Vivek Sagar
A5009817584- Cancer Genomics and Diagnostics
- Pancreatic and Hepatic Oncology Research
- Computational Drug Discovery Methods
- Single-cell and spatial transcriptomics
- Innovative Microfluidic and Catalytic Techniques Innovation
- Lung Cancer Treatments and Mutations
- Cell Image Analysis Techniques
- CRISPR and Genetic Engineering
- Cholinesterase and Neurodegenerative Diseases
- Phosphodiesterase function and regulation
- Enzyme function and inhibition
- Genetics, Bioinformatics, and Biomedical Research
- Advanced Electron Microscopy Techniques and Applications
- CAR-T cell therapy research
- Monoclonal and Polyclonal Antibodies Research
Novartis (United States)
2024-2025
P-cadherin (pCAD) and LI-cadherin (CDH17) are cell-surface proteins belonging to the cadherin superfamily that both highly expressed in colorectal cancer. This co-expression profile presents a novel attractive opportunity for dual targeting approach using an antibody–drug conjugate (ADC). In this study, we used unique avidity-driven vitro screening generate pCAD x CDH17 bispecific antibodies selectively target cells expressing antigens over only or CDH17. Based on binding inhibition of cell...
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Abstract For a majority of patients with non–small cell lung cancer EGFR mutations, treatment inhibitors (EGFRi) induces clinical response. Despite this initial reduction in tumor size, residual disease persists that leads to relapse. Elucidating the preexisting biological differences between sensitive cells and surviving drug-tolerant persister deciphering how evolve response could help identify strategies improve efficacy EGFRi. In study, we tracked origins clonal evolution at high...
Abstract Cancer progression and response to therapy are inextricably reliant on the coevolution of a supportive tissue microenvironment. This is particularly evident in pancreatic ductal adenocarcinoma, tumor type characterized by expansive heterogeneous stroma. Herein, we employed single-cell RNA sequencing spatial transcriptomics normal, inflamed, malignant tissues contextualize stromal dynamics associated with disease treatment status, identifying temporal trajectories fibroblast...
<p>Integration of single-cell and spatial transcriptomics reveals spatially defined fibroblast populations. <b>A,</b> Marker gene expression for clusters overlayed on untreated PDAC sample HTB2779. Black box corresponds to that in whole mount image <b>B</b>. <b>B,</b> Whole progressively higher magnifications H&E-stained section Scale bars, 2 mm (left), 300 μm (middle), 60 (right). The locations histologically cancer glands are indicated by black...
<p>Genetic and transcriptomic features define distinct ductal cell populations. <b>A,</b> UMAP projection based on the top five PCs of transcriptomes. <b>B,</b> Bubble plot demonstrating relative expression marker genes across clusters. The intensity color is proportional to average within a cluster, bubble size number cells expressing marker. <b>C,</b> Quantification each cluster tissue types. <b>D,</b> projections KRAS mutation status...
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<p>TGFβ is a key mediator of gene expression in both cancer cells and CAFs. <b>A</b> <b>B,</b> Circos plots depicting inferred ligand-to-target signaling between target genes (red) fibroblasts (<b>A</b>) (<b>B</b>) their associated paracrine (blue) or autocrine (yellow) ligands identified using NicheNet. Selected represent those enriched CAFs transitional from untreated PDAC, relative to normal ductal (<b>B</b>). Within each...
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<p>Distinct fibroblast populations are associated with tissue types. <b>A,</b> UMAP projection based on the top five PCs of single-cell transcriptomes. <b>B,</b> projections single cells from each type (colored) contributing to (gray). <b>C,</b> autoimmune (left) and idiopathic (right) chronic pancreatitis samples <b>D,</b> Quantification cluster within <b>E,</b> Bubble plot demonstrating relative expression marker genes...
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<p>Fibroblasts drive intercellular communication in the tumor microenvironment of PDAC. <b>A,</b> Aggregated cell–cell network normal pancreas, pancreatitis, untreated PDAC, and NAT-PDAC samples showing signaling (edges) sent from each cell population (nodes) inferred using CellChat. The edge weights between any two populations are scaled to reflect total number interactions. All fibroblast cells shown as one population, depict overall interactome driven by compartment a...
<div>Abstract<p>Cancer progression and response to therapy are inextricably reliant on the coevolution of a supportive tissue microenvironment. This is particularly evident in pancreatic ductal adenocarcinoma, tumor type characterized by expansive heterogeneous stroma. Herein, we employed single-cell RNA sequencing spatial transcriptomics normal, inflamed, malignant tissues contextualize stromal dynamics associated with disease treatment status, identifying temporal trajectories...
<p>scRNA-seq of human pancreatic tissues. <b>A,</b> Schematic representation the types tissues employed in this study and experimental pipeline for their analysis by scRNA-seq. <b>B,</b> UMAP visualization single cells from all samples colored cell type. <b>C,</b> projections each tissue type (colored) contributing to global (gray). <b>D,</b> Representative images H&E-stained sections Scale bar, 100 μm. <b>E,</b>...
<p>Differentiation of fibroblasts is coupled with a loss transcriptional regulatory programs. <b>A,</b> Trajectory analysis fibroblast subclusters inferred by Slingshot. <b>B,</b> Gene expression CAF marker genes plotted along the pseudotime trajectory leading to CAFs. Expression values in natural-log scale. <b>C,</b> RNA velocity cells. <b>D,</b> Volcano plots DE between populations. Transcription factors that are populations, an...