Serum Level of MVIH, HNF1A-AS1, and NEAT1 Long Noncoding RNAs: Potential Biomarkers for Colorectal Cancer

Abstract

Long noncoding RNAs (lncRNAs) are a significant class of non-coding RNAs that play critical roles in cancer development, progression, and metastasis. This study aimed to investigate the expression of MVIH, HNF1A-AS1, and NEAT1 in the blood samples of patients with colorectal cancer (CRC), both before and three months after surgery, in comparison to a healthy control group. The objective was to assess the potential of these genes as biomarkers for CRC. A total of 75 blood samples were collected from patients diagnosed with colorectal carcinomas (before surgery and at the three-month post-surgery mark), while an additional 75 samples were obtained from a healthy control group. The relative expression levels of the target genes in the serum were measured using quantitative real-time PCR. Our findings demonstrated that the levels of MVIH, HNF1A-AS1, and NEAT1 in the serum were significantly upregulated in CRC subjects compared to the healthy controls. Receiver operating characteristic (ROC) curve analysis revealed that the serum levels of all three genes could effectively distinguish CRC cases from controls with notable accuracy. Furthermore, the serum levels of MVIH, HNF1A-AS1, and HNF1A-AS1 were significantly downregulated three months after surgery. However, no significant correlations were observed between the serum levels of the studied genes and the clinical features of the patients. Collectively, our results suggest that the serum levels of MVIH, HNF1A-AS1, and HNF1A-AS1 have the potential to serve as valuable biomarkers for the diagnosis and prognosis of CRC.

Introduction

Colorectal cancer (CRC) exerts a significant global health burden, contributing to over 8 million cancer-related deaths in 2020 and ranking as the third most lethal malignancy worldwide [1, 2]. The disease progresses from benign polyps to metastatic forms over a span of approximately four years, and advanced stages of CRC are associated with high mortality rates. However, early detection and intervention, including surgical resection and adjuvant chemotherapy, have shown significant improvements in patient outcomes. Consequently, there is an urgent need within the field of cancer research to identify novel biomarkers that exhibit enhanced sensitivity and specificity, particularly for CRC prognosis and monitoring [3, 4, 5].

Long noncoding RNAs (lncRNAs) represent a distinct category of non-coding RNA molecules characterized by their length of at least 200 nucleotides and their inability to encode proteins [6]. Despite lacking protein-coding potential, long non-coding RNAs (lncRNAs) have been identified as important regulators in a wide range of biological processes, including cell growth, differentiation, migration, and apoptosis [6, 7]. Furthermore, a growing body of evidence indicates that aberrant expression of lncRNAs is linked to various types of malignancies. This emphasizes their potential as important prognostic indicators [8]. Notably, certain lncRNAs exhibit cancer-specific expression patterns and can function as either oncogenes or tumor suppressors, making them promising targets for novel therapeutic strategies and diagnostic biomarkers to facilitate accurate cancer prediction and personalized treatment approaches [9, 10].

Among the expanding repertoire of lncRNAs, recent attention has been focused on microvascular invasion in hepatocellular carcinoma (MVIH), initially identified as an up-regulated lncRNA in hepatocellular carcinoma [11]. Subsequent investigations have revealed its overexpression in various malignancies, including non-small cell lung cancer and breast cancer, where it plays critical roles in tumor progression and metastasis [11, 12]. Another lncRNA of interest in cancer research is hepatocyte nuclear factor 1A-antisense RNA (HNF1A-AS1), located on chromosome 12. HNF1A-AS1 has demonstrated up-regulation in multiple cancer types, and its dysregulated expression has been associated with poor prognosis and tumor aggressiveness [13, 14]. In CRC, notable mutations in HNF1A-AS1 have been reported in patients with microsatellite instability-high, and aberrant expression levels of HNF1A-AS1 have shown correlations with CRC patient prognosis, emphasizing its potential as a prognostic marker [14]. Additionally, the lncRNA NEAT1 has exhibited oncogenic properties in various cancer types, including ovarian cancer, where it promotes tumor growth and metastasis [15].

In summary, previous studies have shed light on the potential of MVIH, HNF1A-AS1, and NEAT1 as biomarkers in diverse malignancies. However, the majority of investigations have primarily focused on their expression patterns within tissue samples. Given the urgent need for non-invasive and effective biomarkers for CRC screening and the promising prospects of MVIH, HNF1A-AS1, and NEAT1 as cancer biomarkers, this study aims to evaluate the serum levels of these lncRNAs in CRC patients compared to healthy controls. Furthermore, monitoring changes in their expression levels three months post-surgery will validate their association with tumor presence and their potential utility as dynamic biomarkers for CRC surveillance. The ultimate goal is to contribute to the development of non-invasive diagnostic approaches and prognostic models that would improve the early detection, monitoring, and management of CRC, thus leading to better clinical outcomes and patient survival rates.

Materials and Methods

Patients and Samples

This study followed the ethical guidelines set by the institution and was approved by the Ethical Committee of Tabriz University of Medical Sciences (IR.TBZMED.REC.1400.942). A total of 225 samples were collected. Among them, 150 samples were obtained from patients diagnosed with Colorectal cancer (75 samples before surgery and 75 samples two months after surgery), while 75 samples were collected from healthy individuals who served as the control group. The collection of peripheral blood samples (5 ml) took place at Imam Reza Hospital, Tabriz University of Medical Science, Tabriz, Iran, from June 2018 to March 2020. The baseline and clinical data of the included patients are summarized in Table 1.

Table 1.

Clinical Features of Patients who Participated in the Study

Clinicopathological Character	Number		P value MVIH	P value NEAT	P value HNF1A-AS1
Age	>60	41	0.075	0.11	0.086
	<60	34
Sex	Female	28	0.124	0.24	0.095
	Male	47
Family Story	Positive	9	0.091	0.086	0.104
	Negative	66
Smoking	Positive	21	0.102	0.45	0.117
	Negative	54
Lymph node Invasion	Positive	59	0.054	0.086	0.042
	Negative	16
Distant Metastasis	Positive	17	0.069	0.094	0.023
	Negative	58
Differentiation	Poor	27	0.0591	0.11	0.079
	Intermediate	31
	Good	16

RNA Extraction and Real-time PCR

Serum samples were obtained from peripheral blood by centrifugation. Total RNA was isolated from the samples using Tripure isolation reagent (Roche, Cat No. 11667165001) following the manufacturer’s protocol. The quality and quantity of the extracted RNAs were determined by measuring the optical density (OD) using Nanodrop (NanoDrop ND-2000C, Thermo Fisher Scientific, USA). Subsequently, cDNA synthesis was performed using the TAKARA cDNA synthesis kit (TAKARA Cat No. 6130) according to the manufacturer’s instructions. Real-time PCR was carried out using the LightCycler 96 system (Roche, Germany) with specific primers (refer to Table 2). The expression level of the target genes was normalized to the housekeeping gene GAPDH. The relative expression level of the studied genes was determined by comparing the transcript level of the target genes to the transcript level of the corresponding housekeeping gene in each sample using the comparative Ct method (2^−ΔΔCT). [16].

Table 2.

Primer Sequences and Properties

Primer	Sequences	Tm	Product Size
GAPDH	Forward: 5′‐AAGGTGAAGGTCGGAGTCAAC‐3′	64 °C	102 bp
	Reverse: 5′‐GGGGTCATTGATGGCAACAA‐3′
NEAT-1	Forward:5′‐GGAGTTAGCGACAGGGAGGGA‐3′	60 °C	91 bp
	Reverse:5′‐ATCTCTCCCTGTCTGTCCCCT‐3′
HNF1A-AS1 -AS1	Forward:5′‐AGTAAGTGCAGTAGGTAGGCC‐3′	59 °C	146bp
	Reverse:5′‐GGCCTCCCGTTAGTACATCCA‐3′
MVIH	Forward:5′‐GAGACAGGATTTAGCCGTGTTG‐3′	59 °C
	Reverse:5′‐ACAGATTCGGAAGGTTTCACGA‐3′

Statistical Analysis

The statistical analysis was performed using GraphPad Prism v.6.00 (Graph Pad Software Inc., San Diego, CA, USA). The normal distribution of data was assessed using the Kolmogorov-Smirnov test. Independent sample t-tests were employed to compare the expression levels of the target genes between the study groups. Cross-tab (Eta) analysis was conducted to evaluate the relationship between the clinical features of the patients and the relative expression of NEAT1, HNF1A-AS1, and MVIH. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC) was calculated to assess the sensitivity and specificity of each target gene as a biomarker for colorectal cancer (CRC). All data were reported as mean ± standard deviation (SD) or as percentages where applicable. Statistical significance was set at p < 0.05.

Results

The expression levels of MVIH in the serum of the control group were significantly lower compared to the patient group, with a p-value of 0.0035 (Figure 1a). Furthermore, our findings showed a significant decrease in the serum level of MVIH in our patients three months after surgery, with a p-value of 0.0027. Similar to MVIH, our results demonstrated significantly higher levels of HNF1A-AS1 expression in serum samples of patients with colorectal cancer (CRC) compared to healthy controls, with a p-value of 0.019 (Figure 1b). Additionally, the expression level of HNF1A-AS1 was significantly down-regulated three months after surgery, with a p-value of 0.028. NEAT-1, another gene analyzed in this study using qRT-PCR, showed upregulation in CRC samples, with a p-value of 0.023. Furthermore, NEAT-1 exhibited a similar pattern after surgery, with a significant down-regulation (p-value < 0.0001) (Figure 1c). However, we could not find any correlation between the studied genes and the clinical features of our patients (Table 1).

Figure 1.

The Expression Levels of NEAT-1 (a), HNF1A-AS1 -AS1 (b), and MVIH (c) in Studies Groups

High potential of NEAT-1, HNF1A-AS1 -AS1, and MVIH as diagnostic biomarkers for CRC

An evaluation of the diagnostic potential of NEAT-1, HNF1A-AS1, and MVIH genes in differentiating individuals with colorectal cancer (CRC) from healthy individuals was performed using receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (AUC) values were calculated as follows: NEAT-1 (AUC = 0.69, p-value = 0.0009), HNF1A-AS1 (AUC = 0.68, p-value = 0.0011), and MVIH (AUC = 0.68, p-value < 0.0011). These findings suggest that these lncRNAs exhibit a high potential as diagnostic biomarkers for CRC (Figure 2). However, it is important to note that further validation in a larger sample size is necessary to confirm the reliability and accuracy of these results.

Figure 2.

Results of ROC Curve Analysis of NEAT-1, HNF1A-AS1 -AS1, and MVIH in CRC Patient Compression to Healthy Controls

Discussion

Colorectal cancer (CRC) is recognized as the third most common type of cancer and the second most significant contributor to cancer-related mortality. Early detection of CRC is crucial as it allows for the implementation of effective treatment strategies such as chemotherapy and surgery, ultimately improving patients’ quality of life. Consequently, the identification of reliable molecular markers capable of detecting CRC at its early stages is of paramount importance [17, 18].

Long non-coding RNAs (LncRNAs) represent a class of non-coding mRNA molecules that do not possess protein-coding abilities. Despite their inability to produce proteins, LncRNAs play vital roles in maintaining cellular homeostasis and regulating various cellular processes [19]. Numerous studies have highlighted the dysregulation of LncRNAs in different disorders, and some LncRNAs have shown potential as diagnostic or prognostic biomarkers for human diseases. Pertaining to malignancies, critical changes in LncRNAs have been observed in tumor cells, implicating their involvement in cancer development and progression [9, 20]. In fact, certain LncRNAs have been proposed as cancer-specific biomarkers [21]. Furthermore, research has revealed alterations in LncRNAs present in cell-secreted vesicles and exosomes, thereby affecting the circulating levels of these molecules and potentially serving as diagnostic markers [22].

An interesting long non-coding RNA (lncRNA) that has garnered attention is NEAT-1, as it has been observed to exhibit increased expression levels in different cancer types. Recent studies have provided evidence indicating that elevated NEAT-1 expression contributes to cancer cell proliferation in squamous cell carcinoma. Similarly, increased levels of NEAT-1 have been associated with metastasis in hepatocellular carcinoma. Reports have also indicated overexpression of NEAT-1 in ovarian cancer and CRC [23, 24]. Another oncogenic LncRNA, HNF1A-AS1, has been extensively studied in various tumor types, particularly in CRC. Studies have shown a correlation between HNF1A-AS1 mutation and the prognosis of CRC patients. Furthermore, the deregulation of HNF1A-AS1 impacts the characteristics of colon cancer cells in vitro [14, 25].

The third LncRNA investigated in this study is MVIH, which has been examined in various tumors. Previous studies have reported a correlation between overexpression of MVIH and patient outcomes [26]. In our study, we aimed to evaluate the circulating levels of NEAT-1, HNF1A-AS1, and MVIH in patients with CRC, comparing them with healthy controls to determine the potential of these genes in distinguishing between the two groups. Our data confirmed the overexpression of all three LncRNAs in the serum of patients compared to normal controls. ROC curve analysis of the expression levels of these genes demonstrated their potential as biomarkers for the diagnosis of CRC. However, further studies are required to fully validate these findings. Additionally, we measured and analyzed the expression levels of NEAT-1, HNF1A-AS1, and MVIH three months after surgery to ascertain the association between gene expression and the presence of tumor cells. Surprisingly, contrary to other studies, we did not observe a correlation between the expression levels of our target genes and pathological features.

In conclusion, the identification of reliable biomarkers for the early detection of CRC is critical for improving patient outcomes. LncRNAs have emerged as promising candidates in this regard, given their dysregulated expression patterns in various cancers. Our study demonstrated the overexpression of NEAT-1, HNF1A-AS1, and MVIH in patients with CRC, suggesting their potential as diagnostic biomarkers. However, further studies involving larger sample sizes are necessary to validate our findings and elucidate the precise roles of these LncRNAs in CRC development and progression. Ultimately, the implementation of effective biomarkers holds promise for enhancing the early detection and management of CRC, thereby improving patient survival rates and overall prognosis.

Author Contribution Statement

Conceptualization: MM, TAK and MRF; methodology: HZ, SHH, and VZ; validation: MM and RF; Qualitative data collection and analysis: MM, TAK, and NP; investigation: VZ, RF, and NP; writing—review and editing: MM, TAK, and HZ. All authors have read and agreed to the published version of the manuscript.