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The Bottlenecks in Translating Placenta-Derived Amniotic Epithelial and Mesenchymal Stromal Cells Into the Clinic: Current Discrepancies in Marker Reports.

ABSTRACT: Placenta-derived amniotic cells have prominent features for application in regenerative medicine. However, there are still discrepancies in the characterization of human amniotic epithelial and mesenchymal stromal cells. It seems crucial that the characterization of human amniotic membrane cells be investigated to determine whether there are currently discrepancies in their characterization reports. In addition, possible causes for the witnessed discrepancies need to be addressed toward paving the way for further clinical application and safer practices. The objective of this review is to investigate the marker characterization as well as the potential causes of the discrepancies in the previous reports on placenta-derived amniotic epithelial and mesenchymal stromal cells. The current discrepancies could be potentially due to reasons including passage number and epithelial to mesenchymal transition (EMT), cell heterogeneity, isolation protocols and cross-contamination, the region of cell isolation on placental disk, measuring methods, and gestational age.

SUBMITTER: Ghamari SH

PROVIDER: S-EPMC7083014 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Bottlenecks in Translating Placenta-Derived Amniotic Epithelial and Mesenchymal Stromal Cells Into the Clinic: Current Discrepancies in Marker Reports.

Ghamari Seyyed-Hadi SH Abbasi-Kangevari Mohsen M Tayebi Tahereh T Bahrami Soheyl S Niknejad Hassan H

Frontiers in bioengineering and biotechnology 20200313

Placenta-derived amniotic cells have prominent features for application in regenerative medicine. However, there are still discrepancies in the characterization of human amniotic epithelial and mesenchymal stromal cells. It seems crucial that the characterization of human amniotic membrane cells be investigated to determine whether there are currently discrepancies in their characterization reports. In addition, possible causes for the witnessed discrepancies need to be addressed toward paving t ...[more]

PMID: 32232037

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Project description:BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal disorder of the motor neuron system with poor prognosis and marginal therapeutic options. Current clinical diagnostic criteria are based on electrophysiological examination and exclusion of other ALS-mimicking conditions. Neuroprotective treatments are, however, most promising in early disease stages. Identification of disease-specific CSF biomarkers and associated biochemical pathways is therefore most relevant to monitor disease progression, response to neuroprotective agents and to enable early inclusion of patients into clinical trials. METHODS AND FINDINGS: CSF from 35 patients with ALS diagnosed according to the revised El Escorial criteria and 23 age-matched controls was processed using paramagnetic bead chromatography for protein isolation and subsequently analyzed by MALDI-TOF mass spectrometry. CSF protein profiles were integrated into a Random Forest model constructed from 153 mass peaks. After reducing this peak set to the top 25%, a classifier was built which enabled prediction of ALS with high accuracy, sensitivity and specificity. Further analysis of the identified peptides resulted in a panel of five highly sensitive ALS biomarkers. Upregulation of secreted phosphoprotein 1 in ALS-CSF samples was confirmed by univariate analysis of ELISA and mass spectrometry data. Further quantitative validation of the five biomarkers was achieved in an 80-plex Multiple Reaction Monitoring mass spectrometry assay. CONCLUSIONS: ALS classification based on the CSF biomarker panel proposed in this study could become a valuable predictive tool for early clinical risk stratification. Of the numerous CSF proteins identified, many have putative roles in ALS-related metabolic processes, particularly in chromogranin-mediated secretion signaling pathways. While a stand-alone clinical application of this classifier will only be possible after further validation and a multicenter trial, it could be readily used to complement current ALS diagnostics and might also provide new insights into the pathomechanisms of this disease in the future.

Project description:ObjectivesTo compare the frequency of discrepancies in retracted reports of clinical trials with those in adjacent unretracted reports in the same journal.DesignBlinded case-control study.SettingJournals in PubMed.Population50 manuscripts, classified on PubMed as retracted clinical trials, paired with 50 adjacent unretracted manuscripts from the same journals. Reports were randomly selected from PubMed in December 2012, with no restriction on publication date. Controls were the preceding unretracted clinical trial published in the same journal. All traces of retraction were removed. Three scientists, blinded to the retraction status of individual reports, reviewed all 100 trial reports for discrepancies. Discrepancies were pooled and cross checked before being counted into prespecified categories. Only then was the retraction status unblinded for analysis.Main outcome measureTotal number of discrepancies (defined as mathematically or logically contradictory statements) in each clinical trial report.ResultsOf 479 discrepancies found in the 100 trial reports, 348 were in the 50 retracted reports and 131 in the 50 unretracted reports. On average, individual retracted reports had a greater number of discrepancies than unretracted reports (median 4 (interquartile range 2-8.75) v 0 (0-5); P<0.001). Papers with a discrepancy were significantly more likely to be retracted than those without a discrepancy (odds ratio 5.7 (95% confidence interval 2.2 to 14.5); P<0.001). In particular, three types of discrepancy arose significantly more frequently in retracted than unretracted reports: factual discrepancies (P=0.002), arithmetical errors (P=0.01), and missed P values (P=0.02). Results from a retrospective analysis indicated that citations and journal impact factor were unlikely to affect the result.ConclusionsDiscrepancies in published trial reports should no longer be assumed to be unimportant. Scientists, blinded to retraction status and with no specialist skill in the field, identify significantly more discrepancies in retracted than unretracted reports of clinical trials. Discrepancies could be an early and accessible signal of unreliability in clinical trial reports.

Dataset Information

The Bottlenecks in Translating Placenta-Derived Amniotic Epithelial and Mesenchymal Stromal Cells Into the Clinic: Current Discrepancies in Marker Reports.

Publications

The Bottlenecks in Translating Placenta-Derived Amniotic Epithelial and Mesenchymal Stromal Cells Into the Clinic: Current Discrepancies in Marker Reports.

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