Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter to the Editor
  • Published:

Complete mutational spectrum of the autophagy interactome: a novel class of tumor suppressor genes in myeloid neoplasms

Leukemia volume 31, pages 505–510 (2017)Cite this article

Subjects

Analysis of the cytogenetic profiles of the mutant patients showed that four genes mapped to commonly deleted regions, for example, 5q (CDKN2AIPNL, SQSTM1) or 7q (SMURF1, PRKAG2) and coincided with haploinsufficient expression, whereas three genes had hemizygous configuration (SMURF1, PPP2R3A, PIK3C2G) (Supplementary Table S2). Analysis of the variant types showed that loss-of-function mutations were observed in ULK4 (stopgain; p.L1220X), NOD2 (stopgain; p.E1008X), VTI1A (stopgain; p.E53X), PTPN2 (stopgain; p.R26X), PRKAA2 (stopgain; p.R227X), VPS11 (frameshift insertion; p.S64fs*), DNM2 (frameshift insertion; T471fs*), WAC (frameshift insertion; p.E87fs) and USP10 (frameshift deletion; p.P386fs*) genes. We also dissected the clonal hierarchy of autophagy gene mutations. Clonal hierarchy showed that autophagy mutations were predominantly secondary events, were ancestral events in seven patients (ATG2A, SEC22B, STAT3, PRKACB, DNML1, PTPN2, PRKAG1) and co-dominant in two patients (NOD2, MLST8). When autophagy gene mutations were secondary, the most represented ancestral mutations were in splicing factors (N=9; SRSF2, PRPF8, U2AF1) and DNA methylation genes (N=4; TET2, DNMT3A). The characterization of ancestral vs secondary events suggested to us that autophagy gene mutations are cooperative rather than initiating events in clonal evolution. We also observed that autophagy gene mutations are secondary mutations in several cases when ancestral mutations occurred in splicing factor genes. A recent article reported that autophagy genes may be implicated in the epigenetic mechanism of patients with MDS carrying U2AF1 mutations and may contribute to disease phenotypes. U2AF1S34 mutation has been described to possibly promote leukemogenesis by aberrant splicing of the autophagy gene ATG7.4 This observation led us to investigate whether epigenetic defects in autophagy genes are also commonly detected in MDS and, if present, whether they correlate with specific biological and clinical MDS phenotypes. We analyzed RNA sequencing of patients with MDS and found that the expression levels of several autophagy genes were increased in SF3B1MUT MDS compared with SF3B1WT MDS cells: early-stage autophagy genes (ATG2A/B, FC=2; ATG4A, FC=2; ATG9A, FC=5; ATG4C, P=0.05; ATG18 (FC=4.8; P=0.02), autophagy-initiating kinases (ULK1, FC=2; ULK3, FC=3.9; P=0.05) and late stage autophagy genes (CTSL1, FC=20; CTSD, FC=5.8; P=0.05; CTSB, FC=2.1; CTSE, FC=5.9; CTSD, FC=2; P=0.01). Of note, two genes (ATG2A and ATG4C) carried somatic mutations and increased expression levels. One of them, ATG2A was also an ancestral event when mutated. We originally reported a list of genes found differentially expressed in Sf3b1+/− murine BM cells compared with Sf3b1+/+ murine BM cells5 (Supplementary Table S1) by RNA sequencing analysis. Interestingly enough, we merged the list of genes found mutated in our cohort of patients with the list of genes found modulated in Sf3b1+/− mice and found that 17 genes were up-regulated more than twofold change in our mouse model of MDS (ATG16L1, PIK3CB, GYS1, SEC22B, KIF1B, STAT3, VT1A, TNFSF10, PTPN2, DNML1, DNM2, HIF1A, MLST8, CDKN2AIPNL, WAC, BCL2, USP10). These observations suggested that the autophagy pathway can potentially be targeted in MDS cells for therapeutic benefit. Autophagy gene mutations were most prevalent in high-risk MDS (12/40; 30%) and almost equally prevalent in sAML and pAML patients (6/9). A total of 21/37 (57%) had abnormal karyotype with 4 patients having complex karyotype including −17 and −7. Among the cases with abnormal karyotype, 4 cases had del (5q). Overall, 21 patients had a fatal outcome. Comparative analysis of Sanger sequencing, TruSeq-targeted DNA sequencing, WES and TCGA data was used to assess the global mutational spectrum of the patients harboring mutations in the autophagy network. We found that the most commonly mutated gene was TET2 (11/40; 27.5%), followed by RUNX1 and STAG2 (8/40; 20%), SRSF2 (7/40; 7.5%) and DNMT3A and ASXL1 (6/40; 15%). Hemizygosity due to somatic deletions for genes associated with poor prognosis was also noted (TP53: 2 patients; PRPF8, CUX1, DDX41: 1 patient each) (Figure 1c). Comparative analysis (Sanger, TruSeq, WES, TCGA) found that patients with autophagy-related genes are more susceptible to acquire mutations in signal transduction pathways (26 mutations), DNA methylation (24 mutations) and RNA-splicing (20 mutations) (Figure 1c; Supplementary Figure S2). Twenty-five mutations had a cut-off more than 20% variant allele frequency (Supplementary Figure S3). Targeted-gene panel sequencing was applied for 22 genes and confirmed the presence of high-variant allele frequency mutations like NOD2 (63%), PIK3C2B (44%), PRKACB (36%) and STAT3 (38%). The majority of mutant patients had a dismal prognosis, suggesting that these patients had cumulative unfavorable mutations like RUNX1, ASXL1, DNMT3A and that these negative prognostic mutations6 represented driver mutations in these patients. Seven patients receiving hypomethylating agents had no response to therapy (Supplementary Table S1). Comparison of mutant and wild type (WT) patients showed that mutant patients had lower survival trending toward significance compared with WT (14 months vs 20 months; NMUT vs NWT=20 vs 90; log-rank=0.09). Among disease subtypes, autophagy network mutations were associated with significantly inferior survival in patients with MDS (NMUT=13, mean survival: 17 months; NWT=61, mean survival: 35 months, log-rank: 0.0187) and MDS/MPN overlap syndromes (NMUT=4, mean survival: 12 months; NWT=31, mean survival: 30 months, log-rank: 0.0374).

Given the recent discovery of familial AML and MDS cases carrying pathogenic germline variants,7, 8 we also evaluated whether the same autophagy genes we found to be somatically mutated may also be prone to germline alterations. An in house analysis of a database of 263 973 variants obtained from WES was conducted by testing different predictive tools assessing deleterious variants and by calling a variant as deleterious if present as deleterious in all predictive scores (Supplementary Methods). We found four variants in three genes among four patients with possible deleterious exonic non-synonymous variants that were predicted to be significantly damaging by all the tested scores: PIK3C2G (rs377020826, c.T3083C, total allele frequency: 0.0001; rs201569993, c.C2938T, total allele frequency: 0.0007), NOD2 (rs104895423, c.T662G, total allele frequency: 0.0006) and HIF1A (c.A1666G; total allele frequency: undetermined) (Supplementary Table S3). In total, PIK3C2G carried one somatic and two germline variants, NOD2 had two somatic and one germline variants, and HIF1A harbored one somatic and one germline variant. A complete table summarizes the somatic and germline status of the variants we identified in the autophagy pathway (Supplementary Table S4).

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1

References

  1. Kroemer G . Autophagy: a druggable process that is deregulated in aging and human disease. J Clin Invest 2015; 125: 1–4.

    Article  Google Scholar 

  2. Thorburn A, Thamm DH, Gustafson DL . Autophagy and cancer therapy. Mol Pharmacol 2014; 85: 830–838.

    Article  Google Scholar 

  3. White E . The role for autophagy in cancer. J Clin Invest 2015; 125: 42–46.

    Article  Google Scholar 

  4. Park SM, Ou J, Chamberlain L, Simone TM, Yang H, Virbasius CM et al. U2AF35(S34F) promotes transformation by directing aberrant ATG7 pre-mRNA 3' end formation. Mol Cell 2016; 62: 479–490.

    Article  CAS  Google Scholar 

  5. Visconte V, Tabarroki A, Zhang L, Parker Y, Hasrouni E, Mahfouz R et al. Splicing factor 3b subunit 1 (Sf3b1) haploinsufficient mice display features of low risk Myelodysplastic syndromes with ring sideroblasts. J Hematol Oncol 2014; 7: 89.

    Article  Google Scholar 

  6. Harada H, Harada Y . Recent advances in myelodysplastic syndromes: molecular pathogenesis and its implications for targeted therapies. Cancer Sci 2015; 106: 329–336.

    Article  CAS  Google Scholar 

  7. Liew E, Owen C . Familial myelodysplastic syndromes: a review of the literature. Haematologica 2011; 96: 1536–1542.

    Article  Google Scholar 

  8. Churpek JE, Pyrtel K, Kanchi KL, Shao J, Koboldt D, Miller CA et al. Genomic analysis of germ line and somatic variants in familial myelodysplasia/acute myeloid leukemia. Blood 2015; 126: 2484–2490.

    Article  CAS  Google Scholar 

  9. Gong C, Song E, Codogno P, Mehrpour M . The roles of BECN1 and autophagy in cancer are context dependent. Autophagy 2012; 8: 1853–1855.

    Article  CAS  Google Scholar 

  10. Liang C, Jung JU . Autophagy genes as tumor suppressors. Curr Opin Cell Biol 2010; 22: 226–233.

    Article  CAS  Google Scholar 

  11. Kim HJ, Zhong Q, Sheng ZH, Yoshimori T, Liang C, Jung JU . Beclin-1-interacting autophagy protein Atg14L targets the SNARE-associated protein Snapin to coordinate endocytic trafficking. J Cell Sci 2012; 125: 4740–4750.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by the Scott Hamilton CARES (VV) and 2016 ASH Scholar award (VV), the National Cancer Institute grants R01CA172443 (JSC) and R01CA190789 (STN). We thank The Cancer Genome Atlas (TCGA) data portal and cBioPortal for Cancer Genomics to allow us the retrieval of helpful information.

Author contributions

VV designed the study, analyzed and interpreted data and wrote the manuscript; BP analyzed and interpreted the data and edited the manuscript; YH performed experiments and edited the manuscript; STN analyzed and interpreted data and edited the manuscript; ST collected clinical data; KRK provided intellectual input; BJP collected clinical information; CH analyzed the data; ASA, HEC and MAS contributed to data interpretation and manuscript preparation; JMP contributed patient specimens and genomic data, and participated in data analysis and manuscript preparation; JSC designed the study, analyzed and interpreted data, and wrote the manuscript. All authors approved the manuscript before submission.

Author information

Authors and Affiliations

  1. Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA

    V Visconte, B Przychodzen, Y Han, S Thota, B J Patel, C Hirsch, M A Sekeres, J P Maciejewski & J S Carew

  2. Department of Medicine, Division of Translational and Regenerative Medicine, University of Arizona Cancer Center, Tucson, AZ, USA

    S T Nawrocki & J S Carew

  3. Department of Medicine, USC Norris Comprehensive Cancer Center, Los Angeles, CA, USA

    K R Kelly

  4. Department of Hematology/Oncology, Leukemia Program, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA

    A S Advani, H E Carraway & M A Sekeres

Authors
  1. V Visconte
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B Przychodzen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Y Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. S T Nawrocki
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S Thota
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. K R Kelly
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. B J Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. C Hirsch
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. A S Advani
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. H E Carraway
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. M A Sekeres
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. J P Maciejewski
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. J S Carew
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J S Carew.

Ethics declarations

Competing interests

JMP (Celgene and Ra Pharmaceuticals); and the remaining authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on the Leukemia website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Visconte, V., Przychodzen, B., Han, Y. et al. Complete mutational spectrum of the autophagy interactome: a novel class of tumor suppressor genes in myeloid neoplasms. Leukemia 31, 505–510 (2017). https://doi.org/10.1038/leu.2016.295

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/leu.2016.295

This article is cited by

Search

Advanced search

Quick links