Project Details
Projekt
Non-invasive framework for detection and stratification of Richter transformation by integrating genetic and epigenetic cell-free DNA features
Applicant
Dr. Lena Oßwald
Subject Area
Hematology, Oncology
Term
since 2025
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 570116408
Richter transformation (RT), the transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, remains a major clinical challenge. Diagnosis is frequently delayed due to reliance on invasive tissue biopsies; and conventional treatment regimens show poor efficacy, resulting in a median survival of only one year. Although several studies have investigated novel therapeutic approaches, effective treatment recommendations are still lacking, highlighting the urgent need for improved diagnostic and therapeutic strategies. Circulating tumor DNA (ctDNA) analysis is an emerging non-invasive diagnostic tool for malignancies, with a rapidly expanding range of clinical applications. So far, studies exploring ctDNA in RT remain limited. This project will evaluate and refine novel ctDNA-based approaches for the non-invasive detection, characterization, and therapeutic stratification of Richter transformation. We will utilize two innovative technologies developed by the host lab to analyze genetic and epigenetic features of cell-free DNA (cfDNA) from patients with RT: Cancer Personalized Profiling by deep Sequencing (CAPP-Seq), a targeted deep sequencing method that enables sensitive ctDNA detection and genotyping, and EPIC-Seq (epigenetic expression inference from cell-free DNA sequencing), a novel approach that infers gene expression profiles from cfDNA by analyzing chromatin fragmentation patterns and allows non-invasive tumor subtyping. Our first goal is to establish and validate a blood-based diagnostic framework that can robustly distinguish RT from CLL based on cfDNA molecular signatures. By overcoming the limitations of invasive tissue biopsies, this approach would significantly accelerate diagnosis and enable early treatment initiation. Additionally, using longitudinal plasma samples from RT patients, we will characterize genetic alterations and gene expression profiles both before and during treatment to gain insights into molecular mechanisms of disease progression and therapeutic resistance. In particular, we will focus on samples from RT patients enrolled in the RT1 trial, which evaluated a novel combination therapy of PD-1 blockade and BTK inhibition, yielding promising overall response rates. By correlating cfDNA-derived molecular features with clinical outcomes, we aim to develop a non-invasive stratification tool that predicts treatment response and prognosis. In conclusion, this project aims to advance the clinical management of Richter transformation by enhancing precision medicine approaches that enable early non-invasive detection and cfDNA-guided treatment recommendations, ultimately improving patient outcomes.
DFG Programme
WBP Fellowship
International Connection
USA
