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Abstract

To evaluate the diagnostic efficacy and prognostic value of serum long non-coding RNA (lncRNA) HIF 1alpha-antisense RNA 1 (HIF1A-AS1) in patients with colorectal carcinoma (CRC). We obtained serum samples from 151 CRC patients and 160 health controls. Serum level of HIF1A-AS1 was detected via real-time PCR (RT-PCR). Receiver operating characteristics (ROC) curve analysis was conducted to determine the diagnostic value of HIF1A-AS1. Then HIF1A-AS1 in CRC was divided into high- and low-expression groups, and the associations of the HIF1A-AS1 serum level with clinicopathological features and prognosis were analyzed. Serum level of HIF1A-AS1 was significantly increased from CRC patients as compared to those of health controls ( $P<$ 0.05). ROC curve analysis revealed a relative high diagnostic performance of HIF1A-AS1 to distinguish CRC from health controls, with the area under the curves (AUC) of 0.960 (95% CI: 0.940 $\sim$ 0.980; $P<$ 0.001). Kaplan-Meier analysis showed that differentiation degree, tumor size, TNM stage, T stage, N stage, M stage and serum level of HIF1A-AS1 were all linked to CRC prognosis (All $P<$ 0.05). Compared to CRC patients with low HIF1A-AS1 expression, high expression of patients were associated with a shorter 5-year-survival rate ( $P<$ 0.001). Multivariate Cox regression analysis revealed that lower differentiation degree, tumor $>$ 5 cm and higher expression of HIF1A-AS1 were independent risk factors affecting the survival rate of patients with CRC ( $P<$ 0.05). Our results illustrated that elevated serum HIF1AAS1 could be clinically functioned as a potential biomarker for CRC diagnoses and prognosis.

Keywords

Long chain noncoding RNA HIF1A-AS colorectal carcinoma diagnosis prognosis clinicopathological features

1. Introduction

As the one of most common malignancies, colorectal cancer (CRC) ranks on the 3 ${}^{\rm rd}$ or 4 ${}^{\rm th}$ with 1.3 million newly diagnosed cases and 0.7 million cancer-related deaths annually [1]. Although we have made some progress in the early diagnosis and treatment of CRC in recent years, an annually increasing is still observed in the incidence and mortality of CRC [2]. As is well known, CRC is multi-stage and long-term formed complex lesions related to a wide range of genetic changes [3]. Thus, CRC investigations, which were mainly focused on identifying effective tumor-associated molecular biomarkers, could clinically illustrate characteristics and significance of CRC [4].

Long non-coding RNA (lncRNA) is a class of non-coding RNA with over 200 nucleotides in length, which lacks the function of protein coding [5]. Mounting researches reported that lncRNAs acted as important biomarkers to play crucial roles in the diagnosis, treatment and prognosis of CRC [6, 7]. For example, lncRNA H19 inhibits $\beta$ -catenin expression and promotes CRC cell proliferation via binding to miR-200a [8]. While, TUSC7, a potential tumor suppressor gene, could suppress CRC cell proliferation by absorbing miR-211-3p [9]. What’s more, HNF1A-antisense RNA 1 (HNF1A-AS1), as a newly found lncRNA, is located on chromosome 12, with 2455 nucleotides in length [10]. HIF1A-AS1 has been investigated by Wang et al. to be up-regulated in aortic media, positively interacted with BRG1 to participant in the regulation of cell proliferation and apoptosis [11]. Similarly, Wang et al. also revealed that clopidogrel could inhibit cell apoptosis and promotes palmitic acid induced proliferation of human vascular endothelial cells through suppressing HIF1A-AS1 [12]. Furthermore, HNF1A-AS1 has been demonstrated to involve in various tumors progression as suggested by the previous published documents, such as oesophageal adenocarcinoma [13], lung [10, 14], gastric [15] and hepatocellular carcinomas [16]. However, little is known regarding the role and mechanism of HNF1A-AS1 in CRC so far. Therefore, this study enrolled 151 CRC patients and 160 healthy controls to detect the serum HIF1A-AS1 level, aiming to evaluate its diagnostic efficacy and prognostic value in CRC.

2. Material and methods

2.1 Ethics statement

The present study was approved by the the First College of Clinical Medical Science, China Three Gorges University, Yichang Central People’s Hospital, which was in rigorous agreement with the Helsinki declaration [17]. All participated subjects were provided the purpose of the study and signed informed consent.

2.2 Subjects

A total of 151 patients, who underwent tumor resection and confirmed by histopathological evaluation as CRC from February 2010 to February 2012 in our hospital, were included in our study as case group. The study consisted of 89 males and 62 females with the mean age of 58.59 $\pm$ 20.64 years. In this study, 78 patients were less than 60 years, and 73 patients were over 60 years old. Among these 151 patients, 81 cases were with rectal cancer and 70 cases were with colon cancer. Based on the American Joint Committee on Cancer (AJCC) [18] for TNM staging criteria, 21 cases were in stage I, 56 cases in stage II, 45 cases in stage III, and 29 cases in stage IV; besides, T1 had 18 cases, T2 had 20 cases, T3 had 54 cases, and T4 had 59 cases; N0 had 77 cases, N1 had 32 cases, N2 had 42 cases; M0 had 122 cases, M1 had 29 cases. According to the histopathological grading of WHO, 28 patients were poorly differentiated, while 123 patients were well-and-moderate differentiated. Inclusion criteria: all patients were primary tumors who were pathologically diagnosed as CRC; who had adequate imaging and clinical examination for diagnosis; who had complete clinical and pathology data; who received at least one time follow-up or check; who did not receive any radiotherapy, chemotherapy or targeted therapy. Exclusion criteria: the patients received chemotherapy, radiation therapy and biological therapy; or in unknown conditions; or combined with hepatitis and cirrhosis of the liver, intestinal obstruction, peritonitis, acute pancreatitis, renal failure and other serious diseases or dysfunction, or even other tumors in patients with CRC; or did not cooperate with the investigation. Another 160 healthy people, including 93 males and 67 females (mean age: 56.21 $\pm$ 20.08 years) were age- and gender-matched with CRC patients as control group (All $P>$ 0.05).

2.3 Sample collections and RNA extraction

A total of 3 $\sim$ 5 ml of fasting peripheral venous blood was collected and immediately anticoagulated with EDTANa2 in 5 ml tubes, and then stored at $-$ 20 ${}^{\circ}$ C refrigeration. After blood samples were treated, the total RNA was extracted using the kit purchased from Qiagen (GmbH, Hilden, Germany), while the reverse transcription kit was purchased from Hangzhou Bioer Technology Co. Ltd (Zhejiang, China). All the operations were in line with the kit instructions. The ultraviolet spectrophotometer was conducted to measure the OD260/280 value of the extracted RNA samples, and the extracted RNA was stored at $-$ 80 ${}^{\circ}$ C.

2.4 Real time-polymerase chain reaction (RT-PCR)

According to the gene sequence published in Genbank database and miR BASE database, using Primer 5.0 primer design software, synthesized through Shanghai Biotechnology Company, the primer sequences used in our study were shown in Table 1. By using PrimeScript RT-polymerase (Takara, Dalian, China), the reaction volume (20 $\mu$ l), with 2 $\mu$ g of total RNA containing, was reversely transcribed to cDNA. The first-strand cDNAs served as the template for the regular polymerase chain reaction (PCR) by a DNA Engine (ABI 9700, Foster City, CA, USA). Cycling parameters were: 30 s polymerase activation at 95 ${}^{\circ}$ C, then 40 cycles of 5 s at 95 ${}^{\circ}$ C, and 60 ${}^{\circ}$ C for 30 s. GAPDH was functioned as the reference gene. The target expression was calculated by comparing the Ct value of the target gene with the Ct value of GAPDH as follows: $\Delta$ Ct ${}_{\text{(target)}}=$ Ct ${}_{\text{(target)}}$ $-$ Ct ${}_{\text{(GAPDH)}}$ , $\Delta\Delta$ Ct $=\Delta$ Ct ${}_{\text{(Case group)}}-\Delta$ Ct ${}_{\text{(Control group)}}$ , and the relative expression of HIF1A-AS1 was measured by 2 ${}^{\rm-\Delta\Delta Ct}$ method.

Table 1
Primer sequences for RT-PCR

Gene	Primer sequences (5 ${}^{\prime}$ -3 ${}^{\prime}$ )
HIF1A-AS1
Forward	5 ${}^{\prime}$ -GTCACGATTCGGTACAC-3 ${}^{\prime}$
Reverse	5 ${}^{\prime}$ -CGCGCAGGTCATAAGAGTTGTG-3 ${}^{\prime}$
GAPDH
Forward	5 ${}^{\prime}$ -ACAGGGGAGGTGATAGCATT-3 ${}^{\prime}$
Reverse	5 ${}^{\prime}$ -GACCAAAAGCCTTCATACATCTC-3 ${}^{\prime}$

2.5 Follow up

All follow-up data has been collected through the means of telephone or outpatient service to revisit for the patients, as well as their family members. The deadline of follow-up was May 2016, and a 5-year overall survival rate was calculated. The overall survival period referred to the length of time from the date of diagnose under surgery to death or to the time of the last follow-up. Kaplan-Meier (K-M) survival curves were plotted based on follow-up results to compare overall survival rate.

Figure 1.

Expression level of serum HIF1A-AS1 in patients with CRC and its diagnostic efficacy. Note: A: The expression levels of serum HIF1A-AS1 in CRC patients and health controls were detected by RT-PCR; B: The diagnostic efficacy of HIF1A-AS1 for CRC was assessed by ROC curve analysis; AUC: Area under the curve.

Figure 2.

The expression levels of serum HIF1A-AS1 in CRC patients with different clinicopathological characteristics. Note: A: Histology; B: Tumor size (cm); C: TNM stage; D: T stage; E: N stage; F: M stage; different letters indicated statistically significant differences, $P<$ 0.05; the same letters indicated no significant difference, $P>$ 0.05.

Figure 3.

The Kaplan-Meier curves of HIF1A-AS1 expression, and its clinicopathological features and the survival status of patients with CRC. Note: A: Histology; B: Tumor size (cm); C: TNM stage; D: T stage; E: N stage; F: M stage; G: HIF1A-AS1 expression.

Table 2

Correlation between HIF1A-AS1 serum levels and clinicopathological factors in 151 patients with CRC

Variables	$N$	Low HIF1A-AS1 group	High HIF1A-AS1 group	$Z/c^{2}$	$P$
		( $<$ 2.175, $n=$ 75)	( $\geqslant$ 2.175, $n=$ 76)
Age (years)
$\leqslant$ 60	78	34	44
$>$ 60	73	41	32	2.385	0.123
Gender
Male	89	45	44
Female	62	30	32	0.069	0.793
Tumor location
Colon	81	35	46
Rectum	70	40	30	2.916	0.088
Histology
Moderate/well-differentiated	123	67	56
Poor-differentiated	28	8	20	6.12	0.013
Tumor size (cm)
$\leqslant$ 5	100	58	42
$>$ 5	51	17	34	8.22	0.004
T stage
T1	18	17	1
T2	20	14	6
T3	54	21	33
T4	59	23	36	3.378	$<$ 0.001
N stage
N0	77	58	19
N1	32	10	22
N2	42	7	35	6.468	$<$ 0.001
M stage
M0	122	70	52
M1	29	5	24	15.1	$<$ 0.001
TNM stage
I	21	18	3
II	56	40	16
III	45	12	33
IV	29	5	24	6.377	$<$ 0.001

Table 3

Multivariate analyses of prognostic parameters in 151 patients with CRC by Cox regression analysis

	B	SE	Wald	df	$P$	HR	95%CI
TNM stage			12.87	3	0.005
II vs. I	0.115	0.928	0.015	1	0.901	1.122	0.182 $\sim$ 6.913
III vs. I	$-$ 1.114	0.938	1.411	1	0.235	0.328	0.052 $\sim$ 2.063
IV vs. I	0.035	1.007	0.001	1	0.972	1.035	0.144 $\sim$ 7.446
T stage			1.476	3	0.688
T (T2 vs. T1)	$-$ 0.589	0.803	0.538	1	0.463	0.555	0.115 $\sim$ 2.677
T (T3 vs. T1)	0.122	0.746	0.027	1	0.870	1.129	0.262 $\sim$ 4.874
T (T4 vs. T1)	0.251	0.779	0.104	1	0.747	1.285	0.28 $\sim$ 5.912
N stage			0.692	1 ${}^{\rm a}$	0.406
N1 vs. N0	$-$ 0.297	0.357	0.692	1	0.406	0.743	0.369 $\sim$ 1.495
M stage (M1 vs. M0)				0 ${}^{\rm a}$
Histology (poor vs. moderate-well)	0.909	0.395	5.298	1	0.021	2.481	1.144 $\sim$ 5.379
Tumor size ( $>$ 5 cm vs. $\leqslant$ 5 cm)	1.258	0.305	16.998	1	$<$ 0.001	3.518	1.935 $\sim$ 6.399
HIF1A-AS1 expression	2.505	0.44	32.429	1	$<$ 0.001	12.247	5.171 $\sim$ 29.008

Note: a: Constant or Linearly Dependent Covariates N(2) $=$ TNM(2) $+$ TNM(3) $-$ N(1); M $=$ TNM(3).

2.6 Statistical analysis

All statistical data were analyzed by SPSS version 20.0 software (SPSS, Inc., Chicago, IL, USA). The quantitative data are expressed as mean $\pm$ standard deviation. Differences between the two groups were compared using an independent sample $t$ -test for quantitative data with a normal distribution. The Fisher’s exact test or $\chi^{2}$ test was performed as appropriate for qualitative data to analyze the relationship between HIF1A-AS1 and clinicopathological factors. The diagnostic performance of serum HIF1A-AS1 was evaluated by receiver operating characteristic (ROC) curve analysis. Kaplan-Meier method and Cox proportional hazards model were used in univariate and multivariate analysis respectively. A value of $P<$ 0.05 was indicated statistically significant.

3. Results

3.1 Expression of serum HIF1A-AS1 in CRC patients and its diagnostic efficacy

The relative serum level of HIF1A-AS1 in CRC patients was higher than those in control group (2.22 $\pm$ 0.56 vs. 1.07 $\pm$ 0.38, $t=$ 21.30, $P<$ 0.001, Fig. 1A) by using RT-PCR. ROC curve analysis showed that (Fig. 1B) serum HIF1A-AS1 level had an AUC value of 0.960 (95% confidence interval: 0.940 $\sim$ 0.980, $P<$ 0.001), with 86.8% sensitivity and 92.5% specificity respectively, and the diagnostic threshold value of 1.643, indicating that HIF1A-AS1 could distinguish patients with CRC from health controls.

3.2 Association of serum HIF1A-AS1 level with clinicopathological characteristics in CRC patients

To explore the associations between the serum HIF1A-AS1 level with clinicopathological features, the 151 CRC patients were divided into two groups by the median value (Median $=$ 2.175) of relative HIF1A-AS1 serum level: a high expression group ( $\geqslant$ 2.175, $n=$ 76) and a low expression group ( $<$ 2.175, $n=$ 75). As shown in Table 2, the serum HIF1A-AS1 level was not associated with patient age ( $P=$ 0.123), gender ( $P=$ 0.793) or tumor location ( $P=$ 0.088); but strongly correlated with differentiation degree ( $P=$ 0.013), tumor size ( $P=$ 0.004), T stage, N stage and M stage, as well as TNM stage (All $P<$ 0.001), illustrated in Fig. 2.

3.3 Association of serum HIF1A-AS1 level with prognostic value in CRC patients

All patients were followed up for 5 years, and the Kaplan-Meier analysis showed that the degree of differentiation, tumor size, TNM stage, T stage, N stage and M stage were related to prognosis of patients with CRC (All $P<$ 0.05, Fig. 3A–F). Besides, the 5-year-survival rate of CRC patients in high expression group was 32.89% (25/76), but was 76.00% (57/75) in low expression group; as compared to patients with low HIF1A-AS1 expression, the 5-year-survival rate of CRC patients with high HIF1A-AS1 expression was obviously reduced ( $\chi^{2}=$ 34.143, $P<$ 0.001, Fig. 3G). In addition, multivariate Cox regression analysis revealed degree of differentiation, tumor size and serum HIF1A-AS1 level to be independent prognostic factor for overall survival of patients with CRC survival rate (All $P<$ 0.05, Table 3).

4. Discussion

LncRNA is expected to be a novel tumor biomarker for clinical diagnosis and prognosis evaluation, since it is crucial in cancer development [19, 20, 21].

We firstly found that the expression of HIF1A-AS1 in serum was evidently up-regulated in CRC patients in the current investigation. To our knowledge, blood test has been widely used in early screening and diagnosis of diseases due to its advantages of simplicity, rapidness and non-invasion [22]. More importantly, an increasing number of lncRNAs such as MEG3, SNHG16, MALAT1 and PCAT1, were viable and detectable in serum, which could be employed as monitoring tools for cancer [23, 24]. There was a possibility that the circulating RNA in outer chromosome protected RNA degradation from RNase, and thereby lncRNA can be stably expressed in peripheral blood [25]. For instance, LINC00152, another typical lncRNA, was a new biomarker for the diagnosis of gastric cancer since it is stably expressed in plasma, revealing by Li and his team [26]. Hence, we conducted RT-PCR to determine the expression of HIF1A-AS in serum of CRC patients, and our results showed HIF1A-AS was highly expressed in contrast to health controls. Coincidently, as shown by Tong, HNF1A-AS1 expression was obviously increased in patients with esophageal squamous cell carcinoma (ESCC), both in tissue and serum according to the results of qPCR. Besides, the qPCR products were further conformed by raditional Sanger-based method, to ensure whether lncRNAs could exist in plasma, and as a consequence, HNF1A-AS1 enters the circulation and its different expressions in plasma exerted a diagnostic function for ESCC [27]. Meanwhile, in non-small-cell lung cancer, Tantai et al. obtained the consistent results in cancerous tissue, as well as in serum of patients [14]. But interestingly, a contrary conclusion was found in gastric cancer cell lines, tissues and serum by Gao’s team as well as Dang’s team [4, 15]. Although the specific mechanism is not clear, the possible reason is due to the relative complexity of cancer, and the same lncRNA might be presented in differential expressions, or interact with other genes, in different types of tumors [4]. Additionally, we performed ROC curves to evaluate the diagnostic value of HIF1A-AS1 in serum for CRC, and identified that the AUC was 0.960 in CRC with 86.8% sensitivity and 92.5% specificity, further indicating the serum HIF1A-AS1 in CRC has a relative high diagnostic efficacy, and consequently playing a potential diagnostic role in early screening of CRC from healthy individuals.

Another important result was that the expression of HIF1A-AS in serum has potential prognostic values in CRC, which was associated with the differentiation degree of CRC, tumor size, TNM stage, T stage, N stage and M stage, to be an independent prognostic risk factor influencing the survival rate of CRC patients as conformed by multivariate Cox analysis. Consistent with our study, a study documented by Wu and his group stating that the high expression of HIF1A-AS1 was positively linked to lung adenocarcinoma progression and lymph node metastasis, and the Kaplan-Meier results illustrated that patients with high expression of HIF1A-AS1 had a unfavorable prognosis, because HIF1A-AS1 could promote the cell proliferation and metastasis of lung cancer [10]. In hepatocellular carcinoma, HNF1A-AS1 demonstrated to serves as oncogene and autophagy promoter to inhibit the expressions of hsa-miR-30b-5p and Bcl-2, then affect the growth and apoptosis of hepatoma cells, which was correlated with the number of lesions, differentiation and TNM staging [16]. Therefore, it suggested that the serum levels of HIF1A-AS1 are of clinical significance to assess the prognosis and survival of patients with CRC. Nevertheless, there were also some limitations in this study. Hence, the large sample size and more abundant clinical pathological characteristics should be observed in our future studies, and vitro experiments were needed to further explore the effects of HIF1A-AS1 on CRC and its possible mechanism.

In summary, this study demonstrated an enhanced serum HIF1A-AS1 level in CRC, which could serve as a useful diagnostic and independent prognostic biomarker for CRC, associated with low differentiation of CRC, large tumor size, high TNM stage, high T stage, as well as lymph node metastasis and distant metastasis.

Conflict of interest

There is no conflict of interests regarding the publication of this paper.

Footnotes

Acknowledgments

The authors want to thank all the people for their help in the paper editing.

References

Zhou

Zhang

Lai

Diao

Dang

and Song

, Relationships between p14ARF gene methylation and clinicopathological features of colorectal cancer: A meta-analysis, PLoS One 11 (2016), e0152050.

Zhou

Fang

X.Q.

Zhu

S.W.

and Xiong

M.M.

, Increased long noncoding RNA SNHG20 predicts poor prognosis in colorectal cancer, BMC Cancer 16 (2016), 655.

Roy

and Majumdar

A.P.

, Cancer stem cells in colorectal cancer: Genetic and epigenetic changes, J Stem Cell Res Ther Suppl 7 (2012).

Gao

Cao

and Mu

, Long non-coding RNA UCA1 may be a novel diagnostic and predictive biomarker in plasma for early gastric cancer, Int J Clin Exp Pathol 8 (2015), 12936–12942.

Dempsey

J.L.

and Cui

J.Y.

, Long non-coding RNAs: A novel paradigm for toxicology, Toxicol Sci 155 (2017), 3–21.

Weng

Yang

Peng

Wang

and Li

, Noncoding RNAs in the development, diagnosis, and prognosis of colorectal cancer, Transl Res 181 (2017), 108–120.

Zhang

Han

Yin

Liu

Zhang

Lin

Mao

and Shen

, Long noncoding RNA BLACAT1 indicates a poor prognosis of colorectal cancer and affects cell proliferation by epigenetically silencing of p15, Cell Death Dis 8 (2017), e2665.

Yang

Ning

and Jin

, The lncRNA H19 promotes cell proliferation by competitively binding to miR-200a and derepressing beta-catenin expression in colorectal cancer, Biomed Res Int 2017 (2017), 2767484.

Zhang

and Zhao

, The novel long noncoding RNA TUSC7 inhibits proliferation by sponging MiR-211 in colorectal cancer, Cell Physiol Biochem 41 (2017), 635–644.

10.

Liu

Shi

Yao

Yang

and Song

, The long non-coding RNA HNF1A-AS1 regulates proliferation and metastasis in lung adenocarcinoma, Oncotarget 6 (2015), 9160–9172.

11.

Wang

Zhang

Yuan

Tan

Zhang

Xue

Yan

Han

and Xu

, BRG1 expression is increased in thoracic aortic aneurysms and regulates proliferation and apoptosis of vascular smooth muscle cells through the long non-coding RNA HIF1A-AS1 in vitro, Eur J Cardiothorac Surg 47 (2015), 439–446.

12.

Wang

Chen

Yang

Gong

Wang

and Zhao

, Clopidogrel reduces apoptosis and promotes proliferation of human vascular endothelial cells induced by palmitic acid via suppression of the long non-coding RNA HIF1A-AS1 in vitro, Mol Cell Biochem 404 (2015), 203–210.

13.

Yang

Song

J.H.

Cheng

Bhagat

Abraham

J.M.

Ibrahim

Ravich

Roland

B.C.

Khashab

Singh

V.K.

Shin

E.J.

Yang

Verma

A.K.

Meltzer

S.J.

and Mori

, Long non-coding RNA HNF1A-AS1 regulates proliferation and migration in oesophageal adenocarcinoma cells, Gut 63 (2014), 881–90.

14.

Tantai

Yang

and Geng

, Combined identification of long non-coding RNA XIST and HIF1A-AS1 in serum as an effective screening for non-small cell lung cancer, Int J Clin Exp Pathol 8 (2015), 7887–7895.

15.

Dang

Lan

Ouyang

Wang

Lin

Wang

and Huang

, Expression and clinical significance of long non-coding RNA HNF1A-AS1 in human gastric cancer, World J Surg Oncol 13 (2015), 302.

16.

Liu

Wei

Zhang

Bai

and Dong

, Long non-coding RNA HNF1A-AS1 functioned as an oncogene and autophagy promoter in hepatocellular carcinoma through sponging hsa-miR-30b-5p, Biochem Biophys Res Commun 473 (2016), 1268–1275.

17.

Human

, Declaration of helsinki, Lancet 353 (1999), 1888.

18.

Obrocea

F.L.

Sajin

Marinescu

E.C.

and Stoica

, Colorectal cancer and the 7th revision of the TNM staging system: Review of changes and suggestions for uniform pathologic reporting, Rom J Morphol Embryol 52 (2011), 537–544.

19.

Serghiou

Kyriakopoulou

and Ioannidis

J.P.

, Long noncoding RNAs as novel predictors of survival in human cancer: A systematic review and meta-analysis, Mol Cancer 15 (2016), 50.

20.

Yang

and Yuan

, LncRNA: A link between RNA and cancer, Biochim Biophys Acta 1839 (2014), 1097–1109.

21.

Silva

Bullock

and Calin

, The clinical relevance of long non-coding RNAs in cancer, Cancers (Basel) 7 (2015), 2169–2182.

22.

Pox

, Colon cancer screening: Which non-invasive filter tests? Dig Dis 29(Suppl 1) (2011), 56–59.

23.

Duan

Jiang

Wang

Yan

Xie

Yan

Wang

Zhang

Pan

Yang

and Wang

, Identification of a serum circulating lncRNA panel for the diagnosis and recurrence prediction of bladder cancer, Oncotarget 7 (2016), 78850–78858.

24.

Shen

Zhang

Guo

Shi

Cong

Wang

and Ju

, Upregulated lncRNA-PCAT1 is closely related to clinical diagnosis of multiple myeloma as a predictive biomarker in serum, Cancer Biomark (2017).

25.

Tsui

N.B.

E.K.

and Lo

Y.M.

, Stability of endogenous and added RNA in blood specimens, serum, and plasma, Clin Chem 48 (2002), 1647–1653.

26.

Shao

Zhang

Zheng

Miao

Qin

Wang

Xiao

and Guo

, Plasma long noncoding RNA protected by exosomes as a potential stable biomarker for gastric cancer, Tumour Biol 36 (2015), 2007–2012.

27.

Tong

Y.S.

Wang

X.W.

Zhou

X.L.

Liu

Z.H.

Yang

T.X.

Shi

W.H.

Xie

H.W.

Q.Q.

and Cao

X.F.

, Identification of the long non-coding RNA POU3F3 in plasma as a novel biomarker for diagnosis of esophageal squamous cell carcinoma, Mol Cancer 14 (2015), 3.

Elevated serum level of lncRNA-HIF1A-AS1 as a novel diagnostic predictor for worse prognosis in colorectal carcinoma

Abstract

Keywords

1. Introduction

2. Material and methods

2.1 Ethics statement

2.2 Subjects

2.3 Sample collections and RNA extraction

2.4 Real time-polymerase chain reaction (RT-PCR)

Table 1 Primer sequences for RT-PCR

3. Results

3.1 Expression of serum HIF1A-AS1 in CRC patients and its diagnostic efficacy

3.2 Association of serum HIF1A-AS1 level with clinicopathological characteristics in CRC patients

3.3 Association of serum HIF1A-AS1 level with prognostic value in CRC patients

4. Discussion

Conflict of interest

Footnotes

Acknowledgments

References

Table 1
Primer sequences for RT-PCR