Breast Cancer Research and Treatment

, Volume 132, Issue 3, pp 1025–1034 | Cite as

RecurrenceOnline: an online analysis tool to determine breast cancer recurrence and hormone receptor status using microarray data

  • Balázs Győrffy
  • Zsombor Benke
  • András Lánczky
  • Bálint Balázs
  • Zoltán Szállási
  • József Timár
  • Reinhold Schäfer
Preclinical study

Abstract

In the last decades, several gene expression-based predictors of clinical behavior were developed for breast cancer. A common feature of these is the use of multiple genes to predict hormone receptor status and the probability of tumor recurrence, survival or response to chemotherapy. We developed an online analysis tool to compute ER and HER2 status, Oncotype DX 21-gene recurrence score and an independent recurrence risk classification using gene expression data obtained by interrogation of Affymetrix microarray profiles. We implemented rigorous quality control algorithms to promptly exclude any biases related to sample processing, hybridization and scanning. After uploading the raw microarray data, the system performs the complete evaluation automatically and provides a report summarizing the results. The system is accessible online at http://www.recurrenceonline.com. We validated the system using data from 2,472 publicly available microarrays. The validation of the prediction of the 21-gene recurrence score was significant in lymph node negative patients (Cox-Mantel, P = 5.6E-16, HR = 0.4, CI = 0.32–0.5). A correct classification was obtained for 88.5% of ER- and 90.5% of ER + tumors (n = 1,894). The prediction of recurrence risk in all patients by using the mean of the independent six strongest genes (P < 1E-16, HR = 2.9, CI = 2.5–3.3), of the four strongest genes in lymph node negative ER positive patients (P < 1E-16, HR = 2.8, CI = 2.2–3.5) and of the three genes in lymph node positive patients (P = 3.2E-9, HR = 2.5, CI = 1.8–3.4) was highly significant. In summary, we integrated available knowledge in one platform to validate currently used predictors and to provide a global tool for the online determination of different prognostic parameters simultaneously using genome-wide microarrays.

Keywords

Survival analysis Breast cancer Prognosis Bioinformatics Microarray Recurrence score Recurrence risk Lymph node status 

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Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  • Balázs Győrffy
    • 1
    • 2
  • Zsombor Benke
    • 2
    • 3
  • András Lánczky
    • 2
    • 3
  • Bálint Balázs
    • 2
    • 3
  • Zoltán Szállási
    • 4
  • József Timár
    • 5
  • Reinhold Schäfer
    • 1
  1. 1.Laboratory of Functional Genomics, CharitéBerlinGermany
  2. 2.Research Laboratory for Pediatrics and NephrologyHungarian Academy of SciencesBudapestHungary
  3. 3.Pázmány Péter University, Faculty of Informatic TechnologyBudapestHungary
  4. 4.Children’s Hospital Informatics Program, Harvard Medical SchoolBostonUSA
  5. 5.2nd Department of PathologySemmelweis UniversityBudapestHungary

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