Diagnostic value of lnc-RNAs TINCR, GC1 and AFAP1-AS1 in gastric cancer differentiation from healthy people

ABSTRACT

Aims and background

Gastric cancer is a significant health challenge globally, necessitating the identification of novel biomarkers for improved diagnosis. Our study aimed to address this gap by investigating the diagnostic potential a set of long non-coding RNAs (lncRNAs) in gastric cancer patients compared to healthy controls.

Materials and methods

We conducted a retrospective case-control analysis involving 256 participants, including 128 gastric cancer patients and 128 healthy individuals. Alongside the measurement of serum levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 19–9 (CA19.9), the plasma expression profiling of eight lnc-RNAs was performed in the selected samples.

Results

Our findings revealed significant alterations in CEA and CA19.9 levels in gastric cancer patients compared to controls (p < 0.05). Moreover, upregulated expression of lncRNAs, including HOTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1, were all observed in gastric cancer patients (p < 0.05). Excluding lncUGC1 and FAM49B-AS, ROC curve analysis demonstrated the diagnostic potential of lncRNAs in gastric cancer detection, with notable specificity and sensitivity.

Conclusion

Our study disclosed the diagnostic utility of plasma HOTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1 lncRNAs as appropriate diagnostic biomarkers for gastric cancer. The identification of dysregulated lncRNAs offers promising avenues for noninvasive diagnostic assessment in gastric cancer.

1. Introduction

Gastric cancer remains a major global health issue with significant epidemiological variation across different regions [1]. Globally, as of 2022, gastric cancer is the fifth most commonly diagnosed cancer worldwide [2]. Gastric cancer is the fourth leading cause of cancer-related deaths globally, accounting for approximately 768,000 deaths in 2020, or 7.7% of all cancer deaths [1]. Some high-income countries have seen a decline in mortality due to early detection and improved treatment strategies [3]. However, this decline is slowing due to the rise in gastro-esophageal junction adenocarcinomas and stable H. pylori prevalence. Gastric cancer predominantly affects older adults, with the highest incidence in individuals aged 60 years and above [4]. However, there is a notable increase in incidence among younger individuals in high-income countries. Men are approximately twice as likely to develop gastric cancer compared to women, a trend observed across most regions [5]. Helicobacter pylori is the strongest known risk factor for gastric cancer, linked to approximately 89% of non-cardia gastric cancers worldwide [6].

One of the critical challenges in combating gastric cancer is the difficulty in early diagnosis. Often, the disease is asymptomatic in its early stages or presents with nonspecific symptoms, leading to delayed detection and treatment [7]. Traditional diagnostic methods, including endoscopy and histopathological examination, although effective, are invasive and may not be feasible for large-scale screening [8]. In this context, the identification and utilization of biomarkers for early detection have become increasingly important. Biomarkers, measurable biological indicators of disease, can be detected in blood, plasma, and other biological fluids, offering a promising avenue for noninvasive screening and early diagnosis of gastric cancer [9]. These include molecular markers like circulating tumor DNA (ctDNA), microRNAs (miRNAs), long non-coding RNA(lnc-RNA) and protein-based markers, which can reflect the presence of malignancy at a stage when clinical symptoms have not yet manifested [10]. Early detection through biomarker screening could significantly improve prognosis by enabling timely therapeutic interventions and potentially reducing mortality rates [11]. Therefore, advancing research and integration of these biomarkers into clinical practice is crucial for enhancing the effectiveness of gastric cancer control strategies and clinical management.

Long non-coding RNAs (lncRNAs) represent a substantial portion of the mammalian genomes transcriptomen, with evidence indicating their significant regulatory roles in gene expression at both transcriptional and post-transcriptional levels [12]. They exhibit diverse functions, including epigenetic regulation, modulation of gene transcription and protein degradation, involvement in organelle biogenesis and subcellular trafficking, and interactions with small regulatory RNAs [13–17]. Dysregulation of lncRNAs is implicated in various human cancers, including leukemia [17], colon cancer [18], prostate cancer [19], breast cancer [20], gastric cancer [21], and [22] hepatocellular carcinoma. Long non-coding RNAs (lncRNAs) have emerged as promising biomarkers for cancer detection and prognosis due to their stability and abundance in blood or serum samples [23]. The use of lncRNAs as prognostic biomarkers in blood or serum samples opens up the possibility of personalized medicine approaches for cancer patients since lncRNAs have been found to be specifically dysregulated in various types of cancer, making them highly specific biomarkers for different cancer types.

lncRNAs FAM49B-AS is another lncRNA which exclusively highly abundant in plasma of patients with gastric cancer, showed by Zheng et al. [24]. They also indicated that increased GC cell viability and invasion. It is also considered as prognostic biomarker for hepatocellular carcinoma [25] and also contribute to the breast cancer proliferation, metastasis, and chemoresistance [26]. In a study the role of circulating extracellular vesicles-derived lncRNA-GC1 as a biomarker for evaluating the efficacy of neoadjuvant chemotherapy (neoCT) in gastric cancer (GC) patients was investigated. LncRNA-GC1 levels correlated strongly with tumor burden and exhibited earlier dynamic changes compared to traditional gastrointestinal biomarkers during the first cycle of neoadjuvant chemotherapy (neoCT). Agreement between lncRNA-GC1 response and radiographic response was strong, indicating its potential as an early predictor of treatment efficacy. Furthermore, lncRNA-GC1 response was associated with improved disease-free survival and overall survival in GC patients undergoing neoCT, suggesting its utility as a prognostic marker [27]. Actin Filament Associated Protein 1-Antisense RNA 1 (AFAP1-AS1) has emerged as an oncogenic lncRNA. It is notably upregulated in multiple solid tumors and exerts its effects by modulating downstream genes and signaling pathways through interactions with microRNAs or direct binding to proteins. AFAP1-AS1 contributes to tumor cell proliferation, resistance to chemotherapy and apoptosis, maintenance of stemness, and enhancement of invasion and migration [28,29]. HOXA transcript at the distal tip (HOTTIP)-an oncogenic lnc-RNA which highly expressed in many cancers has a significant correlation with poor overall survival, increased incidence of lymph node metastasis and distant metastasis as well as higher tumor stage, suggesting a valuable biomarker for predicting poor prognosis in cancer patients [30,31].

Zinc Finger NFX1-Type Containing 1 Antisense RNA 1 (ZFAS1) is a long non-coding RNA located on chromosome 20q13.13, known for its involvement in regulating alveolar and epithelial cell differentiation in the mammary gland. It emerges as an oncogene across various cancer types, including colorectal cancer, gastric cancer, cholangiocarcinoma, hepatoblastoma, and others [32,33]. The TINCR gene is another lnc-RNA which Morgado-Palacin et revealed that TINCR acts as a tumor suppressor in squamous cell carcinoma (SCC) [34]. By contrast, Li et al in a meta-analysis unveiled high expression of TINCR correlates with larger tumor size and poor overall survival (OS) [35]. In addition, TINCR expression was elevated in colon cancer tissues and correlated with poor overall survival. TINCR expression also correlated with clinicopathological parameters. Knockdown of TINCR led to reduced proliferation and increased apoptosis, as well as decreased invasion and migration in colon cancer cell lines. Furthermore, increased autophagy was observed upon TINCR knockdown, indicated by Xu et al. [36].

The eight lncRNAs investigated in this study HOTIP, BANCR, ZFAS1, TINCR, GC1, AFAP1-AS1, FAM49B-AS, and lncUGC1 were selected based on a systematic review of the literature. This process prioritized candidates with established evidence of dysregulated expression in gastric cancer or other major gastrointestinal and solid tumors. Furthermore, their documented functional involvement in critical oncogenic pathways, including the regulation of cell proliferation, apoptosis, invasion, and metastasis, provided a strong biological rationale for their evaluation as potential noninvasive diagnostic biomarkers in the plasma of gastric cancer patients

In this study, we aim to investigate expression profiles of lncRNAs, including FAM49B-AS, AFAP1-AS1, HOTIP, ZFAS1, IncUGC, GC1, BANCR, and TINCR in gastric cancer patients’ plasma as well as to elucidate their associations with clinicopathological parameters of patient and their diagnostic value in detecting gastric cancer. This investigation might holds promise for the development of novel strategies for early detection and personalized management of gastric cancer, ultimately contributing to improved clinical outcomes and patient care.

2. Material and methods

2.1. Study population

This case-control study consists of 128 individuals diagnosed with gastric cancer and 128 healthy individuals (control group). Standard demographic, clinical, and pathological data were collected using a standardized questionnaire, including age, gender, cancer stage, tumor grade, metastatic status, and therapeutic interventions. All enrolled patients with GC were diagnosed by histopathological examination after radical resection or endoscopic biopsy. Inclusion criteria encompassed patients with a confirmed diagnosis of gastric cancer based on standard clinical, pathological, and laboratory criteria, with no therapeutic interventions administered at the time of sampling. The patient cohort (n = 128) was composed of a majority of newly diagnosed, treatment-naive individuals, alongside patients with a history of prior treatment. Specifically, 83 patients (64.8%) were newly diagnosed and had not received any prior cancer-directed therapy. The remaining 45 patients (35.2%) had a history of prior treatment. This subgroup primarily consisted of 28 patients (21.9%) who had undergone prior surgical resection only and 17 patients (13.3%) who had received both prior surgery and adjuvant chemotherapy. For all previously treated patients, blood samples were collected during routine follow-up visits, with a minimum of 3 months having elapsed since the completion of their last treatment, and before the initiation of any new line of therapy. The control group was selected in two ways, including non-hospitalized individuals and hospitalized patients with no evidence of any stomach disease or other malignancy, representing the same community as the study population. Furthermore, controls were age and gender-matched with the patients under investigation, and routine cancer marker laboratory test results (CEA, CA19–9) fell within normal ranges. Exclusion criteria included undergoing chemotherapy or surgery, the presence of gastric cancer, and related precancerous diseases (metaplasia) in the selected individuals as controls. The present study was approved by the Research Ethics Committee of the Kurdistan University Medical Sciences. Written informed consent forms were prepared and completed by participants following a comprehensive explanation of the study. Samples for this research were collected from two centers: laboratory of Imam Khomeini Hospital and the endoscopy center of Firouzgar Hospital, where 5 mL of whole blood samples were obtained from hospitalized patients and individuals referred by physicians for gastric cancer diagnosis and individuals defined as the controls according to inclusion and exclusion criteria. All sample collection were taken 2 years and experimental procedures took 6 months.

2.2. Tumor marker measurement

In this study, the measurement of tumor markers CEA (Carcinoembryonic Antigen) and CA19.9 (Carbohydrate Antigen 19–9) in serum samples was conducted using the Cobas e-411 instrument (Roche/Hitachi, Germany). Immediately after sample collecting the fresh serum were centrifuged and the assays for CEA and CA19.9 were performed according to the manufacturer’s instructions, utilizing specific reagents and protocols designed for the Cobas system.

2.3. RNA extraction and cDNA synthesis

Total RNA was extracted from serum samples collected from patients using the Trizol-Ls reagent (Ribo Ex™ LS, Gene All, South Korea), following the manufacturer’s instructions. Briefly, 250 μL of serum sample were lysed using 750 μL of RiboEx™ LS triazole solution. The lysates were then processed using spin columns to bind RNA, followed by washing steps to remove contaminants. Finally, RNA was eluted from the columns in RNase-free water and stored at −80°C until further analysis. cDNA synthesis was performed using the Parstous kit (Easy cDNA Synthesis Kit A101161, Iran) according to the manufacturers protocol. In brief, RNA extracted from serum samples was reverse transcribed into cDNA using oligo-dT primers and reverse transcriptase enzyme. The reaction mixture was incubated at 42–55°C for 1 hour followed by enzyme inactivation. The synthesized cDNA was then stored at −20°C.

2.4. RT-qPCR

Quantitative real-time polymerase chain reaction (RT-qPCR) was performed to analyze the expression levels of the selected long non-coding RNAs (lncRNAs) in the cDNA samples obtained from serum. The RT-qPCR reactions were carried out using the RealQ Plus 2x Master Mix Green (Cat. No.: A323402) on a Corbett Rotor Gene 6000 instrument. Primers specific for each lncRNA target and an endogenous control gene (GAPDH) were designed and synthesized by (Pishgam Company). The primer sequences and characteristics are listed in Table 1. Each RT-qPCR reaction contained 500ng of template cDNA, 1 μL of Reverse Transcriptase, 0.5 μM of Forward Primer, 0.5 μM of Reverse Primer, 10 μl of RealQ Plus 2x Master Mix, and Nuclease-free Water up to a total volume of 20 μl. The cycling conditions included an initial denaturation step at 95°C for 5 minutes, followed by 40 cycles of denaturation at 95°C for 30 seconds, annealing at 60°C for 30 seconds, and extension at 72°C for 30 seconds. The relative expression levels of the target lncRNAs were calculated using the comparative ΔΔCt method, with normalization to the endogenous control gene.

Table 1.

Specific primers of lncRnas.

Genes	Sequences	Product size	Annealing Tm
GAPDH	Forward: 5′‐CGCTGAGTACGTCGTGGAGTC −3′ Reverse: 5′‐ GCTGATGATCTTGAGGCTGTTGTC-3′	172 bp	60°C
HOTIP	Forward: 5′‐ GGGACTCAGAAAAGACGGCA-3′ Reverse: 5′‐ GTGGGAGATGCTCCTCATGG −3′	158 bp	59°C
BANCR	Forward: 5′‐ CAGAGTCAAACCTGAATCTCACC-3′ Reverse: 5′‐ CATCACAATGAAGAAAGCCTGGT-3′	122 bp	59°C
ZFAS1	Forward: 5′‐ GGAAAGAGAGCGTTTCGGGT −3′ Reverse: 5′‐ TAACGGGCAGGACAATAGCG-3′	161 bp	60°C
TINCR	Forward: 5′‐ TGTGGCCCAAACTCAGGGATACAT −3′ Reverse: 5′‐ AGATGACAGTGGCTGGAGTTGTCA-3′	213 bp	62°C
FAM49B-AS	Forward: 5′‐ GTAGAAAGAGCCAAGCAA-3′ Reverse: 5′‐ GGAAGCCAAGATCACATC −3′	163 bp	55°C
IncUGC1	Forward: 5′‐ AGCGTGGTCAGAGTGGTAGG-3′ Reverse: 5′‐ CAAAGCCAGAAAAGCCACTC-3′	156 bp	58°C
GC1	Forward: 5′‐ TGGGGTAACTTAGCAGTTTCAAT −3′ Reverse: 5′‐ GGCAAGCAGTAATCTTACATGACAC-3′	251 bp	59°C
AFAP1-AS1	Forward: 5′‐ AGCCTGTTGAATCAGCCAACTC-3′ Reverse: 5′‐ GTGTGCCTCAAAGGGAAGTGA −3′	196 bp	60°C

2.5. Statistical analysis

The collected data were analyzed using statistical software R (version 4.0.3). Descriptive statistics were utilized to summarize the demographic and clinical characteristics of the study population. Continuous variables were expressed as means ± standard deviations (SD). To compare the differences between groups, Student’s t-test or Mann-Whitney U test was used for continuous variables, depending on the distribution. For categorical variables, the chi-square test or Fisher’s exact test was applied, as appropriate. The association between lncRNA expression levels and clinical parameters was assessed using Spearman correlation coefficient. ROC curve analysis was applied to determine diagnostic value of lnc-RNA in gastric cancer detection. All statistical tests were two-sided, and a p-value < 0.05 was considered statistically significant.

3. Results

3.1. Population characteristics

In total, 256 cases were enrolled in this study, with 128 diagnosed with gastric cancer and 128 classified as healthy controls. Within the control group, gender distribution was 46% female and 54% male (p value > 0.05). The mean age for females was 57.48 years with a standard deviation of 5.32, while for males it was 56.23 years with a standard deviation of 12.1 (p value > 0.05). In the patient group, 43% were female, with a mean age of 61.48 years and a standard deviation of 8.05, whereas 57% were male, with a mean age of 59.12 years and a standard deviation of 6.65 (p value > 0.05). Additional tumor characteristics in the patient group are delineated in Table 2.

Table 2.

Tumor features and patients distribution.

Features	Values (count)	P value
Invasion Depth	T1 (8) T2 (17) T3 (44) T4 (59)	P= 0.003
TNM Stage	I (29) II (10) II (60) IV (29)	P= 0.01
Pathological Differentiation	Well (28) Moderate (91) Poor (9)	P= 0.001
Lymph Node Metastasis	Positive (77) Negative [](51)	P= 0.04
Tumor Size (Mean±SD, mm)	<40mm >40mm	P= 0.002

3.2. Serum level of tumor markers

In both groups, serum levels of CEA and CA19.9 were assessed. As anticipated, notable alterations were observed in the serum levels of both tumor markers in patients compared to the control group. As depicted in Figure 1, CEA levels were elevated in both gender in patients and irrespective of gender compared to the healthy individuals. Similarly, CA19.9 levels exhibited a significant increase in the patient group compared to the healthy controls, regardless of gender.

Figure 1.

Statistical analysis were used to compare the mean serum level of both tumor markers. Man Whitney test were applied to compare the mean level of groups. **= p < 0.001.

3.3. Lnc-RNAs expression analysis

In the present study, we evaluated the expression levels of eight long non-coding RNAs (lncRNAs) in both the patient and control groups. Our findings revealed no significant alterations in the expression rates of FAM49B-AS and lncUGC1 in the patient group compared to the healthy individuals (p > 0.05). Conversely, the remaining lncRNAs, including HPTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1, exhibited upregulation in the patients relative to the controls (p < 0.05). These results underscore the potential significance of these dysregulated lncRNAs in the context of gastric cancer pathology (Figure 2).

Figure 2.

Differential expression of long non-coding RNAs (lncRnas) in gastric cancer patients and healthy controls. The expression levels of eight lncRnas were assessed in both groups. While FAM49B-AS and lncUGC1 showed non-significant changes (p > 0.05) between patients and controls, HPTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1 were significantly upregulated (p < 0.05) in the patient group compared to control. Student t.Test was used to compare the mean expression level of each lncRNA in patients compared to control group. ns= not significant, *** = p value <0.0001.

3.4. Correlation analysis

3.4.1. Correlation of tumor markers, lncRnas and tumor features

A correlation matrix was constructed to investigate the relationships among tumor markers, lncRNAs, and tumor features in gastric cancer. Notably, no significant correlation was observed between tumor markers and the mean expression of lncRNAs. However, lncRNAs exhibited a significant positive correlation with each other, except for HPTTIP. Specifically, BANCR, ZFAS1, TINCR, FAM49B-AS, lncUGC1, and GC1 showed positive correlations, suggesting a coherent expression pattern in gastric cancer.

Interestingly, ZFAS1 exhibited a positive correlation with invasion depth, indicating its elevated expression in T4 stage tumors. Conversely, TINCR, FAM49B-AS, and lncUC1 displayed a negative correlation with TNM stage, suggesting downregulation in advanced stages and upregulation in early stages of gastric cancer. Furthermore, FAM49B-AS and lncUC1 demonstrated a significant negative correlation with lymph node metastasis, implying that higher expression levels may decrease the likelihood of lymph node metastasis. Additionally, FAM49B-AS exhibited a negative correlation with pathological differentiation, indicating that increased expression may lead to poorer differentiation. Notably, tumor size displayed a unique positive correlation with GC1, suggesting that elevated GC1 expression may contribute to increased tumor size (Figure 3).

Figure 3.

Figure 3 illustrates the heatmap displaying the correlation between tumor markers, the mean expression of lncRnas, and tumor features. The heatmap highlights a positive and significant correlation among a subset of lncRnas, while no significant correlation was observed between HOTTIP and the studied lncRnas. Notably, ZFAS1 and AGAP1-AS1 exhibited significant positive correlations with tumor features, specifically invasion depth and tumor size, respectively. Conversely, TINCR, FAM49B-AS, and lncUGC1 were lncRnas displaying significant negative correlations with tumor features, including TNM stage, lymph node metastasis, and pathological differentiation. This heatmap provides insights into the complex interplay between tumor markers, lncRnas, and tumor features in gastric cancer. *= p value <0.05, **=P value <0.001, ***= p value < 0.0001.

3.4.2. Correlation of age and gender with tumor marker, lncRnas and tumor features

Pearson correlation analysis revealed no significant correlation between gender and tumor markers, lncRNAs, or tumor features. Similarly, age showed no significant correlation with tumor markers; however, it exhibited significant correlations with certain lncRNA expressions. Specifically, age displayed a negative correlation with the expression of FAM49B-AS and lncUGC1, suggesting a reduction in their expression with advancing age. Conversely, age exhibited a positive correlation with GC1 expression, indicating an increase in its expression with age. Furthermore, age demonstrated a significant positive correlation with all studied tumor features. This suggests that with increasing age, individuals were observed to exhibit greater invasion depth, advanced TNM stage, lymph node metastasis, poorer pathological differentiation, and increased tumor size (Table 3). These findings underscore the potential influence of age on the progression and characteristics of gastric cancer

Table 3.

Correlation of gender and age with tumor markers, lncRnas expression and tumor features.

Features	Gender(correlation)	Gender (p value)	Age(correlation)	Age (p value)
CEA	−0.08	P=0.30	0.08	P=0.35
CA19.9	−0.09	P=0.34	0.14	P=0.11
HOTIP	−0.07	P=0.26	0.04	P=0.50
BANCR	−0.07	P=0.24	−0.05	P=0.34
ZFAS1	−0.05	P=0.40	0.06	P=0.31
TINCR	−0.09	P=0.11	−0.03	P=0.53
FAM49B-AS	−0.04	P=0.45	−0.20	P=0.001**
lncUGC1	−0.01	P=0.75	−0.18	P=0.002**
GC1	−0.09	P=0.12	0.13	P=0.03*
AFAP1-AS1	−0.09	P=0.11	0.11	P=0.05
Invasion Depth	0.028	0.75	0.70	<0.0001***
TNM stage	−0.0006	0.94	0.64	<0.0001***
Lymph Node Metastasis	−0.02	0.80	0.80	<0.0001***
Pathological Differentiation	0.07	0.39	0.74	<0.0001***
Tumor Size	0.09	0.26	0.29	P=0.0008***

3.5. Association of lncRNA expression with clinicopathological features

To further investigate the relationship between lncRNA levels and disease severity, a stratified analysis was performed to compare plasma lncRNA expression across key clinicopathological features. The detailed results of these analyses are provided in Supplementary Tables S1-S5. This analysis revealed distinct patterns of lncRNA expression associated with tumor progression. A subset of lncRNAs, including TINCR, FAM49B-AS, and lncUGC1, were significantly associated with earlier disease stages. Their expression levels were highest in patients with TNM Stage I disease and showed a significant decrease with advancing stage (Supplementary Table S1, all p < 0.001). This pattern was consistent for FAM49B-AS and lncUGC1, which also showed significantly lower expression in patients with positive lymph node metastasis (Supplementary Table S4, P&lt;0.001), and for FAM49B-AS, which was lower in poorly differentiated tumors (Supplementary Table S3, P&lt;0.001).

Conversely, other lncRNAs were associated with specific markers of tumor aggressiveness. ZFAS1 expression showed a strong, statistically significant increase with deeper tumor invasion (T-stage) (Supplementary Table S2, P&lt;0.001), consistent with our correlation analysis. Similarly, GC1 expression was significantly higher in patients with larger tumors ( > 40 mm) (Supplementary Table S5, p = 0.002). The expression of HOTIP, BANCR, and AFAP1-AS1 did not show a significant association with any of the clinicopathological features analyzed in this stratified manner. These findings suggest that different circulating lncRNAs may reflect distinct aspects of gastric cancer biology, with some indicating early-stage disease and others marking specific aggressive phenotypes.

3.6. Diagnostic value of selected plasma lncRnas for gastric cancer patients

ROC curve analysis was employed to assess the diagnostic utility of lncRNAs in detecting gastric cancer. Notably, lncUGC1 and FAM49B-AS exhibited non-significant specificity and sensitivity (confidence interval 0.41 to 0.56, 0.52–0.66 respectively) for gastric cancer detection (Table 4). In contrast, all other investigated lncRNAs demonstrated significant specificity and sensitivity (p < 0.0001) for distinguishing gastric cancer cases from controls (Figures 4 and 5).

Table 4.

Specificity and sensitivity of lncRNA for distinguishing gastric cancer cases from controls.

lncRNAs	Area Under ROC curve	95% confidence interval	P value
HOTIP	0.947	0.92–0.97	<0.0001
BANCR	0.923	0.89–0.95	<0.0001
ZFAS1	0.719	0.65–0.78	<0.0001
TINCR	0.988	0.97–0.99	<0.0001
FAM49B-AS	0.593	0.52–0.66	P=0.09
lncUGC1	0.487	0.41–0.56	P=0.71
GC1	0.994	0.98–0.99	<0.0001
AFAP1-AS1	0.992	0.98–0.99	<0.0001
Total	0.924	0.91–0.93	<0.0001

Figure 4.

ROC curve for lnc-RNA which had significant in differentiation of gastric cancer patients from healthy people.

Figure 5.

RUC curve for all studied lnc-RNAs. When individual value of lnc-RNAs were combined they showed high sensitivity and specificity in gastric patient differentiation, suggesting valuable lnc-RNA panel in gastric cancer detection.

3.7. Multivariable analysis and combined diagnostic model

To explore the interrelationships between biomarkers and to construct a combined diagnostic model, a multivariable analysis was performed. The detailed results of this analysis are presented in Supplementary File 2.

A preliminary factor analysis revealed that all eight lncRNAs were highly correlated, loading onto a single primary factor, while CEA and CA19.9 loaded onto a distinct second factor (Supplementary Table S6). Due to this high multicollinearity among the lncRNAs, a direct logistic regression model including all individual markers was not statistically feasible.

Therefore, a diagnostic model was constructed using the non-collinear traditional markers (CEA, CA19.9) and demographic variables. This model demonstrated excellent diagnostic performance, with an Area Under the Curve (AUC) of 0.988 (95% CI: 0.978–0.997) (Supplementary Figure S1). The model, detailed in Supplementary Table S7, correctly classified 93.75% of all cases (Supplementary Table S8), confirming the strong diagnostic power of the established biomarkers in this cohort. This analysis highlights the distinct information provided by the lncRNA panel versus the traditional markers and highlights the challenge of multicollinearity in combining highly related novel biomarkers.

3.7.1. Discussion

Gastric cancer remains a significant health challenge worldwide, with challenges in early diagnosis. In this study, we investigated well-known tumor markers for gastric cancer (CEA and CA19.9) and the expression profiles of lncRNAs in gastric cancer patients compared to healthy individuals. Our findings shed light on the potential diagnostic and prognostic significance of these lnc-RNAs in gastric cancer.

The discovery of noninvasive biomarkers represents a significant advancement in gastric cancer detection, offering several advantages over traditional diagnostic methods [37]. While conventional diagnostic modalities such as endoscopy and biopsy remain integral components of gastric cancer diagnosis, they are invasive procedures associated with inherent limitations, including patient discomfort, procedural risks, and sampling variability [38]. In contrast, noninvasive biomarkers present a promising alternative that addresses these shortcomings and offers unique benefits in terms of accessibility, and patient acceptance. Noninvasive biomarkers, such as circulating tumor markers and lncRNAs, can be readily assessed through minimally invasive procedures such as blood tests or liquid biopsy. Moreover, molecular alterations precede morphological and clinical changes in the progression of cancer [39], underscoring the importance of detecting these changes at the molecular level for early diagnosis and intervention, providing a window of opportunity for early intervention and improved patient outcomes. In addition, the inherent heterogeneity of cancer underscores the importance of adopting a comprehensive and multi-dimensional approach to diagnostic assessment. A panel of lncRNA measurements offers several advantages over single biomarker assays, including enhanced sensitivity, specificity, and predictive value. A lncRNA panel can capture the diverse molecular signatures associated with different cancer subtypes and stages, overcoming the limitations of single biomarker assays and reducing variability in diagnostic accuracy.

Our analysis for the first time revealed not only significant alterations in the serum levels of well-established tumor markers for detecting gastric cancer, CEA and CA19.9 in gastric cancer patients compared to controls, but also showed significant dysregulation and importance of lncRNAs in differentiation of gastric cancer from healthy individuals. HOTTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1 were found to be upregulated in gastric cancer patients, suggesting their potential roles as oncogenic drivers in gastric carcinogenesis. These lncRNAs previously have been shown to be upregulated in many cancers, including HOTTIP in oral squamous cell carcinoma [40], BANCR, ZFAS1,TINCR and AFAP1-AS1 in gastric cancer, making them critically important since these lnc-RNAs involve in escalate cell proliferation, and cancer cell migration [41,42–44]. One unique aspect of this study is revealing possible relationships between tumor markers, lncRNAs, and tumor features in gastric cancer. First, we observed a lack of significant correlation between tumor markers and the mean expression of lncRNAs. This suggests independent regulatory mechanisms governing the expression of these lncRNA in relation CEA and CA19.9 in gastric cancer. However, lncRNAs exhibited significant positive correlations with each other, indicating potential co-regulation or functional interactions in gastric carcinogenesis. Furthermore, our analysis identified specific correlations between lncRNAs and clinicopathological features of gastric cancer. ZFAS1 demonstrated a positive correlation with invasion depth, implicating its involvement in tumor invasion and metastasis. This is consistent with previous studies, showing ZFAS1 contribute to the metastatic behavior of cancer cells [45]. Mechanistically, this is important as ZFAS1 has been shown to elevates Matrix Metalloproteinases 14 and 16, which these MMP significantly cause cancer metastasis [46]. Additionally, ZFAS1 sponges some vital miRNAs, including miR-3924 [47], miR-892b [48], miR-135a-5p [49] and miR-497-5p [50] all of which play integral part in metastasis of cancer cells. Conversely, TINCR, FAM49B-AS, and lncUGC1 exhibited negative correlations with TNM stage and lymph node metastasis, they are highly upregulated in in early stage of the gastric cancer which make them potential biomarker for early detection, meanwhile, their higher expression may be found in case of lymph node metastasis. Regarding TINCR there is controversial issue in the context of cancer, since it has been shown to play the role of a tumor suppressor in pancreatic [51] and prostate cancer [52]. Nevertheless, other evidence indicated that TINCR significantly contribute to the development of colorectal cancer [53] and lung cancer [54]. These findings underscore the association between lncRNAs and tumor phenotypes in gastric cancer development and progression.

We also employed ROC curve analysis to evaluate the diagnostic potential of lncRNAs in gastric cancer detection. Remarkably, while lncUGC1 and FAM49B-AS did not exhibit significant specificity and sensitivity in gastric cancer detection, all other lncRNAs demonstrated significant diagnostic accuracy for distinguishing gastric cancer patients from healthy individuals. Specifically, TINCR, GC1 and AFAP1-AS1 indicated the highest both sensitivity and specificity. This is the first report of their importance in diagnostic application of gastric cancer. These findings highlight the promise of these three lncRNAs as potential biomarkers for gastric cancer diagnosis and highlight the need for further validation in larger cohorts. Additionally, upon lnc-RNAs value in patients and healthy people were combined and ROC curve analysis was performed we observed a significant sensitivity and specificity of their potentiality to diagnose gastric cancer patients. This suggests that these lnc-RNAs individually and together are highly efficient in distinguishing patient with gastric cancer in control group. Our results suggest that lncRNAs may serve as noninvasive biomarkers for early detection, diagnosis, and therapeutic stratification in gastric cancer. By applying the unique expression profiles of lncRNAs, clinicians may enhance the precision and efficacy of diagnostic and therapeutic interventions, leading to improved patient outcomes and personalized treatment strategies.

Interestingly, age demonstrated significant correlations with lncRNA expression and tumor features in gastric cancer patients. While no significant correlations were observed between gender and biomarker expression, age showed notable associations with FAM49B-AS, lncUGC1, and GC1 expression levels. These findings suggest age-related alterations in the molecular landscape of gastric cancer, with implications for disease diagnosis and management. Specifically, negative correlations between age and FAM49B-AS, lncUGC1, and positive correlation with GC1 expression highlight age-associated changes in the expression of these lncRNAs. Additionally, age exhibited significant positive correlations with various clinicopathological features, including invasion depth, TNM stage, lymph node metastasis, poor pathological differentiation, and increased tumor size. These correlations suggest that older individuals may present with more advanced disease characteristics, emphasizing the importance of age in gastric cancer prognosis and risk stratification.

Despite the valuable insights gained from our study, several limitations warrant consideration. Firstly, the sample size of our case-control may limit the generalizability of our findings, necessitating validation in larger, multi-center cohorts. Additionally, the retrospective nature of our study precludes causal inference, highlighting the need for prospective studies to elucidate the mechanistic underpinnings of lncRNA dysregulation in gastric cancer. Future research endeavors should also explore the functional roles of dysregulated lncRNAs in gastric cancer progression and investigate their potential as therapeutic targets.

In conclusion, our study provides comprehensive insights into the dysregulated expression of lncRNAs HOTTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1 in gastric cancer and their associations with clinicopathological features. We demonstrated the diagnostic potential of lncRNAs in gastric cancer detection and underscore their relevance as diagnostic indicators. Moving forward, further investigation into the functional roles of dysregulated lncRNAs and their clinical utility is warranted to harness their potential for improving gastric cancer management and patient outcomes. Further investigation should be performed to complete the follow-up process to study the prognostic value of these biomarkers.

Funding Statement

This work was supported by the Kurdistan University Of Medical Sciences [IR.MUK.REC.1403.101].

Article highlights

• Plasma levels of lncRNAs HOTIP, BANCR, ZFAS1, TINCR, GC1, and AFAP1-AS1 are significantly upregulated in gastric cancer patients.

• These circulating lncRNAs, particularly TINCR, GC1, and AFAP1-AS1, demonstrate high sensitivity and specificity for distinguishing gastric cancer cases from healthy controls.

• A panel of these plasma lncRNAs offers a promising avenue for developing a non-invasive diagnostic test for the early detection of gastric cancer.

Author contribution

Conceptualization and methodology were developed by Mohammad Bagher Khademerfan and Asaad Azarnezhad. Pouneh Pourfarzam was responsible for the investigation, including sample collection, all laboratory work, and data acquisition, and also contributed to the initial report preparation. Mohammad Bagher Khademerfan, Ramin Shakeri, and Reza Ghanbari contributed to the formal data analysis and review and editing of the manuscript. Asaad Azarnezhad supervised the study, prepared the final manuscript, and contributed to its review and editing. All authors made a significant contribution to the work reported, have drafted or substantially revised or critically reviewed the article, agreed on the journal for submission, reviewed and agreed on all versions of the article before submission and during revision (including the final version accepted for publication and any significant changes introduced at the proofing stage), and agree to take responsibility and be accountable for the contents of the article and to share responsibility to resolve any questions raised about the accuracy or integrity of the published work. All data were generated in-house, and no paper mill was used.

Disclosure statement

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Reviewer Disclosure

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval (Kurdistan University of Medical Sciences (ethical codes: IR.MUK.REC.1403.101).) and/or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved.

Data availability statement

All data generated or analyzed in this study are available upon reasonable request.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/17520363.2025.2542112