Biology subjects

Hitt, M.

Publications and source records attributed to Hitt, M..

4 recordsLinked to original sources

bioRxiv2026

Machine Learning Ensemble Reveals Distinct Molecular Pathways of Retinal Damage in Spaceflown Mice

BackgroundSpaceflight-associated neuro-ocular syndrome (SANS) poses significant risks to astronaut visual health during long-duration missions, yet its underlying molecular mechanisms remain incompletely understood. Oxidative stress and apoptosis are candidate molecular drivers, but their transcriptomic signatures in spaceflight-exposed retinal tissue have not been systematically characterized. MethodsWe applied a machine learning ensemble of linear regression models to predict two ocular phenotypes: 4-hydroxynonenal (4-HNE) immunostaining as a marker of lipid peroxidation-mediated oxidative damage; and TUNEL positivity as a marker of apoptotic cell death. In this observational study, we use bulk retinal gene expression data obtained from a controlled experiment with ground control and spaceflown mice to predict these phenotypes. Gene Ontology pathway enrichment was performed on the most predictive gene sets for each phenotype. ResultsThe 4-HNE phenotype was predicted by genes that converge on membrane-associated pathways, photoreceptor protein modification, synaptic dysfunction, and extracellular matrix dysregulation, including B2m, Tf, Cnga1, mt-Nd1, Snap25, and Efemp1. The genes predicting the TUNEL phenotype revealed a distinct signature emphasizing stress-induced apoptosis, rod photoreceptor degeneration, and endoplasmic reticulum dysfunction, with Ddit4, Nrl, Rom1, Reep6, and Gabarapl1 emerging as central regulators. ConclusionsOxidative lipid peroxidation and apoptotic cell death represent complementary and molecularly distinct pathological mechanisms in spaceflight-exposed murine retinal tissue. The gene signatures provide a putative molecular framework for developing noninvasive biomarkers and therapeutic targets to monitor and protect astronaut visual health during long-duration and deep-space missions.

bioinformatics↗

bioRxiv2022

Establishing combination PAC-1 and TRAIL regimens for treating ovarian cancer based on patient-specific pharmacokinetic profiles using in silico clinical trails

Ovarian cancer is commonly diagnosed in its late stages, and new treatment modalities are needed to improve patient outcomes and survival. We have recently established the synergistic effects of combination tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) and procaspase activating compound (PAC-1) therapies in granulosa cell tumours (GCT) of the ovary, a rare form of ovarian cancer, using a mathematical model of the effects of both drugs in a GCT cell line. Here, to understand the mechanisms of combined TRAIL and PAC-1 therapy, study the viability of this treatment strategy, and accelerate preclinical translation, we leveraged our mathematical model in combination with population pharmacokinetics (PopPK) models of both TRAIL and PAC-1 to expand a realistic heterogeneous cohort of virtual patients and optimize treatment schedules. Using this approach, we investigated treatment responses in this virtual cohort and determined optimal therapeutic schedules based on patient-specific pharmacokinetic characteristics. Our results showed that schedules with high initial doses of PAC-1 were required for therapeutic efficacy. Further analysis of individualized regimens revealed two distinct groups of virtual patients within our cohort: one with high PAC-1 elimination, and one with normal PAC-1 elimination. In the high elimination group, high weekly doses of both PAC-1 and TRAIL were necessary for therapeutic efficacy, however virtual patients in this group were predicted to have a worse prognosis when compared to those in the normal elimination group. Thus, PAC-1 pharmacokinetic characteristics, particularly clearance, can be used to identify patients most likely to respond to combined PAC-1 and TRAIL therapy. This work underlines the importance of quantitative approaches in preclinical oncology.

cancer biology↗

bioRxiv2019

Breast tumor-associated metalloproteases restrict reovirus oncolysis by cleaving the σ1 cell-attachment protein, and can be overcome by mutation of σ1

Reovirus is undergoing clinical testing as an oncolytic therapy for breast cancer. Given that reovirus naturally evolved to thrive in enteric environments, we sought to better understand how breast tumor microenvironments impinge on reovirus infection. Reovirus was treated with extracellular extracts generated from polyoma virus middle T-antigen-derived mouse breast tumors. Unexpectedly, these breast tumor extracellular extracts inactivated reovirus, reducing infectivity of reovirus particles by 100-fold. Mechanistically, inactivation was attributed to proteolytic cleavage of the viral cell attachment protein {sigma}1, which diminished virus binding to sialic acid-low tumor cells. Among various specific protease class inhibitors and metal ions, EDTA and ZnCl2 effectively modulated {sigma}1 cleavage, indicating that breast tumor-associated zinc-dependent metalloproteases are responsible for reovirus inactivation. Moreover, media from MCF7, MB468, MD-MB-231 and HS578T breast cancer cell lines recapitulated {sigma}1 cleavage and reovirus inactivation, suggesting that inactivation of reovirus is shared among mouse and human breast cancers, and that breast cancer cells in by themselves can be a source of reovirus-inactivating proteases. Binding assays and quantification of sialic acid (SA) levels on a panel of cancer cells showed that truncated {sigma}1 reduced virus binding to cells with low surface SA. To overcome this restriction, we generated a reovirus mutant with a mutation (T249I) in {sigma}1 that prevents {sigma}1 cleavage and inactivation by breast tumor-associated proteases. The mutant reovirus showed similar replication kinetics in tumorigenic cells, equivalent toxicity as wild-type reovirus in a severely compromised mouse model, and increased tumor titers. Overall, the data shows that tumor microenvironments have the potential to reduce infectivity of reovirus.\n\nSIGNIFICANCEWe demonstrate that metalloproteases in breast tumor microenvironments can inactivate reovirus. Our findings expose that tumor microenvironment proteases could have negative impact on proteinaceous cancer therapies such as reovirus, and that modification of such therapies to circumvent inactivation by tumor metalloproteases merits consideration.

microbiology↗

bioRxiv2018

Estrogen receptor regulates hormone-induced growth arrest in a luminal A like breast cancer model

Estrogen receptor positive (ER+) breast cancer has been divided into two subtypes, luminal A and luminal B, which differ in their ER expression and response to hormone therapy. The absence of luminal A cell lines means the extensive amount of in vitro work studying the response to hormones in ER+ breast cancers is biased for the luminal B subtype. We have developed a luminal A like cell model by increasing the ER expression in the MCF-7 cell line. Our results show that increased ER expression promotes an anti-proliferative response to estrogen through regulation of genes involved in the G1/S-phase transition of the cell cycle. Furthermore, increased ER expression increases ER-DNA binding in the absence of estrogen and regulates basal gene transcription by promoting DNA looping. These results provide novel evidence that the characteristic increased ER expression of luminal A tumors may promote a novel chromatin configuration that enables growth of these tumors in the absence of estrogen and enables gene repression in the presence of hormones.

pathology↗