Why and how does cancer start? Building from a Symposium at the 2025 Society of Toxicology meeting, we convened a group of international experts to answer this seemingly simple question. As experimental evidence has evolved, perspectives on cancers’ origins have shifted from the accumulation of DNA mutations in single cells to complex processes involving signals from an altered tissue microenvironment which promote tumorigenesis. Carcinogen exposures impact the biology of the microenvironment in complex and tissue-specific ways. These changes can include the infiltration of inflammatory cells that produce growth factors, neo-angiogenesis, morphological changes, and immune tolerance that avoids immune-mediated elimination. In this in-depth review, we discuss the evidence linking chemical-driven microenvironmental changes in the development of a range of solid and liquid tumors. We discuss specific phenotypic alterations, such as selection pressure driving clonal expansion and cellular plasticity and reacquisition of stem cell states, linked to carcinogen-induced changes in the microenvironment. We describe assays and biomarkers which can allow us to experimentally assess links between chemical exposures, the microenvironment, and cancer phenotypes. We end by discussing how understanding the role of the microenvironment and malignancy in toxicology is essential for accurate cancer hazard evaluation, development of next-generation risk assessment frameworks, identifying new strategies for cancer prevention, and improving patient care.

Most known chemical carcinogens induce the direct activation of DNA damage, either directly or following metabolic activation. However, carcinogens do not always operate directly through genotoxic mechanisms but can do so via non-genotoxic carcinogenic (NGTxC) mechanisms. Immune dysfunction is one of these key events that NGTxCs have been shown to modify. The immune system is a first line of defence against transformed cells, with an innate immune response against cancer cells and mechanisms of immune evasion. Here, we review the key events of immune dysfunction. These include immunotoxicity, immune evasion, immune suppression and inflammatory-mediated immune responses, and the key players in the molecular disruption of immune anti-cancer molecular signalling pathways, particularly those mediated by cytokines and the Aryl hydrocarbon Receptor, in relation to the identification of NGTxC. The plasticity of cytokines towards functional flexibility in response to environmental stressors is also discussed from an evolutionary heritage perspective. This is combined with a critical assessment of the suitability for the regulatory application of currently available test method tools and is corroborated by the key biomarkers of, e.g., MAPK, mTOR, PD-L1, TIL and Tregs, CD8+, FoxP3+, WNT, IL-17, IL-11, IL-10, and TNFα, as identified from robust cancer biopsy studies. Finally, an understanding of how to address these endpoints for chemical hazard regulatory purposes, within an integrated approach to testing and assessment for NGTxC, is proposed.

Perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are the major components of long-chain per- and polyfluorinated alkyl substances (PFAS), known for their chemical stability and environmental persistence. Even if PFOA and PFOS have been phased out or are limited in use, they still represent a concern for human and environmental health. Several studies have been per­formed to highlight the toxicological behavior of these chemicals and their mode of action (MoA). Data have suggested a causal association between PFOA or PFOS exposure and carcinogenicity in humans, but the outcomes of epidemiological studies showed some inconsistency. Moreover, the hypothesized MoA based on animal studies is considered not relevant for human cancer. To improve the knowledge on PFAS toxicology and contribute to the weight of evidence for the regu­latory classification of PFAS, we used the BALB/c 3T3 cell transformation assay (CTA), an in vitro model under consideration to be included in an integrated approach to testing and assessment for non-genotoxic carcinogens (NGTxCs). PFOS and PFOA were tested at several concentrations using a validated experimental protocol. Our results demonstrate that PFOA does not induce cell transformation, whereas PFOS exposure induced a concentration-related increase of type III foci. Malignant foci formation was triggered at PFOS concentrations equal to or higher than 50 ppm and was not directly associated with cytotoxicity or proliferation induction. The divergent CTA outcomes suggest that different molecular events could be responsible for the toxicological profiles of PFOS and PFOA, which were not fully captured in our study.

Di(ethylhexyl) phthalate (DEHP) is a ubiquitous environmental contaminant to which humans are exposed via multiple routes. Human health risk assessments for this substance have recently been updated, focusing on reproductive toxicity, including DEHP, in the list of chemicals classified as carcinogenic, mutagenic, or toxic to reproduction (CMR). Moreover, DEHP has also been defined as probably and possibly carcinogenic to humans based on its carcinogenicity in rodents. However, the mechanism of action of DEHP and its relevance in humans remain unclear. Rodent data suggests that DEHP induces cancer through non-genotoxic mechanisms related to multiple molecular signals, including PPARα activation, perturbation of fatty acid metabolism, induction of cell proliferation, decreased apoptosis, production of reactive oxygen species, and oxidative stress. According to the DEHP toxicological dataset, several in vitro cell transformation assays have been performed using different protocols and cellular models to produce different results. This study aimed to evaluate the carcinogenic potential of DEHP by using the A31-1-1 BALB/c-3T3 cell line in a standard cell transformation assay. Additionally, transcriptomic analysis was performed to explore the molecular responses and identify the affected toxicological pathways. Although DEHP treatment did not induce transformation in BALB/c-3T3 cells, the transcriptomic results revealed significant modulation of several pathways associated with DEHP metabolism, tissue-specific functions related to systemic metabolism, and basal cellular signaling with pleiotropic outcomes. Among these signaling pathways, modulation of cell-regulating signaling pathways, such as Notch, Wnt, and TGF-β, can be highlighted. More specific modulation of such genes and pathways with double functions in metabolism and neurophysiology underlies the well-known crosstalk that may be crucial for the mechanism of action of DEHP. Our findings offer evidence to support the notion that these models are effective in minimizing the use of animal testing for toxicity assessment.

Introduction: Long-term contamination of tap water and groundwater by perfluoroalkyl and polyfluoroalkyl substances (PFASs) has been documented in the Veneto region of northern Italy. This study aimed to assess the exposure of individuals residing in the contaminated area and to test several toxicokinetic (TK) models of varying complexities to identify an efficient method for predicting perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) concentrations in human serum using observed data.The ultimate goal is to provide public health officials with guidance on selecting the appropriate TK model for specific contexts, a reliable and rapid tool to support human bio-monitoring (HBM) studies. Methods: Two simpler empirical TK models and a more complex multi-compartment physiologically based toxicokinetic (PBTK) model were compared with individual and aggregate data from an HBM study. In addition, the PBPK model was modified by adjusting input parameters and introducing new terms into the equations within the original model code. These modifications aimed to optimize the results compared to the original model, with some versions incorporating adjustments to account for the influence of menstruation in women. All models were evaluated to understand their strengths and weaknesses, providing guidance on the appropriate model to use according to specific scenarios. Results: The results obtained from the tested models were quite similar, with significant improvements observed only in the modified models. Simpler models also provided satisfactory results in scenarios involving low PFOS serum concentrations and recent exposure cessation. In many cases, predictions demonstrated high accuracy, particularly at the aggregate level and for women. Conclusions: These findings suggest that environmental protection agencies and health authorities may benefit from employing the tested models at the aggregate level as an initial step in HBM studies, rather than conducting more invasive and expensive screening campaigns.

The study investigated the application of Wastewater-Based Epidemiology (WBE) as a tool for monitoring the SARS-CoV-2 prevalence in a city in northern Italy from October 2021 to May 2023. Based on a previously used deterministic model, this study proposed a variation to account for the population characteristics and virus biodegradation in the sewer network. The model calculated virus loads and corresponding COVID-19 cases over time in different areas of the city and was validated using healthcare data while considering viral mutations, vaccinations, and testing variability. The correlation between the predicted and reported cases was high across the three waves that occurred during the period considered, demonstrating the ability of the model to predict the relevant fluctuations in the number of cases. The population characteristics did not substantially influence the predicted and reported infection rates. Conversely, biodegradation significantly reduced the virus load reaching the wastewater treatment plant, resulting in a 30% reduction in the total virus load produced in the study area. This approach can be applied to compare the virus load values across cities with different population demographics and sewer network structures, improving the comparability of the WBE data for effective surveillance and intervention strategies.

The complexity of cancer requires a comprehensive approach to understand its diverse manifestations and underlying mechanisms. Initially outlined by Hanahan and Weinberg in 2000 and updated in 2010, the hallmarks of cancer provide a conceptual basis for understanding inherent variability in cancer biology. Recent expansions have further elucidated additional hallmarks, including phenotypic plasticity and senescent cells. The International Agency for Research on Cancer (IARC) has identified the key characteristics of carcinogens (KCCs) to evaluate their carcinogenic potential. We analyzed chemicals of concern for environmental exposure that interact with specific receptors to induce genomic instability, epigenetic alterations, immune suppression, and receptor-mediated effects, thereby contributing to chronic inflammation. Despite their varying degrees of carcinogenicity, these chemicals have similar KCC profiles. Our analysis highlights the pivotal role of receptor binding in activating most other KCCs, underscoring their significance in cancer initiation. Although KCCs are associated with early molecular or cellular events, they do not encompass processes directly linked to full cellular malignancy. Thus, there is a need to integrate clear endpoints that anchor KCCs to the acquisition of a complete malignant phenotype into chemical testing. From the perspective of toxicology and cancer research, an all-encompassing strategy that incorporates both existing and novel KCCs and cancer hallmarks is essential to enable the targeted identification of prevalent carcinogens and facilitate zone-specific prevention strategies. To achieve this goal, collaboration between the KCC and cancer hallmarks communities becomes essential.

The history of the development of the cell transformation assays (CTAs) is described, providing an overview of in vitro cell transformation from its origin to the new transcriptomic-based CTAs. Application of this knowledge is utilized to address how the different types of CTAs, variously addressing initiation and promotion, can be included on a mechanistic basis within the integrated approach to testing and assessment (IATA) for non-genotoxic carcinogens. Building upon assay assessments targeting the key events in the IATA, we identify how the different CTA models can appropriately fit, following preceding steps in the IATA. The preceding steps are the prescreening transcriptomic approaches, and assessment within the earlier key events of inflammation, immune disruption, mitotic signaling and cell injury. The CTA models address the later key events of (sustained) proliferation and change in morphology leading to tumor formation. The complementary key biomarkers with respect to the precursor key events and respective CTAs are mapped, providing a structured mechanistic approach to represent the complexity of the (non-genotoxic) carcinogenesis process, and specifically their capacity to identify non-genotoxic carcinogenic chemicals in a human relevant IATA.

Reducing children’s exposure to air pollutants should be considered a primary goal, especially for the most vulnerable subjects. The goal of this study was to test the effectiveness of applying a protocol in the event of alert days, i.e., days with forecasted PM10 levels above the EU limit value (50 µg/m3). The test was conducted, before the onset of SARS-CoV-2 restrictions, in a classroom of a primary school in Parma (Italy)—a highly polluted area in Northern Italy. The protocol included indications for the frequency of opening windows and doors, as well as the activation of an air purifier. Teachers and students were asked to apply the protocol only in the event of alert days, while no indications were provided for non-alert days. A monitoring system measuring PM1, PM2.5, PM10, CO2, and NO2 was deployed in the classroom. Measurements of the same parameters were also performed outdoors near the school. The application of the protocol reduced the indoor/outdoor (I/O) ratio for all toxic pollutants. The reduction was also remarkable for PM10—the most critical air quality parameter in the study area (1.5 and 1.1 for non-alert and alert days, respectively). Indoor concentrations of PM10—especially during non-alert days—were often higher than outdoors, showing a major contribution from resuspension due to the movement of people and personal cloud. The protocol did not cause any increase in indoor CO2 levels. Our findings showed that the application of a ventilation protocol together with the contribution of an air purifier may represent an effective way to reduce children’s exposure to air pollution during severe air pollution episodes. Considering the onset of COVID-19 and the airborne transmission of pathogens, this protocol now has more meaningful implications for children’s welfare, and can be integrated with protocols designed as measures against the spread of SARS-CoV-2.

The Transformics Assay is an in vitro test which combines the BALB/c 3T3 Cell Transformation Assay (CTA) with microarray transcriptomics. It has been shown to improve upon the mechanistic understanding of the CTA, helping to identify mechanisms of action leading to chemical-induced transformation thanks to RNA extractions in specific time points along the process of in vitro transformation. In this study, the lowest transforming concentration of the carcinogenic benzo(a)pyrene (B(a)P) has been tested in order to find molecular signatures of initial events relevant for oncotransformation. Application of Enrichment Analysis (Metacore) to the analyses of the results facilitated key biological interpretations. After 72 h of exposure, as a consequence of the molecular initiating event of aryl hydrocarbon receptor (AhR) activation, there is a cascade of cellular events and microenvironment modification, and the immune and inflammatory responses are the main processes involved in cell response. Furthermore, pathways and processes related to cell cycle regulation, cytoskeletal adhesion and remodeling processes, cell differentiation and transformation were observed.

Introduction: The relationship between air pollution and respiratory morbidity has been widely addressed in urban and metropolitan areas but little is known about the effects in non-urban settings. Aims: To assess the short-term effects of PM10 and PM2.5 on respiratory admissions in whole country of Italy during 2006-2015. Methods: We estimated daily PM concentrations at the municipality level (n 8,092) using a machine learning method based on satellite data and spatiotemporal predictors. We collected daily counts of respiratory hospital admissions for each Italian municipality. We considered five different outcomes: all respiratory, asthma, chronic obstructive pulmonary disease (COPD), lower and upper respiratory tract infections (LRTI and URTI). We ran municipality-specific time-series models and we meta-analyzed individual effects to obtain national estimates for the above outcomes. Finally, we tested for effect modification by sex, age classes and degree of urbanization. Results: A total of 4,154,887 non-scheduled acute respiratory admission were registered during 2006-2015, of which 29%, 12%, 6%, and 3% were for LRTI, COPD, URTI and asthma, respectively. Daily mean PM10 and PM2.5 concentrations over the study period were 23.3 and 17 mg/m3. For each 10 mg/m3 increases in PM10 and PM2.5 at lag 0-5 days, we found excess risks of total respiratory diseases equal to 1.10% (95% confidence intervals: 0.82, 1.39) and 0.82 (0.35, 1.30), respectively. Higher effects were found in the elderly and in areas less urbanized. Conclusions: Short-term exposure to PM is harmful for the respiratory system, especially in elderly patients. Strong effects were found also in rural areas.

Abstract The rodent-based life-time cancer bioassay is still the basic experimental paradigm to assess the carcinogenic potential of chemicals, with relatively little progress regarding the acceptance of in vitro tests. The Transformics Assay is an in vitro test which combines the BALB/c 3T3 Cell Transformation Assay (CTA) with microarray transcriptomics. It has been shown to improve upon the mechanistic understanding of the CTA, helping to identify mechanisms of action leading to chemical-induced transformation thanks to RNA extractions in specific time points along the process of in vitro transformation. In this study the lowest transforming concentration of the carcinogenic benzo(a)pyrene (B(a)P) has been tested in order to find molecular signatures of initial events relevant for oncotransformation. Some biological interpretations are presented related to the Enrichment Analysis provided by Metacore. Results show that after 72 hrs of exposure, the immune and inflammatory responses are the main processes involved in cell response. Furthermore, pathways and processes related to cell cycle regulation, cytoskeletal adhesion and remodeling processes, cell differentiation and transformation were observed. All these data are interpreted as a consequence of the initial aryl hydrocarbon receptor (AhR) activation leading to a cascade of cellular events and microenvironment modification.

Background and aims: Ionizing radiation (IR) are a well-known carcinogenic agent, acting through genotoxic mechanisms. In the last years, great attention has been paid to the effects of IR at low doses and to the non-monotonic dose-response curve for IR exposures. To improve the knowledge of IR-mediated effects and possibly identify biomarkers for IR effects, we combined the Cell Transformation Assay (CTA) with transcriptomics, to correlate cytotoxicity and transformation endpoints with the modulation of gene profiles after IR exposure. Methods: BALB/c3T3 cells were exposed to ionizing radiation ranging from 0.25Gy and 6Gy. Irradiated cells were seeded for the CTA 20h later. At the same time, RNA was extracted for microarray experiments. The cell clonal survival was significantly increased in 0.25Gy IR exposed cells, while the 3Gy dose strongly inhibited cellular growth. Cell transformation was observed only at the highest dose (3Gy). Results: Cell’s transformation was observed at 1.5, 2 and 3Gy doses. The 0.25Gy dose, which was able to induce an increment of clonal efficiency, did not induce cell transformation. The gene expression profile, which was obtained by comparing cells treated with the highest tested dose of 3Gy with the cells exposed to the lowest, not transforming, dose of 0.25Gy, identified several genes related to mitotic cell cycle and cholesterol biosynthesis. Conclusion: Our study showed that the up-regulation of genes belonging to the Spindle Assembly Checkpoint and mitosis progression could support the transforming ability of the 3Gy BALB/c3T3 exposed cells, probably through the involvement of genomic instability. Gene transcripts involved into cholesterol biosynthesis appear to be critical, as well. All these transcripts may be regarded as potential biomarkers of IR effects.

Cities are severely affected by air pollution. Local emissions and urban structures can produce large spatial heterogeneities. We aim to improve the estimation of NO2, O-3, PM2.5 and PM10 concentrations in 6 Italian metropolitan areas, using chemical-transport and machine learning models, and to assess the effect on population exposure by using information on urban population mobility. Three years (2013-2015) of simulations were performed by the Chemical-Transport Model (CTM) FARM, at 1 km resolution, fed by boundary conditions provided by national-scale simulations, local emission inventories and meteorological fields. A downscaling of daily air pollutants at higher resolution (200 m) was then carried out by means of a machine learning Random-Forest (RF) model, considering CTM and spatial-temporal predictors, such as population, land-use, surface greenness and vehicular traffic, as input. RF achieved mean cross-validation (CV) R-2 of 0.59, 0.72, 0.76 and 0.75 for NO2, PM10, PM2.5 and O-3, respectively, improving results from CTM alone. Mean concentration fields exhibited clear geographical gradients caused by climate conditions, local emission sources and photochemical processes. Time series of population weighted exposure (PWE) were estimated for two months of the year 2015 and for five cities, by combining population mobility data (derived from mobile phone traffic volumes data), and concentration levels from the RF model. PWE_RF metric better approximated the observed concentrations compared with the predictions from either CTM alone or CTM and RF combined, especially for pollutants exhibiting strong spatial gradients, such as NO2. 50% of the population was estimated to be exposed to NO2 concentrations between 12 and 38 mu g/m(3) and PM10 between 20 and 35 mu g/m(3). This work supports the potential of machine learning methods in predicting air pollutant levels in urban areas at high spatial and temporal resolutions.

Background and goals: A wide area in the Veneto region (northern Italy) has been faced a perfluoroalkyl substances (PFAS) contamination occurred mainly in groundwater and drinking water. Exposure of the population likely started in the Sixties, had a sure decrease after filters installation in 2013. The Veneto Region is conducting a biomonitoring study to investigate health conditions of the exposed population, collecting hundreds of serum samples. Some Physiologically based Pharmacokinetic (PBPK) models are being tested comparing PFOA and PFOS measured levels with the estimated ones.Methods: Original Loccisano model corrected by EFSA Scientific Panel was tested for this case study. A worst case scenario (WCS) and a best case scenario (BCS) were developed. Both scenarios took into account individual simulations carried out on 25 people (11 men and 14 women), aged 22-39 years, living in an area with both groundwater and drinking water contamination. WCS considered water intake from the private well, company water and bottled water in the same proportion. In the BCS we assumed 1/3 of the water intake from drinking water and 2/3 from bottled water.Results: Estimated average PFOA serum level obtained from the WCS was very near to the measured one for men (E:151.4±68.4;M:108.6±51.0 ng/mL), while was farther but still quite near the measured value for women (E:132.2±108.2;M:30.9±30.1 ng/mL). In the BCS the result is the opposite (men, E:23.9±10.4; women, E:22.1±13.2 ng/mL).Conclusions: Model seems to predict well PFOA serum levels in the exposed population even with high entity of uncertainties. Loccisano model is a multi-compartment PBPK model created specifically for PFAS, but with no modelization of menstruation and pregnancy losses. New simulations are being running to increase statistical significance but we are also looking at other models to take into account gender differences, to explain differences between men and women observed in measured data.

Background and goals: The estimate of the internal dose provided by physiologically based pharmacokinetic (PBPK) modelling is a big step forward in the frame of human health risk assessment (HRA) from contaminating sources. The PBPK model included in the MERLIN-Expo platform was here tested with data collected in a human biomonitoring (HBM) pilot study to check model efficacy in predicting concentrations in human blood and urine of people exposed to a modern solid waste incinerator (SWI). The aim of the study was to investigate if the use of a PBPK model integrated in a computational platform could replace more expensive and invasive pilot studies. Twenty eight subjects living and working within 4 km of the incinerator (exposed) and 21 subjects living and working outside this area (unexposed) were selected among the population recruited in the HBM study. The group of exposed (E) subjects and the group of non-exposed (NE) subjects were comparable for all relevant anthropometric characteristics and exposure parameters except for the exposure to SWI emissions. Three different scenarios were created: an “only diet-scenario” (DS), a “worst case scenario” (WCS) and a “most likely scenario” (MLS). The platform was tested for blood-lead (B-Pb), urinary-lead (U-Pb), urinary-anthracene (U-Ant) and urinary-fluoranthene (U-Flt). Average estimated U-Pb was statistically equal to the measured one (est. 0.411~0.278; meas. 0.398~0.455 µg/L) and estimated vs. measured U-Ant differ by one order of magnitude only (est. 0.018~0.010; meas. 0.537~0.444 ng/L) while for U-Flt and B-Pb, the error was respectively of two and four orders of magnitude. It is likely that the extremely high accuracy in the Pb concentration input values referring to diet led to the very accurate estimate for this chemical in urine, but the higher error in the B-Pb computed value suggests that PBPK model equations cannot entirely capture the dynamics for blood compartments. MERLIN-Expo seems a very promising tool in saving time, energy and money in the screening step of the HRA framework; however, many software validations are still required.