The goal of the Cancer Epidemiology Program (CEP) is to improve our ability to prevent cancer and reduce its burden through new knowledge in surveillance, etiology, patterns of care, and survival, using an interdisciplinary approach. Special emphasis is placed on racial, ethnic, cultural, and other groups with an unequal burden of cancer. This research has been conducted primarily via large populationbased case-control and cohort studies in the ethnically diverse population of the San Francisco Bay Area, which includes Oakland and San Jose. Case-control studies typically collect demographic and exposure data, DNA from peripheral lymphocytes, and/or archived tumor samples. Cohort studies are based on follow-up of healthy individuals for cancer incidence (e.g., California Teachers Study), and of incident cases for cancer care, quality of life, and survival (e.g., CanCORS and Family Registries). Cancer sites of particular interest include breast, ovary, prostate, and lymphomas. This work has been facilitated and enhanced by the recent formal affiliation between Stanford University and the Northern California Cancer Center (NCCC). Some highlights of Program research include findings that oral contraceptive use is associated with reduced ovarian cancer risk and no elevation in breast cancer risk among carriers of BRCA1 mutations, that Helicobacter pylori infection is associated with reduced risk of esophageal cancer, that ethnic differences exist in use of alternative cancer therapies, and that choice of breastconserving surgery is related to socioeconomic status, immigration status and acculturation, and race/ethnicity. The Program adds value to the Cancer Center through its population-based study resources that provide a strong basis for developing important interdisciplinary collaborations and conducting translational research. Dr. Alice S. Whittemore and Dr. Esther M. John lead the Program, both senior cancer epidemiologists with extensive cancer research programs who have worked together for over 15 years. The CEP consists of 23 members, with direct cost funding of $20,220,819, including $6,463,763 in NCI funding. In the period from 2000 to the present, the average number of publications by Program members was 33 per year; of these, 40% were intra-programmatic and 14% were interprogrammatic. Future plans include expanding intra- and inter-programmatic interactions among investigators, identifying new research opportunities, and evaluating the feasibility of a data collection Shared Resource within the Cancer Center.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA124435-02
Application #
7623557
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2008-06-01
Budget End
2009-05-31
Support Year
2
Fiscal Year
2008
Total Cost
$20,368
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Malta, Tathiane M; Sokolov, Artem; Gentles, Andrew J et al. (2018) Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation. Cell 173:338-354.e15
Banerjee, Imon; Gensheimer, Michael Francis; Wood, Douglas J et al. (2018) Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives. Sci Rep 8:10037
Thorsson, Vésteinn; Gibbs, David L; Brown, Scott D et al. (2018) The Immune Landscape of Cancer. Immunity 48:812-830.e14
Rogers, Zoë N; McFarland, Christopher D; Winters, Ian P et al. (2018) Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice. Nat Genet 50:483-486
Nair, Viswam S; Sundaram, Vandana; Desai, Manisha et al. (2018) Accuracy of Models to Identify Lung Nodule Cancer Risk in the National Lung Screening Trial. Am J Respir Crit Care Med 197:1220-1223
She, Richard; Jarosz, Daniel F (2018) Mapping Causal Variants with Single-Nucleotide Resolution Reveals Biochemical Drivers of Phenotypic Change. Cell 172:478-490.e15
Champion, Magali; Brennan, Kevin; Croonenborghs, Tom et al. (2018) Module Analysis Captures Pancancer Genetically and Epigenetically Deregulated Cancer Driver Genes for Smoking and Antiviral Response. EBioMedicine 27:156-166
Zhou, Mu; Leung, Ann; Echegaray, Sebastian et al. (2018) Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications. Radiology 286:307-315
Pollom, Erqi L; Fujimoto, Dylann K; Han, Summer S et al. (2018) Newly diagnosed glioblastoma: adverse socioeconomic factors correlate with delay in radiotherapy initiation and worse overall survival. J Radiat Res 59:i11-i18
Nørgaard, Caroline Holm; Jakobsen, Lasse Hjort; Gentles, Andrew J et al. (2018) Subtype assignment of CLL based on B-cell subset associated gene signatures from normal bone marrow - A proof of concept study. PLoS One 13:e0193249

Showing the most recent 10 out of 322 publications