Glyphosate is the most widely used broad-spectrum systemic herbicide in the world. Recent evaluations of the carcinogenic potential of glyphosate-based herbicides (GBHs) by various regional, national, and international agencies have engendered controversy. We investigated whether there was an association between high cumulative exposures to GBHs and increased risk of non-Hodgkin lymphoma (NHL) in humans. We conducted a new meta-analysis that included the most recent update of the Agricultural Health Study (AHS) cohort published in 2018 along with five case-control studies. Using the highest exposure groups when available in each study, we report the overall meta-relative risk (meta-RR) of NHL in GBH-exposed individuals was increased by 41% (meta-RR = 1.41, 95% CI, confidence interval: 1.13-1.75). For comparison, we also performed a secondary meta-analysis using high-exposure groups with the earlier AHS (2005), and we determined a meta-RR for NHL of 1.45 (95% CI: 1.11-1.91), which was higher than the meta-RRs reported previously. Multiple sensitivity tests conducted to assess the validity of our findings did not reveal meaningful differences from our primary estimated meta-RR. To contextualize our findings of an increased NHL risk in individuals with high GBH exposure, we reviewed available animal and mechanistic studies, which provided supporting evidence for the carcinogenic potential of GBH. We documented further support from studies of malignant lymphoma incidence in mice treated with pure glyphosate, as well as potential links between GBH exposure and immunosuppression, endocrine disruption, and genetic alterations that are commonly *

Due to the unprecedented public health crisis caused by COVID-19, our first contribution to the newly launching journal, Advances in Biomarker Sciences and Technology , has abruptly diverted to focus on the current pandemic. As the number of new COVID-19 cases and deaths continue to rise steadily around the world, the common goal of healthcare providers, scientists, and government officials worldwide has been to identify the best way to detect the novel coronavirus, named SARS-CoV-2, and to treat the viral infection – COVID-19. Accurate detection, timely diagnosis, effective treatment, and future prevention are the vital keys to management of COVID-19, and can help curb the viral spread. Traditionally, biomarkers play a pivotal role in the early detection of disease etiology, diagnosis, treatment and prognosis. To assist myriad ongoing investigations and innovations, we developed this current article to overview known and emerging biomarkers for SARS-CoV-2 detection, COVID-19 diagnostics, treatment and prognosis, and ongoing work to identify and develop more biomarkers for new drugs and vaccines. Moreover, biomarkers of socio-psychological stress, the high-technology quest for new virtual drug screening, and digital applications are described.

Formaldehyde (FA), a major industrial chemical and ubiquitous environmental pollutant, has been classified as a leukemogen. The causal relationship remains unclear, however, due to limited evidence that FA induces toxicity in bone marrow, the site of leukemia induction, and in other distal organs. Although induction of DNA-protein crosslinks (DPC), a hallmark of FA toxicity, was not previously detected in the bone marrow of FA-exposed rats and monkeys in studies published in the 1980s, our recent studies showed increased DPC in the bone marrow, liver, kidney, and testes of exposed Kunming mice. To confirm these preliminary results, in the current study we exposed BALB/c mice to 0, 0.5, 1.0, and 3.0 mg m(-3) FA (8 hr per day, for 7 consecutive days) by nose-only inhalation and measured DPC levels in bone marrow and other organs of exposed mice. As oxidative stress is a potential mechanism of FA toxicity, we also measured glutathione (GSH), reactive oxygen species (ROS), and malondialdehyde (MDA), in the bone marrow, peripheral blood mononuclear cells, lung, liver, spleen, and testes of exposed mice. Significant dose-dependent increases in DPC, decreases in GSH, and increases in ROS and MDA were observed in all organs examined (except for DPC in lung). Bone marrow was among the organs with the strongest effects for DPC, GSH, and ROS. In conclusion, exposure of mice to FA by inhalation induced genotoxicity and oxidative stress in bone marrow and other organs. These findings strengthen the biological plausibility of FA-induced leukemogenesis and systemic toxicity.

BackgroundPreviously, using microarrays and mRNA-Sequencing (mRNA-Seq) we found that occupational exposure to a range of benzene levels perturbed gene expression in peripheral blood mononuclear cells.ObjectivesIn the current study, we sought to identify gene expression biomarkers predictive of benzene exposure below 1 part per million (ppm), the occupational standard in the U.S.MethodsFirst, we used the nCounter platform to validate altered expression of 30 genes in 33 unexposed controls and 57 subjects exposed to benzene (<1 to ≥5 ppm). Second, we used SuperLearner (SL) to identify a minimal number of genes for which altered expression could predict <1 ppm benzene exposure, in 44 subjects with a mean air benzene level of 0.55±0.248 ppm (minimum 0.203ppm).ResultsnCounter and microarray expression levels were highly correlated (coefficients >0.7, p<0.05) for 26 microarray-selected genes. nCounter and mRNA-Seq levels were poorly correlated for 4 mRNA-Seq-selected genes. Using negative binomial regression with adjustment for covariates and multiple testing, we confirmed differential expression of 23 microarray-selected genes in the entire benzene-exposed group, and 27 genes in the <1 ppm-exposed subgroup, compared with the control group. Using SL, we identified 3 pairs of genes that could predict <1 ppm benzene exposure with cross-validated AUC estimates >0.9 (p<0.0001) and were not predictive of other exposures (nickel, arsenic, smoking, stress). The predictive gene pairs are PRG2/CLEC5A, NFKBI/CLEC5A, and ACSL1/CLEC5A. They play roles in innate immunity and inflammatory responses.ConclusionsUsing nCounter and SL, we validated the altered expression of multiple mRNAs by benzene and identified gene pairs predictive of exposure to benzene at levels below the US occupational standard of 1ppm.

ObjectiveRecent evidence has accumulated that the immune system is intimately intertwined with cancer development. Two key characteristics of carcinogens in which the immune system plays a central role are chronic inflammation and immunosuppression. In this systematic review, we investigated the association of chronic inflammatory and immunosuppressive outcomes with benzene, a widely used industrial chemical. Benzene has been confirmed to cause acute myeloid leukaemia and suspected to cause non-Hodgkin lymphoma, two cancers of the blood-forming system that affect immune cells.MethodsWe systematically searched PubMed and Embase for all relevant studies using a combination of Medical Subject Headings (MeSH) and selected key words. The detailed review protocol, including search strategy, was registered with PROSPERO, the international prospective register of systematic reviews (#CRD42019138611).ResultsBased on all human studies selected in the final review, we report new evidence of a benzene-induced immunosuppressive effect on the adaptive immune system and activation of the innate immune system to cause inflammation. In particular, benzene significantly lowers the number of white blood cells, particularly lymphocytes such as CD4+ T-cells, B-cells and natural killer cells, and increases proinflammatory biomarkers at low levels of exposure.ConclusionTo the best of our knowledge, this is the first comprehensive review of benzene’s immunotoxicity in humans. Based on results obtained from this review, we propose two potential immunotoxic mechanisms of how benzene induces leukaemia/lymphoma: (1) cancer invasion caused by proinflammatory cytokine production, and (2) cancer promotion via impaired immunosurveillance. Further studies will be required to confirm the connection between benzene exposure and its effects on the immune system.

Background Non-Hodgkin lymphoma comprises a heterogeneous group of cancers with unresolved aetiology, although risk factors include environmental exposures to toxic chemicals. Although the ubiquitous pollutant benzene is an established leukemogen, its potential to cause non-Hodgkin lymphoma has been widely debated. We aimed to examine the potential link between benzene exposure and risk of non-Hodgkin lymphoma in humans by evaluating a wide array of cohort and case-control studies using electronic systematic review.Methods We did a comprehensive systematic review and meta-analysis of all qualified human epidemiological studies that assessed the relationship between benzene exposure and non-Hodgkin lymphoma. We queried the PubMed and Embase databases for relevant articles published before June 5, 2019, and applied the SysRev platform for study selection. All peer-reviewed human cohort and case-control studies that reported non-Hodgkin lymphoma risk estimates specifically for benzene exposure were eligible for inclusion. Studies that calculated relative risks (RRs) for industries or job types without identifying those specifically exposed to benzene, that combined non-Hodgkin lymphoma with other cancer types, or that reported many different solvent exposures together were excluded. From each study, two investigators independently extracted information on the study design, location, years, sample size, participation rates, age, sex, sources of cases and controls, diagnosis, histological verification, exposure assessment, results, adjustment, and statistical analysis, and subsequently assessed study quality. We calculated the meta-analysis relative risk (meta-RR) and CIs using the fixed effect and random effect models, as well as assessing publication bias.Findings Our search yielded 2481 articles. After screening and removal of duplicates, 20 case-control studies and eight cohort studies were included in our meta-analysis, which included a total of 9587 patients with non-Hodgkin lymphoma. We reported an increased meta-relative risk (meta-RR) of 33% in highly exposed groups, when data were available (meta-RR 1•33 [95% CI 1•13-1•57], n=28). The meta-RR rose to 1•51 (1•22-1•87, n=18) in the studies that provided results specifically for highly exposed individuals. In particular, we reported a doubling of this risk for diffuse large B-cell lymphoma, a major non-Hodgkin lymphoma subtype (1•67 [1•01-2•77]). We also detected increased risks for follicular lymphoma (1•47 [0•95-2•27]) and hairy cell leukaemia (1•77 [0•99-3•16]), though they were not statistically significant. Funnel plot, Egger's test (p=0•77) and Begg's test (p=0•98) did not show evidence of publication bias. We evaluated the major aspects of causal inference and found evidence to support all the Hill considerations for assigning causation.Interpretation Our findings suggest a causal link between benzene exposure and non-Hodgkin lymphoma, especially for diffuse large B-cell lymphoma.

Benzene is a recognized hematotoxin and leukemogen; however, its mechanism of action in humans remain unclear. To provide insight into the processes underlying benzene hematotoxicity, we performed high-resolution metabolomic (HRM) profiling of plasma collected from a cross-sectional study of 33 healthy workers exposed to benzene (median 8-hr time-weighted average exposure; 20 ppma), and 25 unexposed controls in Shanghai, China. Metabolic features associated with benzene were identified using a metabolome-wide association study (MWAS) that tested for the relationship between feature intensity and benzene exposure. MWAS identified 478 mass spectral features associated with benzene exposure at FDR&lt;20%. Comparison to a list of 13 known benzene metabolites and metabolites predicted using a multi-component biotransformation algorithm showed five metabolites were detected, which included the known metabolites phenol and benzene diolepoxide. Metabolic pathway enrichment identified 41 pathways associated with benzene exposure, with altered pathways including carnitine shuttle, fatty acid metabolism, sulfur amino acid metabolism, glycolysis, gluconeogenesis, and branched chain amino acid metabolism. These results suggest disruption to fatty acid uptake, energy metabolism and increased oxidative stress, and point towards pathways related to mitochondrial dysfunction, which has previously been linked to benzene exposure in animal models and human studies. Taken together, these results suggest benzene exposure is associated with disruption of mitochondrial pathways, and provide promising, systems biology biomarkers for risk assessment of benzene-induced hematotoxicity in humans.

BACKGROUND: People are exposed to numerous chemicals throughout their lifetimes. Many of these chemicals display one or more of the key characteristics of carcinogens or interact with processes described in the hallmarks of cancer. Therefore, evaluating the effects of chemical mixtures on cancer development is an important pursuit. Challenges involved in designing research studies to evaluate the joint action of chemicals on cancer risk include the time taken to perform the experiments because of the long latency and choosing an appropriate experimental design. OBJECTIVES: The objectives of this work are to present the case for developing a research program on mixtures of environmental chemicals and cancer risk and describe recommended approaches. METHODS: A working group comprising the coauthors focused attention on the design of mixtures studies to inform cancer risk assessment as part of a larger effort to refine the key characteristics of carcinogens and explore their application. Working group members reviewed the key characteristics of carcinogens, hallmarks of cancer, and mixtures research for other disease end points. The group discussed options for developing tractable projects to evaluate the joint effects of environmental chemicals on cancer development. RESULTS AND DISCUSSION: Three approaches for developing a research program to evaluate the effects of mixtures on cancer development were proposed: a chemical screening approach, a transgenic model-based approach, and a disease-centered approach. Advantages and disadvantages of each are discussed.