A Blockchain-Based Dynamic Consent Architecture to Support Clinical Genomic Data Sharing (ConsentChain): Proof-of-Concept Study

Background In clinical genomics, sharing of rare genetic disease information between genetic databases and laboratories is essential to determine the pathogenic significance of variants to enable the diagnosis of rare genetic diseases. Significant concerns regarding data governance and security have reduced this sharing in practice. Blockchain could provide a secure method for sharing genomic data between involved parties and thus help overcome some of these issues. Objective This study aims to contribute to the growing knowledge of the potential role of blockchain technology in supporting the sharing of clinical genomic data by describing blockchain-based dynamic consent architecture to support clinical genomic data sharing and provide a proof-of-concept implementation, called ConsentChain, for the architecture to explore its performance. Methods The ConsentChain requirements were captured from a patient forum to identify security and consent concerns. The ConsentChain was developed on the Ethereum platform, in which smart contracts were used to model the actions of patients, who may provide or withdraw consent to share their data; the data creator, who collects and stores patient data; and the data requester, who needs to query and access the patient data. A detailed analysis was undertaken of the ConsentChain performance as a function of the number of transactions processed by the system. Results We describe ConsentChain, a blockchain-based system that provides a web portal interface to support clinical genomic sharing. ConsentChain allows patients to grant or withdraw data requester access and allows data requesters to query and submit access to data stored in a secure off-chain database. We also developed an ontology model to represent patient consent elements into machine-readable codes to automate the consent and data access processes. Conclusions Blockchains and smart contracts can provide an efficient and scalable mechanism to support dynamic consent functionality and address some of the barriers that inhibit genomic data sharing. However, they are not a complete answer, and a number of issues still need to be addressed before such systems can be deployed in practice, particularly in relation to verifying user credentials.

Integrated Pan-Cancer Analysis Reveals Distinct Clinical, Genomic and Immunological Features of the LILRB Immune Checkpoint Family in Acute Myeloid Leukemia

Background Leukocyte immunoglobulin (Ig)-like receptor Bs (LILRBs), a family of type I transmembrane glycoproteins, are known to inhibit immune activation. Methods We comprehensively evaluated the transcriptional levels and prognostic significances of LILRB members in a broad spectrum of cancer types, focusing on its role in AML. In addition, we systematically characterized the genomic and immune landscape in AML patients with altered LILRBs expression. Results Here, we show that LILRBs were significantly dysregulated in a number of cancers, especially in acute myeloid leukemia (AML). Clinically, high expression of LILRB1-LILRB4 predicted poor survival in six independent AML cohorts. Genetically, LILRB1 was associated with more mutational events than other LILRB members, and multiple genes involving in immune activation were deleted in LILRB1-high patients. Epigenetically, LILRB4 was significantly hypomethylated and marked by MLL-associated histone modifications in AML. Immunologically, LILRBs were positively associated with monocytic cells including M2 macrophages, but were negatively associated with tumor-suppressive CD8 T cells. Conclusions Our findings reveal critical immunological and clinical implications of LILRBs in AML, and indicate that LILRBs may represent promising targets for immunotherapy of AML.

PROMISE: a real-world clinical-genomic database to address knowledge gaps in prostate cancer

Purpose Prostate cancer is a heterogeneous disease with variable clinical outcomes. Despite numerous recent approvals of novel therapies, castration-resistant prostate cancer remains lethal. A “real-world” clinical-genomic database is urgently needed to enhance our characterization of advanced prostate cancer and further enable precision oncology. Methods The Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) is a consortium whose aims are to establish a repository of de-identified clinical and genomic patient data that are linked to patient outcomes. The consortium structure includes a (1) bio-informatics committee to standardize genomic data and provide quality control, (2) biostatistics committee to independently perform statistical analyses, (3) executive committee to review and select proposals of relevant questions for the consortium to address, (4) diversity/inclusion committee to address important clinical questions pertaining to racial disparities, and (5) patient advocacy committee to understand patient perspectives to improve patients’ quality of care. Results The PROMISE consortium was formed by 16 academic institutions in early 2020 and a secure RedCap database was created. The first patient record was entered into the database in April 2020 and over 1000 records have been entered as of early 2021. Data entry is proceeding as planned with the goal to have over 2500 patient records by the end of 2021. Conclusions The PROMISE consortium provides a powerful clinical-genomic platform to interrogate and address data gaps that have arisen with increased genomic testing in the clinical management of prostate cancer. The dataset incorporates data from patient populations that are often underrepresented in clinical trials, generates new hypotheses to direct further research, and addresses important clinical questions that are otherwise difficult to investigate in prospective studies.

To disclose, or not to disclose? Perspectives of clinical genomics professionals toward returning incidental findings from genomic research

Background Clinical genomic professionals are increasingly facing decisions about returning incidental findings (IFs) from genetic research. Although previous studies have shown that research participants are interested in receiving IFs, yet there has been an argument about the extent of researcher obligation to return IFs. We aimed in this study to explore the perspectives of clinical genomics professionals toward returning incidental findings from genomic research. Methods We conducted a national survey of a sample (n = 113) of clinical genomic professionals using a convenient sampling. A self-administered questionnaire was used to explore their attitudes toward disclosure of IFs, their perception of the duties to return IFs and identifying the barriers for disclosure of IFs. A descriptive analysis was employed to describe participants' responses. Results Sixty-five (57.5%) respondents had faced IFs in their practice and 31 (27.4%) were not comfortable in discussing IFs with their research subjects. Less than one-third of the respondents reported the availability of guidelines governing IFs. The majority 84 (80%) and 69 (62.7%) of the study participants indicated they would return the IFs if the risk of disease threat ≥ 50% and 6–49%, respectively and 36 (31.9%) reported they have no obligation to return IFs. Conclusion Clinical genomics professionals have positive attitudes and perceptions toward the returning IFs from genomic research, yet some revealed no duty to do so. Detailed guidelines must be established to provide insights into how genomics professionals should be handled IFs.

Clinical genomic profiling of novel grey zone lymphoma paired lesions with sequential central nervous system involvement in two adolescent patients

Not available.