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High throughput sequencing (HTS) is increasingly important in determining cancer diagnoses, with subsequent prognostic and therapeutic implications. The biology of cancer is becoming increasingly deciphered and it is clear that therapy needs to be individually tailored. Whilst translational research plays an important role in lymphoid malignancies, few guidelines exist to guide biologists and routine laboratories through this constantly evolving field. In this article, we review the challenges of interpreting HTS in lymphoid malignancies and provide a toolkit to interpret single nucleotide variants obtained from HTS. We define the pre-analytical issues such as sequencing DNA obtained from formalin-fixed and paraffin-embedded tissue (FFPE), the acquisition of germline DNA, or the bioinformatic pitfalls, the analytical issues encountered and how to manage them. We describe the main constitutional and cancer databases, their characteristics and limitations, with an emphasis on variant interpretation in lymphoid malignancies. Finally, we discuss the challenges of predictions that one can make using in silico or in vitro modelling, pharmacogenomic screening, and the limits of those prediction tools. This description of the current status in genomic interpretation highlights the need for new large databases and international collaboration in the lymphoma field. [ABSTRACT FROM AUTHOR]

The use of digital technologies to conduct large-scale research with limited interaction (i.e. no in-person contact) and objective endpoints (i.e. biological testing) has significant potential for the field of epidemiology, but limited research to date has been published on the successes and challenges of such approaches. We analyzed data from a cohort study of sexual minority men across the United States, collected using digital strategies during a 10-month period from 2017 to 2018. Overall, 113,874 individuals were screened, of whom 26,000 were invited to the study, 10,691 joined the study, and 7,957 completed all enrollment steps, including return of a human immunodeficiency virus–negative sample. We examined group differences in completion of the steps towards enrollment to inform future research and found significant differences according to several factors, including age and race. This study adds to prior work to provide further proof-of-concept for this limited-interaction, technology-mediated methodology, highlighting some of its strengths and challenges, including rapid access to more diverse populations but also potential for bias due to differential enrollment. This method has strong promise, and future implementation research is needed to better understand the roles of burden, privacy, access, and compensation, to enhance representativeness and generalizability of the data generated. [ABSTRACT FROM AUTHOR]