor, has powerful antitumor activity against hepatocellular carcinoma via modulation of lysosomal functions

Background & AimsHepatocellular carcinoma (HCC) is the most frequent primary liver cancer. Autophagy inhibitors have been extensively studied in cancer but, to date, none has reached efficacy in clinical trials. Approach & ResultsTo explore the antitumor effects of GNS561, a new autophagy inhibitor, we first achieved in vitro assays using various human cancer cell lines. Having demonstrated that GNS561 displayed high liver tropism using mass spectrometry imaging, the potency of GNS561 on tumor was evaluated in vivo in two HCC models (human orthotopic patient-derived xenograft mouse model and diethylnitrosanime-induced cirrhotic immunocompetent rat model). Oral administration of GNS561 was well tolerated and decreased tumor growth in these two models. GNS561 mechanism of action was assessed in an HCC cell line, HepG2. We showed that due to its lysosomotropic properties, GNS561 could reach and inhibited its enzyme target, palmitoyl-protein thioesterase 1, resulting in lysosomal unbound Zn2+ accumulation, impairment of cathepsin activity, blockage of autophagic flux, altered location of mTOR, lysosomal membrane permeabilization, caspase activation and cell death. ConclusionsGNS561, currently tested in a global Phase 1b/2a clinical trial against primary liver cancer, represents a promising new drug candidate and a hopeful therapeutic strategy in cancer treatment. With an estimated 782,000 deaths in 2018, hepatocellular carcinoma (HCC) stands as the most common primary liver cancer and constitutes the fourth leading cause of cancer-related death worldwide (1). The rising incidence of HCC, the high worldwide mortality rate, and limited therapeutic options at advanced stages, make HCC a significant unmet medical need. Autophagy-related lysosomal cell death, either alone or in connection with several other cell death pathways, has been recognized as a major target for cancer therapy (2). Dysregulated autophagic-lysosomal activity and mTOR signaling were shown to allow cancer cells to become resistant to the cellular stress induced by chemotherapy and targeted therapy (3). Recently, several lysosome-specific inhibitors were shown to target palmitoyl-protein thioesterase 1 (PPT1), resulting in the modulation of protein palmitoylation and autophagy, and antitumor activity in melanoma and colon cancer models (4, 5). Chloroquine (CQ) and hydroxychloroquine (HCQ) have been used for more than 50 years to prevent and treat malarial infections and autoimmune diseases. Based on the lysosomotropic properties and the capacity for autophagy inhibition, these molecules have been proposed as active drugs in cancer (6-9). Over 40 clinical trials have been reported to evaluate the activity of both CQ or HCQ as single agent or in combination with chemotherapy in several tumor types (6-8. However, the required drug concentrations to inhibit autophagy were not achieved in humans, leading to inconsistent results in cancer clinical trials (5, 10). This prompted research to identify novel compounds with potent inhibitory properties against autophagy for cancer therapy. We previously reported that GNS561 was efficient in intrahepatic cholangiocarcinoma (iCCA) by inhibiting late-stage autophagy (11). In this study, we investigated the mechanism of action of GNS561. We identified lysosomal PPT1 as a target of GNS561. Exposure to GNS561 induced lysosomal accumulation of unbound zinc ion (Zn2+), inhibition of PPT1 and cathepsin activity, blockage of autophagic flux and mTOR displacement. Interestingly, these effects resulted in lysosomal membrane permeabilization (LMP) and caspase activation that led to cancer cell death. This mechanism was associated with dose-dependent inhibition of cancer cell proliferation and tumor growth inhibition in two HCC in vivo models. These data establish PPT1 and lysosomes as major targets for cancer cells and led to the development of a clinical program investigating the effects of GNS561 in patients with advanced HCC.

cancer biology↗

bioRxiv2023

Drug screening in human physiologic medium identifies uric acid as an inhibitor of rigosertib efficacy

The non-physiological nutrient levels found in traditional culture media have been shown to affect numerous aspects of cancer cell physiology, including how cells respond to certain therapeutic agents. Here, we comprehensively evaluated how physiological nutrient levels impact therapeutic response by performing drug screening in human plasma-like medium (HPLM). We observed dramatic nutrient-dependent changes in sensitivity to a variety of FDA-approved and clinically trialed compounds, including rigosertib, an experimental cancer therapeutic that has recently failed in phase 3 clinical trials. Mechanistically, we found that the ability of rigosertib to destabilize microtubules is strongly inhibited by the purine metabolism waste product uric acid, which is uniquely abundant in humans relative to traditional in vitro and in vivo cancer models. Structural modelling studies suggest that uric acid interacts with the tubulin-rigosertib complex and may act as an uncompetitive inhibitor of rigosertib. These results offer a possible explanation for the failure of rigosertib in clinical trials and demonstrate the utility of physiological media to achieve in vitro results that better represent human therapeutic responses.

cancer biology↗

bioRxiv2018

Effects and Feasibility of Hyperthermic Baths for Patients with Depressive Disorder: A Randomized Controlled Clinical Pilot Trial

BackgroundEvaluation of efficacy, safety and feasibility of hyperthermic baths (HTB; head-out-of-water-immersion in 40{degrees}C), twice a week, compared to a physical exercise program (PEP; moderate intensity aerobic exercises) in moderate to severe depression.\n\nMethodSingle-site, open-label randomized controlled 8-week parallel-group pilot study at an university outpatient clinic as part of usual depression care. Medically stable outpatients with depressive disorder (ICD-10: F32/F33) as determined by the 17-item Hamilton Depression Rating Scale (HAM-D) score [≥]18 and a score [≥]2 on item 1 (Depressed Mood) were randomly assigned to receive either two sessions of HTB or PEP per week (40-45 min) provided by two trained doctoral students. An independent biometric center used computer-generated tables to allocate treatments. Primary outcome measure was the change in HAM-D total score from baseline (T0) to the 2-week time point (T1). Linear regression analyses, adjusted for baseline values, were performed to estimate intervention effects on an intention-to-treat (ITT) principle.\n\nFindings45 patients (HTB n = 22; PEP n = 23) were randomized and analyzed according to ITT (mean age = 48.4 years, SD = 11.3, mean HAM-D score = 21.7, SD = 3.2). Baseline-adjusted mean difference was 4.3 points in the HAM-D score in favor of HTB (p<0.001). This improvement was achieved after two weeks. Compliance with the intervention and follow-up was far better in the HTB group (2 vs 13 dropouts). There were no treatment-related serious adverse events. Main limitation: the number of dropouts in the PEP group (13 of 23) was far higher than in other trials investigating exercise in depression (18.1 % dropouts).\n\nConclusionsHTB seems to be a fast-acting, safe and easy accessible method leading to clinically relevant improvement in depressive disorder after two weeks; it is also suitable for persons who have problems performing exercise training.\n\nTrial registrationGerman Clinical Trials Register (DRKS) with the registration number DRKS00011013 (registration date 2016-09-19) before onset of the study.

clinical trials↗

bioRxiv2017

A Low-Cost Multiplex Biomarker Assay Stratifies Colorectal Cancer Patient Samples into Clinically-Relevant Subtypes

Previously, we classified colorectal cancers (CRCs) into five CRCA subtypes with different prognoses and potential treatment responses, using a 786-gene signature. We merged our subtypes and those described by five other groups into four consensus molecular subtypes (CMS) that are similar to CRCA subtypes. Here we demonstrate the analytical development and application of a custom NanoString platform-based biomarker assay to stratify CRC into subtypes. To reduce costs, we switched from the standard protocol to a custom modified protocol (NanoCRCA) with a high Pearson correlation coefficient (>0.88) between protocols. Technical replicates were highly correlated (>0.96). The assay included a reduced robust 38-gene panel from the 786-gene signature that was selected using an in-laboratory developed computational pipeline of class prediction methods. We applied our NanoCRCA assay to untreated CRCs including fresh-frozen and formalin-fixed paraffin-embedded (FFPE) samples (n=81) with matched microarray or RNA-Seq profiles. We further compared the assay results with CMS classification, different platforms (microarrays/RNA-Seq) and gene-set classifiers (38 and 786 genes). NanoCRCA classified fresh-frozen samples (n=39; not including those showing a mixture of subtypes) into all five CRCA subtypes with overall high concordance across platforms (89.7%) and with CMS subtypes (84.6%), independent of tumour cellularity. This analytical validation of the assay shows the association of subtypes with their known molecular, mutational and clinical characteristics. Overall, our modified NanoCRCA assay with further clinical assessment may facilitate prospective validation of CRC subtypes in clinical trials and beyond.\n\nNovelty and ImpactWe previously identified five gene expression-based CRC subtypes with prognostic and potential predictive differences using a 786-gene signature and microarray platform. Subtype-driven clinical trials require a validated assay suitable for routine clinical use. This study demonstrates, for the first time, how molecular CRCA subtype can be detected using NanoString Technology-based biomarker assay (NanoCRCA) suitable for clinical validation. NanoCRCA is suitable for analysing FFPE samples, and this assay may facilitate patient stratification within clinical trials.

cancer biology↗

bioRxiv2018

Predicting onset, progression, and clinical subtypes of Parkinson disease using machine learning

BackgroundThe clinical manifestations of Parkinson disease are characterized by heterogeneity in age at onset, disease duration, rate of progression, and constellation of motor versus nonmotor features. Due to these variable presentations, counseling of patients about their individual risks and prognosis is limited. There is an unmet need for predictive tests that facilitate early detection and characterization of distinct disease subtypes as well as improved, individualized predictions of the disease course. The emergence of machine learning to detect hidden patterns in complex, multi-dimensional datasets provides unparalleled opportunities to address this critical need.\n\nMethods and FindingsWe used unsupervised and supervised machine learning approaches for subtype identification and prediction. We used machine learning methods on comprehensive, longitudinal clinical data from the Parkinson Disease Progression Marker Initiative (PPMI) (n=328 cases) to identify patient subtypes and to predict disease progression. The resulting models were validated in an independent, clinically well-characterized cohort from the Parkinson Disease Biomarker Program (PDBP) (n=112 cases). Our analysis distinguished three distinct disease subtypes with highly predictable progression rates, corresponding to slow, moderate and fast disease progressors. We achieved highly accurate projections of disease progression four years after initial diagnosis with an average Area Under the Curve of 0.93 (95% CI: 0.96 {+/-} 0.01 for PDvec1, 0.87 {+/-} 0.03 for PDvec2, and 0.96 {+/-} 0.02 for PDvec3). We have demonstrated robust replication of these findings in the independent validation cohort.\n\nConclusionsThese data-driven results enable clinicians to deconstruct the heterogeneity within their patient cohorts. This knowledge could have immediate implications for clinical trials by improving the detection of significant clinical outcomes that might have been masked by cohort heterogeneity. We anticipate that machine learning models will improve patient counseling, clinical trial design, allocation of healthcare resources and ultimately individualized clinical care.

neuroscience↗

bioRxiv2022

Clinically oriented prediction of patient response to targeted and immunotherapies from the tumor transcriptome

BackgroundPrecision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. MethodsWe present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patients response to a variety of therapies in multiple cancer types, without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: Personalized Oncology (PO), aimed at prioritizing treatments for a single patient, and Clinical Trial Design (CTD), selecting the most likely responders in a patient cohort. FindingsEvaluating ENLIGHTs performance on 21 blinded clinical trial datasets in the PO setting, we show that it can effectively predict a patients treatment response across multiple therapies and cancer types. Its prediction accuracy is better than previously published transcriptomics-based signatures and is comparable to that of supervised predictors developed for specific indications and drugs. In combination with the IFN-{gamma}signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, ENLIGHT can potentially enhance clinical trial success for immunotherapies and other monoclonal antibodies by excluding non-responders, while overall achieving more than 90% of the response rate attainable under an optimal exclusion strategy. ConclusionENLIGHT demonstrably enhances the ability to predict therapeutic response across multiple cancer types from the bulk tumor transcriptome. FundingThis research was supported in part by the Intramural Research Program, NIH and by the Israeli Innovation Authority.

bioinformatics↗

bioRxiv2021

GLS1 is a Protective Factor Rather than a Molecular Target in ARID1A-Mutated Ovarian Clear Cell Carcinoma

Targeting glutamine metabolism has emerged as a novel therapeutic strategy for several human cancers, including ovarian cancer. The primary target of this approach is the kidney isoform of glutaminase, glutaminase 1 (GLS1), a key enzyme in glutamine metabolism that is overexpressed in several human cancers. A first-in-class inhibitor of GLS1, called CB839 (Telaglenastat), has been investigated in several clinical trials, with promising results. The first clinical trial of CB839 in platinum-resistant ovarian cancer patients is forthcoming. ARID1A-mutated ovarian clear cell carcinoma (OCCC) is a relatively indolent and chemoresistant ovarian cancer histotype. In OCCC-derived cells in vitro and mouse models, loss of ARID1A leads to upregulation of GLS1. Thus, targeting of GLS1 with CB839 has been suggested as a targeted approach for OCCC patients with tumors harboring ARID1A-mutations. Here, we investigated whether GLS1 is differentially expressed between OCCC patients whose tumors are ARID1A positive and patients whose tumors are ARID1A negative. In clinical specimens of OCCC, we found that GLS1 overexpression was not correlated with ARID1A loss. In addition, GLS1 overexpression was associated with better clinical outcomes. Our findings suggest that GLS1 expression in OCCC may be a protective factor and that caution should be taken when considering the use of CB839 to treat OCCC patients.

cancer biology↗

bioRxiv2019

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

IntroductionTumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.\n\nObjectiveHere we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase 3 clinical trial.\n\nMethodsIn the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne(R) CDx assay.\n\nResultsTMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearmans r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearmans r = 0.90).\n\nConclusionsParameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.\n\nKey PointsO_LITumor mutational burden (TMB) is a clinically relevant biomarker for efficacy of immunotherapy in patients with cancer\nC_LIO_LIVariations in TMB assessment parameters can shift the final TMB value. Harmonization and standardization are important to the successful clinical implementation of TMB testing\nC_LIO_LITMB values assessed by different methods are highly correlated. Harmonization of TMB testing in patients with cancer is therefore achievable\nC_LI

bioinformatics↗

bioRxiv2022

Impact of 98 LRRK2 variants linked to Parkinson's Disease on kinase activity and microtubule binding

Mutations enhancing the kinase activity of LRRK2 cause Parkinsons disease (PD) and therapies that reduce LRRK2 kinase activity are being tested in clinical trials. Numerous rare variants of unknown clinical significance have been reported, but how the vast majority impact on LRRK2 function is unknown. Here, we investigate 100 LRRK2 variants linked to PD, including previously described pathogenic mutations. We identify 23 LRRK2 variants that robustly stimulate kinase activity, including variants within the N-terminal non-catalytic regions [ARM (E334K, A419V), ANK(R767H), LRR (R1067Q, R1325Q)], as well as variants predicted to destabilise the ROC:CORB interface [ROC (A1442P, V1447M), CORA (R1628P) CORB (S1761R, L1795F)] and COR:COR dimer interface [CORB (R1728H/L)]. Most activating variants decrease LRRK2 biomarker site phosphorylation (pSer935/pSer955/pSer973), consistent with the notion that the active kinase conformation blocks their phosphorylation. We conclude that the impact of variants on kinase activity is best evaluated by deploying a cellular assay of LRRK2-dependent Rab10 substrate phosphorylation, compared to a biochemical kinase assay, as only a minority of activating variants [CORB (Y1699C, R1728H/L, S1761R) and kinase (G2019S, I2020T, T2031S)], enhance in vitro kinase activity of immunoprecipitated LRRK2. Twelve variants including several that activate LRRK2 and have been linked to PD, suppressed microtubule association in the presence of a Type I kinase inhibitor [ARM(M712V), LRR(R1320S), ROC (A1442P, K1468E, S1508R), CORA(A1589S), CORB (Y1699C, R1728H/L) and WD40(R2143M, S2350I, G2385R)]. Our findings will stimulate work to better understand the mechanisms by which variants impact biology and provide rationale for variant carrier inclusion or exclusion in ongoing and future LRRK2 inhibitor clinical trials.

neuroscience↗

bioRxiv2018

Vitamin D status and risk of incident tuberculosis disease: a systematic review and individual participant data meta-analysis

BackgroundFew studies have evaluated the association between pre-existing vitamin D deficiency (VDD) and incident TB. We assessed the impact of baseline vitamin D on TB risk. MethodsWe assessed the association between baseline vitamin D and incident TB in a prospective cohort of 6751 household contacts of TB patients in Peru. We also conducted a one-stage individual participant data meta-analysis searching PubMed and Embase for studies of vitamin D and TB until December 31, 2017. We included studies that assessed vitamin D before TB diagnosis. We defined VDD as 25-(OH)D <50 nmol/L, insufficiency as 50-75 nmol/L and sufficiency as >75nmol/L. We estimated the association between vitamin D and incident TB using conditional logistic regression in the Peru cohort and generalized linear mixed models in the meta-analysis. FindingsIn Peru, baseline VDD was associated with a statistically insignificant increase in incident TB (aOR 1{middle dot}70, 95% CI 0{middle dot}84-3{middle dot}46; p=0{middle dot}14). We identified seven studies for the meta-analysis and analyzed 3544 participants. Individuals with VDD and very low vitamin D (<25nmol/L) had increased TB risk (aOR 1{middle dot}48, 95% CI 1{middle dot}04-210;p=0{middle dot} 03 and aOR 2 08, 95% CI 0{middle dot}88-4{middle dot}92; p trend=002 respectively). Among HIV-positive patients, VDD and very low vitamin D conferred a 2-fold (aOR 2.18, 95% CI 1{middle dot} 22-3{middle dot}90; p=0{middle dot} 01) and 4-fold (aOR 4{middle dot}28, 95% CI 0{middle dot}85-21{middle dot}44; p trend=0{middle dot}01) increased risk of TB respectively. InterpretationOur findings suggest vitamin D predicts TB risk in a dose-dependent manner and vitamin D supplementation may play a role in TB prevention. FundingNational Institute of Health (NIH), National Institute of Allergy and Infectious Diseases (NIAID), National Institute on Drug Abuse (NIDA), National Institute of Mental Health (NIMH), International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT), Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institute of Dental and Craniofacial Research (NIDCR), Boehringer-Ingelheim, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, Foundation, Ujala Foundation, Wyncote Foundation, NIH - Fogarty International Center Program of International Training Grants in Epidemiology Related to AIDS, NIAID Byramjee Jeejeebhoy Medical College HIV Clinical Trials Unit, NIAIDs Baltimore-Washington-India Clinical Trials Unit, National Commission on Biotechnology, the Higher Education Commission, International Research Support Initiative Program of the Higher Education Commission Government of Pakistan, the Bill and Melinda Gates Foundation, and the NIH Fogarty International Center. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSNumerous studies have found lower serum vitamin D levels among patients with active TB disease compared to healthy controls. However, research has not clarified whether low vitamin D increases TB risk or whether TB disease leads to decreased vitamin D levels. We conducted PubMed and Medline searches for all studies available through December 31, 2017 on the association between vitamin D status and TB disease. We included the following keywords: "vitamin D," "vitamin D deficiency," "hypovitaminosis D," "25-hydroxyvitamin D," "1,25-dihydroxyvitamin D," "vitamin D2," "vitamin D3," "ergocalciferol," "cholecalciferol," and "tuberculosis." We found only seven studies had prospectively evaluated the impact of baseline vitamin D levels on risk of progression to TB disease. We report here the results of a case control study nested within a large prospective longitudinal cohort study of household contacts of TB cases and the results of an individual participant data (IPD) metaanalysis of available evidence on the association between vitamin D levels and incident TB disease. Added value of this studyWe demonstrated that low vitamin D levels predicts risk of future progression to TB disease in a dose-dependent manner. Implications of all the available evidenceThese findings suggest the possibility that vitamin D supplementation among individuals at high risk for developing TB disease might play a role in TB prevention efforts.

epidemiology↗

bioRxiv2019

Genomic Analyses of SLAMF7 CAR-T Cells Manufactured by Sleeping Beauty Transposon Gene Transfer for Immunotherapy of Multiple Myeloma

Widespread treatment of human diseases with gene therapies necessitates the development of gene transfer vectors that integrate genetic information effectively, safely and economically. Accordingly, significant efforts have been devoted to engineer novel tools that i) achieve high-level stable gene transfer at low toxicity to the host cell; ii) induce low levels of genotoxicity and possess a safe integration profile with a high proportion of integrations into safe genomic locations; and iii) are associated with acceptable cost per treatment and scalable/exportable vector production to serve large numbers of patients. The Sleeping Beauty (SB) transposon has been transformed into a vector system that is fulfilling these requirements.\n\nIn the CARAMBA project, we use SB transposition to genetically modify T cells with a chimeric antigen receptor (CAR) specific for the SLAMF7 antigen, that is uniformly and highly expressed on malignant plasma cells in multiple myeloma. We have demonstrated that SLAMF7 CAR-T cells confer specific and very potent anti-myeloma reactivity in pre-clinical models, and are therefore preparing a Phase I/IIa clinical trial of adoptive immunotherapy with autologous, patient-derived SLAMF7-CAR T cells in multiple myeloma (EudraCT Nr. 2019-001264-30/CARAMBA-1).\n\nHere we report on the characterization of genomic safety attributes in SLAMF7 CAR-T cells that we prepared in three clinical-grade manufacturing campaigns under good manufacturing practice (GMP), using T cells that we obtained from three healthy donor volunteers. In the SLAMF7 CAR-T cell product, we determined the average transposon copy number, the genomic insertion profile, and presence of residual SB100X transposase. The data show that the SLAMF7 CAR transposon had been inserted into the T cell genome with the close-to-random distribution pattern that is typical for SB, and with an average transposon copy number ranging between 6 and 12 per T cell. No residual SB100X transposase could be detected by Western blotting in the infusion products. With these attributes, the SLAMF7 CAR-T products satisfy criteria set forth by competent regulatory authorities in order to justify administration of SLAMF7 CAR-T cells to humans in the context of a clinical trial. These data set the stage for the CARAMBA clinical trial, that will be the first in the European Union to use virus-free SB transposition for CAR-T engineering.\n\nDisclosuresThis project is receiving funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 754658 (CARAMBA).

bioengineering↗

bioRxiv2025

Mechanistic modeling and machine learning identifies optimum radiotherapy schedules to prevent treatment-induced metastasis

Lung cancer patients often experience increased metastasis formation after radiotherapy. However, it is incompletely understood whether radiation affects the migratory behavior of tumor cells and how altered radiotherapy schedules might mitigate this risk. To address these questions, we performed live-cell microscopy experiments to profile changes in cell migration during radiation across 12 cancer cell lines and developed a predictive computational modeling platform describing tumor volume and dissemination during radiotherapy. Using this platform, we identified optimal fractionation schedules and then performed extensive in silico clinical trials, establishing that our optimized schedules substantially reduce metastatic seeding relative to the standard of care schedule. Training transformer models on the in silico clinical trial data enabled us to recover mechanistic parameters with high accuracy, demonstrating that the features determining optimal radiotherapy can be inferred from longitudinal tumor data. Our integrative predictive approach enables the rational design of optimum clinical trials across indications.

bioinformatics↗

bioRxiv2024

High-Throughput Assay for Predicting Diarrhea Risk Using a 2D Human Intestinal Stem Cell-Derived Model

Gastrointestinal toxicities (GITs) are the most prevalent adverse events (AE) reported in clinical trials, often resulting in dose-limitations that reduce drug efficacy and delay development and treatment optimization. Preclinical animal models do not accurately replicate human GI physiology, leaving few options for early detection of GI side effects prior to human studies. Development of an accurate model that predicts GIT earlier in drug discovery programs would better support successful clinical trial outcomes. Chemotherapeutics, which exhibit high rates of clinical GIT, frequently target mitotic cells. Therefore, we hypothesized that a model utilizing proliferative cell populations derived from human intestinal crypts would predict the occurrence of clinical GITs with high accuracy. Here, we describe the development of a multiparametric assay utilizing the RepliGut(R) Planar system, an intestinal stem cell-derived platform cultured in an accessible high throughput Transwell format. This assay addresses key physiological elements of GIT by assessing cell proliferation (EdU incorporation), cell abundance (DAPI quantification), and barrier function (TEER). Using this approach, we demonstrate that primary proliferative cell populations reproducibly respond to marketed chemotherapeutics at physiologic concentrations. To determine the ability of this model to predict clinical diarrhea risk, we evaluated a set of 30 drugs with known clinical diarrhea incidence in three human donors, comparing results to known plasma drug concentrations. This resulted in highly accurate predictions of diarrhea potential for each endpoint (balanced accuracy of 91% for DAPI, 90% for EdU, 88% for TEER) with minimal variation across human donors. In vitro toxicity screening using primary proliferative cells may enable improved safety evaluations, reducing the risk of AEs in clinical trials and ultimately lead to safer and more effective treatments for patients.

pharmacology and toxicology↗

bioRxiv2025

Trajectory-matching ABC-MCMC for simulating heterogeneous dynamics in mechanistic models

The inherent heterogeneity of complex biological systems makes it difficult to experimentally and clinically explore individual outcomes. Mechanistic mathematical models are essential tools for studying such heterogeneity. Thus, there is increasing interest in integrating newer mechanistic model-based techniques, like virtual patient cohorts and virtual clinical trials, within experimental and regulatory pipelines to probe relationships that may be difficult or impossible to ascertain through traditional wet-lab or clinical experimentation alone. Approximate Bayesian Computation (ABC) is an attractive method for generating virtual patient cohorts and running virtual clinical trials. However, ABC-based approaches can become computationally demanding when stringent acceptance criteria are imposed. In response, we developed a model-based technique called trajectory-matching random-walk feasibility sampling (TM-RWFS) that captures the variability of complex biological systems by constraining model trajectories between the upper and lower bounds of available data to generate heterogeneity. By testing the method's performance on existing mechanistic models, we show that TM-RWS generates parameter sets whose simulated trajectories reproduce the observed variability in biological systems of varying complexity while maintaining computational efficiency. Thus, TM-RWFS is a fast, new approach for generating heterogeneity in mechanistic mathematical models with implications for model-based experimental design, virtual patient cohorts, and virtual clinical trials.

systems biology↗

bioRxiv2022

Use of Transient Transfection for cGMP Manufacturing of eOD-GT8 60mer, a Self-Assembling Nanoparticle Germline-Targeting HIV-1 Vaccine Candidate

We describe the current Good Manufacturing Practice (cGMP) production and subsequent characterization of eOD-GT8 60mer, a glycosylated self-assembling nanoparticle HIV-1 vaccine candidate germline-targeting priming immunogen. Production was carried out by transient expression in the human embryonic kidney 293 (HEK293) cell line followed by a combination of purification techniques. A large scale cGMP (200 L) production run yielded 354 mg of the purified eOD-GT8 60mer drug product material, which was formulated at 1 mg/mL in 10% sucrose in phosphate-buffered saline (PBS) at pH 7.2. The clinical trial material was comprehensively characterized for purity, antigenicity, glycan composition, amino acid sequence, aggregation, and by several safety-related tests during cGMP lot release. A comparison of purified products produced at 1 L scale and 200 L cGMP scale demonstrated consistency and robustness of the transient transfection upstream process and the downstream purification strategies. The cGMP clinical trial material is being tested in a phase 1 clinical trial (NCT03547245) and is currently stored at -80{degrees}C and on a stability testing program as per regulatory guidelines. The methods described here illustrate the utility of transient transfection for cGMP production of complex products such as glycosylated self-assembling nanoparticles.

biochemistry↗

bioRxiv2026

Characterization of tumor interactions with the immune system in an autochthonous mouse model of glioblastoma

BackgroundGlioblastoma is an aggressive and incurable brain tumor. Clinical trials of immune checkpoint inhibitors showed no clinical benefit in glioblastoma when given after surgery. However, a clinical trial in which PD1 inhibition was given prior to second surgery did show pharmacodynamic evidence for activity. This suggests the possibility that immune checkpoint inhibitors may be more effective in a setting where large tumors are present. Here we have studied immune responses to large tumors in an autochthonous mouse model of glioblastoma. MethodsGlioblastoma was induced by transfection with oncogenic plasmids injected directly into the lateral ventricle of neonatal mice. Immune responses were assessed using a combination of spectral flow cytometry and immunohistochemistry. ResultsThere was a marked immune response to large tumors, with significant increases in CD4 T cells and dendritic cells. T cell changes occurred primarily at leptomeningeal/perivascular border sites. A large proportion of CD4 T cells expressed PD1 and half of these were regulatory T cells. NK cells were also increased in mice with large tumors, but were predominantly in immature states. The mouse model accurately recapitulates the formation of palisading necroses. These contain apoptotic cells and avidly recruit myeloid cells that are induced to express large amounts of TGF{beta}. ConclusionsLarge glioblastoma tumors generate a border site population of PD1 positive T cells that may explain the pharmacodynamic response in neoadjuvant trials, and a palisading necrosis-driven immunosuppressive mechanism that may explain why responses are insufficient to provide a significant clinical benefit. KEY POINTSThe SB mouse model accurately recapitulates immune features of human glioblastoma Large tumors induce a significant border site immune response Palisading necroses in large tumors counter this with a strong immunosuppressive response IMPORTANCE OF STUDYImmune checkpoint inhibitors have not shown efficacy in glioblastoma when used post-surgery, but do show pharmacodynamic activity when used in patients prior to second surgery (i.e. neoadjuvant). This suggest the possibility that immune checkpoint inhibition is more effective when large tumors are present. Using a clinically-relevant autochthonous mouse model, we show here that large tumors induce an immune response that is evident in leptomeningeal border sites. Large tumors in this mouse model also generate palisading necroses, a well-known diagnostic feature in glioblastoma tumors. These palisading necroses generate large amounts of TGF{beta}, providing a mechanism by which large tumors can suppress border site immune responses. This further supports the concept that palisading necroses are drivers of glioblastoma malignancy and suggests novel strategies to enhance responses to immune checkpoint inhibition in this cancer.

cancer biology↗

bioRxiv2020

SLC7A11 is a superior determinant of APR-246 (Eprenetapopt) response than TP53 mutation status

PurposeAPR-246 (Eprenetapopt) is in clinical development with a focus on haematological malignancies and is marketed as a mutant-p53 reactivation therapy. Currently, the detection of at least one TP53 mutation is an inclusion criterion for patient selection into most clinical trials. Preliminary results from our phase Ib/II clinical trial investigating APR-246 combined with combination chemotherapy (cisplatin and 5-Fluorouracil) in metastatic oesophageal cancer, together with previous pre-clinical studies, indicate that TP53 mutation status alone may not be a sufficient biomarker for response to APR-246. This study aimed to identify a robust biomarker for response to APR-246. MethodsCorrelation analysis of the PRIMA-1 activity (lead compound to APR-246) with mutational status, gene expression, protein expression and metabolite abundance across over 800 cancer cell lines was performed. Functional validation and a boutique siRNA screen of over 750 redox-related genes were also conducted. ResultsTP53 mutation status was not predictive of response to APR-246. The expression of SLC7A11, the cystine/glutamate transporter, was identified as a superior determinant of response to APR-246. Genetic regulators of SLC7A11, including ATF4, MDM2, wild-type p53 and c-Myc were confirmed to also regulate cancer cell sensitivity to APR-246. ConclusionsSLC7A11 expression is the major determinant of sensitivity to APR-246 and should be utilised as a predictive biomarker in future clinical investigation of APR-246.

cancer biology↗