IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0086511.html
   My bibliography  Save this article

Accurate Data Processing Improves the Reliability of Affymetrix Gene Expression Profiles from FFPE Samples

Author

Listed:
  • Maurizio Callari
  • Antonio Lembo
  • Giampaolo Bianchini
  • Valeria Musella
  • Vera Cappelletti
  • Luca Gianni
  • Maria Grazia Daidone
  • Paolo Provero

Abstract

Formalin fixed paraffin-embedded (FFPE) tumor specimens are the conventionally archived material in clinical practice, representing an invaluable tissue source for biomarkers development, validation and routine implementation. For many prospective clinical trials, this material has been collected allowing for a prospective-retrospective study design which represents a successful strategy to define clinical utility for candidate markers. Gene expression data can be obtained even from FFPE specimens with the broadly used Affymetrix HG-U133 Plus 2.0 microarray platform. Nevertheless, important major discrepancies remain in expression data obtained from FFPE compared to fresh-frozen samples, prompting the need for appropriate data processing which could help to obtain more consistent results in downstream analyses. In a publicly available dataset of matched frozen and FFPE expression data, the performances of different normalization methods and specifically designed Chip Description Files (CDFs) were compared. The use of an alternative CDFs together with fRMA normalization significantly improved frozen-FFPE sample correlations, frozen-FFPE probeset correlations and agreement of differential analysis between different tumor subtypes. The relevance of our optimized data processing was assessed and validated using two independent datasets. In this study we demonstrated that an appropriate data processing can significantly improve the reliability of gene expression data derived from FFPE tissues using the standard Affymetrix platform. Tools for the implementation of our data processing algorithm are made publicly available at http://www.biocut.unito.it/cdf-ffpe/.

Suggested Citation

  • Maurizio Callari & Antonio Lembo & Giampaolo Bianchini & Valeria Musella & Vera Cappelletti & Luca Gianni & Maria Grazia Daidone & Paolo Provero, 2014. "Accurate Data Processing Improves the Reliability of Affymetrix Gene Expression Profiles from FFPE Samples," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    • Handle: RePEc:plo:pone00:0086511
    DOI: 10.1371/journal.pone.0086511
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0086511
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0086511&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0086511?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Charles M. Perou & Therese Sørlie & Michael B. Eisen & Matt van de Rijn & Stefanie S. Jeffrey & Christian A. Rees & Jonathan R. Pollack & Douglas T. Ross & Hilde Johnsen & Lars A. Akslen & Øystein Flu, 2000. "Molecular portraits of human breast tumours," Nature, Nature, vol. 406(6797), pages 747-752, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Xi & Hoadley, Katherine A. & Hannig, Jan & Marron, J.S., 2023. "Jackstraw inference for AJIVE data integration," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    2. Manish G & Anil Kumar Badana & Rama Rao Malla, 2017. "Emerging Diagnostic and Prognostic Biomarkers of Triple Negative Breast Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 1(3), pages 561-565, August.
    3. Jacob Elnaggar & Fern Tsien & Lucio Miele & Chindo Hicks & Clayton Yates & Melisa Davis, 2019. "An Integrative Genomics Approach for Associating Genetic Susceptibility with the Tumor Immune Microenvironment in Triple Negative Breast Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 15(1), pages 1-12, February.
    4. María Elena Martínez & Jonathan T Unkart & Li Tao & Candyce H Kroenke & Richard Schwab & Ian Komenaka & Scarlett Lin Gomez, 2017. "Prognostic significance of marital status in breast cancer survival: A population-based study," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    5. Yishai Shimoni, 2018. "Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-15, February.
    6. Marcin Pilarczyk & Mehdi Fazel-Najafabadi & Michal Kouril & Behrouz Shamsaei & Juozas Vasiliauskas & Wen Niu & Naim Mahi & Lixia Zhang & Nicholas A. Clark & Yan Ren & Shana White & Rashid Karim & Huan, 2022. "Connecting omics signatures and revealing biological mechanisms with iLINCS," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    7. Junhee Seok & Ronald W Davis & Wenzhong Xiao, 2015. "A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-15, May.
    8. Qing Qu & Yan Mao & Xiao-chun Fei & Kun-wei Shen, 2013. "The Impact of Androgen Receptor Expression on Breast Cancer Survival: A Retrospective Study and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    9. Bourret, Pascale & Keating, Peter & Cambrosio, Alberto, 2011. "Regulating diagnosis in post-genomic medicine: Re-aligning clinical judgment?," Social Science & Medicine, Elsevier, vol. 73(6), pages 816-824, September.
    10. G. Gambardella & G. Viscido & B. Tumaini & A. Isacchi & R. Bosotti & D. di Bernardo, 2022. "A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    11. Yoo-Ah Kim & Stefan Wuchty & Teresa M Przytycka, 2011. "Identifying Causal Genes and Dysregulated Pathways in Complex Diseases," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-13, March.
    12. Pauliina M. Munne & Lahja Martikainen & Iiris Räty & Kia Bertula & Nonappa & Janika Ruuska & Hanna Ala-Hongisto & Aino Peura & Babette Hollmann & Lilya Euro & Kerim Yavuz & Linda Patrikainen & Maria S, 2021. "Compressive stress-mediated p38 activation required for ERα + phenotype in breast cancer," Nature Communications, Nature, vol. 12(1), pages 1-17, December.
    13. Radhakrishnan Nagarajan & Marco Scutari, 2013. "Impact of Noise on Molecular Network Inference," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    14. R Joseph Bender & Feilim Mac Gabhann, 2013. "Expression of VEGF and Semaphorin Genes Define Subgroups of Triple Negative Breast Cancer," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    15. Marron, J.S., 2017. "Big Data in context and robustness against heterogeneity," Econometrics and Statistics, Elsevier, vol. 2(C), pages 73-80.
    16. Deepak Poduval & Zuzana Sichmanova & Anne Hege Straume & Per Eystein Lønning & Stian Knappskog, 2020. "The novel microRNAs hsa-miR-nov7 and hsa-miR-nov3 are over-expressed in locally advanced breast cancer," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-23, April.
    17. Mariana Segovia-Mendoza & Margarita Isabel Palacios-Arreola & Luz María Monroy-Escamilla & Alexandra Estela Soto-Piña & Karen Elizabeth Nava-Castro & Yizel Becerril-Alarcón & Roberto Camacho-Beiza & D, 2022. "Association of Serum Levels of Plasticizers Compounds, Phthalates and Bisphenols, in Patients and Survivors of Breast Cancer: A Real Connection?," IJERPH, MDPI, vol. 19(13), pages 1-22, June.
    18. Chi-Cheng Huang & Shih-Hsin Tu & Heng-Hui Lien & Jaan-Yeh Jeng & Ching-Shui Huang & Chi-Jung Huang & Liang-Chuan Lai & Eric Y Chuang, 2013. "Concurrent Gene Signatures for Han Chinese Breast Cancers," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.
    19. Fadia Gujam & Katie Dickson & Pamela McCall & Donald McMillan & Joanne Edwards, 2018. "The Relationship Between Androgen Receptor, Components of Tumour Microenvironment and Survival in Breast Cancer Molecular Subtypes," Cancer Therapy & Oncology International Journal, Juniper Publishers Inc., vol. 11(3), pages 77-85, July.
    20. Zhiguang Huo & Li Zhu & Tianzhou Ma & Hongcheng Liu & Song Han & Daiqing Liao & Jinying Zhao & George Tseng, 2020. "Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 1-22, April.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0086511. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.