Biology subjects

Cagan, R. L.

Publications and source records attributed to Cagan, R. L..

4 recordsLinked to original sources

bioRxiv2026

Functional Exploration of African Colorectal Cancer Patients Using Personalised Drosophila Avatars

Colorectal cancer across sub-Saharan Africa presents a growing global health burden, with increasing cases and mortality linked to late diagnosis, limited healthcare access and lack of effective treatments. African patients typically present with aggressive disease marked by distinct genomic signatures, indicating the need for targeted treatment approaches. We integrated genetic modelling, phenotypic scoring, imaging and biochemical analysis to explore how mutations found in individual Nigerian colorectal cancer patients influence drug responsiveness. We used the data from Cancer Genome Atlas to identify mutation profiles specific to Nigerian patients. We then generated ten stable Drosophila melanogaster personalised patient avatar lines designed to model patient genomic profiles. This study focused on three lines; each line included oncogenic RAS plus targeting patient-specific variants. These models exhibited various phenotypes including altered larval size, gut size and reduced survival. Two of the three avatar lines showed improved survival, reduced hindgut proliferation zone expansion and restored redox balance after treatment with regorafenib and trametinib. Mirroring clinical patient responses, we found that response to therapy is dependent on the specific genetic profile of the tumour. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/714433v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@db03forg.highwire.dtl.DTLVardef@ae2750org.highwire.dtl.DTLVardef@196f89dorg.highwire.dtl.DTLVardef@9c1577_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIAfrican colorectal cancer showed distinct mutation patterns that contribute to tumour heterogeneity. C_LIO_LIPatient-derived Drosophila avatars were engineered using tumour-specific genetic mutations with key features of human colorectal cancer. C_LIO_LITreatment with targeted therapies showed responses patterned by tumour genotype. C_LIO_LIResponse patterns indicated the need for personalised for colorectal cancer therapies among diverse populations. C_LI

cancer biology↗

bioRxiv2024

Rigosertib reverses hypertrophic cardiomyopathy in RAF1-associated Noonan syndrome

BackgroundRASopathies constitute a group of rare genetic disorders caused by mutations in genes that reside along the canonical Ras/MAPK signaling pathway, affecting cell growth and differentiation. These syndromes, which include conditions like Noonan syndrome (NS), are characterized by developmental delays, distinctive facial dysmorphia, and a variety of cardiac defects, notably hypertrophic cardiomyopathy (HCM). Despite their prevalence and impact, therapeutic options for RASopathies remain limited. Rigosertib, a novel dual Ras/MAPK and PI3K/AKT pathway inhibitor, is currently in clinical trials for treatment of melanoma and recessive dystrophic epidermolysis bullosa. Here, we identify rigosertib as a candidate therapy for RAF1-associated HCM. Methods and ResultsOur Drosophila screen of clinically relevant drugs and compounds identified rigosertib as broadly effective across a panel of transgenic RASopathy fly transgenic models, indicating that rigosertib may be effective against multiple disease isoforms. Analysis of a Drosophila model targeting a RAF1L613V transgene to the heart found that rigosertib reduced aspects of cardiac hypertrophy. Rigosertib treatment prevented or regressed cellular hypertrophy in human induced pluripotent stem cell-(iPSC-) derived cardiomyocytes homozygous for the NS-associated RAF1S257L allele. We extended these findings to a mammalian model, using Raf1L613V/+ KI mice to explore the therapeutic implications of rigosertib on RAF1-driven HCM. Longitudinal six-week treatment with rigosertib in these mice resulted in significant improvement in left ventricular chamber dimension and posterior wall thickness, total heart mass, size of individual cardiomyocytes (CMs), as well as reversal of cardiac hypertrophy. Rigosertib treatment also led to normalized fetal gene expression and inhibition of ERK and AKT pathway activities in primary CMs isolated from Raf1L613V/+ mice. Cardiac function, as assessed by echocardiography, showed significant improvement in ejection fraction and fractional shortening, with molecular studies confirming downregulation of hypertrophic markers and signaling pathways. Together with the Drosophila data, these mammalian results support the potential and use for rigosertib to reverse pathological hypertrophy in NS through targeted pathway inhibition in patients. Moreover, in addition to its effects in the heart, rigosertib treatment in mice also significantly improved other NS-associated syndromic features, including increasing bone growth and correcting craniofacial abnormalities. ConclusionsTaken together, our findings suggest rigosertib effectively normalizes and reverses RASopathy-associated HCM as well as other NS-associated syndromic features, supporting its potential for development as a promising treatment for RAF1-associated HCM and, potentially, other RASopathies-dependent pathologies. This study not only highlights the therapeutic potential of rigosertib but also demonstrates the utility of an integrated approach using Drosophila, iPSC and mammalian models to elucidate drug effects across complex biological systems.

molecular biology↗

bioRxiv2020

Functional Exploration of Copy Number Alterations in a Drosophila Model of Triple Negative Breast Cancer

Accounting for 10-20% of breast cancer cases, TNBC is associated with a disproportionate number of breast cancer deaths. Despite recent progress, many patients fail to respond to current targeted therapies. Responses to chemotherapy are variable, and the tumor characteristics that determine response are poorly understood. One challenge in studying TNBC is its genomic profile: outside of TP53 loss, most cases are characterized by copy number alterations (CNAs), making modeling the disease in whole animals challenging. We analyzed 186 previously identified CNA regions in breast cancer to rank genes within each region by likelihood of acting as a tumor driver. We characterized a Drosophila p53-Myc model of TNBC, demonstrating aspects of transformation. We then used this model to assess highly ranked genes, identifying 48 as functional drivers. To demonstrate the utility of this functional database, we combined six of these drivers with p53-Myc to generate six 3-hit genotypes. These 3-hit models showed increased aspects of transformation as well as resistance to the standard-of-care chemotherapeutic drug fluorouracil. Our work provides a functional database of CNA-associated TNBC drivers, and uses this database to support the model that increased genetic complexity leads to increased therapeutic resistance. Further, we provide a template for an integrated computational/whole animal approach to identify functional drivers of transformation and drug resistance within CNAs for other tumor types.

genetics↗

bioRxiv2018

Integrated in silico and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network

Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) with disease-promoting kinase network activated by mutant dRetM955T. Structural models for kinases relevant to MTC were generated for virtually screening to identify initial hits that were dissimilar to known kinase inhibitors yet suppressed dRetM955T-induced oncogenicity. We then combined features from the hits and known inhibitors to create a hybrid molecule with improved dRetM955T phenotypic outcome. Our platform provides a framework to efficiently explore novel chemical spaces, develop compounds outside of the current inhibitor chemical space, and correct cancer-causing signaling networks to improve disease prognosis while minimizing whole body toxicity.\n\nAUTHOR SUMMARYEffective and safe treatment of multigenic diseases often involves drugs that modulate whole systems by interacting with multiple nodes in pathways and networks, i.e., polypharmacology. Polypharmacology is increasingly appreciated as a potential desirable property of kinase drugs; however, most known drugs that interact with multiple targets have been identified as such by chance, and most polypharmacological compounds are not chemically unique resembling to structures of known kinase inhibitors. The fruit fly Drosophila has been established as a robust screening platform that provides an inexpensive, rapid, and quantitative measure of whole animal drug response, complementing computational approaches. We present a chemical genetics approach that efficiently combines Drosophila with structural prediction and virtual screening, creating a unique discovery platform. We demonstrate the utility of our approach by developing useful small molecules targeting a kinase network in a Drosophila model of Medullary Thyroid Cancer (MTC) driven by the active mutant dRetM955T.

cancer biology↗