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Sex differences have been widely observed in human health. However, little is known about the underlying mechanism behind these observed sex differences. We hypothesize that sex-differentiated genetic effects are contributors of these phenotypic differences. Focusing on a collection of drug metabolism enzymes and transporters (DMET) genes, we discover sex-differentiated genetic regulatory mechanisms between these genes and human complex traits. Here, we show that sex-differentiated genetic effects were present at genome-level and at DMET gene regions for many human complex traits. These sex-differentiated regulatory mechanisms are reflected in the levels of gene expression and endogenous serum biomarkers. Through Mendelian Randomization analysis, we identify putative sex-differentiated causal effects in each sex separately. Furthermore, we identify and validate sex differential gene expression of a subset of DMET genes in human liver samples. We observe higher protein abundance and enzyme activity of CYP1A2 in male-derived liver microsomes, which leads to higher level of an active metabolite formation of clozapine, a commonly prescribed antipsychotic drug. Taken together, our results demonstrate the presence of sex-differentiated genetic effects on DMET gene regulation, which manifest in various phenotypic traits including disease risks and drug responses.

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Background and Objective: Multiple agents have been developed for treating non-small cell lung cancer (NSCLC). However, patients' response to these therapies vary drastically, which indicates a need to tailor therapy. Sex is a readily usable clinical characteristic that has been shown to impact patients' response to drugs. The main objective of this narrative review is to summarize the current state of knowledge, compiled from meta-analyses, on sex differences in treatment efficacy for targeted therapy and immunotherapy in NSCLC. We discuss the interplay of patient characteristics, both molecular and demographic, with sex on how they impact therapeutic response.Methods: PubMed search was performed with the term "sex/gender differences" with currently FDA approved targeting therapy and immunotherapy agents in treating NSCLC.

Prostate cancer (PC) is the most frequently diagnosed malignancy and a leading cause of cancer deaths in US men. Many PC cases metastasize and develop resistance to systemic hormonal therapy, a stage known as castration-resistant prostate cancer (CRPC). Therefore, there is an urgent need to develop effective therapeutic strategies for CRPC. Traditional drug discovery pipelines require significant time and capital input, which highlights a need for novel methods to evaluate the repositioning potential of existing drugs. Here, we present a computational framework to predict drug sensitivities of clinical CRPC tumors to various existing compounds and identify treatment options with high potential for clinical impact. We applied this method to a CRPC patient cohort and nominated drugs to combat resistance to hormonal therapies including abiraterone and enzalutamide. The utility of this method was demonstrated by nomination of multiple drugs that are currently undergoing clinical trials for CRPC. Additionally, this method identified the tetracycline derivative COL-3, for which we validated higher efficacy in an isogenic cell line model of enzalutamide-resistant vs. enzalutamide-sensitive CRPC. In enzalutamide-resistant CRPC cells, COL-3 displayed higher activity for inhibiting cell growth and migration, and for inducing G1-phase cell cycle arrest and apoptosis. Collectively, these findings demonstrate the utility of a computational framework for independent validation of drugs being tested in CRPC clinical trials, and for nominating drugs with enhanced biological activity in models of enzalutamide-resistant CRPC. The efficiency of this method relative to traditional drug development approaches indicates a high potential for accelerating drug development for CRPC.

BackgroundLung cancer is the top killer cancer in the US. Monolayer cultures of lung cancer cells and their animal xenografts are major models for testing therapeutic modalities against lung cancer. Injection of suspended cancer cells into the lung is one of the most common approach to build an orthotopic lung cancer model but carry several major disadvantages, including the omission of a primary solid tumor and the artificial metastasis generated from the premature leakage of the injected cell suspension [1]. All such drawbacks could severely mislead the development of new therapies against lung cancer. Compared to cell monolayers or cell suspensions in culture, three‐dimension (3D) cancer cell spheroids better mimic the tumor microenvironment [2].PurposeThe purpose of this study is to build a more clinically relevant, orthotopic lung cancer model by inoculating 3D spheroids of lung cancer cells into the mouse lung.MethodThe 3D spheroids were cultured by seeding human lung cancer cell line A549‐iRFP in corning 96 multicellular microplate. The cells stably expressed infrared fluorescent protein, whose signal was detected on Odyssey CLx imaging machine (λex = 685 nm, λem = 700 nm) to image the tumor growth in vivo. Tumor inoculation was performed by transpleural surgery on the left side of the athymic nude mice [3].ResultsThe fluorescence of the spheroids was proportional to their volume and viability (R2=0.9845 and 0.9305). Early in Day 7, the mice inoculated with the 3D spheroids (right 2 and 3) showed confined tumor growth at the inoculation side of the lung whereas those inoculated with cancer cell suspension (left 1) displayed perfused signal on both sides of the lung, indicating premature leakage of the inoculated cancer cells.ConclusionThe mice inoculated with the cancer cell suspension displayed artificial metastasis due to premature leakage of the injected cells inside the lung, which decreased its clinical relevance of mimicking lung cancer progression. In contrast, mice inoculated with the 3D cancer cell spheroids better mimic the progression of non‐small cell lung cancer in clinic.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.