Searching for LINCS to Stress: Using Text Mining to Automate Reference Chemical Curation

Adaptive stress response pathways (SRPs) restore cellular homeostasis following perturbation but may activate terminal outcomes like apoptosis, autophagy, or cellular senescence if disruption exceeds critical thresholds. Because SRPs hold the key to vital cellular tipping points, they are targeted for therapeutic interventions and assessed as biomarkers of toxicity. Hence, we are developing a public database of chemicals that perturb SRPs to enable new data-driven tools to improve public health. Here, we report on the automated text-mining pipeline we used to build and curate the first version of this database. We started with 100 reference SRP chemicals gathered from published biomarker studies to bootstrap the database. Second, we used information retrieval to find co-occurrences of reference chemicals with SRP terms in PubMed abstracts and determined pairwise mutual information thresholds to filter biologically relevant relationships. Third, we applied these thresholds to find 1206 putative SRP perturbagens within thousands of substances in the Library of Integrated Network-Based Cellular Signatures (LINCS). To assign SRP activity to LINCS chemicals, domain experts had to manually review at least three publications for each of 1206 chemicals out of 181,805 total abstracts. To accomplish this efficiently, we implemented a machine learning approach to predict SRP classifications from texts to prioritize abstracts. In 5-fold cross-validation testing with a corpus derived from the 100 reference chemicals, artificial neural networks performed the best (F1-macro = 0.678) and prioritized 2479/181,805 abstracts for expert review, which resulted in 457 chemicals annotated with SRP activities. An independent analysis of enriched mechanisms of action and chemical use class supported the text-mined chemical associations (p < 0.05): heat shock inducers were linked with HSP90 and DNA damage inducers to topoisomerase inhibition. This database will enable novel applications of LINCS data to evaluate SRP activities and to further develop tools for biomedical information extraction from the literature.

Exploring the effects of experimental parameters and data modeling approaches on in vitro transcriptomic point-of-departure estimates

Multiple new approach methods (NAMs) are being developed to rapidly screen large numbers of chemicals to aid in hazard evaluation and risk assessments. High-throughput transcriptomics (HTTr) in human cell lines has been proposed as a first-tier screening approach for determining the types of bioactivity a chemical can cause (activation of specific targets vs. generalized cell stress) and for calculating transcriptional points of departure (tPODs) based on changes in gene expression. In the present study, we examine a range of computational methods to calculate tPODs from HTTr data, using six data sets in which MCF7 cells cultured in two different media formulations were treated with a panel of 44 chemicals for 3 different exposure durations (6, 12, 24 hr). The tPOD calculation methods use data at the level of individual genes and gene set signatures, and compare data processed using the ToxCast Pipeline 2 (tcplfit2), BMDExpress and PLIER (Pathway Level Information ExtractoR). Methods were evaluated by comparing to in vitro PODs from a validated set of high-throughput screening (HTS) assays for a set of estrogenic compounds. Key findings include: (1) for a given chemical and set of experimental conditions, tPODs calculated by different methods can vary by several orders of magnitude; (2) tPODs are at least as sensitive to computational methods as to experimental conditions; (3) in comparison to an external reference set of PODs, some methods give generally higher values, principally PLIER and BMDExpress; and (4) the tPODs from HTTr in this one cell type are mostly higher than the overall PODs from a broad battery of targeted in vitro ToxCast assays, reflecting the need to test chemicals in multiple cell types and readout technologies for in vitro hazard screening.

Enhancing diabetes care for the most vulnerable in the 21st century: Interim findings of the National Advisory Panel on Care Home Diabetes (NAPCHD)

Older adults with diabetes may carry a substantial health burden in Western ageing societies, occupy more than one in four beds in care homes, and are a highly vulnerable group who often require complex nursing and medical care. The global pandemic (COVID-19) had its epicentre in care homes and revealed many shortfalls in diabetes care resulting in hospital admissions and considerable mortality and comorbid illness. The purpose of this work was to develop a national Strategic Document of Diabetes Care for Care Homes which would bring about worthwhile, sustainable and effective quality diabetes care improvements, and address the shortfalls in care provided. A large diverse and multidisciplinary group of stakeholders (NAPCHD) defined 11 areas of interest where recommendations were needed and using a subgroup allocation approach were set tasks to produce a set of primary recommendations. Each subgroup was given 5 starter questions to begin their work and a format to provide responses. During the initial phase, 16 key findings were identified. Overall, after a period of 18 months, 49 primary recommendations were made, and 7 major conclusions were drawn from these. A model of community and integrated diabetes care for care home residents with diabetes was proposed, and a series of 5 'quick-wins' were created to begin implementation of some of the recommendations that would not require significant funding. The work of the NAPCHD is ongoing but we hope that this current resource will help leaders to make these required changes happen.

Ready for regulatory use: NAMs and NGRA for chemical safety assurance

New approach methodologies (NAMs) that do not use experimental animals are, in certain settings, entirely appropriate for assuring the safety of chemical ingredients, although regulatory adoption has been slow. In this opinion article we discuss how scientific advances that utilize NAMs to certify systemic safety are available now and merit broader acceptance within the framework of next generation risk assessments (NGRA).

Mapping the dynamics of Nrf2 antioxidant and NFκB inflammatory responses by soft electrophilic chemicals in human liver cells defines the transition from adaptive to adverse responses

A comprehensive understanding of the dynamic activation and crosstalk between different cellular stress response pathways that drive cell adversity is crucial in chemical safety assessment. Various chemicals have electrophilic properties that drive cell injury responses in particular oxidative stress signaling and inflammatory signaling. Here we used bacterial artificial chromosome-based GFP cellular stress reporters with live cell confocal imaging, to systematically monitor the differential modulation of the dynamics of stress pathway activation by six different soft electrophiles: sulforaphane, andrographolide, diethyl maleate, CDDO-Me, ethacrynic acid and tert-butyl hydroquinone. The various soft electrophiles showed differential potency and dynamics of Nrf2 activation and nuclear translocation. These differences in Nrf2 dynamics correlated with distinct activation pattern of Nrf2 downstream targets SRNX1 and HMOX1. All soft electrophiles caused a strong dose dependent suppression of a cytokine-induced NFĸB response represented by suppression of NFĸB nuclear oscillation and inhibition of the downstream target gene activation A20 and ICAM1, which followed the potency of Nrf2 modulation but occurred at higher concentration close to saturation of Nrf2 activation. RNAi-based depletion of RelA resulted in a prolonged presence of Nrf2 in the nucleus after soft electrophile treatment; depletion of Nrf2 caused the induction of NFĸB signaling and activation of its downstream targets A20 and ICAM1. A systematic transcriptome analysis confirmed these effects by soft electrophiles on Nrf2 and NFκB signaling crosstalk in human induced-pluripotent stem cell-derived hepatocyte-like cells. Altogether our data indicate that modulation of Nrf2 by soft electrophiles may have consequences for efficient inflammatory signaling.

Latent Variables Capture Pathway-Level Points of Departure in High-Throughput Toxicogenomic Data

Estimation of points of departure (PoDs) from high-throughput transcriptomic data (HTTr) represents a key step in the development of next-generation risk assessment (NGRA). Current approaches mainly rely on single key gene targets, which are constrained by the information currently available in the knowledge base and make interpretation challenging as scientists need to interpret PoDs for thousands of genes or hundreds of pathways. In this work, we aimed to address these issues by developing a computational workflow to investigate the pathway concentration–response relationships in a way that is not fully constrained by known biology and also facilitates interpretation. We employed the Pathway-Level Information ExtractoR (PLIER) to identify latent variables (LVs) describing biological activity and then investigated in vitro LVs’ concentration–response relationships using the ToxCast pipeline. We applied this methodology to a published transcriptomic concentration–response data set for 44 chemicals in MCF-7 cells and showed that our workflow can capture known biological activity and discriminate between estrogenic and antiestrogenic compounds as well as activity not aligning with the existing knowledge base, which may be relevant in a risk assessment scenario. Moreover, we were able to identify the known estrogen activity in compounds that are not well-established ER agonists/antagonists supporting the use of the workflow in read-across. Next, we transferred its application to chemical compounds tested in HepG2, HepaRG, and MCF-7 cells and showed that PoD estimates are in strong agreement with those estimated using a recently developed Bayesian approach (cor = 0.89) and in weak agreement with those estimated using a well-established approach such as BMDExpress2 (cor = 0.57). These results demonstrate the effectiveness of using PLIER in a concentration–response scenario to investigate pathway activity in a way that is not fully constrained by the knowledge base and to ease the biological interpretation and support the development of an NGRA framework with the ability to improve current risk assessment strategies for chemicals using new approach methodologies.

Next generation risk assessment (NGRA): Bridging in vitro points-of-departure to human safety assessment using physiologically-based kinetic (PBK) modelling - A case study of doxorubicin with dose metrics considerations

Using the chemical doxorubicin (DOX), the objective of the present study was to evaluate the impact of dose metrics selection in the new approach method of integrating physiologically-based kinetic (PBK) modelling and relevant human cell-based assays to inform a priori the point of departure for human health risk. We reviewed the literature on the clinical consequences of DOX treatment to identify dosing scenarios with no or mild cardiotoxicity observed. Key concentrations of DOX that induced cardiomyocyte toxicity in vitro were derived from studies of our own and others. A human population-based PBK model of DOX was developed and verified against pharmacokinetic data. The model was then used to predict plasma and extracellular and intracellular heart concentrations of DOX under selected clinical settings and compared with in vitro outcomes, based on several dose metrics: C_max (maximum concentration) or AUC (area under concentration-time curve) in free or total form of DOX. We found when using in vitro assays to predict cardiotoxicity for DOX, AUC is a better indicator. Our study illustrates that when appropriate dose metrics are used, it is possible to combine PBK modelling with in vitro-derived toxicity information to define margins of safety and predict low-risk human exposure levels.

A Retrospective Study of Administrative Data to Identify Factors Associated with Future Disability Status among Older Colorectal Cancer Survivors

Disability is associated with loss of independence and early mortality. Currently, only 1–2% of cancer survivors who reported physical limitations received rehabilitation services. It is critical to identify factors associated with the development of disability to guide clinical practice given treatment changes. We aimed to 1) identify demographic and cancer-related characteristics associated with future disability status among older colorectal cancer survivors, and 2) compared the future disability status among cancer and matched non-cancer cohorts. Methods: We conducted a retrospective cohort study using the Texas Cancer Registry-national Medicare linked database. The cancer cohort included Medicare beneficiaries with a primary colorectal cancer diagnosis between 2005 and 2013 (n = 13,229). The non-cancer cohort was identified from a 5% sample of Medicare beneficiaries (n = 11,416). Diagnosis dates from the cancer cohort were used as the index date for the non-cancer cohort. Cohorts were matched 1:1 based on index date, age, and gender. Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals. Disability status was defined according to Davidoff and colleagues using inpatient, outpatient and durable medical equipment claims files, and assessed monthly, beginning 1 month after cancer diagnosis (or index date), continuing until disability, death, end of Medicare continuous enrollment, or end of study. Results: Factors that were significantly associated with disability status in the cancer cohort were age (HR = 3.50 for &gt;80 years old), female gender (HR = 1.50), race/ethnicity (HR = 1.34 for Hispanic and 1.21 for Black), stage (HR = 2.26 for distant stage), comorbidity (HR = 2.18 for &gt;1), and radiation (HR = 1.21). When compared to the non-cancer cohort, having a cancer diagnosis (HR = 1.07) and comorbidity (HR = 2.09 for &gt;1) were associated with developing disability. Conclusions: Colorectal diagnosis is an independent risk for disability status. Beyond well-known risk factors “age and mortality” subsets of survivors (Hispanic and Black survivors and those with comorbidity) are found to be at higher risk for developing disability. This warrants further investigation and may indicate targeted intervention to prevent future disability.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Doxorubicin-induced mitophagy and mitochondrial damage is associated with dysregulation of the PINK1/parkin pathway

The usefulness of doxorubicin (DOX), a potent anticancer agent, is limited by its cardiotoxicity. Mitochondria play a central role in DOX-induced cardiotoxicity though the precise mechanisms are still obscure. Increasing evidence indicates that excessive activation of mitophagy and mitochondrial dysfunction are key causal events leading to DOX-induced cardiac injury. The PINK1/parkin pathway has emerged as a critical pathway in regulation of mitophagy as well as mitochondrial function. The present study was aimed to investigate the role of PINK1/parkin pathway in DOX-induced mitochondrial damage and cardiotoxicity. Our results showed that DOX concentration-dependently induced cytotoxicity and mitochondrial toxic effects including mitochondrial superoxide accumulation, decreased mitochondrial membrane potential and mitochondrial DNA copy number, as well as mitochondrial ultrastructural alterations. DOX induced mitophagy as evidenced by increases of the markers of autophagosomes, LC3, Beclin 1, reduction of p62, and co-localization of LC3 in mitochondria. DOX activated PINK1/parkin pathway and promoted translocation of PINK1/parkin to mitochondria. Meanwhile, DOX inhibited the expression of PGC-1α and its downstream targets nuclear respiratory factor 1 (NRF1) and mitochondrial transcription factor A (TFAM), and reduced the expression of mitochondrial proteins. Inhibition of mitophagy by mdivi-1 was found to attenuate activation of the PINK1/parkin pathway by DOX and preserve mitochondrial biogenesis, consequently mitigating DOX-induced mitochondrial superoxide overproduction and mitochondrial dysfunction. Moreover, scavenging mitochondrial superoxide by Mito-tempo was also found to effectively attenuate activation of the PINK1/parkin pathway and rescue the cells from DOX-induced adverse effects. Taken together, these findings suggest that DOX-induced mitophagy and mitochondrial damage in cardiomyocytes are mediated, at least in part, by dysregulation of the PINK1/parkin pathway.

Optical Modulation of the Diffraction Efficiency in an Indoline Azobenzene/Amorphous Polycarbonate Film

We have made a diffraction grating in an indoline azobenzene/amorphous polycarbonate film by two-beam interference at 532 nm that periodically photodegrades the indoline azobenzene dye. Subsequent illumination of the film with 532-nm light into the trans-isomer band leads to trans-cis isomerization in the indoline azobenzene dye and results in a decrease in the trans-isomer band absorption coefficient. This causes the diffraction efficiency to decrease when probed at 655 nm. The diffraction efficiency returns to its original value when the 532-nm light is blocked by thermal relaxation from the indoline azobenzene cis-isomer to the trans-isomer. Thus, we have been able to optically modulate the diffraction efficiency in a thin film diffraction grating.

Concomitant expression of far upstream element (FUSE) binding protein (FBP) interacting repressor (FIR) and its splice variants induce migration and invasion of non-small cell lung cancer (NSCLC) cells

Transcription factors integrate a variety of oncogenic input information, facilitate tumour growth and cell dissemination, and therefore represent promising therapeutic target structures. Because over-expression of DNA-interacting far upstream element binding protein (FBP) supports non-small cell lung cancer (NSCLC) migration, we asked whether its repressor, FBP-interacting repressor (FIR) is functionally inactivated and how FIR might affect NSCLC cell biology. Different FIR splice variants were highly expressed in the majority of NSCLCs, with the highest levels in tumours carrying genomic gains of chromosome 8q24.3, which contained the FIR gene locus. Nuclear FIR expression was significantly enriched at the invasion front of primary NSCLCs, but this did not correlate with tumour cell proliferation. FIR accumulation was associated with worse patient survival and tumour recurrence; in addition, FIR over-expression significantly correlated with lymph node metastasis in squamous cell carcinomas (SCCs). In vitro, we applied newly developed methods and modelling approaches for the quantitative and time-resolved description of the pro-migratory and pro-invasive capacities of SCC cells. siRNA-mediated silencing of all FIR variants significantly reduced the speed and directional movement of tumour cells in all phases of migration. Furthermore, sprouting efficiency and single cell invasiveness were diminished following FIR inhibition. Interestingly, the silencing of FIR isoforms lacking exon 2 (FIR(Δexon2)) alone was sufficient to reduce lateral migration and invasion. In summary, by using scale-spanning data derived from primary human tissues, quantitative cellular analyses and mathematical modelling, we have demonstrated that concomitant over-expression of FIR and its splice variants drives NSCLC migration and dissemination.

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders.