Literature DB >> 31516583

Integrated bioinformatics analysis revealing independent prognostic long non-coding RNAs DNAH17-AS1 and RP11-400N13.2 and their potential oncogenic roles in colorectal cancer.

Wen Zhou1, Boyu Pan2,3, Liren Liu2,3.   

Abstract

The aberrant expression of long non-coding RNAs (lncRNAs) has been associated with a variety of malignancies, including colorectal cancer (CRC); however, the key lncRNAs associated with patient prognosis and their biological roles in CRC are yet to be determined. The aim of the present study was to determine the key lncRNAs associated with patient prognosis as well as their biological roles in CRC. Therefore, a dataset from The Cancer Genome Atlas containing the lncRNA expression data of 521 CRC and normal colorectal mucosal tissues, as well as the corresponding clinical data, were screened. A total of 1,180 significantly differentially expressed lncRNAs were associated with CRC as determined by t-tests in edgeR. Kaplan-Meier analysis revealed that 56 of the 1,180 lncRNAs were associated with overall survival (OS); 7 of the 56 lncRNAs were identified as key lncRNAs associated with the Tumor-Node-Metastasis stage of CRC by Kruskal-Wallis test. Subsequent univariate and multivariate Cox regression analyses of the 7 lncRNAs revealed 2 lncRNAs, DNAH17-AS1 and RP11-400N13.2, as potential independent prognostic factors for the OS of patients with CRC. Furthermore, the expression levelsof these 2 lncRNAs were significantly upregulated in CRC compared with those in normal tissues, which suggested that they may serve an oncogenic role in CRC. In addition, networks comprising the 2 lncRNAs and their respective co-expressed protein-coding genes (PCGs) were constructed using cor.test in R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of these PCGs were conducted; DNAH17-AS1- and RP11-400N13.2-associated PCGs were reported to be involved in G-protein coupling-related functions. Thus, these independent prognostic lncRNAs and their associated functions identified in the present study may provide novel insight into potential prognostic biomarkers and therapeutic targets for the treatment of CRC.

Entities:  

Keywords:  DNAH17-AS1; RP11-400N13.2; bioinformatics analysis; colorectal cancer; independent prognostic biomarker; long non-coding RNA; oncogenic

Year:  2019        PMID: 31516583      PMCID: PMC6732947          DOI: 10.3892/ol.2019.10730

Source DB:  PubMed          Journal:  Oncol Lett        ISSN: 1792-1074            Impact factor:   2.967


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.

lncRNAEnsembl_Gene_IDlogFCP-valueFDR
PVT1ENSG000002498592.581.70×10−674.23×10−65
CCAT1ENSG000002478444.471.68×10−592.51×10−57
BLACAT1ENSG000002814065.123.88×10−595.59×10−57
LINC02163ENSG000002510267.081.19×10−541.37×10−52
CRNDEENSG000002456944.581.30×10−521.31×10−50
MAFG-AS1ENSG000002656882.887.82×10−517.51×10−49
RP5-884M6.1ENSG000002287426.311.04×10−509.69×10−49
CASC19ENSG000002541664.513.30×10−503.02×10−48
RP5-1120P11.1ENSG000002376864.417.64×10−506.65×10−48
AC007128.1ENSG000002299704.482.64×10−482.17×10−46

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.

lncRNAEnsembl_Gene_IDlogFCP-valueFDR
XXbac-B476C20.9ENSG00000225335−2.722.14×10−1731.60×10−169
CDKN2B-AS1ENSG00000240498−5.219.05×10−1403.39×10−136
LINC01645ENSG00000224968−4.606.90×10−1271.72×10−123
PP7080ENSG00000188242−3.483.24×10−1246.07×10−121
XXyac-YM21GA2.7ENSG00000214888−5.697.06×10−1201.06×10−116
RP11-1090M7.1ENSG00000265489−4.481.49×10−1161.85×10−113
RP11-396O20.2ENSG00000254645−5.011.71×10−1141.83×10−111
AC007182.6ENSG00000224721−4.674.65×10−1084.35×10−105
AC106869.2ENSG00000226087−4.182.71×10−1052.25×10−102
LINC00682ENSG00000245870−4.551.18×10−968.82×10−94

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).
Table III.

lncRNAs significantly associated with OS.

lncRNAEnsembl_Gene_IDP-value
RP11-108K3.2ENSG000002593061.98646×10−5
RP11-815M8.1ENSG000002380422.78454×10−5
LINC01836ENSG000002675300.000256940
AC079612.1ENSG000001967580.000535749
LINC01354ENSG000002317680.000985613
RBAKDNENSG000002733130.001143877
RP11-400N13.2ENSG000002284370.002268513
RP1-142L7.9ENSG000002706610.003700521
AFAP1-AS1ENSG000002726200.004000305
LINC01655ENSG000002279250.004380952
RP11-10A14.5ENSG000002485380.004693149
RP11-384P7.7ENSG000002609470.004845978
RP11-434D9.2ENSG000002498940.005561553
RP11-742B18.1ENSG000002490010.007363036
CTC-327F10.4ENSG000002513200.008786437
AC064834.1ENSG000002240990.00890189
ARHGEF26-AS1ENSG000002430690.008966797
RP3-380B8.4ENSG000002330640.009485845
LINC01829ENSG000002367800.009974597
GAS1RRENSG000002262370.013908392
RP11-84A19.4ENSG000002699670.014180465
LINC02043ENSG000002322330.016339686
LINC00922ENSG000002617420.016854765
RP11-278L15.2ENSG000002438850.017325027
RP1-122P22.4ENSG000002686280.018507105
RP11-366L20.2ENSG000001973010.019632443
DUXAP8ENSG000002061950.020361403
CTB-181H17.1ENSG000002722190.020685373
MIR31HGENSG000001718890.021365649
AC012531.25ENSG000002605970.023942649
FOXD3-AS1ENSG000002307980.024144909
AC007128.1ENSG000002299700.027145232
DNAH17-AS1ENSG000002674320.02735923
LINC01833ENSG000002594390.027941465
RP11-429J17.5ENSG000002545480.028089082
LL22NC03-N14H11.1ENSG000002728720.031532618
RP1-79C4.4ENSG000002718110.031571197
CTB-186G2.4ENSG000002673750.031679272
RP11-114H23.2ENSG000002580880.033221364
LINC00484ENSG000002296940.035515205
RP1-29C18.10ENSG000002129390.035961207
AC073326.3ENSG000002285400.036298277
RP11-126H7.4ENSG000002040490.036449014
CTD-2619J13.13ENSG000002683070.037145687
LINC01748ENSG000002264760.038383393
RP11-532F6.3ENSG000002724630.042708274
RP11-728G15.1ENSG000002560080.043149989
LINC01060ENSG000002493780.045508319
KCNQ1OT1ENSG000002698210.045529181
LINC01996ENSG000002618630.046591159
ELFN1-AS1ENSG000002360810.046625182
HOTAIRENSG000002286300.047908786
LINC00461ENSG000002455260.04796558
CTD-2600O9.1ENSG000001871850.048650792
LEF1-AS1ENSG000002320210.049375626
FLJ16779ENSG000002756200.049920309

lncRNA, long non-coding RNA.

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.

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.
Table IV.

lncRNAs significantly associated with tumor clinical stage.

lncRNAEnsembl_Gene_IDP-value
FLJ16779ENSG000002756200.049920309
DNAH17-AS1ENSG000002674326.42×10−5
RP11-429J17.5ENSG000002545480.000628536
RP11-742B18.1ENSG000002490010.00141941
RP11-400N13.2ENSG000002284370.003179863
LL22NC03-N14H11.1ENSG000002728720.005376623
LINC01836ENSG000002675300.011461646
HOTAIRENSG000002286300.013000989

lncRNA, long non-coding RNA.

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.

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.

UnivariateMultivariate


CharacteristicP-valueHRHR (lower 0.95)HR (upper 0.95)P-valueHRHR (lower 0.95)HR (upper 0.95)
Age, years1.54×10−21.0247051.004670061.0451395278.62×10−51.0432931.0214527411.065600322
Sex8.11×10−11.0559930.6753209041.6512449465.15×10−10.8597530.5452339861.355701712
Stage4.32×10−102.2605381.7498176462.920321653.09×10−11.4817530.6937529643.164805106
T5.85×10−62.8421691.8090616844.4652575114.32×10−21.7537151.0172446013.023378521
M6.75×10−104.3482022.7264930716.9344969483.83×10−11.5847560.5625330314.464537953
N1.29×10−72.0140391.5530719572.6118243112.84×10−11.2815190.8137880462.01808327
DNAH17-AS11.17×10−356.080874.924770723638.62149371.61×10−229.593421.872773849467.6327355

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.

UnivariateMultivariate


CharacteristicP-valueHRHR (lower 0.95)HR (upper 0.95)P-valueHRHR (lower 0.95)HR (upper 0.95)
Age, years1.54×10−21.0247051.004670061.0451395273.70×10−41.037411.0166471951.058596272
Sex8.11×10−11.0559930.6753209041.6512449467.37×10−10.9254320.5884642441.455355124
Stage4.32×10−102.2605381.7498176462.920321652.61×10−11.546230.7225696963.308782317
T5.85×10−62.8421691.8090616844.4652575113.02×10−21.8423781.0599487913.202377507
M6.75×10−104.3482022.7264930716.9344969483.49×10−11.6287190.5867035774.521408077
N1.29×10−72.0140391.5530719572.6118243114.82×10−11.1815260.7416992341.882169148
RP11-400N13.22.49×10−41.146291.0655320181.2331696286.46×10−31.1170751.0315232891.209722556

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.

A, Genes co-expressed with DNAH17-AS1

Co-expressed geneEnsembl_Gene_IDr[a]P-value
DNAH17ENSG000001877750.6562.73×10−65
SSPOENSG000001975580.5644.89×10−45
TPTEENSG000002743910.5054.31×10−35
DPPA2ENSG000001635300.4731.96×10−30
GPR179ENSG000002773990.4732.22×10−30
RP11-505K9.4ENSG000002603000.4548.07×10−28
CFAP74ENSG000001426090.4531.15×10−27
POLG2ENSG000002565250.4511.99×10−27
KIF6ENSG000001646270.4493.41×10−27
STKLD1ENSG000001988700.4459.44×10−27

B, Genes co-expressed with RP11-400N13.2

Co-expressed geneEnsembl_Gene_IDr[a]P-value

RP11-371E8.4ENSG000002590660.4395.20×10−26
RP11-507M3.1ENSG000002760870.4388.64×10−26
HIST3H3ENSG000001681480.4281.26×10−24
RP4-809F18.1ENSG000002555950.4281.34×10−24
OPRPNENSG000001711990.4262.51×10−24
RP11-385D13.1ENSG000002515370.4234.79×10−24
OR52B2ENSG000002553070.4225.87×10−24
OR52B6ENSG000001877470.4227.24×10−24
OR2AG2ENSG000001881240.4011.44×10−21
BDNFENSG000001766970.3973.93×10−21

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.
  7 in total

1.  Upregulation of MiR-1274a is Correlated with Survival Outcomes and Promotes Cell Proliferation, Migration, and Invasion of Colon Cancer.

Authors:  Bin Ren; Binlin Yang; Ping Li; Liang Ge
Journal:  Onco Targets Ther       Date:  2020-07-17       Impact factor: 4.147

2.  A Novel Prognostic Model Based on Autophagy-Related Long Non-Coding RNAs for Clear Cell Renal Cell Carcinoma.

Authors:  Xinyuan Li; Haitao Yu; Zongjie Wei; Xin Gou; Simin Liang; Fu Liu
Journal:  Front Oncol       Date:  2021-08-03       Impact factor: 6.244

3.  Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer.

Authors:  Meihong Gao; Yang Guo; Yifu Xiao; Xuequn Shang
Journal:  World J Surg Oncol       Date:  2021-04-09       Impact factor: 2.754

4.  Risk SNP-induced lncRNA-SLCC1 drives colorectal cancer through activating glycolysis signaling.

Authors:  Tingting Yan; Chaoqin Shen; Penglei Jiang; Chenyang Yu; Fangfang Guo; Xianglong Tian; Xiaoqiang Zhu; Shiyuan Lu; Bingshe Han; Ming Zhong; Jinxian Chen; Qiang Liu; Yingxuan Chen; Junfang Zhang; Jie Hong; Haoyan Chen; Jing-Yuan Fang
Journal:  Signal Transduct Target Ther       Date:  2021-02-19

5.  ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization.

Authors:  Meihong Gao; Shuhui Liu; Yang Qi; Xinpeng Guo; Xuequn Shang
Journal:  Front Genet       Date:  2022-01-10       Impact factor: 4.599

Review 6.  Chemical Approaches To Analyzing RNA Structure Transcriptome-Wide.

Authors:  Whitney E England; Chely M Garfio; Robert C Spitale
Journal:  Chembiochem       Date:  2021-02-09       Impact factor: 3.164

7.  Construction of ceRNA Coexpression Network and Screening of Molecular Targets in Colorectal Cancer.

Authors:  Zhao Hui; Wang Zhanwei; Yang Xi; Liu Jin; Zhuang Jing; Han Shuwen
Journal:  Dis Markers       Date:  2020-04-21       Impact factor: 3.434

  7 in total

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