# Discovery of clinically distinct CLL subgroups by integrative mapping of large-scale CLL genetic, expression and clinical data

> **NIH NIH P01** · DANA-FARBER CANCER INST · 2020 · $331,617

## Abstract

Project Summary
By creating seminal tools for the computational analysis of massively parallel sequencing data, the Getz group
has generated vital pipelines and the analysis framework for large-scale processing and systematic analysis of
cancer genome datasets. Through collaborations with an international network of investigators, we have
gathered whole-exome, matched transcriptome, and methylome data from >1000 CLL patients. Through
saturation analysis and statistical modeling, we have calculated this collection of samples to provide sufficient
statistical power to detect all intermediate and high frequency genetic drivers of this disease (94% power to
detect events in >2% of patients), based on the background mutation frequency of CLLs. The goals of our
analyses are to: (1) Build a comprehensive catalog of all genetic and epigenetic drivers of CLL and
their interdependencies, both clonal and subclonal, integrating information on somatic point mutations, copy-
number changes, and DNA methylation; (2) Integrate all genomic data modalities to identify molecular
subtypes of CLL and associate with drivers, cellular processes and cancer hallmarks; and (3) Develop new
models to predict outcome based on the genomic map of CLL subtypes. Designing a framework and tools to
maximize our understanding of the relevant genetic and epigenetic determinants of CLL development and
response to treatment is the focus of this project. These results and framework will generate a valuable
resource for the CLL and the broader cancer community.

## Key facts

- **NIH application ID:** 10005157
- **Project number:** 5P01CA206978-05
- **Recipient organization:** DANA-FARBER CANCER INST
- **Principal Investigator:** GAD A GETZ
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $331,617
- **Award type:** 5
- **Project period:** 2016-09-01 → 2021-09-16

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10005157

## Citation

> US National Institutes of Health, RePORTER application 10005157, Discovery of clinically distinct CLL subgroups by integrative mapping of large-scale CLL genetic, expression and clinical data (5P01CA206978-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10005157. Licensed CC0.

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