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Clonal evolution of glioblastoma under therapy

Nature Genetics volume 48, pages 768–776 (2016)Cite this article

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Abstract

Glioblastoma (GBM) is the most common and aggressive primary brain tumor. To better understand how GBM evolves, we analyzed longitudinal genomic and transcriptomic data from 114 patients. The analysis shows a highly branched evolutionary pattern in which 63% of patients experience expression-based subtype changes. The branching pattern, together with estimates of evolutionary rate, suggests that relapse-associated clones typically existed years before diagnosis. Fifteen percent of tumors present hypermutation at relapse in highly expressed genes, with a clear mutational signature. We find that 11% of recurrence tumors harbor mutations in LTBP4, which encodes a protein binding to TGF-β. Silencing LTBP4 in GBM cells leads to suppression of TGF-β activity and decreased cell proliferation. In recurrent GBM with wild-type IDH1, high LTBP4 expression is associated with worse prognosis, highlighting the TGF-β pathway as a potential therapeutic target in GBM.

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Figure 1: Mutational landscape of recurrent glioblastoma.
Figure 2: Temozolomide-related hypermutation.
Figure 3: Mathematical model of tumor evolution.
Figure 4: Clonal mutation replacement in key driver genes.
Figure 5: Expression-based subtyping of recurrent GBM.
Figure 6: LTBP4 and the TGF-β signaling pathway in recurrent GBM.

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Gene Expression Omnibus

Sequence Read Archive

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Acknowledgements

R.R. acknowledges funding from the NIH (U54 CA193313, R01 CA185486, and R01 CA179044). J.W. is supported by a Precision Medicine Fellowship (UL1 TR000040). E.L. is supported by the Cancer Biology Training Program (T32 CA09503). D.I.S.R. is supported by the US National Library of Medicine (T15 LM007079). S.Z. is supported by a Personalized Medicine Fellowship (TL1 TR000082). This work is also supported by NIH grants to A.L. (R01 CA101644 and R01 CA131126) and A.I. (R01 CA178546 and R01 NS061776 and a grant from the Chemotherapy Foundation). V.F. is supported by a fellowship from the American Brain Tumor Association (ABTA). G.F. is partly funded by the Italian Ministry of Health. D.-H.N. is supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (HI14C3418).

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Authors and Affiliations

  1. Department of Systems Biology, Columbia University, New York, New York, USA

    Jiguang Wang, Erik Ladewig, Daniel I S Rosenbloom, Sakellarios Zairis, Francesco Abate, Zhaoqi Liu, Oliver Elliott & Raul Rabadan

  2. Department of Biomedical Informatics, Columbia University, New York, New York, USA

    Jiguang Wang, Erik Ladewig, Daniel I S Rosenbloom, Sakellarios Zairis, Francesco Abate, Zhaoqi Liu, Oliver Elliott & Raul Rabadan

  3. Fondazione IRCCS Istituto Neurologico Besta, Unit of Molecular Neuro-Oncology, Milan, Italy

    Emanuela Cazzato, Marica Eoli & Gaetano Finocchiaro

  4. Institute for Cancer Genetics, Columbia University, New York, New York, USA

    Veronique Frattini, Anna Lasorella & Antonio Iavarone

  5. Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    Yong-Jae Shin, Jin-Ku Lee, In-Hee Lee & Do-Hyun Nam

  6. Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    Woong-Yang Park

  7. Department of Mathematics, University of Texas, Austin, Texas, USA

    Andrew J Blumberg

  8. Department of Pediatrics, Columbia University, New York, New York, USA

    Anna Lasorella

  9. Department of Pathology, Columbia University, New York, New York, USA

    Anna Lasorella & Antonio Iavarone

  10. Department of Health Sciences and Technology, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea

    Do-Hyun Nam

  11. Department of Neurology, Columbia University, New York, New York, USA

    Antonio Iavarone

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  1. Jiguang Wang
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  2. Emanuela Cazzato
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  3. Erik Ladewig
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Contributions

E.C., M.E., and G.F. started the collection of samples and prepared libraries for genomic and transcriptomic analyses. E.C., V.F., and A.L. performed LTBP4 experiments. V.F. performed Sanger validation. S.Z. and A.J.B. performed the statistical analysis of phylogenetic trees. D.-H.N. provided additional data. F.A. and S.Z. ran Pegasus analysis. Z.L. ran ssGSEA analysis. D.I.S.R. constructed the mathematical model of tumor evolution before and after treatment. R.R., J.W., E.L., and O.E. developed and carried out analysis of genomic data. A.L., R.R., and A.I. conceived the methodology. D.-H.N., J.-K.L., I.-H.L., and W.-Y.P. provided clinical and genomic information for the SMC cohort. D.-H.N. and Y.-J.S. performed the validation of MGMT fusion. R.R., A.I., and J.W. conceived the project, discussed the results and implications, and wrote the manuscript.

Corresponding authors

Correspondence to Do-Hyun Nam, Gaetano Finocchiaro, Antonio Iavarone or Raul Rabadan.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–16 and Supplementary Note. (PDF 20648 kb)

Supplementary Data

Sanger validation of selected mutations. (PDF 32218 kb)

Supplementary Table 1

Coverage for whole-exome sequencing. (XLSX 67 kb)

Supplementary Table 2

All somatic mutations in patients with recurrent GBM. (XLSX 5494 kb)

Supplementary Table 3

Significant regions and potential driver genes reported by GISTIC2. (XLSX 150 kb)

Supplementary Table 4

Significant driver genes predicted by MutComFocal. (XLSX 366 kb)

Supplementary Table 5

Analysis of loss of heterozygosity. (XLSX 175 kb)

Supplementary Table 6

Selected list of gene fusion candidates. (XLSX 5925 kb)

Supplementary Table 7

Tumor purity estimation from ABSOLUTE. (XLSX 59 kb)

Supplementary Table 8

Cellular frequency prediction from PyClone. (XLSX 3816 kb)

Supplementary Table 9

EGFRvIII prediction from PRADA. (XLSX 53 kb)

Supplementary Table 10

Patient clinical data. (XLSX 29 kb)

Supplementary Table 11

Primer/oligo sequences for experimental validation. (XLSX 40 kb)

Supplementary Table 12

Validation of selected mutations by CancerSCAN. (XLSX 48 kb)

Supplementary Code

Glioblastoma evolution. (TXT 16 kb)

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Wang, J., Cazzato, E., Ladewig, E. et al. Clonal evolution of glioblastoma under therapy. Nat Genet 48, 768–776 (2016). https://doi.org/10.1038/ng.3590

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