About

Alice C. Fan is an Associate Professor of Medicine (Oncology) and, by courtesy, of Urology at Stanford University School of Medicine. Her research focuses on how turning off oncogenes can cause tumor regression, with clinical trials investigating the impact of tyrosine kinase inhibitors on the hypoxia pathway in kidney cancer and exploring the use of atorvastatin for certain non-Hodgkin's lymphomas. In her laboratory, she employs preclinical models of cancer to validate new nanotechnology strategies for tumor diagnosis and treatment, including the development of a nano-immunoassay (NIA) to measure drug efficacy in tumor cells from patients with leukemia, lymphoma, and myelodysplastic syndrome. Her translational research aims to advance early diagnostics, therapeutic monitoring, and response prediction in solid tumors such as kidney and lung cancers, with the goal of facilitating personalized medicine.

Research topics

• Medicine
• Internal medicine
• Nursing
• Medical emergency
• Surgery
• Psychology
• Medical physics
• Family medicine
• Engineering

Selected publications

• Supplementary Table S8 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S8: Comparison of lung cancer incidence between the LEAP cohort and the NLST, stratified by age at enrollment, sex, pack-year cigarette use and race.</p>

  PublisherDOI

• Supplementary Figure S1 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Figure S1: Map of participating study centers</p>

  PublisherDOI

• Supplementary Table S3 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S3: Characteristics of the nodules detected during the LEAP program for each screening timepoint.</p>

  PublisherDOI

• Supplementary Table S7 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S7: Lung cancers characteristics diagnosed during the active phase of the LEAP study based on the selection method for inclusion criteria: NLST criteria vs broadened criteria (≥ 20 pack-years, ≥ 50 years old, one additional lung cancer risk factor)</p>

  PublisherDOI

• Supplementary Table S2 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S2: Management procedures for positive screening tests within the LEAP cohort, all sites.</p>

  PublisherDOI

• Supplementary Table S1 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S1: Comparison of participants characteristics between the LEAP study and the NLST study</p>

  PublisherDOI

• Supplementary Table S5 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S5: Characteristics of screen-detected lung cancers and during follow-up in the LEAP cohort</p>

  PublisherDOI

• Supplementary Table S4 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S4: LDCT screening results in the LEAP cohort by centers</p>

  PublisherDOI

• Supplementary Table S6 from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <p>Supplementary Table S6: Analysis of LDCT screening results in the LEAP cohort based on the selection method for inclusion criteria: NLST criteria vs broadened criteria (≥ 20 pack-years, ≥ 50 years old, one additional lung cancer risk factor)</p>

  PublisherDOI

• Data from The LEAP Study: A Multicenter Biospecimen and Imaging Resource for Lung Cancer Screening

  2026-01-09

  articleOpen access

  <div>AbstractBackground:<p>Blood-based biomarkers could improve the effectiveness of lung cancer screening (LCS) with low-dose CT (LDCT) through more accurate lung cancer risk stratification and nodule malignancy risk assessment. The Lung Cancer, Early Detection, Assessment of Risk, and Prevention (LEAP) study aims to establish a reference set to validate promising cancer biomarkers in the context of LCS.</p>Methods:<p>This prospective international cohort study (United States, France, and Spain) enrolled individuals with elevated risk of developing lung cancer based on National Comprehensive Cancer Network Guidelines into an LCS program. Participants underwent three annual rounds of LDCT-LCS, with blood specimens collected at each time point. Questionnaires and medical chart reviews were utilized to determine participants’ cancers status.</p>Results:<p>Between 2014 and 2019, 2,841 participants were enrolled who underwent LDCT: 2,841 at baseline, 2,097 at year 1 (74%), and 1,779 at year 2 (63%). Rates at baseline, year 1, and year 2 were positive scans (13%, 7.5%, and 7.5%, respectively), false positives (12%, 6.8%, and 6.9%, respectively), and screen-detected lung cancer (0.9%, 0.9%, and 0.7%, respectively). After 5 years of follow-up, 74 lung cancer cases were detected: 55% stage I, 11% stage II, 16% stage III, and 12% stage IV. The LEAP biobank collected 6,586 blood specimens, including 126 (lung) and 201 (other) prediagnostic samples within 5 years of diagnosis.</p>Conclusions:<p>The LEAP cohort provides a resource with a longitudinal database of participant data, LDCT imaging, and matched blood specimens for biomarker validation, aiming to address unmet clinical needs in LCS.</p>Impact:<p>LEAP provides longitudinal biospecimens linked with clinical follow-up and LDCT imaging for biomarker validation in the context of imaging findings and lung cancer diagnosis.</p></div>

  PublisherDOI

Recent grants

• NIH Grant K23CA140722

  NIH · $867k · 2015

• Analysis of CTCs for Early Prediction of Response to Treatment in RCC

  NIH · $383k · 2014–2016

• NIH Grant U54CA199075

  NIH · $15.3M · 2022

Frequent coauthors

• Dean W. Felsher

  Stanford University

  78 shared

• Sandy Srinivas

  Stanford Medicine

  50 shared

• Heather A. Wakelee

  27 shared

• Sumit Shah

  26 shared

• Christian R. Hoerner

  Stanford University

  25 shared

• John T. Leppert

  Stanford Medicine

  25 shared

• Joel W. Neal

  23 shared

• Johanna C. Bendell

  Sarah Cannon

  21 shared

Labs

• Stanford Medicine OncologyPI

Education

• M.D.

  Stanford University

• B.S.

  University of California, Berkeley

Awards & honors

• Early Detection of Hereditary Renal Cancer (RCC) Pilot Grant…
• Career Development Award, ConquerCancer/ASCO (2016-2019)
• K23 Career Development Award, NIH/NCI (July 2010-June 2015)
• R21: Analysis of CTCs for Early Prediction of Response to Tr…
• Innovation Award, Stanford Cancer Institute (2014-2016)