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PubMed2025

BOGO: A Proteome-Wide Gene Overexpression Platform for Discovering Rational Cancer Combination Therapies.

Cancer drug resistance remains a major barrier to durable treatment success, often leading to relapse despite advances in precision oncology. While combination therapies are being increasingly investigated, such as chemotherapy with small molecule inhibitors, predicting drug response and identifying rational drug combinations based on resistance mechanisms remain major challenges. Therefore, a proteome-wide, single-gene overexpression screening platform is essential for guiding rational therapy selection. Here, we present BOGO (Bxb1-landing pad human ORFeome-integrated system for a proteome-wide Gene Overexpression), a robust, scalable, and reproducible screening platform that enables single-copy, site-specific integration and overexpression of ~19,000 human open across cancer cell models. Using BOGO, we identified drug-specific response drivers for 16 chemotherapeutic agents and integrated clinical datasets to uncover proliferation and resistance-associated genes with prognostic potential. Drug response similarity networks revealed both shared and unique mechanisms, highlighting key pathways such as autophagy, apoptosis, and Wnt signaling, and notable resistance-associated genes including BCL2, POLD2, and TRADD. In particular, we proposed a synergistic combination of the BCL2 family inhibitor ABT-263 (Navitoclax®) and the DNA analog TAS-102 (Lonsurf®), which revealed that lysosomal modulation is a key mechanism driving DNA analog resistance. This combination therapy selectively enhanced cytotoxicity in colorectal and pancreatic cancer cells in vitro, and demonstrated therapeutic benefit in vivo in both cell line-derived xenograft (CDX) and patient-derived xenograft (PDX) models. Together, these findings establish BOGO as a powerful gene overexpression perturbation platform for systematically identifying chemoresistance and chemosensitization drivers, and for discovering rational combination therapies. Its scalability and reproducibility position BOGO as a broadly applicable tool for functional genomics and therapeutic discovery beyond cancer resistance.

Journal Article↗

PubMed2025

Creating an atlas of variant effects to resolve variants of uncertain significance and guide cardiovascular medicine.

Cardiovascular diseases are leading global causes of death and disability, often presenting as interrelated phenotypes of atherosclerotic vascular disease, heart failure and arrhythmias. Cardiovascular diseases arise from interactions between environmental factors and predisposing genotypes and include common Mendelian lipid disorders, cardiomyopathies and arrhythmia syndromes. The identification of a pathogenic variant through genetic testing can inform disease diagnosis, risk prediction, treatment and family screening. However, a major roadblock in genomic medicine is that for many variants, especially missense variants, we lack sufficient evidence to enable a definitive classification, and therefore these variants are deemed as 'variants of uncertain significance'. In this Review, we describe how multiplexed assays of variant effects can enable the functional assessment of nearly all coding variants in a target sequence, potentially offering a proactive approach to identifying the functional significance of gene variants that are observed later in a patient. We discuss validation, including the role of in silico variant effect predictors, and how multiplexed experimental methods are informing cardiovascular disease biology and ultimately resolving the problem of variants of uncertain significance at scale.

Humans↗