A recurrent inactivating mutation in RHOA GTPase in angioimmunoblastic T cell lymphoma

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Abstract

The molecular mechanisms underlying angioimmunoblastic T cell lymphoma (AITL), a common type of mature T cell lymphoma of poor prognosis, are largely unknown. Here we report a frequent somatic mutation in RHOA (encoding p.Gly17Val) using exome and transcriptome sequencing of samples from individuals with AITL. Further examination of the RHOA mutation encoding p.Gly17Val in 239 lymphoma samples showed that the mutation was specific to T cell lymphoma and was absent from B cell lymphoma. We demonstrate that the RHOA mutation encoding p.Gly17Val, which was found in 53.3% (24 of 45) of the AITL cases examined, is oncogenic in nature using multiple molecular assays. Molecular modeling and docking simulations provided a structural basis for the loss of GTPase activity in the RHOA Gly17Val mutant. Our experimental data and modeling results suggest that the RHOA mutation encoding p.Gly17Val is a driver mutation in AITL. On the basis of these data and through integrated pathway analysis, we build a comprehensive signaling network for AITL oncogenesis.

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Figure 1: Mutation profiles for AITL cases.
Figure 2: Comparison of the mutation profiles in AITL, Burkitt lymphoma and DLBCL.
Figure 3: Mutation structure and functional domains of the RHOA and CD28 proteins.
Figure 4: Effect of the p.Gly17Val alteration on RHOA activity.
Figure 5: Structural model of RHOA-GTP binding via docking simulation.
Figure 6: Pathway model of AITL.

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Gene Expression Omnibus

Protein Data Bank

References

  1. 1

    Vose, J., Armitage, J. & Weisenburger, D. International peripheral T-cell and natural killer/T-cell lymphoma study: pathology findings and clinical outcomes. J. Clin. Oncol. 26, 4124–4130 (2008).

  2. 2

    Cairns, R.A. et al. IDH2 mutations are frequent in angioimmunoblastic T-cell lymphoma. Blood 119, 1901–1903 (2012).

  3. 3

    Couronné, L., Bastard, C. & Bernard, O.A. TET2 and DNMT3A mutations in human T-cell lymphoma. N. Engl. J. Med. 366, 95–96 (2012).

  4. 4

    de Leval, L. et al. The gene expression profile of nodal peripheral T-cell lymphoma demonstrates a molecular link between angioimmunoblastic T-cell lymphoma (AITL) and follicular helper T (TFH) cells. Blood 109, 4952–4963 (2007).

  5. 5

    Richter, J. et al. Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing. Nat. Genet. 44, 1316–1320 (2012).

  6. 6

    Schmitz, R. et al. Burkitt lymphoma pathogenesis and therapeutic targets from structural and functional genomics. Nature 490, 116–120 (2012).

  7. 7

    Lohr, J.G. et al. Discovery and prioritization of somatic mutations in diffuse large B-cell lymphoma (DLBCL) by whole-exome sequencing. Proc. Natl. Acad. Sci. USA 109, 3879–3884 (2012).

  8. 8

    Zhang, J. et al. Genetic heterogeneity of diffuse large B-cell lymphoma. Proc. Natl. Acad. Sci. USA 110, 1398–1403 (2013).

  9. 9

    Pasqualucci, L. et al. Inactivating mutations of acetyltransferase genes in B-cell lymphoma. Nature 471, 189–195 (2011).

  10. 10

    Vogelstein, B. et al. Cancer genome landscapes. Science 339, 1546–1558 (2013).

  11. 11

    Morin, P., Flors, C. & Olson, M.F. Constitutively active RhoA inhibits proliferation by retarding G1 to S phase cell cycle progression and impairing cytokinesis. Eur. J. Cell Biol. 88, 495–507 (2009).

  12. 12

    Ghiaur, G. et al. Inhibition of RhoA GTPase activity enhances hematopoietic stem and progenitor cell proliferation and engraftment. Blood 108, 2087–2094 (2006).

  13. 13

    Li, Z. et al. Regulation of PTEN by Rho small GTPases. Nat. Cell Biol. 7, 399–404 (2005).

  14. 14

    Brazil, D.P., Park, J. & Hemmings, B.A. PKB binding proteins. Getting in on the Akt. Cell 111, 293–303 (2002).

  15. 15

    Klink, B.U. et al. Structure of Shigella IpgB2 in complex with human RhoA: implications for the mechanism of bacterial guanine nucleotide exchange factor mimicry. J. Biol. Chem. 285, 17197–17208 (2010).

  16. 16

    Piccaluga, P.P. et al. Gene expression analysis of peripheral T cell lymphoma, unspecified, reveals distinct profiles and new potential therapeutic targets. J. Clin. Invest. 117, 823–834 (2007).

  17. 17

    Luo, W., Friedman, M., Shedden, K., Hankenson, K. & Woolf, P. GAGE: generally applicable gene set enrichment for pathway analysis. BMC Bioinformatics 10, 161 (2009).

  18. 18

    Lemonnier, F. et al. Recurrent TET2 mutations in peripheral T-cell lymphomas correlate with TFH-like features and adverse clinical parameters. Blood 120, 1466–1469 (2012).

  19. 19

    Ridley, A. Rho GTPases. Integrating integrin signaling. J. Cell Biol. 150, F107–F109 (2000).

  20. 20

    Jaganathan, B.G., Anjos-Afonso, F., Kumar, A. & Bonnet, D. Active RHOA favors retention of human hematopoietic stem/progenitor cells in their niche. J. Biomed. Sci. 20, 66 (2013).

  21. 21

    Vega, F.M., Fruhwirth, G., Ng, T. & Ridley, A.J. RhoA and RhoC have distinct roles in migration and invasion by acting through different targets. J. Cell Biol. 193, 655–665 (2011).

  22. 22

    Cleverley, S.C., Costello, P.S., Henning, S.W. & Cantrell, D.A. Loss of Rho function in the thymus is accompanied by the development of thymic lymphoma. Oncogene 19, 13–20 (2000).

  23. 23

    Forbes, S.A. et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 39, D945–D950 (2011).

  24. 24

    Palomero, T. et al. Recurrent mutations in epigenetic regulators, RHOA and FYN kinase in peripheral T cell lymphomas. Nat. Genet. 46, 166–170 (2014).

  25. 25

    Sakata-Yanagimoto, M. et al. Somatic RHOA mutation in angioimmunoblastic T cell lymphoma. Nat. Genet. 46, 171–175 (2014).

  26. 26

    Su, I.H. et al. Polycomb group protein EZH2 controls actin polymerization and cell signaling. Cell 121, 425–436 (2005).

  27. 27

    Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595 (2010).

  28. 28

    McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).

  29. 29

    Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).

  30. 30

    Saunders, C.T. et al. Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs. Bioinformatics 28, 1811–1817 (2012).

  31. 31

    Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

  32. 32

    Langmead, B. & Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  33. 33

    Albers, C.A. et al. Dindel: accurate indel calls from short-read data. Genome Res. 21, 961–973 (2011).

  34. 34

    Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

  35. 35

    Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

  36. 36

    Johnson, W.E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).

  37. 37

    Page, R.D. Visualizing phylogenetic trees using TreeView. Curr. Protoc. Bioinformatics Chapter 6, Unit 6.2 (2002).

  38. 38

    Olshen, A.B., Venkatraman, E., Lucito, R. & Wigler, M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 5, 557–572 (2004).

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Acknowledgements

We appreciate helpful discussion and comments from P.J. Park (Harvard Medical School). This work was supported by grants from the Samsung Biomedical Research Institute (SP2-B2-04 to Y.H.K., W.S.K. and H.Y.Y. and GE1-B2-071 to H.Y.Y.), the Samsung Cancer Research Institute (cancer genomics project SCRI-12-02), the National Research Foundation of Korea (NRF-2012M3A9D1054744 and NRF-2012M3A9B9036673 to S.L. and NRF-2011-0019745), the GIST (Gwangju Institute of Science and Technology) Systems Biology Infrastructure Establishment Grant through ERCSB (S.L. and J.K.) and the Ewha Global Top5 Grant of Ewha Womans University.

Author information

Y.H.K., S.L., W.S.K., S.J.K. and H.Y.Y. conceptualized the research program and designed the experiments. S.J.K., W.S.K. and Y.H.K. were involved in sample collection and clinical interpretation. Y.H.K. reviewed pathology. H.Y.Y., S.H.L. and H.J. conducted laboratory experiments. M.K.S., S.K., S.P., S.C.K., B.L. and K.R. analyzed the high-throughput sequencing and microarray data. H.L., K.-H.C. and W.K. performed the structural modeling of proteins. J.-E.L. supervised data generation. H.Y.Y., J.K., S.L. and Y.H.K. participated in preparing the manuscript.

Correspondence to Sanghyuk Lee or Young Hyeh Ko.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Representative histologic evaluation of the tumor tissue.

(a) Classical morphology with effacement of normal architecture and marked vascular proliferation associated with aggregates of atypical lymphoid cells (H&E staining). (b) The majority of atypical cells express CD3. (c) CD21 immunostaining showing hyperplastic follicular dendritic cell meshwork. (d) A portion of tumor cells express CD10. (e) Some tumor cells express CXCL13. (f) PD-1 is expressed in some neoplastic cells.

Supplementary Figure 2 Frozen section of the tumor sample.

Frozen section of the tumor sample showing hypercellular lymphoid tissue without necrosis (H&E staining).

Supplementary Figure 3 Sanger sequencing traces of RHOA G17V mutation in T cell lymphoma patients.

Patient ID with RHOA G17V mutation is indicated by red text and arrows. Representative traces of wild-type and G17V mutant RHOA are shown in the top left panel. The horizontal red arrow shows the direction of genomic DNA sequencing. The mutant sequence shows a clear heterozygous mutation. Traces from tumor samples obtained from 45 AITL, 20 NK/T cell and 13 PTCL-NOS patients are shown in the rectangles. Patients 5, 6, 9, 10, 29, 30 and 43 in the AITL group showed the mutant as the dominant peak. The other 17 AITL patients showed the heterozygous mutation clearly. All three NK/T cell patients with somatic mutation showed the heterozygous genotype. Only one PTCL-NOS patient showed a heterozygous mutation. Sequencing trace chromatograms are representative of at least three independent experiments.

Supplementary Figure 4 Kaplan-Meier survival plot according to RHOA mutation.

Supplementary Figure 5 In vitro proliferation assays.

In vitro proliferation assays in (a) the SUP-T1 cell line and (b) the MOLT-4 cell line. Cells expressing inactive RHOA (G17V and T19N) displayed enhanced cell proliferation. P < 0.01 compared with the cells expressing WT. Each condition with three replicates was repeated three times and expressed as the ± s.d.

Supplementary Figure 6 Inhibition of the RHOA-ROCK pathway downregulates AKT phosphorylation and promotes cell proliferation.

Inhibition of the RHOA-ROCK pathway downregulates AKT phosphorylation and promotes cell proliferation. (a) After transfection of Jurkat cells with control siRNA or RHOA siRNA, AKT phosphorylation levels and cell proliferation were assessed. Cell lysates were prepared 48 h after transfection and processed for immunoblotting with the indicated antibodies. The extent of RHOA depletion was determined by immunoblotting with anti-RHOA antibodies. As a loading control, a-tubulin was used. Cells transfected with siRNA were incubated for 48 h, and relative cell proliferation was determined using a cell counting kit (CCK-8). Five replicates of each condition were repeated three times; the data are expressed as mean ± s.d. (b) After treatment with the ROCK inhibitor, Y-27632 (30 μM), AKT phosphorylation levels and cell proliferation were measured. Cell lysates were prepared 48 h after treatment and processed for immunoblotting with the indicated antibodies. Cells treated with Y-27632 were incubated for 48 h, and relative cell proliferation was determined using a cell counting kit (CCK-8). Five replicates of each condition were repeated three times, and the data are expressed as mean ± s.d.

Supplementary Figure 7 Structural models of wild-type and mutant RHOA proteins.

Structural models of wild-type and mutant RHOA mutant proteins. Homology modeling was based on the PDB structure of 3LXR. GTP substrate and its ribose moiety are indicated in yellow and pink, respectively. The glycine and valine residues are shown in green and red, respectively.

Supplementary Figure 8 Heat map from the hierarchical clustering of DEGs.

Heat map from hierarchical clustering of differentially expressed genes. AITL patients from our study (PAT1–PAT9) and GSE6338 (AITL1–AITL6) were included. Normal control samples are indicated as CD4+. Gene clusters from hierarchical classification were subjected to the DAVID web server for Gene Ontology analysis, and the most enriched term for each cluster was determined using the q value from the FDR test.

Supplementary Figure 9 Statistically significant KEGG pathways from GAGE gene set enrichment analysis.

Pathways are grouped into functional categories. Up- and downregulated pathways are indicated by pink and green backgrounds, respectively. Numbers of SNVs, indels, CNVs and DEGs indicate the number of genes affected in each pathway.

Supplementary Figure 10 Comparison of gene expression according to RHOA mutation status.

(a) Patients with wild-type RHOA (PAT1 and PAT3). (b) Patients with G17V RHOA (PAT2 and PAT4–PAT9).

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1–3, 5–7 and 9, and Supplementary Figures 1–10 (PDF 2830 kb)

Supplementary Table 4

Full list of somatic SNVs. (XLS 294 kb)

Supplementary Table 8

Full list of differentially expressed genes. (XLS 979 kb)

Supplementary Table 10

List of genes affected by copy number variations. (XLS 3064 kb)

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Yoo, H., Sung, M., Lee, S. et al. A recurrent inactivating mutation in RHOA GTPase in angioimmunoblastic T cell lymphoma. Nat Genet 46, 371–375 (2014) doi:10.1038/ng.2916

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