A chemo-centric view of human health and disease

Efforts to compile the phenotypic effects of drugs and environmental chemicals offer the opportunity to adopt a chemo-centric view of human health that does not require detailed mechanistic information. Here we consider thousands of chemicals and analyse the relationship of their structures with adverse and therapeutic responses. Our study includes molecules related to the aetiology of 934 health-threatening conditions and used to treat 835 diseases. We first identify chemical moieties that could be independently associated with each phenotypic effect. Using these fragments, we build accurate predictors for approximately 400 clinical phenotypes, finding many privileged and liable structures. Finally, we connect two diseases if they relate to similar chemical structures. The resulting networks of human conditions are able to predict disease comorbidities, as well as identifying potential drug side effects and opportunities for drug repositioning, and show a remarkable coincidence with clinical observations

Detecting similar binding pockets to enable systems polypharmacology

In the era of systems biology, multi-target pharmacological strategies hold promise for tackling disease-related networks. In this regard, drug promiscuity may be leveraged to interfere with multiple receptors: the so-called polypharmacology of drugs can be anticipated by analyzing the similarity of binding sites across the proteome. Here, we perform a pairwise comparison of 90,000 putative binding pockets detected in 3,700 proteins, and find that 23,000 pairs of proteins have at least one similar cavity that could, in principle, accommodate similar ligands. By inspecting these pairs, we demonstrate how the detection of similar binding sites expands the space of opportunities for the rational design of drug polypharmacology. Finally, we illustrate how to leverage these opportunities in protein-protein interaction networks related to several therapeutic classes and tumor types, and in a genome-scale metabolic model of leukemia

Residues coevolution guides the systematic identification of alternative functional conformations in proteins

We present here a new approach for the systematic identification of functionally relevant conformations in proteins. Our fully automated pipeline, based on discrete molecular dynamics enriched with coevolutionary information, is able to capture alternative conformational states in 76% of the proteins studied, providing key atomic details for understanding their function and mechanism of action. We also demonstrate that, given its sampling speed, our method is well suited to explore structural transitions in a high-throughput manner, and can be used to determine functional conformational transitions at the entire proteome level

Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns

Altres ajuts: L.M. is a recipient of an FPI fellowship. P.A. acknowledges the support of the Spanish Ministerio de Economía y Competitividad, the European Research Council (SysPharmAD: 614944), and the Generalitat de Catalunya. V.S. is a recipient of a Miguel Servet grant from ISCIII and receives funds from AGAUR (). The PDX program is supported by a GHD-Pink (FERO foundation) grant to V.S., A.G.-O. and M.P. received a FI-AGAUR and a Juan de la Cierva (MJCI-2015-25412) fellowship, respectively. M.S., P.R., and S.C. acknowledge the support of the NIH grants P30 CA008748, RO1CA190642, and the Breast Cancer Research Foundation. Additionally, P.R. receives funds from the Breast Cancer Alliance.Identification of actionable genomic vulnerabilities is key to precision oncology. Utilizing a large-scale drug screening in patient-derived xenografts, we uncover driver gene alteration connections, derive driver co-occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug-response predictors attains an average balanced accuracy of 58% in a cross-validation setting, rising to 66% for a subset of high-confidence predictions. We experimentally validated 12 out of 14 predictions in mice and adapted our strategy to obtain drug-response models from patients' progression-free survival data. Our strategy reveals links between oncogenic alterations, increasing the clinical impact of genomic profiling

Isolation of Human Colon Stem Cells Using Surface Expression of PTK7

SummaryInsertion of reporter cassettes into the Lgr5 locus has enabled the characterization of mouse intestinal stem cells (ISCs). However, low cell surface abundance of LGR5 protein and lack of high-affinity anti-LGR5 antibodies represent a roadblock to efficiently isolate human colonic stem cells (hCoSCs). We set out to identify stem cell markers that would allow for purification of hCoSCs. In an unbiased approach, membrane-enriched protein fractions derived from in vitro human colonic organoids were analyzed by quantitative mass spectrometry. Protein tyrosine pseudokinase PTK7 specified a cell population within human colonic organoids characterized by highest self-renewal and re-seeding capacity. Antibodies recognizing the extracellular domain of PTK7 allowed us to isolate and expand hCoSCs directly from patient-derived mucosa samples. Human PTK7+ cells display features of canonical Lgr5+ ISCs and include a fraction of cells that undergo differentiation toward enteroendocrine lineage that resemble crypt label retaining cells (LRCs)

Cervical cancer screening outcomes in Zambia, 2010-19: a cohort study.

BACKGROUND Globally, cervical cancer is the fourth leading cause of cancer-related death among women. Poor uptake of screening services contributes to the high mortality. We aimed to examine screening frequency, predictors of screening results, and patterns of sensitisation strategies by age group in a large, programmatic cohort. METHODS We did a cohort study including 11 government health facilities in Lusaka, Zambia, in which we reviewed routine programmatic data collected through the Cervical Cancer Prevention Program in Zambia (CCPPZ). Participants who underwent cervical cancer screening in one of the participating study sites were considered for study inclusion if they had a screening result. Follow-up was accomplished per national guidelines. We did descriptive analyses and mixed-effects logistic regression for cervical cancer screening results allowing random effects at the individual and clinic level. FINDINGS Between Jan 1, 2010, and July 31, 2019, we included 183 165 women with 204 225 results for visual inspection with acetic acid and digital cervicography (VIAC) in the analysis. Of all those screened, 21 326 (10·4%) were VIAC-positive, of whom 16 244 (76·2%) received treatment. Of 204 225 screenings, 92 838 (45·5%) were in women who were HIV-negative, 76 607 (37·5%) were in women who were HIV-positive, and 34 780 (17·0%) had an unknown HIV status. Screening frequency increased 65·7% between 2010 and 2019 with most appointments being first-time screenings (n=158 940 [77·8%]). Women with HIV were more likely to test VIAC-positive than women who were HIV-negative (adjusted odds ratio 3·60, 95% CI 2·14-6·08). Younger women (≤29 years) with HIV had the highest predictive probability (18·6%, 95% CI 14·2-22·9) of screening positive. INTERPRETATION CCPPZ has effectively increased women's engagement in screening since its inception in 2006. Customised sensitisation strategies relevant to different age groups could increase uptake and adherence to screening. The high proportion of screen positivity in women younger than 20 years with HIV requires further consideration. Our data are not able to discern if women with HIV have earlier disease onset or whether this difference reflects misclassification of disease in an age group with a higher sexually transmitted infection prevalence. These data inform scale-up efforts required to achieve WHO elimination targets. FUNDING US President's Emergency Plan for AIDS Relief

Isolation of Human Colon Stem Cells Using Surface Expression of PTK7.

Insertion of reporter cassettes into the Lgr5 locus has enabled the characterization of mouse intestinal stem cells (ISCs). However, low cell surface abundance of LGR5 protein and lack of high-affinity anti-LGR5 antibodies represent a roadblock to efficiently isolate human colonic stem cells (hCoSCs). We set out to identify stem cell markers that would allow for purification of hCoSCs. In an unbiased approach, membrane-enriched protein fractions derived from in vitro human colonic organoids were analyzed by quantitative mass spectrometry. Protein tyrosine pseudokinase PTK7 specified a cell population within human colonic organoids characterized by highest self-renewal and re-seeding capacity. Antibodies recognizing the extracellular domain of PTK7 allowed us to isolate and expand hCoSCs directly from patient-derived mucosa samples. Human PTK7+ cells display features of canonical Lgr5+ ISCs and include a fraction of cells that undergo differentiation toward enteroendocrine lineage that resemble crypt label retaining cells (LRCs)

Evaluation of kidney function among people living with HIV initiating antiretroviral therapy in Zambia

As the response to the HIV epidemic in sub-Saharan Africa continues to mature, a growing number of people living with HIV (PLHIV) are aging and risk for non-communicable diseases increases. Routine laboratory tests of serum creatinine have been conducted to assess HIV treatment (ART) suitability. Here we utilize those measures to assess kidney function impairment among those initiating ART. Identification of non-communicable disease (NCD) risks among those in HIV care creates opportunity to improve public health through care referral and/or NCD/HIV care integration. We estimated glomerular filtration rates (eGFR) using routinely collected serum creatinine measures among a cohort of PLHIV with an HIV care visit at one of 113 Centre for Infectious Disease Research Zambia (CIDRZ) supported sites between January 1, 2011 and December 31, 2017, across seven of the ten provinces in Zambia. We used mixed-effect Poisson regression to assess predictors of eGFR <60ml/min/1.73m2 allowing random effects at the individual and facility level. Additionally, we assessed agreement between four eGFR formulae with unadjusted CKD-EPI as a standard using Scott/Fleiss method across five categories of kidney function. A total of 72,933 observations among 68,534 individuals met the inclusion criteria for analysis. Of the 68,534, the majority were female 41,042 (59.8%), the median age was 34 (interquartile range [IQR]: 28–40), and median CD4 cell count was 292 (IQR: 162–435). The proportion of individuals with an eGFR <60ml/min/1.73m2 was 6.9% (95% CI: 6.7–7.1%) according to the unadjusted CKD-EPI equation. There was variation in agreement across eGFR formulas considered compared to unadjusted CKD-EPI (χ2 p-value <0.001). Estimated GFR less than 60ml/min/1.73m2, per the unadjusted CKD-EPI equation, was significantly associated with age, sex, body mass index, and blood pressure. Using routine serum creatinine measures, we identified a significant proportion of individuals with eGFR indicating moderate or great kidney function impairment among PLHIV initiating ART in Zambia. It is possible that differentiated service delivery models could be developed to address this subset of those in HIV care with increased risk of chronic kidney disease

A community challenge for a pancancer drug mechanism of action inference from perturbational profile data

The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with similar to 400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among similar to 1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessments of drug mechanisms of action.Peer reviewe