Optimizing Retrieval of Biospecimens Using the Curated Cancer Clinical Outcomes Database (C3OD)

To fully support their role in translational and personalized medicine, biorepositories and biobanks must continue to advance the annotation of their biospecimens with robust clinical and laboratory data. Translational research and personalized medicine require well-documented and up-to-date information, but the infrastructure used to support biorepositories and biobanks can easily be out of sync with the host institution. To assist researchers and provide them with accurate pathological, epidemiological, and bio-molecular data, the Biospecimen Repository Core Facility (BRCF) at the University of Kansas Medical Center (KUMC) merges data from medical records, the tumor registry, and pathology reports using the Curated Cancer Clinical Outcomes Database (C3OD). In this report, we describe the utilization of C3OD to optimally retrieve and dispense biospecimen samples using these 3 data sources and demonstrate how C3OD greatly increases the efficiency of obtaining biospecimen samples for the researchers.

Driving innovation through collaboration: development of clinical annotation datasets for brain cancer biobanking

Background

A key component of cancer research is the availability of clinical samples with appropriately annotated clinical data. Biobanks facilitate research by collecting/storing various types of clinical samples for research. Brain Cancer Biobanking Australia (BCBA) was established to facilitate the networking of brain cancer biobanking operations Australia-wide. Maximizing biospecimen utility in a networked biobanking environment requires the standardization of procedures and data across different sites. The aim of this research was to scope and develop a recommended clinical annotation dataset both for pediatric and adult brain cancer biobanks.

Methods

A multidisciplinary working group consisting of members from the BCBA Consortium was established to develop clinical dataset recommendations for brain cancer biobanks. A literature search was undertaken to identify any published clinical dataset recommendations for brain cancer biobanks. An audit of data items collected and stored by BCBA member biobanks was also conducted to survey current clinical data collection practices across the BCBA network.

Results

BCBA has developed a clinical annotation dataset recommendation for pediatric and adult brain cancer biobanks. The clinical dataset recommendation has 5 clinical data categories: demographic, clinical and radiological diagnosis and surgery, neuropathological diagnosis, patient treatment, and patient follow-up. The data fields have been categorized into 1 of 3 tiers; essential, preferred, and comprehensive. This enables biobanks and researchers to prioritize appropriately where resources are limited.

Conclusion

This dataset can be used to guide the integration of data from multiple existing biobanks for research studies and for planning prospective brain cancer biobanking activities.

Germline Missense Variants in BRCA1: New Trends and Challenges for Clinical Annotation

Genetic testing allows for the identification of germline DNA variations, which are associated with a significant increase in the risk of developing breast cancer (BC) and ovarian cancer (OC). Detection of a BRCA1 or BRCA2 pathogenic variant triggers several clinical management actions, which may include increased surveillance and prophylactic surgery for healthy carriers or treatment with the PARP inhibitor therapy for carriers diagnosed with cancer. Thus, standardized validated criteria for the annotation of BRCA1 and BRCA2 variants according to their pathogenicity are necessary to support clinical decision-making and ensure improved outcomes. Upon detection, variants whose pathogenicity can be inferred by the genetic code are typically classified as pathogenic, likely pathogenic, likely benign, or benign. Variants whose impact on function cannot be directly inferred by the genetic code are labeled as variants of uncertain clinical significance (VUS) and are evaluated by multifactorial likelihood models that use personal and family history of cancer, segregation data, prediction tools, and co-occurrence with a pathogenic BRCA variant. Missense variants, coding alterations that replace a single amino acid residue with another, are a class of variants for which determination of clinical relevance is particularly challenging. Here, we discuss current issues in the missense variant classification by following a typical life cycle of a BRCA1 missense variant through detection, annotation and information dissemination. Advances in massively parallel sequencing have led to a substantial increase in VUS findings. Although the comprehensive assessment and classification of missense variants according to their pathogenicity remains the bottleneck, new developments in functional analysis, high throughput assays, data sharing, and statistical models are rapidly changing this scenario.

Impact of amino acid substitutions at secondary structures in the BRCT domains of the tumor suppressor BRCA1: Implications for clinical annotation

Genetic testing for BRCA1, a DNA repair protein, can identify carriers of pathogenic variants associated with a substantially increased risk for breast and ovarian cancers. However, an association with increased risk is unclear for a large fraction of BRCA1 variants present in the human population. Most of these variants of uncertain clinical significance lead to amino acid changes in the BRCA1 protein. Functional assays are valuable tools to assess the potential pathogenicity of these variants. Here, we systematically probed the effects of substitutions in the C terminus of BRCA1: the N- and C-terminal borders of its tandem BRCT domain, the BRCT-[N-C] linker region, and the α1 and α'1 helices in BRCT-[N] and -[C]. Using a validated transcriptional assay based on a fusion of the GAL4 DNA-binding domain to the BRCA1 C terminus (amino acids 1396-1863), we assessed the functional impact of 99 missense variants of BRCA1. We include the data obtained for these 99 missense variants in a joint analysis to generate the likelihood of pathogenicity for 347 missense variants in BRCA1 using VarCall, a Bayesian integrative statistical model. The results from this analysis increase our understanding of BRCA1 regions less tolerant to changes, identify functional borders of structural domains, and predict the likelihood of pathogenicity for 98% of all BRCA1 missense variants in this region recorded in the population. This knowledge will be critical for improving risk assessment and clinical treatment of carriers of BRCA1 variants.

Integrating massively parallel sequencing into diagnostic workflows and managing the annotation and clinical interpretation challenge

Massively parallel sequencing has become a powerful tool for the clinical management of patients with applications in diagnosis, guidance of treatment, prediction of drug response, and carrier screening. A considerable challenge for the clinical implementation of these technologies is the management of the vast amount of sequence data generated, in particular the annotation and clinical interpretation of genomic variants. Here, we describe annotation steps that can be automated and common strategies employed for variant prioritization. The definition of best practice standards for variant annotation and prioritization is still ongoing; at present, there is limited consensus regarding an optimal clinical sequencing pipeline. We provide considerations to help define these. For the first time, clinical genetics and genomics is not limited by our ability to sequence, but our ability to clinically interpret and use genomic information in health management. We argue that the development of standardized variant annotation and interpretation approaches and software tools implementing these warrants further support. As we gain a better understanding of the significance of genomic variation through research, patients will be able to benefit from the full scope that these technologies offer.