Biobank literature update week 33 (2015)
[1] Semi-automated biobank sample processing with a 384 high density sample tube robot used in cancer and
cardiovascular studies. Malm J, Lindberg H, Erlinge D et al. Clinical and translational medicine 2015; 4:67.
BACKGROUND: In the postgenomic era, it has become evident that analysis of genetic and protein expression
changes alone is not sufficient to understand most disease processes in e.g. cardiovascular and cancer disease.
Biobanking has been identified as an important area for development and discovery of better diagnostic tools and
new treatment modalities. Biobanks are developed in order to integrate the collection of clinical samples from both
healthy individuals and patients and provide valuable information that will make possible improved patient care.
Modern healthcare developments are intimately linked to information based on studies of patient samples from
biobank archives in large scale studies. Today biobanks form important national, as well as international, networks
that share and combine global resources. METHODS: We have developed and validated a novel biobanking workflow
process that utilizes 384-tube systems with a high speed sample array robot with unique processing principles.
RESULTS: The 384-tube format and robotic processing is incorporated into a cancer and cardiovascular
diagnostic/prognostic research program with therapeutic interventions. Our biobank practice has gained acceptance
within many hospitals and research units and is based on high-density sample storage with small aliquot sample
volumes. The previous standard of 5-10 mL sample volume tubes is being replaced by smaller volumes of 50-70 muL
blood fractions that typically result in hundreds of thousands of aliquot fractions in 384-tube systems. CONCLUSIONS:
Our novel biobanking workflow process is robust and well suited for clinical studies.
[2] How well do whole exome sequencing results correlate with medical findings? A study of 89 Mayo Clinic Biobank
samples. Middha S, Lindor NM, McDonnell SK et al. Frontiers in genetics 2015; 6:244. Whole exome sequencing
(WES) is increasingly being used for diagnosis without adequate information on predictive characteristics of
reportable variants typically found on any given individual and correlation with clinical phenotype. In this study, we
performed WES on 89 deceased individuals (mean age at death 74 years, range 28-93) from the Mayo Clinic Biobank.
Significant clinical diagnoses were abstracted from electronic medical record via chart review. Variants [Single
Nucleotide Variant (SNV) and insertion/deletion] were filtered based on quality (accuracy >99%, read-depth >20,
alternate-allele read-depth >5, minor-allele-frequency <0.1) and available HGMD/OMIM phenotype information.
Variants were defined as Tier-1 (nonsense, splice or frame-shifting) and Tier-2 (missense, predicted-damaging) and
evaluated in 56 ACMG-reportable genes, 57 cancer-predisposition genes, along with examining overall genotypephenotype correlations. Following variant filtering, 7046 total variants were identified (~79/person, 644 Tier-1, 6402
Tier-2), 161 among 56 ACMG-reportable genes (~1.8/person, 13 Tier-1, 148 Tier-2), and 115 among 57 cancerpredisposition genes (~1.3/person, 3 Tier-1, 112 Tier-2). The number of variants across 57 cancer-predisposition
genes did not differentiate individuals with/without invasive cancer history (P > 0.19). Evaluating genotypephenotype correlations across the exome, 202(3%) of 7046 filtered variants had some evidence for phenotypic
correlation in medical records, while 3710(53%) variants had no phenotypic correlation. The phenotype associated
with the remaining 44% could not be assessed from a typical medical record review. These data highlight significant
continued challenges in the ability to extract medically meaningful predictive results from WES.
[3] A semiquantitative metric for evaluating clinical actionability of incidental or secondary findings from genomescale sequencing. Berg JS, Foreman AK, O'Daniel JM et al. Genetics in medicine : official journal of the American
College of Medical Genetics 2015. PURPOSE: As genome-scale sequencing is increasingly applied in clinical scenarios,
a wide variety of genomic findings will be discovered as secondary or incidental findings, and there is debate about
how they should be handled. The clinical actionability of such findings varies, necessitating standardized frameworks
for a priori decision making about their analysis. METHODS: We established a semiquantitative metric to assess five
elements of actionability: severity and likelihood of the disease outcome, efficacy and burden of intervention, and
knowledge base, with a total score from 0 to 15. RESULTS: The semiquantitative metric was applied to a list of
putative actionable conditions, the list of genes recommended by the American College of Medical Genetics and
Genomics (ACMG) for return when deleterious variants are discovered as secondary/incidental findings, and a
random sample of 1,000 genes. Scores from the list of putative actionable conditions (median = 12) and the ACMG
list (median = 11) were both statistically different than the randomly selected genes (median = 7) (P < 0.0001, two-
Biobank literature update week 33 (2015)
tailed Mann-Whitney test). CONCLUSION: Gene-disease pairs having a score of 11 or higher represent the top
quintile of actionability. The semiquantitative metric effectively assesses clinical actionability, promotes
transparency, and may facilitate assessments of clinical actionability by various groups and in diverse contexts.Genet
Med advance online publication 13 August 2015Genetics in Medicine (2015); doi:10.1038/gim.2015.104.
[4] A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience. Kraus WE, Granger CB, Sketch MH,
Jr. et al. Journal of cardiovascular translational research 2015. The CATHeterization GENetics (CATHGEN)
biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010,
we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples
were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke
Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date,
race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at
catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations
included interim information: vital status (verified via National Death Index search and supplemented by Social
Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization
procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular
data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.
[5] Proposed Ebola biobank would strengthen African science. Check Hayden E. Nature 2015; 524:146-147.
[6] Establishment and management of a lung cancer biobank in Eastern China. Yu K, Zhang J, Li X et al. Thoracic cancer
2015; 6:58-63. BACKGROUND: The prevalence of lung cancer, a highly complex neoplasm, increases annually. Thus, a
lung cancer biobank, which stores lung cancer tissue and blood matched according to standard methods, is needed
to advance lung cancer research and develop promising therapies. METHODS: To accomplish this aim, we
implemented standardized procedures for tissue samples and patient information acquired from consenting donors.
The banked tissue includes blood, pleural effusions, and surgical resection samples. An independent information
management system was used to match samples and collect data, including clinical cancer manifestation, laboratory
tests, and de-identified data about cancer patients. RESULTS: From 2009 to 2013, more than 2000 lung cancer cases
were collected. At this time, we have more than 10 000 biological samples stored in our biobank. DNA, ribonucleic
acid (RNA), and protein quality were confirmed to be appropriate for clinical and basic research. CONCLUSION: Our
standardized, large-scale lung cancer biobank offers high quality cancer research samples for China and the world.
[7] Challenges for quality management in implementation, maintenance, and sustainability of research tissue
biobanks. Schmitt S, Kynast K, Schirmacher P, Herpel E. Virchows Archiv : an international journal of pathology 2015.
Availability of high-quality human tissue samples and access to associated histopathological and clinical data is
essential for basic and translational biomedical research, especially in areas of personalized medicine, drug, and
biomarker development and mechanistically oriented biomedical research projects. Therefore, it is pivotal to
establish and maintain quality-assured tissue biobanks that provide high-quality biomaterial to research thereby
increasing the impact and reliability of scientific results. Quality concerns do not only address the biomaterial
specimen itself but include all biobanking-related procedures. Tissue biobanks thus face essential challenges that
encompass the implementation of adequate structural components, documentation of tissue sample collection and
storage (procedures), as well as data and project management and IT. An integral and indispensable component of
tissue biobanks is expert-driven evaluation (entry and exit controls) of tissue specimen to guarantee provision of
high-quality assured biomaterials.