RNA labeling and array hybridization

Labeled sample and array hybridization were analyzed according to the Agilent One-Color Microarray-Based Gene Expression Analysis protocol (Agilent Technology). The rRNA was removed, and mRNA was purified from total RNA (mRNA-ONLY™ Eukaryotic mRNA Isolation Kit, Epicentre). Then, each specimen was amplified and transcribed into fluorescent cRNA (Arraystar Flash RNA Labeling Kit, Arraystar). The labeled cRNAs were purified using RNeasy Mini Kit (Qiagen). The concentration and specific activity of the labeled cRNAs (pmol Cy3/μg cRNA) were determined by NanoDrop ND-1000. Each labeled cRNA (1 μg) was fragmented by adding 5 μl 10×Blocking Agent and 1 μl of 25×Fragmentation Buffer. The mixture was heated at 60 °C for 30 min, and 25 μl 2×GE Hybridization buffer was added. Hybridization solution (50 μl) was applied and assembled to the lncRNA expression microarray slide. The slides were treated for 17 h at 65 °C in an Agilent Hybridization Oven. The hybridized arrays were scanned by the Agilent DNA Microarray Scanner (part number G2505C).

Microarray and computational analysis

LncRNA expression profiles of SW480 and SW620 (n=3/group) were used to synthesize double-stranded cDNA and hybridized to the 8x60K. RNA quantity and quality were measured by NanoDrop ND-1000. RNA integrity was assessed by standard denaturing agarose gel electrophoresis or Agilent 2100 Bioanalyzer. Arraystar Human LncRNA Microarray V4.0 was designed for the global profiling of human lncRNAs and protein-coding transcripts.

Agilent Feature Extraction software (version 11.0.1.1) was used to analyze acquired array images. Quantile normalization and subsequent data processing were performed with GeneSpring GX v12.1 software package (Agilent Technologies). Differentially expressed lncRNAs and mRNAs were identified through fold change/p value/FDR filtering (fold change ≥2.0, a P value ≤0.05, and FDR ≤0.05). Hierarchical clustering was performed based on differentially expressed mRNAs and lncRNAs using Cluster_Treeview software. The microarray analysis was performed by KangChen Bio-tech, Shanghai, China.

Gene ontological and pathway analysis

The Gene Ontology (GO) project provided a controlled vocabulary to describe gene and gene product attributed in any organism (http://www.geneontology.org). The ontology covers three domains: biological process, cellular component, and molecular function. Fisher’s exact test was used to determine whether the overlap between the differentially expressed list and the GO annotation list was greater than that expected by chance. The lower the P value was the more significant in the GO term enrichment among differentially expressed genes (P value ≤0.05 was recommended).

Pathway analysis was a functional analysis that mapped genes to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways (http://www.genome.jp/kegg/). The P value (EASE-score, Fisher P value, or hypergeometric P value) denoted the significance of the pathway correlated to the condition. The GO and KEGG pathways were analyzed by KangChen Bio-tech, Shanghai, China.

CNC analyses and ceRNA analyses

A coding/non-coding gene co-expression network using 21 mRNAs and the differentially expressed lncRNAs were constructed. The CNC analysis was based on calculating the Pearson correlation coefficient between the expression of coding and noncoding genes. Two correlated genes were screened based on the Pearson correlation using the selection parameters PCC ≥0.99 and FDR <0.05. The co-expression network was illustrated using Cytoscape (v3.4.0). Analyses were performed by KangChen Bio-tech, Shanghai, China.

The potential miRNA response elements were searched on the sequences of lncRNAs and mRNAs. The miRNA binding sites were predicted by miRcode (http://www.mircode.org/), and the miRNA-mRNA interaction was predicted by Targetscan (http://www.targetscan.org/).

RNA isolation and qRT-PCR analyses

RNA isolation and qRT-PCR analyses were performed. The primers to amplify SNHG7: forward, 5′-TTGCTGGCGTCTCGGTTAAT-3′; reverse, 5′-GGAAGTC CATCACAGGCGAA-3′; GALNT7: forward, 5-GGTACCAT GGCCTCATGTTG-3; reverse, 5-GCCACCACACTGCCATATCT-3′; miR-34a: forward, 5′-CACGGACTC GGGGCATTTGGAGATTTT-3′; reverse, 5′-CTGTCTAGATCGCTTATCTTCCC CTTGG3′. U6: forward 5′-CTCGCTTCGGCAGCACA-3′; reverse 5′-AACGCTT CACGAATTTGCGT-3′; GAPDH: forward 5′-AACGTGTCAGTGGTGGACCTG-3′; reverse, 5′-AGTGGGTGTCGCTGTTGAAGT-3′; miR-34a was normalized to U6, lncRNA-SNHG7 and mRNA expression data were normalized to GAPDH. The relative expression was calculated using the 2-ΔΔCT method.

Plasmids, oligonucleotides, siRNA, transfection, and dual luciferase assay

SNHG7 pcDNA3.1 vector (SNHG7), GALNT7 pcDNA3.1 vector (GALNT7), and empty vector (vector) were subcloned into the expression vector pcDNA3.1 (Invitrogen, USA). MiR-34a mimic, negative control oligonucleotides (miR-NC), miR-34a inhibitor, negative control oligonucleotide (NC inhibitor), small interfering RNA of SNHG7 or GALNT7 (siSNHG7, siGALNT7), and scramble siRNA of SNHG7 or GALNT7 (siSCR) were purchased from RiboBio (Guangzhou, China). The cells were seeded into six-well plates, and transfection was performed using Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instruction. ShSCR and shSNHG7 were purchased from RiboBio (Guangzhou, China) and constructed into CRC cell lines for further in vivo experiments. The transfection efficiency was evaluated by fluorescence microscopy by calculating the percentage of fluorescein-labeled cells.

Cells were cultured overnight until 70–80% confluence. Next, cells were co-transfected with pcDNA3.1 SNHG7-wt, pcDNA3.1 SNHG7-mut, pcDNA3.1 GALNT7-wt or pcDNA3.1 GALNT7-mut was transfected into HEK-293T cells together with miR-34a mimic or the control, respectively. Lipofectamine 2000 (Invitrogen Co., Carlsbad, CA, USA) was used according to the manufacturer’s instructions. After 48 h, cells were harvested for luciferase detection using the dual-luciferase reporter gene assay system (Promega, Madison, WI, USA). All values were obtained from at least three independent repetitions of the transfection.

RNA immunoprecipitation (RIP) assay

RIP assay was performed using the Magna RIP™ RNA Binding Protein Immunoprecipitation Kit (Millipore, Bedford, MA, USA). Cells were collected and lysed in complete RIPA buffer containing a protease inhibitor cocktail and RNase inhibitor. Next, the cell extracts were incubated with RIP buffer containing magnetic bead conjugated with human anti-Ago2 antibody (Millipore) or mouse immunoglobulin G (IgG) control. The protein was digested with proteinase K, and subsequently, the immunoprecipitated RNA was obtained. The purified RNA was finally subjected to a qRT-PCR analysis to demonstrate the presence of the binding targets.

Ethynyldeoxyuridine (Edu) analysis

Edu detection kit (KeyGENBioTECH, Nanjing, China) was used to assess cell proliferation. Cells were cultured in 96-well plates at 4×10⁴ cells/well. Twenty-micromolar Edu labeling media was added to the 96-well plates, and they were then incubated for 2 h at 37 °C under 5% CO₂. After treatment with 4% paraformaldehyde and 0.5% Triton X-100, the cells were stained with the anti-Edu working solution.

Viability assay, colony formation assay, and tumorigenicity assays in nude mice

The cell viability was monitored using the Cell Counting Kit-8 (CCK8) according to the manufacturer’s protocol. Measured the OD (optical density) value by microplate computer software (Bio-Rad Laboratories, Hercules, CA). Absorbance at 450 nM (A450) was read on a microplate reader (168–1000 Model 680, Bio-Rad).

Colony formation assay was performed to measure the capacity of cell proliferation. Briefly, 1×10³ cells were plated in six-well plates. After incubated for 12 days, cells were fixed, stained, photographed, and analyzed.

Tumorigenicity assays in nude mice were performed. Briefly, the mice in groups were inoculated subcutaneously with 1×10⁷ cells in the right flank with SNHG7, shSNHG7, or control. Tumor volumes were calculated by using the equation volume (mm³)=A×B²/2, where A is the largest diameter, and B is the perpendicular diameter.

Cell cycle analysis and apoptosis analysis

Cell cycle and apoptosis analysis were cultured as previously described [16].

Wound healing, transwell migration, transwell invasion, and endothelial tube formation assay

Wound healing assay was performed to measure the capacity of cell migration. Detailed description of wound healing assay was cultured as previously describe [16]. The results were photographed using an inverted microscope (Olympus, Japan) and analyzed by software IPP Image-Pro Plus 6.0.

Transwell assay was performed using Boyden chambers containing a transwell membrane filter (Corning, New York, USA). Transwell assay analysis was cultured as previously described [16]. Evaluation of invasive capacity was performed by counting invading cells under a microscope (40×10). Five random fields of view were analyzed for each chamber.

Detailed description of angiogenesis assay was cultured as previously described [16] and analyzed by ImageJ software (National Institutes of Health, Bethesda, MD).

Western blot analysis

Western blot analysis was cultured as previously described [16]. GALNT7 monoclonal antibody (1:1000, Abcam, Cambridge, UK), PI3K, p-PI3K Tyr458, Akt, p-Akt Ser473, mTOR, p-mTOR Ser2248 antibody (1:1000 Proteintech, Chicago, USA). Immunoreactive bands were visualized using ECL Western blotting kit (Amersham Biosciences, Buckinghamshire, UK) and were normalized to GAPDH.

LncRNA SNHG7 is upregulated in CRC tissues and cell lines and correlated with poor progression

The microarray results showed that SNHG7 level was significantly higher in SW620 than in SW480 cells. To further explore SNHG7 expression, CRC cell lines were validated. SNHG7 expression was significantly higher in SW620 cells than in SW480 cells (Fig. 2a). In parallel, SNHG7 level was also higher in CRC tissues than that in adjacent tissues (Fig. 2b, c).

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Fig. 2

Expression of SNHG7 in CRC tissues, CRC cell lines, and its clinical significance. a Expression of SNHG7 in CRC cells was analyzed by qRT-PCR. b SNHG7 expression in CRC tissues were determined (cohort 2, n=70). c Relative expression of SNHG7 in CRC tissues in comparison with non-tumor tissues was analyzed (cohort 1, n=53). d–g The correlation between SNHG7 expression and clinical pathological features was shown. SNHG7 upregulation was correlated with larger tumor size, lymphatic metastasis, distant metastasis, and advanced pathological stage in CRC. h, i Kaplan–Meier OS and DFS rates of 53 patients were shown. The error bars in graphs represented SD. Each experiment was repeated thrice. *P<0.05, **P<0.01, ***P<0.001

In order to examine the correlation between SNHG7 level and clinical pathological features, we stratified 53 tumor tissue samples (cohort 1) into high and low expression groups (Table 2) and found that SNHG7 expression was significantly correlated with tumor size (<5 vs. ≥5 cm, P =0.025), lymphatic metastasis (absent vs. present, P=0.002), distant metastasis (absent vs. present, P=0.004), and tumor stage (I/II vs. III/IV P =0.002, Fig. 2d–g). Multivariate analysis indicated that SNHG7 expression (95% CI 1.035–5.268; P =0.030), lymphatic metastasis (95% CI 0.869–4.012; P =0.045), distant metastasis (95% CI 1.586–5.275; P=0.011), and tumor stage (95% CI 1.301–6.684; P=0.002) were independent predictors of the prognosis of CRC (Table 3).

Table 2

Relationship between SNHG7 expression and clinicopathologic parameters of 53 colorectal cancer patients (cohort 1)

Characteristics	Number of case	SNHG7 expression		P value
		High (n=30) %	Low (n=23) %
	53
Age (years)				0.477
<60	27	14	13
>60	26	16	10
Gender				0.337
Male	33	17	16
Female	20	13	7
Tumor size				0.025*
<5 cm	23	9	14
≥5 cm	30	21	9
Tumor location				0.745
Colon	29	17	12
Rectum	24	13	11
Depth of invasion				0.194
T1,T2	34	17	17
T3,T4	19	13	6
Histologic grade				0.206
Well/moderately	27	13	14
Poorly/others	26	17	9
Lymphatic metastasis				0.002**
Absent	24	8	16
Present	29	22	7
Venous invasion				0.132
Absent	27	18	9
Present	26	12	14
Nervous invasion				0.414
Absent	31	19	12
Present	22	11	11
Distant metastasis				0.004**
Absent	32	13	19
Present	21	17	4
Tumor stage*				0.002**
I and II	26	9	17
III and IV	27	21	6

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*Tumor stage was obtained according to the TNM criteria

**P<0.05

Table 3

Univariate and multivariate Cox regression analyses of clinicopathological features association with prognosis of 53 CRC patients (cohort 1)

Variables	Subset	Univariate analysis		Multivariate analysis
		HR (95% CI)	P value	HR (95% CI)	P value
Age (years)	<60 vs. ≥60	1.379(0.525–2.484)	0.495	–	–
Gender	Male vs. female	1.514(0.701–2.916)	0.410	–	–
Tumor size	<5 cm vs. ≥5 cm	2.438(1.003–5.105)	0.062	–	–
Tumor location	Colon vs. rectum	1.028(0.712–1.582)	0.875	–	–
Histologic grade	Well/moderately vs. poorly/others	1.847(0.571–2.896)	0.289	–	–
Depth of invasion	T1,T2 vs. T3,T4	2.561(0.911–4.616)	0.124	–	–
Lymphatic metastasis	Absent vs. Present	3.054(1.008–5.531)	0.028*	2.313(0.869–4.012)	0.045*
Venous invasion	Absent vs. Present	1.478(0.491–3.292)	0.353	–	–
Distant metastasis	Absent vs. Present	3.681(1.308–5.928)	0.004*	3.163(1.586–5.275)	0.011*
Tumor stage	I-II vs. III-IV	4.422(1.849–8.241)	<0.001*	3.549(1.301–6.684)	0.002*
SNHG7 expression	Low vs. high	3.317(1.331–5.609)	0.008*	2.924(1.035–5.268)	0.030*

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HR hazard ratio, CI confidence interval

*P<0.05

To understand the prognostic value of SNHG7, the overall survival (OS) and disease-free survival (DFS) rates were analyzed. High expression of SNHG7 had poorer prognosis than low expression of SNHG7 (P=0.0105, OS, and P=0.0043, DFS, Fig. 2h, i) by Kaplan-Meier and log-rank test analyses. These results implied that SNHG7 overexpression might be useful for the novel prognostic markers in CRC.

SNHG7 mediates CRC cell proliferation, cell cycle progression, and apoptosis in vitro

To investigate the biological significance of SNHG7 in CRC progression, the cell proliferation was analyzed. Following SNHG7 overexpression, the proliferative capability of CRC cell lines was increased using CCK8 assay (Fig. 3a), clone formation (Fig. 3b), and Edu staining (Fig. 3c). Knockdown of SNHG7 attenuated the proliferative ability. In addition, the cell cycle was analyzed following SNHG7 overexpression or silencing by fluorescence-activated cell sorting (FACS). G1/S phase was driven in SW480 cell transfected with SNHG7, whereas stalled G1/S was observed in SW620 cell transfected with siSNHG7 in Fig. 3d. The apoptosis cells were decreased in transfected with SNHG7 group, while in transfected with siSNHG7, SW620 cells had a significantly higher percentage of Annexin V-positive cells by FACS analysis (Fig. 3e). Furthermore, upregulation of SNHG7 led to reduced levels of cleaved caspase 3 and cleaved PARP in SW480 cells, and opposite trend was found in SW620 cells transfected with siSNHG7 compared with siSCR (Fig. 3f). These data indicated that SNGH7 promoted cell proliferation, facilitated cell cycle progression, and inhibited apoptosis in vitro.

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Fig. 3

SNHG7 mediates cell proliferation, cell cycle, and apoptosis of CRC cells in vitro. a–c Cell proliferation was analyzed by CCK-8 assay, colony formation assay, and immunofluorescence analysis with ki67 and Edu. d The influence of CRC cell lines in S phase transfected with SNHG7 or siSNHG7 was investigated by FACS analysis. e Apoptosis rates of CRC cells transfected with SNHG7 or siSNHG7 was detected by FACS analysis. f Relative cleaved PARP and cleaved caspase-3 expression following transfected or silencing SNHG7 in CRC cells were analyzed by Western blot. The error bars in graphs represented SD, and each experiment was repeated thrice. *P<0.05, **P<0.01, ***P<0.001

SNHG7 promotes CRC cell migration, invasion, vasculogenic mimicry in vitro, and proliferation in vivo

To measure the migratory and invasive ability of CRC cells, wound healing and transwell assays were utilized. The results showed that the ability of migration and invasion were increased in SW480 cell transfected with SNHG7, while the migratory and invasive ability were decreased in SW620 cell transfected with siSNHG7 (Fig. 4a–c).

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Fig. 4

SNHG7 promotes cell migration, invasion, vasculogenic mimicry of CRC cells in vitro, and proliferation in vivo. a, b The cell migration rates were determined by performing wound healing and transwell assay. c Transwell invasion assays were performed. d The abilities of neovascularization were determined by endothelial tube formation assay. e Effects of SNHG7 overexpression on tumor growth in vivo. Left: images of tumors in nude mice injected with SNHG7-overexpressed SW480 cells. Middle: tumor weights. Right: tumor growth curves. f Effects of SNHG7 knockdown on tumor growth in vivo. Left: images of tumors in nude mice injected with shSNHG7 SW620 cells. Middle: tumor weights. Right: tumor growth curves. g, h Ki67 was detected by IHC assay. The error bars in all graphs represented SD, and each experiment was repeated thrice. *P<0.05, **P<0.01, ***P<0.001

It is well known that new blood vessel is essential in tumor development. The endothelial tube formation assay was used to assess the ability of SNHG7 in CRC cell progression. The results showed that neovascularization rate was increased after transfecting with SNHG7 or decreased after transfecting with siSNHG7 compared with their negative controls (Fig. 4d).

To confirm whether SNHG7 affect CRC tumorigenesis, SW480 cells (transfected with SNHG7 or NC) and SW620 cells (transfected with shSNHG7 or shSCR) were inoculated into nude mice. As shown in Fig. 4e, f, tumor growth in SNHG7 group was significantly faster than that in NC group, while tumor growth was slower in shSNHG7 group than that in shSCR group. Furthermore, the average tumor weight was obviously changed than their corresponding control group. In order to further validate the growth ability mediated by SNHG7 in vivo, the tumor tissues were for IHC staining with ki67 antibody. These results were consistent with our above data that SNHG7 overexpression enhanced the growth and downregulation of SNHG7 decreased the tumor growth of CRC cell lines (Fig. 4g, h). Collectively, these data demonstrated that SNHG7 promoted CRC cell progression.

SNHG7 is a direct target of miR-34a and regulates GALNT7 expression in CRC cell lines

Recently, accumulating evidence has suggested that lncRNA has an inhibitory effect on miRNA expression and activity [17]. CeRNA analysis and bioinformatics software (Starbase v2.0) were used to predict the potential miRNA binding sites in SNHG7. We found that miR-34a was among the numerous possible targets of SNHG7 (Fig. 5a). MiR-34a level was much lower in CRC tissues than that in adjacent tissues (Fig. 5b). Pearson correlation coefficient analysis showed a significant negative correlation between SNHG7 and miR-34a in CRC tissues (Fig. 5c). The luciferase activity of wt-SNHG7 was significantly reduced by miR-34a mimic (Fig. 5d). In contrast, the luciferase activity of mut-SNHG7 experienced no statistical changes. These findings indicated that there were interaction between miR-34a and the binding sites of SNHG7.

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Fig. 5

SNHG7 is a direct target of miR-34a and regulates GALNT7 expression in CRC cells. a Sequence alignment of miR-34a with the binding sites in the wild-type and mutant-type regions of SNHG7 was shown. b miR-34a expression in CRC tissues were determined. c The negative relevance between SNHG7 and miR-34a was revealed by Pearson’s correlation curve. d The relative luciferase activity of 293T cells was tested after co-transfection with SNHG7 wide-type and miR-34a mimic. e RIP assay was performed, and the co-precipitated RNA was subjected to qRT-PCR. RNA levels were presented as fold enrichment in Ago2 relative to IgG immunoprecipitates. f, g Relative GALNT7 expression of CRC tissues and CRC cells were analyzed. h The positive relevance between SNHG7 and GALNT7 expression was revealed by Pearson’s correlation curve. i GALNT7 level in SW480 cells transfected with SNHG7 was shown. j GALNT7 level in SW620 cells transfected with siSNHG7 was shown. The error bars in graphs represented SD, and each experiment was repeated thrice. *P<0.05, **P<0.01, ***P<0.001

The previous study indicated that lncRNAs might act as the sponge of miRNAs and function through binding the miRNAs and Argonaute 2 (Ago2) [18, 19]. According to the bioinformatics software, the sites of SNHG7/miR-34a could also bind the protein Ago2 protein. So, RIP assay was performed in SW480 and SW620 cell extracts utilizing the antibody against Ago2. SNHG7 and miR-34a expression were detected by qRT-PCR. The results illustrated that both SNHG7 and miR-34a were enriched in the Ago2 pellet relative to control IgG immunoprecipitate (Fig. 5e), suggesting that SNHG7 was present in Ago-contained miRNPs, likely through an association with miR-34a.

Gene co-expression networks indicated that SNHG7 was correlated with nine mRNAs (B3GLCT, FUT2, MFNG, MGAT4A, GALNT1, GALNT5, GALNT7, ST3GAL5, ST6GALNAC2). GALNT7 was the highest correlation among these mRNAs in Pearson analysis. GALNT7 level was identified in CRC tissues and metastasis cell lines (Fig. 5f, g), and a positive relationship between the levels of SNHG7 and GALNT7 mRNA was found (Fig. 5h). The expression of GALNT7 mRNA and protein were significantly increased in SW480 cells overexpressing SNHG7 (Fig. 5i). In contrast, GALNT7 level was downregulated in SW620 cells with silencing SNHG7 (Fig. 5j). These results showed that SNHG7 indeed regulated GALNT7 level.

GALNT7 is a target gene of miR-34a in CRC cell lines

Lately, ceRNA hypothesis was proposed to describe the crosstalk of RNA transcripts with each other by using MREs. LncRNAs participate in ceRNA networks and mRNA-miRNA-lncRNA crosstalk [20]. We initially identified GALNT7 as potential target of miR-34a using public prediction algorithms (Target-Scan, miroRNA.org and Starbase v2.0) (Fig. 6a). Then, Pearson analysis showed a negative correlation with miR-34a and GALNT7 in CRC samples (Fig. 6b). Next, the dual luciferase reporter assay revealed that GALNT7 was the direct target of miR-34a (Fig. 6c).

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Fig. 6

GALNT7 is a target gene of miR-34a in CRC cells. a Sequence alignment of miR-34a with the binding sites in the wild-type and mutant-type regions of GALNT7 was shown. b The negative relevance between miR-34a and GALNT7 expression was revealed by Pearson’s correlation curve. c The relative luciferase activity of 293T cells was tested after co-transfection with GALNT7 wide-type and miR-34a mimic. d GALNT7 level in SW480 cells co-tranfected with SNHG7 and miR-34a mimic was analyzed. e GALNT7 level in SW620 cells co-tranfected with siSNHG7 and miR-34a inhibitor was shown. f, g SNHG7 and GALNT7 competing to bind with miR-34a were identified by function screen analysis in SW480 and SW620 cells. The error bars in graphs represented SD, and each experiment was repeated thrice. *P<0.05, **P<0.01

To verify the phenomenon of mRNA and lncRNA competed for the binding of miRNA, GALNT7 expression was analyzed. The GALNT7 level was higher in SW480 cell transfected with Wt-SNHG7 than that transfected with Mut-SNHG7 (Fig. 6d). The influence of Wt-SNHG7 could be reversed by transfecting miR-34a mimic in SW480 cells, which identified that SNHG7 regulated GALNT7 by sponging for miR-34a. SNHG7 knockdown led to a decreased GALNT7 expression, while GALNT7 level could be reversed by co-transfecting siSNHG7 and miR-34a inhibitor in SW620 cells (Fig. 6e).

SNHG7 or GALNT7 and miR-34a mimic were co-transfected into SW480 cells; the ability of proliferation, migration, invasion, and vasculogenic mimicry were recovered (Fig. 6f). By contrary, knockdown of SNHG7 or GALNT7 expression weakened the proliferation and metastasis in SW620 cells. Suppression of miR-34a relieved the reduced level of SNHG7 or GALNT7 (Fig. 6g). All of the outcomes above explained that SNHG7 functioned as a ceRNA to regulate GALNT7 expression by sponging miR-34a in CRC progression.

We thank Nana Li, Yuan Miao, Tianming Qiu, and Yining Zhang for the technical assistance. We also thank Huimin Zhou for the comments and advice.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.