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. 2016 Aug 30;7(35):56209-56218.
doi: 10.18632/oncotarget.10941.

The lncRNA MALAT1 is a novel biomarker for gastric cancer metastasis

Affiliations

The lncRNA MALAT1 is a novel biomarker for gastric cancer metastasis

Hongwei Xia et al. Oncotarget. .

Abstract

The metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is frequently over-expressed and serves as a prognostic marker in human cancers. However, little is known about the role of MALAT1 in gastric cancer. Here, we reported that the tissue and plasma MALAT1 levels were significantly higher in gastric cancer patients with distant metastasis (P<0.01) than patients without distant metastasis and the healthy controls. In addition, high levels of plasma MALAT1 independently correlated to a poor prognosis for gastric cancer patients (hazard ratio, 0.242; 95% CI, 0.154-0.836; P=0.036; Cox regression analysis). Functional studies revealed that knockdown of MALAT1 could inhibit cell proliferation, cell cycle progression, migration and invasion, and promote apoptosis in gastric cancer cells. Furthermore, the miR-122-IGF-1R signaling correlated with the dysregulated MALAT1 expression in gastric cancer. These data suggest that MALAT1 could function as an oncogene in gastric cancer, and high MALAT1 level could serve as a potential biomarker for the distant metastasis of gastric cancer.

Keywords: MALAT1; gastric cancer; long non-coding RNA; metastasis; miR-122.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1
Figure 1. Relative tissue and plasma MALAT1 expression levels and its clinical significance in gastric cancer patients and healthy controls
(A), (B) The expression of MALAT1 in tissue samples was significantly higher in the GC/DM group when compared with that of GC/NDM tissues and adjacent normal tissues. Tissue MALAT1 was detected in 14 pairs of GC/NDM patients and 25 pairs of GC/NDM patients by QRT-PCR. C-DM represents the original cancer tissues from GC/DM patients and the N-DM represents the adjacent normal tissues of the GC/DM patients. C-NDM represents the original cancer tissues from GC/NDM patients and the N-NDM represents the adjacent normal tissues of the GC/NDM patients. Data are presented as fold change. (C), (D) The expression of plasma MALAT1 was significantly higher in the GC/DM group when compared with the expression in the GC/NDM and HC groups. Plasma MALAT1 was detected in 72 pairs of patients with gastric cancer and 36 healthy controls by Q-PCR. Data are presented as fold change, and MALAT1 expression was significantly higher in patients at advanced pathological stages. (E), (F) Diagnostic efficiency of MALAT1 in the three groups. The AUC of the ROC curve for detecting DM from NDM was 0.860 (P<0.0001). The AUC of the ROC curve for detecting DM from HC was 0.923 (P<0.0001). GC, gastric cancer; GC/DM, GC with distant metastasis; GC/NDM, GC with no distant metastasis; HC, healthy controls; AUC, area under the curve; ROC, receiver operating characteristic. Values were normalized to those for β-actin. Data represent the mean ± S.D. *P< 0.05, ***P < 0.001.
Figure 2
Figure 2. MALAT1 expression levels in gastric cancer cell lines and the effect of MALAT1 on cell proliferation
(A) qRT-PCR analysis of MALAT1 expression levels in gastric cancer cell lines (SGC7901, BGC823, MKN45, CTC105 and CTC141) compared with the normal bronchial epithelial cell line (GES-1). (B) qRT-PCR analysis of MALAT1 expression following treatment of MKN45 and CTC141 cells with two individual siRNAs targeting MALAT1. (C), (D) MKN45 and CTC141 cells were transfected with si-MALAT1 or si-NC, CCK8 assays were performed to determine the proliferation of MKN45 and CTC141 cells. (E), (F) Flow cytometry was used to examine the cell cycle progression of MKN45 and CTC141 cells transfected with si-MALAT1 or si-NC. Data represent the mean ± S.D. from three independent experiments. *P< 0.05, ***P < 0.001.
Figure 3
Figure 3. Effect of MALAT1 on cell apoptosis
(A), (C) MKN45 cells were transfected with si-MALAT1 or si-NC. Early apoptotic rates were detected by flow cytometry. (B),(D) Early apoptotic rates of CTC141 transfected with si-MALAT1 or si-NC. Data represent the mean ± S.D. from three independent experiments *P< 0.05.
Figure 4
Figure 4. Effect of MALAT1 on cell migration and invasion
(A, C) MKN45 cells were transfected with MALAT1 siRNA or si-NC. Transwell assays were performed to investigate the migratory and invasive ability. (B), (D) The migratory and invasive ability of CTC141 were detected by transwell assays. Data represent the mean ± S.D. from three independent experiments. ** P <0.01.
Figure 5
Figure 5. The miR-122-IGF-1R signaling might participate in the dysregulated MALAT1 expression in gastric cancer
(A) Plasma levels of MALAT1 and miR-122 is negatively correlated in the validation set. (r= −0.5576, P < 0.01). (B) RT-PCR and Q-PCR analysis the effect of miR-122 mimics and SiRNA mediated IGF-1R down-regulation on the expression of MALAT1 in BGC823 gastric cancer cells, β-actin was used as an internal control. (C) RT-PCR and Q-PCR analysis the effect of miR-122 inhibitor on the expression of MALAT1 in SGC7901 gastric cancer cells, β-actin was used as an internal control. (D), (E) RT-PCR, Q-PCR and WB analysis of IGF-1R expression following treatment of BGC823 and CTC141 cells with miR-122 mimics, IGF-1R siRNAs or miR-NC. (F), (G) RT-PCR, Q-PCR and WB analysis of IGF-1R expression following treatment of SGC7901 and GES cells with miR-122 inhibitor or miR-NC. Data represent the mean ± S.D. from three independent experiments. ***P< 0.001.

References

    1. Jemal A, BF, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90. - PubMed
    1. Lee JH, Kim KM, Cheong JH, Noh SH. Current management and future strategies of gastric cancer. Yonsei Med J. 2012;53(2):248–257. - PMC - PubMed
    1. Hartgrink HH, JE, van Grieken NC, van de Velde CJ. Gastric cancer. Lancet. 2009;374:477–490. - PMC - PubMed
    1. Hohenberger P GS. Gastric cancer. Lancet. 2003;362:305–315. - PubMed
    1. Diederichs S. The four dimensions of noncoding RNA conservation. Trends in Genet. 2014;30(4):121–123. - PubMed

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