A resource for cell line authentication, annotation and quality control

Metabolic Reprogramming of Macrophages Exposed to Silk, Poly(lactic-co-glycolic acid), and Silica Nanoparticles

Monitoring macrophage metabolism in response to nanoparticle exposure provides new insights into biological outcomes, such as inflammation or toxicity, and supports the design of tailored nanomedicines. This paper describes the metabolic signature of macrophages exposed to nanoparticles ranging in diameter from 100 to 125 nm and made from silk, poly(lactic-co-glycolic acid) or silica. Nanoparticles of this size and type are currently at various stages of preclinical and clinical development for drug delivery applications. ¹ H NMR analysis of cell extracts and culture media is used to quantify the changes in the intracellular and extracellular metabolomes of macrophages in response to nanoparticle exposure. Increased glycolytic activity, an altered tricarboxylic acid cycle, and reduced ATP generation are consistent with a proinflammatory phenotype. Furthermore, amino acids possibly arising from autophagy, the creatine kinase/phosphocreatine system, and a few osmolytes and antioxidants emerge as important players in the metabolic reprogramming of macrophages exposed to nanoparticles. This metabolic signature is a common response to all nanoparticles tested; however, the direction and magnitude of some variations are clearly nanoparticle specific, indicating material-induced biological specificity. Overall, metabolic reprogramming of macrophages can be achieved with nanoparticle treatments, modulated through the choice of the material, and monitored using ¹ H NMR metabolomics.

The impact of fraudulent and irreproducible data to the translational research crisis - solutions and implementation

One of the aims of basic neuroscience research is ultimately the development of therapeutics to cure diseases. Funders granting money to research institutions increasingly express interest into how their financial resources are used and look for successful translation in clinical practice. Disappointingly, many findings that started out promising in basic research projects and phase I trials did not live up to the promise of therapeutic efficacy in later phase II or III trials. An inordinately high amount of time and money is thus spent on research that does not always have the required human impact. Potential reasons for these problems are numerous. Although research misconduct occurs and contributes to this shortcoming, it is not the only important factor. Frequently, basic science results turn out to be irreproducible. Irreproducibility, outside of malfeasance, is multifactorial and can include poor experimental design, conduct, statistical analysis, reporting standards, and conceptual flaws. Further confounding problems include an insufficient transferability of animal to human physiology, as well as intersubject group variability, for example, sexual dimorphisms. While the causes of poor data reproducibility are therefore numerous, equally there are many groups that can contribute to improvements in how basic science is reported. Here, we will review how the Journal of Neurochemistry can contribute to increasing the value of preclinical and translational research. Despite a vast amount of very promising basic research findings, these failed to successfully translate into the clinical practice so far. The reasons for this 'data reproducibility crisis' are numerous, for example, rooting in insufficient experimental design, conceptual flaws, incorrect statistical planning and evaluation, incomplete model system that do not adequately reproduce the human physiology, and further reasons discussed in this Review with the aim to present practical solutions that can be implemented by researchers, journals editors, and reviewers. We will also explain measures the Journal of Neurochemistry have implemented to overcome these issues and weaknesses in preclinical research. These includes adherence to the ARRIVE ( www.nc3rs.org) guidelines, NINDS standards (doi: 10.1038/nature11556), and The Transparency and Openness Promotion Guidelines (TOP) Committee guidelines (https://cos.io/top/#TOP). This article is part of the 60th Anniversary special issue.

Flatbed epi relief-contrast cellular monitoring system for stable cell culture

Consistent cell preparation is a fundamental preliminary step for understanding complex cellular mechanisms in various cell-based research fields, including basic cell biology, cancer research, and tissue engineering. However, certain elusive factors, such as cellular de-differentiation and contamination with mycoplasma or other types of cells, have compromised the reproducibility and reliability of cell-based approaches. Here, we propose an epi relief-contrast cellular monitoring system (eRC-CMS) that allows images of cells in a typical culture plate to be acquired, stored, and analysed for daily cell quality control. Due to its full flatbed nature and automated system, cells placed at any location on the stage can be analysed without special attention. Using this system, changes in the size, circularity, and proliferation of endothelial cells in subculture were recorded. Analyses of images of ~9,930,000 individual cells revealed that the growth activity and cell circularity in subcultures were closely correlated with their angiogenic activity in a subsequent hydrogel assay, demonstrating that eRC-CMS is useful for assessing cell quality in advance. We further demonstrated that eRC-CMS was feasible for the imaging of neurite elongation and spheroid formation. This system may provide a robust and versatile approach for daily cell preparation to facilitate reliable and reproducible cell-based studies.

MYB fusions and CD markers as tools for authentication and purification of cancer stem cells from salivary adenoid cystic carcinoma

Cancer stem cells (CSC) are considered the major cause of aggressive tumor behavior, recurrence, metastases, and resistance to radiation, making them an attractive therapeutic target. However, isolation of CSC from tumor tissue and their characterization are challenging due to uncertainty about their molecular markers and conditions for their propagation. Adenoid cystic carcinoma (ACC), which arises predominantly in the salivary glands, is a slow-growing but relentless tumor that frequently invades nerves and metastasizes. New effective treatment approaches for ACC have not emerged over the last 40years. Previously, based on a highly conserved SOX10 gene signature that we identified in the majority of ACC tumors, we suggested the existence in ACC of SOX10+ cells with neural stem properties and corroborated this hypothesis via isolation from ACC tissue a novel population of CSC, termed ACC-CSC. These cells activated NOTCH1 signaling and co-expressed SOX10 and other ACC-intrinsic neural crest stem cell markers with CD133, a CSC cell surface marker, suggesting that ACC is driven by a previously uncharacterized population of SOX10+/CD133+ cells with neural stem cell properties. Here, we authenticated ACC identity of our primary cultures by demonstrating that most of them harbor MYB-NFIB fusions, which are found in 86% of ACC. We demonstrated using CyTOF, a novel mass cytometry technology, that these cells express high β-catenin and STAT3 levels and are marked by CD24 and CD44. Finally, to streamline development of ACC cell lines, we developed RT-PCR tests for distinguishing mouse and human cells and used immunomagnetic cell sorting to eliminate mouse cells from long-term cell cultures. Overall, this study describes a new population of CSC that activates signaling pathways associated with poor prognosis, validates their ACC identity, and optimizes approaches that can be used for purification of ACC-CSC and generation of cell lines.

Reproducibility2020: Progress and priorities

The preclinical research process is a cycle of idea generation, experimentation, and reporting of results. The biomedical research community relies on the reproducibility of published discoveries to create new lines of research and to translate research findings into therapeutic applications. Since 2012, when scientists from Amgen reported that they were able to reproduce only 6 of 53 "landmark" preclinical studies, the biomedical research community began discussing the scale of the reproducibility problem and developing initiatives to address critical challenges. Global Biological Standards Institute (GBSI) released the "Case for Standards" in 2013, one of the first comprehensive reports to address the rising concern of irreproducible biomedical research. Further attention was drawn to issues that limit scientific self-correction, including reporting and publication bias, underpowered studies, lack of open access to methods and data, and lack of clearly defined standards and guidelines in areas such as reagent validation. To evaluate the progress made towards reproducibility since 2013, GBSI identified and examined initiatives designed to advance quality and reproducibility. Through this process, we identified key roles for funders, journals, researchers and other stakeholders and recommended actions for future progress. This paper describes our findings and conclusions.

Establishing a reference dataset for the authentication of spinal muscular atrophy cell lines using STR profiling and digital PCR

Fibroblasts and lymphoblastoid cell lines (LCLs) derived from individuals with spinal muscular atrophy (SMA) have been and continue to be essential for translational SMA research. Authentication of cell lines helps ensure reproducibility and rigor in biomedical research. This quality control measure identifies mislabeling or cross-contamination of cell lines and prevents misinterpretation of data. Unfortunately, authentication of SMA cell lines used in various studies has not been possible because of a lack of a reference. In this study, we provide said reference so that SMA cell lines can be subsequently authenticated. We use short tandem repeat (STR) profiling and digital PCR (dPCR), which quantifies SMN1 and SMN2 copy numbers, to generate molecular identity codes for fibroblasts and LCLs that are commonly used in SMA research. Using these molecular identity codes, we clarify the familial relationships within a set of fibroblasts commonly used in SMA research. This study presents the first cell line reference set for the SMA research community and demonstrates its usefulness for re-identification and authentication of lines commonly used as in vitro models for future studies.

Widespread Use of Misidentified Cell Line KB (HeLa): Incorrect Attribution and Its Impact Revealed through Mining the Scientific Literature

Continuous cell lines are widely used, but can result in invalid, irreproducible research data. Cell line misidentification is a common problem that can be detected by authentication testing; however, misidentified cell lines continue to be used in publications. Here we explore the impact of one misidentified cell line, KB (HeLa), on the scientific literature. We identified 574 articles between 2000 and 2014 that provided an incorrect attribution for KB, in accordance with its false identity as oral epidermoid carcinoma, but only 57 articles that provided a correct attribution for KB, as HeLa or cervical adenocarcinoma. Statistical analysis of 57 correct and 171 incorrect articles showed that the number of citations to these articles increased over time. Content analysis of 200 citing articles showed there was a tendency to describe the cell line in accordance with the description in the cited paper. Analysis of journal impact factor showed no significant difference between correct and incorrect groups. Articles using KB or citing that usage were most frequently published in the subject areas of pharmacology, pharmacy, oncology, and medicinal chemistry. These findings are important for science policy and support the need for journals to require authentication testing as a condition of publication. Cancer Res; 77(11); 2784-8. ©2017 AACR.

The need for a worldwide consensus for cell line authentication: Experience implementing a mandatory requirement at the International Journal of Cancer

Cell lines are used in life science research worldwide as biological surrogates. All cell lines are subject to major limitations when used as research tools, including (i) cross-contamination with other cells cultured in the same laboratory environment and (ii) evolution in vitro that renders a given cell line inappropriate as a surrogate for a specific biological hypothesis. There is ample evidence that cross-contamination or phenotypic drift of cells in culture can generate irreproducible or misleading data. A small number of scientific journals—the International Journal of Cancer being at the forefront—and funding agencies have recently moved forward to ask for obligatory cell line authentication data. The history of implementing such rules by the International Journal of Cancer exemplifies the difficulties encountered when installing mandatory quality measures in life sciences.

A novel RNA sequencing data analysis method for cell line authentication

We have developed a novel analysis method that can interrogate the authenticity of biological samples used for generation of transcriptome profiles in public data repositories. The method uses RNA sequencing information to reveal mutations in expressed transcripts and subsequently confirms the identity of analysed cells by comparison with publicly available cell-specific mutational profiles. Cell lines constitute key model systems widely used within cancer research, but their identity needs to be confirmed in order to minimise the influence of cell contaminations and genetic drift on the analysis. Using both public and novel data, we demonstrate the use of RNA-sequencing data analysis for cell line authentication by examining the validity of COLO205, DLD1, HCT15, HCT116, HKE3, HT29 and RKO colorectal cancer cell lines. We successfully authenticate the studied cell lines and validate previous reports indicating that DLD1 and HCT15 are synonymous. We also show that the analysed HKE3 cells harbour an unexpected KRAS-G13D mutation and confirm that this cell line is a genuine KRAS dosage mutant, rather than a true isogenic derivative of HCT116 expressing only the wild type KRAS. This authentication method could be used to revisit the numerous cell line based RNA sequencing experiments available in public data repositories, analyse new experiments where whole genome sequencing is not available, as well as facilitate comparisons of data from different experiments, platforms and laboratories.

Reproducibility Issues: Avoiding Pitfalls in Animal Inflammation Models

In light of an enhanced awareness of ethical questions and ever increasing costs when working with animals in biomedical research, there is a dedicated and sometimes fierce debate concerning the (lack of) reproducibility of animal models and their relevance for human inflammatory diseases. Despite evident advancements in searching for alternatives, that is, replacing, reducing, and refining animal experiments-the three R's of Russel and Burch (1959)-understanding the complex interactions of the cells of the immune system, the nervous system and the affected tissue/organ during inflammation critically relies on in vivo models. Consequently, scientific advancement and ultimately novel therapeutic interventions depend on improving the reproducibility of animal inflammation models. As a prelude to the remaining hands-on protocols described in this volume, here, we summarize potential pitfalls of preclinical animal research and provide resources and background reading on how to avoid them.

Prior knowledge transfer across transcriptional data sets and technologies using compositional statistics yields new mislabelled ovarian cell line

Here, we describe gene expression compositional assignment (GECA), a powerful, yet simple method based on compositional statistics that can validate the transfer of prior knowledge, such as gene lists, into independent data sets, platforms and technologies. Transcriptional profiling has been used to derive gene lists that stratify patients into prognostic molecular subgroups and assess biomarker performance in the pre-clinical setting. Archived public data sets are an invaluable resource for subsequent in silico validation, though their use can lead to data integration issues. We show that GECA can be used without the need for normalising expression levels between data sets and can outperform rank-based correlation methods. To validate GECA, we demonstrate its success in the cross-platform transfer of gene lists in different domains including: bladder cancer staging, tumour site of origin and mislabelled cell lines. We also show its effectiveness in transferring an epithelial ovarian cancer prognostic gene signature across technologies, from a microarray to a next-generation sequencing setting. In a final case study, we predict the tumour site of origin and histopathology of epithelial ovarian cancer cell lines. In particular, we identify and validate the commonly-used cell line OVCAR-5 as non-ovarian, being gastrointestinal in origin. GECA is available as an open-source R package.

Revisiting inconsistency in large pharmacogenomic studies

In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.

Revisiting inconsistency in large pharmacogenomic studies

In 2013, we published a comparative analysis of mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. We present a new analysis using these expanded data, where we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should be compared across cell lines, and that the software analysis tools provided should have been easier to run, particularly as the GDSC and CCLE released additional data. Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. Using new statistics to assess data consistency allowed identification of two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs. Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.

Revisiting inconsistency in large pharmacogenomic studies

In 2013, we published a comparative analysis mutation and gene expression profiles and drug sensitivity measurements for 15 drugs characterized in the 471 cancer cell lines screened in the Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line Encyclopedia (CCLE). While we found good concordance in gene expression profiles, there was substantial inconsistency in the drug responses reported by the GDSC and CCLE projects. We received extensive feedback on the comparisons that we performed. This feedback, along with the release of new data, prompted us to revisit our initial analysis. Here we present a new analysis using these expanded data in which we address the most significant suggestions for improvements on our published analysis - that targeted therapies and broad cytotoxic drugs should have been treated differently in assessing consistency, that consistency of both molecular profiles and drug sensitivity measurements should both be compared across cell lines, and that the software analysis tools we provided should have been easier to run, particularly as the GDSC and CCLE released additional data.             Our re-analysis supports our previous finding that gene expression data are significantly more consistent than drug sensitivity measurements. The use of new statistics to assess data consistency allowed us to identify two broad effect drugs and three targeted drugs with moderate to good consistency in drug sensitivity data between GDSC and CCLE. For three other targeted drugs, there were not enough sensitive cell lines to assess the consistency of the pharmacological profiles. We found evidence of inconsistencies in pharmacological phenotypes for the remaining eight drugs.             Overall, our findings suggest that the drug sensitivity data in GDSC and CCLE continue to present challenges for robust biomarker discovery. This re-analysis provides additional support for the argument that experimental standardization and validation of pharmacogenomic response will be necessary to advance the broad use of large pharmacogenomic screens.

"Cell identity" crisis: Another call for immediate action

Comment on: J. Wei, J. Zhang, Y. Si, M. Kanada, Z. Zhang, S. Terakawa, H. Watanabe, Blockage of LMP1-modulated store-operated Ca(2+) entry reduces metastatic potential in nasopharyngeal carcinoma cell, Cancer Lett. 360 (2015) 234-244. doi:10.1016/j.canlet.2015.02.032.

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.

First Proposal of Minimum Information About a Cellular Assay for Regenerative Medicine

: Advances in stem cell research have triggered scores of studies in regenerative medicine in a large number of institutions and companies around the world. However, reproducibility and data exchange among laboratories or cell banks are constrained by the lack of a standardized format for experiments. To enhance information flow in stem cell and derivative cell research, here we propose a minimum information standard to describe cellular assay data to facilitate practical regenerative medicine. Based on the existing Minimum Information About a Cellular Assay, we developed Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), which allows for the description of advanced cellular experiments with defined taxonomy of human cell types. By using controlled terms, such as ontologies, MIACARM will provide a platform for cellular assay data exchange among cell banks or registries that have been established at more than 20 sites in the world.

SIGNIFICANCE

Currently, there are more than 20 human cell information storage sites around the world. However, reproducibility and data exchange among different laboratories or cell information providers are usually inadequate or nonexistent because of the lack of a standardized format for experiments. This study, which is the fruit of collaborative work by scientists at stem cell banks and cellular information registries worldwide, including those in the U.S., the U.K., Europe, and Japan, proposes new minimum information guidelines, Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM), for cellular assay data deposition. MIACARM is intended to promote data exchange and facilitation of practical regenerative medicine.

Reproducible pharmacogenomic profiling of cancer cell line panels

The use of large-scale genomic and drug response screening of cancer cell lines depends crucially on the reproducibility of results. Here we consider two previously published screens, plus a later critique of these studies. Using independent data, we show that consistency is achievable, and provide a systematic description of the best laboratory and analysis practices for future studies.

Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response

The utility of tumor-derived cell lines is dependent on their ability to recapitulate underlying genomic aberrations and primary tumor biology. Here, we sequenced the exomes of 25 bladder cancer (BCa) cell lines and compared mutations, copy number alterations (CNAs), gene expression and drug response to BCa patient profiles in The Cancer Genome Atlas (TCGA). We observed a mutation pattern associated with altered CpGs and APOBEC-family cytosine deaminases similar to mutation signatures derived from somatic alterations in muscle-invasive (MI) primary tumors, highlighting a major mechanism(s) contributing to cancer-associated alterations in the BCa cell line exomes. Non-silent sequence alterations were confirmed in 76 cancer-associated genes, including mutations that likely activate oncogenes TERT and PIK3CA, and alter chromatin-associated proteins (MLL3, ARID1A, CHD6 and KDM6A) and established BCa genes (TP53, RB1, CDKN2A and TSC1). We identified alterations in signaling pathways and proteins with related functions, including the PI3K/mTOR pathway, altered in 60% of lines; BRCA DNA repair, 44% and SYNE1–SYNE2, 60%. Homozygous deletions of chromosome 9p21 are known to target the cell cycle regulators CDKN2A and CDKN2B. This loci was commonly lost in BCa cell lines and we show the deletions extended to the polyamine enzyme methylthioadenosine (MTA) phosphorylase (MTAP) in 36% of lines, transcription factor DMRTA1 (27%) and antiviral interferon epsilon (IFNE, 19%). Overall, the BCa cell line genomic aberrations were concordant with those found in BCa patient tumors. We used gene expression and copy number data to infer pathway activities for cell lines, then used the inferred pathway activities to build a predictive model of cisplatin response. When applied to platinum-treated patients gathered from TCGA, the model predicted treatment-specific response. Together, these data and analysis represent a valuable community resource to model basic tumor biology and to study the pharmacogenomics of BCa.

Standards for Cell Line Authentication and Beyond

Different genomic technologies have been applied to cell line authentication, but only one method (short tandem repeat [STR] profiling) has been the subject of a comprehensive and definitive standard (ASN-0002). Here we discuss the power of this document and why standards such as this are so critical for establishing the consensus technical criteria and practices that can enable progress in the fields of research that use cell lines. We also examine other methods that could be used for authentication and discuss how a combination of methods could be used in a holistic fashion to assess various critical aspects of the quality of cell lines.

NF-κB oscillations translate into functionally related patterns of gene expression

Several transcription factors (TFs) oscillate, periodically relocating between the cytoplasm and the nucleus. NF-κB, which plays key roles in inflammation and cancer, displays oscillations whose biological advantage remains unclear. Recent work indicated that NF-κB displays sustained oscillations that can be entrained, that is, reach a persistent synchronized state through small periodic perturbations. We show here that for our GFP-p65 knock-in cells NF-κB behaves as a damped oscillator able to synchronize to a variety of periodic external perturbations with no memory. We imposed synchronous dynamics to prove that transcription of NF-κB-controlled genes also oscillates, but mature transcript levels follow three distinct patterns. Two sets of transcripts accumulate fast or slowly, respectively. Another set, comprising chemokine and chemokine receptor mRNAs, oscillates and resets at each new stimulus, with no memory of the past. We propose that TF oscillatory dynamics is a means of segmenting time to provide renewing opportunity windows for decision.

Phosphorylation and linear ubiquitin direct A20 inhibition of inflammation

Inactivation of the TNFAIP3 gene, encoding the A20 protein, is associated with critical inflammatory diseases including multiple sclerosis, rheumatoid arthritis and Crohn's disease. However, the role of A20 in attenuating inflammatory signalling is unclear owing to paradoxical in vitro and in vivo findings. Here we utilize genetically engineered mice bearing mutations in the A20 ovarian tumour (OTU)-type deubiquitinase domain or in the zinc finger-4 (ZnF4) ubiquitin-binding motif to investigate these discrepancies. We find that phosphorylation of A20 promotes cleavage of Lys63-linked polyubiquitin chains by the OTU domain and enhances ZnF4-mediated substrate ubiquitination. Additionally, levels of linear ubiquitination dictate whether A20-deficient cells die in response to tumour necrosis factor. Mechanistically, linear ubiquitin chains preserve the architecture of the TNFR1 signalling complex by blocking A20-mediated disassembly of Lys63-linked polyubiquitin scaffolds. Collectively, our studies reveal molecular mechanisms whereby A20 deubiquitinase activity and ubiquitin binding, linear ubiquitination, and cellular kinases cooperate to regulate inflammation and cell death.

Spontaneous ATM Gene Reversion in A-T iPSC to Produce an Isogenic Cell Line

A spontaneously reverted iPSC line was identified from an A-T subject with heterozygous ATM truncation mutations. The reverted iPSC line expressed ATM protein and was capable of radiation-induced phosphorylation of CHK2 and H2A.X. Genome-wide SNP analysis confirmed a match to source T cells and also to a distinct, non-reverted iPSC line from the same subject. Rearranged T cell receptor sequences predict that the iPSC culture originated as several independently reprogrammed cells that resolved into a single major clone, suggesting that gene correction likely occurred early in the reprogramming process. Gene expression analysis comparing ATM(-/-) iPSC lines to unrelated ATM(+/-) cells identifies a large number of differences, but comparing only the isogenic pair of A-T iPSC lines reveals that the primary pathway affected by loss of ATM is a diminished expression of p53-related mRNAs. Gene reversion in culture, although likely a rare event, provided a novel, reverted cell line for studying ATM function.

Reproducibility blues

Research findings advance science only if they are significant, reliable and reproducible. Scientists and journals must publish robust data in a way that renders it optimally reproducible. Reproducibility has to be incentivized and supported by the research infrastructure but without dampening innovation.

Primary cilia found on HeLa and other cancer cells

For many years now, researchers have known of a sensory appendage on the surface of most differentiated cell types called primary cilium. Primary cilia are both chemo- and mechano-sensory in function and have an obvious role in cell cycle control. Because of this, it has been thought that primary cilia are not found on rapidly proliferating cells, for example, cancer cells. Here we report using immunofluorescent staining for the ciliary protein Arl13b that primary cilia are frequently found on HeLa (human epithelial adenocarcinoma) and other cancer cell lines such as MG63 (human osteosarcoma) commonly used for cell culture studies and that the ciliated population is significantly higher (ave. 28.6% and 46.5%, respectively in starved and 15.7-18.6% in un-starved cells) than previously anticipated. Our finding impacts the current perception of primary cilia formed in highly proliferative cells.

Hallmarks of pluripotency

Stem cells self-renew and generate specialized progeny through differentiation, but vary in the range of cells and tissues they generate, a property called developmental potency. Pluripotent stem cells produce all cells of an organism, while multipotent or unipotent stem cells regenerate only specific lineages or tissues. Defining stem-cell potency relies upon functional assays and diagnostic transcriptional, epigenetic and metabolic states. Here we describe functional and molecular hallmarks of pluripotent stem cells, propose a checklist for their evaluation, and illustrate how forensic genomics can validate their provenance.

Public data and open source tools for multi-assay genomic investigation of disease

Molecular interrogation of a biological sample through DNA sequencing, RNA and microRNA profiling, proteomics and other assays, has the potential to provide a systems level approach to predicting treatment response and disease progression, and to developing precision therapies. Large publicly funded projects have generated extensive and freely available multi-assay data resources; however, bioinformatic and statistical methods for the analysis of such experiments are still nascent. We review multi-assay genomic data resources in the areas of clinical oncology, pharmacogenomics and other perturbation experiments, population genomics and regulatory genomics and other areas, and tools for data acquisition. Finally, we review bioinformatic tools that are explicitly geared toward integrative genomic data visualization and analysis. This review provides starting points for accessing publicly available data and tools to support development of needed integrative methods.

Effectiveness of a 95 SNP panel for the screening of breed label fraud in the Chinese meat market

Breed assignment has proved to be useful to control meat trade and protect the value of special productions. Meat-related frauds have been detected in China; therefore, 95 SNPs selected from the ISAG core panel were evaluated to develop an automated and technologically updated tool to screen breed label fraud in the Chinese meat market. A total of 271 animals from four Chinese yellow cattle (CYC) populations, six Bos taurus breeds, two Bos indicus and one composite were used. The allocation test distinguished European, Japanese and Zebu breeds, and two Chinese genetic components. It correctly allocated Japanese Black, Zebu and British breeds in 100, 90 and 89% of samples, respectively. CYC evidenced the Zebu, Holstein and Limousin introgression. The test did not detect CYC components in any of the 25 samples from Argentinean butchers. The method could be useful to certify Angus, Hereford and Japanese Black meat, but a modification in the panel would be needed to differentiate other breeds.

Tumor-Derived Cell Lines as Molecular Models of Cancer Pharmacogenomics

Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic alterations. Often, these changes underlie cancer development, progression, and drug resistance, so the utility of model systems rests on their ability to recapitulate the genomic aberrations observed in primary tumors. Tumor-derived cell lines have long been used to study the underlying biologic processes in cancer, as well as screening platforms for discovering and evaluating the efficacy of anticancer therapeutics. Multiple -omic measurements across more than a thousand cancer cell lines have been produced following advances in high-throughput technologies and multigroup collaborative projects. These data complement the large, international cancer genomic sequencing efforts to characterize patient tumors, such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Given the scope and scale of data that have been generated, researchers are now in a position to evaluate the similarities and differences that exist in genomic features between cell lines and patient samples. As pharmacogenomics models, cell lines offer the advantages of being easily grown, relatively inexpensive, and amenable to high-throughput testing of therapeutic agents. Data generated from cell lines can then be used to link cellular drug response to genomic features, where the ultimate goal is to build predictive signatures of patient outcome. This review highlights the recent work that has compared -omic profiles of cell lines with primary tumors, and discusses the advantages and disadvantages of cancer cell lines as pharmacogenomic models of anticancer therapies.

Unknown unknowns in biomedical research: does an inability to deal with ambiguity contribute to issues of irreproducibility?

The credibility and consequent sustainability of the biomedical research "ecosystem" is in jeopardy, in part due to an inability to reproduce data from the peer-reviewed literature. Despite obvious and relatively inexpensive solutions to improve reproducibility-ensuring that experimental reagents, specifically cancer cell lines and antibodies, are authenticated/validated before use and that best practices in statistical usage are incorporated into the design, analysis, and reporting of experiments-these are routinely ignored, a reflection of hubris and a comfort with the status quo on the part of many investigators. New guidelines for the peer review of publications and grant applications introduced in the past year, while well-intended, lack the necessary consequences, e.g., denial of funding, that would result in sustained improvements when scientific rigor is lacking and/or transparency is, at best, opaque. An additional factor contributing to irreproducibility is a reductionist mindset that prioritizes certainty in research outcomes over the ambiguity intrinsic to biological systems that is often reflected in "unknown unknowns". This has resulted in a tendency towards codifying "rules" that can provide "yes-no" outcomes that represent a poor substitute for the intellectual challenge and skepticism that leads to an awareness and consideration of "unknown unknowns". When acknowledged as potential causes of unexpected experimental outcomes, these can often transition into the "knowns" that facilitate positive, disruptive innovation in biomedical research like the human microbiome. Changes in investigator mindset, both in terms of validating reagents and embracing ambiguity, are necessary to aid in reducing issues with reproducibility.

Activity, assay and target data curation and quality in the ChEMBL database

The emergence of a number of publicly available bioactivity databases, such as ChEMBL, PubChem BioAssay and BindingDB, has raised awareness about the topics of data curation, quality and integrity. Here we provide an overview and discussion of the current and future approaches to activity, assay and target data curation of the ChEMBL database. This curation process involves several manual and automated steps and aims to: (1) maximise data accessibility and comparability; (2) improve data integrity and flag outliers, ambiguities and potential errors; and (3) add further curated annotations and mappings thus increasing the usefulness and accuracy of the ChEMBL data for all users and modellers in particular. Issues related to activity, assay and target data curation and integrity along with their potential impact for users of the data are discussed, alongside robust selection and filter strategies in order to avoid or minimise these, depending on the desired application.

The answer is not 42

During his long and illustrious career that now spans over 50 years David Triggle has had a major impact on biomedical science that can be linked to his research spanning the disciplines of chemistry and biology. Capitalizing on his undergraduate and postgraduate education in chemistry David's early research explored the pharmacology of adreno- and muscarinic receptors ultimately leading to studies of the cellular signaling processes that mediated the effects of receptor activation particularly with respect to calcium homeostasis. David's contributions to the identification and development of calcium channel antagonists resulted in benefits beyond the impact of such drugs in the treatment of diseases of the cardiovascular system. During David's 50+ year career many technological changes have occurred that have affected how research is conducted, funded and published and how its impact evaluated. Not all of these technological advances are necessarily positive and it is valuable to reflect on the long lasting impact of David's accomplishments with reference to such changes.

Guidelines for manuscript submission in the peer-reviewed pharmacological literature

Recent reports have highlighted studies in biomedical research that cannot be reproduced, tending to undermine the credibility, relevance and sustainability of the research process. To address this issue, a number of factors can be monitored to improve the overall probability of reproducibility. These include: (i) shortcomings in experimental design and execution that involve hypothesis conceptualization, statistical analysis, and data reporting; (ii) investigator bias and error; (iii) validation of reagents including cells and antibodies; and (iv) fraud. Historically, research data that have undergone peer review and are subsequently published are then subject to independent replication via the process of self-correction. This often leads to refutation of the original findings and retraction of the paper by which time considerable resources have been wasted in follow-on studies. New NIH guidelines focused on experimental conduct and manuscript submission are being widely adopted in the peer-reviewed literature. These, in their various iterations, are intended to improve the transparency and accuracy of data reporting via the use of checklists that are often accompanied by "best practice" guidelines that aid in validating the methodologies and reagents used in data generation. The present Editorial provides background and context to a newly developed checklist for submissions to Biochemical Pharmacology that is intended to be clear, logical, useful and unambiguous in assisting authors in preparing manuscripts and in facilitating the peer review process. While currently optional, development of this checklist based on user feedback will result in it being mandatory within the next 12 months.