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Challenges in bioinformatics approaches to tumor mutation burden analysis

  • Authors:
    • Francesca Fenizia
    • Raffaella Pasquale
    • Riziero Esposito Abate
    • Matilde Lambiase
    • Cristin Roma
    • Francesca Bergantino
    • Ruchi Chaudhury
    • Fiona Hyland
    • Christopher Allen
    • Nicola Normanno
  • View Affiliations / Copyright

    Affiliations: Cell Biology and Biotherapy Unit, Department of Research, Istituto Nazionale Tumori-IRCCS-Fondazione G. Pascale, I-80131 Naples, Italy, Department of Molecular Medicine and Medical Biotechnology, Federico II University, I-80131 Naples, Italy, Thermo Fisher Scientific, Inc., South San Francisco, CA 94080, USA, Thermo Fisher Scientific, Inc., Paisley, Renfrewshire PA1-PA3, UK
    Copyright: © Fenizia et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 555
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    Published online on: May 24, 2021
       https://doi.org/10.3892/ol.2021.12816
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Abstract

Several immune checkpoint inhibitors (ICIs) have already been introduced into clinical practice or are in advanced phases of clinical experimentation. Extensive efforts are being made to identify robust biomarkers to select patients who may benefit from treatment with ICIs. Tumor mutation burden (TMB) may be a relevant biomarker of response to ICIs in different tumor types; however, its clinical use is challenged by the analytical methods required for its evaluation. The possibility of using targeted next‑generation sequencing panels has been investigated as an alternative to the standard whole exome sequencing approach. However, no standardization exists in terms of genes covered, types of mutations included in the estimation of TMB, bioinformatics pipelines for data analysis, and cut‑offs used to discriminate samples with high, intermediate or low TMB. Bioinformatics serve a relevant role in the analysis of targeted sequencing data and its standardization is essential to deliver a reliable test in clinical practice. In the present study, cultured and formalin‑fixed, paraffin‑embedded cell lines were analyzed using a commercial panel for TMB testing; the results were compared with data from the literature and public databases, demonstrating a good correlation. Additionally, the correlation between high tumor mutation burden and microsatellite instability was confirmed. The bioinformatics analyses were conducted using two different pipelines to highlight the challenges associated with the development of an appropriate analytical workflow.
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Copy and paste a formatted citation
Spandidos Publications style
Fenizia F, Pasquale R, Abate RE, Lambiase M, Roma C, Bergantino F, Chaudhury R, Hyland F, Allen C, Normanno N, Normanno N, et al: Challenges in bioinformatics approaches to tumor mutation burden analysis. Oncol Lett 22: 555, 2021.
APA
Fenizia, F., Pasquale, R., Abate, R.E., Lambiase, M., Roma, C., Bergantino, F. ... Normanno, N. (2021). Challenges in bioinformatics approaches to tumor mutation burden analysis. Oncology Letters, 22, 555. https://doi.org/10.3892/ol.2021.12816
MLA
Fenizia, F., Pasquale, R., Abate, R. E., Lambiase, M., Roma, C., Bergantino, F., Chaudhury, R., Hyland, F., Allen, C., Normanno, N."Challenges in bioinformatics approaches to tumor mutation burden analysis". Oncology Letters 22.1 (2021): 555.
Chicago
Fenizia, F., Pasquale, R., Abate, R. E., Lambiase, M., Roma, C., Bergantino, F., Chaudhury, R., Hyland, F., Allen, C., Normanno, N."Challenges in bioinformatics approaches to tumor mutation burden analysis". Oncology Letters 22, no. 1 (2021): 555. https://doi.org/10.3892/ol.2021.12816
Copy and paste a formatted citation
x
Spandidos Publications style
Fenizia F, Pasquale R, Abate RE, Lambiase M, Roma C, Bergantino F, Chaudhury R, Hyland F, Allen C, Normanno N, Normanno N, et al: Challenges in bioinformatics approaches to tumor mutation burden analysis. Oncol Lett 22: 555, 2021.
APA
Fenizia, F., Pasquale, R., Abate, R.E., Lambiase, M., Roma, C., Bergantino, F. ... Normanno, N. (2021). Challenges in bioinformatics approaches to tumor mutation burden analysis. Oncology Letters, 22, 555. https://doi.org/10.3892/ol.2021.12816
MLA
Fenizia, F., Pasquale, R., Abate, R. E., Lambiase, M., Roma, C., Bergantino, F., Chaudhury, R., Hyland, F., Allen, C., Normanno, N."Challenges in bioinformatics approaches to tumor mutation burden analysis". Oncology Letters 22.1 (2021): 555.
Chicago
Fenizia, F., Pasquale, R., Abate, R. E., Lambiase, M., Roma, C., Bergantino, F., Chaudhury, R., Hyland, F., Allen, C., Normanno, N."Challenges in bioinformatics approaches to tumor mutation burden analysis". Oncology Letters 22, no. 1 (2021): 555. https://doi.org/10.3892/ol.2021.12816
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