Pan-Cancer Interrogation of MUTYH Variants Reveals Biallelic Inactivation and Defective Base Excision Repair Across a Spectrum of Solid Tumors.

PURPOSE: Biallelic germline pathogenic variants of the base excision repair (BER) pathway gene MUTYH predispose to colorectal cancer (CRC) and other cancers. The possible association of heterozygous variants with broader cancer susceptibility remains uncertain. This study investigated the prevalence and consequences of pathogenic MUTYH variants and MUTYH loss of heterozygosity (LOH) in a large pan-cancer analysis. MATERIALS AND METHODS: Data from 354,366 solid tumor biopsies that were sequenced as part of routine clinical care were analyzed using a validated algorithm to distinguish germline from somatic MUTYH variants. RESULTS: Biallelic germline pathogenic MUTYH variants were identified in 119 tissue biopsies. Most were CRCs and showed increased tumor mutational burden (TMB) and a mutational signature consistent with defective BER (COSMIC Signature SBS18). Germline heterozygous pathogenic variants were identified in 5,991 biopsies and their prevalence was modestly elevated in some cancer types. About 12% of these cancers (738 samples: including adrenal gland cancers, pancreatic islet cell tumors, nonglioma CNS tumors, GI stromal tumors, and thyroid cancers) showed somatic LOH for MUTYH, higher rates of chromosome 1p loss (where MUTYH is located), elevated genomic LOH, and higher COSMIC SBS18 signature scores, consistent with BER deficiency. CONCLUSION: This analysis of MUTYH alterations in a large set of solid cancers suggests that in addition to the established role of biallelic pathogenic MUTYH variants in cancer predisposition, a broader range of cancers may possibly arise in MUTYH heterozygotes via a mechanism involving somatic LOH at the MUTYH locus and defective BER. However, the effect is modest and requires confirmation in additional studies before being clinically actionable.

Using in silico tools to predict flame retardant metabolites for more informative exposomics-based approaches.

Introduction: The positive identification of xenobiotics and their metabolites in human biosamples is an integral aspect of exposomics research, yet challenges in compound annotation and identification continue to limit the feasibility of comprehensive identification of total chemical exposure. Nonetheless, the adoption of in silico tools such as metabolite prediction software, QSAR-ready structural conversion workflows, and molecular standards databases can aid in identifying novel compounds in untargeted mass spectral investigations, permitting the assessment of a more expansive pool of compounds for human health hazard. This strategy is particularly applicable when it comes to flame retardant chemicals. The population is ubiquitously exposed to flame retardants, and evidence implicates some of these compounds as developmental neurotoxicants, endocrine disruptors, reproductive toxicants, immunotoxicants, and carcinogens. However, many flame retardants are poorly characterized, have not been linked to a definitive mode of toxic action, and are known to share metabolic breakdown products which may themselves harbor toxicity. As U.S. regulatory bodies begin to pursue a subclass- based risk assessment of organohalogen flame retardants, little consideration has been paid to the role of potentially toxic metabolites, or to expanding the identification of parent flame retardants and their metabolic breakdown products in human biosamples to better inform the human health hazards imposed by these compounds. Methods: The purpose of this study is to utilize publicly available in silico tools to 1) characterize the structural and metabolic fates of proposed flame retardant classes, 2) predict first pass metabolites, 3) ascertain whether metabolic products segregate among parent flame retardant classification patterns, and 4) assess the existing coverage in of these compounds in mass spectral database. Results: We found that flame retardant classes as currently defined by the National Academies of Science, Engineering and Medicine (NASEM) are structurally diverse, with highly variable predicted pharmacokinetic properties and metabolic fates among member compounds. The vast majority of flame retardants (96%) and their predicted metabolites (99%) are not present in spectral databases, posing a challenge for identifying these compounds in human biosamples. However, we also demonstrate the utility of publicly available in silico methods in generating a fit for purpose synthetic spectral library for flame retardants and their metabolites that have yet to be identified in human biosamples. Discussion: In conclusion, exposomics studies making use of fit-for-purpose synthetic spectral databases will better resolve internal exposure and windows of vulnerability associated with complex exposures to flame retardant chemicals and perturbed neurodevelopmental, reproductive, and other associated apical human health impacts.

Transcriptomic Effects of Low-Dose Inorganic Arsenic Exposure on Murine Bone Marrow-Derived Macrophages.

Both tissue-resident macrophages and monocytes recruited from the bone marrow that transform into tissue-resident cells play critical roles in mediating homeostasis as well as in the pathology of inflammatory diseases. Inorganic arsenic (iAs) is the most common drinking water contaminant worldwide and represents a major public health concern. Several diseases that macrophages have implicated involvement in are caused by iAs exposure, including cardiovascular disease, cancer, and increased risk of infectious disease. Therefore, understanding the effects of iAs exposure on macrophages can help us better grasp the full range of arsenic immunotoxicity and better design therapeutic targets for iAs-induced diseases particularly in exposed populations. In this study, we analyzed the transcriptome of low dose iAs-exposed male and female murine bone marrow-derived macrophages (BMDMs) with either M0, M1, or M2 stimulation. We identified differentially expressed genes by iAs in a sex- and stimulation-dependent manner and used bioinformatics tools to predict protein-protein interactions, transcriptional regulatory networks, and associated biological processes. Overall, our data suggest that M1-stimulated, especially female-derived, BMDMs are most susceptible to iAs exposure. Most notably, we observed significant downregulation of major proinflammatory transcription factors, like IRF8, and its downstream targets, as well as genes encoding proteins involved in pattern recognition and antigen presentation, such as TLR7, TLR8, and H2-D1, potentially providing causal insight regarding arsenic's role in perturbing immune responses to infectious diseases. We also observed significant downregulation of genes involved in processes crucial to coordinating a proinflammatory response including leukocyte migration, differentiation, and cytokine and chemokine production and response. Finally, we discovered that 24 X-linked genes were dysregulated in iAs-exposed female stimulation groups compared to only 3 across the iAs-exposed male stimulation groups. These findings elucidate the potential mechanisms underlying the sex-differential iAs-associated immune-related disease risk.

Similarities and Differences in Gene Expression Networks Between the Breast Cancer Cell Line Michigan Cancer Foundation-7 and Invasive Human Breast Cancer Tissues.

Failure to adequately characterize cell lines, and understand the differences between in vitro and in vivo biology, can have serious consequences on the translatability of in vitro scientific studies to human clinical trials. This project focuses on the Michigan Cancer Foundation-7 (MCF-7) cells, a human breast adenocarcinoma cell line that is commonly used for in vitro cancer research, with over 42,000 publications in PubMed. In this study, we explore the key similarities and differences in gene expression networks of MCF-7 cell lines compared to human breast cancer tissues. We used two MCF-7 data sets, one data set collected by ARCHS4 including 1032 samples and one data set from Gene Expression Omnibus GSE50705 with 88 estradiol-treated MCF-7 samples. The human breast invasive ductal carcinoma (BRCA) data set came from The Cancer Genome Atlas, including 1212 breast tissue samples. Weighted Gene Correlation Network Analysis (WGCNA) and functional annotations of the data showed that MCF-7 cells and human breast tissues have only minimal similarity in biological processes, although some fundamental functions, such as cell cycle, are conserved. Scaled connectivity-a network topology metric-also showed drastic differences in the behavior of genes between MCF-7 and BRCA data sets. Finally, we used canSAR to compute ligand-based druggability scores of genes in the data sets, and our results suggested that using MCF-7 to study breast cancer may lead to missing important gene targets. Our comparison of the networks of MCF-7 and human breast cancer highlights the nuances of using MCF-7 to study human breast cancer and can contribute to better experimental design and result interpretation of study involving this cell line.

Complex abdominal wall reconstruction after oncologic resection in a sequalae of giant omphalocele: A case report.

INTRODUCTION: Trauma injuries and oncologic resection are common aetiologies of complex abdominal wall defect. Reconstruction of abdominal wall is an everlasting question for general, paediatric and reconstructive surgeons. The plethora of techniques, bioprosthetic and engineered tissues offer countless possibilities. PRESENTATION OF CASE: The patient was a 28 years old woman, with past history of untreated giant liver omphalocele, admitted for a suspicious hepatic tumefaction without specific clinical signs. The thoraco abdominopelvic CT scan revealed lung metastasis and a bilobed left hepatic tumour. Pre-operative cytologic findings of mild differentiated hepatocellular carcinoma differed from the post-operative findings of hepatoblastoma. The full-thickness abdominal wall defect after a radical resection was reconstructed with a combined acellular dermal matrix, NPWT and skin graft solution. A total epithelization was obtained after 8 weeks follow-up. DISCUSSION: Hepatoblastoma in adult is rare, with no consensus. A radical resection in context of giant untreated omphalocele is an unusual challenge for the surgical team. The pre-operative evaluation, the defect classification and the general conditions of the patient are paramount steps for an appropriate reconstruction. Primary or delayed reconstruction with myocutaneous flap as gold standard, depends on the oncologic management and anticipated post-operative complications. Acellular dermal matrix used for a bridged fascial repair directly on viscera and covered by NPWT, favourited a healthy granulation tissue. The full-thickness defect was then reconstructed with an ADM, NPWT and skin graft instead of an association with the myocutaneous flap. The patient follow-up was emphasized in the hepatoblastoma, but the complications of this reconstruction strategy are unknown. A total epithelization was obtained, the abdominal bulge or hernia is the first complication under surveillance. CONCLUSION: Delayed reconstruction after an oncologic large abdominal wall resection has the advantage to manage post-operative complications and prepare alternative solutions. Acellular dermal matrix was not first designed for skin tissue regeneration, some authors as us experimented the conclusion that this matrix could be used for permanent abdominal wall reconstruction.

Posttraumatic pseudoaneurysm of a superficial branch of the ulnar artery: A case report.

INTRODUCTION: Hand and Upper limb pseudoaneurysms are uncommon and misdiagnosed. The delayed diagnostic and treatment lead to severe vascular and nerve complications. Many mechanisms are involved like acute injury, chronic micro traumatism of the hand, with specific clinic and para clinic signs. PRESENTATION OF CASE: The patient was a 30-years old woman, right-handed, admitted at the emergencies for a penetrating hand injury at the junction of the middle third - distal third of the left forearm, palmar surface, with a good radial and ulnar pulse, without sensory or motor deficit. No vessels injuries observed per operatively. A post-operative worsened pain opposite to the scar with a purplish pulsatile swelling appeared after 20 days of complete wound healing. A needle puncture with a red blood contain, motivated an US Doppler revealing a pseudoaneurysm of a superficial artery of the ulnar artery, surgically resected, without complication. DISCUSSION: Two main mechanisms are involved in upper limb especially hand pseudoaneurysm: penetrating trauma and repeated micro traumatism. Superficial vessels are rarely damaged compare to deep subfascial vessels according to Laplace law. The diagnostic is clinical confirmed with the medical imaging. A pseudoaneurysm is suspected in front of a pulsatile painful tumefaction following a vessel path, with medical imaging in favor. A delayed misdiagnosis lead to a delayed care with severe complications as thrombosis, embolism and vessel. The therapeutic care is mainly surgical. CONCLUSION: This case reports a delayed diagnostic of posttraumatic pseudoaneurysm of a superficial branch of the ulnar artery, managed with a surgical resection.

Author Correction: Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Functionally Enigmatic Genes in Cancer: Using TCGA Data to Map the Limitations of Annotations.

Cancer is a comparatively well-studied disease, yet despite decades of intense focus, we demonstrate here using data from The Cancer Genome Atlas that a substantial number of genes implicated in cancer are relatively poorly studied. Those genes will likely be missed by any data analysis pipeline, such as enrichment analysis, that depends exclusively on annotations for understanding biological function. There is no indication that the amount of research - indicated by number of publications - is correlated with any objective metric of gene significance. Moreover, these genes are not missing at random but reflect that our information about genes is gathered in a biased manner: poorly studied genes are more likely to be primate-specific and less likely to have a Mendelian inheritance pattern, and they tend to cluster in some biological processes and not others. While this likely reflects both technological limitations as well as the fact that well-known genes tend to gather more interest from the research community, in the absence of a concerted effort to study genes in an unbiased way, many genes (and biological processes) will remain opaque.

Weighted Gene Correlation Network Analysis (WGCNA) Reveals Novel Transcription Factors Associated With Bisphenol A Dose-Response.

Despite Bisphenol-A (BPA) being subject to extensive study, a thorough understanding of molecular mechanism remains elusive. Here we show that using weighted gene correlation network analysis (WGCNA), which takes advantage of a graph theoretical approach to understanding correlations amongst genes and grouping genes into modules that typically have co-ordinated biological functions and regulatory mechanisms, that despite some commonality in altered genes, there is minimal overlap between BPA and estrogen in terms of network topology. We confirmed previous findings that ZNF217 and TFAP2C are involved in the estrogen pathway, and are implicated in BPA as well, although for BPA they appear to be active in the absence of canonical estrogen-receptor driven gene expression. Furthermore, our study suggested that PADI4 and RACK7/ZMYNDB8 may be involved in the overlap in gene expression between estradiol and BPA. Lastly, we demonstrated that even at low doses there are unique transcription factors that appear to be driving the biology of BPA, such as SREBF1. Overall, our data is consistent with other reports that BPA leads to subtle gene changes rather than profound aberrations of a conserved estrogen signaling (or other) pathways.

Toxicity, recovery, and resilience in a 3D dopaminergic neuronal in vitro model exposed to rotenone.

To date, most in vitro toxicity testing has focused on acute effects of compounds at high concentrations. This testing strategy does not reflect real-life exposures, which might contribute to long-term disease outcome. We used a 3D-human dopaminergic in vitro LUHMES cell line model to determine whether effects of short-term rotenone exposure (100 nM, 24 h) are permanent or reversible. A decrease in complex I activity, ATP, mitochondrial diameter, and neurite outgrowth were observed acutely. After compound removal, complex I activity was still inhibited; however, ATP levels were increased, cells were electrically active and aggregates restored neurite outgrowth integrity and mitochondrial morphology. We identified significant transcriptomic changes after 24 h which were not present 7 days after wash-out. Our results suggest that testing short-term exposures in vitro may capture many acute effects which cells can overcome, missing adaptive processes, and long-term mechanisms. In addition, to study cellular resilience, cells were re-exposed to rotenone after wash-out and recovery period. Pre-exposed cells maintained higher metabolic activity than controls and presented a different expression pattern in genes previously shown to be altered by rotenone. NEF2L2, ATF4, and EAAC1 were downregulated upon single hit on day 14, but unchanged in pre-exposed aggregates. DAT and CASP3 were only altered after re-exposure to rotenone, while TYMS and MLF1IP were downregulated in both single-exposed and pre-exposed aggregates. In summary, our study shows that a human cell-based 3D model can be used to assess cellular adaptation, resilience, and long-term mechanisms relevant to neurodegenerative research.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17ß estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERß were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

Metabolomic network analysis of estrogen-stimulated MCF-7 cells: a comparison of overrepresentation analysis, quantitative enrichment analysis and pathway analysis versus metabolite network analysis.

In the context of the Human Toxome project, mass spectroscopy-based metabolomics characterization of estrogen-stimulated MCF-7 cells was studied in order to support the untargeted deduction of pathways of toxicity. A targeted and untargeted approach using overrepresentation analysis (ORA), quantitative enrichment analysis (QEA) and pathway analysis (PA) and a metabolite network approach were compared. Any untargeted approach necessarily has some noise in the data owing to artifacts, outliers and misidentified metabolites. Depending on the chemical analytical choices (sample extraction, chromatography, instrument and settings, etc.), only a partial representation of all metabolites will be achieved, biased by both the analytical methods and the database used to identify the metabolites. Here, we show on the one hand that using a data analysis approach based exclusively on pathway annotations has the potential to miss much that is of interest and, in the case of misidentified metabolites, can produce perturbed pathways that are statistically significant yet uninformative for the biological sample at hand. On the other hand, a targeted approach, by narrowing its focus and minimizing (but not eliminating) misidentifications, renders the likelihood of a spurious pathway much smaller, but the limited number of metabolites also makes statistical significance harder to achieve. To avoid an analysis dependent on pathways, we built a de novo network using all metabolites that were different at 24 h with and without estrogen with a p value <0.01 (53) in the STITCH database, which links metabolites based on known reactions in the main metabolic network pathways but also based on experimental evidence and text mining. The resulting network contained a "connected component" of 43 metabolites and helped identify non-endogenous metabolites as well as pathways not visible by annotation-based approaches. Moreover, the most highly connected metabolites (energy metabolites such as pyruvate and alpha-ketoglutarate, as well as amino acids) showed only a modest change between proliferation with and without estrogen. Here, we demonstrate that estrogen has subtle but potentially phenotypically important alterations in the acyl-carnitine fatty acids, acetyl-putrescine and succinoadenosine, in addition to likely subtle changes in key energy metabolites that, however, could not be verified consistently given the technical limitations of this approach. Finally, we show that a network-based approach combined with text mining identifies pathways that would otherwise neither be considered statistically significant on their own nor be identified via ORA, QEA, or PA.

Genetic variability in a frozen batch of MCF-7 cells invisible in routine authentication affecting cell function.

Common recommendations for cell line authentication, annotation and quality control fall short addressing genetic heterogeneity. Within the Human Toxome Project, we demonstrate that there can be marked cellular and phenotypic heterogeneity in a single batch of the human breast adenocarcinoma cell line MCF-7 obtained directly from a cell bank that are invisible with the usual cell authentication by short tandem repeat (STR) markers. STR profiling just fulfills the purpose of authentication testing, which is to detect significant cross-contamination and cell line misidentification. Heterogeneity needs to be examined using additional methods. This heterogeneity can have serious consequences for reproducibility of experiments as shown by morphology, estrogenic growth dose-response, whole genome gene expression and untargeted mass-spectroscopy metabolomics for MCF-7 cells. Using Comparative Genomic Hybridization (CGH), differences were traced back to genetic heterogeneity already in the cells from the original frozen vials from the same ATCC lot, however, STR markers did not differ from ATCC reference for any sample. These findings underscore the need for additional quality assurance in Good Cell Culture Practice and cell characterization, especially using other methods such as CGH to reveal possible genomic heterogeneity and genetic drifts within cell lines.

The human toxome project.

The Human Toxome Project, funded as an NIH Transformative Research grant 2011-2016, is focused on developing the concepts and the means for deducing, validating and sharing molecular pathways of toxicity (PoT). Using the test case of estrogenic endocrine disruption, the responses of MCF-7 human breast cancer cells are being phenotyped by transcriptomics and mass-spectroscopy-based metabolomics. The bioinformatics tools for PoT deduction represent a core deliverable. A number of challenges for quality and standardization of cell systems, omics technologies and bioinformatics are being addressed. In parallel, concepts for annotation, validation and sharing of PoT information, as well as their link to adverse outcomes, are being developed. A reasonably comprehensive public database of PoT, the Human Toxome Knowledge-base, could become a point of reference for toxicological research and regulatory test strategies.

HistoneHits: a database for histone mutations and their phenotypes.

Histones are the basic protein components of nucleosomes. They are among the most conserved proteins and are subject to a plethora of post-translational modifications. Specific histone residues are important in establishing chromatin structure, regulating gene expression and silencing, and responding to DNA damage. Here we present HistoneHits, a database of phenotypes for systematic collections of histone mutants. This database combines assay results (phenotypes) with information about sequences, structures, post-translational modifications, and evolutionary conservation. The web interface presents the information through dynamic tables and figures. It calculates the availability of data for specific mutants and for nucleosome surfaces. The database currently includes 42 assays on 677 mutants multiply covering 405 of the 498 residues across yeast histones H3, H4, H2A, and H2B. We also provide an interface with an extensible controlled vocabulary for research groups to submit new data. Preliminary analyses confirm that mutations at highly conserved residues and modifiable residues are more likely to generate phenotypes. Buried residues and residues on the lateral surface tend to generate more phenotypes, while tail residues generate significantly fewer phenotypes than other residues. Yeast mutants are cross referenced with known human histone variants, identifying a position where a yeast mutant causes loss of ribosomal silencing and a human variant increases breast cancer susceptibility. All data sets are freely available for download.