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.

ARID2 deficiency promotes tumor progression and is associated with higher sensitivity to chemotherapy in lung cancer

Abstract

The survival rate in lung cancer remains stubbornly low and there is an urgent need for the identification of new therapeutic targets. In the last decade, several members of the SWI/SNF chromatin remodeling complexes have been described altered in different tumor types. Nevertheless, the precise mechanisms of their impact on cancer progression, as well as the application of this knowledge to cancer patient management are largely unknown. In this study, we performed targeted sequencing of a cohort of lung cancer patients on genes involved in chromatin structure. In addition, we studied at the protein level the expression of these genes in cancer samples and performed functional experiments to identify the molecular mechanisms linking alterations of chromatin remodeling genes and tumor development. Remarkably, we found that 20% of lung cancer patients show ARID2 protein loss, partially explained by the presence of ARID2 mutations. In addition, we showed that ARID2 deficiency provokes profound chromatin structural changes altering cell transcriptional programs, which bolsters the proliferative and metastatic potential of the cells both in vitro and in vivo. Moreover, we demonstrated that ARID2 deficiency impairs DNA repair, enhancing the sensitivity of the cells to DNA-damaging agents. Our findings support that ARID2 is a bona fide tumor suppressor gene in lung cancer that may be exploited therapeutically.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Frequent ARID2 mutations associated with protein loss.
Fig. 2: ARID2 deficiency is associated with an increase in oncogenesis in vitro and in vivo.
Fig. 3: Profound chromatin structural changes on enhancers affect gene expression after ARID2 loss.
Fig. 4: ARID2 deficiency affects DNA repair and affects sensitivity to antitumor therapies.

Data availability

DNA-Seq, ATAC-Seq, and RNA-Seq data: https://www.ebi.ac.uk/ena/data/search?query=PRJEB26936.

Code availability

All computer code is available upon request.

References

  1. 1.

    Lovly CM, Carbone DP. Lung cancer in 2010: one size does not fit all. Nat Rev Clin Oncol. 2011;8:68–70.

    CAS  PubMed  Google Scholar 

  2. 2.

    Gelsomino F, Rossi G, Tiseo M. MET and small-cell lung cancer. Cancers. 2014;6:2100–15.

    PubMed  PubMed Central  Google Scholar 

  3. 3.

    Chen Z, Fillmore CM, Hammerman PS, Kim CF, Wong K-K. Non-small-cell lung cancers: a heterogeneous set of diseases. Nat Rev Cancer. 2014;14:535–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Masliah-Planchon J, Bièche I, Guinebretière J-M, Bourdeaut F, Delattre O. SWI/SNF chromatin remodeling and human malignancies. Annu Rev Pathol Mech Dis. 2015;10:145–71.

    CAS  Google Scholar 

  5. 5.

    Reisman DN, Sciarrotta J, Wang W, Funkhouser WK, Weissman BE. Loss of BRG1/BRM in human lung cancer cell lines and primary lung cancers: correlation with poor prognosis. Cancer Res. 2003;63:560–6.

    CAS  PubMed  Google Scholar 

  6. 6.

    Imielinski M, Berger AH, Hammerman PS, Hernandez B, Pugh TJ, Hodis E, et al. Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing. Cell. 2012;150:1107–20.

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Mularoni L, Sabarinathan R, Deu-Pons J, Gonzalez-Perez A, López-Bigas N. OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations. Genome Biol. 2016;17:128. https://doi.org/10.1186/s13059-016-0994-0.

  8. 8.

    Forbes SA, Beare D, Boutselakis H, Bamford S, Bindal N, Tate J, et al. COSMIC: somatic cancer genetics at high-resolution. Nucleic Acids Res. 2017;45:D777–83.

    CAS  PubMed  Google Scholar 

  9. 9.

    Sheffield NC, Thurman RE, Song L, Safi A, Stamatoyannopoulos JA, Lenhard B, et al. Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions. Genome Res. 2013;23:777–88.

    CAS  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Fishilevich S, Nudel R, Rappaport N, Hadar R, Plaschkes I, Iny Stein T, et al. GeneHancer: genome-wide integration of enhancers and target genes in GeneCards. Database. 2017;2017. https://doi.org/10.1093/database/bax028.

  11. 11.

    Kayser G, Csanadi A, Kakanou S, Prasse A, Kassem A, Stickeler E, et al. Downregulation of MTSS1 expression is an independent prognosticator in squamous cell carcinoma of the lung. Br J Cancer. 2015;112:866–73.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Lord CJ, Ashworth A. PARP inhibitors: synthetic lethality in the clinic. Science. 2017;355:1152–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Manceau G, Letouzé E, Guichard C, Didelot A, Cazes A, Corté H, et al. Recurrent inactivating mutations of ARID2 in non-small cell lung carcinoma. Int J Cancer. 2013;132:2217–21.

    CAS  PubMed  Google Scholar 

  14. 14.

    Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, Theurillat J-P, et al. A landscape of driver mutations in melanoma. Cell. 2012;150:251–63.

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Li M, Zhao H, Zhang X, Wood LD, Anders RA, Choti MA, et al. Inactivating mutations of the chromatin remodeling gene ARID2 in hepatocellular carcinoma. Nat Genet. 2011;43:828–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Flowers S, Beck GR, Moran E. Transcriptional Activation by pRB and Its Coordination with SWI/SNF Recruitment. Cancer Res. 2010;70:8282–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Tordella L, Khan S, Hohmeyer A, Banito A, Klotz S, Raguz S, et al. SWI/SNF regulates a transcriptional program that induces senescence to prevent liver cancer. Genes Dev. 2016;30:2187–98.

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Romero OA, Torres-Diz M, Pros E, Savola S, Gomez A, Moran S, et al. MAX inactivation in small cell lung cancer disrupts MYC-SWI/SNF programs and is synthetic lethal with BRG1. Cancer Discov. 2014;4:292–303.

    CAS  PubMed  Google Scholar 

  19. 19.

    Wilson BG, Roberts CWM. SWI/SNF nucleosome remodellers and cancer. Nat Rev Cancer. 2011;11:481–92.

    CAS  PubMed  Google Scholar 

  20. 20.

    Alver BH, Kim KH, Lu P, Wang X, Manchester HE, Wang W, et al. The SWI/SNF chromatin remodelling complex is required for maintenance of lineage specific enhancers. Nat Commun. 2017;8:14648.

    PubMed  PubMed Central  Google Scholar 

  21. 21.

    Nakayama RT, Pulice JL, Valencia AM, McBride MJ, McKenzie ZM, Gillespie MA. et al. SMARCB1 is required for widespread BAF complex–mediated activation of enhancers and bivalent promoters. Nat Genet. 2017;46:1613–23. https://doi.org/10.1038/ng.3958.

    CAS  Article  Google Scholar 

  22. 22.

    Giacobbe A, Compagnone M, Bongiorno-Borbone L, Antonov A, Markert EK, Zhou JH, et al. p63 controls cell migration and invasion by transcriptional regulation of MTSS1. Oncogene. 2016;35:1602–8.

    CAS  PubMed  Google Scholar 

  23. 23.

    Taylor MD, Bollt O, Iyer SC, Robertson GP. Metastasis suppressor 1 (MTSS1) expression is associated with reduced in-vivo metastasis and enhanced patient survival in lung adenocarcinoma. Clin Exp Metastasis. 2018;35:15–23.

    CAS  PubMed  Google Scholar 

  24. 24.

    Lee H-S, Park J-H, Kim S-J, Kwon S-J, Kwon J. A cooperative activation loop among SWI/SNF, γ-H2AX and H3 acetylation for DNA double-strand break repair. EMBO J. 2010;29:1434–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Niimi A, Chambers AL, Downs JA, Lehmann AR. A role for chromatin remodellers in replication of damaged DNA. Nucleic Acids Res. 2012;40:7393–403.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Ray A, Mir SN, Wani G, Zhao Q, Battu A, Zhu Q, et al. Human SNF5/INI1, a component of the human SWI/SNF chromatin remodeling complex, promotes nucleotide excision repair by influencing ATM recruitment and downstream H2AX phosphorylation. Mol Cell Biol. 2009;29:6206–19.

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Rugo HS, Olopade OI, DeMichele A, Yau C, van’t Veer LJ, Buxton MB, et al. Adaptive randomization of Veliparib–Carboplatin treatment in breast cancer. N Engl J Med. 2016;375:23–34.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Pan D, Kobayashi A, Jiang P, Ferrari de Andrade L, Tay RE, Luoma A, et al. A major chromatin regulator determines resistance of tumor cells to T cell–mediated killing. Science. 2018;359:770–5.

  29. 29.

    Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25:1754–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–9.

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20:1297–303.

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Martínez N, Almaraz C, Vaqué JP, Varela I, Derdak S, Beltran S, et al. Whole-exome sequencing in splenic marginal zone lymphoma reveals mutations in genes involved in marginal zone differentiation. Leukemia. 2014;28:1334–40.

    PubMed  Google Scholar 

  33. 33.

    Ye K, Schulz MH, Long Q, Apweiler R, Ning Z. Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads. Bioinformatics. 2009;25:2865–71.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9:R137.

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Yu G, Wang L-G, He Q-Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 2015;31:2382–3.

    CAS  PubMed  Google Scholar 

  37. 37.

    Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26:841–2.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Ramírez F, Ryan DP, Grüning B, Bhardwaj V, Kilpert F, Richter AS, et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 2016;44:W160–5.

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–89.

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Robinson JT, Thorvaldsdóttir H, Wenger AM, Zehir A, Mesirov JP. Variant review with the integrative genomics viewer. Cancer Res. 2017;77:e31–4.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14:R36.

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11:R106.

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Anders S, Pyl PT, Huber W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9.

    CAS  Google Scholar 

  44. 44.

    Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci. 2005;102:15545–50.

    CAS  PubMed  Google Scholar 

  45. 45.

    Lauand C, Niero EL, Dias VM, Machado-Santelli GM. Cell cycle synchronization and BrdU incorporation as a tool to study the possible selective elimination of ErbB1 gene in the micronuclei in A549 cells. Braz J Med Biol Res Rev Bras Pesqui Medicas E Biol. 2015;48:382–91.

    CAS  Google Scholar 

Download references

Acknowledgements

In memoriam of Carlos Revilla, we will miss you forever. We would like to thank the support of the funding agencies Ministerio de Economía y Competitividad, Fundación Ramón Areces, European Research Council, Asociación Española contra el cáncer, Cancer Research UK, UK Medical Research Council, Wellcome Trust, Servicio de Salud del Principado de Asturias, Instituto de Salud Carlos III and Fundación Bancaria Cajastur (specific grant references are included in the funding support section). We will like to thank as well the technical support of the different institutions and common services as well as the patients that agreed to participate in this study. We finally want to thank Dr Francisco Real, Dr Roland Rad, Dr Jose Pedro Vaqué, and Dr Javier Leon for providing critical reagents and advice as well as to all the patients that agreed to participate in this study. For the purpose of Open Access, the authors have applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

Funding

IV is supported by SAF2012-31627 and SAF2016-76758-R grants from the Spanish Ministerio de Economía y Competitividad (MINECO), by a Fundación Ramón Areces grant and by ERC2014-StG637904 grant from the European Research Council. IV has been awardee of the Programa Ramón y Cajal (MINECO, Spain). TM has been awardee of the Ayudas para la contratación de investigadores predoctorales (MINECO, Spain). BM is awardee of the Ayudas para la formación de profesorado universitario (FPU, Ministerio de Educación y Formación Profesional, Spain). PC laboratory is supported by grant SAF-2015-63638R (MINECO/FEDER, UE); by Centro de Investigación Biomédica en Red de Cáncer (CIBERONC) and by Asociación Española Contra el Cáncer (AECC), grant GCB141423113. BC has been supported by a Retos Jóvenes Investigadores grant SAF-2015-73364-JIN (AEI/FEDER, UE) and a grant from Fundación Francisco Cobos. PS is supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001152) and the UK Medical Research Council (FC001152). HUCA/IUOPA is jointly financed by Servicio de Salud del Principado de Asturias, Instituto de Salud Carlos III, and Fundación Bancaria Cajastur. This research was funded in part by the Wellcome Trust [FC001152].

Author information

Affiliations

Authors

Corresponding author

Correspondence to Ignacio Varela.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Moreno, T., Monterde, B., González-Silva, L. et al. ARID2 deficiency promotes tumor progression and is associated with higher sensitivity to chemotherapy in lung cancer. Oncogene 40, 2923–2935 (2021). https://doi.org/10.1038/s41388-021-01748-y

Download citation

Search

Quick links