Biospecimen Reporting for improved study quality (BRISQ)

[Quality assurance in tissue biobanking-an overview]

Tissue biobanks are important resource and technology platforms for biomedical research, which deals with molecular pathogenesis and the prevention, diagnosis and treatment of diseases.Due to this central role in the standardised collection, storage and distribution of human tissue and its derivatives, a practised quality management is one of the most important measures to achieve and maintain a comprehensive quality assurance of all biobanking processes. At the same time, this promotes acceptance and credibility. External quality assurance of biobanks can be achieved through accreditation. Within the German biobanking community, increasing harmonisation of biobanking processes has also been achieved through the provision of various quality assurance measures by the German Biobank Node (GBN).In the following, challenges and opportunities in the implementation of a comprehensive quality assurance in biobanking will be discussed and solutions for tissue biobanking will be presented using the example of the tissue bank of the National Centre for Tumour Diseases (NCT).

A Versatile, Secure, and Sustainable All-in-One Biobank-Registry Data Solution: The A3BC REDCap Model

Introduction: A key element in the big data revolution is large-scale biobanking and the associated development of high-quality data collections and supporting informatics solutions. As such, in establishing the Australian Arthritis and Autoimmune Biobank Collaborative (A3BC), we sought to establish a low-cost, nation-scale data management system capable of managing a multisite biobank registry with complex longitudinal sample and data requirements. Materials and Methods: We assessed several international commercial and nonprofit software platforms using standardized system requirement criteria and follow-up interviews. Vendor compliance scoring was prioritized to meet our project-critical requirements. Consumer/end-user codesign was integral to refining our system requirements for optimized adoption. Customization of the selected software solution was performed to optimize field auto-population between participant timepoints and forms, using modules that are transferable and that do not impact core code. Institutional and independent testing was used to ensure data security. Results: We selected the widely used research web application Research Electronic Data Capture (REDCap), which is "free" (under nonprofit license agreement terms), highly configurable, and customizable to a variety of biobank and registry needs and can be developed/maintained by biobank users with modest IT skill, time, and cost. We created a secure, comprehensive participant-centric biobank-registry database that includes: (1) best practice data security measures (incl. multisite access login using institutional user credentials), (2) permission-to-contact and dynamic itemized electronic consent, (3) a complete chain of custody from consent to longitudinal biospecimen data collection to publication, (4) complex longitudinal patient-reported surveys, (5) integration of record-level extracted/linked participant data, (6) significant form auto-population for streamlined data capture, and (7) native dashboards for operational visualizations. Conclusion: We recommend the versatile, reusable, and sustainable informatics model we have developed in REDCap for prospective chronic disease biobanks or registry biobanks (of local to national complexity) supporting holistic research into disease prediction, precision medicine, and prevention strategies.

From laboratory to clinic: Translation of extracellular vesicle based cancer biomarkers

The past decade has witnessed a rapid growth in the field of extracellular vesicle (EV) based biomarkers for the diagnosis and monitoring of cancer. Several studies have reported novel EV based biomarkers, but the technical and clinical validation phase has been hampered by general challenges common to biomedical research field as well as specific challenges inherent to the nanoparticle field. This has led to more common failures than success stories in the biomarker discovery pipeline. As a result, more attention must be focused on the process of biomarker discovery, verification, and validation to allow for translation and application of novel EV based research to patient care. Herein, we briefly discuss the hurdles and potential solutions in EV biomarker discovery and verification and validation, and clinical translation.

Mass spectrometry based analytical quality assessment of serum and plasma specimens with patterns of endo- and exogenous peptides

Background

Inappropriate preanalytical sample handling is a major threat for any biomarker discovery approach. Blood specimens have a genuine proteolytic activity that leads to a time dependent decay of peptidic quality control markers (QCMs). The aim of this study was to identify QCMs for direct assessment of sample quality (DASQ) of serum and plasma specimens.

Methods

Serum and plasma specimens of healthy volunteers and tumor patients were spiked with two synthetic reporter peptides (exogenous QCMs) and aged under controlled conditions for up to 24 h. The proteolytic fragments of endogenous and exogenous QCMs were monitored for each time point by mass spectrometry (MS). The decay pattern of peptides was used for supervised classification of samples according to their respective preanalytical quality.

Results

The classification accuracy for fresh specimens (1 h) was 96% and 99% for serum and plasma specimens, respectively, when endo- and exogenous QCMs were used for the calculations. However, classification of older specimens was more difficult and overall classification accuracy decreased to 79%.

Conclusions

MALDI-TOF MS is a simple and robust method that can be used for DASQ of serum and plasma specimens in a high throughput manner. We propose DASQ as a fast and simple step that can be included in multicentric large-scale projects to ensure the homogeneity of sample quality.

Enteric dysbiosis and fecal calprotectin expression in premature infants

BACKGROUND

Premature infants often develop enteric dysbiosis with a preponderance of Gammaproteobacteria, which has been related to adverse clinical outcomes. We investigated the relationship between increasing fecal Gammaproteobacteria and mucosal inflammation, measured by fecal calprotectin (FC).

METHODS

Stool samples were collected from very-low-birth weight (VLBW) infants at ≤2, 3, and 4 weeks' postnatal age. Fecal microbiome was surveyed using polymerase chain reaction amplification of the V4 region of 16S ribosomal RNA, and FC was measured by enzyme immunoassay.

RESULTS

We enrolled 45 VLBW infants (gestation 27.9 ± 2.2 weeks, birth weight 1126 ± 208 g) and obtained stool samples at 9.9 ± 3, 20.7 ± 4.1, and 29.4 ± 4.9 days. FC was positively correlated with the genus Klebsiella (r = 0.207, p = 0.034) and its dominant amplicon sequence variant (r = 0.290, p = 0.003), but not with the relative abundance of total Gammaproteobacteria. Klebsiella colonized the gut in two distinct patterns: some infants started with low Klebsiella abundance and gained these bacteria over time, whereas others began with very high Klebsiella abundance.

CONCLUSION

In premature infants, FC correlated with relative abundance of a specific pathobiont, Klebsiella, and not with that of the class Gammaproteobacteria. These findings indicate a need to define dysbiosis at genera or higher levels of resolution.

Dichotomous development of the gut microbiome in preterm infants

BACKGROUND

Preterm infants are at risk of developing intestinal dysbiosis with an increased proportion of Gammaproteobacteria. In this study, we sought the clinical determinants of the relative abundance of feces-associated Gammaproteobacteria in very low birth weight (VLBW) infants. Fecal microbiome was characterized at ≤ 2 weeks and during the 3rd and 4th weeks after birth, by 16S rRNA amplicon sequencing. Maternal and infant clinical characteristics were extracted from electronic medical records. Data were analyzed by linear mixed modeling and linear regression.

RESULTS

Clinical data and fecal microbiome profiles of 45 VLBW infants (gestational age 27.9 ± 2.2 weeks; birth weight 1126 ± 208 g) were studied. Three stool samples were analyzed for each infant at mean postnatal ages of 9.9 ± 3, 20.7 ± 4.1, and 29.4 ± 4.9 days. The average relative abundance of Gammaproteobacteria was 42.5% (0-90%) at ≤ 2 weeks, 69.7% (29.9-86.9%) in the 3rd, and 75.5% (54.5-86%) in the 4th week (p < 0.001). Hierarchical and K-means clustering identified two distinct subgroups: cluster 1 started with comparatively low abundance that increased with time, whereas cluster 2 began with a greater abundance at ≤ 2 weeks (p < 0.001) that decreased over time. Both groups resembled each other by the 3rd week. Single variants of Klebsiella and Staphylococcus described variance in community structure between clusters and were shared between all infants, suggesting a common, hospital-derived source. Fecal Gammaproteobacteria was positively associated with vaginal delivery and antenatal steroids.

CONCLUSIONS

We detected a dichotomy in gut microbiome assembly in preterm infants: some preterm infants started with low relative gammaproteobacterial abundance in stool that increased as a function of postnatal age, whereas others began with and maintained high abundance. Vaginal birth and antenatal steroids were identified as predictors of Gammaproteobacteria abundance in the early (≤ 2 weeks) and later (3rd and 4th weeks) stool samples, respectively. These findings are important in understanding the development of the gut microbiome in premature infants.

Tumor Pre-Analytics in Molecular Pathology: Impact on Protein Expression and Analysis

Purpose of Review

Precision medicine promises patient tailored, individualized diagnosis and treatment of diseases and relies on clinical specimen integrity and accuracy of companion diagnostic testing. Therefore, pre-analytics, which are defined as the collection, processing, and storage of clinical specimens, are critically important to enable optimal diagnostics, molecular profiling, and clinical decision-making around harvested specimens. This review article discusses the impact of tumor pre-analytics on molecular pathology focusing on biospecimen protein expression and analysis.

Recent Findings

Due to busy clinical schedules and workflows that have been established for many years and to lack of standardization and limited assessment tools to quantify variability in pre-analytical processing, the effects of pre-analytics on biospecimen integrity are often overlooked. Several studies have recently emphasized an emerging crisis in science and reproducibility of results.

Summary

Biomarker instability due to pre-analytical variables affects comprehensive analysis and molecular phenotyping of patients’ tissue. This problematic emphasizes the critical need for standardized protocols and technologies to be applied in the clinical and research setting.

Urinary Protein Markers for the Detection and Prognostication of Urothelial Carcinoma

Bladder cancer diagnosis and surveillance is mainly based on cystoscopy and urine cytology. However, both methods have significant limitations; urine cytology has a low sensitivity for low-grade tumors, while cystoscopy is uncomfortable for the patients. Therefore, in the last decade urine analysis was the subject of intensive research resulting in the identification of many potential biomarkers for the detection, surveillance, or prognostic stratification of bladder cancer. Current trends move toward the development of multiparametric models to improve the diagnostic accuracy compared with single molecular markers. Recent technical advances for high-throughput and more sensitive measurements have led to the development of multiplex assays showing potential for more efficient tools toward future clinical application. In this review, we focus on the findings of urinary protein research in the context of detection and prognostication of bladder cancer. Furthermore, we provide an up-to-date overview on the recommendations for the quality evaluation of published studies as well as for the conduction of future urinary biomarker studies.

Biobanking of Fresh-Frozen Human Adenocarcinomatous and Normal Colon Tissues: Which Parameters Influence RNA Quality?

Medical research projects become increasingly dependent on biobanked tissue of high quality because the reliability of gene expression is affected by the quality of extracted RNA. Hence, the present study aimed to determine if clinical, surgical, histological, and molecular parameters influence RNA quality of normal and tumoral frozen colonic tissues. RNA Quality Index (RQI) was evaluated on 241 adenocarcinomas and 115 matched normal frozen colon tissues collected between October 2006 and December 2012. RQI results were compared to patients’ age and sex, tumor site, kind of surgery, anastomosis failure, adenocarcinoma type and grade, tumor cell percentage, necrosis extent, HIF-1α and cleaved caspase-3 immunohistochemistry, and BRAF, KRAS and microsatellites status. The RQI was significantly higher in colon cancer tissue than in matched normal tissue. RQI from left-sided colonic cancers was significantly higher than RQI from right-sided cancers. The RNA quality was not affected by ischemia and storage duration. According to histological control, 7.9% of the samples were unsatisfactory because of inadequate sampling. Biobanked tumoral tissues with RQI ≥5 had lower malignant cells to stromal cells ratio than samples with RQI <5 (p <0.05). Cellularity, necrosis extent and mucinous component did not influence RQI results. Cleaved caspase-3 and HIF-1α immunolabelling were not correlated to RQI. BRAF, KRAS and microsatellites molecular status did not influence RNA quality. Multivariate analysis revealed that the tumor location, the surgical approach (laparoscopy versus open colectomy) and the occurrence of anastomotic leakage were the only parameters influencing significantly RQI results of tumor samples. We failed to identify parameter influencing RQI of normal colon samples. These data suggest that RNA quality of colonic adenocarcinoma biospecimens is determined by clinical and surgical parameters. More attention should be paid during the biobanking procedure of right-sided colon cancer or laparoscopic colectomy specimen. Histological quality control remains essential to control sampling accuracy.

Biobanking Comes of Age: The Transition to Biospecimen Science

Biobanking involves the collection, processing, storage, and distribution of biological specimens and the policies and procedures necessary to accomplish those aims successfully. Although biobanking may also involve collections for environmental studies or museum archives, most efforts to standardize biobanking practices have been directed toward human biomedical research. Initially focused primarily on collecting samples for diagnostic purposes in pathology settings, biobanks have evolved into complex organizations engaged in advancing personalized (or precision) medicine and translational research. This evolution has involved the development of biobanking best practices and the transformation of a field driven by empirical approaches into the emerging area of biospecimen science. It has become increasingly important to develop evidence-based practices for collecting biospecimens and data that can be shared with confidence with international collaborators. Aside from these technical approaches, other factors play crucial roles, such as ethical and regulatory issues, business planning and sustainability, and approaches to data collection and sharing.

A critical analysis of cancer biobank practices in relation to biospecimen quality

There are concerns that a substantial proportion of published research data is not reproducible, which may partially explain the frequent failure to translate pre-clinical results to clinical care. High-quality cancer biospecimens are needed for robust, reproducible research findings, with most researchers obtaining these specimens from cancer biobanks or tumour banks. This review provides an overview of the types of quality control (QC) activities conducted within cancer biobanks that pertain to biospecimen quality and of biospecimen quality reporting tools, including SPREC and BRISQ. We examine how QC assay results and other biospecimen data are communicated from biobanks to researchers, and whether these activities lead to improved biospecimen quality reporting within the literature and/or to improved research outcomes. We also discuss operational factors that limit QC activities within biobanks and evidence gaps requiring further research. In summary, whereas the provision of quality biospecimens is a common aim of cancer biobanks, QC activities remain underreported and are rarely discussed in the literature, compared with other aspects of biobank operations. Further research is required to determine how biobanks can most efficiently optimise biospecimen quality, and how communication between biobanks and researchers can be improved.

The Informatics Challenges Facing Biobanks: A Perspective from a United Kingdom Biobanking Network

The challenges facing biobanks are changing from simple collections of materials to quality-assured fit-for-purpose clinically annotated samples. As a result, informatics awareness and capabilities of a biobank are now intrinsically related to quality. A biobank may be considered a data repository, in the form of raw data (the unprocessed samples), data surrounding the samples (processing and storage conditions), supplementary data (such as clinical annotations), and an increasing ethical requirement for biobanks to have a mechanism for researchers to return their data. The informatics capabilities of a biobank are no longer simply knowing sample locations; instead the capabilities will become a distinguishing factor in the ability of a biobank to provide appropriate samples. There is an increasing requirement for biobanking systems (whether in-house or commercially sourced) to ensure the informatics systems stay apace with the changes being experienced by the biobanking community. In turn, there is a requirement for the biobanks to have a clear informatics policy and directive that is embedded into the wider decision making process. As an example, the Breast Cancer Campaign Tissue Bank in the UK was a collaboration between four individual and diverse biobanks in the UK, and an informatics platform has been developed to address the challenges of running a distributed network. From developing such a system there are key observations about what can or cannot be achieved by informatics in isolation. This article will highlight some of the lessons learned during this development process.

Closing the gap between brain banks and proteomics to advance the study of neurodegenerative diseases

Neurodegenerative diseases (NDs), such as Alzheimer's disease and Parkinson's disease, are among the most debilitating neurological disorders, and as life expectancy rises quickly around the world, the scientific and clinical challenges of dealing with them will also increase dramatically, putting increased pressure on the biomedical community to come up with innovative solutions for the understanding, diagnosis, and treatment of these conditions. Despite several decades of intensive research, there is still little that can be done to prevent, cure, or even slow down the progression of NDs in most patients. There is an urgent need to develop new lines of basic and applied research that can be quickly translated into clinical application. One way to do this is to apply the tools of proteomics to well-characterized samples of human brain tissue, but a closer partnership must still be forged between proteomic scientists, brain banks, and clinicians to explore the maximum potential of this approach. Here, we analyze the challenges and potential benefits of using human brain tissue for proteomics research toward NDs.

Infrastructure and facilities for human biobanking in low- and middle-income countries: a situation analysis

OBJECTIVE

To collect information on biobanking facilities in low- and middle-income countries (LMICs) as a first step towards establishing an LMIC biobank and cohort building network (BCNet) to support research, with a focus on cancer control.

METHOD

Sixty centres were identified from sources including cancer centres, universities, hospitals, and public health facilities and invited to participate in a survey between December 2012 and March 2013.

RESULTS

Of the 27 centres (45%) that responded, most have existed for <10 years. They store between 1,000 and 1,000,000 research samples as well as samples remaining after clinical diagnosis. Sample storage is mostly in freezers, although 45% (9/20) of the centres do not have regular access to electricity. Biobank managers, sample management systems, and mechanisms for follow-up using linkages are uncommon. Many (80%; 21/26) of the centres have regulations to govern research, but regulations for the use of biobank resources (samples and data) are not well developed.

CONCLUSIONS

Biobanking facilities are being developed in LMICs. Shortcomings in international visibility, sample sharing regulations, standardization, quality assurance, and sample management systems could be alleviated by international networking. Stakeholders need to work together to increase access to high-quality biological resources for scientific research.

A data standard for sourcing fit-for-purpose biological samples in an integrated virtual network of biobanks

Human tissue biobanks are at the epicenter of clinical research, responsible for providing both clinical samples and annotated data. There is a need for large numbers of samples to provide statistical power to research studies, especially since treatment and diagnosis are becoming ever more personalized. A single biobank cannot provide sufficient numbers of samples to capture the full spectrum of any disease. Currently there is no infrastructure in the United Kingdom (UK) to integrate biobanks. Therefore the National Cancer Research Institute (NCRI) Confederation of Cancer Biobanks (CCB) Working Group 3 looked to establish a data standard to enable biobanks to communicate about the samples they hold and so facilitate the formation of an integrated national network of biobanks. The Working Group examined the existing data standards available to biobanks, such as the MIABIS standard, and compared these to the aims of the working group. The CCB-developed data standard has brought many improvements: (1) Where existing data standards have been developed, these have been incorporated, ensuring compatibility with other initiatives; (2) the standard was written with the expectation that it will be extended for specific disease areas, such as the Breast Cancer Campaign Tissue Bank (BCCTB) and the Strategic Tissue Repository Alliances Through Unified Methods (STRATUM) project; and (3) biobanks will be able to communicate about specific samples, as well as aggregated statistics. The development of this data standard will allow all biobanks to integrate and share information about the samples they hold, facilitating the possibility of a national portal for researchers to find suitable samples for research. In addition, the data standard will allow other clinical services, such as disease registries, to communicate with biobanks in a standardized format allowing for greater cross-discipline data sharing.