Darren R. Tyson

The paper identifies a KRT13+ hillock-like cell state in LUSC, driven by KLF4, which contributes to therapeutic resistance and heterogeneity.

The paper identifies basal cells as the origin of neuroendocrine-tuft-like tumors in SCLC, revealing lineage plasticity and transcriptional states that mirror human cancer and normal cell injury responses.

The paper investigates how intercellular signaling influences phenotypic transitions in cancer cells using scRNA-seq data and mathematical models, finding that signaling reinforces heterogeneity and robustness in tumor populations.

This study identifies three distinct DDR phenotypes in SCLC associated with chemotherapy response and tumor evolution.

This study identifies purinergic Ca2+ signaling via P2X7 receptors as a mechanism enabling drug tolerance in BRAF-mutant melanoma, with implications for overcoming treatment resistance.

The paper discusses challenges in digital image analysis of cancerous tissues and outlines solutions developed during a 2022 hackathon.

This study shows SCLC cells exist in a continuum of plastic states rather than discrete subtypes, with gene expression patterns linked to cancer hallmarks and potential therapeutic targets.

This paper introduces a method using real-time luminescence to estimate drug response in cell lines, avoiding the need for cell counting and fluorescent labeling.

The paper identifies heterogeneous drug-tolerant persisters (DTPs) as population-level states with distinct division and death rates, showing increased ferroptosis susceptibility.

The paper discusses computational challenges in analyzing multiplexed imaging data and outlines community-driven approaches to address them through workshops and hackathons.

This study disentangles genetic, epigenetic, and stochastic factors contributing to drug-response variability in an in vitro tumor heterogeneity model using PC9 cell lines.

ACDC automates cell detection and counting in time-lapse microscopy images, achieving high accuracy without large annotated datasets.

The paper identifies four SCLC subtypes using a systems approach, with NEv2 being a new subtype, and finds master regulators and destabilizers using BooleaBayes.