Tumor mutation burden derived from small next generation sequencing targeted gene panel as an initial screening method

被引:13
作者
Tang, Yuan [1 ]
Li, Yuli [1 ]
Wang, Weiya [1 ]
Lizaso, Analyn [2 ]
Hou, Ting [2 ]
Jiang, Lili [1 ]
Huang, Meijuan [3 ]
机构
[1] West China Hosp, Dept Pathol, Chengdu 610041, Peoples R China
[2] Burning Rock Biotech, Guangzhou 510300, Peoples R China
[3] West China Hosp, Dept Thorac Oncol, Chengdu 610041, Peoples R China
关键词
Non-small cell lung cancer (NSCLC); small gene panel; tumor mutation burden (TMB); TMB in NSCLC; LUNG-CANCER; PD-1; BLOCKADE; DISCOVERY; GENOME;
D O I
10.21037/tlcr.2019.12.27
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: With the increasing use of immune checkpoint inhibitors, tumor mutation burden (TMB) assessment is now routinely included in reports generated from targeted sequencing with large gene panels; however, not all patients require comprehensive profiling with large panels. Our study aims to explore the feasibility of using a small 56-gene panel as a screening method for TMB prediction. Methods: TMB from 406 non-small cell lung cancer (NSCLC) patients was estimated using a large 520-gene panel simulated with the prospective TMB status for the small panel. This information was then used to determine the optimal cut-off. An independent cohort of 30 NSCLC patients was sequenced with both panels to confirm the cut-off value. Results: By comparing sensitivity, specificity, and positive predictive value (PPV), the cut-off was set up as 10 mutations/megabase, yielding 81.4% specificity, 83.6% sensitivity, and 62.4% PPV. Further validation with an independent cohort sequenced with both panels using the same cut-off achieved 95.7% sensitivity, 71.4% specificity and 91.7% PPV. The decreasing trend of sensitivity with the increasing trend of both specificity and PPV with a concomitant increase in the cut-off for the small panel suggests that TMB is overestimated but highly unlikely to yield false-positive results. Hence, patients with low TMB (<10) can be reliably stratified from patients with high TMB (>= 10). Conclusions: The small panel, more cost-effective, can be used as a screening method to screen for patients with low TMB, while patients with TMB >= 10 are recommended for further validation with a larger panel.
引用
收藏
页码:71 / +
页数:15
相关论文
共 24 条
  • [1] Size matters: Dissecting key parameters for panel-based tumor mutational burden analysis
    Buchhalter, Ivo
    Rempel, Eugen
    Endris, Volker
    Allgaeuer, Michael
    Neumann, Olaf
    Volckmar, Anna-Lena
    Kirchner, Martina
    Leichsenring, Jonas
    Lier, Amelie
    von Winterfeld, Moritz
    Penzel, Roland
    Christopoulos, Petros
    Thomas, Michael
    Froehling, Stefan
    Schirmacher, Peter
    Budczies, Jan
    Stenzinger, Albrecht
    [J]. INTERNATIONAL JOURNAL OF CANCER, 2019, 144 (04) : 848 - 858
  • [2] Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice
    Campesato, Luis Felipe
    Barroso-Sousa, Romualdo
    Jimenez, Leandro
    Correa, Bruna R.
    Sabbaga, Jorge
    Hoff, Paulo M.
    Reis, Luiz F. L.
    Galante, Pedro Alexandre F.
    Camargo, Anamaria A.
    [J]. ONCOTARGET, 2015, 6 (33) : 34221 - 34227
  • [3] Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden
    Chalmers, Zachary R.
    Connelly, Caitlin F.
    Fabrizio, David
    Gay, Laurie
    Ali, Siraj M.
    Ennis, Riley
    Schrock, Alexa
    Campbell, Brittany
    Shlien, Adam
    Chmielecki, Juliann
    Huang, Franklin
    He, Yuting
    Sun, James
    Tabori, Uri
    Kennedy, Mark
    Lieber, Daniel S.
    Roels, Steven
    White, Jared
    Otto, Geoffrey A.
    Ross, Jeffrey S.
    Garraway, Levi
    Miller, Vincent A.
    Stephens, Phillip J.
    Frampton, Garrett M.
    [J]. GENOME MEDICINE, 2017, 9
  • [4] A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3
    Cingolani, Pablo
    Platts, Adrian
    Wang, Le Lily
    Coon, Melissa
    Tung Nguyen
    Wang, Luan
    Land, Susan J.
    Lu, Xiangyi
    Ruden, Douglas M.
    [J]. FLY, 2012, 6 (02) : 80 - 92
  • [5] Molecular Diagnostic Profiling of Lung Cancer Specimens with a Semiconductor-Based Massive Parallel Sequencing Approach Feasibility, Costs, and Performance Compared with Conventional Sequencing
    Endris, Volker
    Penzel, Roland
    Warth, Arne
    Muckenhuber, Alexander
    Schirmacher, Peter
    Stenzinger, Albrecht
    Weichert, Wilko
    [J]. JOURNAL OF MOLECULAR DIAGNOSTICS, 2013, 15 (06) : 765 - 775
  • [6] Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing
    Frampton, Garrett M.
    Fichtenholtz, Alex
    Otto, Geoff A.
    Wang, Kai
    Downing, Sean R.
    He, Jie
    Schnall-Levin, Michael
    White, Jared
    Sanford, Eric M.
    An, Peter
    Sun, James
    Juhn, Frank
    Brennan, Kristina
    Iwanik, Kiel
    Maillet, Ashley
    Buell, Jamie
    White, Emily
    Zhao, Mandy
    Balasubramanian, Sohail
    Terzic, Selmira
    Richards, Tina
    Banning, Vera
    Garcia, Lazaro
    Mahoney, Kristen
    Zwirko, Zac
    Donahue, Amy
    Beltran, Himisha
    Mosquera, Juan Miguel
    Rubin, Mark A.
    Dogan, Snjezana
    Hedvat, Cyrus V.
    Berger, Michael F.
    Pusztai, Lajos
    Lechner, Matthias
    Boshoff, Chris
    Jarosz, Mirna
    Vietz, Christine
    Parker, Alex
    Miller, Vincent A.
    Ross, Jeffrey S.
    Curran, John
    Cronin, Maureen T.
    Stephens, Philip J.
    Lipson, Doron
    Yelensky, Roman
    [J]. NATURE BIOTECHNOLOGY, 2013, 31 (11) : 1023 - +
  • [7] Data mining in bioinformatics using Weka
    Frank, E
    Hall, M
    Trigg, L
    Holmes, G
    Witten, IH
    [J]. BIOINFORMATICS, 2004, 20 (15) : 2479 - 2481
  • [8] Additive logistic regression: A statistical view of boosting - Rejoinder
    Friedman, J
    Hastie, T
    Tibshirani, R
    [J]. ANNALS OF STATISTICS, 2000, 28 (02) : 400 - 407
  • [9] The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer
    Goldstraw, Peter
    Chansky, Kari
    Crowley, John
    Rami-Porta, Ramon
    Asamura, Hisao
    Eberhardt, Wilfried E. E.
    Nicholson, Andrew G.
    Groome, Patti
    Mitchell, Alan
    Bolejack, Vanessa
    [J]. JOURNAL OF THORACIC ONCOLOGY, 2016, 11 (01) : 39 - 51
  • [10] Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers
    Goodman, Aaron M.
    Kato, Shumei
    Bazhenova, Lyudmila
    Patel, Sandip P.
    Frampton, Garrett M.
    Miller, Vincent
    Stephens, Philip J.
    Daniels, Gregory A.
    Kurzrock, Razelle
    [J]. MOLECULAR CANCER THERAPEUTICS, 2017, 16 (11) : 2598 - 2608