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Introduction

Colon cancer is the most common type of tumor of the gastrointestinal tract, and ranks as the third highest cause of cancer-associated mortality worldwide (1). The etiology and pathogenesis of colon cancer are complex and are associated with various factors, such as diet- and lifestyle-associated genetic and epigenetic changes (2). Recent advances in the treatment of colon cancer have been reported, including surgery combined with chemotherapy, radiofrequency ablation or targeted therapy; however, the rate of postoperative recurrence remain at ~50%, leading to a poor overall survival (OS) for the patients with colon cancer (3). Therefore, there is an urgent need to identify novel biomarkers and potential therapeutic targets for this deadly disease (4).

Long non-coding RNAs (lncRNAs), which are >200 nucleotides in length, have been reported to act as key regulators of various biological processes; the aberrant expression of lncRNAs are associated with several diseases, including cancer (5–9). Accumulating evidence has suggested that lncRNAs could serve as potential biomarkers for the early diagnosis, prognosis and prediction of metastasis for various types of malignancy (10–15).

In recent years, with advances in bioinformatics and interdisciplinary studies involving the development of a series of computational methods and software tools for the analysis of extensive biological data, numerous lncRNAs have been identified to be dysregulated in colon cancer. For instance, by a bioinformatic approach, a recent study classified Linc00659 as a novel oncogenic lncRNA involved in the tumorigenesis of colon cancer by modulating the progression of the cell cycle; downregulation of Linc00659 expression resulted in severe cell cycle arrest and enhanced the apoptosis of colon cancer cells (16). Similarly, based on bioinformatics analysis of The Cancer Genome Atlas (TCGA) and/or the Gene Expression Omnibus datasets, as well as subsequent experimental validation, metastasis-associated lung adenocarcinoma transcript 1 and small nuclear host gene 1 have been recently identified to be oncogenic lncRNAs, which may serve as potential diagnostic and therapeutic targets in colorectal cancer (CRC) (17–20). These results suggest the potential clinical value of lncRNAs in CRC; however, the lncRNAs associated with the prognosis and survival of patients, as well as their biological roles, require further investigation.

Therefore, the present study aimed to identify the key lncRNAs associated with their prognostic and biological roles using a comprehensive bioinformatics process. The gene expression datasets downloaded from The Cancer Genome Atlas (TCGA) database, which includes the corresponding survival and Tumor-Node-Metastasis (TNM) stage (21) status of patients with CRC, were utilized to construct a prognostic prediction system.

Materials and methods

TCGA CRC data mining and screening

The level 3 normalized lncRNA expression data of CRC, CRC gene expression data and corresponding clinical data were obtained from the TCGA database (https://cancergenome.nih.gov). The expression profiling platform RNA-seqv2 was used. No further normalizations were applied to the level 3 lncRNA expression profile data. A total of 521 samples were obtained, of which 480 were CRC tissues and 41 were adjacent normal tissues. The lncRNA expression profile of tumor and normal tissues was determined to screen for differentially expressed lncRNAs using edgeR (http://www.bioconductor.org/packages/release/bioc/html/edgeR.html; R software; version 3.4.2; Bell Laboratories) with thresholds of |log2[fold-change (FC)]|>2.0 and adjusted P-value [false discovery rate (FDR)]<0.05. A volcano plot was generated using theplot function in R (https://www.rdocumentation.org/packages/graphics/versions/3.6.0/topics/pl; R software; version 3.4.2; Bell Laboratories).

Survival analysis

Kaplan-Meier analysis followed by a log-rank test was performed to assess the OS between low- and high-lncRNA expression groups using the R package ‘survival’ (https://cran.r-project.org/web/packages/survival/index.html; R software; version 3.4.2; Bell Laboratories). The Kruskal-Wallis test was used to evaluate the association between tumor stage. The staging system of colon cancer using UICC/AJCC (7th edition) (21), and the lncRNAs that were significantly associated with OS. Additionally, univariate and multivariate Cox regression analyses were used to evaluate the association between the expression levels of lncRNAs and the OS of patients with CRC, and to identify independent prognostic values of lncRNAs. P<0.05 was considered to indicate a statistically significant difference.

Analysis of co-expressed protein-coding genes (PCGs)

To determine the association between lncRNAs and co-expressed PCGs, the Pearson correlation coefficients (r) of the lncRNAs and PCGs were calculated using the cor.test function in R. The PCGs with |r|>0.4 and P<0.001 were considered as lncRNA-associated PCGs.

Functional and pathway enrichment analyses

The identified co-expressed PCGs were further investigated using clusterProfiler R package (http://www.bioconductor.org/packages/release/bioc/html/clusterProfiler.html; R software; version 3.4.2; Bell Laboratories), including functional Gene Ontology (GO) (22) and Kyoto Encyclopedia of Genes and Genomes (KEGG) (23) pathway enrichment analyses. P<0.05 was considered to indicate a statistically significant difference.

Results

Identification of significantly differentially expressed lncRNAs in CRC

In a preliminary screening, the data of 480 CRC and 41 adjacent normal colorectal mucosal tissues were extracted from the symbol matrix. A total of 1,180 significant differentially expressed lncRNAs were identified with |logFC|>2 and FDR<0.05, of which 916 were upregulated and 264 were downregulated. A volcano plot of the identified lncRNAs was constructed (Fig. 1). The top 10 upregulated and downregulated lncRNAs are presented in Tables I and II.

Figure 1. Volcano plot of significantly differentially expressed lncRNAs associated with colorectal cancer. Red, green and black dots represent upregulated, downregulated and non-differentially expressed lncRNAs, respectively. lncRNA, long non-coding RNA; FC, fold-change; FDR, false discovery rate.

Table I. Top 10 upregulated lncRNAs with significantly different expression between tumor and normal tissues in The Cancer Genome Atlas colon cancer data.

Table I.

Top 10 upregulated lncRNAs with significantly different expression between tumor and normal tissues in The Cancer Genome Atlas colon cancer data.

lncRNA	Ensembl_Gene_ID	logFC	P-value	FDR
PVT1	ENSG00000249859	2.58	1.70×10−67	4.23×10−65
CCAT1	ENSG00000247844	4.47	1.68×10−59	2.51×10−57
BLACAT1	ENSG00000281406	5.12	3.88×10−59	5.59×10−57
LINC02163	ENSG00000251026	7.08	1.19×10−54	1.37×10−52
CRNDE	ENSG00000245694	4.58	1.30×10−52	1.31×10−50
MAFG-AS1	ENSG00000265688	2.88	7.82×10−51	7.51×10−49
RP5-884M6.1	ENSG00000228742	6.31	1.04×10−50	9.69×10−49
CASC19	ENSG00000254166	4.51	3.30×10−50	3.02×10−48
RP5-1120P11.1	ENSG00000237686	4.41	7.64×10−50	6.65×10−48
AC007128.1	ENSG00000229970	4.48	2.64×10−48	2.17×10−46

[i] lncRNA, long non-coding RNA; FC, fold-change; FDR, false discovery rate.

Table II. Top 10 downregulated lncRNAs with significantly different expression between tumor and normal tissues in The Cancer Genome Atlas colon cancer data.

Table II.

Top 10 downregulated lncRNAs with significantly different expression between tumor and normal tissues in The Cancer Genome Atlas colon cancer data.

lncRNA	Ensembl_Gene_ID	logFC	P-value	FDR
XXbac-B476C20.9	ENSG00000225335	−2.72	2.14×10−173	1.60×10−169
CDKN2B-AS1	ENSG00000240498	−5.21	9.05×10−140	3.39×10−136
LINC01645	ENSG00000224968	−4.60	6.90×10−127	1.72×10−123
PP7080	ENSG00000188242	−3.48	3.24×10−124	6.07×10−121
XXyac-YM21GA2.7	ENSG00000214888	−5.69	7.06×10−120	1.06×10−116
RP11-1090M7.1	ENSG00000265489	−4.48	1.49×10−116	1.85×10−113
RP11-396O20.2	ENSG00000254645	−5.01	1.71×10−114	1.83×10−111
AC007182.6	ENSG00000224721	−4.67	4.65×10−108	4.35×10−105
AC106869.2	ENSG00000226087	−4.18	2.71×10−105	2.25×10−102
LINC00682	ENSG00000245870	−4.55	1.18×10−96	8.82×10−94

[i] lncRNA, long non-coding RNA; FC, fold-change; FDR, false discovery rate.

Analysis of significant differentially expressed lncRNAs in CRC samples associated with OS and pathological stages

To investigate the association between lncRNA expression and OS, the expression profile of the 1,180 lncRNAs in tumor samples were determined, of which 56 lncRNAs were associated with OS, as determined by Kaplan-Meier analysis (Table III). The top 10 lncRNAs significantly associated with OS (P<0.05) were RP11-108K3.2, RP11-815M8.1, LINC01836, AC079612.1, LINC01354, RBAKDN, RP11-400N13.2, RP1-142L7.9, AFAP1-AS1 and LINC01655 (Fig. 2).

Figure 2. Top 10 lncRNAs associated with overall survival derived from 1,180 significantly differentially expressed genes. Patients were divided into high and low expression groups according to the median value of all patients. The data of the top 10 of the 56 lncRNAs are presented. lncRNA, long non-coding RNA.

Table III. lncRNAs significantly associated with OS.

Table III.

lncRNAs significantly associated with OS.

lncRNA	Ensembl_Gene_ID	P-value
RP11-108K3.2	ENSG00000259306	1.98646×10−5
RP11-815M8.1	ENSG00000238042	2.78454×10−5
LINC01836	ENSG00000267530	0.000256940
AC079612.1	ENSG00000196758	0.000535749
LINC01354	ENSG00000231768	0.000985613
RBAKDN	ENSG00000273313	0.001143877
RP11-400N13.2	ENSG00000228437	0.002268513
RP1-142L7.9	ENSG00000270661	0.003700521
AFAP1-AS1	ENSG00000272620	0.004000305
LINC01655	ENSG00000227925	0.004380952
RP11-10A14.5	ENSG00000248538	0.004693149
RP11-384P7.7	ENSG00000260947	0.004845978
RP11-434D9.2	ENSG00000249894	0.005561553
RP11-742B18.1	ENSG00000249001	0.007363036
CTC-327F10.4	ENSG00000251320	0.008786437
AC064834.1	ENSG00000224099	0.00890189
ARHGEF26-AS1	ENSG00000243069	0.008966797
RP3-380B8.4	ENSG00000233064	0.009485845
LINC01829	ENSG00000236780	0.009974597
GAS1RR	ENSG00000226237	0.013908392
RP11-84A19.4	ENSG00000269967	0.014180465
LINC02043	ENSG00000232233	0.016339686
LINC00922	ENSG00000261742	0.016854765
RP11-278L15.2	ENSG00000243885	0.017325027
RP1-122P22.4	ENSG00000268628	0.018507105
RP11-366L20.2	ENSG00000197301	0.019632443
DUXAP8	ENSG00000206195	0.020361403
CTB-181H17.1	ENSG00000272219	0.020685373
MIR31HG	ENSG00000171889	0.021365649
AC012531.25	ENSG00000260597	0.023942649
FOXD3-AS1	ENSG00000230798	0.024144909
AC007128.1	ENSG00000229970	0.027145232
DNAH17-AS1	ENSG00000267432	0.02735923
LINC01833	ENSG00000259439	0.027941465
RP11-429J17.5	ENSG00000254548	0.028089082
LL22NC03-N14H11.1	ENSG00000272872	0.031532618
RP1-79C4.4	ENSG00000271811	0.031571197
CTB-186G2.4	ENSG00000267375	0.031679272
RP11-114H23.2	ENSG00000258088	0.033221364
LINC00484	ENSG00000229694	0.035515205
RP1-29C18.10	ENSG00000212939	0.035961207
AC073326.3	ENSG00000228540	0.036298277
RP11-126H7.4	ENSG00000204049	0.036449014
CTD-2619J13.13	ENSG00000268307	0.037145687
LINC01748	ENSG00000226476	0.038383393
RP11-532F6.3	ENSG00000272463	0.042708274
RP11-728G15.1	ENSG00000256008	0.043149989
LINC01060	ENSG00000249378	0.045508319
KCNQ1OT1	ENSG00000269821	0.045529181
LINC01996	ENSG00000261863	0.046591159
ELFN1-AS1	ENSG00000236081	0.046625182
HOTAIR	ENSG00000228630	0.047908786
LINC00461	ENSG00000245526	0.04796558
CTD-2600O9.1	ENSG00000187185	0.048650792
LEF1-AS1	ENSG00000232021	0.049375626
FLJ16779	ENSG00000275620	0.049920309

[i] lncRNA, long non-coding RNA.

The association between clinical stages (UICC/AJCC 7th Edition) (21) and the 56 lncRNAs associated with OS was determined via a Kruskal-Wallis test. The results demonstrated that 7 lncRNAs were identified as key lncRNAs associated with the Tumor-Node-Metastasis (TNM) stages of colon cancer, including DNAH17-AS1, RP11-429J17.5, RP11-742B18.1, RP11-400N13.2, LL22NC03-N14H11.1, LINC01836 and HOTAIR (Table IV; Fig. 3). The detailed information of the patients at each TNM stage is presented in Table SI. Notably, these 7 lncRNAs were upregulated in colon cancer tissues compared with adjacent normal tissues, suggesting that they may serve a tumorigenic role in the initiation and progression of CRC.

Figure 3. A total of 7 lncRNAsare significantly associated with the clinical stages of patients with colorectal cancer. The horizontal axis represents the clinical stage, whereas the vertical axis represents the expression levels of 7 lncRNAs that were significantly associated with the clinical stages of patients with colorectal cancer. lncRNA, long noncoding RNA.

Table IV. lncRNAs significantly associated with tumor clinical stage.

Table IV.

lncRNAs significantly associated with tumor clinical stage.

lncRNA	Ensembl_Gene_ID	P-value
FLJ16779	ENSG00000275620	0.049920309
DNAH17-AS1	ENSG00000267432	6.42×10−5
RP11-429J17.5	ENSG00000254548	0.000628536
RP11-742B18.1	ENSG00000249001	0.00141941
RP11-400N13.2	ENSG00000228437	0.003179863
LL22NC03-N14H11.1	ENSG00000272872	0.005376623
LINC01836	ENSG00000267530	0.011461646
HOTAIR	ENSG00000228630	0.013000989

[i] lncRNA, long non-coding RNA.

Identification of independent prognostic lncRNAs in CRC

In order to detect potential independent prognostic lncRNAs in patients with CRC, univariate and multivariate Cox regression analyses of these 7 lncRNAs associated with TNM stage were performed. The association between the expression levels of lncRNAs and the OS of patients with colon cancer was explored using the R package ‘survival’; 2 lncRNAs, DNAH17-AS1 and RP11-400N13.2, were identified to be independent prognostic factors for OS in patients with CRC (P<0.05; Tables V and VI).

Table V. Cox regression analyses of the association between DNAH17-AS1 and patient clinicopathological characteristics.

Table V.

Cox regression analyses of the association between DNAH17-AS1 and patient clinicopathological characteristics.

	Univariate				Multivariate
Characteristic	P-value	HR	HR (lower 0.95)	HR (upper 0.95)	P-value	HR	HR (lower 0.95)	HR (upper 0.95)
Age, years	1.54×10−2	1.024705	1.00467006	1.045139527	8.62×10−5	1.043293	1.021452741	1.065600322
Sex	8.11×10−1	1.055993	0.675320904	1.651244946	5.15×10−1	0.859753	0.545233986	1.355701712
Stage	4.32×10−10	2.260538	1.749817646	2.92032165	3.09×10−1	1.481753	0.693752964	3.164805106
T	5.85×10−6	2.842169	1.809061684	4.465257511	4.32×10−2	1.753715	1.017244601	3.023378521
M	6.75×10−10	4.348202	2.726493071	6.934496948	3.83×10−1	1.584756	0.562533031	4.464537953
N	1.29×10−7	2.014039	1.553071957	2.611824311	2.84×10−1	1.281519	0.813788046	2.01808327
DNAH17-AS1	1.17×10−3	56.08087	4.924770723	638.6214937	1.61×10−2	29.59342	1.872773849	467.6327355

[i] HR, hazard ratio; HR (lower 0.95), hazard ratio (lower 95% CI); HR (upper 0.95), hazard ratio (upper 95%CI); T, tumor; N, node; M, metastasis.

Table VI. Cox regression analyses of the association between RP11-400N13.2 and patient clinicopathological characteristics.

Table VI.

Cox regression analyses of the association between RP11-400N13.2 and patient clinicopathological characteristics.

	Univariate				Multivariate
Characteristic	P-value	HR	HR (lower 0.95)	HR (upper 0.95)	P-value	HR	HR (lower 0.95)	HR (upper 0.95)
Age, years	1.54×10−2	1.024705	1.00467006	1.045139527	3.70×10−4	1.03741	1.016647195	1.058596272
Sex	8.11×10−1	1.055993	0.675320904	1.651244946	7.37×10−1	0.925432	0.588464244	1.455355124
Stage	4.32×10−10	2.260538	1.749817646	2.92032165	2.61×10−1	1.54623	0.722569696	3.308782317
T	5.85×10−6	2.842169	1.809061684	4.465257511	3.02×10−2	1.842378	1.059948791	3.202377507
M	6.75×10−10	4.348202	2.726493071	6.934496948	3.49×10−1	1.628719	0.586703577	4.521408077
N	1.29×10−7	2.014039	1.553071957	2.611824311	4.82×10−1	1.181526	0.741699234	1.882169148
RP11-400N13.2	2.49×10−4	1.14629	1.065532018	1.233169628	6.46×10−3	1.117075	1.031523289	1.209722556

[i] HR, hazard ratio; HR (lower 0.95), hazard ratio (lower 95% CI); HR (upper 0.95), hazard ratio (upper 95% CI); T, tumor stage; N, node stage; M, metastasis stage.

Analyses of PCGs co-expressed with lncRNAs DNAH17-AS1 and RP11-400N13.2

Analysis of the PCGs co-expressed with DNAH17-AS1 and RP11-400N13.2 was conducted using the cor.test function with thresholds of |r|>0.4 and P<0.001. The results revealed that 1,048 PCGs were co-expressed with DNAH17-AS1 (Fig. 4A). Due to a large number of PCGs in DNAH17-AS1, only the top 100 genes with a lower P-value were presented in Fig. 4A. A total of 126 PCGs co-expressed with RP11-400N13.2 (Fig. 4B). The top 10 significant PCGs that were identified to be co-expressed with the 2 lncRNAs are listed in Table VII.

Figure 4. Interactions between two long non-coding RNAs and co-expressed PCGs. (A) DNAH17-AS1 was co-expressed with 1,048 PCGs. (B) RP11-400N13.2 was co-expressed with 126 PCGs. PCGs, protein-coding genes.

Table VII. Co-expression analyses between DNAH17-AS1 and RP11-400N13.2 and the top 10 significant protein-coding genes.

Table VII.

Co-expression analyses between DNAH17-AS1 and RP11-400N13.2 and the top 10 significant protein-coding genes.

A, Genes co-expressed with DNAH17-AS1
Co-expressed gene	Ensembl_Gene_ID	ra	P-value
DNAH17	ENSG00000187775	0.656	2.73×10−65
SSPO	ENSG00000197558	0.564	4.89×10−45
TPTE	ENSG00000274391	0.505	4.31×10−35
DPPA2	ENSG00000163530	0.473	1.96×10−30
GPR179	ENSG00000277399	0.473	2.22×10−30
RP11-505K9.4	ENSG00000260300	0.454	8.07×10−28
CFAP74	ENSG00000142609	0.453	1.15×10−27
POLG2	ENSG00000256525	0.451	1.99×10−27
KIF6	ENSG00000164627	0.449	3.41×10−27
STKLD1	ENSG00000198870	0.445	9.44×10−27
B, Genes co-expressed with RP11-400N13.2
Co-expressed gene	Ensembl_Gene_ID	ra	P-value
RP11-371E8.4	ENSG00000259066	0.439	5.20×10−26
RP11-507M3.1	ENSG00000276087	0.438	8.64×10−26
HIST3H3	ENSG00000168148	0.428	1.26×10−24
RP4-809F18.1	ENSG00000255595	0.428	1.34×10−24
OPRPN	ENSG00000171199	0.426	2.51×10−24
RP11-385D13.1	ENSG00000251537	0.423	4.79×10−24
OR52B2	ENSG00000255307	0.422	5.87×10−24
OR52B6	ENSG00000187747	0.422	7.24×10−24
OR2AG2	ENSG00000188124	0.401	1.44×10−21
BDNF	ENSG00000176697	0.397	3.93×10−21

a Pearson's correlation coefficient.

GO and KEGG enrichment analyses of the PCGs co-expressed with DNAH17-AS1 and RP11-400N13.2

To further investigate the potential roles of the two independent prognostic lncRNAs identified in the present study, functional enrichment analyses for their co-expressed PCGs were performed using the clusterProfiler R package. The results indicated that the PCGs co-expressed with DNAH17-AS1 were mainly enriched in ‘G-protein coupled receptor signaling pathway’, ‘detection of chemical stimulus involved in sensory perception of smell’, ‘integral component of membrane’, ‘integral component of plasma membrane’, ‘G-protein coupled receptor activity’ and ‘olfactory receptor activity’. Collectively, these PCGs were associated with G-protein coupling and cell membrane function (Fig. 5A). Additionally, the PCGs co-expressed with RP11-400N13.2 were mainly enriched in ‘G-protein coupled receptor signaling pathway’, ‘G-protein coupled receptor activity’, ‘spermatogenesis’, ‘negative regulation of endopeptidase activity’ and ‘endopeptidase inhibitor activity’, which are involved in G-protein coupling and endopeptidase function (Fig. 5B). Functional enrichment analysis revealed a high level of involvement of the associated PCGs inG-protein coupling, which suggested a crucial biological function of DNAH17-AS1 and RP11-400N13.2. The detailed information of the genes with G-protein-associated functions co-expressed with DNAH17-AS1 and RP11-400N13.2 is presented in Table SII. A total of 3 of these genes, 5′-hydroxytryptamine receptor 6, melanocortin 5 receptor and prokineticin receptor 2, were significantly associated with OS (P<0.05; Fig. S1).

Figure 5. GO enrichment analysis maps of co-expressed PCGs associated with certain long non-coding RNAs. (A) The most enriched GO terms of PCGs co-expressed with DNAH17-AS1. (B) The most enriched GO terms of PCGs co-expressed with RP11-400N13.2. The colors of the columns represent the different types of terms. GO, Gene Ontology; PCGs, protein-coding genes; BP, biological process; CC, cellular component; MF, molecular function.

KEGG pathway enrichment analysis of the PCGs co-expressed with the two independent prognostic lncRNAs was performed using clusterProfiler package in R with a threshold of P<0.05. The results revealed that the PCGs co-expressed with DNAH17-AS1 were involved in seven pathways, including ‘olfactory transduction’, ‘neuroactive ligand-receptor interaction’, ‘phototransduction’, ‘nicotine addiction’, ‘cocaine addiction’, ‘collecting duct acid secretion’ and ‘signaling pathways regulating pluripotency of stem cells’ (Fig. 6). This result provided novel insights into the potential associations between these pathways and CRC, which warrant further investigation. Of note, P>0.05 was reported for the enriched pathways of the PCGs co-expressed with RP11-400N13.2.

Figure 6. KEGG enrichment analysis of PCGs co-expressed with DNAH17-AS1. The size of the dots indicates the number of enriched PCGs; the color of the dots represents the degree of significance based on the P-value. KEGG, Kyoto Encyclopedia of Genes and Genomes; PCGs, protein-coding genes.

Discussion

In the present study, in silico analysis revealed 1,180 significantly differentially expressed lncRNAs that were associated with colorectal cancer, of which 56 and 7 genes were significantly associated with OS and TNM stage, respectively. Subsequent univariate and multivariate Cox regression analyses indicated that 2 of the 7 lncRNAs, DNAH17-AS1 and RP11-400N13.2, may be independent prognostic lncRNAs for the OS of patients with colorectal cancer.

To the best of our knowledge, lncRNAs DNAH17-AS1 and RP11-400N13.2 have not been previously associated with colon cancer; however, a missense variant p.R3953Y of DNAH17, the related protein of DNAH17-AS1, was reported in undifferentiated embryonal sarcoma of the liver in a child (24). Additionally, p.R3953 of DNAH17 exhibited a high level of conservation among a variety of species, suggesting that this allele may be an important locus associated with protein function (24). A recent study revealed the mutational profile and a distinct mutation signature of T:A>A:T transversion in early-stage hepatocellular carcinoma (HCC) with hepatitis B virus (HBV) infection; thus, as a key gene of the mutational profile, DNAH17 was proposed to serve an important role in the HBV-mediated transformation of liver cells (25). Additionally, the hypomethylation status of DNAH17 has been reported in HCC, which is associated with several clinical characteristics and may serve as a potential biomarker of tumor thrombosis in patients with HCC (26). In the present study, the lncRNA expression level of DNAH17-AS1 in CRC samples was analyzed and compared with that in normal samples; however, the expression level and the methylation status of DNAH17 were not analyzed. Although the expression level of DNAH17, as well as its methylation status in CRC samples, may be informative to determine the role of DNAH17 in CRC, this was beyond the scope of the present study. Therefore, relevant studies will be performed in the future.

A limited number of studies have investigated RP11-400N13.2; however, other RP11 family members have been frequently reported to be dysregulated in CRC. RP11-708H21.4, an RP11 family lncRNA located in the 17q21 gene desert region, was proposed to serve a suppressive role in the tumorigenesis of colorectal cancer and act as a novel powerful diagnostic biomarker, as well as a therapeutic target for the treatment of CRC (27). The expression levels of RP11-462C24.1, another member of the RP11 family, were determined to be significantly correlated with distant metastasis in patients with CRC, and may serve as a potential prognostic marker for such patients (28). Additionally, the dysregulation of RP11 family members has been reported to be involved in other types of cancer. For instance, a recent study revealed that overexpression of lncRNA RP11-190D6.2 inhibited the proliferation, migration and invasion of epithelial ovarian cancer (EOC) cells and may be considered a novel biomarker and therapeutic target for EOC (29). Furthermore, lncRNA RP11-436H11.5 was identified to function as a competing endogenous RNA to promote the proliferation and invasion of renal cell carcinoma (RCC) cells, which suggests that RP11-436H11.5 may be a potential therapeutic target to suppress RCC tumorigenesis (30). Collectively, the RP11 family of lncRNAs serve important roles in carcinogenesis and may be used as potential diagnostic and prognostic biomarkers for various types of cancer.

Following the identification of two independent prognostic lncRNAs in colorectal cancer, the co-expressed PCGs were analyzed, and stepwise GO and KEGG enrichment analyses were conducted to determine the potential biological functions of these lncRNAs associated with CRC and the signaling pathways involved. The results of the functional enrichment analysis of DNAH17-AS1 and RP11-400N13.2 differed; however, these lncRNAs were determined to possess similar G-protein coupling-associated functions. G-protein coupled receptors have been previously reported to be associated with CRC tumorigenesis (31–34). For example, the G-protein coupled receptor GPR55 may promote tumor progression by acting as an pro-oncogenic factor in CRC (31). In addition, GPR55 has been proposed to be involved in the migration of CRC cells and may serve as a potential target for the prevention of metastasis (32). On the contrary, orexin receptor type 1 and cholecystokinin A receptor, which belong to family A of the G-protein coupled receptors, serve opposing roles in the regulation of HT-29 CRC cell migration, but have also been reported to be involved in the pathogenesis of CRC metastasis (33). Furthermore, a recent study revealed that GPR109A, a G-protein coupled receptor for short-chain fatty acids, was silenced in CRC cells (34). In addition, the host immune system may employ interferon γ to counteract methylation-mediated silencing of GPR109A as a mechanism to suppress tumor development (34). Therefore, G-protein coupled receptors maybe associated with the carcinogenesis and metastasis of CRC; the roles of DNAH17-AS1 and RP11-400N13.2 in CRC, which may be mediated by these receptors, require further investigation.

In the present study, DNAH17-AS1 and RP11-400N13.2 were identified as potential independent prognostic lncRNAs for OS in patients with CRC. Further bioinformatics analyses revealed that these 2 lncRNAs may serve a pro-oncogenic role in CRC via G-protein coupling-related functions. Therefore, DNAH17-AS1 and RP11-400N13.2 may serve as prognostic biomarkers for CRC in the future. The detailed methodology of the present study is presented in Fig. S2.

Supplementary Material

Supporting Data

Supporting Data

Supporting Data

Acknowledgements

Not applicable.

Funding

This study was funded by the National Natural Science Foundation of China (grant no. 81572416), the National Key Technologies R&D Program of China (grant no. 2016YFC1303200), and the Tianjin Medical University Cancer Institute and Hospital Cancer Translational Medicine Seed Funds (grant no. 1701-1).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

LL designed and supervised the study and finalized the manuscript. WZ and BP made substantial contributions to the study design, performed the bioinformatics analysis and drafted the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Glossary

Abbreviations

Abbreviations:

References