lncRNA VLDLR-AS1 Gene Expression in Colorectal Cancer in Patients from East Azerbaijan Province, Iran

authors:

avatar Amin Moqadami ORCID 1 , avatar Alireza Ahmadi ORCID 1 , avatar Mohammad Khalaj-Kondori ORCID 1 , *

Department of Animal Biology, Faculty of Natural Sciences, University of Tabriz, Tabriz, Iran

how to cite: Moqadami A, Ahmadi A, Khalaj-Kondori M. lncRNA VLDLR-AS1 Gene Expression in Colorectal Cancer in Patients from East Azerbaijan Province, Iran. Jentashapir J Cell Mol Biol. 2023;14(4):e141522. https://doi.org/10.5812/jjcmb-141522.

Abstract

Background:

Colorectal cancer (CRC) is the third most common cancer that frequently spreads to other parts of the body, with a low chance of recovery and a high mortality rate. Long non-coding RNAs are considered significant prognostic and diagnostic indicators because they are dysregulated in various cancers and have distinctive expression patterns and high tissue- and cell-specificity. VLDLR-AS1 lncRNA deregulation has been associated with several malignancies.

Objectives:

This study aimed to evaluate the expression levels of VLDLR-AS1 in CRC. It was the first time this assessment was conducted.

Methods:

We studied 188 samples, including 94 tumor samples and 94 paired adjacent non-tumor tissues. Total RNA was extracted, and its quantity and purity were assessed. TaKaRa PrimeScript 1st Strand cDNA Synthesis Kit (Kusatsu, Japan) was used for the reaction. The StepOnePlus Real-Time PCR System (Applied Biosystems) was set up to assess the relative expression of VLDLR-AS1.

Results:

According to the qRT-PCR data, the VLDLR-AS1 expression levels in CRC tissues were significantly lower than in tumor margins (P < 0.0001). In addition, receiver operating characteristic curve analysis demonstrated that VLDLR-AS1 expression can discriminate between tumor and non-tumor samples with the sensitivity and specificity of 72.34% and 51.06%, respectively (P = 0.03, AUC = 0.6274). However, no significant association was found between the expression levels of VLDLR-AS1 and clinicopathological features in CRC patients.

Conclusions:

The results of this study indicated that VLDLR-AS1 lncRNA is significantly downregulated in the tumor tissues of CRC patients compared to healthy tumor margin tissues. This evidence shows the potential of this gene as a promising biomarker for the early detection of CRC development.

1. Background

Colorectal cancer (CRC), one of the most common malignancies worldwide, has a poor prognosis and extensive metastatic dissemination. Radiotherapy is a crucial procedure for CRC therapy, but its use is limited by radioresistance. In addition, surgery is an option for advanced CRC, which is frequently followed by further chemotherapy (1, 2). Although CRC screening can reduce the incidence and mortality rate, it is not usually performed. On the other hand, blood tests are the preferred fundamental way of detection. As a result, more markers must be discovered (3). Predictive biomarkers provide valuable details for directing therapeutic decisions in patients who are favorable for the biomarker compared to those who are negative (4). Despite improvements in traditional screening methods and the development of promising medications, the survival rates for CRC remain low. The increased incidence is ascribed to illnesses, poor diet, and obesity (5).

Long non-coding RNAs (lncRNAs) that are not translated to proteins have critical roles in gene expression regulation, epigenetic modifications, cell growth, and differentiation (6). Furthermore, lncRNAs are dysregulated in several malignancies, and they are regarded as important prognostic and diagnostic biomarkers because of their distinct expression patterns and high tissue- and cell-specificity (7). In addition, recent research has demonstrated that lncRNAs may be involved in migration, metastasis, chemoresistance, epithelial-to-mesenchymal transition (EMT), and proliferation of CRC (8-12).

According to research by Liu et al., VLDLR-AS1 regulated the expression of genes related to lipid loss in cancer cachexia, responsible for 20% of all cancer-related deaths. Further investigation discovered that genes associated with VLDLR-AS1 were implicated in EMT, the Wnt signaling pathway, and small GTPase-mediated signal transduction (13). Chen et al. reported that esophageal cancer cells had increased levels of VLDLR-AS1, an exosomal lncRNA, that led to chemoresistance. Furthermore, they revealed that the extracellular vesicles (EVs) generated by drug-resistant cells might upregulate the expression of ABCG2 and, hence, affect drug resistance related to the VLDLR-AS1 carried by EVs (14). By comprehensive RNA-seq data analysis in patients with thymomas, Ji et al. discovered 65 differently expressed (DE) lncRNAs. VLDLR-AS1 was overexpressed and validated by The Cancer Genome Atlas (TCGA) (15).

2. Objectives

In the current study, VLDLR-AS1 expression levels were evaluated in the CRC tissues compared to healthy tumor margins for the first time. The biomarker potency of VLDLR-AS1 for discriminating tumoral and non-tumoral CRC tissues was also investigated.

3. Methods

3.1. CRC Tissue Sampling

Ninety-four paired samples of cancerous and non-cancerous adjacent tissues were collected from patients with CRC referred to the Noor-e Nejat Hospital in Tabriz, Iran. Samples were immediately placed in liquid nitrogen, transferred to the laboratory, and stored at -80°C. The Ethical Committee of the University of Tabriz approved this study. Written informed consent was obtained from all patients. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki, as reflected in a prior approval by the institution's human research committee.

3.2. RNA Extraction, cDNA Synthesis, and qRT-PCR

Total RNA was extracted from tissues using TRIZOL reagent (Invitrogen, Massachusetts, USA) based on the manufacturer's guidelines. Thermo Fisher Scientific NanoDrop (2000, CA, USA) was used to assess the purity and quantity of the isolated RNAs. The integrity of RNA molecules was evaluated using 2% gel electrophoresis. DNase I (Gene All, Korea) treatment was performed to remove residual DNA contaminations. For cDNA synthesis, PrimeScript™ 1st Strand cDNA Synthesis Kit (TaKaRa, Kusatsu, Japan) was utilized. Gene-specific primers were designed by the Gene Runner software, and the BLAST program evaluated their specificity. Sequences of the primers were VLDLR-AS1 forward: 5’-GAATCGAAGCGCCCCTATCA-3’, reverse: 5’-CAGTGAGGCAAGCTGGTTCT-3’, U6 forward: 5’-CTCGCTTCGGCAGCACAT-3’, U6 reverse: 5’-GGAACGCTTCACGAATTTGC-3’. The U6 was used as internal control. Expression of VLDLR-AS1 and U6 was assessed using StepOnePlusTM Real-Time PCR System (Applied Biosystems). The reaction mixture, including SYBER Green Master Mix (Amplicon Company) 5 µL, forward primer 0.12 µL, reverse primer 0.12 µL, cDNA (diluted 1:100) 4 µL, and ddH2O 0.76 µL, in a final volume of 10 µL was used for amplification. The cycling program was 10 min at 95°C, 45 cycles of 30 sec at 95°C, 30 sec at 58°C, 30 sec at 72°C, followed by 5 min at 72°C. The reactions were duplicated, and the results were normalized to U6. The fold change of VLDLR-AS1 was calculated using the 2-ΔΔCT method.

3.3. Statistical Analysis

The SPSS version 27 and GraphPad version 9 were used for data analysis. The normality of the data was examined using Kolmogorov-Smirnov test. The students' t-test compared the data between two groups. The Mann-Whitney and one-way ANOVA tests were applied to study the association of clinicopathological features with the expression of VLDLR-AS1. The receiver operating characteristic (ROC) curve was utilized to evaluate the biomarker potential of VLDLR-AS1. P-value < 0.05 was considered statistically significant.

4. Results

4.1. Clinicopathological Characteristics of Study Subjects

A total of 188 tissue samples, including 94 tumor and 94 corresponding tumor marginal samples from 94 CRC patients, were studied. The clinicopathological attributes of the patients are described in Table 1; 16 were female, and 78 were male. Concerning age dispersion, 8 cases were ≤55 years old, and 86 were >55 years old.

Table 1.

Correlation of VLDLR-AS1 Expression with the Clinicopathological Features of CRC Patients

Clinical ParametersNo. (%)P-Value
Age0.22
>5586 (91)
≤558 (9)
Gender0.46
Female16 (17)
Male78 (83)
Location0.72
Colon70 (74)
Rectum24 (26)
Invasion0.25
Yes80 (85)
No14 (15)
Lymph0.33
Yes34 (36)
No60 (64)
Smoking0.42
Yes70 (74)
No24 (26)
TNM0.24
I/II58 (62)
III/IV36 (38)

4.2. VLDLR-AS1 Downregulation in CRC Tissue Samples

The fold change of VLDLR-AS1 lncRNA was assessed by qRT-PCR. The results showed that the downregulation of VLDLR-AS1 in tumor samples had a 0.44 ± 0.08 fold change compared to the marginal samples (Figure 1, P < 0.0001).

Bar plot representing the expression levels of VLDLR-AS1 in tumors compared to the marginal non-tumor tissues. **** P < 0.0001
Bar plot representing the expression levels of VLDLR-AS1 in tumors compared to the marginal non-tumor tissues. **** P < 0.0001

4.3. Correlation of VLDLR-AS1 Expression with Clinicopathological Features

The correlation between VLDLR-AS1 expression levels and clinicopathological characteristics of CRC patients, including age, gender, tumor location, invasion, lymph, smoking habits, and TNM, were analyzed. The results showed no significant correlation between each feature and VLDLR-AS1 expression.

4.4. Biomarker Potential of VLDLR-AS1

The ROC curve analysis was used to evaluate the biomarker potency of VLDLR-AS1 expression levels for CRC (Figure 2). Table 2 shows that VLDLR-AS1 expression can distinguish tumor and non-tumor samples with a sensitivity and specificity of 72.34% and 51.06%, respectively (P = 0.03, AUC = 0.6274). In addition, the cutoff value (0.0028), standard error (0.0579), and 95% confidence interval (0.5139 - 0.7410) were calculated for the two groups. The results showed that VLDLR-AS1 could be considered a potential diagnostic biomarker.

ROC curve presenting biomarker potency of VLDLR-AS1
ROC curve presenting biomarker potency of VLDLR-AS1
Table 2.

ROC Curve Analysis Outputs a

ROC Curve DataAUCSensitivitySpecificityCutoff ValueStd. ErrorP-Value95% CI
VLDLR-AS10.627472.34%51.06%0.00280.05790.03a0.5139 - 0.7410

5. Discussion

CRC is common worldwide, and younger people are being affected more frequently. Further investigations must be conducted to prevent new cases and fatalities (16). The primary therapeutical approach for metastatic CRC is chemotherapy, either alone or in combination with target therapy. It is challenging to achieve advancements in traditional approaches regarding the side effects of chemotherapies and molecular features of the tumor cells (17). As a result, lncRNAs have been identified as beneficial indicators for cancer onset and cell growth (9, 18). Comprehending the role of lncRNAs in cancer biology could be helpful for the treatment, prognosis, and diagnosis of cancer (7, 19, 20). In the current study, for the first time, we investigated VLDLR-AS1 expression levels in CRC and compared its expression levels between tumoral and non-tumoral margin tissue samples.

We found that CRC tissues had significantly reduced levels of VLDLR-AS1 expression compared to the marginal tissues. The results of Zheng et al. were consistent with our research. They indicated that in ovarian cancer (OC), VLDLR-AS1 is enriched in ovarian steroidogenesis or the GnRH signaling pathway. Furthermore, the downregulation of VLDLR-AS1 was related to poor survival and appeared to be an oncogene in OC cellular function (21). In addition, Wu et al. demonstrated that as a protective gene in OC development, the downregulation of VLDLR-AS1 was related to poor survival (22).

In contrast to our findings, Takahashi et al. revealed that VLDLR-AS1 was significantly upregulated in hepatocellular carcinoma. The EVs from tumor cells containing VLDLR-AS1 contributed to cellular stress responses (23). Moreover, malignant hepatocytes had increased VLDLR-AS1 and lincRNA-ROR (linc-ROR) levels, enriched explicitly inside EV and subsequently stimulated by TGFβ to increase EV release. Altogether, these findings provide evidence for the existence of TGFβ-mediated mechanisms for the precise enrichment of these lncRNAs inside EV and their possible roles in intercellular signaling affected by TGF as prospective drug resistance regulators (24).

Moreover, we found that VLDLR-AS1 could be regarded as a possible biomarker, in accordance with the research conducted by Yue et al. These authors also showed that according to survival analysis, patients with lung adenocarcinomas had better prognoses and overall survival rates once VLDLR-AS1 expression levels were raised. A database called TCGA_LUAD was used to verify the mentioned result (25). In addition, Gong et al. revealed that the overexpression of LINC00324, AFAP1-AS1, and VLDLR-AS1 lncRNAs was associated with the enhanced proliferation of thymomas. Furthermore, the VLDLR-AS1 expression profile was linked to relapse-free survival of patients, which could be helpful as a prognostic biomarker (26). In addition, using TCGA data, Ye et al. showed that 76 DE lncRNAs, including VLDLR-AS1, were found in gastric cancer. Further investigation revealed that VLDLR-AS1 and the other 8 hub lncRNAs might play a role in the MAPK signaling pathway. Lower patient overall survival was linked to greater levels of VLDLR-AS1 (27). Overall, TGFβ (24), MAPK (27), and Wnt (13) signaling pathways leading to EMT and chemoresistance (13) may all be altered by VLDLR-AS1 via EVs released from cancer cells. Moreover, in this study, there was no significant association between the expression levels of VLDLR-AS1 and the clinicopathological features of patients with CRC. More research is required because VLDLR-AS1 lncRNA and its critical roles have not been sufficiently studied.

5.1. Conclusions

Downregulation of VLDLR-AS1 lncRNA in CRC tumor tissue was indicated compared to healthy tumor margin tissue. In addition, VLDLR-AS1 might be considered a biomarker for diagnosing CRC progression.

References

  • 1.

    Karimpur Zahmatkesh A, Moqadami A, Khalaj-Kondori M. Insights into the radiotherapy-induced deferentially expressed RNAs in colorectal cancer management. Iran J Basic Med Sci. 2023;26(12):1380-9. [PubMed ID: 37970448]. [PubMed Central ID: PMC10634048]. https://doi.org/10.22038/IJBMS.2023.71259.15482.

  • 2.

    Brockmueller A, Samuel SM, Mazurakova A, Busselberg D, Kubatka P, Shakibaei M. Curcumin, calebin A and chemosensitization: How are they linked to colorectal cancer? Life Sci. 2023;318:121504. [PubMed ID: 36813082]. https://doi.org/10.1016/j.lfs.2023.121504.

  • 3.

    Chang LC, Chiu HM, Wu MS, Shen TL. The Role of Small Extracellular Vesicles in the Progression of Colorectal Cancer and Its Clinical Applications. Int J Mol Sci. 2022;23(3). [PubMed ID: 35163305]. [PubMed Central ID: PMC8835972]. https://doi.org/10.3390/ijms23031379.

  • 4.

    Koncina E, Haan S, Rauh S, Letellier E. Prognostic and Predictive Molecular Biomarkers for Colorectal Cancer: Updates and Challenges. Cancers (Basel). 2020;12(2). [PubMed ID: 32019056]. [PubMed Central ID: PMC7072488]. https://doi.org/10.3390/cancers12020319.

  • 5.

    El Zarif T, Yibirin M, De Oliveira-Gomes D, Machaalani M, Nawfal R, Bittar G, et al. Overcoming Therapy Resistance in Colon Cancer by Drug Repurposing. Cancers (Basel). 2022;14(9). [PubMed ID: 35565237]. [PubMed Central ID: PMC9099737]. https://doi.org/10.3390/cancers14092105.

  • 6.

    Al-Noshokaty TM, Mansour A, Abdelhamid R, Abdellatif N, Alaaeldien A, Reda T, et al. Role of long non-coding RNAs in pancreatic cancer pathogenesis and treatment resistance- A review. Pathol Res Pract. 2023;245:154438. [PubMed ID: 37043965]. https://doi.org/10.1016/j.prp.2023.154438.

  • 7.

    Khajehdehi M, Khalaj-Kondori M, Ghasemi T, Jahanghiri B, Damaghi M. Long Noncoding RNAs in Gastrointestinal Cancer: Tumor Suppression Versus Tumor Promotion. Dig Dis Sci. 2021;66(2):381-97. [PubMed ID: 32185664]. https://doi.org/10.1007/s10620-020-06200-x.

  • 8.

    Ghasemi T, Khalaj-Kondori M, Hosseinpour Feizi MA, Asadi P. lncRNA-miRNA-mRNA interaction network for colorectal cancer; An in silico analysis. Comput Biol Chem. 2020;89:107370. [PubMed ID: 32932199]. https://doi.org/10.1016/j.compbiolchem.2020.107370.

  • 9.

    Ghasemi T, Khalaj-Kondori M, Hosseinpour Feizi MA, Asadi P. Aberrant expression of lncRNAs SNHG6, TRPM2-AS1, MIR4435-2HG, and hypomethylation of TRPM2-AS1 promoter in colorectal cancer. Cell Biol Int. 2021;45(12):2464-78. [PubMed ID: 34431156]. https://doi.org/10.1002/cbin.11692.

  • 10.

    Zhou L, Li J, Liao M, Zhang Q, Yang M. LncRNA MIR155HG induces M2 macrophage polarization and drug resistance of colorectal cancer cells by regulating ANXA2. Cancer Immunol Immunother. 2022;71(5):1075-91. [PubMed ID: 34562123]. https://doi.org/10.1007/s00262-021-03055-7.

  • 11.

    Lv C, Yu H, Wang K, Chen C, Tang J, Han F, et al. ENO2 Promotes Colorectal Cancer Metastasis by Interacting with the LncRNA CYTOR and Activating YAP1-Induced EMT. Cells. 2022;11(15). [PubMed ID: 35954207]. [PubMed Central ID: PMC9367517]. https://doi.org/10.3390/cells11152363.

  • 12.

    Han S, Cao Y, Guo T, Lin Q, Luo F. Targeting lncRNA/Wnt axis by flavonoids: A promising therapeutic approach for colorectal cancer. Phytother Res. 2022;36(11):4024-40. [PubMed ID: 36227024]. https://doi.org/10.1002/ptr.7550.

  • 13.

    Liu H, Zhou T, Wang B, Li L, Ye D, Yu S. Identification and functional analysis of a potential key lncRNA involved in fat loss of cancer cachexia. J Cell Biochem. 2018;119(2):1679-88. [PubMed ID: 28782835]. https://doi.org/10.1002/jcb.26328.

  • 14.

    Chen Y, Liu L, Li J, Du Y, Wang J, Liu J. Effects of long noncoding RNA (linc-VLDLR) existing in extracellular vesicles on the occurrence and multidrug resistance of esophageal cancer cells. Pathol Res Pract. 2019;215(3):470-7. [PubMed ID: 30606658]. https://doi.org/10.1016/j.prp.2018.12.033.

  • 15.

    Ji G, Ren R, Fang X. Identification and Characterization of Non-Coding RNAs in Thymoma. Med Sci Monit. 2021;27. e929727. [PubMed ID: 34219124]. [PubMed Central ID: PMC8268976]. https://doi.org/10.12659/MSM.929727.

  • 16.

    Morgan E, Arnold M, Gini A, Lorenzoni V, Cabasag CJ, Laversanne M, et al. Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut. 2023;72(2):338-44. [PubMed ID: 36604116]. https://doi.org/10.1136/gutjnl-2022-327736.

  • 17.

    Weng J, Li S, Zhu Z, Liu Q, Zhang R, Yang Y, et al. Exploring immunotherapy in colorectal cancer. J Hematol Oncol. 2022;15(1):95. [PubMed ID: 35842707]. [PubMed Central ID: PMC9288068]. https://doi.org/10.1186/s13045-022-01294-4.

  • 18.

    Amini F, Khalaj-Kondori M, Moqadami A, Rajabi A. Expression of HOTAIR and MEG3 are negatively associated with H. pylori positive status in gastric cancer patients. Genes Cancer. 2022;13:1-8. [PubMed ID: 35186192]. [PubMed Central ID: PMC8849211]. https://doi.org/10.18632/genesandcancer.219.

  • 19.

    Ostovarpour M, Khalaj-Kondori M, Ghasemi T. Correlation between expression levels of lncRNA FER1L4 and RB1 in patients with colorectal cancer. Mol Biol Rep. 2021;48(5):4581-9. [PubMed ID: 34132945]. https://doi.org/10.1007/s11033-021-06488-6.

  • 20.

    Moqadami A, Khalaj-Kondori M. Study of lncRNA NEAT1 Gene Expression in Ovarian Cancer. J Cell Mol Res. 2022;14(1):63-70. https://doi.org/10.22067/jcmr.2022.76959.1041.

  • 21.

    Zheng J, Guo J, Zhang H, Cao B, Xu G, Zhang Z, et al. Four Prognosis-Associated lncRNAs Serve as Biomarkers in Ovarian Cancer. Front Genet. 2021;12:672674. [PubMed ID: 34367239]. [PubMed Central ID: PMC8336869]. https://doi.org/10.3389/fgene.2021.672674.

  • 22.

    Wu W, Gao C, Chen L, Zhang D, Guo S. Comprehensive analysis of competitive endogenous RNAs networks reveals potential prognostic biomarkers associated with epithelial ovarian cancer. Oncol Lett. 2021;22(6):843. [PubMed ID: 34777587]. [PubMed Central ID: PMC8581474]. https://doi.org/10.3892/ol.2021.13104.

  • 23.

    Takahashi K, Yan IK, Wood J, Haga H, Patel T. Involvement of extracellular vesicle long noncoding RNA (linc-VLDLR) in tumor cell responses to chemotherapy. Mol Cancer Res. 2014;12(10):1377-87. [PubMed ID: 24874432]. [PubMed Central ID: PMC4201956]. https://doi.org/10.1158/1541-7786.MCR-13-0636.

  • 24.

    Takahashi K, Yan IK, Kogure T, Haga H, Patel T. Extracellular vesicle-mediated transfer of long non-coding RNA ROR modulates chemosensitivity in human hepatocellular cancer. FEBS Open Bio. 2014;4:458-67. [PubMed ID: 24918061]. [PubMed Central ID: PMC4050189]. https://doi.org/10.1016/j.fob.2014.04.007.

  • 25.

    Yue D, Liu W, Gao L, Zhang L, Wang T, Xiao S, et al. Integrated Multiomics Analyses Revealing Different Molecular Profiles Between Early- and Late-Stage Lung Adenocarcinoma. Front Oncol. 2021;11:746943. [PubMed ID: 34745971]. [PubMed Central ID: PMC8567144]. https://doi.org/10.3389/fonc.2021.746943.

  • 26.

    Gong J, Jin S, Pan X, Wang G, Ye L, Tao H, et al. Identification of Long Non-Coding RNAs for Predicting Prognosis Among Patients with Thymoma. Clin Lab. 2018;64(7):1193-8. [PubMed ID: 30146820]. https://doi.org/10.7754/Clin.Lab.2018.180136.

  • 27.

    Ye L, Jin W. Identification of lncRNA-associated competing endogenous RNA networks for occurrence and prognosis of gastric carcinoma. J Clin Lab Anal. 2021;35(12). e24028. [PubMed ID: 34704289]. [PubMed Central ID: PMC8649378]. https://doi.org/10.1002/jcla.24028.