US regulations to curb alleged cancer causes are ineffectual and compromised by scientific, constitutional and ethical violations.

The 1958 Delaney amendment to the Federal Food Drug and Cosmetics Act prohibited food additives causing cancer in animals by appropriate tests. Regulators responded by adopting chronic lifetime cancer tests in rodents, soon challenged as inappropriate, for they led to very inconsistent results depending on the subjective choice of animals, test design and conduct, and interpretive assumptions. Presently, decades of discussions and trials have come to conclude it is impossible to translate chronic animal data into verifiable prospects of cancer hazards and risks in humans. Such conclusion poses an existential crisis for official agencies in the US and abroad, which for some 65 years have used animal tests to justify massive regulations of alleged human cancer hazards, with aggregated costs of $trillions and without provable evidence of public health advantages. This article addresses suitable remedies for the US and potentially worldwide, by critically exploring the practices of regulatory agencies vis-á-vis essential criteria for validating scientific evidence. According to this analysis, regulations of alleged cancer hazards and risks have been and continue to be structured around arbitrary default assumptions at odds with basic scientific and legal tests of reliable evidence. Such practices raise a manifold ethical predicament for being incompatible with basic premises of the US Constitution, and with the ensuing public expectations of testable truth and transparency from government agencies. Potential remedies in the US include amendments to the US Administrative Procedures Act, preferably requiring agencies to justify regulations compliant with the Daubert opinion of the Daubert ruling of the US Supreme Court, which codifies the criteria defining reliable scientific evidence. International reverberations are bound to follow what remedial actions may be taken in the US, the origin of current world regulatory procedures to control alleged cancer causing agents.

Corrigendum: DeepCarc: Deep learning-powered carcinogenicity prediction using model-level representation.

[This corrects the article DOI: 10.3389/frai.2021.757780.].

DeepCarc: Deep Learning-Powered Carcinogenicity Prediction Using Model-Level Representation.

Carcinogenicity testing plays an essential role in identifying carcinogens in environmental chemistry and drug development. However, it is a time-consuming and label-intensive process to evaluate the carcinogenic potency with conventional 2-years rodent animal studies. Thus, there is an urgent need for alternative approaches to providing reliable and robust assessments on carcinogenicity. In this study, we proposed a DeepCarc model to predict carcinogenicity for small molecules using deep learning-based model-level representations. The DeepCarc Model was developed using a data set of 692 compounds and evaluated on a test set containing 171 compounds in the National Center for Toxicological Research liver cancer database (NCTRlcdb). As a result, the proposed DeepCarc model yielded a Matthews correlation coefficient (MCC) of 0.432 for the test set, outperforming four advanced deep learning (DL) powered quantitative structure-activity relationship (QSAR) models with an average improvement rate of 37%. Furthermore, the DeepCarc model was also employed to screen the carcinogenicity potential of the compounds from both DrugBank and Tox21. Altogether, the proposed DeepCarc model could serve as an early detection tool (https://github.com/TingLi2016/DeepCarc) for carcinogenicity assessment.

Key Characteristics of Human Hepatotoxicants as a Basis for Identification and Characterization of the Causes of Liver Toxicity.

Hazard identification regarding adverse effects on the liver is a critical step in safety evaluations of drugs and other chemicals. Current testing paradigms for hepatotoxicity rely heavily on preclinical studies in animals and human data (epidemiology and clinical trials). Mechanistic understanding of the molecular and cellular pathways that may cause or exacerbate hepatotoxicity is well advanced and holds promise for identification of hepatotoxicants. One of the challenges in translating mechanistic evidence into robust decisions about potential hepatotoxicity is the lack of a systematic approach to integrate these data to help identify liver toxicity hazards. Recently, marked improvements were achieved in the practice of hazard identification of carcinogens, female and male reproductive toxicants, and endocrine disrupting chemicals using the key characteristics approach. Here, we describe the methods by which key characteristics of human hepatotoxicants were identified and provide examples for how they could be used to systematically identify, organize, and use mechanistic data when identifying hepatotoxicants.

Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma.

High-risk neuroblastoma (NB) remains a significant therapeutic challenge facing current pediatric oncology patients. Structural variants such as gene fusions have shown an initial promise in enhancing mechanistic understanding of NB and improving survival rates. In this study, we performed a comprehensive in silico investigation on the translational ability of gene fusions for patient stratification and treatment development for high-risk NB patients. Specifically, three state-of-the-art gene fusion detection algorithms, including ChimeraScan, SOAPfuse, and TopHat-Fusion, were employed to identify the fusion transcripts in a RNA-seq data set of 498 neuroblastoma patients. Then, the 176 high-risk patients were further stratified into four different subgroups based on gene fusion profiles. Furthermore, Kaplan-Meier survival analysis was performed, and differentially expressed genes (DEGs) for the redefined high-risk group were extracted and functionally analyzed. Finally, repositioning candidates were enriched in each patient subgroup with drug transcriptomic profiles from the LINCS L1000 Connectivity Map. We found the number of identified gene fusions was increased from clinical the low-risk stage to the high-risk stage. Although the technical concordance of fusion detection algorithms was suboptimal, they have a similar biological relevance concerning perturbed pathways and regulated DEGs. The gene fusion profiles could be utilized to redefine high-risk patient subgroups with significant onset age of NB, which yielded the improved survival curves (Log-rank p value ≤ 0.05). Out of 48 enriched repositioning candidates, 45 (93.8%) have antitumor potency, and 24 (50%) were confirmed with either on-going clinical trials or literature reports. The gene fusion profiles have a discrimination power for redefining patient subgroups in high-risk NB and facilitate precision medicine-based drug repositioning implementation.

Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.

Drug-induced liver injury (DILI) is one of the most cited reasons for the high drug attrition rate and drug withdrawal from the market. The accumulated large amount of high throughput transcriptomic profiles and advances in deep learning provide an unprecedented opportunity to improve the suboptimal performance of DILI prediction. In this study, we developed an eight-layer Deep Neural Network (DNN) model for DILI prediction using transcriptomic profiles of human cell lines (LINCS L1000 dataset) with the current largest binary DILI annotation data [i.e., DILI severity and toxicity (DILIst)]. The developed models were evaluated by Monte Carlo cross-validation (MCCV), permutation test, and an independent validation (IV) set. The developed DNN model achieved the area under the receiver operating characteristic curve (AUC) of 0.802 and 0.798, and balanced accuracy of 0.741 and 0.721 for training and an IV set, respectively, outperforming the conventional machine learning algorithms, including K-nearest neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF). Moreover, the developed DNN model provided a more balanced sensitivity of 0.839 and specificity of 0.603. Besides, we found the developed DNN model had a superior predictive performance for oncology drugs. Also, the functional and network analysis of genes driving the predictions revealed their relevance to the underlying mechanisms of DILI. The proposed DNN model could be a promising tool for early detection of DILI potential in the pre-clinical setting.

A decade of toxicological trends: what the papers say.

Here we look at popular trends and concepts in toxicology over the decade 2009-2019. The top 10 concepts included methodological approaches such as zebrafish and genomics as well as broader concepts such as personalized medicine and adverse outcome pathways. The total number and rank order for each of the top 10 were tracked year by year via PubMed with >9500 papers contributing to the analysis. The data revealed a slow upward trend in the number of papers across all the concepts from 260 in 2009 to >1700 in 2019. Zebrafish, genomics and personalized medicine remained in the top four slots since 2009 with zebrafish dominating the rankings over the entire decade. Genomics was a strong second until 2013 when it was displaced first by the microbiome in 2014 and secondly by personalized medicine in 2015. Other notable trends were the ascendancy of the microbiome and adverse outcome pathways and the descendancy of hormesis and the 3Rs (replacement, reduction and refinement of animals in testing). The observation that the top four slots have been static over the past 4 years suggests that new ideas are introduced and increase in popularity until they find their place in scientific culture. This may suggest that relatively new concepts such as artificial intelligence and microphysiological systems have yet to find their steady state in the rankings. Similarly, as a relatively new player in toxicology, the full impact of the human microbiome on drug efficacy and safety remains to be seen.

Can Transcriptomic Profiles from Cancer Cell Lines Be Used for Toxicity Assessment?

In vitro toxicogenomics (TGx) has the potential to replace or supplement animal studies. However, TGx studies often suffer from a limited sample size and cell types. Meanwhile, transcriptomic data have been generated for tens of thousands of compounds using cancer cell lines mainly for drug efficacy screening. Here, we asked the question of whether these types of transcriptomic data can be used to support toxicity assessment. We compared transcriptomic profiles from three cancer lines (HL60, MCF7, and PC3) from the CMap data set with those using primary hepatocytes or in vivo repeated dose studies from the Open TG-GATEs database by using our previously reported pair ranking (PRank) method. We observed an encouraging similarity between HL60 and human primary hepatocytes (PRank score = 0.70), suggesting the two cellular assays could be potentially interchangeable. When the analysis was limited to drug-induced liver injury (DILI)-related compounds or genes, the cancer cell lines exhibited promise in DILI assessment in comparison with conventional TGx systems (i.e., human primary hepatocytes or rat in vivo repeated dose). Also, some toxicity-related pathways, such as PPAR signaling pathways and fatty acid-related pathways, were preserved across various assay systems, indicating the assay transferability is biological process-specific. Furthermore, we established a potential application of transcriptomic profiles of cancer cell lines for studying immune-related biological processes involving some specific cell types. Moreover, if PRank analysis was focused on only landmark genes from L1000 or S1500+, the advantage of cancer cell lines over the TGx studies was limited. In conclusion, repurposing of existing cancer-related transcript profiling data has great potential for toxicity assessment, particularly in predicting DILI.

Derivatisation of parthenolide to address chemoresistant chronic lymphocytic leukaemia.

Parthenolide is a natural product that exhibits anti-leukaemic activity, however, its clinical use is limited by its poor bioavailability. It may be extracted from feverfew and protocols for growing, extracting and derivatising it are reported. A novel parthenolide derivative with good bioavailability and pharmacological properties was identified through a screening cascade based on in vitro anti-leukaemic activity and calculated "drug-likeness" properties, in vitro and in vivo pharmacokinetics studies and hERG liability testing. In vitro studies showed the most promising derivative to have comparable anti-leukaemic activity to DMAPT, a previously described parthenolide derivative. The newly identified compound was shown to have pro-oxidant activity and in silico molecular docking studies indicate a prodrug mode of action. A synthesis scheme is presented for the production of amine 7 used in the generation of 5f.

The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury.

INTRODUCTION: Drug-induced liver injury (DILI) is challenging for drug development, clinical practice and regulation. The Liver Toxicity Knowledge Base (LTKB) provides essential data for DILI study. Areas covered: The LTKB provided various types of data that can be used to assess and predict DILI. Among much information available, several reference drug lists with annotated human DILI risk are of important. The LTKB DILI classification data include DILI severity concern determined by the FDA drug labeling, DILI severity score from the NIH LiverTox database, and other DILI classification schemes from the literature. Overall, ~1000 drugs were annotated with at least one classification scheme, of which around 750 drugs were flagged for some degree of DILI risk. Expert commentary: The LTKB provides a centralized repository of information for DILI study and predictive model development. The DILI classification data in LTKB could be a useful resource for developing biomarkers, predictive models and assessing data from emerging technologies such as in silico, high-throughput and high-content screening methodologies. In coming years, streamlining the prediction process by including DILI predictive models for both DILI severity and types in LTKB would enhance the identification of compounds with the DILI potential earlier in drug development and risk assessment.

Lessons Learned from Two Decades of Anticancer Drugs.

Tremendous efforts have been made to elucidate the basis of cancer biology with the aim of promoting anticancer drug development. Especially over the past 20 years, anticancer drug development has developed from conventional cytotoxic agents to target-based and immune-related therapies. Consequently, more than 200 anticancer drugs are available on the market. However, anticancer drug development still suffers high attrition during the later phases of clinical development and is considered to be a difficult and risky therapeutic category within the drug development arena. The disappointing performance of investigational anticancer candidates implies that there are some shortcomings in the translation of preclinical in vitro and in vivo models to humans, and that heterogeneity in the patient population presents a significant challenge. Here, we summarize both successful and failed experiences in anticancer development during the past 20 years and help identify why the current paradigm may be suboptimal. We also offer potential strategies for improvement.

Skin sensitization induced Langerhans' cell mobilization: variable requirements for tumour necrosis factor-α.

Upon antigen/allergen recognition, epidermal Langerhans' cells (LC) are mobilized and migrate to the local lymph node where they play a major role in initiating or regulating immune responses. It had been proposed that all chemical allergens induce LC migration via common cytokine signals delivered by TNF-α and IL-1ß. Here the dependence of LC migration on TNF-α following treatment of mice with various chemical allergens has been investigated. It was found that under standard conditions the allergens oxazolone, paraphenylene diamine, and trimellitic anhydride, in addition to the skin irritant sodium lauryl sulfate, were unable to trigger LC mobilization in the absence of TNF-α signalling. In contrast, two members of the dinitrohalobenezene family (2,4-dinitrochlorobenzene [DNCB] and 2,4-dinitrofluorobenzene [DNFB]) promoted LC migration independently of TNF-R2 (the sole TNF-α receptor expressed by LC) and TNF-α although the presence of IL-1ß was still required. However, increasing doses of oxazolone overcame the requirement of TNF-α for LC mobilization, whereas lower doses of DNCB were still able to induce LC migration in a TNF-α-independent manner. These novel findings demonstrate unexpected heterogeneity among chemical allergens and furthermore that LC can be induced to migrate from the epidermis via different mechanisms that are either dependent or independent of TNF-α. Although the exact mechanisms with regard to the signals that activate LC have yet to be elucidated, these differences may translate into functional speciation that will likely impact on the extent and quality of allergic sensitization.

De novo LINE-1 retrotransposition in HepG2 cells preferentially targets gene poor regions of chromosome 13.

Long interspersed nuclear elements (Line-1 or L1s) account for ~17% of the human genome. While the majority of human L1s are inactive, ~80-100 elements remain retrotransposition competent and mobilize through RNA intermediates to different locations within the genome. De novo insertions of L1s account for polymorphic variation of the human genome and disruption of target loci at their new location. In the present study, fluorescence in situ hybridization and DNA sequencing were used to characterize retrotransposition profiles of L1(RP) in cultured human HepG2 cells. While expression of synthetic L1(RP) was associated with full-length and truncated insertions throughout the entire genome, a strong preference for gene-poor regions, such as those found in chromosome 13 was observed for full-length insertions. These findings shed light into L1 targeting mechanisms within the human genome and question the putative randomness of L1 retrotransposition.

An integrated characterization of serological, pathological, and functional events in doxorubicin-induced cardiotoxicity.

Many efficacious cancer treatments cause significant cardiac morbidity, yet biomarkers or functional indices of early damage, which would allow monitoring and intervention, are lacking. In this study, we have utilized a rat model of progressive doxorubicin (DOX)-induced cardiomyopathy, applying multiple approaches, including cardiac magnetic resonance imaging (MRI), to provide the most comprehensive characterization to date of the timecourse of serological, pathological, and functional events underlying this toxicity. Hannover Wistar rats were dosed with 1.25 mg/kg DOX weekly for 8 weeks followed by a 4 week off-dosing "recovery" period. Electron microscopy of the myocardium revealed subcellular degeneration and marked mitochondrial changes after a single dose. Histopathological analysis revealed progressive cardiomyocyte degeneration, hypertrophy/cytomegaly, and extensive vacuolation after two doses. Extensive replacement fibrosis (quantified by Sirius red staining) developed during the off-dosing period. Functional indices assessed by cardiac MRI (including left ventricular ejection fraction (LVEF), cardiac output, and E/A ratio) declined progressively, reaching statistical significance after two doses and culminating in "clinical" LV dysfunction by 12 weeks. Significant increases in peak myocardial contrast enhancement and serological cardiac troponin I (cTnI) emerged after eight doses, importantly preceding the LVEF decline to <50%. Troponin I levels positively correlated with delayed and peak gadolinium contrast enhancement, histopathological grading, and diastolic dysfunction. In summary, subcellular cardiomyocyte degeneration was the earliest marker, followed by progressive functional decline and histopathological manifestations. Myocardial contrast enhancement and elevations in cTnI occurred later. However, all indices predated "clinical" LV dysfunction and thus warrant further evaluation as predictive biomarkers.

Reprogramming of the HepG2 genome by long interspersed nuclear element-1.

Long Interspersed Nuclear Element-1 (LINE-1 or L1) is an autonomous, mobile element within the human genome that transposes via a "copy and paste" mechanism and relies upon L1-encoded endonuclease and reverse transcriptase (RT) activities to compromise genome integrity. L1 has been implicated in various forms of cancer, but its role in the regulation of the oncogenic phenotype is not understood. The present studies were conducted to evaluate mechanisms of genetic regulatory control in HepG2 cells by human L1, or a D702Y mutant deficient in RT activity, and their influence on cellular phenotype. Forced expression of synthetic L1 ORF1p and ORF2p was associated with formation of cytoplasmic foci and minor association with the nuclear compartment. While de novo L1 mobilizations were only identified in cells expressing wild type L1, and were absent in the D702Y mutant, changes in gene expression profiles involved RT dependent as well as RT independent mechanisms. Synthetic L1 altered the expression of 24 in silico predicted genetic targets; ten of which showed RT-dependence, ten RT-independence, and four reciprocal regulatory control by both wild type and RT mutant. Of five targets examined, only VCAM1 and PTPRB colocalized with newly retrotransposed wild type L1. Biological discretization to partition patterns of gene expression into unique frequencies identified adhesion, inflammation, and cellular metabolism as key processes targeted for molecular interference with disruption of epithelial-to-mesenchymal programming seen irrespective of the RT phenotype. These findings establish L1 as a key regulator of genome plasticity and EMT via mechanisms independent of RT activity.

Target organ toxicities in studies conducted to support first time in man dosing: an analysis across species and therapy areas.

An analysis of target organ toxicities in first time in man (FTiM) toxicity studies for 77 AstraZeneca candidate drugs (CDs) was conducted across a range of therapy areas. In the rodent, the most frequently affected organ was the liver followed by adrenal glands, kidney, spleen, bone marrow and thymus. In non-rodent, liver and thymus were the most frequently affected organs, followed closely by the testis and GI tract. The profile of affected organs was largely similar across the therapy areas of respiratory and inflammation, cardiovascular/gastrointestinal and CNS/pain. The oncology/infection therapy area differed with a larger range of organs affected. For the 75 CDs for which both rodent and non-rodent studies were conducted, new target organs were identified in non-rodents for 43 of the CDs. Notably, the changes seen only in non-rodents included organ systems of high relevance for human risk assessment such as the liver, male reproductive tissues and CNS. Additionally, profiles were similar for those CDs that progressed into human trials and those that did not. Overall, our data provide new insights into drug toxicity profiles in pre-clinical species and additionally confirm the value of using non-rodents as a second species in toxicity testing to support human safety.

Exploring family communication about sickle cell disease in adolescence.

Sickle cell disease (SCD) is a lifelong disorder that involves progressive organ damage and requires ongoing medical attention to prevent and treat episodic acute complications. Children with SCD need ongoing monitoring and extra attention that may be stressful to family members. Communication within families can help resolve family stress and may be associated with medical follow-up and management of SCD. Focus groups were conducted with 12 African American families to explore the communication that occurred within and outside of the family from the perspectives of adolescents with SCD, siblings, and parents. Factors that influence family communication were explored. The extended family was an important social network and resource to adolescents, siblings, and parents. Family member knowledge of SCD was an important factor that influenced communication about SCD; adolescents and parents communicated more easily than siblings and also reported having more knowledge of SCD than siblings. Future research focusing on the knowledge of immediate and extended family members and their recognition of their contribution to the child with SCD is recommended.

Induction of heart valve lesions by small-molecule ALK5 inhibitors.

Aberrant signaling by transforming growth factor-ß (TGF-ß) and its type I (ALK5) receptor has been implicated in a number of human diseases and this pathway is considered a potential target for therapeutic intervention. Transforming growth factor-ß signaling via ALK5 plays a critical role during heart development, but the role of ALK5 in the adult heart is poorly understood. In the current study, the preclinical toxicology of ALK5 inhibitors from two different chemistry scaffolds was explored. Ten-week-old female Han Wistar rats received test compounds by the oral route for three to seven days. Both compounds induced histopathologic heart valve lesions characterized by hemorrhage, inflammation, degeneration, and proliferation of valvular interstitial cells. The pathology was observed in all animals, at all doses tested, and occurred in all four heart valves. Immunohistochemical analysis of ALK5 in rat hearts revealed expression in the valves, but not in the myocardium. Compared to control animals, protein levels of ALK5 were unchanged in the heart valves of treated animals. We also observed a physeal dysplasia in the femoro-tibial joint of rats treated with ALK5 inhibitors, a finding consistent with a pharmacological effect described previously with ALK5 inhibitors. Overall, these findings suggest that TGF-ß signaling via ALK5 plays a critical role in maintaining heart valve integrity.

Cardiotoxicity associated with targeting kinase pathways in cancer.

Cardiotoxicity, also referred to as drug-induced cardiac injury, is an issue associated with the use of some small-molecule kinase inhibitors and antibody-based therapies targeting signaling pathways in cancer. Although these drugs have had a major impact on cancer patient survival, data have implicated kinase-targeting agents such as sunitinib, imatinib, trastuzumab, and sorafenib in adversely affecting cardiac function in a subset of treated individuals. In many cases, adverse cardiac events in the clinic were not anticipated based on preclinical safety evaluation of the molecule. In order to support the development of efficacious and safe kinase inhibitors for the treatment of cancer and other indications, new preclinical approaches and screens are required to predict clinical cardiotoxicity. Laboratory investigations into the underlying molecular mechanisms of heart toxicity induced by these molecules have identified potentially common themes including mitochondrial perturbation and modulation of adenosine monophosphate-activated protein kinase activity. Studies characterizing cardiac-specific kinase knockout mouse models have developed our understanding of the homeostatic role of some of these signaling mediators in the heart. Therefore, when considering kinases as potential future targets or when examining secondary pharmacological interactions of novel kinase inhibitors, these models may help to inform us of the potential adverse cardiac effects in the clinic.

Toxicological and pathophysiological roles of reactive oxygen and nitrogen species.

'Oxidative and Nitrative Stress in Toxicology and Disease' was the subject of a symposium held at the EUROTOX meeting in Dresden 15th September 2009. Reactive oxygen (ROS) and reactive nitrogen species (RNS) produced during tissue pathogenesis and in response to viral or chemical toxicants, induce a complex series of downstream adaptive and reparative events driven by the associated oxidative and nitrative stress. As highlighted by all the speakers, ROS and RNS can promote diverse biological responses associated with a spectrum of disorders including neurodegenerative/neuropsychiatric and cardiovascular diseases. Similar pathways are implicated during the process of liver and skin carcinogenesis. Mechanistically, reactive oxygen and nitrogen species drive sustained cell proliferation, cell death including both apoptosis and necrosis, formation of nuclear and mitochondrial DNA mutations, and in some cases stimulation of a pro-angiogenic environment. Here we illustrate the pivotal role played by oxidative and nitrative stress in cell death, inflammation and pain and its consequences for toxicology and disease pathogenesis. Examples are presented from five different perspectives ranging from in vitro model systems through to in vivo animal model systems and clinical outcomes.