University of Texas Southwestern Medical Center

About: University of Texas Southwestern Medical Center is a healthcare organization based out in Dallas, Texas, United States. It is known for research contribution in the topics: Population & Cancer. The organization has 39107 authors who have published 75242 publications receiving 4497256 citations. The organization is also known as: UT Southwestern & UT Southwestern Medical School.

Phase separation of signaling molecules promotes T cell receptor signal transduction

Abstract: Activation of various cell surface receptors triggers the reorganization of downstream signaling molecules into micrometer- or submicrometer-sized clusters. However, the functional consequences of such clustering have been unclear. We biochemically reconstituted a 12-component signaling pathway on model membranes, beginning with T cell receptor (TCR) activation and ending with actin assembly. When TCR phosphorylation was triggered, downstream signaling proteins spontaneously separated into liquid-like clusters that promoted signaling outputs both in vitro and in human Jurkat T cells. Reconstituted clusters were enriched in kinases but excluded phosphatases and enhanced actin filament assembly by recruiting and organizing actin regulators. These results demonstrate that protein phase separation can create a distinct physical and biochemical compartment that facilitates signaling.

Activating and resistance mutations of EGFR in non-small-cell lung cancer: role in clinical response to EGFR tyrosine kinase inhibitors.

Abstract: The epidermal growth factor receptor tyrosine kinase inhibitors (EGFR TKIs), gefitinib and erlotinib, are reversible competitive inhibitors of the tyrosine kinase domain of EGFR that bind to its adenosine-5' triphosphate-binding site. Somatic activating mutations of the EGFR gene, increased gene copy number and certain clinical and pathological features have been associated with dramatic tumor responses and favorable clinical outcomes with these agents in patients with non-small-cell lung cancer (NSCLC). The specific types of activating mutations that confer sensitivity to EGFR TKIs are present in the tyrosine kinase (TK) domain of the EGFR gene. Exon 19 deletion mutations and the single-point substitution mutation L858R in exon 21 are the most frequent in NSCLC and are termed 'classical' mutations. The NSCLC tumors insensitive to EGFR TKIs include those driven by the KRAS and MET oncogenes. Most patients who initially respond to gefitinib and erlotinib eventually become resistant and experience progressive disease. The point mutation T790M accounts for about one half of these cases of acquired resistance. Various second-generation EGFR TKIs are currently being evaluated and may have the potential to overcome T790M-mediated resistance by virtue of their irreversible inhibition of the receptor TK domain.

A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

Abstract: We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed for all examined platforms, including qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.