# Deep exploration of drivers, evolution, and microenvironment toward discovering principal themes in cancer

> **NIH NIH U24** · WASHINGTON UNIVERSITY · 2024 · $309,626

## Abstract

Summary/Abstract
Tremendous progress on cancer has been made at the molecular level over the past decade, largely due to
the broad application of high throughput, large-scale bulk whole genome, exome and RNA sequencing. In
particular, the discovery of numerous medium to high-penetrance drivers, characterization of pathogenic
germline variants, and the revelation of many-to-many relationships of genes and pathways, have brought a
fuller view of the combinatorial complexity of cancer. Indeed, newer technologies, like single-cell and spatial
genomics methods, are now augmenting bulk sequence data to power deeper studies of cancer dynamics,
such as heterogeneity, evolution, and interaction with the microenvironment. The current view is that such
advanced data, augmented by improved bioinformatics analysis tools and larger, well-curated cohorts will
enable medicine to push beyond statistical descriptions toward a genuine deterministic understanding of
cancer. Toward this goal, our proposal seeks to extend and apply established bioinformatics systems to
integrate the above technologies and leverage our broad range of capabilities and to support the NCI Genomic
Characterization Network (NCI-GCN) and Center for Cancer Genomics (CCG) via three specific aims: (1)
annotating and interpreting coding and non-coding somatic and germline alterations, (2) characterizing tumor
cell populations, evolution, and the tumor microenvironment, and (3) unlocking biological and clinical insights at
both the individual and cross-cancer (Pan-Cancer) levels to discern basic themes across the major human
cancers. Our approach involves fluencies in four areas of core competence outlined in the program RFA: DNA
mutations, long-read sequence analysis, scRNA-Seq analysis, and spatial genomics data analysis (with
connection to digital imaging analysis).

## Key facts

- **NIH application ID:** 10914880
- **Project number:** 5U24CA264010-04
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Li Ding
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $309,626
- **Award type:** 5
- **Project period:** 2021-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10914880

## Citation

> US National Institutes of Health, RePORTER application 10914880, Deep exploration of drivers, evolution, and microenvironment toward discovering principal themes in cancer (5U24CA264010-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10914880. Licensed CC0.

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