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The serine hydroxymethyltransferase-2 (SHMT2) initiates lymphoma development through epigenetic tumor suppressor silencing

Nature Cancer volume 1, pages 653–664 (2020)Cite this article

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Abstract

Cancer cells adapt their metabolic activities to support growth and proliferation. However, increased activity of metabolic enzymes is not usually considered an initiating event in the malignant process. Here, we investigate the possible role of the enzyme serine hydroxymethyltransferase-2 (SHMT2) in lymphoma initiation. SHMT2 localizes to the most frequent region of copy number gains at chromosome 12q14.1 in lymphoma. Elevated expression of SHMT2 cooperates with BCL2 in lymphoma development; loss or inhibition of SHMT2 impairs lymphoma cell survival. SHMT2 catalyzes the conversion of serine to glycine and produces an activated one-carbon unit that can be used to support S-adenosyl methionine synthesis. SHMT2 induces changes in DNA and histone methylation patterns leading to promoter silencing of previously uncharacterized mutational genes, such as SASH1 and PTPRM. Together, our findings reveal that amplification of SHMT2 in cooperation with BCL2 is sufficient in the initiation of lymphomagenesis through epigenetic tumor suppressor silencing.

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Fig. 1: Genomic amplification of SHMT2 in human B-cell lymphomas.
Fig. 2: SHMT2 acts as an oncogenic driver in a mouse model of FL.
Fig. 3: MYC regulates the expression of SHMT2 in both human and mice tFL.
Fig. 4: Targeting SHMT2 activity or expression for lymphoma therapy.
Fig. 5: Epigenetic studies of VavP-Bcl2; SHMT2 B cells.
Fig. 6: Epigenetic silencing of tumor suppressor genes contributes to the oncogenic action of SHMT2.
Fig. 7: Characterization of candidate tumor suppressor genes in vivo.

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Data availability

Sequencing (RNA-seq, proton sequencing, ChIP–seq and ERRBS) data that support the findings of this study have been deposited in the Gene Expression Omnibus under accession codes GSE142336 and GSE139523. Previously published microarray data that were reanalyzed in this study are available under accession code GSE132929. Histone mass spectrometry data were deposited to MassIVE under accession code MSV000085251. Source data for Figs. 1–7 and Extended Data Fig. 2 have been provided as Source Data Files 1–12. All other data supporting the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

Any custom computer code or algorithm previously used to generate results that are reported in this paper and central to its main claims are available upon request.

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Acknowledgements

We thank R.L. Possemato (NYU) for sharing the pMXS-IRES-blast; SHMT2res and pMXS-IRES-blast; SHMT2-CD (SHMT2 K280A) plasmids, and T. Oellerich for sharing the lentiviral catalytic dead SHMT2 (SHMT2 K280A) plasmid. We thank Raze Therapeutics for sharing the SHIN1 drug. We thank K.R. Keshari, L.W.S. Finely, W. Beguelin and L. Cerchietti for helpful discussions and suggestions. We thank V. Sanghavi, K. Singh, D. Salloum and other members of Wendel laboratory for advice and reagents. Also, we thank V. Di Gialleonardo and C. Duy. We thank all members of the MSK Antitumor Assessment Core for technical assistance with the mice; the MSK Laboratory of Comparative Pathology and MSK Flow Cytometry for their support in processing biological samples; and the Weill Cornell Epigenomics Core for performing the RNA-seq, ERBBS and ChIP–seq. We acknowledge the use of the Integrated Genomics Operation Core, funded by an NCI Cancer Center Support Grant (CCSG, P30 CA08748), Cycle for Survival and the Marie-Josée and Henry R. Kravis Center for Molecular Oncology. This research was supported by funding from the National Institutes of Health (NIH) SPORE in Soft Tissue Sarcoma (grant no. P50 CA217694 to H.-G.W.), Starr Cancer Consortium (to H.-G.W. and B.-K), Technology Development Fund (grant no. GC230724 to H.-G.W.), Starr Cancer Consortium (grant no. I10-0064 to H.-G.W.), the Lymphoma Research Foundation (grant no. GC233089 to H.-G.W.), NIH grant nos. RO1CA183876-05, RO1CA207217-03, NIH Spore P50 CA192937-03, LLS 7014-17 and LLS 1318-15 (to H.-G.W.). H.-G.W. is a Scholar of the Leukemia and Lymphoma Society.

Author information

Author notes

  1. These authors contributed equally: Sara Parsa, Ana Ortega-Molina.

Authors and Affiliations

  1. Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Sara Parsa, Ana Ortega-Molina, Man Jiang, Chunying Zhao, Joyce P. Pasion, Prathibha Mohan, Shenqiu Wang, Nicholas Socci, Elisa De Stanchina & Hans-Guido Wendel

  2. Department of Medicine and Weill Cornell Cancer Center, Weill Cornell Medicine, New York, NY, USA

    Hsia-Yuan Ying, Matt Teater & Ari M. Melnick

  3. The Jackson Laboratory Cancer Center, Farmington, CT, USA

    Jiahui Wang & Sheng Li

  4. Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Ed Reznik

  5. Department of Physiology, Biophysics, and Systems Biology, Weill Cornell Graduate School of Medical Sciences, New York, NY, USA

    David Kuo

  6. Department of Chemistry, Molecular Biosciences and the National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA

    Jeannie M. Camarillo, Paul M. Thomas, Byoung-kyu Cho & Neil L. Kelleher

  7. Department of Lymphoma and Myeloma, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Neeraj Jain & Michael R. Green

  8. Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Neeraj Jain & Michael R. Green

  9. Laboratory of Metabolic Regulation and Genetics, Rockefeller University, New York, NY, USA

    Javier Garcia-Bermudez & Kivanc Birsoy

  10. Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA

    Wayne Tam

  11. Hematopathology Service, Departments of Pathology and Laboratory Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY, USA

    Ahmet Dogan

  12. Department of Computational Biology, University of Lausanne, Lausanne, Switzerland

    Giovanni Ciriello

  13. Swiss Institute of Bioinformatics, Lausanne, Switzerland

    Giovanni Ciriello

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  1. Sara Parsa
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Contributions

S.P. contributed to the conception and design of the study, the development of its methodology, the acquisition of data, data analysis and interpretation, and the writing and revision of the manuscript. A.O.-M. contributed to the conception and design of the study, the development of its methodology, the acquisition of data, data analysis and interpretation, and the writing and revision of the manuscript. H.-Y.Y., M.J., C.Z., J.M.C., J.P.P., P.M., S.W., P.M.T., B.-K.C., N.L.K., J.G-B., W.T., E.D.S. and N.L.K. contributed to the acquisition of data (provided animals, acquired and provided patient samples, provided facilities). J.W., M.T., E.R., D.K., N.J., A.D., N.S. and G.C. contributed to the analysis and interpretation of data (for example, statistical analysis, biostatistics, computational analysis). A.D. contributed to the analysis and interpretation of histological samples. M.R.G. contributed to the analysis and interpretation of genomics data (statistical studies) and reviewed the manuscript. S.L. contributed to the statistical analysis of data and reviewed the manuscript. K.B. contributed to the conception and design of the experiments, data analysis and interpretation, and reviewed the manuscript. A.M.M. contributed to the conception and design of the study, the development of its methodology, data analysis and interpretation, and reviewed the manuscript. H.-G.W. contributed to the conception and design of the study, the development of its methodology, data analysis and interpretation, and wrote and revised the manuscript.

Corresponding author

Correspondence to Hans-Guido Wendel.

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Competing interests

A.D. has received personal consultancy fees from Roche, Corvus Pharmaceuticals, Physicians’ Education Resource, Seattle Genetics, Takeda, EUSA Pharma and AbbVie, and research grants from Roche. The other authors declare no competing interests.

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Extended data

Extended Data Fig. 1 De novo serine synthesis pathway in human B cell lymphoma.

a, Bar graphs presenting the functional gain (red) or loss (blue) of SHMT2 located on chromosome 12 by DNA copy number analysis of 568 DLBCL and 176 FL tumors. b, The frequency of loss (blue), gain (red) or diploid (black) status of serine synthesis pathway genes in 568 human DLBCL and 176 human FL tumors. c, Diagrams demonstrating the overlaps of amplification (red) and loss (blue) of SHMT2 vs other serine biosynthesis pathway enzymes (PSPH, PHGDH, PSAT1, SHMT1) in 568 DLBCL and 176 FL tumors. d, Bar graph showing the frequency of SHMT2 amplification in different subtype (GC-like, ABC-like or unclassified) of 249 human DLBCL tumors.

Extended Data Fig. 2 SHMT2 promotes lymphomagenesis in vivo.

a, Diagram of FL mouse model. Fetal VavPBcl2 HSCs were transduced by MSCV-GFP plasmid carrying SHMT2 cDNA or empty vector and injected to lethally irradiated female mice. b, Representative graphs of flow cytometry analysis comparing GFP+ HSCs before injection vs GFP+ splenic lymphoma cells from VavPBcl2;vector- and VavPBcl2;SHMT2- induced tumors collected 5 months after injection. c, Dot plot representing the initial GFP+ cells in hematopoietic stem cells before injection vs GFP+ cells enriched in splenic cells collected from VavP-Bcl2;vector (N = 5 mice) and VavP-Bcl2;SHMT2 (N = 10 mice) tumors. Two-tailed Student’s t-test was used to determine statistical significance; VavP-Bcl2;vector: P(HSCvsLymphoma)= 0.443, NS; VavP-Bcl2;SHMT2: P(HSCvsLymphoma)=0.0006. d, Representative images of histology studies of VavPBcl2;vector and VavPBcl2;SHMT2 lung. The slides were stained with H&E, and antibodies for B220, TUNEL, Ki67, PNA. This experiment was independently repeated three times with similar results. Scale Bars, 500 nm. e, tumor clonality analysis on B220+ cDNA collected from VavPBcl2;vector vs VavPBcl2;SHMT2 tumors. Each lane corresponds to one tumor. This experiment was independently repeated two times with four independent samples in each genotype with similar results f, Immunoblot against SHMT2, SHMT1 and ACTIN in DLBCL cell lines carrying two different short hairpins against SHMT2. This experiment was independently repeated two times with similar results. The uncropped images of the original blots are presented in Source Data Extended Data File 12. The numerical data for this figure are presented in Source Data Extended Data File 2.

Source data

Supplementary information

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Supplementary Tables

Supplementary Tables 1–13.

Source data

Source Data Fig. 1

Numerical data for Fig. 1.

Source Data Fig. 2

Unprocessed western blots for Fig. 2b.

Source Data Fig. 2

Numerical data for Fig. 2.

Source Data Fig. 2

Histological micrographs and flow cytometry analysis of replicates in Fig. 2e,f.

Source Data Fig. 3

Unprocessed western blots for Fig. 3j.

Source Data Fig. 3

Numerical data for Fig. 3.

Source Data Fig. 4

Unprocessed western blots for Fig. 4g.

Source Data Fig. 4

Numerical data for Fig. 4.

Source Data Fig. 4

Flow cytometry analysis of replicates in Fig. 4b,f.

Source Data Fig. 5

Numerical data for Fig. 5.

Source Data Fig. 5

Unprocessed dot blots for Fig. 5.

Source Data Fig. 6

Numerical data for Fig. 6.

Source Data Fig. 7

Histological micrographs and flow cytometry analysis of replicates in Fig. 7.

Source Data Fig. 7

Numerical data for Fig. 7.

Source Data Extended Data Fig. 2

Unprocessed western blots for Extended Data Fig. 2.

Source Data Extended Data Fig. 2

Numerical data for Extended Data Fig. 2.

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Parsa, S., Ortega-Molina, A., Ying, HY. et al. The serine hydroxymethyltransferase-2 (SHMT2) initiates lymphoma development through epigenetic tumor suppressor silencing. Nat Cancer 1, 653–664 (2020). https://doi.org/10.1038/s43018-020-0080-0

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