Biology subjects

Durmaz, A.

Publications and source records attributed to Durmaz, A..

9 recordsLinked to original sources

bioRxiv2026

Urothelial-lineage master transcription factor hub proteomics shows mechanisms impeding urothelial cancer cell differentiation

Urothelial cancer (UC) cells of the luminal subtype exhibit partial, incomplete differentiation towards umbrella cells that line bladder lumen, seen by morphology and gene expression. Differentiation is stalled even though the cells express master transcription factors (MTFs) that drive luminal urothelial differentiation, e.g., FOXA1 and CEBPB, at levels seen in normal differentiated urothelium. We therefore analyzed the FOXA1/CEBPB MTF hub by mass spectrometry. SWI/SNF coactivator complex (CoA) components, e.g., SMARCA4, ARID1A, that read the epigenetic activation mark histone 3 lysine 27 acetylation (H3K27ac) and use ATP-hydrolysis to open chromatin, were the most abundant proteins pulled-down with FOXA1/CEBPB. However, genes for these and other CoA, e.g., CREBBP, EP300 that write H3K27ac, were mutated/deleted in >95% of UCs in clinical series. Also contained in the hub were corepressors (CoR) that erase H3K27ac and close chromatin, e.g., HDAC1, CHD4 - genes for these CoR were recurrently gained in UCs. Chromatin analyses showed H3K27ac-centered remodeling was needed to activate umbrella but not constitutively accessible cell growth/division/housekeeping genes. Restoring ARID1A into ARID1A-mutated UC cells using lentiviral transduction, or inhibiting CoR with siRNA or small molecules, activated umbrella genes and terminated replications. In summary, UC-genesis selects for loss- and gain-of-function of CoA and CoR respectively in the urothelial-lineage MTF hub; small molecule CoR-inhibitors are candidate remedies to renew maturation towards terminal differentiated-fates. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/744501v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@bda7e5org.highwire.dtl.DTLVardef@159ea57org.highwire.dtl.DTLVardef@28132borg.highwire.dtl.DTLVardef@1028bee_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Cell-Cell Fusion in NSCLC Confers a Fitness Benefit Under Drug Selection

Cell-cell fusion has been implicated in various physiological and pathological processes, including cancer progression. This study investigated the role of cell-cell fusion in non-small cell lung cancer (NSCLC), focusing on its contribution to chemoresistance and tumor evolution. By co-culturing drug-sensitive and drug-resistant NSCLC cell lines, we observed spontaneous cell-cell fusion events, particularly under gefitinib selection. These fused cells exhibited enhanced fitness and a higher degree of chemoresistance compared to parental lines across a panel of 12 chemotherapeutic agents. Further analysis, including fluorescence imaging and cell cycle analysis, confirmed nuclear fusion and increased DNA content in the fused cells. Bulk RNA sequencing revealed genomic heterogeneity in fused cells, including enrichment of gene sets associated with cell cycle progression and epithelial-mesenchymal transition, both of which are hallmarks of cancer. These findings demonstrate that cell-cell fusion can act as a novel source of chemotherapeutic resistance and further promote aggressive phenotypes in NSCLC, highlighting the potential of fusion as a therapeutic target.

cancer biology↗

bioRxiv2023

Frequency-dependent ecological interactions increase the prevalence and shape the distribution of pre-existing drug resistance

The evolution of resistance remains one of the primary challenges for modern medicine from infectious diseases to cancers. Many of these resistance-conferring mutations often carry a substantial fitness cost in the absence of treatment. As a result, we would expect these mutants to undergo purifying selection and be rapidly driven to extinction. Nevertheless, pre-existing resistance is frequently observed from drug-resistant malaria to targeted cancer therapies in non-small cell lung cancer (NSCLC) and melanoma. Solutions to this apparent paradox have taken several forms from spatial rescue to simple mutation supply arguments. Recently, in an evolved resistant NSCLC cell line, we found that frequency-dependent ecological interactions between ancestor and resistant mutant ameliorate the cost of resistance in the absence of treatment. Here, we hypothesize that frequency-dependent ecological interactions in general play a major role in the prevalence of pre-existing resistance. We combine numerical simulations with robust analytical approximations to provide a rigorous mathematical framework for studying the effects of frequency-dependent ecological interactions on the evolutionary dynamics of pre-existing resistance. First, we find that ecological interactions significantly expand the parameter regime under which we expect to observe pre-existing resistance. Next, even when positive ecological interactions between mutants and ancestors are rare, these resistant clones provide the primary mode of evolved resistance because even weak positive interaction leads to significantly longer extinction times. We then find that even in the case where mutation supply alone is sufficient to predict pre-existing resistance, frequency-dependent ecological forces still contribute a strong evolutionary pressure that selects for increasingly positive ecological effects (negative frequency-dependent selection). Finally, we genetically engineer several of the most common clinically observed resistance mechanisms to targeted therapies in NSCLC, a treatment notorious for pre-existing resistance. We find that each engineered mutant displays a positive ecological interaction with their ancestor. As a whole, these results suggest that frequency-dependent ecological effects can play a crucial role in shaping the evolutionary dynamics of pre-existing resistance.

evolutionary biology↗

bioRxiv2022

TP53 mutations in endometrial cancer contribute to clinically-relevant radiation resistance and highlight the potential for biomarker-driven radiosensitization strategies.

Endometrial cancer (EC) is the most common type of gynecologic malignancy in the United States, with over 66, 200 new cases expected in 2023. The number of mortalities per year now approximate that of ovarian cancer. Despite our ability to identify different biologic clusters of EC, we have yet to understand the functional impact of key genomic alterations associated with discrepant prognoses and exploit this knowledge for therapeutic benefit. Given this, we set out to determine how alterations in p53 signaling, as conferred my TP53 mutations, impact radiotherapy response in EC. We also explored if manipulation of this signaling pathway could be utilized as a radio-sensitization strategy in EC. Our work demonstrates that p53 signaling plays a significant role in radiotherapy response for EC and that leveraging this genomic data may allow us to exploit this pathway as a viable radiotherapeutic target in a significant number of EC cases.

cancer biology↗

bioRxiv2021

Variability in scRNA-Seq analysis is mitigated by regularized or supervised approaches

Transcriptional dynamics of evolutionary processes through time are highly complex and require single-cell resolution datasets. This is especially important in cancer during the evolution of resistance, where stochasticity can lead to selection for divergent transcriptional mechanisms. Statistical methods developed to address various questions in single-cell datasets are prone to variability and require careful adjustments of multiple parameter space. To assess the impact of this variation, we utilized commonly used single-cell RNA-Seq analysis tools in a combinatorial fashion to evaluate how repeatable the results are when different methods are combined. In the context of clustering and trajectory estimation, we benchmark the combinatorial space and highlight ares and methods that are sensitive to parameter changes. We have observed that utilizing temporal information in a supervised framework or regularization in latent modeling reduces variability leading to improved overlap when different parameters/methods are used. We hope that future studies can benefit from the results presented here as use of scRNA-Seq analysis tools as out of the box is becoming a standard approach in cancer research.

bioinformatics↗

bioRxiv2020

Dose dependent evolutionary game dynamics modulate competitive release in cancer therapy

Therapeutic strategies for tumor control have traditionally assumed that maximizing reduction in tumor volume correlates with clinical efficacy. Unfortunately, this rapid decrease in tumor burden is almost invariably followed by the emergence of therapeutic resistance. Evolutionary based treatment strategies attempt to delay resistance via judicious treatments that maintain a significant treatable subpopulation. While these strategies have shown promise in recent clinical trials, they often rely on biological conjecture and intuition to derive parameters. In this study we experimentally measure the frequency-dependent interactions between a gefitinib resistant non-small cell lung cancer (NSCLC) population and its sensitive ancestor via the evolutionary game assay. We show that cost of resistance is insufficient to accurately predict competitive exclusion and that frequency-dependent growth rate measurements are required. In addition, we show that frequency-dependent growth rate changes may ultimately result in a safe harbor for resistant populations to safely accumulate, even those with significant cost of resistance. Using frequency-dependent growth rate data we then show that gefitinib treatment results in competitive exclusion of the ancestor, while absence of treatment results in a likely, but not guaranteed exclusion of the resistant strain. Finally, using our empirically derived growth rates to constrain simulations, we demonstrate that incorporating ecological growth effects can dramatically change the predicted time to sensitive strain extinction. In addition, we show that higher drug concentrations may not lead to the optimal reduction in tumor burden. Taken together, these results highlight the potential importance of frequency-dependent growth rate data for understanding competing populations, both in the laboratory and the clinic.

cancer biology↗

bioRxiv2020

Development and Characterization of Patient-Derived Xenografts from Non-Small Cell Lung Cancer Brain Metastases

IntroductionThe purpose of this study was to establish and characterize a direct-from patient-derived xenograft (PDX) model of non-small cell lung cancer (NSCLC) brain metastases. MethodsSurgically obtained tissue was implanted subcutaneously and as orthotopic intracranial implants into immunodeficient mice. Histology and DNA loci were compared between original tumor and subsequent PDX passages. Tumors underwent RNA and DNA sequencing and relevant therapeutic targets were identified. Tumor growth rates were assessed following treatment with radiation, MEK inhibitor selumetinib, or MET inhibitor savolitinib. Cell lines were established. ResultsNine NSCLC brain metastases PDXs were established. Morphologically, strong retention of cytoarchitectural features was observed between original patient tumor and subcutaneous and intracranial tumors. Short tandem repeat analysis demonstrated strong concordance between patient tumors and subsequent PDX passages. Transcriptome and mutation analysis revealed high correlation between matched patient and PDX samples. Significant growth inhibition occurred with radiation, with selumetinib in tumors harboring KRAS G12C mutations and with savolitinib in a tumor with MET exon 14 skipping mutation. The combination of radiation and savolitinib resulted in significant tumor growth delay compared to radiation or savolitinib alone our MET exon 14 skipping mutation PDX. Early passage cell strains showed high consistency between patient and PDX tumors. ConclusionWe have established a robust human xenograft model system for investigating NSCLC brain metastases. These PDXs and cell lines show strong phenotypic and molecular correlation with the original patient tumors and provide a valuable resource for testing preclinical therapeutics.

cancer biology↗

bioRxiv2020

Identifying states of collateral sensitivity during the evolution of therapeutic resistance in Ewings sarcoma

Advances in the treatment of Ewings sarcoma (EWS) are desperately needed, particularly in the case of metastatic disease. A deeper understanding of collateral sensitivity, where the evolution of therapeutic resistance to one drug aligns with sensitivity to another drug, may improve our ability to effectively target this disease. For the first time in a solid tumor, we produced a temporal collateral sensitivity map that demonstrates the evolution of collateral sensitivity and resistance in EWS. We found that the evolution of collateral resistance was predictable with some drugs, but had significant variation in response to other drugs. Using this map of temporal collateral sensitivity in EWS, we can see that the path towards collateral sensitivity is not always repeatable, nor is there always a clear trajectory towards resistance or sensitivity. Identifying transcriptomic changes that accompany these states of transient collateral sensitivity could improve treatment planning for EWS patients.

evolutionary biology↗

bioRxiv2020

Impact of immediate cryopreservation on the establishment of patient derived xenografts from head and neck cancer patients.

BackgroundPatient-derived xenografts established from human cancers are important tools for investigating novel anti-cancer therapies. Establishing PDXs requires a significant investment and many PDXs may be used infrequently due to their similarity to existing models, their growth rate, or the lack of relevant mutations. We performed this study to determine whether we could efficiently establish PDXs after cryopreservation to allow molecular profiling to be completed prior to implanting the human cancer. MethodsFresh tumor was split with half used to establish a PDX immediately and half cryopreserved for later implantation. Resulting tumors were assessed histologically and tumors established from fresh or cryopreserved tissues compared as to the growth rate, extent of tumor necrosis, mitotic activity, keratinization, and grade. All PDXs were subjected to short tandem repeat testing to confirm identity and assess similarity between methods. ResultsTumor growth was seen in 70% of implanted cases. No growth in either condition was seen in 30% of tumors. One developed a SCC from the immediate implant but a lymphoproliferative mass without SCC from the cryopreserved specimen. No difference in growth rate was seen. No difference between histologic parameters was seen between the two approaches. ConclusionsFresh human cancer tissue can be immediately cryopreserved and later thawed and implanted to establish PDXs. This resource saving approach allows for tumor profiling prior to implantation into animals thus maximizing the probability that the tumor will be utilized for future research.

cancer biology↗