# Generating an atlas of Richter's Syndrome: from molecular understanding to outcome prediction, detection and monitoring > **NIH NIH P01** · DANA-FARBER CANCER INST · 2024 · $369,858 ## Abstract Project Summary: Recent therapeutic advances have dramatically improved patient outcomes in chronic lymphocytic leukemia (CLL). However, Richter's Syndrome (RS), which is the transformation of CLL to an aggressive lymphoma (that occurs in 0.5-1% of CLL patients annually), is often refractory to existing therapeutic approaches. Building on the success of our current P01 in creating the world's largest map of genetic drivers and subtypes of CLL (n=~1100) and using it to build prognostic models, this renewal application seeks to apply similar (and new) approaches to comprehensively map the genetic underpinnings of RS. Currently, and in contrast to CLL, little is known about the genetics, clonal composition, drivers and cell circuitry of RS, and hence there is neither a framework for molecularly based risk stratification nor targets for therapeutic development. Therefore, understanding the molecular (genetic, epigenetic and proteomic) underpinnings of the transformation from CLL to RS will create opportunities for more effective therapeutic interventions, prediction of response, and potentially early detection, all with the goal of improving patient outcome. To achieve these goals, we propose to: (1) Define the drivers of RS and delineate the relationship of RS to CLL and DLBCL. Using whole-exome and RNA sequencing, we will study the genetic and transcriptomic landscape of >300 RS cases, including analyzing their pre-transformation CLL and RS samples. We will then further delineate the genetic relationship between CLL and RS using whole-genome sequencing of a subset of cases, and chart their epigenetic landscape using chromatin and histone methylation profiling. Moreover, we will trace the evolution of the CLL cells to RS and determine distinct patterns of genetic, epigenetic, and transcriptomic states at a single-cell resolution. Finally, we will combine these data to identify molecular subtypes of RS and associate them with outcome. (2) Define the changes in cellular circuitry associated with transformation from CLL to RS. We will use the power of microscaled proteomic and phosphoproteomic analysis to identify changes in the wiring of cellular processes associated with transformation to RS and create a comprehensive proteomic map of RS. We will identify deregulated signaling pathways and potential therapeutic targets. Finally, we will integrate the proteomic data to refine the molecular subtypes identified above as well as develop a high-throughput proteomic assay for detecting biomarkers of these subtypes and validate them in an independent set of RS patients. (3) Develop a non-invasive tool for RS detection and monitoring. Building on our understanding of the RS genome, we will build a robust and inexpensive cell-free DNA assay based on low-pass whole-genome sequencing aimed at detecting RS-specific alterations in plasma samples. We will test whether we can detect RS clones in patients' blood to monitor the emergence, progression and relapse of R... ## Key facts - **NIH application ID:** 10912489 - **Project number:** 5P01CA206978-09 - **Recipient organization:** DANA-FARBER CANCER INST - **Principal Investigator:** GAD A GETZ - **Activity code:** P01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $369,858 - **Award type:** 5 - **Project period:** 2016-09-01 → 2026-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10912489 ## Citation > US National Institutes of Health, RePORTER application 10912489, Generating an atlas of Richter's Syndrome: from molecular understanding to outcome prediction, detection and monitoring (5P01CA206978-09). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10912489. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*