Unmet Need
In the U.S., there are an estimated 1,297,027 people living with blood cancers (leukemia, lymphoma or myeloma), with an additional 178,520 people expected to be diagnosed each year (see Leukemia & Lymphoma Society). Diagnostics tools that utilize next-generation sequencing (NGS) technologies are often performed to identify gene rearrangements that are indicative of blood cancers, a practice that is expected to become more routine due to the lower cost of sequencing and the precision that the method offers. As such, the global market for diagnosing blood cancers is the fastest growing area, as compared to the diagnosis of other types of cancers using NGS technologies, and is expected to grow from $135.7 million in 2019 to $595.2 at a 32.4% CAGR (see BCC Research). However, the process of analyzing NGS data and generating an actionable diagnostic decision remains a major barrier to the adoption of NGS-based blood cancer diagnostics due to its complexity and lack of standardization. Therefore, there is a strong need for automated tools that simplify the process of analyzing NGS data to inform the diagnosis of blood cancers.
Technology Overview
Researchers at Johns Hopkins have developed a web-based software tool that screens large next-generation sequencing (NGS) datasets to identify clonal B- and T-cell populations. The tool is particularly useful in a diagnostic setting, whereby the overwhelming presence of a clonal population indicates the presence of blood cancers. The software is capable of processing hundreds of samples in parallel and can, thereby, scale to meet the demands of researchers, clinical trial laboratories, and diagnostic laboratories. The tool’s user friendly interface and easy-to-interpret data outputs simplify the process of NGS analysis and may, therefore, accelerate the widespread adoption of NGS-based pipelines for diagnosing blood cancers.
Stage of Development
Web-based software is available online that identifies clonal B- and T-cell populations from NGS data. The specificity and sensitivity of the tool has been has been validated by the authors using two data sets. Software is currently in alpha stage development (validation) and additional features are being added.
Publication
Alpha version of tool is accessible at clone-retriever.herokuapp.com. Please contact JHTV or inventors for access.
