# Cancer Genetics Program

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $87,279

## Abstract

Cancer Genetics Program: Summary 
The overall mission of the Cancer Genetics (CG) Program is to conduct innovative basic and translational 
research on the genetics of cancer susceptibility, tumorigenesis, and disease progression. The CG Program 
themes bring together experts in advanced genomic, genetic, and computational analysis methods to identify 
abnormalities in genetic architectures that contribute to cancer pathogenesis. The goals of the CG Program are 
carried out through three themes: 
Theme 1: Determining the Impact of Germline Genetics on Cancer Susceptibility, Progression, Treatment 
Choices, and Response 
Theme 2: Exploiting Somatic Tumor Genomic Events for Precision Medicine Drug Development and Targeted 
Therapy 
Theme 3: Developing New Biological Insights and Combinatorial Therapies through Systems Views of Cancer 
CG Program: Key Metrics 
Membership (20 departments, 3 schools) 40 
Full 27 
Associate 13 
Cancer-relevant Funding (direct costs as of 
$20,450,174 
05/31/2017) 
NCI $8,976,865 44% 
Peer-reviewed $3,899,508 19% 
Non-peer-reviewed $7,573,801 37% 
Cancer-relevant Publications (1/2012-7/2017) 666 
Inter-programmatic 298 45% 
Intra-Programmatic 141 21% 
High-Impact 213 32% 
Accruals to Clinical Trials (2016) 0 0 
Therapeutic 0 0 
Other Interventional 0 0 
Non-interventional 0 0

## Key facts

- **NIH application ID:** 10406947
- **Project number:** 5P30CA082103-23
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** John S. Witte
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $87,279
- **Award type:** 5
- **Project period:** 1999-08-05 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406947

## Citation

> US National Institutes of Health, RePORTER application 10406947, Cancer Genetics Program (5P30CA082103-23). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10406947. Licensed CC0.

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