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Paolo Manca

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    Lunch & Poster Display session (ID 58)

    • Event: ELCC 2019
    • Type: Poster Display session
    • Track:
    • Presentations: 1
    • Moderators:
    • Coordinates: 4/11/2019, 12:30 - 13:00, Hall 1
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      24P - A new bioinformatic pipeline allows the design of small, targeted gene panels for efficient TMB estimation (ID 192)

      12:30 - 13:00  |  Presenting Author(s): Paolo Manca

      • Abstract
      • Slides


      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.

      a9ded1e5ce5d75814730bb4caaf49419 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.

      20c51b5f4e9aeb5334c90ff072e6f928 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)

      Performance (adjusted R2) in TMB estimation of existing gene panels and gene panels built with our method of similar length.
      Other panels IDs (length)Other panels performanceOur panels performance (length)
      panel #1 (0.187 Mb)0.760.83 (0.187 Mb)
      panel #2 (0.240 Mb)0.580.85 (0.25 Mb)
      panel #3 (0.300 Mb)0.690.85 (0.25 Mb)
      panel #4 (0.98 Mb)0.810.91 (0.98 Mb)
      panel #5 (1.1 Mb)0.920.92 (1.1 Mb)
      panel #6 (1.9 Mb)0.930.93 (2.0 Mb)

      fd69c5cf902969e6fb71d043085ddee6 Conclusions

      Our method allows the design of gene panels particularly suitable for the TMB estimation in patients with LUAD and outperforms existing gene panels less than 1 Mb long.

      b651e8a99c4375feb982b7c2cad376e9 Legal entity responsible for the study

      Paolo Manca.

      213f68309caaa4ccc14d5f99789640ad Funding

      Has not received any funding.

      682889d0a1d3b50267a69346a750433d Disclosure

      All authors have declared no conflicts of interest.


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