Related Experiment Video
Updated: Feb 14, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Tumor PIK3CA Genotype and Prognosis in Early-Stage Breast Cancer: A Pooled Analysis of Individual Patient Data
Dimitrios Zardavas1, Luc Te Marvelde1, Roger L Milne1
1Dimitrios Zardavas and Debora Fumagalli, Breast International Group; Christos Sotiriou, Université Libre de Bruxelles, Brussels, Belgium; Luc te Marvelde and Roger L. Milne, Cancer Council; Roger L. Milne and Sherene Loi, University of Melbourne, Melbourne; Barry Iacopetta, University of Western Australia, Western Australia; Sandra O'Toole and Elena Lopez-Knowles, Garvan Institute of Medical Research, Darlinghurst, Australia; George Fountzilas and Vassiliki Kotoula, Hellenic Foundation for Cancer Research/Aristotle University of Thessaloniki, Thessaloniki; Evangelia Razis, Hygeia Hospital; George Papaxoinis, Hippokration Hospital, Athens, Greece; Heikki Joensuu, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; Mary Ellen Moynahan, Memorial Sloan Kettering Cancer Center, New York, NY; Bryan T. Hennessy, Beaumont Hospital and Royal College of Surgeons, Dublin, Ireland; Ivan Bieche, Curie Institut, Paris; Thomas Bachelot, Centre de Recherche en Cancérologie de Lyon, Lyon; Stefan Michiels, Gustave Roussy and Inserm, Univ. Paris-Sud, Univ. Paris-Saclay, Villejuif, France; Lao H. Saal, Lund University, Lund; Olle Stal, Qing Wang, and Gizeh Perez-Tenorio, Linköping University, Linköping, Sweden; Jeanette Dupont Jensen, University of Southern Denmark, on behalf of the Danish Breast Cancer Cooperative Group, Odense, Denmark; Elena Lopez-Knowles, Royal Marsden NHS Trust and Institute of Cancer Research, London; Daniel W. Rea, University of Birmingham, Birmingham, United Kingdom; Mattia Barbaraeschi, Santa Chiara Hospital, Trento, Italy; Shinzaburo Noguchi, Osaka University, Osaka Japan; Hatem A. Azim Jr, American University of Beirut (AUB), Beirut, Lebanon; Enrique Lerma, Universitat Autònoma de Barcelona, Barcelona, Spain; Cornelis J.H. can de Velde, Leiden University Medical Center, Leiden, the Netherlands; Vicky Sabine, University of Guelph, Guelph; John M.S. Bartlett, Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
Abstract:
Purpose Phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit alpha ( PIK3CA) mutations are frequently observed in primary breast cancer. We evaluated their prognostic relevance by performing a pooled analysis of individual patient data. Patients and Methods Associations between PIK3CA status and clinicopathologic characteristics were tested by applying Cox regression models adjusted for age, tumor size, nodes, grade, estrogen receptor (ER) status, human epidermal growth factor receptor 2 (HER2) status, treatment, and study. Invasive disease-free survival (IDFS) was the primary end point; distant disease-free survival (DDFS) and overall survival (OS) were also assessed, overall and by breast cancer subtypes. Results Data from 10,319 patients from 19 studies were included (median OS follow-up, 6.9 years); 1,787 patients (17%) received chemotherapy, 4,036 (39%) received endocrine monotherapy, 3,583 (35%) received both, and 913 (9%) received none or their treatment was unknown. PIK3CA mutations occurred in 32% of patients, with significant associations with ER positivity, increasing age, lower grade, and smaller size (all P < .001). Prevalence of PIK3CA mutations was 18%, 22%, and 37% in the ER-negative/HER2-negative, HER2-positive, and ER-positive/HER2-negative subtypes, respectively. In univariable analysis, PIK3CA mutations were associated with better IDFS (HR, 0.77; 95% CI, 0.71 to 0.84; P < .001), with evidence for a stronger effect in the first years of follow-up (0 to 5 years: HR, 0.73; 95% CI, 0.66 to 0.81; P < .001; 5 to 10 years: HR, 0.82; 95% CI, 0.68 to 0.99; P = .037); > 10 years: (HR, 1.15; 95% CI, 0.84 to 1.58; P = .38; P heterogeneity = .02). In multivariable analysis, PIK3CA genotype remained significant for improved IDFS ( P = .043), but not for the DDFS and OS end points. Conclusion In this large pooled analysis, PIK3CA mutations were significantly associated with a better IDFS, DDFS, and OS, but had a lesser prognostic effect after adjustment for other prognostic factors.
Related Concept Videos
Analysis of Population Pharmacokinetic Data
Data Reporting and Recording
Impact of Individuals on Individuals
Cancer Stem Cells and Tumor Maintenance
Cancer stem cells are thought to originate from tissue-specific normal stem cells or progenitor cells. The normal stem cells usually reside in...
Cancer Survival Analysis
Overview of Microsoft Excel as a Data Analysis Tool

