BMC Biology (Feb 2024)

Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

  • Célia Dupain,
  • Tom Gutman,
  • Elodie Girard,
  • Choumouss Kamoun,
  • Grégoire Marret,
  • Zahra Castel-Ajgal,
  • Marie-Paule Sablin,
  • Cindy Neuzillet,
  • Edith Borcoman,
  • Ségolène Hescot,
  • Céline Callens,
  • Olfa Trabelsi-Grati,
  • Samia Melaabi,
  • Roseline Vibert,
  • Samantha Antonio,
  • Coralie Franck,
  • Michèle Galut,
  • Isabelle Guillou,
  • Maral Halladjian,
  • Yves Allory,
  • Joanna Cyrta,
  • Julien Romejon,
  • Eleonore Frouin,
  • Dominique Stoppa-Lyonnet,
  • Jennifer Wong,
  • Christophe Le Tourneau,
  • Ivan Bièche,
  • Nicolas Servant,
  • Maud Kamal,
  • Julien Masliah-Planchon

DOI
https://doi.org/10.1186/s12915-024-01839-8
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 12

Abstract

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Abstract Background High tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests. Results FFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm. Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as “true TMB high.” Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10–3927] versus 8.2 mut/Mb [2.5–897], p < 0.001). Conclusions We herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

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