Biology subjects

Clendenin, C.

Publications and source records attributed to Clendenin, C..

5 recordsLinked to original sources

bioRxiv2024

Effect of Stroma-directed Drugs in Combination with Chemotherapy Against Pancreatic Cancer- a Preclinical Study

Cytotoxic chemotherapy plays an important role for extending the survival of patients with pancreatic ductal adenocarcinoma (PDAC). To enhance the efficacy of chemotherapy for eradicating the cancer cells, we have compared the standard care chemotherapy (combination of nab-paclitaxel, gemcitabine and cisplatin, NGC) versus NGC plus stroma-directed agents (calcipotriol and losartan, respectively) in a genetically engineered mouse model of PDAC. Over a 2-week study period, MRI was conducted to measure the tumor size and to test the sensitivity of imaging markers derived from diffusion-weighted imaging (DWI), dynamic contrast enhanced MRI (DCE) and magnetization transfer ratio (MTR) for assessing the tumor cellularity and stromal changes. Detailed immunohistochemistry and preliminary single cell RNA sequencing (scRNAseq) study were applied to tumor tissues collected upon euthanasia on day-14. Our major findings are: 1. Compared the untreated controls, NGC chemotherapy induced significant tumor growth inhibition and stromal changes including pronounced reduction of fibroblast associated protein (FAP) level accompanied by increased matrix collagen content, significantly reduced microvascular permeability revealed by DCE corroborated with reduced microvascular density. 2. Losartan+NGC significantly enhanced inhibition of tumor growth beyond NGC and increased lymphocytes infiltration in the tumor which may contribute to enhanced cancer cells eradication. 3. NGC treatment enriched the fraction of mesenchymal (M) subtype while reducing the epithelial (E) subtype of cancer cells compared to the controls, and this trend was reversed by calcipotriol+NGC. In conclusion, our study captured changes in cancer cell and tumor microenvironment in response to chemo stromal therapy versus chemotherapy alone with mechanistic insights.

cancer biology↗

bioRxiv2024

Quantitative MRI Measurements Capture Pancreatic Cancer and Stroma Reactions to New KRAS Inhibitor

PurposeIn pancreatic ductal adenocarcinoma (PDAC), KRAS mutations drive both cancer cell growth and formation of a dense stroma. Small molecule KRAS inhibitors (KRASi) represent a promising new treatment hence clinical tools that can assess early response, detect resistance and/or predict prolonged survival are desirable to understand clinical biology of KRASi. We hypothesized that diffusion-weighted MRI (DWI) can detect cell death while dynamic contrast enhanced MRI (DCE) and magnetization transfer ratio (MTR) imaging are sensitive to tumor microenvironment changes, and these metrics shed insights into tumor size change induced by KRASi treatment. Experimental DesignMultiple preclinical PDAC models including a genetically engineered mouse model (KPC) received MRTX1133, a KRASi specific for KRASG12D mutation. Quantitative imaging markers were corroborated with immunohistochemistry (IHC) analyses. ResultsSignificant increase of tumor apparent diffusion coefficient (a DWI metric) was detected as early as 48h and persisted to Day7 after initiation of KRASi treatment and was strongly correlated with cell death and reduced cellularity, resulting in greatly prolonged median survival in treated mice. Capillary perfusion/permeability (a DCE metric) exhibited an inverse relationship with microvascular density. Distinct responses of KRASG12C versus KRASG12D tumors to MRTX1133 were captured by the MRI metrics corroborated with IHC. When tumors developed resistance to MRTX1133, the imaging marker values exhibited a reversal from those of responding tumors. ConclusionsMultiparametric MRI provides early biological insights of cancer and stromal response to KRASi treatment and sets the stage for testing the utility of these clinically ready MRI methods in patients receiving KRASi therapy. Translational relevanceEmerging small molecule KRAS inhibitors (KRASi) represent a new class of therapy for PDAC. Clinical tools that can provide early biological insights of KRASi therapy are desirable. In PDAC models, we examined a clinically ready imaging protocol that combines MRI-based tumor size, diffusion-weighted MRI (DWI), dynamic contrast enhanced MRI (DCE), and magnetization transfer ratio (MTR) for detection of early response as well as acquired resistance to MRTX1133, a KRASi being evaluated in clinical trials. Our data show that DWI and DCE metrics provided key insights of significant cell death and tumor microenvironment changes underlying tumor size regression as early as 48 hours after KRASi treatment initiation. These MRI metrics also captured resistance to KRASi developed over prolonged treatment. This study has high translational relevance by employing clinically applied MRI methods, an investigational new drug and a genetically engineered mouse model that recapitulates salient features of human PDAC.

cancer biology↗

bioRxiv2024

Single-cell Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper

High-throughput single-cell cytometry data are crucial for understanding involvement of immune system in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In this study, we propose a cytometry masked autoencoder (cyMAE), which offers an automated solution for immunophenotyping tasks including cell type annotation. The cyMAE model is designed to uphold user-defined cell type definitions, thereby facilitating easier interpretation and cross-study comparisons. The cyMAE model operates on a pre-train and fine-tune approach. In the pre-training phase, cyMAE employs Masked Cytometry Modelling (MCM) to learn relationships between protein markers in immune cells solely based on protein expression, without relying on prior information such as cell identity and cell type-specific marker proteins. Subsequently, the pre-trained cyMAE is fine-tuned on multiple specialized tasks via task-specific supervised learning. The pre-trained cyMAE addresses the shortcomings of manual gating and clustering methods by providing accurate and interpretable predictions. Through validation across multiple cohorts, we demonstrate that cyMAE effectively identifies co-occurrence patterns of bound labeled antibodies, delivers accurate and interpretable cellular immunophenotyping, and improves the prediction of subject metadata status. Specifically, we evaluated cyMAE for cell type annotation and imputation at the cellular-level and SARS-CoV-2 infection prediction, secondary immune response prediction against COVID-19, and prediction of the infection stage in COVID-19 progression at the subject-level. The introduction of cyMAE marks a significant step forward in immunology research, particularly in large-scale and high-throughput human immune profiling. This approach offers new possibilities for predicting and interpreting cellular-level and subject-level phenotypes in both health and disease.

bioinformatics↗

bioRxiv2023

Tumor-selective effects of active RAS inhibition in pancreatic ductal adenocarcinoma

Broad-spectrum RAS inhibition holds the potential to benefit roughly a quarter of human cancer patients whose tumors are driven by RAS mutations. However, the impact of inhibiting RAS functions in normal tissues is not known. RMC-7977 is a highly selective inhibitor of the active (GTP-bound) forms of KRAS, HRAS, and NRAS, with affinity for both mutant and wild type (WT) variants. As >90% of human pancreatic ductal adenocarcinoma (PDAC) cases are driven by activating mutations in KRAS, we assessed the therapeutic potential of RMC-7977 in a comprehensive range of PDAC models, including human and murine cell lines, human patient-derived organoids, human PDAC explants, subcutaneous and orthotopic cell-line or patient derived xenografts, syngeneic allografts, and genetically engineered mouse models. We observed broad and pronounced anti-tumor activity across these models following direct RAS inhibition at doses and concentrations that were well-tolerated in vivo. Pharmacological analyses revealed divergent responses to RMC-7977 in tumor versus normal tissues. Treated tumors exhibited waves of apoptosis along with sustained proliferative arrest whereas normal tissues underwent only transient decreases in proliferation, with no evidence of apoptosis. Together, these data establish a strong preclinical rationale for the use of broad-spectrum RAS inhibition in the setting of PDAC.

cancer biology↗

bioRxiv2023

Prior vaccination enhances immune responses during SARS-CoV-2 breakthrough infection with early activation of memory T cells followed by production of potent neutralizing antibodies

SARS-CoV-2 infection of vaccinated individuals is increasingly common but rarely results in severe disease, likely due to the enhanced potency and accelerated kinetics of memory immune responses. However, there have been few opportunities to rigorously study early recall responses during human viral infection. To better understand human immune memory and identify potential mediators of lasting vaccine efficacy, we used high-dimensional flow cytometry and SARS-CoV-2 antigen probes to examine immune responses in longitudinal samples from vaccinated individuals infected during the Omicron wave. These studies revealed heightened Spike-specific responses during infection of vaccinated compared to unvaccinated individuals. Spike-specific CD4 T cells and plasmablasts expanded and CD8 T cells were robustly activated during the first week. In contrast, memory B cell activation, neutralizing antibody production, and primary responses to non-Spike antigens occurred during the second week. Collectively, these data demonstrate the functionality of vaccine-primed immune memory and highlight memory T cells as rapid responders during SARS-CoV-2 infection.

immunology↗