What’s up with MALAT1?
Editorial

What’s up with MALAT1?

Gary A. Clawson

Department of Pathology & Biochemistry and Molecular Biology, Hershey Medical Center, Pennsylvania State University, Hershey, PA 17033, USA

Correspondence to: Gary A. Clawson, PhD, MD. Department of Pathology & Biochemistry and Molecular Biology, Hershey Medical Center, Pennsylvania State University, Hershey, PA 17033, USA. Email: Gac4gac4@gmail.com.

Provenance: This is an invited article commissioned by Executive Editor-in-Chief Dr. Hualin Sun (Jiangsu Key Laboratory of Neuroregeneration, Nantong University, Nantong, China).

Comment on: Kim J, Piao HL, Kim BJ, et al. Long noncoding RNA MALAT1 suppresses breast cancer metastasis. Nat Genet 2018;50:1705-15.


Received: 04 January 2019; Accepted: 07 January 2019; Published: 25 January 2019.

doi: 10.21037/biotarget.2019.01.01


Long noncoding RNAs (lncRNAs) comprise transcripts longer than 200 nucleotides which do not code for proteins. lncRNAs have engendered considerable interest with regard to their potential role(s) in metastasis and cancer progression, with particular interest focused on the lncRNA metastasis-associated lung adenocarcinoma transcript 1 [MALAT1; see (1,2) for recent reviews]. While nearly all reports on MALAT1 have described it as promoting cancer metastasis/progression, a recent report in Nature Genetics by Kim et al. (3) clearly and thoroughly describes a suppression of metastasis in human breast cancer cells and a variety of mouse models (transgenic, xenograft, and syngeneic). In their molecular studies, these authors found that MALAT1 interferes with the pro-metastatic transcription factor TEAD, preventing it from interacting with its co-activator YAP, and thus interfering with activity at target gene promoters (there were also a number of other MALAT1 interacting factors identified, although these consisted of a bewildering array of other proteins containing cytosolic proteins, neurofilaments, etc.). Kim et al. (3) point out that other reports in general “have never been validated to be MALAT1 specific through rescue experiments”: While this is true, it is not tantamount to declaring that all pro-metastatic results are wrong. There are several examples of particular genes acting as tumor suppressor in one setting vs. oncogene in another (e.g., the lncRNA XIST, etc.). In fact, there may be several reasons to question whether any particular molecular pathway(s) underpin the global effects of MALAT1 (and for that matter other lncRNAs) in cancers in general.

Perhaps more importantly than specific molecular mechanisms are the clinical ramifications of MALAT1 expression. Whereas the molecular pathway was clearly defined, the clinical results described by Kim et al. are at odds with nearly all the existing literature: They found that “lower MALAT1 levels correlated with shorter distant metastasis-free survival in total breast cancers and in luminal A and basal subtypes”, although these results are unfortunately relegated to supplementary materials. Diametrically opposed to this, there are a large number of studies which have clearly (and uniformly) documented just the opposite, with MALAT1 expression levels directly related to poor clinical outcomes, which creates a real problem for interpretation. Furthermore, it should be noted that the clinical correlations are essentially independent of any putative molecular mechanisms observed in companion studies. Several large studies have correlated MALAT1 expression levels with poor clinical outcomes in many cancers [including overall survival, disease free survival, lymph node metastases, distant metastases, etc.; see (4-6) for recent meta-analyses; these included 87 studies encompassing 11,066 patients], and the literature also prominently includes correlations between MALAT1 expression and poor clinical outcomes in breast cancer [(7-10); these included 2,320 patients]. In addition, there are even genetic variants of MALAT1 which appear to impact breast cancer susceptibility and even expression levels (11).

It is noteworthy that these meta-analyses extracted data directly from publications meeting generally strict inclusion criteria, or generated their own data in general. While the analyses presented by Kim et al. (3) appear to be standard approaches, it should be noted that they often included relatively small numbers of samples, and/or they relied on TCGA data, which are known to suffer from various problems, which seem to be increasingly recognized (12-14). Wang et al. (13) actually identified MALAT1 as being badly under covered in large numbers of “exome” samples across multiple cohorts within the TCGA data. In fact, they determined that the commonly used VCRome exome capture kit does not even contain probes for the loci containing MALAT1 (and for that matter XIST). How this may relate to a potential misinterpretation of MALAT1 expression levels is not clear, although it seems quite likely that RNASeq (transcriptome) data may not be optimized for amplifications of lncRNAs.

To further complicate matters significantly, expression levels of several other lncRNAs also correlate with poor clinical outcomes in cancer patients in essentially the same manner as MALAT1 does. Specific examples where expression levels of lncRNAs have been directly correlated with poor clinical outcomes include NEAT1 (15), HOTAIR (16), LINC00152 (17), XIST (18,19), AFAP1-AS1 (20), HULC (21), CCAT2 (22), HOTTIP (23), and HOXA11-AS (24), as well as several lncRNAs considered together (25). This would seem to suggest that lncRNAs may be acting in a more global manner (26), perhaps involving complex competing endogenous RNA networks (27), and not necessarily through singular specific molecular pathways. This may well involve unique structural features of MALAT1 (28,29) and potentially the other lncRNAs as well [for example, HOTAIR appears to function as a scaffold (30)]. In fact, this seems to suggest some sort of “functional substitution” is possible between lncRNAs.

Finally, the other feature of MALAT1 expression which isn’t explained at all is the very high expression levels which are generally observed. The sheer magnitude of the high expression would not seem to be necessary to overwhelm particular transcription factors or other singular molecular targets. So, what’s really going on with MALAT1 and other lncRNAs?


Acknowledgements

None.


Footnote

Conflicts of Interest: The author has no conflicts of interest to declare.


References

  1. Zhang X, Hamblin MH, Yin KJ. The long noncoding RNA MALAT1: Its physiological and pathophysiological functions. RNA Biol 2017;14:1705-14. [Crossref] [PubMed]
  2. Liu J, Peng WX, Mo YY, et al. MALAT1-mediated tumorigenesis. Front Biosci (Landmark Ed) 2017;22:66-80. [Crossref] [PubMed]
  3. Kim J, Piao HL, Kim BJ, et al. Long noncoding RNA MALAT1 suppresses breast cancer metastasis. Nat Genet 2018;50:1705-15. [Crossref] [PubMed]
  4. Tian X, Xu G. Clinical value of lncRNA MALAT1 as a prognostic marker in human cancer: systematic review and meta-analysis. BMJ Open 2015;5:e008653. [Crossref] [PubMed]
  5. Wei Y, Niu B. Role of MALAT1 as a prognostic factor for survival in various caners: A systematic review of the literature with meta-analysis. Dis Markers 2015;2015:164635. [Crossref] [PubMed]
  6. Li J, Cui Z, Li H, et al. Clinicopathological and prognostic significance of long noncoding RNA MALAT1 in human cancers: a review and meta-analysis. Cancer Cell Int 2018;18:109. [Crossref] [PubMed]
  7. Xiping Z, Bo C, Shifeng Y, et al. Roles of MALAT1 in development and migration of triple negative and Her-2 positive breast cancer. Oncotarget 2017;9:2255-67. [PubMed]
  8. Miao Y, Fan R, Chen L, et al. Clinical significance of long non-coding RNA MALAT1 expression in tissue and serum of breast cancer. Ann Clin Lab Sci 2016;46:418-24. [PubMed]
  9. Huang NS, Chi YY, Xue JY, et al. Long non-coding RNA metastasis associated in lung adenocarcinoma transcript 1 (MALAT1) interacts with estrogen receptor and predicted poor survival in breast cancer. Oncotarget 2016;7:37957-65. [PubMed]
  10. Jadaliha M, Zong X, Malakar P, et al. Functional and prognostic significance of long non-coding RNA MALAT1 as a metastasis driver in ER negative lymph node negative breast cancer. Oncotarget 2016;7:40418-36. [Crossref] [PubMed]
  11. Peng R, Luo C, Guo Q, et al. Association analyses of genetic variants of long non-coding RNA MALAT1 with breast cancer susceptibility and mRNA expression of MALAT1 in Chinese Han population. Gene 2018;642:241-8. [Crossref] [PubMed]
  12. Buckley AR, Standish KA, Bhutani K, et al. Pan-cancer analysis reveals technical artifacts in TCGA germline. BMC Genomics 2017;18:458. [Crossref] [PubMed]
  13. Wang VG, Kim H, Chuang JH. Whole-exome sequencing capture kit biases yield false negative mutation calls in TCGA cohorts. PLoS One 2018;13:e0204912. [Crossref] [PubMed]
  14. Koire A, Katsonis P, Lichtarge O. Repurposing germline exomes of the cancer genome atlas demands a cautious approach and sample specific variant filtering. Pac Symp Biocomput 2016;21:207-18. [PubMed]
  15. Yang C, Li Z, Li Y, et al. Long non-coding RNA NEAT1 overexpression is associated with poor prognosis in cancer patients: a systematic review and meta-analysis. Oncotarget 2017;8:2672-80. [PubMed]
  16. Zhang Y, Wang LJ, Li WF, et al. The prognostic value of HOTAIR for predicting long-term prognosis of patients with gastrointestinal cancers. Medicine (Baltimore) 2018;97:e11139. [Crossref] [PubMed]
  17. Zhang J, Yin M, Huang J, et al. Long noncoding RNA LINC00152 as a novel predictor of lymph node metastasis and survival in human cancer: a systematic review and meta-analysis. Clin Chim Acta 2018;483:25-32. [Crossref] [PubMed]
  18. Zhou Q, Hu W, Zhu W, et al. Long non coding RNA XIST as a prognostic cancer marker - A meta-analysis. Clin Chim Acta 2018;482:1-7. [Crossref] [PubMed]
  19. Mao H, Wang K, Feng Y, et al. Prognostic role of long non-coding RNA XIST expression in patients with solid tumors: a meta-analysis. Cancer Cell Int 2018;18:34. [Crossref] [PubMed]
  20. Zhou Y, Chen S, Cheng S, et al. The prognostic value of high LncRNA AFAP1-AS1 expression in various cancers: A systematic review and meta-analysis containing 21 studies. Clin Chim Acta 2018;481:147-53. [Crossref] [PubMed]
  21. Chen X, Lun L, Hou H, et al. The value of lncRNA HULC as a prognostic factor for survival of cancer outcome: A meta-analysis. Cell Physiol Biochem 2017;41:1424-34. [Crossref] [PubMed]
  22. Fan YH, Fang H, Ji CX, et al. Long noncoding RNA CCAT2 can predict metastasis and poor prognosis: A meta-analysis. Clin Chim Acta 2017;466:120-6. [Crossref] [PubMed]
  23. Fan Y, Yan T, Chai Y, et al. Long noncoding RNA HOTTIP as an independent prognostic marker in cancer. Clin Chim Acta 2018;482:224-30. [Crossref] [PubMed]
  24. Mu S, Ai L, Fan F, et al. Prognostic and clinicopathological significance of long noncoding RNA HOXA11-AS expression in human solid tumors: a meta-analysis. Cancer Cell Int 2018;18:1. [Crossref] [PubMed]
  25. Guo H, Huang SY, Li S, et al. Prognostic significance of the long noncodng RNAs in nasopharyngeal carcinoma: a systematic review and meta-analysis. Cancer Manag Res 2018;10:1763-79. [Crossref] [PubMed]
  26. Anastasiadou E, Faggioni A, Trivedi P, et al. The nefarious nexus of noncoding RNAs in cancer. Int J Mol Sci 2018.19. [PubMed]
  27. Chan JJ, Tay Y. Noncoding RNA: RNA regulatory networks in cancer. Int J Mol Sci 2018.19. [PubMed]
  28. Wilusz JE. Long noncoding RNAs: Re-writing dogmas of RNA processing and stability. Biochim Biophys Acta 2016;1859:128-38. [Crossref] [PubMed]
  29. Brown JA, Bulkley D, Wang J, et al. Structural insights into the stabilization of MALAT1 noncoding RNA by a bipartite triple helix. Nat Struct Mol Biol 2014;21:633-40. [Crossref] [PubMed]
  30. Yoon JH, Abdelmohsen K, Kim J, et al. Scaffold function of long non-coding RNA NOTAIR in protein ubiquitination. Nat Commun 2013;4:2939. [Crossref] [PubMed]
doi: 10.21037/biotarget.2019.01.01
Cite this article as: Clawson GA. What’s up with MALAT1? Biotarget 2019;3:3.