Challenges in bioinformatics approaches to tumor mutation burden analysis

Fenizia,Francesca; Pasquale,Raffaella; Abate,Riziero Esposito; Lambiase,Matilde; Roma,Cristin; Bergantino,Francesca; Chaudhury,Ruchi; Hyland,Fiona; Allen,Christopher; Normanno,Nicola

doi:10.3892/ol.2021.12816

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

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
Published online on: May 24, 2021 https://doi.org/10.3892/ol.2021.12816
Article Number: 555
Copyright: © Fenizia et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

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.

View Figures

View References

1	Robert C, Long GV, Brady B, Dutriaux C, Maio M, Mortier L, Hassel JC, Rutkowski P, McNeil C, Kalinka-Warzocha E, et al: Nivolumab in previously untreated melanoma without BRAF mutation. N Engl J Med. 372:320–330. 2015. View Article : Google Scholar : PubMed/NCBI
2	Garon EB, Rizvi NA, Hui R, Leighl N, Balmanoukian AS, Eder JP, Patnaik A, Aggarwal C, Gubens M, Horn L, et al KEYNOTE-001 investigators, : Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med. 372:2018–2028. 2015. View Article : Google Scholar : PubMed/NCBI
3	Brahmer J, Reckamp KL, Baas P, Crinò L, Eberhardt WE, Poddubskaya E, Antonia S, Pluzanski A, Vokes EE, Holgado E, et al: Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med. 373:123–135. 2015. View Article : Google Scholar : PubMed/NCBI
4	Patel SP and Kurzrock R: Pd-l1 expression as a predictive biomarker in cancer immunotherapy. Mol Cancer Ther. 14:847–856. 2015. View Article : Google Scholar : PubMed/NCBI
5	Reck M, Rodríguez-Abreu D, Robinson AG, Hui R, Csőszi T, Fülöp A, Gottfried M, Peled N, Tafreshi A, Cuffe S, et al KEYNOTE-024 Investigators, : Pembrolizumab versus chemotherapy for pd-l1-positive non-small-cell lung cancer. N Engl J Med. 375:1823–1833. 2016. View Article : Google Scholar : PubMed/NCBI
6	Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, Skora AD, Luber BS, Azad NS, Laheru D, et al: Pd-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 372:2509–2520. 2015. View Article : Google Scholar : PubMed/NCBI
7	Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky JM, Desrichard A, Walsh LA, Postow MA, Wong P, Ho TS, et al: Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 371:2189–2199. 2014. View Article : Google Scholar : PubMed/NCBI
8	Carbone DP, Reck M, Paz-Ares L, Creelan B, Horn L, Steins M, Felip E, van den Heuvel MM, Ciuleanu TE, Badin F, et al CheckMate 026 investigators, : First-line nivolumab in stage iv or recurrent non-small-cell lung cancer. N Engl J Med. 376:2415–2426. 2017. View Article : Google Scholar : PubMed/NCBI
9	Van Allen EM, Miao D, Schilling B, Shukla SA, Blank C, Zimmer L, Sucker A, Hillen U, Foppen MHG, Goldinger SM, et al: Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 350:207–211. 2015. View Article : Google Scholar : PubMed/NCBI
10	Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, Lee W, Yuan J, Wong P, Ho TS, et al: Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 348:124–128. 2015. View Article : Google Scholar : PubMed/NCBI
11	Rizvi H, Sanchez-Vega F, La K, Chatila W, Jonsson P, Halpenny D, Plodkowski A, Long N, Sauter JL, Rekhtman N, et al: Molecular determinants of response to anti-programmed cell death (pd)-1 and anti-programmed death-ligand 1 (pd-l1) blockade in patients with non-small-cell lung cancer profiled with targeted next-generation sequencing. J Clin Oncol. 36:633–641. 2018. View Article : Google Scholar : PubMed/NCBI
12	Samstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY, Barron DA, Zehir A, Jordan EJ, Omuro A, et al: Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 51:202–206. 2019. View Article : Google Scholar : PubMed/NCBI
13	Hellmann MD, Ciuleanu TE, Pluzanski A, Lee JS, Otterson GA, Audigier-Valette C, Minenza E, Linardou H, Burgers S, Salman P, et al: Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N Engl J Med. 378:2093–2104. 2018. View Article : Google Scholar : PubMed/NCBI
14	Yarchoan M, Hopkins A and Jaffee EM: Tumor mutational burden and response rate to pd-1 inhibition. N Engl J Med. 377:2500–2501. 2017. View Article : Google Scholar : PubMed/NCBI
15	Rosenberg JE, Hoffman-Censits J, Powles T, van der Heijden MS, Balar AV, Necchi A, Dawson N, O'Donnell PH, Balmanoukian A, Loriot Y, et al: Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: A single-arm, multicentre, phase 2 trial. Lancet. 387:1909–1920. 2016. View Article : Google Scholar : PubMed/NCBI
16	Brown SD, Warren RL, Gibb EA, Martin SD, Spinelli JJ, Nelson BH and Holt RA: Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival. Genome Res. 24:743–750. 2014. View Article : Google Scholar : PubMed/NCBI
17	Schumacher TN and Schreiber RD: Neoantigens in cancer immunotherapy. Science. 348:69–74. 2015. View Article : Google Scholar : PubMed/NCBI
18	Anagnostou V, Smith KN, Forde PM, Niknafs N, Bhattacharya R, White J, Zhang T, Adleff V, Phallen J, Wali N, et al: Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer. Cancer Discov. 7:264–276. 2017. View Article : Google Scholar : PubMed/NCBI
19	Büttner R, Longshore JW, López-Ríos F, Merkelbach-Bruse S, Normanno N, Rouleau E and Penault-Llorca F: Implementing TMB measurement in clinical practice: Considerations on assay requirements. ESMO Open. 4:e0004422019. View Article : Google Scholar
20	Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, Bignell GR, Bolli N, Borg A, Børresen-Dale AL, et al Australian Pancreatic Cancer Genome Initiative; ICGC Breast Cancer Consortium; ICGC MMML-Seq Consortium; ICGC PedBrain, : Signatures of mutational processes in human cancer. Nature. 500:415–421. 2013. View Article : Google Scholar : PubMed/NCBI
21	Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, Carter SL, Stewart C, Mermel CH, Roberts SA, et al: Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 499:214–218. 2013. View Article : Google Scholar : PubMed/NCBI
22	Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA Jr and Kinzler KW: Cancer genome landscapes. Science. 339:1546–1558. 2013. View Article : Google Scholar : PubMed/NCBI
23	Ready N, Hellmann MD, Awad MM, Otterson GA, Gutierrez M, Gainor JF, Borghaei H, Jolivet J, Horn L, Mates M, et al: First-line nivolumab plus ipilimumab in advanced non-small-cell lung cancer (checkmate 568): Outcomes by programmed death ligand 1 and tumor mutational burden as biomarkers. J Clin Oncol. 37:992–1000. 2019. View Article : Google Scholar : PubMed/NCBI
24	Cristescu R, Mogg R, Ayers M, Albright A, Murphy E, Yearley J, Sher X, Liu XQ, Lu H, Nebozhyn M, et al: Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science. 362:3622018. View Article : Google Scholar : PubMed/NCBI
25	Innocenti F, Ou FS, Qu X, Zemla TJ, Niedzwiecki D, Tam R, Mahajan S, Goldberg RM, Bertagnolli MM, Blanke CD, et al: Mutational analysis of patients with colorectal cancer in calgb/swog 80405 identifies new roles of microsatellite instability and tumor mutational burden for patient outcome. J Clin Oncol. 37:1217–1227. 2019. View Article : Google Scholar : PubMed/NCBI
26	Owada-Ozaki Y, Muto S, Takagi H, Inoue T, Watanabe Y, Fukuhara M, Yamaura T, Okabe N, Matsumura Y, Hasegawa T, et al: Prognostic impact of tumor mutation burden in patients with completely resected non-small cell lung cancer: Brief report. J Thorac Oncol. 13:1217–1221. 2018. View Article : Google Scholar : PubMed/NCBI
27	Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J, et al: Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 9:342017. View Article : Google Scholar : PubMed/NCBI
28	Frampton GM, Fichtenholtz A, Otto GA, Wang K, Downing SR, He J, Schnall-Levin M, White J, Sanford EM, An P, et al: Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 31:1023–1031. 2013. View Article : Google Scholar : PubMed/NCBI
29	Roszik J, Haydu LE, Hess KR, Oba J, Joon AY, Siroy AE, Karpinets TV, Stingo FC, Baladandayuthapani V, Tetzlaff MT, et al: Novel algorithmic approach predicts tumor mutation load and correlates with immunotherapy clinical outcomes using a defined gene mutation set. BMC Med. 14:1682016. View Article : Google Scholar : PubMed/NCBI
30	Campesato LF, Barroso-Sousa R, Jimenez L, Correa BR, Sabbaga J, Hoff PM, Reis LF, Galante PA and Camargo AA: Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice. Oncotarget. 6:34221–34227. 2015. View Article : Google Scholar : PubMed/NCBI
31	Berg KCG, Eide PW, Eilertsen IA, Johannessen B, Bruun J, Danielsen SA, Bjørnslett M, Meza-Zepeda LA, Eknaes M, Lind GE, et al: Multi-omics of 34 colorectal cancer cell lines - a resource for biomedical studies. Mol Cancer. 16:1162017. View Article : Google Scholar : PubMed/NCBI
32	Catalogue Of Somatic Mutations In Cancer (COSMI), . Cell Lines Project v92, released 27-AUG-20. Available from. https://cancer.sanger.ac.uk/cell_linesAugust 28–2019
33	Gupta A, Connelly C, Frampton G, Chmielecki J, Ali S, Suh J, Schrock A, Ross J, Stephens P and Miller V: The druggable mutation landscape of lung adenocarcinoma. J Thorac Oncol. 12:9772017. View Article : Google Scholar
34	Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, Kim S, Wilson CJ, Lehár J, Kryukov GV, Sonkin D, et al: The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature. 483:603–607. 2012. View Article : Google Scholar : PubMed/NCBI
35	Fenizia F, Pasquale R, Roma C, Bergantino F, Iannaccone A and Normanno N: Measuring tumor mutation burden in non-small cell lung cancer: Tissue versus liquid biopsy. Transl Lung Cancer Res. 7:668–677. 2018. View Article : Google Scholar : PubMed/NCBI
36	Chaudhary R, Quagliata L, Martin JP, Alborelli I, Cyanam D, Mittal V, Tom W, Au-Young J, Sadis S and Hyland F: A scalable solution for tumor mutational burden from formalin-fixed, paraffin-embedded samples using the Oncomine Tumor Mutation Load Assay. Transl Lung Cancer Res. 7:616–630. 2018. View Article : Google Scholar : PubMed/NCBI
37	Endris V, Buchhalter I, Allgäuer M, Rempel E, Lier A, Volckmar AL, Kirchner M, von Winterfeld M, Leichsenring J, Neumann O, et al: Measurement of tumor mutational burden (TMB) in routine molecular diagnostics: In silico and real-life analysis of three larger gene panels. Int J Cancer. 144:2303–2312. 2019.PubMed/NCBI
38	Turajlic S, Litchfield K, Xu H, Rosenthal R, McGranahan N, Reading JL, Wong YNS, Rowan A, Kanu N, Al Bakir M, et al: Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: A pan-cancer analysis. Lancet Oncol. 18:1009–1021. 2017. View Article : Google Scholar : PubMed/NCBI
39	Mandal R, Samstein RM, Lee KW, Havel JJ, Wang H, Krishna C, Sabio EY, Makarov V, Kuo F, Blecua P, et al: Genetic diversity of tumors with mismatch repair deficiency influences anti-PD-1 immunotherapy response. Science. 364:485–491. 2019. View Article : Google Scholar : PubMed/NCBI
40	Chae YK, Viveiros P, Lopes G, Sukhadia B, Sheikh MM, Saravia D, Florou V, Sokol ES, Frampton GM, Chalmers ZR, et al: Clinical and immunological implications of frameshift mutations in lung cancer. J Thorac Oncol. 14:1807–1817. 2019. View Article : Google Scholar : PubMed/NCBI