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Biology subjects

Gürsoy, G.

Publications and source records attributed to Gürsoy, G..

2 recordsLinked to original sources

Paired CRISPR screens to map gene regulation in cis and trans

Recent massively-parallel approaches to decipher gene regulatory circuits have focused on the discovery of either cis-regulatory elements (CREs) or trans-acting factors. Here, we develop a scalable approach that pairs cis- and trans-regulatory CRISPR screens to systematically dissect how the key immune checkpoint PD-L1 is regulated. In human pancreatic ductal adenocarcinoma (PDAC) cells, we tile the PD-L1 locus using [~]25,000 CRISPR perturbations in constitutive and IFN{gamma}-stimulated conditions. We discover 67 enhancer- or repressor-like CREs and show that distal CREs tend to contact the promoter of PD-L1 and related genes. Next, we measure how loss of all [~]2,000 transcription factors (TFs) in the human genome impacts PD-L1 expression and, using this, we link specific TFs to individual CREs and reveal novel PD-L1 regulatory circuits. For one of these regulatory circuits, we confirm the binding of predicted trans-factors (SRF and BPTF) using CUT&RUN and show that loss of either the CRE or TFs potentiates the anti-cancer activity of primary T cells engineered with a chimeric antigen receptor. Finally, we show that expression of these TFs correlates with PD-L1 expression in vivo in primary PDAC tumors and that somatic mutations in TFs can alter response and overall survival in immune checkpoint blockade-treated patients. Taken together, our approach establishes a generalizable toolkit for decoding the regulatory landscape of any gene or locus in the human genome, yielding insights into gene regulation and clinical impact.

genomics↗

Ultra-secure storage and analysis of genetic data for the advancement of precision medicine

1Cloud computing provides the opportunity to store the ever-growing genotype-phenotype data sets needed to achieve the full potential of precision medicine. However, due to the sensitive nature of this data and the patchwork of data privacy laws across states and countries, additional security protections are proving necessary to ensure data privacy and security. Here we present SQUiD, a secure queryable database for storing and analyzing genotype-phenotype data. With SQUiD, genotype-phenotype data can be stored in a low-security, low-cost public cloud in the encrypted form, which researchers can securely query without the public cloud ever being able to decrypt the data. We demonstrate the usability of SQUiD by replicating various commonly used calculations such as polygenic risk scores, cohort creation for GWAS, MAF filtering, and patient similarity analysis both on synthetic and UK Biobank data. Our work represents a new and scalable platform enabling the realization of precision medicine without security and privacy concerns.

bioinformatics↗