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    A new bioinformatic pipeline allows the design of small, targeted gene panels for efficient TMB estimation

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    Author
    Manca, P.
    Mallona, I.
    Rolfo, C.D.
    Date
    2019
    Journal
    Annals of Oncology
    Publisher
    Elsevier Ltd
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1093/annonc/mdz073.003
    Abstract

    Background: The tumor mutation burden (TMB) is emerging as a prognostic and predictive marker for the response to immune checkpoint blockade (ICB) drugs. We aimed to develop a new method for the definition of gene panels that can precisely estimate the TMB with a considerably lower amount of genome. Methods: We developed a bioinformatic pipeline which allows the design of gene panels suited for TMB estimation. The method is particularly efficient in optimizing the balance between the precision of the TMB estimate and the length of the gene panel created. We tested in silico the efficiency of different panels obtained with our method in an independent cohort of patients with lung adenocarcinoma (LUAD). We also compared in the same cohort of patients the performance of our panels with the performance of existing gene panels. Results: We designed a 0.080 Megabases (Mb) long gene panel which estimated TMB in an independent LUAD cohort with an acceptable precision (adjusted R2=0.745; Spearman ρ = 0.827, Pearson ρ = 0.864). The panel showed 0.89 accuracy in the identification of TMB-high patients (25/28 patients, CI: 0.73 – 0.96). Every unitary increase of our TMB estimate was associated with lower risk of disease progression (univariate analysis: HR = 0.78; CI: 0.65-0.93; p = 0.006; multivariate analysis: HR = 0.8; CI: 0.63-1.01; p = 0.0621). Different existing panels of less than 1 Mb long showed a lower adjusted R2 when compared to our gene panel (Table). Two other commercial panels of 1.9 Mb and 1.1 Mb showed a similar adjusted R2 to panels of the same lengths built with our method; nevertheless, they showed a lower accuracy in TMB-high patients definition (ROC curves AUC of 0.862, 0.870, 0.946 and 0.967 were observed, respectively, for the commercial 1.9 Mb panel, the commercial 1.1 Mb panel, our 0.080 Mb panel and our 2.0 Mb panel).
    Keyword
    tumor
    tumor mutation burden
    bioinformatic pipeline
    gene panels
    Mutation
    Prognosis
    Biomarkers
    Computational Biology
    Identifier to cite or link to this item
    https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079689793&doi=10.1093%2fannonc%2fmdz073.003&partnerID=40&md5=0e0c752411532857249067c6c30db727; http://hdl.handle.net/10713/12134
    ae974a485f413a2113503eed53cd6c53
    10.1093/annonc/mdz073.003
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