Human biosample authentication using the high-throughput, cost-effective SNPtrace(TM) system

A repository of Ogden syndrome patient derived iPSC lines and isogenic pairs by X-chromosome screening and genome-editing

Amino-terminal (Nt-) acetylation (NTA) is a common protein modification, affecting 80% of cytosolic proteins in humans. The human essential gene, NAA10, encodes the enzyme NAA10, as the catalytic subunit for the N-terminal acetyltransferase A (NatA) complex, including the accessory protein, NAA15. The first human disease directly involving NAA10 was discovered in 2011, and it was named Ogden syndrome (OS), after the location of the first affected family residing in Ogden, Utah, USA. Since that time, other variants have been found in NAA10 and NAA15. Here we describe the generation of 31 iPSC lines, with 16 from females and 15 from males. This cohort includes CRISPR-mediated correction to the wild-type genotype in 4 male lines, along with editing one female line to generate homozygous wild-type or mutant clones. Following the monoclonalizaiton and screening for X-chromosome activation status in female lines, 3 additional pairs of female lines, in which either the wild type allele is on the active X chromosome (Xa) or the pathogenic variant allele is on Xa, have been generated. Subsets of this cohort have been successfully used to make cardiomyocytes and neural progenitor cells (NPCs). These cell lines are made available to the community via the NYSCF Repository.

Homology Identification and Cross-Contamination Analysis: A Method for Evaluating the Quality of Biological Samples Stored in a Biobank Using the Advanta Sample ID Genotyping Panel

Biological samples are important resources for scientific research. These samples are stored in biobanks over years until needed, and some of them can never be retrieved if they are improperly stored, causing them to be wasted. Thus, they are priceless, and they should be used correctly and effectively. Sample quality substantially affects biomedical research results. However, sample misidentification or mix-up is common. It is necessary to establish quality standards for sample identification. In this study, we used the Advanta Sample ID genotyping panel to detect homology identification and cross-contamination. We compared the single-nucleotide polymorphism (SNP) typing results of two different samples and calculated the similarity score of homologous sample pairs and nonhomologous sample pairs. Through analysis, we obtained a similarity score cutoff point of 0.8620, which was an effective way to distinguish homology and nonhomology. Cross-contamination was detected in two sets of mixtures (STD8:STD6 and jj3:1-P) mixed at a series of special ratios. Sensitivity was dependent on the sample characteristics and mixing ratios. Finally, we assessed the effect of sample degradation degree on SNP genotyping and found that degraded samples with a minimal DNA integrity number of 1.9 had complete genotyping results. On the whole, this study shows that the Sample ID panel is reliable for homology identification and cross-contamination analysis. Moreover, this technology has promising further applications in biological sample quality control.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing

OBJECTIVE

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

RESULTS

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Genetic Risk Factors for Early-Onset Merkel Cell Carcinoma

Importance

Merkel cell carcinoma (MCC) is a rare, aggressive neuroendocrine skin cancer. Of the patients who develop MCC annually, only 4% are younger than 50 years.

Objective

To identify genetic risk factors for early-onset MCC via genomic sequencing.

Design, Setting, and Participants

The study represents a multicenter collaboration between the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Institute of Allergy and Infectious Diseases (NIAID), and the University of Washington. Participants with early-onset and later-onset MCC were prospectively enrolled in an institutional review board-approved study at the University of Washington between January 2003 and May 2019. Unrelated controls were enrolled in the NIAID Centralized Sequencing Program (CSP) between September 2017 and September 2021. Analysis was performed from September 2021 and March 2023. Early-onset MCC was defined as disease occurrence in individuals younger than 50 years. Later-onset MCC was defined as disease occurrence at age 50 years or older. Unrelated controls were evaluated by the NIAID CSP for reasons other than familial cancer syndromes, including immunological, neurological, and psychiatric disorders.

Results

This case-control analysis included 1012 participants: 37 with early-onset MCC, 45 with later-onset MCC, and 930 unrelated controls. Among 37 patients with early-onset MCC, 7 (19%) had well-described variants in genes associated with cancer predisposition. Six patients had variants associated with hereditary cancer syndromes (ATM = 2, BRCA1 = 2, BRCA2 = 1, and TP53 = 1) and 1 patient had a variant associated with immunodeficiency and lymphoma (MAGT1). Compared with 930 unrelated controls, the early-onset MCC cohort was significantly enriched for cancer-predisposing pathogenic or likely pathogenic variants in these 5 genes (odds ratio, 30.35; 95% CI, 8.89-106.30; P < .001). No germline disease variants in these genes were identified in 45 patients with later-onset MCC. Additional variants in DNA repair genes were also identified among patients with MCC.

Conclusions and Relevance

Because variants in certain DNA repair and cancer predisposition genes are associated with early-onset MCC, genetic counseling and testing should be considered for patients presenting at younger than 50 years.

Multiple approaches revealed MGc80-3 as a somatic hybrid with HeLa cells rather than a gastric cancer cell line

The short-tandem-repeats (STR) profiles of MGc80-3 and HeLa partially overlap, raising suspicion of contamination in the MGc80-3 cell line. However, there has not been any relevant study demonstrating whether MGc80-3 was fully replaced by HeLa cells, just mixed with HeLa cells (co-existing), or was a somatic hybrid with HeLa cells. In addition to STR profiling, various approaches, including single nucleotide polymorphisms genotyping, polymerase chain reaction, screening for human papillomaviruses type 18 (HPV-18) fragment, chromosome karyotyping, pathological examination of xenografts, tissue-specific-90-gene expression signature and high-throughput RNA sequencing were used to determine the nature of MGc80-3. Our study found that the abnormal STR profile, partially overlapping with that of HeLa cells (64.62% to 71.64%), could not verify MGc80-3 as a HeLa cell line. However, the STR 13.3 repeat allele in the D13S317 locus that seemed to be unique to HeLa cells was detected in MGc80-3. Almost all the MGc80-3 cells exhibited HPV-18 fragments in the genome as well as certain HeLa marker chromosomes, such as M7 and M12. The molecular assay of the 90-gene expression signature still considered MGc80-3 as a stomach cancer using an algorithmic analysis. The expression pattern of multiple genes in MGc80-3 was quite different from that in HeLa cells, which showed that certain characteristics belonged to gastric cancer cell lines. High throughput RNA sequencing showed the distinct patterns of gene expression in MGc80-3. In conclusion, MGc80-3 cell line is a somatic hybrid with HeLa cells rather than a pure gastric cancer cell line.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e. cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g. indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism's genome (i.e. epitope insertions, gene deletions and SNPs).

Genetic Sex Validation for Sample Tracking in Clinical Testing

Objective

Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.

Results

Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.

Rare variant enrichment analysis supports GREB1L as a contributory driver gene in the etiology of Mayer-Rokitansky-Küster-Hauser syndrome

Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by aplasia of the female reproductive tract; the syndrome can include renal anomalies, absence or dysgenesis, and skeletal anomalies. While functional models have elucidated several candidate genes, only WNT4 (MIM: 603490) variants have been definitively associated with a subtype of MRKH with hyperandrogenism (MIM: 158330). DNA from 148 clinically diagnosed MRKH probands across 144 unrelated families and available family members from North America, Europe, and South America were exome sequenced (ES) and by family-based genomics analyzed for rare likely deleterious variants. A replication cohort consisting of 442 Han Chinese individuals with MRKH was used to further reproduce GREB1L findings in diverse genetic backgrounds. Proband and OMIM phenotypes annotated using the Human Phenotype Ontology were analyzed to quantitatively delineate the phenotypic spectrum associated with GREB1L variant alleles found in our MRKH cohort and those previously published. This study reports 18 novel GREB1L variant alleles, 16 within a multiethnic MRKH cohort and two within a congenital scoliosis cohort. Cohort-wide analyses for a burden of rare variants within a single gene identified likely damaging variants in GREB1L (MIM: 617782), a known disease gene for renal hypoplasia and uterine abnormalities (MIM: 617805), in 16 of 590 MRKH probands. GREB1L variant alleles, including a CNV null allele, were found in 8 MRKH type 1 probands and 8 MRKH type II probands. This study used quantitative phenotypic analyses in a worldwide multiethnic cohort to identify and strengthen the association of GREB1L to isolated uterine agenesis (MRKH type I) and syndromic MRKH type II.

Patient-derived models facilitate precision medicine in liver cancer by remodeling cell-matrix interaction

Liver cancer is an aggressive tumor originating in the liver with a dismal prognosis. Current evidence suggests that liver cancer is the fifth most prevalent cancer worldwide and the second most deadly type of malignancy. Tumor heterogeneity accounts for the differences in drug responses among patients, emphasizing the importance of precision medicine. Patient-derived models of cancer are widely used preclinical models to study precision medicine since they preserve tumor heterogeneity ex vivo in the study of many cancers. Patient-derived models preserving cell-cell and cell-matrix interactions better recapitulate in vivo conditions, including patient-derived xenografts (PDXs), induced pluripotent stem cells (iPSCs), precision-cut liver slices (PCLSs), patient-derived organoids (PDOs), and patient-derived tumor spheroids (PDTSs). In this review, we provide a comprehensive overview of the different modalities used to establish preclinical models for precision medicine in liver cancer.

GenoPipe: identifying the genotype of origin within (epi)genomic datasets

Confidence in experimental results is critical for discovery. As the scale of data generation in genomics has grown exponentially, experimental error has likely kept pace despite the best efforts of many laboratories. Technical mistakes can and do occur at nearly every stage of a genomics assay (i.e., cell line contamination, reagent swapping, tube mislabelling, etc.) and are often difficult to identify post-execution. However, the DNA sequenced in genomic experiments contains certain markers (e.g., indels) encoded within and can often be ascertained forensically from experimental datasets. We developed the Genotype validation Pipeline (GenoPipe), a suite of heuristic tools that operate together directly on raw and aligned sequencing data from individual high-throughput sequencing experiments to characterize the underlying genome of the source material. We demonstrate how GenoPipe validates and rescues erroneously annotated experiments by identifying unique markers inherent to an organism’s genome (i.e., epitope insertions, gene deletions, and SNPs).

Establishing Institutional Scores With the Rigor and Transparency Index: Large-scale Analysis of Scientific Reporting Quality

BACKGROUND

Improving rigor and transparency measures should lead to improvements in reproducibility across the scientific literature; however, the assessment of measures of transparency tends to be very difficult if performed manually.

OBJECTIVE

This study addresses the enhancement of the Rigor and Transparency Index (RTI, version 2.0), which attempts to automatically assess the rigor and transparency of journals, institutions, and countries using manuscripts scored on criteria found in reproducibility guidelines (eg, Materials Design, Analysis, and Reporting checklist criteria).

METHODS

The RTI tracks 27 entity types using natural language processing techniques such as Bidirectional Long Short-term Memory Conditional Random Field-based models and regular expressions; this allowed us to assess over 2 million papers accessed through PubMed Central.

RESULTS

Between 1997 and 2020 (where data were readily available in our data set), rigor and transparency measures showed general improvement (RTI 2.29 to 4.13), suggesting that authors are taking the need for improved reporting seriously. The top-scoring journals in 2020 were the Journal of Neurochemistry (6.23), British Journal of Pharmacology (6.07), and Nature Neuroscience (5.93). We extracted the institution and country of origin from the author affiliations to expand our analysis beyond journals. Among institutions publishing >1000 papers in 2020 (in the PubMed Central open access set), Capital Medical University (4.75), Yonsei University (4.58), and University of Copenhagen (4.53) were the top performers in terms of RTI. In country-level performance, we found that Ethiopia and Norway consistently topped the RTI charts of countries with 100 or more papers per year. In addition, we tested our assumption that the RTI may serve as a reliable proxy for scientific replicability (ie, a high RTI represents papers containing sufficient information for replication efforts). Using work by the Reproducibility Project: Cancer Biology, we determined that replication papers (RTI 7.61, SD 0.78) scored significantly higher (P<.001) than the original papers (RTI 3.39, SD 1.12), which according to the project required additional information from authors to begin replication efforts.

CONCLUSIONS

These results align with our view that RTI may serve as a reliable proxy for scientific replicability. Unfortunately, RTI measures for journals, institutions, and countries fall short of the replicated paper average. If we consider the RTI of these replication studies as a target for future manuscripts, more work will be needed to ensure that the average manuscript contains sufficient information for replication attempts.

Targeted Genotyping in Clinical Pharmacogenomics: What Is Missing?

Clinical pharmacogenomic testing typically uses targeted genotyping, which only detects variants included in the test design and may vary among laboratories. To evaluate the potential patient impact of genotyping compared with sequencing, which can detect common and rare variants, an in silico targeted genotyping panel was developed based on the variants most commonly included in clinical tests and applied to a cohort of 10,030 participants who underwent sequencing for CYP1A2, CYP2C19, CYP2C9, CYP2D6, CYP3A4, CYP3A5, DPYD, SLCO1B1, TPMT, UGT1A1, and VKORC1. The results of in silico targeted genotyping were compared with the clinically reported sequencing results. Of the 10,030 participants, 2780 (28%) had at least one potentially clinically relevant variant/allele identified by sequencing that would not have been detected in a standard targeted genotyping panel. The genes with the largest number of participants with variants only detected by sequencing were SLCO1B1, DPYD, and CYP2D6, which affected 13%, 6.3%, and 3.5% of participants, respectively. DPYD (112 variants) and CYP2D6 (103 variants) had the largest number of unique variants detected only by sequencing. Although targeted genotyping detects most clinically significant pharmacogenomic variants, sequencing-based approaches are necessary to detect rare variants that collectively affect many patients. However, efforts to establish pharmacogenomic variant classification systems and nomenclature to accommodate rare variants will be required to adopt sequencing-based pharmacogenomics.

High prevalence of multilocus pathogenic variation in neurodevelopmental disorders in the Turkish population

Neurodevelopmental disorders (NDDs) are clinically and genetically heterogenous; many such disorders are secondary to perturbation in brain development and/or function. The prevalence of NDDs is > 3%, resulting in significant sociocultural and economic challenges to society. With recent advances in family-based genomics, rare-variant analyses, and further exploration of the Clan Genomics hypothesis, there has been a logarithmic explosion in neurogenetic "disease-associated genes" molecular etiology and biology of NDDs; however, the majority of NDDs remain molecularly undiagnosed. We applied genome-wide screening technologies, including exome sequencing (ES) and whole-genome sequencing (WGS), to identify the molecular etiology of 234 newly enrolled subjects and 20 previously unsolved Turkish NDD families. In 176 of the 234 studied families (75.2%), a plausible and genetically parsimonious molecular etiology was identified. Out of 176 solved families, deleterious variants were identified in 218 distinct genes, further documenting the enormous genetic heterogeneity and diverse perturbations in human biology underlying NDDs. We propose 86 candidate disease-trait-associated genes for an NDD phenotype. Importantly, on the basis of objective and internally established variant prioritization criteria, we identified 51 families (51/176 = 28.9%) with multilocus pathogenic variation (MPV), mostly driven by runs of homozygosity (ROHs) - reflecting genomic segments/haplotypes that are identical-by-descent. Furthermore, with the use of additional bioinformatic tools and expansion of ES to additional family members, we established a molecular diagnosis in 5 out of 20 families (25%) who remained undiagnosed in our previously studied NDD cohort emanating from Turkey.

Transposable element profiles reveal cell line identity and loss of heterozygosity in Drosophila cell culture

Cell culture systems allow key insights into biological mechanisms yet suffer from irreproducible outcomes in part because of cross-contamination or mislabeling of cell lines. Cell line misidentification can be mitigated by the use of genotyping protocols, which have been developed for human cell lines but are lacking for many important model species. Here, we leverage the classical observation that transposable elements (TEs) proliferate in cultured Drosophila cells to demonstrate that genome-wide TE insertion profiles can reveal the identity and provenance of Drosophila cell lines. We identify multiple cases where TE profiles clarify the origin of Drosophila cell lines (Sg4, mbn2, and OSS_E) relative to published reports, and also provide evidence that insertions from only a subset of long-terminal repeat retrotransposon families are necessary to mark Drosophila cell line identity. We also develop a new bioinformatics approach to detect TE insertions and estimate intra-sample allele frequencies in legacy whole-genome sequencing data (called ngs_te_mapper2), which revealed loss of heterozygosity as a mechanism shaping the unique TE profiles that identify Drosophila cell lines. Our work contributes to the general understanding of the forces impacting metazoan genomes as they evolve in cell culture and paves the way for high-throughput protocols that use TE insertions to authenticate cell lines in Drosophila and other organisms.

Human sample authentication in biomedical research: comparison of two platforms

Samples used in biomedical research are often collected over years, in some cases from subjects that may have died and thus cannot be retrieved in any way. The value of these samples is priceless. Sample misidentification or mix-up are unfortunately common problems in biomedical research and can eventually result in the publication of incorrect data. Here we have compared the Fluidigm SNPtrace and the Agena iPLEX Sample ID panels for the authentication of human genomic DNA samples. We have tested 14 pure samples and simulated their cross-contamination at different percentages (2%, 5%, 10%, 25% and 50%). For both panels, we report call rate, allele intensity/probability score, performance in distinguishing pure samples and contaminated samples at different percentages, and sex typing. We show that both panels are reliable and efficient methods for sample authentication and we highlight their advantages and disadvantages. We believe that the data provided here is useful for sample authentication especially in biorepositories and core facility settings.

Prospective experimental treatment of colorectal cancer patients based on organoid drug responses

Background

Organoid technology has recently emerged as a powerful tool to assess drug sensitivity of individual patient tumors in vitro. Organoids may therefore represent a new avenue for precision medicine, as this circumvents many of the complexities associated with DNA- or transcriptional-profiling.

Materials and methods

The SENSOR trial was a single-arm, single-center, prospective intervention trial to evaluate the feasibility of patient-derived organoids to allocate patients for treatment with off-label or investigational agents. The primary endpoint was an objective response rate of ≥20%. Patients underwent a biopsy for culture before commencing their last round standard of care. Organoids were exposed to a panel of eight drugs and patients were treated after progression on standard-of-care treatment and when a clear signal of antitumor activity was identified in vitro.

Results

Sixty-one patients were included and we generated 31 organoids of 54 eligible patients. Twenty-five cultures were subjected to drug screening and 19 organoids exhibited substantial responses to one or more drugs. Three patients underwent treatment with vistusertib and three with capivasertib. Despite drug sensitivity of organoids, patients did not demonstrate objective clinical responses to the recommended treatment.

Conclusions

Organoid technology had limited value as a tool for precision medicine in this patient population because a large fraction of patients could not undergo treatment or because the recommended treatment did not elicit an objective response. We identified several essential parameters, such as the culture success rate, clinical deterioration of patients during standard of care, and rational design of drug panels that need to be accounted for in organoid-guided clinical studies.

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The first prospective clinical trial that leverages tumor organoids to guide experimental treatment decisions.

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Clinical implementation of tumor-organoid-guided treatment is challenging.

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Patients that received organoid-informed treatment did not experience clinical benefit.

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Organoid drug screening can distinguish differential drug responses in identical genetic genotypes.

Short tandem repeat profiling for the authentication of cancer stem-like cells

Colorectal and glioblastoma cancer stem‐like cells (CSCs) are essential for translational research. Cell line authentication by short tandem repeat (STR) profiling ensures reproducibility of results in oncology research. This technique enables to identify mislabeling or cross‐contamination of cell lines. In our study, we provide a reference dataset for a panel of colorectal and glioblastoma CSCs that allows authentication. Each cell line was entered into the cell Line Integrated Molecular Authentication database 2.1 to be compared to the STR profiles of 4485 tumor cell lines. This article also provides clinical data of patients from whom CSCs arose and data on the parent tumor stage and mutations. STR profiles and information of our CSCs are also available in the Cellosaurus database (ExPASy) as identified by unique research resource identifier codes.

Human cell lines obtained from cancer stem‐like cells represent an invaluable model for studying tumor properties. Cell line authentication by short tandem repeat (STR) profiling is an important tool to identify the potential mislabeling or cross‐contamination of cell lines. Here, the authors characterized 18 colorectal cancer stem‐like cell lines from 17 patients and 103 glioblastoma cancer stem‐like cell lines from 95 patients by STR profiling to create a reference dataset that allows the authentication of these cell lines and their identification through a unique research resource identifier. The results will help further ensure the reliability and reproducibility of research experiments.

Patient-derived organoids can predict response to chemotherapy in metastatic colorectal cancer patients

There is a clear and unmet clinical need for biomarkers to predict responsiveness to chemotherapy for cancer. We developed an in vitro test based on patient-derived tumor organoids (PDOs) from metastatic lesions to identify nonresponders to standard-of-care chemotherapy in colorectal cancer (CRC). In a prospective clinical study, we show the feasibility of generating and testing PDOs for evaluation of sensitivity to chemotherapy. Our PDO test predicted response of the biopsied lesion in more than 80% of patients treated with irinotecan-based therapies without misclassifying patients who would have benefited from treatment. This correlation was specific to irinotecan-based chemotherapy, however, and the PDOs failed to predict outcome for treatment with 5-fluorouracil plus oxaliplatin. Our data suggest that PDOs could be used to prevent cancer patients from undergoing ineffective irinotecan-based chemotherapy.

Authentication, characterization and contamination detection of cell lines, xenografts and organoids by barcode deep NGS sequencing

Misidentification and contamination of biobank samples (e.g. cell lines) have plagued biomedical research. Short tandem repeat (STR) and single-nucleotide polymorphism assays are widely used to authenticate biosamples and detect contamination, but with insufficient sensitivity at 5–10% and 3–5%, respectively. Here, we describe a deep NGS-based method with significantly higher sensitivity (≤1%). It can be used to authenticate human and mouse cell lines, xenografts and organoids. It can also reliably identify and quantify contamination of human cell line samples, contaminated with only small amount of other cell samples; detect and quantify species-specific components in human–mouse mixed samples (e.g. xenografts) with 0.1% sensitivity; detect mycoplasma contamination; and infer population structure and gender of human samples. By adopting DNA barcoding technology, we are able to profile 100–200 samples in a single run at per-sample cost comparable to conventional STR assays, providing a truly high-throughput and low-cost assay for building and maintaining high-quality biobanks.

Challenges in returning results in a genomic medicine implementation study: the Return of Actionable Variants Empirical (RAVE) study

To inform the process of returning results in genome sequencing studies, we conducted a quantitative and qualitative assessment of challenges encountered during the Return of Actionable Variants Empiric (RAVE) study conducted at Mayo Clinic. Participants (n = 2535, mean age 63 ± 7, 57% female) were sequenced for 68 clinically actionable genes and 14 single nucleotide variants. Of 122 actionable results detected, 118 were returnable; results were returned by a genetic counselor—86 in-person and 12 by phone. Challenges in returning actionable results were encountered in a significant proportion (38%) of the cohort and were related to sequencing and participant contact. Sequencing related challenges (n = 14), affecting 13 participants, included reports revised based on clinical presentation (n = 3); reports requiring corrections (n = 2); mosaicism requiring alternative DNA samples for confirmation (n = 3); and variant re-interpretation due to updated informatics pipelines (n = 6). Participant contact related challenges (n = 44), affecting 38 participants, included nonresponders (n = 20), decedents (n = 1), and previously known results (n = 23). These results should be helpful to investigators preparing for return of results in large-scale genomic sequencing projects.

CeL-ID: cell line identification using RNA-seq data

BACKGROUND

Cell lines form the cornerstone of cell-based experimentation studies into understanding the underlying mechanisms of normal and disease biology including cancer. However, it is commonly acknowledged that contamination of cell lines is a prevalent problem affecting biomedical science and available methods for cell line authentication suffer from limited access as well as being too daunting and time-consuming for many researchers. Therefore, a new and cost effective approach for authentication and quality control of cell lines is needed.

RESULTS

We have developed a new RNA-seq based approach named CeL-ID for cell line authentication. CeL-ID uses RNA-seq data to identify variants and compare with variant profiles of other cell lines. RNA-seq data for 934 CCLE cell lines downloaded from NCI GDC were used to generate cell line specific variant profiles and pair-wise correlations were calculated using frequencies and depth of coverage values of all the variants. Comparative analysis of variant profiles revealed that variant profiles differ significantly from cell line to cell line whereas identical, synonymous and derivative cell lines share high variant identity and are highly correlated (ρ > 0.9). Our benchmarking studies revealed that CeL-ID method can identify a cell line with high accuracy and can be a valuable tool of cell line authentication in biomedical science. Finally, CeL-ID estimates the possible cross contamination using linear mixture model if no perfect match was detected.

CONCLUSIONS

In this study, we show the utility of an RNA-seq based approach for cell line authentication. Our comparative analysis of variant profiles derived from RNA-seq data revealed that variant profiles of each cell line are distinct and overall share low variant identity with other cell lines whereas identical or synonymous cell lines show significantly high variant identity and hence variant profiles can be used as a discriminatory/identifying feature in cell authentication model.

Incidences of problematic cell lines are lower in papers that use RRIDs to identify cell lines

The use of misidentified and contaminated cell lines continues to be a problem in biomedical research. Research Resource Identifiers (RRIDs) should reduce the prevalence of misidentified and contaminated cell lines in the literature by alerting researchers to cell lines that are on the list of problematic cell lines, which is maintained by the International Cell Line Authentication Committee (ICLAC) and the Cellosaurus database. To test this assertion, we text-mined the methods sections of about two million papers in PubMed Central, identifying 305,161 unique cell-line names in 150,459 articles. We estimate that 8.6% of these cell lines were on the list of problematic cell lines, whereas only 3.3% of the cell lines in the 634 papers that included RRIDs were on the problematic list. This suggests that the use of RRIDs is associated with a lower reported use of problematic cell lines.

The Return of Actionable Variants Empirical (RAVE) Study, a Mayo Clinic Genomic Medicine Implementation Study: Design and Initial Results

OBJECTIVES

To identify clinically actionable genetic variants from targeted sequencing of 68 disease-related genes, estimate their penetrance, and assess the impact of disclosing results to participants and providers.

PATIENTS AND METHODS

The Return of Actionable Variants Empirical (RAVE) Study investigates outcomes following the return of pathogenic/likely pathogenic (P/LP) variants in 68 disease-related genes. The study was initiated in December 2016 and is ongoing. Targeted sequencing was performed in 2533 individuals with hyperlipidemia or colon polyps. The electronic health records (EHRs) of participants carrying P/LP variants in 36 cardiovascular disease (CVD) genes were manually reviewed to ascertain the presence of relevant traits. Clinical outcomes, health care utilization, family communication, and ethical and psychosocial implications of disclosure of genomic results are being assessed by surveys, telephone interviews, and EHR review.

RESULTS

Of 29,208 variants in the 68 genes, 1915 were rare (frequency <1%) and putatively functional, and 102 of these (60 in 36 CVD genes) were labeled P/LP based on the American College of Medical Genetics and Genomics framework. Manual review of the EHRs of participants (n=73 with P/LP variants in CVD genes) revealed that 33 had the expected trait(s); however, only 6 of 45 participants with non-familial hypercholesterolemia (FH) P/LP variants had the expected traits.

CONCLUSION

Expected traits were present in 13% of participants with P/LP variants in non-FH CVD genes, suggesting low penetrance; this estimate may change with additional testing performed as part of the clinical evaluation. Ongoing analyses of the RAVE Study will inform best practices for genomic medicine.

Generation of Tumor-Reactive T Cells by Co-culture of Peripheral Blood Lymphocytes and Tumor Organoids

Cancer immunotherapies have shown substantial clinical activity for a subset of patients with epithelial cancers. Still, technological platforms to study cancer T-cell interactions for individual patients and understand determinants of responsiveness are presently lacking. Here, we establish and validate a platform to induce and analyze tumor-specific T cell responses to epithelial cancers in a personalized manner. We demonstrate that co-cultures of autologous tumor organoids and peripheral blood lymphocytes can be used to enrich tumor-reactive T cells from peripheral blood of patients with mismatch repair-deficient colorectal cancer and non-small-cell lung cancer. Furthermore, we demonstrate that these T cells can be used to assess the efficiency of killing of matched tumor organoids. This platform provides an unbiased strategy for the isolation of tumor-reactive T cells and provides a means by which to assess the sensitivity of tumor cells to T cell-mediated attack at the level of the individual patient.

A single nucleotide polymorphism genotyping platform for the authentication of patient derived xenografts

Patient derived xenografts (PDXs) have become a vital, frequently used, component of anti-cancer drug development. PDXs can be serially passaged in vivo for years, and shared across laboratories. As a consequence, the potential for mis-identification and cross-contamination is possible, yet authentication of PDXs appears limited. We present a PDX Authentication System (PAS), by combining a commercially available OpenArray assay of single nucleotide polymorphisms (SNPs) with in-house R studio programs, to validate PDXs established in individual mice from acute lymphoblastic leukemia biopsies. The PAS is sufficiently robust to identify contamination at levels as low as 3%, similar to the gold standard of short tandem repeat (STR) profiling. We have surveyed a panel of PDXs established from 73 individual leukemia patients, and found that the PAS provided sufficient discriminatory power to identify each xenograft. The identified SNP-discrepant PDXs demonstrated distinct gene expression profiles, indicating a risk of contamination for PDXs at high passage number. The PAS also allows for the authentication of tumor cells with complex karyotypes from solid tumors including prostate cancer and Ewing's sarcoma. This study highlights the demands of authenticating PDXs for cancer research, and evaluates a reliable authentication platform that utilizes a commercially available and cost-effective system.

Best practices for authenticating cell lines

Experiments using cell cultures are only valid to the extent that the cell culture is a true model system for the biological system being investigated. To assure that a cell line is and remains an appropriate biological model, its identity, purity, ploidy, and phenotype must be maintained. These characteristics comprise and determine the authenticity of a cell line. Routine monitoring of the cell line through microscopic examination of morphology can help to determine authenticity, as can the determination of phenotypic status. Assays designed to confirm cell identity and ploidy and freedom from cross-contaminating cell types may need to be performed at certain times, as such information may not be obtained through morphologic and phenotypic examinations alone. The best practices associated with establishing cell line authenticity are described in this article.

The ghosts of HeLa: How cell line misidentification contaminates the scientific literature

While problems with cell line misidentification have been known for decades, an unknown number of published papers remains in circulation reporting on the wrong cells without warning or correction. Here we attempt to make a conservative estimate of this ‘contaminated’ literature. We found 32,755 articles reporting on research with misidentified cells, in turn cited by an estimated half a million other papers. The contamination of the literature is not decreasing over time and is anything but restricted to countries in the periphery of global science. The decades-old and often contentious attempts to stop misidentification of cell lines have proven to be insufficient. The contamination of the literature calls for a fair and reasonable notification system, warning users and readers to interpret these papers with appropriate care.

Authentication of M14 melanoma cell line proves misidentification of MDA-MB-435 breast cancer cell line

A variety of analytical approaches have indicated that melanoma cell line UCLA‐SO‐M14 (M14) and breast carcinoma cell line MDA‐MB‐435 originate from a common donor. This indicates that at some point in the past, one of these cell lines became misidentified, meaning that it ceased to correspond to the reported donor and instead became falsely identified (through cross‐contamination or other means) as a cell line from a different donor. Initial studies concluded that MDA‐MB‐435 was the misidentified cell line and M14 was the authentic cell line, although contradictory evidence has been published, resulting in further confusion. To address this question, we obtained early samples of the melanoma cell line (M14), a lymphoblastoid cell line from the same donor (ML14), and donor serum preserved at the originator's institution. M14 samples were cryopreserved in December 1975, before MDA‐MB‐435 cells were established in culture. Through a series of molecular characterizations, including short tandem repeat (STR) profiling and cytogenetic analysis, we demonstrated that later samples of M14 and MDA‐MB‐435 correspond to samples of M14 frozen in 1975, to the lymphoblastoid cell line ML14, and to the melanoma donor's STR profile, sex and blood type. This work demonstrates conclusively that M14 is the authentic cell line and MDA‐MB‐435 is misidentified. With clear provenance information and authentication testing of early samples, it is possible to resolve debates regarding the origins of problematic cell lines that are widely used in cancer research.

What's new?

A variety of analytical approaches have indicated that melanoma cell line M14 and breast carcinoma cell line MDA‐MB‐435 originate from a common donor, but there is ongoing debate regarding which is the misidentified cell line. Here, authentication testing of M14 from 1975 (prior to the establishment of MDA‐MB‐435), with comparison to donor serum and lymphoblastoid cell line ML14, shows that M14 is the authentic cell line and MDA‐MB‐435 is a misidentified derivative. With clear provenance information and authentication testing of early samples, debates regarding the origins of problematic cell lines that are widely used in cancer research can be resolved.

Barrett's metaplasia develops from cellular reprograming of esophageal squamous epithelium due to gastroesophageal reflux

Gastroesophageal reflux disease (GERD) clinically predisposes to columnar Barrett's metaplasia (BM) in the distal esophagus. We demonstrate evidence supporting the cellular origin of BM from reprograming or transcommitment of resident normal esophageal squamous (NES) epithelial cells in response to acid and bile (A + B) exposure using an in vitro cell culture model. The hTERT-immortalized NES cell line NES-B10T was exposed 5 min/day to an A + B mixture for 30 wk. Morphological changes, mRNA, and protein expression levels for the inflammatory marker cyclooxygenase-2; the lineage-determining transcription factors TAp63 (squamous), CDX2, and SOX9 (both columnar); and the columnar lineage markers Villin, Muc-2, CK8, and mAb Das-1 (incomplete phenotype of intestinal metaplasia) were assessed every 10 wk. Markers of columnar lineage and inflammation increased progressively, while squamous lineage-determining transcriptional factors were significantly decreased both at the mRNA and/or protein level in the NES-B10T cells at/after A + B treatment for 30 wk. Distinct modifications in morphological features were only observed at/after 30 wk of A + B exposure. These changes acquired by the NES-B10T 30-wk cells were retained even after cessation of A + B exposure for at least 3 wk. This study provides evidence that chronic exposure to the physiological components of gastric refluxate leads to repression of the discernable squamous transcriptional factors and activation of latent columnar transcriptional factors. This reflects the alteration in lineage commitment of the precursor-like biphenotypic, NES-B10T cells in response to A + B exposure as the possible origin of BM from the resident NES cells.NEW & NOTEWORTHY This study provides evidence of the origins of Barrett's metaplasia from lineage transcommitment of resident esophageal cells after chronic exposure to gastroesophageal refluxate. The preterminal progenitor-like squamous cells alter their differentiation and develop biphenotypic characteristics, expressing markers of incomplete-type columnar metaplasia. Development of these biphenotypic precursors in vitro is a unique model to study pathogenesis of Barrett's metaplasia and esophageal adenocarcinoma.

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.

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.

Investigation of Cross-Contamination and Misidentification of 278 Widely Used Tumor Cell Lines

In recent years, biological research involving human cell lines has been rapidly developing in China. However, some of the cell lines are not authenticated before use. Therefore, misidentified and/or cross-contaminated cell lines are unfortunately commonplace. In this study, we present a comprehensive investigation of cross-contamination and misidentification for a panel of 278 cell lines from 28 institutes in China by using short tandem repeat profiling method. By comparing the DNA profiles with the cell bank databases of ATCC and DSMZ, a total of 46.0% (128/278) cases with cross-contamination/misidentification were uncovered coming from 22 institutes. Notably, 73.2% (52 out of 71) of the cell lines established by the Chinese researchers were misidentified and accounted for 40.6% of total misidentification (52/128). Further, 67.3% (35/52) of the misidentified cell lines established in laboratories of China were HeLa cells or a possible hybrid of HeLa with another kind of cell line. Furthermore, the bile duct cancer cell line HCCC-9810 and degenerative lung cancer Calu-6 exhibited 88.9% match in the ATCC database (9-loci), indicating that they were from the same origin. However, when we used 21-loci to compare these two cell lines with the same algorithm, the percent match was only 48.2%, indicating that these two cell lines were different. The SNP profiles of HCCC-9810 and Calu-6 also revealed that they were different cell lines. 150 cell lines with unique profiles demonstrated a wide range of in vitro phenotypes. This panel of 150 genomically validated cancer cell lines represents a valuable resource for the cancer research community and will advance our understanding of the disease by providing a standard reference for cell lines that can be used for biological as well as preclinical studies.

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.

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.

Studying both sexes: a guiding principle for biomedicine

In May 2014, the U.S. National Institutes of Health (NIH) announced that it will ensure that investigators account for sex as a biological variable (SABV) in NIH-funded preclinical research as part of the agency's rigor and transparency initiative. Herein, I describe in more detail the rationale behind the SABV policy component and provide additional detail about policy goals. In short, studying both sexes is a guiding principle in biomedical research that will expand knowledge toward turning discovery into health. NIH expects that considering SABV in preclinical research will help to build a knowledge base that better informs the design of clinical research and trials in humans. Integrating the practice of studying both sexes in preclinical research will, over time, expand our currently incomplete knowledge base that plays a critical role in informing the development of sex- and gender-appropriate medical care for women and men.