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bioRxiv2026

Functional T cells trapped behind a stromal wall: a Brake-with-Wall phenotype redefines pancreatic adenocarcinoma immunotherapy resistance

BackgroundPancreatic ductal adenocarcinoma (PDAC) is the paradigmatic immunotherapy-refractory cancer, with a 5-year survival of approximately 12% and minimal benefit from immune checkpoint blockade (ICB). The dominant mechanistic explanation classifies PDAC as a T cell-excluded "cold" tumor, implying that no functional anti-tumor T cells are available for checkpoint release. Whether this Block-strategy view is correct has not been re-examined under integrated evasion-framework analysis. MethodsWe applied a previously developed 16-module immune evasion framework to TCGA-PAAD (n=183), integrated with hub-cytokine analysis (IL-10/TGF-{beta}), Kv1.3-immune channelome data, and clinical trial mapping (12,007 trials). Single-cell validation used two independent PDAC cohorts retrieved through TISCH2: PAAD_CRA001160 (Peng 2019, 35 samples [24 PDAC + 11 adjacent normal], 57,443 cells) and PAAD_GSE154778 (Lin 2020, 16 samples, 14,953 cells), examined for CD8A, TOX, PRF1, KCNA3, and FAP expression by cell type. ResultsPDAC scored highest in CAF Wall (z=0.768) and Platelet Cloak (z=0.663) modules; strategy classification yielded Brake -- not Block -- driven by a positive KCNA3-survival relationship (HR=0.649, 95% CI 0.43-0.97, p=0.037). Single-cell qualitative analysis of TISCH2 violin plots showed that CD8 exhausted T cells (CD8Tex) carried (i) high CD8A, (ii) the highest TOX expression among annotated cell types, (iii) preserved PRF1, and (iv) high KCNA3 expression. FAP was strongly localized to fibroblasts (peak [~]3.0 vs. <0.5 elsewhere). The pattern was reproduced in the second cohort. The optimal three-module attack (MHC restoration + CAF disruption + VEGF blockade) suppressed 10 of 16 evasion modules in silico (62.5%); zero of 370 PDAC immunotherapy trials test this combination. ConclusionsPDAC may not be T cell-cold but T cell-trapped: CD8 T cells with intact Kv1.3 channels appear immobilized behind a FAP-positive cancer-associated fibroblast wall. ICB monotherapy is mechanistically insufficient because the brake is engaged on T cells that cannot reach the tumor. The framework predicts that triple-targeted intervention -- checkpoint release + CAF wall disruption + vascular normalization -- is the minimum effective strategy. This is a hypothesis-generating computational analysis; prospective experimental and clinical validation are required.

cancer biology↗

bioRxiv2021

Integrative Clinical and Molecular Characterization of Translocation Renal Cell Carcinoma

ABSTRACTTranslocation renal cell carcinoma (tRCC) is an aggressive and poorly-characterized subtype of kidney cancer driven by MiT/TFE gene fusions. Here, we define the landmarks of tRCC through an integrative analysis of 152 tRCC patients identified across multiple genomic, clinical trial, and retrospective cohorts. Most tRCCs harbor few somatic alterations apart from MiT/TFE fusions and homozygous deletions at chromosome 9p21.3 (19.2% of cases). Transcriptionally, tRCCs display a heightened NRF2-driven antioxidant response that is associated with resistance to many targeted therapies. Consistently, we find that outcomes for tRCC patients treated with vascular endothelial growth factor receptor inhibitors (VEGFR-TKI) are worse than those treated with immune checkpoint inhibition (ICI). Multiparametric immunofluorescence confirmed the presence of CD8 + tumor-infiltrating T cells compatible with a clinical benefit from ICI and revealed an exhaustion immunophenotype distinct from clear cell RCC. Our findings comprehensively define the clinical and molecular features of tRCC and may inspire new therapeutic hypotheses.

cancer biology↗

bioRxiv2024

EZH2-driven immune evasion defines high-risk pediatric AML with t(16;21) FUS::ERG gene fusion.

The past 25 years of clinical trials have produced few improvements in pediatric AML (pAML) outcomes. This is acutely evident in patients with t(16;21)(p11;q22), yielding FUS::ERG. Patients with FUS::ERG-positive AML relapse quickly and do not respond to transplantation. Major histocompatibility complex (MHC) class I & II receptors and costimulatory molecules are absent at diagnosis in FUS::ERG-positive AML, mirroring the phenotype and outcomes of post-transplant relapse. We show that this is driven by overexpression of EZH2, in vitro and in multiple clinical cohorts. While FUS::ERG AML is the most extreme example, this phenotype is shared by lethal CBFA2T3::GLIS2-driven AML, and patients with RUNX1::RUNX1T1 have significantly worse outcomes when EZH2 overexpression co-occurs. The FDA-approved EZH2 inhibitor tazemetostat reverses this phenotype, re-establishes MHC presentation, and elicits immune effector cell-mediated elimination. EZH2 inhibitors may provide the first targeted therapeutic frontline option for AML patients with FUS::ERG, with the potential for broader frontline immunostimulatory benefits. STATEMENT OF SIGNIFICANCEHere we show an immune-evasive phenotype, present at diagnosis and characterized by elevated EZH2 levels and loss of MHC class I and II, defines a high-risk subtype of acute leukemia. Treatment with the EZH2 inhibitor tazemetostat and IFN-{gamma} reverses this phenotype and results in immune cell engagement and blast elimination.

cancer biology↗

bioRxiv2020

Mismatch repair deficiency predicts response to HER2 blockade in HER2-negative breast cancer

Estrogen receptor positive (ER+) breast cancer is a leading cause of cancer-related death globally. Resistance to standard of care endocrine treatment occurs in at least 30% of ER+ breast cancer patients resulting in ~40,000 deaths every year in the US alone. Preclinical studies strongly implicate activation of growth factor receptor, HER2 in endocrine treatment resistance of ER+ breast cancer that is HER2- at diagnosis1,2. However, clinical trials of pan-HER inhibitors in ER+/HER2- patients have disappointed, likely due to a lack of predictive biomarkers3-6. Here we demonstrate that loss of MLH1, a principal mismatch repair gene, causally activates HER2 in ER+/HER2- breast cancer upon endocrine treatment. Additionally, we show that HER2 activation is indispensable for endocrine treatment resistant growth of MLH1- cells in vitro and in vivo. Consequently, inhibiting HER2 restores sensitivity to endocrine treatment in multiple experimental models including patient-derived xenograft tumors. Patient data from multiple clinical datasets (TCGA, METABRIC, Alliance (Z1031) and E-GEOD-28826) supports an association between MLH1 loss, HER2 upregulation, and sensitivity to trastuzumab in endocrine treatment-resistant ER+/HER2- patients. These results provide strong rationale that MLH1 could serve as a first-in-class predictive marker of sensitivity to combinatorial treatment with endocrine drugs and HER inhibitors in endocrine treatment-resistant ER+/HER2- breast cancer patients. Implications of this study extend beyond breast cancer to Lynch Syndrome cancers. One Sentence SummaryDefective mismatch repair activates HER2 in HER2-negative breast cancer cells and renders them susceptible to HER2 inhibitors.

cancer biology↗

bioRxiv2024

Optimized AAV capsids for diseases of the basal ganglia show robust potency and distribution in adult nonhuman primates

Huntingtons disease and other disorders of the basal ganglia create challenges for biomolecule-based medicines given the poor accessibility of these deep brain structures following intracerebral or intravascular delivery. Additionally, for adeno-associated viruses (AAVs) intravascular delivery exposes peripheral tissues to the vast majority of the therapy, increasing the risk of immune responses and the quantity and associated cost of goods required for therapeutically relevant brain penetration levels. Here, we found that low dose, low volume delivery of unbiased AAV libraries into a focused brain region allowed recovery of novel capsids capable of broad access to key deep brain and cortical structures relevant for human therapies at doses orders of magnitude lower than used in current clinical trials. One such capsid, AAV-DB-3, provided transduction of up to 45% of medium spiny neurons in the adult NHP striatum, along with substantial transduction of relevant deep layer neurons in the cortex. Notably, AAV-DB-3 behaved similarly in mice as in NHPs and also potently transduced human neurons derived from induced pluripotent stem cells. Thus, AAV-DB-3 provides a unique AAV for network level brain gene therapies that translates up and down the evolutionary scale for preclinical studies and eventual clinical use.

neuroscience↗

bioRxiv2026

RePurpose: An LLM-Assisted, Source-Traceable Drug Repurposing Tool with Retrospective Validation on Clemastine in Multiple Sclerosis

Summary Thus far, evidence for drug repurposing is contained in target-, drug-, trial-, and literature-based data sources that are challenging to synthesize for non-specialists. Here, we introduce RePurpose, a web-based tool that takes as input a topic written in plain language and returns candidate drugs built from data in Open Targets, ClinicalTrials.gov, UniProt, and PubMed. For queries in the form of a goal, RePurpose filters candidate drugs by whether they modulate all targets implicated in the goal in the corresponding direction. Every candidate has a source that contributes evidence: a structured database, a clinical trial, or a proposal from a large language model. An adjustable ranking adjusts the order of candidates from well-studied to less well-known candidate drugs. We retrospectively tested RePurpose with the trial drug clemastine, which was being considered as a remyelinating agent in multiple sclerosis (MS). RePurpose retrieved clemastine in each replicate of the mechanism-worded queries, but in no replicates of the disease-worded queries, and no structured query retrieved it without the language model enabled. Its ranked outputs reflected the evidence supporting clemastine but not later evidence of harm in progressive MS, which was reachable only through an on-demand literature search. Our results imply that RePurpose may be better at tracing evidence around a hypothesis than generating new hypotheses. Availability and Implementation RePurpose Pharma is freely accessible at https://www.repurposepharma.com/. For code and more information on the application, see: https://github.com/nayagamnitin-hub/RePurpose-Pharma.

pharmacology and toxicology↗

bioRxiv2021

In vitro assessment of an engineered tBID-based safety switch system in human T lymphocytes

Cell therapy as a promising therapeutic modality to treat cancer has been intensively studied for decades. However, the clinical trials have indicated that patients under T cell therapy may develop severe cytokine release syndrome resulting in hospitalization or even death. Furthermore, genetic modifications to promote proliferation and persistence of T cells could result in high numbers of long-lived engineered cells in patients after treatment. In this study we developed a novel tBID-based safety switch regulated through a small molecule inducible on switch to control undesired toxicity or ablate engineered cells as needed. We compared several tBID-based safety switch constructs with the clinically validated safety switches, HSV-TK (human herpes simplex virus thymidine kinase) and iCasp9 (inducible Caspase 9), few tBID-based safety switch constructs were systematically tested and investigated in vitro in Jurkat or human primary T cells. We demonstrated that our novel tBID based safety switch, with optimization, was able to eliminate up to ~90% of transduced human primary T cells within 72hr after activation, providing an alternative switch system to manage safety concerns for cell therapy.

molecular biology↗

bioRxiv2024

Identification of novel drug-drug interactions: towards precision medicine in women's reproductive health

Drug-drug interactions (DDIs) may occur when two or more drugs are taken together, leading to undesired side effects or potential synergistic effects. Most clinical effects of drug combinations have not been assessed in clinical trials. Therefore, predicting DDIs can provide better patient management, avoid drug combinations that can negatively affect patient care, and exploit potential synergistic combinations to improve current therapies in women healthcare. For this purpose, a DDI prediction model was built to describe relevant drug combinations affecting reproductive treatments. Approved drug features (chemical structure of drugs, side effects, targets, enzymes, carriers and transporters, pathways, protein-protein interactions, and interaction profile fingerprints) were obtained. A unified predictive score revealed unknown DDIs between reproductive and commonly used drugs and their associated clinical effects on reproductive health. The performance of the prediction model was validated using known DDIs. This prediction model accurately predicted known interactions (AUROC = 0.9876) and identified 2,991 new DDIs between 192 drugs used in different female reproductive conditions and other drugs used to treat unrelated conditions. These DDIs included 836 between drugs used for in-vitro fertilization. Most new DDIs involved estradiol, acetaminophen, bupivacaine, risperidone, and follitropin. Follitropin, bupivacaine, and gonadorelin had the highest discovery rate (42%, 32%, and 25% respectively). Some were expected to improve current therapies (n=23), while others would cause harmful effects (n=11). We also predicted twelve DDIs between oral contraceptives and HIV drugs that could compromise their efficacy. Overall, these results show the importance of DDIs studies to personalize female reproductive therapies.

pharmacology and toxicology↗

bioRxiv2025

Mutations in transcription factors that confer fluconazole resistance also confer reduced susceptibility to manogepix in Candida auris, Candida albicans, Candida parapsilosis, and Candida glabrata (Nakaseomyces glabratus)

The fungal pathogen Candida auris is of global concern due to high levels of multidrug resistance and its propensity to cause infectious outbreaks. Over 90% of isolates are resistant to fluconazole, the most commonly prescribed antifungal world-wide. Fluconazole resistance is multifactorial with many isolates carrying mutations in the gene encoding the transcriptional regulator Tac1B, leading to increased expression of the gene encoding the ATP Binding Cassette (ABC) transporter Cdr1. Recently, a study examining C. auris in vitro resistance mechanisms to manogepix, a promising antifungal agent currently in clinical trials, found a TAC1B mutation that confers reduced manogepix and fluconazole susceptibility. We hypothesized that mutations in C. auris TAC1B and similar transcription factors in other Candida species that confer fluconazole resistance might also confer reduced susceptibility to manogepix. We measured manogepix susceptibilities for selected isolates and strains and found C. auris TAC1B, C. albicans and C. parapsilosis TAC1, and C. glabrata PDR1 confer reduced manogepix susceptibility in a manner dependent on ABC transporters similar to Cdr1. Our findings raise the possibility of fluconazole and manogepix cross resistance for clinical isolates harboring mutations in these genes.

microbiology↗

bioRxiv2026

Strong correlation between phantomless and inline phantom-based densitometric calibration of vertebral properties from CT scans of healthy volunteers

Phantom calibration is currently the gold standard for calibrating CT scans and for calculating material properties of dense tissues for computational models. However, in Oncology departments and low-resource settings, it is not routine to include a calibration phantom within the scanning protocol. Therefore, retrospective scan datasets are challenging to calibrate for biomechanical investigations, precluding detailed measurements of material and mechanical properties. In this study, we compared the results from a phantomless calibration technique, where the density within each scan was independently calibrated based on known tissue densities captured within each scan (e.g. air), with those from a traditional inline phantom calibration. To do so we used scans from a cohort of healthy volunteers from the control arm of a clinical trial dataset (ANTELOPE) in which inline calibration phantoms were included. We found that, when selecting air and the aorta as regions for calibration within individual CT scans, a strong individual-specific correlation existed between bone mineral density measured in the phantomless and phantom calibrations. This indicates that the phantomless calibration method can be a useful and reliable tool for quantifying the densitometric material properties of healthy human vertebrae, and provides the opportunity for further analysis of spinal CT scans in either retrospective datasets or in low-resource clinical settings.

bioengineering↗

bioRxiv2020

Immunochemical analysis of the integrin expression in retinal pigment epithelial cells

Retinal pigment epithelial (RPE) cells have been used in disease modelling and transplantation studies in retinal diseases. Several types of RPE cells have been trialed, ranging from primary cells and immortalized cell lines to stem cell-derived RPE cells. During aging and in disease, the extracellular environment of the RPE cells changes, interfering with RPE cell adhesion. We hypothesize that this could be a key problem in transplantation studies that have reported lack of adhesion and survival of the transplanted RPE cells. Integrins are essential for the proper function of the RPE, mediating adhesion to Bruchs membrane, and the binding and subsequent phagocytosis of photoreceptor outer segments. Variability that has been found in clinical trials might be due to the variability of cell types used and their expression profiles of surface molecules. Here, we set out to analyze integrin expression in primary rat RPE cells and in the human cell line ARPE-19 using immunochemistry. We found that both cell types express integrins to varying degrees. After long-term culturing, ARPE-19 cells resemble mature RPE cells, and increase integrin expression. We hence argue that it is important to test the properties of these cells prior to transplantation to avoid failure of adhesion and to facilitate correct function.

neuroscience↗

bioRxiv2024

Multi-Omics Analysis Reveals the Attenuation of the Interferon Pathway as a Driver of Chemo-Refractory Ovarian Cancer

Ovarian high-grade serous carcinoma (HGSC) represents the deadliest gynecological malignancy, with 10-15% of patients exhibiting primary resistance to first-line chemotherapy. These primarily chemo-refractory patients have particularly poor survival outcomes, emphasizing the urgent need for developing predictive biomarkers and novel therapeutic approaches. Here, we show that interferon type I (IFN-I) pathway activity in cancer cells is a crucial determinant of chemotherapy response in HGSC. Through a comprehensive multi-omics analysis within the DECIDER observational trial (ClinicalTrials.gov identifier NCT04846933) cohort, we identified that chemo-refractory HGSC is characterized by diminished IFN-I and enhanced hypoxia pathway activities. Importantly, IFN-I pathway activity was independently prognostic for patient survival, highlighting its potential as a biomarker. Our results elucidate the heterogeneity of treatment response at the molecular level and suggest that augmentation of IFN-I response could enhance chemosensitivity in refractory cases. This study underscores the potential of the IFN-I pathway as a therapeutic target and advocates for the initiation of clinical trials testing external modulators of the IFN-I response, promising a significant stride forward in the treatment of refractory HGSC.

cancer biology↗

bioRxiv2019

Estimating the impact of pneumococcal conjugate vaccines on childhood pneumonia in sub-Saharan Africa: A systematic review.

BackgroundThe impact of pneumococcal conjugate vaccine introduction in reducing the incidence of childhood pneumonia has not been well documented in sub-Saharan Africa. Many studies evaluating vaccine impact have used invasive pneumococcal disease or pneumococcal pneumonia as an outcome. ObjectiveTo estimate the impact of routine administration of 10-valent and 13-valent PCV on the incidence of pneumonia in children under five years of age in sub-Saharan Africa. Data sourcesA systematic review was conducted between 16 and 31 July 2019. The review was registered on PROSPERO with registration number CRD42019142369. The literature search was conducted in indexed databases including Medline and Embase, grey literature databases and online libraries of two universities. Manual search of the references of included studies was performed to identify additional relevant studies. The search strategy combined pneumococcal conjugate vaccine, pneumonia and child as search concepts. Study selectionStudies investigating the impact of 10- or13-valent PCV on childhood pneumonia in a sub-Saharan African country were eligible for inclusion. Case-control, cohort, pre-post and time-series study designs were eligible for inclusion. Exclusion criteria were use of 7- or 9-valent PCV, systematic review studies, clinical trials and record publication prior to 2009. Data extractionIndependent data extraction was conducted. Key variables include year study conducted, type of study design, type of PCV used and year of introduction, reported PCV coverage, outcome measure evaluated and the effect measure. Data synthesisEight records were included in the final analysis, 6 records were pre-post or time-series studies, 1 was a case-control study and 1 report combined pre-post and case-control studies. Vaccine impact measured as percentage reduction in risk (%RR) of clinical pneumonia was mostly small and non-significant. The risk reduction was more significant and consistent on radiological and pneumococcal pneumonia. Vaccine effectiveness reported in case-control studies was mostly non-significant. ConclusionEvidence of the positive impact of routine infant pneumococcal vaccination on pneumonia in sub-Saharan Africa is weak. There is a need for more research in this area to evaluate the influence of pathogen or serotype replacement in pneumonia after PCV introduction. Ongoing surveillance is also required to establish the long term trend in pneumonia epidemiology after PCV introduction.

pathology↗

bioRxiv2021

Utilisation of semiconductor sequencing for the detection of predictive biomarkers in glioblastoma

The standard treatment for glioblastoma involves a combination of surgery, radiation and chemotherapy but have limited impact on survival. The exponential increase in targeted agents directed at pivotal oncogenic pathways now provide new therapeutic opportunities for this tumour type. However, lack of comprehensive precision oncology testing at diagnosis means such therapeutic opportunities are potentially overlooked. To investigate the role of semiconductor sequencing for detection of predictive biomarkers in routine glioblastoma samples we have undertaken analysis of test trending data generated by a clinically validated next generation sequencing platform designed to capture 764 of the leading anti-cancer targeted agents/combinations and immunotherapies via analysis of actionable genomic variants distributed across 505 genes. Analysis was performed across a cohort of 55 glioblastoma patients. Analysis of trending data has revealed a complex and rich actionable mutational landscape in which 166 actionable mutations were detected across 36 genes linked to 17 off label targeted therapy protocols and 111 clinical trials. The majority of patients harboured three or more actionable mutations affecting key cancer related regulatory networks including the PI3K/AKT/MTOR and RAS/RAF/MEK/MAPK signalling pathways, DNA-damage repair pathways and cell cycle checkpoints. Linkage with immunotherapy and PARP inhibitors was identified in 44% of glioblastoma patients as a consequence of alterations in DNA-damage repair genes. Taken together our data indicates that precision oncology testing utilising semiconductor sequencing can be used to identify a broad therapeutic armamentarium of targeted therapies and immunotherapies that can be potentially employed for the improved clinical management of glioblastoma patients.

pathology↗

bioRxiv2023

Levetiracetam Modulates Brain Metabolic Networks and Transcriptomic Signatures in the 5XFAD Mouse Model of Alzheimer's disease.

INTRODUCTIONSubcritical epileptiform activity is associated with impaired cognitive function and is commonly seen in patients with Alzheimers disease (AD). The anti-convulsant, levetiracetam (LEV), is currently being evaluated in clinical trials for its ability to reduce epileptiform activity and improve cognitive function in AD. The purpose of the current study was to apply pharmacokinetics (PK), network analysis of medical imaging, gene transcriptomics, and PK/PD modeling to a cohort of amyloidogenic mice to establish how LEV restores or drives alterations in the brain networks of mice in a dose-dependent basis using the rigorous preclinical pipeline of the MODEL-AD Preclinical Testing Core. METHODSChronic LEV was administered to 5XFAD mice of both sexes for 3 months based on allometrically scaled clinical dose levels from PK models. Data collection and analysis consisted of a multi-modal approach utilizing 18F-FDG PET/MRI imaging and analysis, transcriptomic analyses, and PK/PD modeling. RESULTSPharmacokinetics of LEV showed a sex and dose dependence in Cmax, CL/F, and AUC0-{infty}, with simulations used to estimate dose regimens. Chronic dosing at 10, 30, and 56 mg/kg, showed 18F-FDG specific regional differences in brain uptake, and in whole brain covariance measures such as clustering coefficient, degree, network density, and connection strength (i.e. positive and negative). In addition, transcriptomic analysis via nanoString showed dose-dependent changes in gene expression in pathways consistent 18F-FDG uptake and network changes, and PK/PD modeling showed a concentration dependence for key genes, but not for network covariance modeling. DISCUSSIONThis study represents the first report detailing the relationships of metabolic covariance and transcriptomic network changes resulting from LEV administration in 5XFAD mice. Overall, our results highlight non-linear kinetics based on dose and sex, where gene expression analysis demonstrated LEV dose- and concentration-dependent changes, along with cerebral metabolism, and/or cerebral homeostatic mechanisms relevant to human AD, which aligned closely with network covariance analysis of 18F-FDG images. Collectively, this study show cases the value of a multimodal connectomic, transcriptomic, and pharmacokinetic approach to further investigate dose dependent relationships in preclinical studies, with translational value towards informing clinical study design.

neuroscience↗

bioRxiv2021

Early Dynamics of Chronic Myeloid Leukemia on Nilotinib Predicts Deep Molecular Response

Chronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase1,2. ABL1-selective tyrosine kinase inhibitors (TKIs) including nilotinib have dramatically improved the prognosis of patients with CML3-7. The ultimate goal of CML treatment is likely to be TKI-free maintenance of deep molecular response (DMR), which is defined by quantitative measurement of BCR-ABL1 transcripts on the international scale (IS)8, and durable DMR is a prerequisite to reach this goal9. Thus, an algorithm to enable the early prediction of DMR achievement on TKI therapy is quite valuable. Here, we show that our mathematical framework based on a clinical trial dataset10 can accurately predict the response to frontline nilotinib. We found that our simple dynamical model can predict nilotinib response by using two common laboratory findings (observation values): IS11,12 and white blood cell (WBC) count. Furthermore, our proposed method identified patients who failed to achieve DMR with high fidelity according to the data collected only at three initial time points during nilotinib therapy. Since our model relies on the general properties of TKI response, our framework would be applicable to CML patients who receive frontline nilotinib or other TKIs in clinical practice. Significance StatementChronic myeloid leukemia (CML) is a myeloproliferative disorder caused by the BCR-ABL1 tyrosine kinase. The goal of this treatment is the sequential achievement of deep molecular response (DMR). Tyrosine kinase inhibitors (TKIs) are effective in the reduction because they inhibit CML cell proliferation. However, because of individual differences in the TKI efficacy, some patients are unable to achieve DMR, so that early prediction of DMR reachability is necessary for personalized medicine. By combining time series analysis and mathematical modeling, we developed a mathematical method that accurately predicts patients who do not achieve DMR in the early stages of TKI administration. Our prediction method gives a basis of effective personalized treatments for CML patients.

systems biology↗

bioRxiv2025

M4 drug discovery: human drug predictions from integrated pre-clinical insights exemplified with a GLP1-R agonist

A major recent breakthrough in the treatment of type 2 diabetes has been the development of glucagon-like peptide-1 receptor agonists (GLP-1RAs). However, current translational frameworks struggle to predict the clinical outcomes of these drugs from preclinical data. There are several reasons for this struggle, which are generic for many drugs: GLP-1RAs act through multi-timescale mechanisms in which short-term effects propagate into long-term changes; no single preclinical system can capture all their effects in humans; and mechanistic extrapolation requires modelling numerous whole-body biological processes. To address this gap, we present a new extrapolation approach, M4 drug discovery, and retrospectively apply it to the GLP-1RA exenatide in a manner that is generalisable to other drugs. The method integrates: Multi-level data (cellular to whole-body), Multi-timescale data (minutes to months), Multi-species data (e.g., rodents to humans), and Mechanistic knowledge. In this study, we integrate human cell and animal data with drug-free human studies to successfully predict human pharmacokinetics (cost < {chi}2, p=0.05; 64 < 97) and the outcomes of a 30-week clinical trial (36 < 45). We found that integrating information across the four M4 axes improved predictive performance and physiological relevance: multi-species data inform pharmacokinetics, human cell data provide human population- and donor-specific potency estimates, animal data reveal additional drug effects not observable in cell cultures, and the multi-timescale mathematical modelling enables short-term effects of exenatide and meals to inform long-term changes in insulin sensitivity. This work provides new tools for drug extrapolations, supporting the community towards safer and more informed preclinical-to-clinical drug extrapolations.

systems biology↗

bioRxiv2017

Combining CRISPR/Cas9 mutagenesis and a small-molecule inhibitor to probe the function of MELK in cancer

The Maternal Embryonic Leucine Zipper Kinase (MELK) has been identified as a promising therapeutic target in multiple cancer types. MELK over-expression is associated with aggressive disease, and MELK has been implicated in numerous cancer-related processes, including chemotherapy resistance, stem cell renewal, and tumor growth. On the basis of these findings, a MELK inhibitor is currently being tested in several clinical trials. Here, we report that cancer cell lines harboring CRISPR/Cas9-induced null mutations in MELK exhibit wild-type growth in vitro, under environmental stress, in the presence of multiple chemotherapy agents, and in vivo. By combining our MELK-knockout clones with a recently-described, highly-specific MELK inhibitor, we further demonstrate that the acute inhibition of MELK results in no specific anti-proliferative phenotype. Analysis of gene expression data from cohorts of cancer patients identifies MELK expression as a correlate of tumor mitotic activity, explaining its association with poor clinical prognosis. In total, our results demonstrate the power of CRISPR/Cas9-based genetic approaches to investigate cancer drug targets, and call into question the rationale for treating patients with anti-MELK monotherapies.

cancer biology↗