Circular RNA Profiling Reveals That circRNA_104433 Regulates Cell Growth by Targeting miR-497-5p in Gastric Cancer

Figures & data

Table 1 Base Sequence of Primers Used in This Work

Name	Base Sequence
miR-497-5p primer	5′- CAGCAGCACACTGTGGTTTGTAA-3′’
U6 forward primer	5′- GGAACGATACAGAGAAGATTAGC-3′
U6 reverse primer	5′- TGGAACGCTTCACGAATTTGCG-3′
circRNA_104433 forward primer	5′-ATCCCAGAGGCTCTCCTCAC-3′
circRNA_104433 reverse primer	5′- AGCACATCAAGAAGCCCATC-3′
CDC25A forward primer	GGCAAGCGTGTCATTGTTGTG
CDC25A reverse primer	ACAGCTCAGGGTAGTGGAGTTTGG
GAPDH forward primer	5′- GTGCACCTTGGTCCATTTG-3′
GAPDH reverse primer	5′-TGGTGAAGACGCCAGTGGA-3′
circRNA_104433-RNAi(70665–2)	5′-CCGGCTTCAAGTGTCGAGATTGCCTCGAGGCAATCTCGACACTTGAAGTTTTT-3′

Figure 1 Differences in circRNA expression profile between GC tissues and paired adjacent normal tissues.

Notes: (A) The box plot showed variations in circRNA expression. (B) Scatter plots are used to evaluate the differences in circRNA expression. (C) Volcano plots illustrated differential circRNA expression, in which the red points represent the differentially expressed circRNAs with statistical significance. (D) The heatmap shows differentially expressed circRNAs in 5 GC tissues and paired adjacent normal tissues. Gene expression profiles are presented in rows. “Red” indicates high relative expression, and “blue” indicates low relative expression.

Table 2 The Differently Expressed circRNAs Between Gastric Cancer and Normal Gastric Tissues

CircRNA	P value	Log2 FC	Regu	Catalog	Chrom	Strand	Best Transcript	Gene Symbol
hsa_circRNA_104433	0.006	4.426	Up	Exonic	chr7	+	NM_005720	ARPC1B
hsa_circRNA_102121	0.006	4.230	Up	Exonic	chr17	–	NM_000088	COL1A1
hsa_circRNA_102400	0.046	2.498	Up	Exonic	chr19	+	NM_004368	CNN2
hsa_circRNA_104084	0.017	2.321	Up	Exonic	chr6	+	NR_015410	CASC15
hsa_circRNA_101904	0.016	2.302	Up	Exonic	chr16	+	NM_017869	BANP
hsa_circRNA_101826	0.006	2.248	Up	Exonic	chr16	+	NM_003869	CES2
hsa_circRNA_101891	0.033	2.209	Up	Exonic	chr16	+	NM_031476	CRISPLD2
hsa_circRNA_101541	0.003	2.133	Up	Exonic	chr15	–	NM_004039	ANXA2
hsa_circRNA_101539	0.003	2.107	Up	Exonic	chr15	–	NM_004039	ANXA2
hsa_circRNA_100041	0.027	2.638	Down	Exonic	chr1	–	NM_012102	RERE
hsa_circRNA_102374	0.046	2.264	Down	Exonic	chr18	+	NM_015285	WDR7
hsa_circRNA_400102	<0.001	2.190	Down	Intronic	chr9	–	ENS298532	SNAPC4
hsa_circRNA_101525	0.021	2.185	Down	Exonic	chr15	+	NM_004855	PIGB
hsa_circRNA_102924	0.005	2.096	Down	Exonic	chr2	–	NM_006216	SERPINE2

Abbreviations: CircRNA, circular RNA; FC, fold change; Regu, regulation; chrom, chromosome.

Figure 2 Filtering and validation of differentially expressed circRNAs in GC.

Notes: (A, B) Based on differentially expressed circRNAs of our chip results, GEO DataSets were selected using Venn diagram. (C–E) qRT-PCR verified the expression of circRNA_104433 in GC cell lines, in which 61 GC patients and GC cells transfected with lentiviral vectors showed knockdown of circRNA_104433. All the data are presented as mean ± S.D. *P < 0.05, **P < 0.01.

Table 3 Clinico-Pathological Variables and the Expression Level (△ct) of circRNA_104433 in Gastric Cancer Patients

Characteristics	No. of Cases (%)	Mean±SD	P value
Age (years)
<60	37 (60.7)	4.604±0.471	0.178
≥60	24 (39.3)	5.635±0.98
Gender
Male	42 (68.9)	4.885±0.451	0.623
Woman	19 (31.1)	5.285±0.675
Tumor size (cm)
<5	32 (52.46)	5.015±0.532	0.043*
≥5	29 (47.54)	4.222±0.487
TNM stage
I-II	25 (40.98)	4.231±0.555	0.081
III-IV	36 (59.02)	5.550±0.485
Lymph node metastasis
No	21 (34.43)	4.372±0.639	0.218
Yes	40 (65.57)	5.344±0.455
Distant metastasis
Mo	42 (68.85)	4.972±0.484	0.883
M1	19 (31.15)	5.092±0.554
Differentiation
Well and moderate	13 (21.31)	6.987±0.736	0.005*
Poor	48 (78.69)	4.474±0.399

Note: * Statistically significant.

Abbreviation: TNM, tumor, node, metastasis.

Figure 3 The effect of knockdown of circRNA_104433 on cell cycle distribution and proliferation in GC cells.

Notes: (A) Flow cytometer assay was performed to assess the cell cycle. (B, C) The cell cycle distribution of each group was compared. (D, E) CCK8 assay was performed to assess cell proliferation. The OA value curve was used to compare cell proliferation of each group. All data are presented as mean ± S.D. *P < 0.05.

Figure 4 The effect of knockdown of circRNA_104433 on cell apoptosis and tumor growth of xenograft in GC.

Notes: (A, C, E) Flow cytometer assay, AO-EB double staining and Hoechst assay were performed to assess cell apoptosis, respectively. (B, D, F) The rate of cell apoptosis of each group was compared. (G) The images of transplanted tumors in each group (three per group) in nude mice. (H) The growth curve was used to compare the tumors of each group. The tumor volume was measured every four days. All data are presented as mean ± S.D. *P < 0.05.

Figure 5 Confirmation of target gene.

Notes: (A) The base sequence of interaction of miR-497-5p and circRNA_104433 wild-type 3′-UTR and continuous missing style of 3′ UTR reporters. (B) The base sequence of interaction of miR-497-5p and CDC25A wild-type 3′-UTR and continuous missing style of 3′UTR reporters. (C, D) Comparison of differentially expressed luciferase activity in each group. (E, F) Comparison of differentially expressed miR-497-5p and CDC25A in each group. All data are presented as mean ± S.D. *P < 0.05, **P < 0.01.

Figure 6 The prognosis of CDC25A and its related protein mechanism in GC cells.

Notes: (A) Images of genes and protein expressions were detected by Western blotting assay. Comparison of differentially expressed genes in each group. 1, 823-NC group; 2, 823-Si- circRNA_104433 group; 3, 7901-NC group, 4, 7901-Si- circRNA_104433 group. All data are presented as mean ± S.D. *P < 0.05. (B) The Kaplan Meier plot was performed to assess the effect of CDC25A gene expression on survival rate in 876 GC patients. Analysis of original microarray data on GEO DataSets with original microarray data (GSE14210, GSE15459, GSE22377, GSE29272, GSE51105, GSE62254). (C) The network proteins associated with CDC25A were analyzed using the online tool STRING version 10.5.