The Cell Transformation Assay: A Historical Assessment of Current Knowledge of Applications in an Integrated Approach to Testing and Assessment for Non-Genotoxic Carcinogens.

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.

Molecular subtyping based on TRP family and prognostic assessment for TRP-associated lncRNAs in pancreatic adenocarcinoma.

BACKGROUND: Transient receptor potential (TRP) channels have high permeability to Ca2+ ions because they are non-selective ion channels. TRP channels have been implicated in tumor onset and progression, proliferation, and migration in recent years. However, the prognostic value of genes related to TRP and their specific mechanism in pancreatic adenocarcinoma (PAAD) are yet to be understood. METHODS: Public databases such as TCGA and GEO were used to retrieve data on gene expression and clinical information of patients with pancreatic adenocarcinoma for our study. ConsensusClusterPlus package was used for unsupervised clustering analysis. The microenvironment cell population (MCP)-counter approach was employed to measure the immune cells infiltration status. The Pearson correlation was performed to identify TRP-associated lncRNAs. RESULTS: Initially, we separated PAAD patients into three clusters depending on TRP-related genes, and of the three clusters, cluster B showed the least immune cell infiltration, which was correlated with poor prognosis. Moreover, GSVA enrichment analysis further revealed that cluster A was subjected to a considerable enrichment in carcinogenic signaling pathways, whereas cluster C was enriched in immune-related pathways. Then, using TRP-associated lncRNAs as a starting point, we constructed a prognostic risk model for PAAD patients that could efficiently predict their prognosis. Further, GSEA revealed that cancer-related pathways, for instance, the cell cycle, p53 signaling pathway, etc. were considerably enriched in the high-risk group. In addition, we looked into the link between the prognostic model and the immunological microenvironment. Lower cytotoxic lymphocytes, NK cells, CD8 T cells, and endothelial cells infiltration were found to be associated with high risk using the MCP-counter algorithm. The expression of CD274, POLE2, MCM6, and LOXL2 was also found to be higher in the high-risk group. TMB was also considerably greater in high-risk individuals, indicating that immune checkpoint inhibitors (ICIs) therapy may benefit them more. Lastly, qRT-PCR further confirmed the differential expression of these prognostic TRP-associated lncRNAs, indicating that these lncRNAs play an imperative role in PAAD tumorigenesis. CONCLUSION: TRP family genes may represent a new class of candidate molecular markers of the occurrence and progression of PAAD. Risk models based on TRP-associated lncRNAs could provide important new references for immunotargeted therapy of pancreatic adenocarcinoma.

MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data with transition pathway and critical point detection.

Clustering cells and depicting the lineage relationship among cell subpopulations are fundamental tasks in single-cell omics studies. However, existing analytical methods face challenges in stratifying cells, tracking cellular trajectories, and identifying critical points of cell transitions. To overcome these, we proposed a novel Markov hierarchical clustering algorithm (MarkovHC), a topological clustering method that leverages the metastability of exponentially perturbed Markov chains for systematically reconstructing the cellular landscape. Briefly, MarkovHC starts with local connectivity and density derived from the input and outputs a hierarchical structure for the data. We firstly benchmarked MarkovHC on five simulated datasets and ten public single-cell datasets with known labels. Then, we used MarkovHC to investigate the multi-level architectures and transition processes during human embryo preimplantation development and gastric cancer procession. MarkovHC found heterogeneous cell states and sub-cell types in lineage-specific progenitor cells and revealed the most possible transition paths and critical points in the cellular processes. These results demonstrated MarkovHC's effectiveness in facilitating the stratification of cells, identification of cell populations, and characterization of cellular trajectories and critical points.

Standardization of diethylnitrosamine-induced hepatocellular carcinoma rat model with time based molecular assessment.

This study was intended (1) to develop a robust animal model for hepatocellular carcinoma (HCC) research, in which HCC tumors develop in a background of fibrosis or cirrhosis; and (2) to explore time-dependent regulatory changes in key molecular markers during disease advancement and HCC development. With the aim of establishing such HCC model, male Sprague-Dawley rats were injected with diethylnitrosamine (DEN) at a dose of 30 mg/kg twice a week for 10 weeks then once a week from 12th to 16th weeks. The rats were kept under observation until 18th week. At defined time intervals (2nd, 4th, 12th, and 18th week), serum biomarkers and microscopic components of tissue samples were used to investigate the chronic progression of liver disease, while gene and protein analysis was used to monitor expression patterns during HCC development. DEN-intoxicated rats manifested inflammation at week 4, fibrosis at week 12 and cirrhosis with early HCC tumors at week 18. Molecular analysis revealed that key markers of inflammation (Il-1ß, Il-6, and Tnf-α), fibrosis (Tgf-ß1, Col1α1, Col3α1, and Timp-1), and angiogenesis (Hif1-α and Vegf) were promptly (P ≤ 0.001) up-regulated at week 4, week 12 and week 18, respectively. Oxidative stress (iNos, Cyp2e1, and Sod1) and pro-apoptotic (Bax) markers showed significant upregulation from week 4 to week 12. However, Sod1 and Bax expressions dropped after week 12 and reached a minimum at 18th week. Strikingly, expressions of anti-apoptotic (Bcl-2) and cell proliferation (Pcna, Hgf, and Afp) markers were abruptly increased at week 18. Collectively, we describe an 18-week HCC model in DEN-intoxicated rats that exhibit chronic inflammation, oxidative imbalance, advance fibrosis/cirrhosis, halted apoptosis, and angiogenic sprouting, progressively.

Filling the gap between risk assessment and molecular determinants of tumor onset.

In the past two decades, a ponderous epidemiological literature has causally linked tumor onset to environmental exposure to carcinogens. As consequence, risk assessment studies have been carried out with the aim to identify both predictive models of estimating cancer risks within exposed populations and establishing rules for minimizing hazard when handling carcinogenic compounds. The central assumption of these works is that neoplastic transformation is directly related to the mutational burden of the cell without providing further mechanistic clues to explain increased cancer onset after carcinogen exposure. Nevertheless, in the last few years, a growing number of studies have implemented the traditional models of cancer etiology, proposing that neoplastic transformation is a complex process in which several parameters and crosstalk between tumor and microenvironmental cells must be taken into account and integrated with mutagenesis. In this conceptual framework, the current strategies of risk assessment that are solely based on the 'mutator model' require an urgent update and revision to keep pace with advances in our understanding of cancer biology. We will approach this topic revising the most recent theories on the biological mechanisms involved in tumor formation in order to envision a roadmap leading to a future regulatory framework for a new, protective policy of risk assessment.

CDPath: Cooperative Driver Pathways Discovery Using Integer Linear Programming and Markov Clustering.

Discovering driver pathways is an essential task to understand the pathogenesis of cancer and to design precise treatments for cancer patients. Increasing evidences have been indicating that multiple pathways often function cooperatively in carcinogenesis. In this study, we propose an approach called CDPath to discover cooperative driver pathways. CDPath first uses Integer Linear Programming to explore driver core modules from mutation profiles by enforcing co-occurrence and functional interaction relations between modules, and by maximizing the mutual exclusivity and coverage within modules. Next, to enforce cooperation of pathways and help the follow-up exact cooperative driver pathways discovery, it performs Markov clustering on pathway-pathway interaction network to cluster pathways. After that, it identifies pathways in different modules but in the same clusters as cooperative driver pathways. We apply CDPath on two TCGA datasets: breast cancer (BRCA) and endometrial cancer (UCEC). The results show that CDPath can identify known (i.e., TP53) and potential driver genes (i.e., SPTBN2). In addition, the identified cooperative driver pathways are related with the target cancer, and they are involved with carcinogenesis and several key biological processes. CDPath can uncover more potential biological associations between pathways (over 100 percent) and more cooperative driver pathways (over 200 percent) than competitive approaches. The demo codes of CDPath are available at http://mlda.swu.edu.cn/codes.php?name=CDPath.

A forward selection algorithm to identify mutually exclusive alterations in cancer studies.

Mutual exclusivity analyses provide an effective tool to identify driver genes from passenger genes for cancer studies. Various algorithms have been developed for the detection of mutual exclusivity, but controlling false positive and improving accuracy remain challenging. We propose a forward selection algorithm for identification of mutually exclusive gene sets (FSME) in this paper. The method includes an initial search of seed pair of mutually exclusive (ME) genes and subsequently including more genes into the current ME set. Simulations demonstrated that, compared to recently published approaches (i.e., CoMEt, WExT, and MEGSA), FSME could provide higher precision or recall rate to identify ME gene sets, and had superior control of false positive rates. With application to TCGA real data sets for AML, BRCA, and GBM, we confirmed that FSME can be utilized to discover cancer driver genes.

Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms.

The gene regulatory network (GRN) of human cells encodes mechanisms to ensure proper functioning. However, if this GRN is dysregulated, the cell may enter into a disease state such as cancer. Understanding the GRN as a system can therefore help identify novel mechanisms underlying disease, which can lead to new therapies. To deduce regulatory interactions relevant to cancer, we applied a recent computational inference framework to data from perturbation experiments in squamous carcinoma cell line A431. GRNs were inferred using several methods, and the false discovery rate was controlled by the NestBoot framework. We developed a novel approach to assess the predictiveness of inferred GRNs against validation data, despite the lack of a gold standard. The best GRN was significantly more predictive than the null model, both in cross-validated benchmarks and for an independent dataset of the same genes under a different perturbation design. The inferred GRN captures many known regulatory interactions central to cancer-relevant processes in addition to predicting many novel interactions, some of which were experimentally validated, thus providing mechanistic insights that are useful for future cancer research.

Diagnosis, Risk Stratification, and Treatment of Peripheral T-Cell Lymphomas: Past and Present.

Peripheral T-cell lymphomas represent an evolving class of aggressive T-cell malignancies that are generally refractory to conventional treatments and historically carry a poor prognosis. Recent advances in gene expression profiling have begun to unravel the specific molecular mechanisms of tumorigenesis in these disease processes, allowing for discrete classification schemes that help guide discussions regarding prognosis and therapy options. We outline here a review of the histopathology, epidemiology, clinical features, and treatment strategies currently used in the management of these diseases.

Assessment of micronuclei counts as tumour marker in cervical carcinogenesis: A follow-up study.

OBJECTIVE: Micronuclei counts were performed in cervical smears with low-grade squamous intraepithelial lesions of the cervix (LSIL) to assess its potentiality as tumour marker in cervical carcinogenesis. METHODS: The cases studied were from the ongoing rural cervical cancer screening in west Lucknow, India. Micronuclei counts were performed in the cervical smears of 100 LSIL cases, and the number of cells with micronuclei was defined as micronucleated cells (MNC) and the number of micronuclei per 1000 cells as MNC score. Human papillomavirus (HPV) DNA testing was also done in 100 LSIL cases by GeneNav qPCR test. RESULTS: A high MNC score was found in 20 of the 100 LSIL cases while the counts were low in the remaining 80. Persistence of LSIL was seen in 19 of the 20 LSIL cases with high MNC score while only six cases of the 80 cases with low MNC score showed persistence. The persistence of LSIL was very high in cases with high MNC score. The multiple high-risk HPV types such as 18, 31, 33 and 35 were seen in 12 of the 100 LSIL cases and a high positivity rate was seen in women with high MNC score. The persistence of LSIL was also higher with HPV positivity. CONCLUSION: The study revealed correlation between high MNC score, persistence of LSIL and HPV positivity. Hence, MNC score can prove to be very useful in discriminating high-risk LSIL cases that are less likely to regress and possibly may progress to high-grade squamous intraepithelial lesions or carcinoma.

Diagnostic Power of DNA Methylation Classifiers for Early Detection of Cancer.

DNA methylation-based epigenetic signatures have become valuable cancer biomarkers. We highlight the advantages of liquid biopsy based DNA-methylation profiling for noninvasive diagnosis of early stage cancers and discuss the advanced analytical approaches developed by commercial and academic partnerships.

A toxicogenomic approach for the risk assessment of the food contaminant acetamide.

Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.

Assessment of Pig-a, Micronucleus, and Comet Assay Endpoints in Tg.RasH2 Mice Carcinogenicity Study of Aristolochic Acid I.

A newly developed in vivo Pig-a gene mutation assay displays great potential for integration into genotoxicity tests. To obtain more evidence for application of the Pig-a assay, we integrated this assay, micronucleus test in peripheral blood (MN-pb test) and bone marrow (MN-bm test), as well as a Comet assay into a transgenic RasH2 mice carcinogenicity study. Fourteen male RasH2 mice and five wild-type (WT) mice were treated with a strong mutagen aristolochic acid I at a dose of 5 mg/kg/day for 4 consecutive weeks. Mice recovered in 5 weeks. Peripheral bloods were collected for Pig-a assay, MN-pb test, and Comet assay at several time points, while bone marrow and target organs were harvested for the MN-bm test and pathological diagnosis after mice were euthanized. Finally, 13 of the 14 RasH2 mice developed squamous cell carcinomas in the forestomach, while there were no carcinomas in the WT mice. Pig-a mutant frequencies (MFs) consecutively increased throughout the study to a maximum value of approximately 63-fold more than background. These frequencies were relative to the incidence, size, and malignant degree of tumors. Micronucleated reticulocytes increased from Day 1 to Day 49, before returning to background levels. No positive responses were observed in either the MN-bm test or the Comet assay. Results suggested that, when compared with the other two tests, the Pig-a assay persistently contributed to sustaining MFs, enhanced detection sensitivity due to the accumulation of Pig-a mutations, and demonstrated better predictability for tumorigenicity. Environ. Mol. Mutagen. 61:266-275, 2020. © 2019 Wiley Periodicals, Inc.

RET/PTC Gene Rearrangements in Thyroid Carcinogenesis: Assessment and Clinico-Pathological Correlations.

Rearranged during transfection (RET) is a proto oncogene implicated in thyroid carcinogenesis of papillary type (PTC). The RET proto-oncogene in PTC is constitutively activated by fusion of its tyrosine kinase domain with the 5 ´region of another gene thereby generating chimeric products collectively named RET/PTCs. RET/PTC1 and RET/PTC3 are best characterized among all RET/PTC rearrangements. Kashmir valley has witnessed an alarming increase in thyroid cancer incidence in young women. Therefore, we investigated the occurrence of RET/PTC 1 & 3 rearrangements by semi quantitative and qPCR in thyroid cancer patients (n = 48) of Kashmiri population and interrelated results with various clinicopathological characteristics. We observed that all the RET/PTC rearrangements were confined to PTC cases (10/40). Presence of RET/PTC rearrangement significantly correlated with gender, elevated TSH levels and lymph node metastasis. Overall, our study advocates that RET/PTC3 rearrangement is a frequent event in the carcinogenesis of thyroid gland in Kashmiri population although a study with a larger sample size is needed to get a clear scenario.

Assessment of biochemical recurrence of prostate cancer (Review).

The assessment of the risk of biochemical recurrence (BCR) is critical in the management of males with prostate cancer (PC). Over the past decades, a comprehensive effort has been focusing on improving risk stratification; a variety of models have been constructed using PC­associated pathological features and molecular alterations occurring at the genome, protein and RNA level. Alterations in RNA expression (lncRNA, miRNA and mRNA) constitute the largest proportion of the biomarkers of BCR. In this article, we systemically review RNA­based BCR biomarkers reported in PubMed according to the PRISMA guidelines. Individual miRNAs, mRNAs, lncRNAs and multigene panels, including the commercially available signatures, Oncotype DX and Prolaris, will be discussed; details related to cohort size, hazard ratio and 95% confidence intervals will be provided. Mechanistically, these individual biomarkers affect multiple pathways critical to tumorigenesis and progression, including epithelial­mesenchymal transition (EMT), phosphatase and tensin homolog (PTEN), Wnt, growth factor receptor, cell proliferation, immune checkpoints and others. This variety in the mechanisms involved not only validates their associations with BCR, but also highlights the need for the coverage of multiple pathways in order to effectively stratify the risk of BCR. Updates of novel biomarkers and their mechanistic insights are considered, which suggests new avenues to pursue in the prediction of BCR. Additionally, the management of patients with BCR and the potential utility of the stratification of the risk of BCR in salvage treatment decision making for these patients are briefly covered. Limitations will also be discussed.

Agent-based model of multicellular tumor spheroid evolution including cell metabolism.

Computational models aiming at the spatio-temporal description of cancer evolution are a suitable framework for testing biological hypotheses from experimental data, and generating new ones. Building on our recent work (J. Theor. Biol. 389, 146 (2016)) we develop a 3D agent-based model, capable of tracking hundreds of thousands of interacting cells, over time scales ranging from seconds to years. Cell dynamics is driven by a Monte Carlo solver, incorporating partial differential equations to describe chemical pathways and the activation/repression of "genes", leading to the up- or down-regulation of specific cell markers. Each cell-agent of different kind (stem, cancer, stromal etc.) runs through its cycle, undergoes division, can exit to a dormant, senescent, necrotic state, or apoptosis, according to the inputs from its systemic network. The basic network at this stage describes glucose/oxygen/ATP cycling, and can be readily extended to cancer-cell specific markers. Eventual accumulation of chemical/radiation damage to each cell's DNA is described by a Markov chain of internal states, and by a damage-repair network, whose evolution is linked to the cell systemic network. Aimed at a direct comparison with experiments of tumorsphere growth from stem cells, the present model will allow to quantitatively study the role of transcription factors involved in the reprogramming and variable radio-resistance of simulated cancer-stem cells, evolving in a realistic computer simulation of a growing multicellular tumorsphere.

Mesothelioma: Scientific clues for prevention, diagnosis, and therapy.

Mesothelioma affects mostly older individuals who have been occupationally exposed to asbestos. The global mesothelioma incidence and mortality rates are unknown, because data are not available from developing countries that continue to use large amounts of asbestos. The incidence rate of mesothelioma has decreased in Australia, the United States, and Western Europe, where the use of asbestos was banned or strictly regulated in the 1970s and 1980s, demonstrating the value of these preventive measures. However, in these same countries, the overall number of deaths from mesothelioma has not decreased as the size of the population and the percentage of old people have increased. Moreover, hotspots of mesothelioma may occur when carcinogenic fibers that are present in the environment are disturbed as rural areas are being developed. Novel immunohistochemical and molecular markers have improved the accuracy of diagnosis; however, about 14% (high-resource countries) to 50% (developing countries) of mesothelioma diagnoses are incorrect, resulting in inadequate treatment and complicating epidemiological studies. The discovery that germline BRCA1-asssociated protein 1 (BAP1) mutations cause mesothelioma and other cancers (BAP1 cancer syndrome) elucidated some of the key pathogenic mechanisms, and treatments targeting these molecular mechanisms and/or modulating the immune response are being tested. The role of surgery in pleural mesothelioma is controversial as it is difficult to predict who will benefit from aggressive management, even when local therapies are added to existing or novel systemic treatments. Treatment outcomes are improving, however, for peritoneal mesothelioma. Multidisciplinary international collaboration will be necessary to improve prevention, early detection, and treatment.

A generalized theory of age-dependent carcinogenesis.

The Multi-Stage Model of Carcinogenesis (MMC), developed in the 1950 s-70s, postulated carcinogenesis as a Darwinian somatic selection process. The cellular organization of tissues was then poorly understood, with almost nothing known about cancer drivers and stem cells. The MMC paradigm was later confirmed, and cancer incidence was explained as a function of mutation occurrence. However, the MMC has never been tested for its ability to account for the discrepancies in the number of driver mutations and the organization of the stem cell compartments underlying different cancers that still demonstrate nearly universal age-dependent incidence patterns. Here we demonstrate by Monte Carlo modeling the impact of key somatic evolutionary parameters on the MMC performance, revealing that two additional major mechanisms, aging-dependent somatic selection and life history-dependent evolution of species-specific tumor suppressor mechanisms, need to be incorporated into the MMC to make it capable of generalizing cancer incidence across tissues and species. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Integrative data fusion for comprehensive assessment of a novel CHEK2 variant using combined genomics, imaging, and functional-structural assessments via protein informatics.

The CHEK2 gene and its encoded protein Chk2 have a well-known role in cancers, especially those related to breast cancer mediated through the BRCA1 gene. Additionally Chk2 has a crucial role in DNA repair, apoptosis and the cell cycle, which is why classification of variants of uncertain significance (VUS) is an area highly sought for a better elucidation of the "genomic effect" that results. Because it can often take years before enough clinical data is accumulated, and the costly and expensive functional analysis for individual variants presents a significant hurdle, it is important to identify other tools to help aid in clarifying the impact of specific variants on a protein's function and eventually the patient's health outcome. Here we describe a newly identified CHEK2 variant and analyze with an integrated approach combining genomics (whole exome analysis), clinical study, radiographic imaging, and protein informatics to identify and predict the functional impact of the VUS on the protein's behavior and predicted impact on the related pathways. The observed and analyzed defects in the protein were consistent with the expected clinical effect. Here, we support the use of personalized protein modeling and informatics and further our goal of developing a large-scale protein deposition archive for all protein-level VUS.

Comparison of Coding Transcriptomes in Fibroblasts Irradiated With Low and High LET Proton Beams and Cobalt-60 Photons.

PURPOSE: To identify differential cellular responses after proton and photon irradiation by comparing transcriptomes of primary fibroblasts irradiated with either radiation type. METHODS AND MATERIALS: A panel of primary dermal fibroblast cultures was irradiated with low and higher linear energy transfer (LET) proton beams. Cobalt-60 photon irradiation was used as reference. Dose was delivered in 3 fractions of 3.5 Gy (relative biological effectiveness) using a relative biological effectiveness of 1.1 for proton doses. Cells were harvested 2 hours after the final fraction was delivered, and RNA was purified. RNA sequencing was performed using Illumina NextSeq 500 with high-output kit. The edgeR package in R was used for differential gene expression analysis. RESULTS: Pairwise comparisons of the transcriptomes in the 3 treatment groups showed that there were 84 and 56 differentially expressed genes in the low LET group compared with the Cobalt-60 group and the higher LET group, respectively. The higher LET proton group and the Cobalt-60 group had the most distinct transcriptome profiles, with 725 differentially regulated genes. Differentially regulated canonical pathways and various regulatory factors involved in regulation of biological mechanisms such as inflammation, carcinogenesis, and cell cycle control were identified. CONCLUSIONS: Inflammatory regulators associated with the development of normal tissue complications and malignant transformation factors seem to be differentially regulated by higher LET proton and Cobalt-60 photon irradiation. The reported transcriptome differences could therefore influence the progression of adverse effects and the risk of developing secondary cancers.