Perspectives and directions of biobanking in case of rare types of cancer

Biobanking is an actively developing area of biotechnology and biomedicine. Briefly, Biobank is a comprehensively characterised biological material collected and stored by standardized methods and accompanied by detailed corresponding information, potentially available to many users. Modern biobanks are instrumental for development of new diagnostic and therapeutic approaches, drug development, personalized medicine and many aspects of pre-clinical research. In part, this is because biobanks are not only «places of sample storage», but also places for conducting research using collections of biomedical materials and all associated data, as well as teaching/ learning hubs providing methodology training and guidance with experiment design to biobank’s clients (and here we emphasize the importance of the human resources component of biobanks – researchers and their unique expertise in biobanking, as an integral part of biobank). Biobanking makes possible to perform various “omics” studies, such as genomics, epigenomics, transcriptomics, proteomics, lipidomics, metabolomics, microbiomics and other “omics” data, and combine them with data obtained on complex 3D tissue culture models, ex-vivo cultures, “patient-like” organoids and “avatars”, data obtained from medical image biobanks, radiology biobanks, and others. Such studies can be longitudinal, recruit participants from several geographical regions and of different ethnicity, involve big data analysis using artificial intelligence, include both ante mortem and post mortem samples, samples collected at different time points of chemo- and/or radio-therapy, et cetera.
This review briefly describes the current state of biobanking and discusses the role of biobanks in the study of malignant neoplasms, with particular focus on the rare or poorly differentiated types of cancer (RPDC) and cancers of unkcnown primary (CUP). Unlike well-described types of cancer with known primary, there are cases of CUP when the primary sites of the appearance of cancer cells are not known, of them up to 25 percent are poorly differentiated, which significantly complicates histological typing of the tumor and selection of adequate therapy. Historically, poorly differentiated cancers have been excluded from many biospecimen collections. Rare cancers are malignant neoplasms with very low incidence, but despite low incidence they account to approximately 25 percent of all diagnosed cancers. There is a plethora of rare cancer types among Head and Neck cancers (HNC). In case of rare cancers, paucity of samples and sample-associated data, as well as slow accrual of the samples (so called “sample bottlenecks”) create significant drawbacks for translational oncologists. As a result, there are still significant inequalities in healthcare in case of RPDC/CUPs compared to common cancers, such as diagnosis uncertainty, limited therapies, drawbacks in the identification of novel therapeutic targets, and finally difficulties in conducting pre-clinical research and clinical trials, resulting in a survival gap between common cancers and RPDCs. Therefore, addressing these challenges is of utmost importance. Noteworthy, although rare subgroups of common cancers are not classified as rare cancers, patients belonging to such subgroups might face challenges similar to those affected by the rare cancers. Creating Rare and Poorly Differentiated Cancer Biobanks (RPDCB) and merging single biobanks into big consortia, as well as long-term sample collection in RPDCB, creates unique opportunity to use biobanking to study such diseases and can significantly facilitate research on their etiology and pathogenesis, drug development and therapy development, including personalized, targeted, and per-emptive therapies. In conclusion, there is an unmet need for creation of RPDCBs which should be addressed.
Key words: biobank, biobanking, head and neck cancer, malignant tumors, translational medicine, personalized medicine, oncology, extracellular matrix, 3D cell culture models
Conflicts of interest. The authors have no conflicts of interest to declare.
Acknowledgements. This study was made possible through the support of the Applied Genetics Resource Facility of MIPT (Support Grant 075-15-2021-684)
Funding. Supported by grants No18-15-00391-п, No21-15-00411.