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Abstract

Non–small cell lung cancer is one of the most common types of cancer, and the prognosis of non–small cell lung cancer is still poor. Recent evidence has proved that long noncoding RNA is involved in tumorigenesis. For non–small cell lung cancer, the expression profile of long noncoding RNA has been studied. Here, we identified a novel long noncoding RNA TRPM2-AS from published dataset and found TRPM2-AS is widely upregulated in non–small cell lung cancer tissues compared with adjacent non-tumor tissues. Higher expression level of TRPM2-AS was correlated with higher TNM stages and larger tumor size. Patients with high TRPM2-AS expression level had poor survival than those with low TRPM2-AS level. We silenced TRPM2-AS by small interfering RNA and found that cell proliferation was significantly inhibited after knockdown of TRPM2-AS. Annexin V/propidium iodide staining and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay confirmed that cell apoptosis increased after TRPM2-AS knockdown. Further experiments showed that silence of TRPM2-AS upregulated SHC1 and silence of SHC1 partially reversed cell apoptosis after TRPM2-AS knockdown. In summary, the novel long noncoding RNA TRPM2-AS upregulated in non–small cell lung cancer, and downregulation of TRPM2-AS promotes apoptosis in vitro.

Keywords

Long noncoding RNA non–small cell lung cancer TRPM2-AS apoptosis

Introduction

Lung cancer is the leading cause of cancer-related death worldwide. Non–small cell lung cancer (NSCLC) is the most common types of lung cancer.^1,2 The prognosis of NSCLC is still poor since most NSCLC cases are diagnosed at advanced or metastatic stages.^1,3,4 The critical problems challenging oncologists are the lack of adequate tumor biomarkers for early diagnosis and metastasis. Thus, it is urgent to further discover the underlying molecular mechanism of NSCLC pathogenesis and progression.

Long noncoding RNA (lncRNA) is a kind of RNA molecules that are longer than 200 nt with no protein coding ability.^4–7 Due to the development of high-throughput technologies, thousands of lncRNAs have been identified and mounting evidence has proved that lncRNAs play important roles in almost every aspect of biological process.^8–10 So far, the expression profiles of lncRNAs have been characterized in many diseases, especially for cancers. The cancer genome atlas (TCGA) project provides huge data for cancer genome, transcriptome, and epigenome; these data have been systematically annotated for lncRNA.¹¹ Thus, these big data provide abundant resource to screening functional lncRNAs in cancers.

For NSCLC, lncRNA expression profiles have been analyzed by many researchers and several NSCLC-specific lncRNAs have been identified.^12–14 However, the functions of most lncRNAs are still unknown. TRPM2 antisense RNA (TRPM2-AS) is an antisense lncRNA of TRPM2, which is located in chr21q22.3 locus. The TRPM2-AS RNA transcript is 875 nt in length and consists of three exons. In this study, we found that TRPM2-AS was widely upregulated in NSCLC tissues compared with adjacent normal tissues and high expression of TRPM2-AS indicated poor survival of NSCLC patients. Silence of TRPM2-AS increased the percentage of apoptotic cells and that the expression of SHC1 increased after knockdown of TRPM2-AS.

Methods

Patients and tissue samples

This study was approved by the Ethics Committee of Peking Union Medical College Hospital and informed written consents were obtained from all patients included in this study. NSCLC tissues and paired adjacent normal tissues were obtained from 60 NSCLC patients between 2006 and 2012. All specimens were snap-frozen and stored at −80°C until total RNA extraction. All tumor and paired normal tissues were confirmed by experienced pathologists.

Cell lines and culture conditions

A549 and H1299 cell lines were cultured in RPMI 1640 medium supplemented with 10% fetal bovine serum (10% FBS, GIBCO), 100 U/mL penicillin, and 100 mg/mL streptomycin in humidified air at 37°C with 5% CO₂. Both A549 and H1299 were purchased from the Institute of Biochemistry and cell biology of Chinese Academy of Sciences (Shanghai, China).

Total RNA extraction and quantitative reverse transcription-polymerase chain reaction analysis

Total RNA was isolated with TRIzol reagent (Invitrogen, CA, USA) according to the manufacturer’s protocol. A total of 1000 ng of total RNA was reverse transcribed in a final volume of 20 µL using the PrimerScript RT Master Mix (Takara, Dalian, China). The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed using the SYBR Select Master Mix (Applied Biosystems, Waltham, MA, USA) on ABI 7500 system according to the manufacturer’s instructions. Glycer-aldehyde 3-phosphate dehydrogenase (GAPDH) was measured as an internal control for cell line and paired tumor and normal tissues. After the reverse transcription, 0.5 µL of the complementary DNA was used for subsequent qRT-PCR reaction. The PCR primers used were as follows: 5′-CCACATCGCTCAGACACCAT-3′ (sense) and 5′-ACCAGGCGCCCAATACG-3′ (antisense) for GAPDH; 5′-CGTGACCAGGTTCAGACACA-3′ (sense) and 5′-TGGGCAGTTTGGTTCTGGTT-3′ (antisense) for TRPM2-AS; 5′-CCCGCTCAGCTCTATCCTG-3′ (sense) and 5′-GGCAACATAGGCGACATACTC-3′ (antisense) for SHC1. The Ct-value for each sample was calculated with the ΔΔCt-method.

Small interfering RNA and transfection of NSCLC cells

Cells cultured on six-well plate were transfected with small interfering RNA (siRNA) or negative control (NC) using Lipofectamine 2000 (Invitrogen, Shanghai, China) according to the manufacturer’s instructions. Cells were harvested after 24 h for q RT-PCR and other experiments. The siRNA sequences for TRPM2-AS1 were as follows: siRNA 1# sense, 5′-GGGAAGAUGUCUCAGCAGACG-3′, antisense, 5′-UCUGCUGAGACAUCUUCCCCU-3′; siRNA 2# sense, 5′-CGAACCUUCCCUAAUAGAAAC-3′, antisense, 5′-UUCUAUUAGGGAAGGUUCGGG-3′; siRNA 3# sense, 5′-AGACCUAUGAGGAGACAUAAC-3′, antisense, 5′-UAUGUCUCCUCAUAGGUCUCG-3′. The siRNA sequence for SHC1 was sense 5′-CGAACUGUGUCUACAGCAACC-3′ and antisense 5′-UUGCUGUAGACACAGUUCGCU-3′.

Cell Counting Kit-8 assay

The Cell Counting Kit-8 (CCK8) assay was used to determine relative cell growth according to the manufacturer’s instructions. Cells were seeded into 96-well plates (3 × 10³/well) and incubated in RPMI 1640 at 37°C and 5% CO₂ atmosphere for 96 h. The absorbance was measured at 450 nm with an ELx-800 Universal Microplate Reader. Each experiment was repeated at least three times independently.

Flow cytometry analysis

Double staining of Annexin V and propidium iodide (PI) was done by the FITC Annexin V Apoptosis Detection Kit (BD Biosciences, Franklin Lakes, NJ, USA) according to the manufacturer’s recommendations. The cells were analyzed with a flow cytometry (FACScan; BD Biosciences) equipped with a Cell Quest software (BD Biosciences). Cells were discriminated into viable cells, dead cells, early apoptotic cells, and apoptotic cells.

Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay

Cells were seeded on coverslips and transfected with siRNA or NC. After 24 h transfection, cells were fixed in 4% paraformaldehyde for 15 min at room temperature. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay was performed according to the manufacturer’s instructions. Cells were then washed and stained with 4’,6-diamidino-2-phenylindole (DAPI). Coverslips were photographed using a Zeiss Axioscope inverted fluorescence microscope (Zeiss, Oberkochen, Germany).

Western blot assay

Cells were lysed using mammalian protein extraction reagent radio-immunoprecipitation assay (RIPA) (Beyotime china) supplemented with protease inhibitors cocktail (Roche, Switzerland) and phenylmethanesulfonyl fluoride (PMSF) (Roche, Switzerland). Protein concentration was measured with the Bio-Rad protein assay kit. In total, 50 µg protein extractions were separated by 12% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), then transferred to 0.22 µm nitrocellulose membranes (Sigma-Aldrich, USA) and incubated with specific antibodies. Enhanced chemiluminescence (ECL) chromogenic substrate was used to visualize the bands. Anti-β-actin and anti-SHC1 were from Abcam (Hong Kong, China).

Statistical and bioinformatics analysis

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed by the online website (https://david.ncifcrf.gov). Protein-coding genes that are correlated with TRPM2-AS in NSCLC (according to TCGA dataset) were downloaded from lncRNAtor database (http://lncrnator.ewha.ac.kr/index.htm). Enrichment plots were performed with Cytoscape software.¹⁵ Student’s t-test and Kaplan–Meier analyses were performed to analyze the data using SPSS 18.0 software. p values less than 0.05 were considered statistically significant.

Results

TRPM2-AS is upregulated in NSCLC

Expression of lncRNAs has been profiled in lung cancer. We analyzed published high-throughput data and the TCGA results and found that many dataset showed lncRNA TRPM2-AS was widely upregulated in various types of cancers, including lung adenocarcinoma and lung squamous cell carcinoma (Supplementary Figure S1).^11,16 Then, we analyzed TRPM2-AS expression in lung cancer tissues and paired adjacent tissues. Compared with adjacent tissues, TRPM2-AS was widely overexpressed in lung cancer tissues (Figure 1(a), increasing fold 5.78 ± 1.35; p < 0.01). Then, we analyzed the association between TRPM2-AS expression level and clinicopathologic characteristics of lung cancer patients. The results indicated that high expression of TRPM2-AS was associated with advanced TNM and larger tumor size (Figure 1(b) and (c) and Table 1). The increasing fold of TRPM2-AS was higher in patients with TNM III–IV stages than that in I–II stages (9.92 vs 3.71; p = 0.031). Prognostic value of TRPM2-AS was also analyzed by Kaplan–Meier curve and we found patients with higher TRPM2-AS expression had poor survival (hazard ratio (HR) = 1.239, p = 0.003, Figure 1(d)). Thus, these lines of evidence suggested that TRPM2-AS was widely overexpressed in lung cancer and high expression of TRPM2-AS indicated advanced TNM stages and poor survival.

Figure 1.

(a) TRPM2-AS is widely upregulated in NSCLC tissues; expression level of TRPM2-AS is higher in (b) NSCLC tissues larger than 4 cm and (c) with advanced TNM stages. (d) Kaplan–Meier curve shows that patients with high TRPM2-AS expression level have poor survival than patients with low expression. **p < 0.01.

Table 1.

Correlation between TRPM2-AS expression level and clinical characteristics.

Characteristics	Number of patients (60)	Percentage	Fold change	p value
Age (years)
<50	7	11.67	8.68	0.403
50–70	45	75.00	4.48
>70	8	13.33	10.55
Smoking
Never	38	63.33	7.45	0.294
Ever	22	16.67	2.89
Gender
Male	29	48.33	5.69	0.650
Female	31	51.67	5.86
Tumor size
<4 cm	40	66.67	3.71	0.031*
>4 cm	20	33.33	9.92
TNM Stage
I–II	44	73.33	2.66	0.002*
III–IV	16	26.67	14.36

Significant correlation.

TRPM2-AS regulates apoptosis in NSCLC

TRPM2-AS is a novel lncRNA and its biological function has not been fully explored. In prostate cancer, Lavorgna G has knockdown TRPM2-AS in prostate cancer cells and analyzed dysregulated genes by microarray.¹⁷ The genes dysregulated upon TRPM2-AS knockdown would provide clues for the biological function of TRPM2-AS. Therefore, we performed functional annotation analyses for these dysregulated genes after TRPM2-AS knockdown. As shown in Figure 2, GO and KEGG analyses showed that many items were enriched, but genes related to apoptosis were significantly enriched, suggesting TRPM2-AS is highly possibly associated with apoptosis.

Figure 2.

Functional annotation analyses of differentially expressed genes after knockdown of TRPM2-AS. (a) KEGG pathway and (b) GO analyses showed that apoptosis-associated genes were significantly enriched.

Then, we designed siRNAs specifically targeting TRPM2-AS and TRPM2-AS expression was significantly inhibited after transfection of siRNAs in two NSCLC cell lines (Figure 3(a)). As shown, siRNA3 showed best inhibitory effect and siRNA was used for further experiments. After knockdown of TRPM2-AS, we found cell proliferation ability was significantly inhibited in both A549 and H1299 cells by CCK8 assay (Figure 3(b) and (c)). After Annexin V/PI staining followed by cell flow cytometry analysis, the percentage of apoptotic cells significantly increased after knockdown of TRPM2-AS (Figure 3(d) and (e)). In addition, TUNEL assay also confirmed that after silence of TRPM2-AS, the number of apoptotic cells increased in both A549 and H1299 cells (Figure 4). These data suggested that silence of TRPM2-AS could promote apoptosis in NSCLC cells.

Figure 3.

(a) TRPM2-AS expression was efficiently knock down by siRNAs and cell proliferation was significantly inhibited by siRNA treatment in (b) A549 and (c) H1299 cells. PI staining and flow cytometry analysis showed that the percentage of apoptotic cells increased in both (d) A549 and (e) H1299 cells after siRNA treatment. *p < 0.05, **p < 0.01.

Figure 4.

TUNEL assay showed that apoptotic cells increased after siRNA treatment in (a) A549 cells and (b) H1299 cells.

Silence of TRPM2-AS increased SHC1 expression

Since it has been shown that after downregulation of TRPM2-AS, a lot genes were dysregulated. The target genes of TRPM2-AS would be positively or negatively correlated with TRMP2-AS in tissue samples. Thus, we can infer the downstream target genes of TRPM2-AS in NSCLC by this method. To this end, we download genes that were significantly correlated with TRPM2-AS in NSCLC according to TCGA. By Venn diagram (Figure 5(a)), we found that nine genes were overlapped (ELAVL1, GNG11, CBX2, CSF2, CXCL2, FYN, TMED7, SHC1, and ACADM) with Lavorgna’s dataset. Among these genes, literature has reported that overexpression of SHC1 promoted apoptosis. Additionally, researchers have suggested that SHC1 was associated with apoptosis in A549 cells.¹⁸ We also confirmed that silence of SHC1 decreased the percentage of apoptotic cells in A549 cell line (Supplementary Figure S2). In a cohort of 20 NSCLC patients, we found SHC1 was significantly negatively correlated with TRPM2-AS (Figure 5(b), p = 0.03). According to Lavorgna’s data, SHC1 was upregulated after silence of TRPM2-AS in prostate cancer. In A549 cell line, we confirmed that after silence of TRPM2-AS, SHC1 expression increased both in RNA level (Figure 5(c)) and protein level (Figure 5(d)). In a rescue experiment, knockdown of TRPM2-AS increased apoptosis in A549 cells and we found knockdown of SHC1 could partially rescue the pro-apoptotic effect caused by TRPM2-AS silence. Thus, these data suggested that downregulation of TRPM2-AS promoted apoptosis and might partially be dependent on SHC1.

Figure 5.

(a) Nine genes were overlapped by TCGA dataset and the dysregulated genes after TRPM2-AS silence. (b) In a cohort of NSCLC patients, RT-PCR results showed that SHC1 and TRPM2-AS expression levels were negatively correlated (p = 0.03). (c and d) Both PCR and Western blot results suggested that SHC1 expression level increased after silence of TRPM2-AS. The rescue experiment (e) showed that knockdown of TRPM2-AS increased apoptosis in A549 cells and silence of SHC1 partially reversed cell apoptosis after TRPM2-AS knockdown. *p < 0.05, **p < 0.01.

Discussion

Identification of effective diagnostic markers and therapeutic targets is critical for NSCLC treatment and prognosis. Researchers have proved that noncoding RNAs especially lncRNA could be effective biomarkers for cancer diagnosis and prognosis.¹⁹ In 2014, Li et al.²⁰ analyzed lncRNA expression in 258 esophagus squamous cell carcinoma (ESCC) patients and showed a signature of three lncRNAs could effectively predict survival of ESCC patients. For NSCLC, researchers have tried to identify novel prognostic or diagnostic biomarkers from the lncRNA world.²¹ In this study, we found that the novel lncRNA TRPM2-AS was widely upregulated in NSCLC tissues. Statistical analyses showed that high expression level of TRPM2-AS was associated with advanced TNM stages and patients with high TRPM2-AS expression level had poor survival than those with low expression. Thus, TRPM2-AS could potentially be a robust biomarker for NSCLC and we will further validate the prognostic value of TRPM2-AS with larger sample size.

It has been demonstrated that lncRNA is involved in various biological processes, like cell differentiation, immune response, and metabolism. For TRPM2-AS, we first performed GO and KEGG analyses to infer the potential biological processes and pathways that were affected after silence of TRPM2-AS. And the functional annotation results suggested that TRPM2-AS would significantly affect cell apoptosis. We then designed siRNAs specifically targeting TRPM2-AS and assessed the impact of TRPM2-AS on apoptosis. Annexin V/PI staining and TUNEL assay both confirmed that downregulation of TRPM2-AS increased apoptosis in A549 and H1299 cells. By bioinformatics analysis, we found that TRPM2-AS was significantly correlated with SHC1. In a cohort of 20 NSCLC samples, we confirmed the expression levels of SHC1 and TRPM2-AS was negatively correlated. Additionally, RT-PCR and Western blot results confirmed that SHC1 expression level increased after TRPM2-AS knockdown. Thus, evidence from tissue samples and cell lines all confirmed that TRPM2-AS and SCH1 were negatively correlated.

Previous papers have proved that upregulation of SHC1 promoted apoptosis,^22–24 suggesting SHC1 could promote apoptosis in vitro. In A549 cells, silence of SHC1 with siRNA decreased apoptosis (Figure S2). Then, we hypothesized that TRPM2-AS may regulate cell apoptosis partially through SHC1. In the rescue experiment (Figure 5(e)), knockdown of TRPM2-AS increased apoptosis in A549 cells and silence of SHC1 partially reversed cell apoptosis after TRPM2-AS knockdown. These lines of evidence demonstrated that TRPM2-AS might regulate cell apoptosis partially through SHC1. However, the exact regulatory mechanism between TRPM2-AS and SHC1 is still elusive and we will focus on this in our future work.

In conclusion, we found lncRNA TRPM2-AS was widely upregulated in NSCLC and high expression of TRPM2-AS was correlated with advanced TNM stages and poor survival. Knockdown of TRPM2-AS promoted apoptosis and increased SHC1 expression.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Parkin

Pisani

Ferlay

Estimates of the worldwide incidence of 25 major cancers in 1990. Int J Cancer 1999; 80: 827–841.

Siegel

Zou

. Cancer statistics, 2014. CA Cancer J Clin 2014; 64: 9–29.

Parkin

Bray

Ferlay

. Global cancer statistics, 2002. CA Cancer J Clin 2005; 55: 74–108.

Ferlay

Shin

Bray

. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer 2010; 127: 2893–2917.

Tsai

Spitale

Chang

HY.

Long intergenic noncoding RNAs: new links in cancer progression. Cancer Res 2011; 71: 3–7.

Ponting

Oliver

Reik

Evolution and functions of long noncoding RNAs. Cell 2009; 136: 629–641.

Wilusz

Sunwoo

Spector

DL.

Long noncoding RNAs: functional surprises from the RNA world. Genes Dev 2009; 23: 1494–1504.

Xing

Lin

. lncRNA directs cooperative epigenetic regulation downstream of chemokine signals. Cell 2014; 159: 1110–1125.

Uchida

Dimmeler

Long noncoding RNAs in cardiovascular diseases. Circ Res 2015; 116: 737–750.

10.

White

Cabanski

Silva-Fisher

. Transcriptome sequencing reveals altered long intergenic non-coding RNAs in lung cancer. Genome Biol 2014; 15: 429.

11.

Yan

Feng

. Comprehensive genomic characterization of long non-coding RNAs across human cancers. Cancer Cell 2015; 28: 529–540.

12.

Wilusz

Freier

Spector

DL.

3′ end processing of a long nuclear-retained noncoding RNA yields a tRNA-like cytoplasmic RNA. Cell 2008; 135: 919–932.

13.

Arab

Park

Lindroth

. Long noncoding RNA TARID directs demethylation and activation of the tumor suppressor TCF21 via GADD45A. Mol Cell 2014; 55: 604–614.

14.

Qiu

Wang

. A novel lncRNA, LUADT1, promotes lung adenocarcinoma proliferation via the epigenetic suppression of p27. Cell Death Dis 2015; 6: e1858.

15.

Shannon

Markiel

Ozier

. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003; 13: 2498–2504.

16.

Brunner

Beck

Edris

. Transcriptional profiling of long non-coding RNAs and novel transcribed regions across a diverse panel of archived human cancers. Genome Biol 2012; 13: R75.

17.

Lavorgna

Chiacchiera

Briganti

. Expression-profiling of apoptosis induced by ablation of the long ncRNA TRPM2-AS in prostate cancer cell. Genom Data 2015; 3: 4–5.

18.

Zheng

Yang

Zhao

. Downregulated adaptor protein p66(Shc) mitigates autophagy process by low nutrient and enhances apoptotic resistance in human lung adenocarcinoma A549 cells. FEBS J 2013; 280: 4522–4530.

19.

Chen

. A long non-coding RNA signature to improve prognosis prediction of colorectal cancer. Oncotarget 2014; 5: 2230–2242.

20.

Chen

Tian

. LncRNA profile study reveals a three-lncRNA signature associated with the survival of patients with oesophageal squamous cell carcinoma. Gut 2014; 63: 1700–1710.

21.

Deng

. An eight-long non-coding RNA signature as a candidate prognostic biomarker for lung cancer. Oncol Rep 2016; 36: 215–222.

22.

Cao

Qian

Wang

. TRPM2 mediates histone deacetylase inhibition-induced apoptosis in bladder cancer cells. Cancer Biother Radiopharm 2015; 30: 87–93.

23.

Tripathi

Batra

Cao

. Influenza A virus nucleoprotein induces apoptosis in human airway epithelial cells: implications of a novel interaction between nucleoprotein and host protein Clusterin. Cell Death Dis 2013; 4: e562.

24.

Sun

Yau

Wong

. Role of TRPM2 in H₂O₂-induced cell apoptosis in endothelial cells. PLoS ONE 2012; 7: e43186.

Supplementary Material

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Downregulation of a novel long noncoding RNA TRPM2-AS promotes apoptosis in non–small cell lung cancer

Abstract

Keywords

Introduction

Methods

Patients and tissue samples

Cell lines and culture conditions

Total RNA extraction and quantitative reverse transcription-polymerase chain reaction analysis

Small interfering RNA and transfection of NSCLC cells

Cell Counting Kit-8 assay

Flow cytometry analysis

Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling assay

Western blot assay

Statistical and bioinformatics analysis

Results

TRPM2-AS is upregulated in NSCLC

TRPM2-AS regulates apoptosis in NSCLC

Silence of TRPM2-AS increased SHC1 expression

Discussion

Footnotes

Declaration of conflicting interests

Funding

References

Supplementary Material