External validation of the first prognostic nomogram for older adults with cancer.

Background: The geriatric oncology population tends to be complex because of multimorbidity, functional and cognitive decline, malnutrition and social frailty. Prognostic indices for predicting survival of elderly cancer patients to guide treatment remain scarce. A nomogram based on all domains of the geriatric assessment was previously developed at the National Cancer Centre Singapore (NCCS) to predict overall survival (OS) in elderly cancer patients. This nomogram comprised of six variables (age, eastern cooperative oncology group performance status, disease stage, geriatric depression scale (GDS), DETERMINE nutritional index and serum albumin). Objectives: To externally validate the NCCS prognostic nomogram. Design: This is a prospective cohort study. Methods: The nomogram was developed based on a training cohort of 249 patients aged ⩾70 years who attended the NCCS outpatient geriatric oncology clinic between May 2007 and November 2010. External validation of the nomogram using the Royston and Altman approach was carried out on an independent testing cohort of 252 patients from the same clinic between July 2015 and June 2017. Model misspecification, discrimination and calibration were assessed. Results: Median OS of the testing cohort was 3.1 years, which was significantly higher than the corresponding 1.0 year for the training cohort (log-rank p < 0.001). The nomogram achieved a high level of discrimination in the testing cohort (0.7112), comparable to the training cohort (0.7108). Predicted death probabilities were generally well calibrated with the observed death probabilities, as the joint test of calibration-in-the-large estimates at year 1, 2 and 3 from zeros and calibration slope from one was insignificant with p = 0.432. There were model misspecifications in GDS and serum albumin. Conclusion: This study externally validated the prognostic nomogram in an independent cohort of geriatric oncology patients. This supports the use of this nomogram in clinical practice.

Feeding state greatly modulates the effect of xenobiotics on gut microbiome metabolism: A case study of tetracycline.

The human gut microbiome is crucial in modulating host health mostly through bacterial metabolites. Chemical exposure is typical external stress which alters its composition and functionality. To date, very few studies have investigated the effect of feeding state on chemical-induced gut microbial metabolic dysregulations. Here, we set up an in vitro human gut microbiome and incorporated a metabolomics approach to investigate the effect of tetracycline (TET) at multiple doses (i.e., 10, 1, and 0.01 mg/L) on gut microbiome under the fed and fasted states. Overall, the metabolome was highly responsive at the fed state with 62 metabolites dysregulated while only 14 were altered at the fasted state under 10 mg/L (clinical TET dose). As expected, nutrient consumption was significantly inhibited under clinical TET dose at the fed state accumulating nutrients such as glutamate and leucine. Interestingly, at the fed state, TET could increase the synthesis of indole and phenyl derivatives including indole-3-aldehyde and hydrocinnamate, while inhibiting indoxyl, tryptamine, and vitamin B production, all of which have host health implications. Furthermore, metabolites like indoxyl and xanthurenic acid were still responsive at 0.01 mg/L (dietary TET dose). Collectively, results demonstrated that the feeding state greatly modulates the chemical-induced gut microbial metabolic alterations.

Risk-Based Chemical Ranking and Generating a Prioritized Human Exposome Database.

BACKGROUND: Due to the ubiquitous use of chemicals in modern society, humans are increasingly exposed to thousands of chemicals that contribute to a major portion of the human exposome. Should a comprehensive and risk-based human exposome database be created, it would be conducive to the rapid progress of human exposomics research. In addition, once a xenobiotic is biotransformed with distinct half-lives upon exposure, monitoring the parent compounds alone may not reflect the actual human exposure. To address these questions, a comprehensive and risk-prioritized human exposome database is needed. OBJECTIVES: Our objective was to set up a comprehensive risk-prioritized human exposome database including physicochemical properties as well as risk prediction and develop a graphical user interface (GUI) that has the ability to conduct searches for content associated with chemicals in our database. METHODS: We built a comprehensive risk-prioritized human exposome database by text mining and database fusion. Subsequently, chemicals were prioritized by integrating exposure level obtained from the Systematic Empirical Evaluation of Models with toxicity data predicted by the Toxicity Estimation Software Tool and the Toxicological Priority Index calculated from the ToxCast database. The biotransformation half-lives (HLBs) of all the chemicals were assessed using the Iterative Fragment Selection approach and biotransformation products were predicted using the previously developed BioTransformer machine-learning method. RESULTS: We compiled a human exposome database of >20,000 chemicals, prioritized 13,441 chemicals based on probabilistic hazard quotient and 7,770 chemicals based on risk index, and provided a predicted biotransformation metabolite database of >95,000 metabolites. In addition, a user-interactive Java software (Oracle)-based search GUI was generated to enable open access to this new resource. DISCUSSION: Our database can be used to guide chemical management and enhance scientific understanding to rapidly and effectively prioritize chemicals for comprehensive biomonitoring in epidemiological investigations. https://doi.org/10.1289/EHP7722.

Metabolomics and In Silico Docking-Directed Discovery of Small-Molecule Enzyme Targets.

The identification of target proteins for small molecules is of great importance in drug discovery and for understanding the cellular mode of action (MOA) of toxicants. Herein, a "bottom-up" oriented target finding strategy is proposed based on the principle that the targeted enzymes can be inferred according to their phenotypic changes at the metabolome level. Meanwhile, computer-assisted in silico molecular docking analysis was performed to evaluate the binding affinities between the chemicals and the target enzymes to further rank the possible targets. In this study, triphenyl phosphate (TPhP) was used as an example to illustrate the workflow. After a comprehensive metabolome and lipidome analysis, 51 related metabolic enzymes were selected for ranking binding energies, wherein 25 proteins exhibited a higher affinity for TPhP than for their endogenous substrates. Two proteins, hydroxyacyl-coenzyme A dehydrogenase (HADH) and 3-hydroxyacyl-CoA dehydrogenase type-2 (HSD17B10), were further confirmed by surface phasma resonance (SPR) and isothermal titration calorimetry (ITC) analysis, displayed Kd values at low micromolar levels for TPhP. Overall, the proposed strategy has provided a feasible means for discovering enzymatic targets for the large-scale small-molecule sets, with the advantages of closely associating with the phenotype change, reducing the cost of groping, and improving the accuracy of target prediction.

Polycyclic aromatic hydrocarbons (PAHs) in indoor environments are still imposing carcinogenic risk.

Polycyclic aromatic hydrocarbons (PAHs) are among the most health-relevant air pollutants. Herein, we conducted meta-analysis and experimental validation to evaluate PAHs in our surroundings and carcinogenic risks. We summarized the occurrence of PAHs in outdoors and indoors from 131 studies with 6,766 samples collected in different countries in 1989-2019. The global weighted-median concentration in outdoor air, indoor air and dust of ΣPAHs were 142 ng/m3, 369 ng/m3 and 10,201 ng/g; respectively. ΣPAHs have decreased in indoor air but remained steady in outdoor air and indoor dust. More carcinogenic PAHs in indoor/outdoor air was observed in Asia, while in dust was North America. Monte-Carlo simulation further showed indoor sources for children's exposure from dust and air can exceed outdoor. To further validate the health effect of PAHs from indoors, 15 more recent indoor dust samples were collected to examine their mutagenicity. The results showed that ΣPAHs were found to be significantly correlated with mutagenicity potency in the dust sample metabolically activated with liver S9 subcellular fraction and likely accounted for 0.42-0.50 of the mutagenic activity. Our findings indicated that PAHs are still likely to have carcinogenic activity in indoor environments and exposure risk of children to indoor dust should be emphasized.