Biology subjects

Hitomi, M.

Publications and source records attributed to Hitomi, M..

9 recordsLinked to original sources

bioRxiv2026

Collateral sensitivities with predictive signatures emerge in a novel model of evolved chemoresistance in osteosarcoma

Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. Despite aggressive multimodal therapy, including surgery and chemotherapy with methotrexate, doxorubicin, and cisplatin (MAP), outcomes for patients with relapsed or refractory disease remain poor, with no standardized second-line regimen. We developed a clinically calibrated, temporally resolved in vitro model to examine how resistance and collateral drug responses evolve during treatment with methotrexate, doxorubicin, and cisplatin (MAP). We modeled the evolution of chemotherapy resistance in vitro by exposing an OS cell line, MG63.3, to clinically relevant cycles of MAP therapy. MAP resistance and collateral drug responses were quantified over time across five independent evolutionary replicates, and three solvent-treated replicates served as controls. We complemented this phenotypic screening with transcriptomic profiling to extract predictive biomarkers of collateral drug response that could be used to personalize second-line treatment in patients with refractory OS. MAP exposure produced progressive resistance to doxorubicin and methotrexate, whereas cisplatin sensitivity remained comparatively stable. Repeated temporal screening against 12 additional drugs and combinations revealed three broad patterns of collateral response: progressive resistance, progressive sensitivity, and non-linear or stochastic change. Etoposide resistance emerged consistently, while sensitivity developed toward palifosfamide-etoposide and gemcitabine-docetaxel. Transcriptomic profiling showed dynamic, replicate-specific evolutionary trajectories rather than a single uniform resistance state. To demonstrate one approach for how our large, paired dataset could be used to translate these findings into potentially actionable clinical tools, we extracted predictive gene expression signatures of collateral drug response. By applying a dynamic, clinically inspired model of chemotherapy resistance in OS, we generated a detailed temporal mapping of collateral drug responses that highlights potential therapeutic windows and can be used inform selection of second-line agents. This approach and the resulting dataset can ultimately support personalized medicine strategies for patients with relapsed or refractory OS.

cancer biology↗

bioRxiv2023

Alamar Blue assay optimization to minimize druginterference and inter-assay viability

Alamar Blue (AB) has become an increasingly popular reagent of choice for cell viability assays. We chose AB over other reagents such as MTT and Cell-Titer Glo due to its cost effectiveness and its ability to be a nondestructive assay. While analyzing the effect of osimertinib, an EGFR inhibitor on the non-small cell lung cancer cell line, PC-9, we noticed unexpected right-shifts of dose response curves as compared to the curve obtained by Cell Titer Glo assay. Here, we describe our modified AB assay method to avoid right shift right shift in dose response curve. Unlike some of the redox drugs that were reported to directly affected AB reading, osimertinib itself did not directly increase AB reading. Yet, the removal of the drug containing medium prior to AB addition eliminated falsely increased reading giving comparable dose response curve as the one determined by Cell Titer Glo assay. When a panel of 11 drugs were assessed, we found that this modified AB assay eliminated unexpected similar right shifts detected in other epidermal growth factor receptor (EGFR) inhibitors. We also found that plate-to-plate variability can be minimized by adding an appropriate concentration of rhodamine B solution to the assay plates to calibrate fluorimeter sensitivity. This calibration method also enables a continuous longitudinal assay to monitor cell growth or recovery from drug toxicity over time. Our new modified AB assay is expected to provide accurate in vitro measurement of EGFR targeted therapies.

cell biology↗

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

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↗

bioRxiv2019

Asymmetric Division Promotes Therapeutic Resistance In Glioblastoma Stem Cells

Asymmetric cell division (ACD) enables the maintenance of a stem cell population while simultaneously generating differentiated progeny. Cancer stem cells (CSCs) undergo multiple modes of cell division during tumor expansion and in response to therapy, yet the functional consequences of these division modes remain to be determined. Using a fluorescent reporter for cell surface receptor distribution during mitosis, we found that ACD in glioblastoma CSCs generated a daughter cell with enhanced therapeutic resistance and increased co-inheritance of epidermal growth factor receptor (EGFR) and neurotrophin receptor (p75NTR). Stimulation of both receptors maintained self-renewal under differentiation conditions. While p75NTR knockdown did not compromise CSC maintenance, therapeutic efficacy of EGFR inhibition was enhanced, indicating that co-inheritance of p75NTR and EGFR promotes resistance to EGFR inhibition through a redundant mechanism. These data demonstrate that ACD produces progeny with co-enriched growth factor receptors, which contributes to the generation of a more therapeutically resistant CSC population.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC=\"FIGDIR/small/569962_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (41K):\norg.highwire.dtl.DTLVardef@15cc472org.highwire.dtl.DTLVardef@1654633org.highwire.dtl.DTLVardef@1e3ec1forg.highwire.dtl.DTLVardef@a2eb45_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

cancer biology↗

bioRxiv2018

Therapeutic suppression of proteolipid protein rescues Pelizaeus-Merzbacher Disease in mice

Mutations in proteolipid protein 1 (PLP1) result in failure of myelination and severe neurological dysfunction in the X-linked pediatric leukodystrophy Pelizaeus-Merzbacher disease (PMD). The majority of PLP1 variants, including supernumerary copies and various point mutations, lead to early mortality. However, PLP1-null patients and mice display comparatively mild phenotypes, suggesting that reduction of aberrant PLP1 expression might provide a therapeutic strategy across PMD genotypes. Here we show, CRISPR-Cas9 mediated germline knockdown of Plp1 in the severe jimpy (Plp1jp) point mutation mouse model of PMD rescued myelinating oligodendrocytes, nerve conduction velocity, motor function, and lifespan to wild-type levels, thereby validating PLP1 suppression as a therapeutic approach. To evaluate the therapeutic potential of Plp1 suppression in postnatal PMD mice, we tested antisense oligonucleotides (ASOs) that stably decrease mouse Plp1 mRNA and protein in vivo. Administration of a single intraventricular dose of Plp1-targeted ASOs to postnatal jimpy mice increased myelination, improved motor behavior, and extended lifespan through an 8-month endpoint. Collectively, these results support the development of PLP1 suppression as a disease-modifying therapy for most PMD patients. More broadly, we demonstrate that RNA therapeutics can be delivered to oligodendrocytes in vivo to modulate neurological function and lifespan, opening a new treatment modality for myelin disorders.

neuroscience↗

bioRxiv2018

High-throughput Automated Single Cell Imaging Analysis Reveals Dynamics Of Glioblastoma Stem Cell Population During State Transition

Cancer stem cells (CSCs) are a heterogeneous and dynamic population that stands at the top of tumor cellular hierarchy and is responsible for maintenance of the tumor microenvironment. As methods of CSC isolation and functional interrogation advance, there is a need for a reliable and accessible quantitative approach to assess heterogeneity and state transition dynamics in CSCs. We developed a High-throughput Automated Single Cell Imaging Analysis (HASCIA) approach for quantitative assessment of protein expression with single cell resolution and applied the method to investigate spatiotemporal factors that influence CSC state transition using glioblastoma (GBM) CSC as a model system. We were able to validate the quantitative nature of this approach through comparison of the protein expression levels determined by HASCIA to those determined by immunoblotting. A virtue of HASCIA was exemplified by detection of a subpopulation of SOX2-low cells, which expanded in fraction size during state transition. HASCIA also revealed that CSCs were committed to loose stem cell state at an earlier time point than the average SOX2 level decreased. Functional assessment of stem cell frequency in combination with quantification of SOX2 expression by HASCIA defined a stable cut-off of SOX2 expression level for stem cell state. We also developed an approach to assess local cell density and found that denser monolayer areas possess higher average levels of SOX2, higher cell diversity and a presence of a sub-population of slowly proliferating SOX2-low CSCs. HASCIA is an open source software that facilitates understanding the dynamics of heterogeneous cell population such as that of CSCs and their progeny. It is a powerful and easy-to-use image analysis and statistical analysis tool available at https://hascia.lerner.ccf.org.

cancer biology↗

bioRxiv2018

Development of a Cx46 targeting strategy for cancer stem cells

Gap junction-mediated cell-cell communication enables tumor cells to synchronize the execution of complex processes. Despite the connexin family of gap junction proteins being considered tumor suppressors, we previously found that glioblastoma cancer stem cells (CSCs) express higher levels of Cx46 compared to non-stem tumor cells, and this was necessary and sufficient for CSC maintenance. To develop a Cx46 targeting strategy, we utilized point mutants to disrupt specific functions of Cx46 and found that gap junction coupling was the critical function of Cx46 for CSCs. Based on this finding, we screened a clinically relevant library of small molecules and identified clofazimine as an inhibitor of Cx46-specific cell-cell communication. Clofazimine attenuated proliferation, self-renewal, and tumor growth and synergized with temozolomide to induce apoptosis. These data suggest that combining clofazimine with standard-of-care therapies may target glioblastoma CSCs. Furthermore, these results demonstrate the importance of targeting cell-cell communication as an anti-cancer therapy.

cancer biology↗

bioRxiv2017

Recasting the cancer stem cell hypothesis: unification using a continuum model of microenvironmental forces

Since the first evidence for cancer stem cells in leukemia, experimentalists have sought to identify tumorigenic subpopulations in solid tumors. In parallel, scientists have argued over the implications of the existence of this subpopulation. On one side, the cancer stem cell hypothesis posits that a small subset of cells within a tumor are responsible for tumorigenesis and are capable of recapitulating the entire tumor on their own. Under this hypothesis, a tumor may be conceptualized as a series of coupled compartments, representing populations of progressively differentiated cell types, starting from stem cells. The allure of this model is that it elegantly explains our therapeutic failures: we have been targeting the wrong cells. Alternatively, the stochastic model states that all cells in a tumor can have stem-like properties, and have an equally small capability of forming a tumor. As tumors are, by nature, heterogeneous, there is ample evidence to support both hypotheses. We propose a mechanistic mathematical description that integrates these two theories, settling the dissonance between the schools of thought and providing a road map for integrating disparate experimental results into a single theoretical framework. We present experimental results from clonogenic assays that demonstrate the importance of defining this novel formulation, and the clarity that is provided when interpreting these results through the lens of this formulation.

cancer biology↗