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Pathological stage-associated non-coding RNA long intergenic non-protein coding RNA 1234 (LINC01234) participation in cell cycle regulation in adrenocortical carcinoma through bromodomain-containing protein 4 (BRD4) expression mediation via sponging microRNA (miR)-140-3p
Dan-Dan Zhu1, Xin-Bo Yu’, Wen Jiang, and Yu Zhu
Department of Urology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Huangpu, Shanghai, China
ABSTRACT
Many researches indicated that long non-coding RNAs (lncRNAs) were involved in the malig- nant progression of tumors, including Adrenocortical Carcinoma (ACC). However, as for most IncRNAs, their biological behaviors and molecular mechanism remain unclear in ACC. In the present research, weighted gene co-expression network analysis (WGCNA) was used to identify pathologically relevant gene, including IncRNAs. By comparing their expressions in GSE61359 tumors and normal controls, long intergenic non-protein coding RNA 1234 (LINC01234) was selected to investigate the clinical significance, biological function, and mechanism in ACC. Data mining revealed that LINC01234 expression was significantly up-regulated in ACC patients, and a shorter survival time presents in patients with higher LINC01234 expression compared to that in patients with lower LINC01234 expression. Further, LINC01234 silencing resulted in cells growth arrest in vitro and in vivo. Mechanism studies suggested that LINC01234 silencing induced cell cycle arrest, and bromodomain-containing protein 4 (BRD4) overexpression could restore this phenomenon. Further research showed that LINC01234 could mediate BRD4 expression through competitively sequestering microRNA (miR)-140-3p, as evidenced by the positive correlation of LINC01234 with BRD4 and inverse correlation with miR-140-3p expression. Luciferase activity assay also verified the targeting relationship between LINC01234, BRD4 and miR-140-3p. And up-regulated LINC01234 in ACC cells signifi- cantly reversed the degradation of BRD4 by miR-140-3p. Collectively, we deduce that LINC01234 functions as a ceRNA to regulate BRD4 expression by sponging miR-140-3p in ACC progress. Our findings have the potential to provide a new target for the diagnosis and treatment of ACC.
ARTICLE HISTORY
Received 8 February 2022 Revised 17 May 2022 Accepted 19 May 2022
KEYWORDS
LINC01234; ACC; cell cycle; BRD4; miR-140-3p
Data mining
Cell function test
Mechanism analysis
Pathological stage-associated non-coding RNA LINC01234 participation in cell cycle regulation in adrenocortical carcinoma through BRD4 expression mediation via sponging miR-140-3p
Highlights
· LINC01234 is a novel pathological-associated lncRNA.
· Upregulated LINC01234 means worse prog- nosis in ACC.
. LINC01234 silencing induces cell cycle arrest.
CONTACT Yu Zhu
zy10478@rjh.com.cn Department of Urology, Ruijin Hospital, No. 197 of Rui Jin 2nd Road, Huangpu 200025, Shanghai, China
These authors contributed equally to this work.
Supplemental data for this article can be accessed online at https://doi.org/10.1080/21655979.2022.2081464
· LINC01234/ miR-140-3p /BRD4 axis is involved in cell cycle in ACC.
Introduction
Adrenocortical carcinoma (ACC) is a rare malig- nancy which hardly shows any obvious clinical symptoms in the early stage [1,2]. Even more serious, conventional radical surgery has little effect on patients with advanced metastases [3]. For patients undergoing surgical treatment, the probability of recurrence is high, which leads to a poor prognosis [4]. At present, no clear molecular markers have been confirmed for early ACC progression. Moreover, the specific molecular mechanism of ACC is still not fully elucidated. Hence, it is critical to explore diagnostic markers related to the progress of ACC and to investigate novel effective treatments.
Weighted gene co-expression network analysis (WGCNA) is a bioinformatic method that can be performed to explore relationships between high throughput data and sample characteristics [5]. WGCNA has been applied to identify novel long non-coding RNA (lncRNA) biomarkers of tumors and to identify abundant lncRNAs associated with tumor prognosis [6,7]. To date, WGCNA has not been used for the identification of lncRNAs in ACC. The prognoses of patients with ACC with various pathological stages are vastly different [8]. Hence, WGCNA was used in this study to explore relation- ships between lncRNAs and pathological stages.
LncRNAs, a set of RNAs with less than 200 nucleo- tides and no coding capacity, have emerged as a novel research focus in tumorigenesis [9]. In recent years, accumulating evidence has linked dysregulation of lncRNAs with malignant tumor progression through multiple biological processes, including chromatin modification [10], X-chromosome inactivation [11], microRNA (miRNA) sponging [12], etc. LINC01234, located at 12q24.13, is a highly abundant, conserved mammalian non-coding RNA. Initially, LINC01234 was universally known for its participation in predict- ing the survival rate of breast cancer [13]. In hepato- cellular carcinoma (HCC), LINC01234 was involved in proliferation and chemoresistance through the MAGEA3/LINC01234/miR-31-5p axis [14]. In colon cancer, LINC01234 competitively binds miR-642a-5p to promote serine hydroxymethyltransferase 2
expression for accelerating cell proliferation [15]. However, few studies have been carried out to clarify the biological function of LINC01234 in the progres- sion of ACC.
In this study, LINC01234 was first identified as a novel pathological-associated lncRNA and its role in ACC was discovered. And data mining revealed that markedly up-regulated LINC01234 was observed in ACC, suggesting a poor prognosis. Hence, we hypothesized that LINC01234 plays a pro-tumor role in tumor progression. And the Assay results confirmed this hypothesis.
Materials and methods data mining
In this study, The Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus (GEO) data- sets (GSE61359 and GSE33371) were used to ana- lyze lncRNA expression patterns in ACC. The GEO data can be found at https://www.ncbi.nlm. nih.gov/geo. In addition, the Gene Expression Profiling Interactive Analysis (GEPIA) database was used (http://gepia2.cancer-pku.cn/) to uncover the prognostic significance of LINC01234 and BRD4 in TCGA-ACC.
RNA-Seq data preprocessing and co-expression network construction
RNA-Seq matrices with corresponding clinical information were downloaded from TCGA- ACC, and then data standardization was per- formed by transforming the reads per kilobase per million mapped reads (RPKM) of genes into transcripts per kilobase of exon model per million mapped reads (TPM). A total of 60,483 genes from 79 ACC samples were anno- tated as gene symbols and biotypes using version 22 of the GENCODE annotation file, and 34,185 genes belonging to messenger RNAs (mRNA) and lncRNAs were separated from the matrix table. Genes with quartile values of TPM <0.3 were discarded, and the remaining abundantly expressed genes (AEGs) were reserved. To nar- row the very large span of TPM, they were then converted into the log2 form (TPM + 1) for subsequent analysis.
WGCNA was performed to identify pathologi- cally relevant lncRNAs as previously described [5]. First, the AEG expression matrix of ACC samples was evaluated to select suitable samples and genes. Then, a scale-free co-expression network for the AEGs was constructed using the WGCNA R package [5]. The distance among ACC samples was evaluated by average linkage clustering, and the reliability of network construction was ensured by removing the outlier samples. A suitable soft- thresholding parameter ß was chosen to ensure network construction in accordance with the char- acteristics of the scale-free network. The adjacency matrix was transformed into a topological overlap matrix (TOM) to measure the network connectiv- ity of a gene, as well as to calculate the correspond- ing dissimilarity (1-TOM). According to the TOM-based dissimilarity measure, average linkage hierarchical clustering was performed to conduct a gene dendrogram (minimum size of mod- ule = 30). Some modules for the subsequent ana- lysis were merged by calculating the dissimilarity of module eigengenes (MEs).
Cell culture
SW-13 and H295R cells were purchased from ATCC (Manassas). DMEM (Solarbio, 11,995) medium containing 10% fetal bovine serum (FBS, Gibco, 10,099-141) was used for cell culturing in a 5% CO2 incubator at 37°C.
Cell transfection
Small interfering RNAs (siRNA) and plasmid vec- tors were transfected by using Lipofectamine 2000 (Invitrogen, 11668019), according to the manufac- turer’s protocol. The sequence of siRNA was as follows: si-LINC01234-1, sense: 5’-GGCAUUAA GCCAGAUUGAGUCUUAA-3’, antisense: 5’- UUAAGACUCAAUCUGGCUUAAUGCC-3’; si- LINC01234-2, sense: 5’-AGUUGAACCAAUCA CUGUGCAUUUG-3’, antisense: 5’-CAAAUGCA CAGUGAUUGGUUAACU-3’. Human LINC01 234 short hairpin RNA (shRNA) targeting LINC01234 was transfected as lentivirus. Cells were collected for qRT-PCR analysis after transfec- tion for 48 hours.
CCK-8 assay
CCK-8 assay was performed using 96-well plates to seed cells with 3 x 103 per well and six replicates were performed in each group. Relative cell growth was detected using CCK-8 (Cell Counting Kit-8, Dojindo, Kumamoto, Japan) every 24 hours, according to the manu- facturer’s instructions.
Colony formation assay
Colony formation assay was performed using 6-well plates to seed cells with 1 x 103 per well and three replicates were performed in each group. Cells were maintained for about 14 days. Cell culture was terminated by fixing with 4% parafor- maldehyde and staining with 0.1% crystal violet for 30 minutes, respectively. The numbers of the stained colony were counted to determine the col- ony formation.
Flow cytometric analysis
The protocol for the flow cytometric assay was performed as previously described [16]. Harvested cells transfecting for 48 hours were analyzed by flow cytometer (BD Biosciences) after propidium iodide (PI) staining. The Flowjo10 software was used to count and compare the percentages of the cells in the G0/G1, S, and G2/M phases.
Animal model construction
All protocols involving animals were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the NIH (Bethesda, MD) and approved by the ethics committee of the Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. One side of the armpit regions of the male BALB/c nude mice (6-8 weeks old) was subcutaneously injected with 1 x 10° cells. Tumor volumes were measured every seven days. The subcutaneous tumors were harvested after four weeks after injection. The harvested tumor tissues were sliced and subjected to immunohistochemistry (IHC) staining [17].
Western blot
Total protein was extracted using RIPA solution. SDS-PAGE (10%) gel and nitrocellulose filter membrane (0.22 mm) were used to separate and transfer protein. The primary antibodies used were as follows: Cyclin D1 (CST, #2922, 1: 1000), p53 (Abcam, ab32389, 1: 1000), p21 (Abcam, ab109520, 1: 2000), BRD4 (Proteintech, 67374- 2-Ig, 1: 5000). GAPDH antibody was used as a control.
RNA immunoprecipitation
RNA immunoprecipitation (RIP) was used to investigate whether LINC01234 and miR-140-3p could interact or bind with the potential binding protein Ago2 in ACC cells. An EZMagna RIP kit (Millipore-17-701) was used according to the manufacturer’s instructions and the immunopre- cipitated RNA was subjected to qRT-PCR to ana- lyze LINC01234 content.
Dual-Luciferase reporter assay
Dual-Luciferase Reporter Assay was implemented as previously described [16]. The complementary DNA fragment containing the wild-type or mutant LINC01234 fragment and the 3’-untranslated region (3’-UTR) of BRD4 was subcloned down- stream of the luciferase gene within the pGL3- basic luciferase reporter vector (Promega). These plasmids were co-transfected into ACC cells together with the miR-140-3p mimic. The Dual- Luciferase Reporter Assay kit (Promega, E1910, USA) was used to consecutively measure the firefly and Renilla luciferase activities in cell lysates after transfection for 48 hours.
Statistical analysis
Data were shown as mean ± SD. Data analysis was conducted using the GraphPad Prism 5 software. A P value of < 0.05 was considered statistically significant. All tests were two-sided.
Results
In this study, by comparing pathological- associated lncRNA expressions in GSE61359 tumors and normal controls, LINC01234 was selected to further investigate its role in ACC. Data mining revealed that the significantly up- regulated LINC01234 expression was observed in ACC compared with that in control patients. And a shorter survival time presents in patients with higher LINC01234 expression compared to that in patients with lower LINC01234 expression. LINC01234 silencing resulted in cell growth arrest in vitro and in vivo. Mechanism studies suggested that LINC01234 silencing induced cell cycle arrest, and that BRD4 overexpression could restore these phenomena. Further research showed that LINC01234 could mediate BRD4 expression through competitively sequestering miR-140-3p, as evidenced by the positive correla- tion of LINC01234 with BRD4 and the inverse correlation with miR-140-3p expression. Luciferase activity assay also verified the targeting relationship between LINC01234, BRD4, and miR-140-3p. Up-regulated LINC01234 in ACC cells significantly reversed the degradation of BRD4 by miR-140-3p.
Identification of pathological stage-associated modules and functional enrichment analysis
After preliminary data processing, a total of 14,334 AEGs were obtained after genes with low expres- sion were removed. The average linkage method combined with the Pearson correlation method was used to perform sample clustering. Then, 17 outlier samples were removed, and the remaining 62 samples were saved for subsequent analysis (Figure la). When soft-thresholding power ß was set to 10, the constructed network was in accor- dance with the characteristics of the scale-free net- work (R2 > 0.9) (Figure 1b, c). We identified 25 co-expressed modules (Figure 1d) after average linkage hierarchical clustering of the AEGs.
Next, by performing correlation analysis between modules and pathological stages, we found that the greenyellow, blue, and lightsteelblue
modules exhibited a higher module significance (MS) with the pathological stage (MS of the green- yellow module = 0.54 and MS of the lightsteelblue module = 0.52) (Figure 1e). This result suggests that genes in the two modules are strongly asso- ciated with the pathological stage of patients with ACC.
Up-regulated LINC01234 indicated a poor prognosis in patients with ACC
Greenyellow and lightsteelblue modules, which had a higher MS among the 25 co-expression modules, were analyzed to identify potential dys- regulated lncRNAs that may have participated in ACC progression. In these two modules, 75 lncRNAs were selected; among them, 44 were detected in the GSE61359 dataset. Significantly up- regulated or down-regulated lncRNAs were pre- sent in tumor (containing ACC and ACA) tissues in contrast with a normal adrenal cortex (Figure 2a). Notably, LINC01234 had a higher log2 (fold change) in ACC vs normal tissue (Figure 2b) than in ACA vs normal tissue (Figure 2c). The detail expression changes of LINC01234 in GSE61359 are shown in Figure 2d. Concurrently, another GEO dataset (Figure 2e, GSE33371) was used to analyze the expression pattern of LINC01234 in ACC. Moreover, the GSE33371 dataset shows that a higher LINC01234 expression implied larger tumor volume when the average value of LINC01234 expression was taken as the cutoff. The relation- ship between the patients’ ACC prognosis and LINC01234 expression level was then evaluated. For this analysis, the median expression level of LINC01234 expression was taken as the cutoff. Using the GEPIA database, the results showed that shorter overall survival (OS) (Figure 2f) and disease-free survival (DFS) (Figure 2g) times existed in patients with higher LINC01234 levels. Collectively, the data above suggested that LINC01234 exerts cancer promoting factors in ACC.
Down-regulated LINC01234-inhibited ACC cancer cell growth
In order to study the biological functions of LINC01234 in ACC, siRNA was transfected into SW-13 and H295R cells to knockdown LINC01234 (Figure 3a). Using CCK-8 assays, we found that LINC01234 silencing significantly slowed SW-13 (Figure 3b) and H295R (Figure 3c) cell prolifera- tion. Likewise, through colony formation assays, we found that the clonogenic survival of SW-13 (Figure 3d,e) and H295R (Figure 3f,g) cells was markedly inhibited by LINC01234 down- regulation. Following these procedures, shRNA of LINC01234 or control vector were stably trans- fected into SW-13 cells to detect the effects of LINC01234 on tumor growth in vivo. Subcutaneous tumor formation (Figure 3h) revealed that the group injected with sh- LINC01234 cells possessed a significantly smaller average size (Figure 3i) and weight (Figure 3j) of tumors than the control. Finally, IHC staining revealed a weaker Ki-67 proliferation marker existed in sh-LINC01234 tumors than in control groups (Figure 3k). In summary, these results ver- ified the carcinogenic role of LINC01234 in ACC.
LINC01234 regulates cell cycles in ACC
To clarify the molecular mechanism of LINC01234 participation in ACC, we performed gene set enrich- ment analysis (GSEA). The results revealed that the cell cycle was positively related to a higher LINC01234 expression (Figure 4a). Hence, we conducted PI assay to analyze the change of cell cycles with or without LINC01234 knockdown. The results revealed that the elevated ratio of G0/G1 was displayed after LINC01234 knockdown in SW-13 (Figure 4b) and H295R (Figure 4c) cells. Meanwhile, cell cycle- related genes, including down-regulated Cyclin D1, up-regulated p53, and p21, were observed in ACC cells after LINC01234 knockdown (Figure 4d), indi- cating that LINC01234 participates in regulating cell cycles.
OD
0
Scale Free Topology Model Fit
b
a
Mean Connectivity
(signed R^2)
0
500
1500
2500
0.2
0.4
0.6
0.8
1.0
weiss_score
Height
0
MEbrown4
Module-trait relationships
0
OS.time
S
1
2
stage
w
N
3
OS
60 80
100
120
0.092
U1
JI
5
MEroyalblue
(0.5)
Soft Threshold (power)
Mean connectivity
Soft Threshold (power)
Scale independence
TCGA.OR.A5LL.01
9
10
10
10
TCGA.OR.A5LT.01
MEdarkorange
(0.4)
12 14 16 18 20 22 24 26 28 30
TCGA.OR.A5L4.01
15
15
TCGA.PK.A5H8.01
0.014
20
TCGA.OR.A5K8.01
(0.9)
20
TCGA.OR.A5K3.01
MEgreen
TCGA.OR.A5JX.01
MEmidnightblue
78:41
25
25
TCGA.OR.A5JK.01
TCGA.OR.A5JC.01
(0:1)
30
49
3
TCGA.OR.A5LM.01
TCGA.OR.A5JV.01
MEblack
Height
0
TCGA.OR.A5K4.01
(0.07)
module
TCGA.OR.A5JR.01
0.8
1.0
TCGA.OR.A5JT.01
MElightyellow
MEcyan
colors
0.2
0.4
0.6
(0.3)
TCGA.OR.A5JZ.01
TCGA.OR.A5K1.01
TCGA.OR.A5LR.01
0.33
0.5
TCGA.PK.A5HA.01
MEdarkgrey
(0.009)
TCGA.OR.A5JQ.01
(0.64)
TCGA.OR.A5JD.01
TCGA.PA.A5YG.01
TCGA.OR.A5LP.01
MEdarkturquoise
MEbrown
Sample dendrogram and trait heatmap
(0.1)
TCGA.OR.A5LK.01
TCGA.OR.A5JI.01
(0.68)
TCGA.OR.A5LN.01
TCGA.OR.A5L6.01
MEskyblue
TCGA.OR.A5LA.01
0.35
(0.005)
TCGA.OR.A5L5.01
MEgreenyellow
TCGA.OR.A5L8.01
0.54
TCGA.OR.A5J9.01 TCGA.OR.A5LJ.0
(7e-06)
0
TCGA.OR.A5J2.0
MElightsteelblue1
MEblue
0.46
TCGA.OR.A5JL.01
(2e-04)
Cluster Dendrogram
TCGA.OR.A5LH.01
0.52
TCGA.OR.A5KU.01
(1e-05)
TCGA.OR.A5JJ.01
MEplum2
TCGA.OR.A5LO.01
0.25
TCGA.OR.A5JG.01
(0.05)
TCGA.OR.A5KY.01
MEtan
TCGA.OR.A5JA.01
0.42
(7e-04)
TCGA.OR.A5KW.01
MEfloralwhite
MEbisque4
TCGA.OR.A5J3.01
(0.1)
TCGA.OR.A5KO.01
TCGA.OR.A5LS.01
TCGA.OU.A5PI.01
0.26
-0.5
(0.04)
TCGA.P6.A5OF.01
TCGA.OR.A5JF.01
MEivory
0.35
TCGA.OR.A5JW.01
MElightcyan1
(0.006)
TCGA.OR.A5LB.01
TCGA.OR.A5LG.01
MEmediumpurple3
-0.32
(0.01)
TCGA.OR.A5J1.0
TCGA.OR.A5JS.01
0.15
TCGA.OR.A5K6.01
MEdarkmagenta
(0.2)
TCGA.OR.A5LC.01
TCGA.OR.A5K9.01
TCGA.OR.A5JM.01
MEskyblue3
(0.06)
TCGA.OR.A5LE.01
TCGA.OR.A5K5.01
(0.03)
-1
TCGA.OR.A5JP.01
TCGA.OR.A5J7.01
MEgrey
0.33
TCGA.OR.A5K2.01
(0.009)
TCGA.OR.A5JE.01
Stage
(y-axis) (d) Cluster dendrogram of the lncRNAs and mRNAs (e) Heatmap displaying the relationship between clustered modules and
the pathological stage of patients with adrenocortical carcinoma. Weiss score: white represents the lowest score, red represents the highest score, and the darker the color, the higher the score, overall survival (OS): White represents survival and red represents
death; OS time: the closer to red, the shorter the time; stage: the closer to red, the higher the stage.
LINC01234 participates in the cell cycle regulation via mediating BRD4 expression
GSEA results revealed that folate biosynthesis was
closely related to LINC01234 expression (Figure 4a). Folate cycle-related gene analysis
showed that BRD4 expression was related to pathological stage (Figure 5a). The detail
expression changes in GSE61359 showed that sig- nificantly up-regulated BRD4 was present in ACC and ACA tissues in contrast with a normal adrenal cortex (Figure 5b). Using the GEPIA database, we
evaluated the relationship between the patients’ prognosis and the BRD4 expression level. For this analysis, the median expression level of
a
All cancer / Normal
b
ACC / Normal (GSE61359)
C
ACA / Normal (GSE61359)
(GSE61359)
5
6
3
-Log10 (p value)
4
LINC01234
-Log10 (p value)
-Log10 (p value)
3
4
LINC01234
2
2
LINC01234
2
1
1
0
0
0
-0.2
0.0
0.2
0.4
-0.4
-0.2
0.0
0.2
0.4
-0.4
-0.2
0.0
0.2
0.4
Log2 (fold change)
Log2 (fold change)
Log2 (fold change)
d
GSE61359
e
GSE33371
f
TCGA-ACC-OS
g
Relative LINC01234 expression
TCGA-ACC-DFS
12-
Relative LINC01234 expression
3.5
1.0
1.0
3.0-
10-
Percent survival
0.8
n = 38
Percent survival
0.8
*
2.5-
0.6
0.6
n = 38
8
0.4
n = 38
0.4
n = 38
2.0-
0.2
Low LINC01234 Group
High LINC01234 Group
0.2
Low LINC01234 Group
High LINC01234 Group
6
1.5
Logrank p=0.037
Logrank p=0.035
Normal
ACA
ACC
Normal
ACA
ACC
0.0
HR(high)=2.4
0.0
HR(high)=2.1
0
50
100
150
0
50
100
150
Months
Months
BRD4 expression was taken as the cutoff. The results showed that shorter OS (Figure 5c) and DFS (Figure 5d) times existed in patients with higher BRD4 levels. Moreover, a positive relation- ship between LINC01234 expression and BRD4 expression was presented using Pearson correla- tion analysis (Figure 5e). BRD4 expression was decreased after LINC01234 knockdown (Figure 5f). Cell cycle assays revealed restored cell cycle arrest after BRD4 overexpression in LINC01234 knockdown cells (Figure 5g,h). Herein, we concluded that LINC01234 regulated cell cycles in ACC by mediating BRD4 expression.
MiR-140-3p may mediate a ceRNA network with LINC01234 and BRD4
Accumulating evidence has shown that lncRNAs are acting as competing endogenous RNAs
(ceRNAs) for miRNAs to allow expression of tar- geted genes [18]. Hence, to investigate the mole- cular link between LINC01234 and BRD4, which forms a ceRNA network, online bioinformatic databases were used. As shown in Figure 6a, 332 miRNAs were predicted to bind to the LINC01234 sequence (the threshold is 0.7) using the LncBase Predicted v.2 DIANA tool (www.microrna.gr/ LncBase) with parameters set according to the website without any adjustment. Additionally, DIANA’s TarBase v8.0 tool (http://www.micro rna.gr/tarbase) with parameters set according to the website without any adjustment, showed that 120 miRNAs experimentally supported interaction with BRD4. Meanwhile, 227 miRNAs were pre- dicted to target BRD4 according to the starBase v2.0 software (ENCORI) (http://starbase.sysu.edu. cn/) with parameters set according to the website without any adjustment. Among them, miR-140- 3p (has-miR-140-3p) was the only overlapped
Relative LINC01234 expression 0)
1.5
b
SW-13
C
H295R
*
2.5
2.0
*
*
*
**
NC
Absorbance at 450nm
2.0
NC
NC
1.0
si-LINC01234-1
si-LINC01234-1
Absorbance at 450nm
*
1.5-
si-LINC01234-1
si-LINC01234-2
1.5
si-LINC01234-2
si-LINC01234-2
**
1.0-
R
*
0.5
1.0.
T
0.5
0.5
0.0
SW-13
H295R
0.0
0.0
0
1
2
3
4
0
1
2
3
4
Times (day)
Times (day)
d
NC
si-LINC01234-1
si-LINC01234-2
e
SW-13 *
1000
*
Number of clones
800
600
SW-13
400
200
T
0
NC
si-LINC01234-1
si-LINC01234-2
f
NC
si-LINC01234-1
si-LINC01234-2
g
H295R
1500
Number of clones
**
1000
H295R
500
0
NC
si-LINC01234-1
si-LINC01234-2
h
1000
SW-13
Tumor volume (mmf? )
NC
k
Ki67
800
sh-LINC01234
*
NC
600
400
NC
*
sh-LINC01234
200
1
0
I
1w
2w
3w
Times (week)
4w
5w
sh-LINC01234
Tumor Weight (g)
0
0
0
ம்
4
1
0 L
1.5-
1
2
3
4
5
6
7
NC.
sh-LINC01234-
**
4
miRNA in the above three intersections (Figure 6a). Next, we found that both the expres- sion of BRD4 (Figure 6b) and LINC01234 (Figure 6c) were negatively associated with the expression of miR-140-3p in TCGA-ACC dataset
analyzed by starBase v2.0. Furthermore, down- regulated miR-140-3p expression often indicated a poor prognosis of ACC (Figure 6d, p = 0.033). Therefore, miR-140-3p was chosen as a candidate for further investigation.
a
Folate biosynthesis
·
Steroid biosynthesis
d
Cell cycle
NES
CyclinD1
CyclinD1
1.65
Oocyte meiosis
1.60
1.55
p53
SW-13
p53
H295R
Nucleotide excision repair
1.50
1.45
p21
p21
Terpenoid backbone biosynthesis
Gene Count
GAPDH
GAPDH
Protein export
25
si-LINC01234-1
si-LINC01234-2
si-LINC01234-1
si-LINC01234-2
50
NC
NC
Rna degradation
75
100
Alpha linolenic acid metabolism
Biosynthesis of unsaturated fatty acids
0.01
0.02
0.03
0.04
b
p value
300
SW-13
120
250
60
*
*
ns
200
**
*
90
200
Count
Count
Count
Cell cycle (%)
40
*
si-LINC01234-2
si-LINC01234-1
NC
150
T
60
100
100
20
30
50
0
0
0
0
0
200
400
600
800
1.0K
0
200
400
600
800
1.0K
0
200
400
600
800
1.0K
GO/G1
5
G2/M
C
NC
si-LINC01234-1
si-LINC01234-2
*
H295R
120
200-
200
60
**
Count
90
Count
150
150
Count
Cell cycle (%)
40
ns
ns
si-LINC01234-2
si-LINC01234-1
NC
60
100-
100
20
30
50.
50
0
0.
0
0
0
200
400
600
800
1.0K
0
200
400
600
800
1.0K
0
200
400
600
800
1.0K
GO/G1
S
G2/M
NC
si-LINC01234-1
si-LINC01234-2
LINC01234 mediates BRD4 expression by competitively binding miR-140-3p in ACC
To confirm the potential interaction between LINC01234 and miR-140-3p, a sequence of mutations was made in the miR-140-3p binding site of LINC01234 (mut-LINC01234, (Figure 7a), the wild type referred to as wt-LINC01234). Dual-Luciferase Reporter Assay showed that miR-140-3p-mediated inhibition of luciferase activity was abolished in the mut-LINC01234 group compared with that in the wt- LINC01234 group (Figure 7b) and the levels of miR-140-3p were increased significantly after LINC01234 knockdown (Figure 7c). Additionally, RIP experiments showed that
LINC01234 and miR-140-3p were enriched in immunoprecipitated Ago2 compared with that in the control IgG (Figure 7d).
Subsequently, to verify the interaction between miR-140-3p and BRD4, the putative binding site between miR-140-3p and the 3’- UTR of BRD4 was determined using starBase v2.0 (Figure 7e). Dual-luciferase reporter assay showed that miR-140-3p significantly decreased the luciferase activity of report genes containing wild-type BRD4 (wt-BRD4), while there was no effect on the mutated 3’-UTR BRD4 (mut- BRD4) in ACC cells (figure 7f). Moreover, we overexpressed miR-140-3p and found that the levels of BRD4 were significantly decreased,
a
b
GSE61359
C
TCGA-ACC-OS
Q
TCGA-ACC-DFS
6
F value = 4.04
Pr(>F) = 0.0104
8-
1.0
1.0
**
Low BRD4 Group
Relatiom BRD4 expression
High BRD4 Group
Logrank p=3.9e-05
5
*
0.8
HR(high)=4.2
7-
Percent survival
0.8
n = 38
Percent survival
n = 38
0.6
0.6
+
6
0.4
n = 38
0.4
n = 38
0
5-
0.2
Low BRD4 Group
0.2
High BRD4 Group
Logrank p=0.0066
N
0.0
0.0
4
HR = 2.9
Stage I
Stage II
Stage III
Stage IV
Normal
ACA
ACC
0
50
100
150
0
50
100
150
Months
Months
e
0
p-value = 9.9e-05
r = 0.43
g
300
200
80
SW-13
n = 79
log2(BRD4 TPM)
5
150
Cell cycle (%)
60
Count
si-LINC01234-1+BRD4
si-LINC01234-1
200
4
ns
ns
Count
100
40
0
100
50
20
2
0
1
2
3
4
5
0
6
0
0.
200
400
600
800
1.0K
1.0K
GO/G1
$
log2(LINC01234 TPM)
0
si-LINC01234-1
0
200
si-LINC01234-1+BRD4
400
600
800
G2/M
h
250
60
H295R
200
ns
200
f
BRD4
SW-13
si-LINC01234-1+BRD4
si-LINC01234-1
GAPDH
150
40
ns
H295R
Count
=150
Count
Cell cycle (%)
BRD4
100
100
GAPDH
20
NC
si-LINC01234-1
si-LINC01234-2
50
50
0
0
0
200
400
600
1.0K
200
600
800
GO/G1
S
G2/M
0
800
0
400
si-LINC01234-1
si-LINC01234-1+BRD4
1.0K
whereas miR-140-3p knockdown displayed an opposite effect (Figure 7g); a similar phenom- enon occurs at protein levels (Figure 7h,i). In light of the fact that LINC01234 can sponge miR-140-3p, we examined whether miR-140-3p plays a role in the relationship between LINC01234 and BRD4. The results showed that sh-LINC01234-mediated down-regulation of BRD4 was effectively reversed by miR-140-3p inhibitors (Figure 7j). Collectively, the data above suggested that LINC01234 modulates BRD4 expression by competitively binding miR-140-3p.
Discussion
In ACC, initial staging is the most important fac- tor in determining prognosis. In the early stage, the five-year survival rate of patients with ACC could be up to 80% [1-3]. However, most patients in this study were diagnosed at an advanced stage and the five-year survival rate was less than 15%, with a high recurrence rate even after radical sur- gery [8]. Hence, it is necessary to explore novel biomarkers for patients with ACC to predict the pathological stage and prognosis in an accurate and timely manner. WGCNA is a novel gene screening method that can be used to explore
a
b
miR-140-3p vs. BRD4 (n = 79)
DIANA
DIANA
6
r = - 0.308
77
10
295
BRD4 (log2(FPKM+0.01))
5
p = 5.83e-03
miRNAs targeting to BRD4
miRNAs binding to LINC01234
1
hsa-miR-140-3p
4
32
26
3
168
2
miRNAs targeting to BRD4
1
ENCORI
9
10
11
12
13
14
miR-140-3p (log2(RPM+0.01))
C
miR-140-3p vs. LINC01234 (n = 79)
d
6
overall survival for miR-140-3p in ACC
LINC01234 (log2(FPKM+0.01))
r = - 0.354
1.00
4.
p = 1.36e-03
2-
Percent Survival
0.75
n = 39
0-
0.50
-2-
High
n = 40
+
-4.
Low
0.25
Log-Rank p = 0.033
-6.
HR = 0.43
-8
0.00
9
10
11
12
13
14
0
miR-140-3p (log2(RPM+0.01))
50
Times (months)
100
150
relationships between pathological traits and expression profiles [5]. Previously, WGCNA has revealed abundant potential biomarkers for the prognostic prediction of tumors [19,20]. For example, CDCA5, ANLN, ASPM, KIAA0101, CENPF, FOXM1, PRC1, RACGAP1, TPX2, MELK, NDC80, and SPAG5 were predicted by WGCNA to be related to the tumor grade and prognosis in ACC [21]. Hence, WGCNA was used to predict pathological stage-associated genes, including lncRNAs.
LncRNA co-expression analysis has been per- formed in multiple cancer cases to identify prog- nostic lncRNA biomarkers, but no corresponding
similarity analysis has been performed in ACC [7,22]. In this study, we constructed 25 co- expression modules related to the clinical traits of patients with ACC by using the WGCNA R package [5]. And pathological-associated LINCRNAs was selected. Subsequent analysis revealed that LINC01234 had the highest fold change with statistical significance, and larger tumor sizes and shorter outcome times were cor- related with a higher expression of LINC01234 in patients with ACC. Assays indicated that LINC01234 silencing inhibited cell growth in vitro and in vivo. These results suggest that LINC01234 is carcinogenic and can be considered
a
wt-LINC01234 5’- uuuccuuauaaaUUACCcaguCUGUGGUA -3’
miR-140-3p
3’- ggcaccaaGAUGG
GACACCAU -5’
mut-LINC01234 5’- uuuccuuauaaaGAUGGcaguGACACCAU -3’
b
1.5
ns
relative luciferase ativity
*
ns
miR-NC
T
miR-140-3p mimic
1.0
T
0.5
0.0
wt-LINC01234 mut-LINC01234
wt-LINC01234
LINC01234
SW-13
H295R
C
d
15
Sh-NC
Relative miR140-3p expression
Sh-LINC01234-1
*
300
LINC01234
Sh-LINC01234-2
miR-140-3p
e
Relative RNA level Ago2 vs. IgG RIP
FOS
wt-BRD4 5’- aacacaugcauuCaUGUGGUg -3’
10.
200
**
*
miR-140-3p 3’- ggcaccaagaugGgACACCAu -5’ mut-BRD4 5’- aacacaugcauuGaACACCAg -3’
5.
100
0
SW-13
H295R
0
SW-13
H295R
f
1.5
ns
g
**
relative luciferase ativity
*
ns
miR-NC
*
miR-140-3p mimic
9
Relatiom BRD4 expression
8
miR-NC
1.0-
7
**
miR-140-3p mimic
6
anti-miR-NC
5
anti-miR-140-3p
0.5
2.0
1.5
*
*
1.0
0.0
0.5
T
wt-BRD4
mut-RD4
wt-RD4
mut-RD4
SW-13
H295R
0.0
SW-13
H295R
j
BRD4
SW-13
h
SW-13
H295R
SW-13
H295R
GAPDH
BRD4
BRD4
BRD4
H295R
GAPDH
GAPDH
GAPDH
miR-NC
+
+
-
anti-miR-NC
+
+
sh-LINC01234-1
+
+
miR-140-3p mimics
+
+
anti-miR-140-3p
+
-
+
anti-miR-140-3p
+
as a potential prognostic indicator for ACC, which is similar to the biological function previously reported in other tumors [15,16].
The GSEA analysis showed that a high LINC01234 expression was positively correlated with cell cycles in ACC. Meanwhile, flow cyto- metric analysis confirmed the role of LINC01234 on cell cycle regulation in ACC cells, and the protein expression level of cell cycle-related mar- kers, including Cyclin D1, p53, and p21, was
also confirmed [23]. As it is known, the key checkpoint protein Cyclin D1 is responsible for cell cycle transformation from the S phase to the G1 phase via participation in transcriptional reg- ulation and DNA repair [24]. Additionally, p53 and p21 can regulate cell cycles in many ways, including DNA repair and transcriptional regu- lation [25,26]. Inspired by this, we speculated that LINC01234 may be involved in DNA repair or transcriptional regulation to regulate cell
cycles; further evidence should be collected to verify this.
The GSEA analysis also revealed that a high LINC01234 expression was positively related to folate biosynthesis. Folate, through its key role in C1 metabolism, is essential for DNA repair and synthesis, as well as DNA methylation [27,28]. This gives us more reason to suspect that LINC01234 may be involved in DNA repair. The relationship between LINC01234 and folate cycle-related genes was then ana- lyzed. We found that BRD4, which interacts with the folate pathway key enzyme MTHFD1 to link folate metabolism to transcriptional reg- ulation [29], was positively related to LINC01234. BRD4, acting as a histone acetyl- reader, is an important regulator of chromatin structure, which plays a role in cancer progres- sion, cell proliferation, DNA damage, and gene regulation [30]. Previous studies have deter- mined that MTHFD1L silencing is related to cell cycle delay [31]. The result above revealed that BRD4 overexpression could restore cell cycle arrest resulting from LINC01234 knock- down. Therefore, we speculated that LINC01234 may affect the cell cycles in ACC by affecting the binding of BRD4 and MTHFD1L.
Generally, lncRNAs exert function by absorb- ing miRNA sponges and they play a role in ceRNAs. Several LINC01234-miRNA-mRNA trios have been identified as the main mechan- isms promoting tumorigenesis. For example, in gastric cancer, LINC01234 functions as an miR- 204-5p sponge to up-regulate the expression of CBFB [16]. In HCC, LINC01234 was reported to be implicated in resistance to chemotherapy via the miR-31-5p/MAGEA3 axis [14]. As it is known, the miRNA target is the core compo- nent of the ceRNA network. Inspired by this, we speculated that LINC01234 may also play a role in ceRNAs in connection with post- transcriptional regulation of BRD4 and miRNAs in ACC. To determine this hypothesis, bioinformatic analysis and luciferase reporter assays were conducted to confirm that miR- 140-3p possesses the putative binding site of LINC01234 and BRD4. Furthermore, RNA-IP assay showed that LINC01234 was significantly
pulled down in miR-140-3p overexpressing cells and the miR-140-3p inhibitor could effectively reverse the down-regulation of BRD4 mediated by sh-LINC01234. Thus, these results indicated that BRD4 is a downstream target of LINC01234 by sponging miR-140-3p in ACC cells. Previous studies confirmed that miR- 140-3p worked as a tumor suppressor in var- ious kinds of cancer [32,33]. Therefore, more studies should be conducted to explore the role of miR-140-3p exertion in ACC. In addition, LINC01234 was reported to work through miR-204-5p [16], miR-31-5p [14], etc. Therefore, LINC01234 may partly function through sponging miR-140-3p in ACC. As a further matter, other miRNAs may also be target regulated by LINC01234 in ACC. Hence, further study needs to be conducted to discover potential miRNAs.
In summary, we determined for the first time that pathological stage-associated lncRNA LINC01234 was overexpressed in ACC, and it is a prognostic risk factor in ACC. LINC01234 plays a carcinogenic role via regulating cell cycles in ACC through the miR-140-3p/BRD4 axis. A better understanding of LINC01234 in ACC development was provided in the current study. LINC01234 has the potential to be a novel target in ACC management.
Conclusion
In conclusion, LINC01234 was proved to func- tions as a ceRNA to regulate BRD4 expression by sponging miR-140-3p in ACC progress. And higher LINC01234 expression observed in ACC patients indicated worse prognosis, which may be a useful candidate for ACC diagnosis and therapy.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Funding
The Natural Science Foundation of Shanghai (No.21ZR1440700)
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