Differentiation and classification of the most common types of indolent and aggressive lymphoma by gene expression inference

• Applicant: Dr. Jurik Mutter
• Subject Area: Hematology, Oncology
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 521387290

In general, lymphomas consist of a group of highly diverse tumors, for which an accurate diagnosis is essential because treatment of the different lymphoma subtypes is fundamentally different. The broadest way of describing different lymphoma subtypes is the division into indolent, slow-growing lymphoma e.g., FL and SLL, and aggressive, fast-growing lymphoma e.g., DLBCL and MCL, all requiring distinct types and a varying amount of clinical attention. Liquid biopsy is an emerging non-invasive tool that uses different types of body fluids including blood and can provide easy access to genetic and epigenetic information. Moreover, Epigenetic Expression Inference from Cell-free DNA Sequencing (EPIC-Seq) is a newly proposed method to infer gene expression based on the fragmentation pattern of those genes, which can also be conducted from liquid biopsy analytes. This approach utilizes the fact that more frequently expressed, active genes are less protected against cleavage by endonucleases and show therefore a more diverse and random cleavage pattern. On the contrary, inactive genes that are less frequently expressed tend to be more protected by nucleosomes and exhibit therefore a more uniform fragmentation diversity. This is measured by a new metric called promotor fragmentation entropy (PFE) and has been shown to be able to reliably distinct lung adenocarcinoma and squamous cell carcinoma subclassify and differentiate DLBCL cell of origin (COO) with high accuracy, showing the potential clinical applicability of EPIC-Seq. In the proposed project, we will further examine the applicability and potential use of EPIC-Seq for distinguishing the most common indolent and aggressive lymphomas in a multi-histology setting and try to predict the transformation from indolent FL to aggressive tFL. This will be extensively examined by firstly designing and validating a lymphoma specific targeted sequencing panel optimized for the use with EPIC-Seq by identifying frequently and highly expressed genes in the most common lymphoma types such as DLBCL, MCL, FL and SLL. Secondly, the selector panel will be used to test for genetic subtypes of DLBCL while examining the multi-histology classification between lymphoma patients and try to distinguish those with different lymphoma types. Lastly, EPIC-Seq will be used to retrospectively investigate multiple patient samples over time and explore its potential for the early prediction of relapses, therapeutic resistance mechanisms, and transforming indolent FL. Taken together, EPIC-Seq is a promising non-invasive method for certain clinical questions, but its capability needs to be further investigated. If successful, this could change routine clinical assessment for lymphoma diagnosis, transformation prediction and relapse monitoring.

• DFG Programme: WBP Fellowship
• International Connection: USA
• Host: Professor Arash Ash Alizadeh, Ph.D.