Clinical Significance of LncRNAs SOX2-OT and NEAT1 in Esophageal Squamous Cell Carcinoma

Clinical Significance of LncRNAs SOX2-OT and NEAT1 in Esophageal Squamous Cell Carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical Significance of LncRNAs SOX2-OT and NEAT1 in Esophageal Squamous Cell Carcinoma Rajiv Ranjan Kumar, Adrija Mohanta, Manjit Kaur Rana, Vivek uttam, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4134350/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Despite strides in diagnostic and therapeutic approaches for ESCC, patient survival rates remain relatively low. Recent studies highlight the pivotal role of long non-coding RNAs (lncRNAs) in regulating diverse cellular activities in humans. Dysregulated lncRNAs have emerged as potential diagnostic indicators across various cancers, including ESCC. However, further research is necessary to effectively leverage ESCC-associated lncRNAs in clinical settings. Understanding their clinical significance for ESCC diagnosis and their mechanisms can pave the way for more effective therapeutic strategies. Our qRT-PCR observations indicated significant downregulation of SOX2-OT and NEAT1 in ESCC blood samples ( SOX2-OT down by ~ 2.02-fold and NEAT1 down by ~ 1.53-fold). The decreased expression of SOX2-OT and NEAT1 shows promise in differentiating ESCC patients from healthy individuals, as demonstrated by Receiver Operating Characteristics (ROC) curves and Area Under the Curve (AUC) values (AUC: SOX2-OT = 0.736, NEAT1 = 0.621) for ESCC diagnosis. Subsequent investigations explored the relationship between aberrant SOX2-OT and NEAT1 expression in ESCC patients and various clinicopathological features, including age, gender, smoking habits, alcohol consumption, hot beverage intake, tumor grade, and TNM stages. In-depth in-silico analysis unveiled the involvement of SOX2-OT and NEAT1 in miRNA sponging through the mTOR and MAPK pathways. In contrast, co-expression network analysis identified genes co-expressed with these lncRNA targets. This groundwork lays the foundation for future endeavours aimed at identifying and predicting ESCC prognosis by leveraging SOX2-OT and NEAT1 . By thoroughly investigating the functions of these lncRNAs, we aim to deepen our understanding of their potential as diagnostic markers and their role in facilitating effective therapeutic interventions for esophageal squamous cell carcinoma (ESCC) within clinical contexts. SOX2-OT ESCC NEAT1 AUC ROC and clinical settings Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Esophageal cancer (EC) is the sixth most common cause of cancer-related deaths worldwide [ 1 , 2 ] and is fourth in the North Indian population [ 3 ]. Histologically, EC is divided into Esophageal Squamous Cell Carcinoma (ESCC), which comprises of around 80% of cases, with the remaining subset being adenocarcinoma. Unfortunately, because of the asymptomatic nature of the disease, the overall five-year survival rate of advance-stage esophageal squamous cell carcinoma patients remains less than 30% [ 4 ]. However, it has been reported that timely detection and proper therapeutic intervention can alleviate the five-year survival rate of cancer patients [ 5 ], which emphasizes the urgency of establishing biomarker-driven detection and therapeutic methods to revolutionize global EC management. In this context, we and others have previously demonstrated the utilities of non-coding RNAs (miRNAs and lncRNAs) as potent cancer biomarkers [ 6 ]. Long non-coding RNAs (lncRNAs) exceeding 200 nucleotides are conserved across species and play a vital role in many physiological processes of our body. They naturally interact with proteins, DNA, and many types of RNA (including mRNA, miRNA, and others), showing their potential in complex physiological processes including tumorigenesis [ 7 – 9 ]. Accumulating studies have indicated that they modulate several cancer-related signaling pathways, including the Wnt/β-catenin, PI3K/Akt/mTOR, Janus kinase/signal transducers and activators of transcription (JAK/STAT3), mitogen-activated protein kinase 1 (MAPK1), nuclear factor-B (NF-B), and NOTCH pathways [ 6 ].Additionally, as competing endogenous RNAs (ceRNAs), lncRNAs may also be able to regulate mRNAs by competitively sponging with miRNAs [ 10 , 11 ] and creating a network of lncRNA-miRNA-mRNA interactions specific to the tumor [ 12 ] Such networks have been investigated in various tumor types, including endometrial cancer [ 13 ], gastric cancer [ 14 ], and papillary renal cell carcinoma [ 15 ]. Likewise, numerous lncRNAs have been previously linked to ESCC, including DNM3OS [ 16 ], CCT1 [ 17 ], CASC9 [ 18 ], LINC00324 and LOC100507053 [ 6 ], SOX2-OT [ 6 , 19 ] and NEAT1 [ 20 ]. Similarly, in one of our previous studies, we showed 296 differentially expressed lncRNAs, in which 137 were downregulated while 159 were upregulated in ESCC patients compared to healthy control blood samples [ 6 ]. Among all lncRNAs, SRY-box transcription factor 2 - overlapping transcript ( SOX2-OT ) and Nuclear enriched abundant transcript 1 (NEAT1) were found to be significantly dysregulated in ESCC patient samples. LncRNA SOX2-OT (ENSG00000242808) is highly conserved and localized to the human chromosomal locus 3q26.33 [ 21 ]. It is located in the intron of the SOX2-OT gene, which contains at least five exons and produces an mRNA-like transcript. Single-nucleotide polymorphisms (SNPs) in the SOX2-OT gene have been associated with various diseases, such as mental illnesses, diabetic complications, and most importantly cancer [ 22 – 25 ]. It has been shown to function as a ceRNA in multiple malignancies such as prostate cancer [ 26 ], ovarian cancer [ 27 ], lung cancer [ 27 ], and laryngeal cancer [ 28 ] via modulating the SOX2-OT /miRNA/mRNA axes through several signaling pathways [ 19 , 26 , 29 , 30 ]. Additionally, NEAT1 (ENSG00000245532) is a large non-coding transcript that typically localizes in the nuclear paraspeckles [ 31 ], which are involved in different aspects of nuclear function [ 32 ], including functioning as a transcription factor and is transcribed from 11q13.1 loci [ 31 ]. Numerous human cancers, including breast cancer [ 33 , 34 ], colorectal cancer [ 35 ], liver cancer [ 36 ], gastric cancer [ 37 ], prostate cancer [ 38 ] and glioma [ 39 ], have been linked to aberrant expression of NEAT1 . However, since there has been a lack of understanding of the precise roles of SOX2-OT and NEAT1 in ESCC, as a pilot study, herein, we explored their regulatory and clinical potential in ESCC. We further observed that both SOX2-OT and NEAT1 have significant diagnostic and prognostic potential in ESCC patients. Additionally, through the in-silico analysis, we demonstrated that SOX2-OT and NEAT1 are involved in sponging miRNAs (miR-26a-5p and miR-449b-5p) via mTOR and MAPK pathways. Moreover, we observed several cancer-related molecular signals interacting with SOX2-OT and NEAT1 , which may be essential components controlling the development and progression of ESCC. MATERIALS AND METHODS 2.1 Clinical Sample Collection and Storage The approval for the present study was obtained from the Ethics Review Board of the Central University of Punjab and the Advanced Cancer Institute in Bathinda (CUPB/IEC/2018/12 and ERB/UCER/2019/4/17), which was carried out in line with the Declaration of Helsinki. According to the 8th edition of TNM staging developed by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC), pathologists used tissue samples to identify ESCC patients. The Tempus Blood RNA Tube (Cat. No. 4342792; Applied Biosystems, CA, USA) was used by the phlebotomist to collect the peripheral blood samples (3 ml) from newly diagnosed ESCC patients (Age ≥ 18) and healthy persons (Age ≥ 18). During the period of sample collection, details about the patient's complete medical history, including age, gender, smoking status, alcohol intake, consumption of hot beverages, tumor grade, and TNM stages, were also acquired. The 50 blood samples from ESCC patients and a control group of age- and sex-matched healthy individuals using already predefined set inclusion and exclusion criteria [ 39 ]. 2.2 LncRNA Isolation and cDNA Synthesis To investigate the expression levels of SOX2-OT and NEAT1 in the blood samples of ESCC patients, we used a QIamp RNA Blood mini kit (Cat. No. 52304, Qiagen, Inc., Valencia, CA, USA) to isolate lncRNAs from 3 mL blood samples of ESCC patients and age- and sex-matched healthy controls by following the manufacturer’s protocol. We evaluated the RNA purity, concentration, and quality using a Nanodrop UV-Vis Spectrophotometer 2000cc (Thermo Fisher Scientific, CA, USA). We synthesized cDNA using the RT2 First Strand Kit (Cat. No.: 330404, Qiagen, Inc., Valencia, CA, USA) as described previously [ 6 , 40 , 41 ]. 2.3 Expression analysis of candidate lncRNAs using quantitative Real-Time PCR (qRT-PCR) Validation of the SOX2-OT and NEAT1 endogenous expression was done using RT2 SYBR Green Master mix (Qiagen), respective primers (Qiagen), and template (cDNA) according to the manufacturer’s protocol on a QIAquant 96; 5 plex qRT-PCR (S/N:3107V-3324269; Qiagen Inc). As a template, we utilized 2 µl of cDNA, 6.25 µl of iTaq Universal SYBR Green, and 1 µl of 10 µM lncRNA-specific primers from Qiagen Inc. The total reaction volume was maintained up to 12.5 µl using nuclease-free water. The qRT-PCR cycling parameters for both SOX2-OT and NEAT1 were 95ºC for 10 minutes (holding stage), 95ºC for 5 seconds (denaturation), 60ºC for 1 minute (annealing), 72ºC for 2 minutes (melt curve), and increment of 2ºC upto 95ºC Every reaction was carried out three times. To determine the fold change values using the Livak technique, the Ct values of these lncRNAs were normalized using Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a reference gene. The normalized expression levels (∆Ct) of these lncRNAs were then used to construct scatter plots. The detailed methodology has been described in our previous paper [ 6 ]. 2.4 Receiver operating characteristic (ROC) curve The ROC curve is a statistical tool used to evaluate the discriminative power of a dichotomous diagnostic test [ 42 ]. The area under the receiver operating characteristic curves typically ranges from 0.5 to 1. The diagnostic effect is enhanced by the AUROC value's proximity to 1. The AUC values were categorized as poor, medium, or high accuracy for the ranges 0.5–0.7, 0.7–0.9, and > 0.9, respectively [ 43 ]. The diagnostic potential of SOX2-OT and NEAT1 in ESCC patients was then assessed using ROC curves that were generated using the normalized Ct values. 2.5 LncRNA target prediction and pathway enrichment analysis It is well established that cytoplasmic lncRNA acts as a ceRNA by harbouring multiple miRNAs binding sites, thereby regulating their downstream targets by "sponging" those miRNAs [ 44 ]. Therefore, to predict the miRNA-mRNA targets of SOX2-OT and NEAT1 , we utilized the following databases: lncRnome ( http://genome.igib.res.in/lncRNome/ ), RAID v2.0 (RNA Interactome) ( http://www.rna-society.org/raid/ ), Starbase ( http://starbase.sysu.edu.cn/ ), miRDB (microRNA database) ( http://mirdb.org/ ), TargetScan ( http://www.targetscan.org/vert_72/ ) for used to confirm the expected targets of SOX2-OT and NEAT1. Furthermore, the Kyoto Encyclopaedia of Genes and Genomes (KEGG) has been utilized to identify potential pathways altered by SOX2-OT and NEAT-1 in ESCC. 2.6 Co-expression networks of lncRNAs and mRNAs Co-expression gene study was carried out using a co-express database ( https://coxpresdb.jp/ ) [ 45 ]. Furthermore, using Cytoscape, a network of co-expressed genes was created. Additionally, we looked at the co-expressed genes' KEGG pathways and molecular locations. 2.7 Statistical analysis We utilized GraphPad Prism v8.0 (La Jolla, California, USA) for data analysis. The Mann-Whitney (non-parametric) test was used to assess differences in the expression levels of lncRNAs in cancer patients and healthy people's blood samples and expressed the data as ‘mean ± standard error mean (SEM)’. A student t-test was utilized in the remaining studies to evaluate the distinction between the two groups. Three independent times each sample was used to conduct each experiment in triplicate. In respect of statistical significance, the symbols ****, ***, **, and * represent p-values less than 0.0001, 0.001, 0.01, and 0.05, respectively, while ‘ns’ stands for p-values greater than 0.05, which are non-significant. RESULTS 4.1 LncRNAs differentially expressed in esophageal squamous cell carcinoma Previously, our group had demonstrated 296 differentially expressed lncRNAs in ESCC patients’ blood samples that may have the potential to be utilized as liquid biopsy markers in ESCC [ 6 ]. Taking clues from our previous study, herein, we have explored the expression of the SOX2-OT and NEAT1 lncRNAs in ESCC (n = 50). We used qRT-PCR to assess the SOX2-OT and NEAT1 expression levels for this. Following 40 cycles of qRT-PCR, we observed that SOX2-OT was expressed in only 36 out of 50 ESCC samples, and NEAT1 was expressed in 34 out of 50 ESCC samples. Further, we observed that SOX2-OT was significantly downregulated (fold-change = 2.02, p-value = 0.0001) [ Figure 1 A ] in blood samples of ESCC patients compared to healthy matched individuals. Similarly, NEAT1 was also down-regulated (fold change = 1.79, p-value = 0.0052) [ Figure 1 B ] in ESCC blood samples compared to matched healthy individuals. The downregulation of both SOX2-OT and NEAT1 suggest that both lncRNAs may act as tumor suppressors in ESCC patients. 4.2 Downregulated SOX2-OT and NEAT1 possess a good diagnostic potential in ESCC Using GEPIA online tools, we first examined how SOX2-OT and NEAT1 were expressed in relation to one another in esophageal squamous cell cancer. After that, we observed that SOX2-OT and NEAT1 have the potential to be used as clinical diagnostics, with Area under the ROC curve (AUC) values of 0.736 [ Figure 2 A ] [95% CI = 0.6479 to 0.8737; p-value = 0.0001] and 0.695 [ Figure 2 B ] [95% CI = 0.5701 to 0.8201; p-value = 0.0057] respectively. Additionally, we explored for the combined efficiency of the lncRNA SOX2-OT and NEAT1 panel in diagnosing ESCC. We observed that the combined Area under the ROC curve (AUC) value came out to be 0.6217 (95% confidence interval [CI] = 0.5245 to 0.7189; p-value = 0.0175]) [ Figure 2 C ] . The combined value of SOX2-OT and NEAT1 is lower than individual AUC values for SOX2-OT and NEAT1 . Therefore, we predict that SOX2-OT and NEAT1 individually may have a better diagnostic potential than being used as a combined diagnostic panel. 4.3 Association of SOX2-OT and NEAT1 expression with the lifestyle and clinicopathological status of ESCC patients Since it is a well-known fact that some lifestyle factors affect the pathogenesis of ESCCs, our next goal was to assess how altered SOX2-OT and NEAT1 levels related to the clinicopathological traits and lifestyle aspects of ESCC patients, including age, gender, tobacco use, alcohol use, consumption of hot drinks, tumor grade, and TNM stages. We found that ESCC patients' lifestyles and their clinicopathological features impacted SOX2-OT expression more significantly than healthy persons. Notably, we found a ~ 1.69-fold reduction in SOX2-OT expression in ESCC patients aged 18 to 50 years (n = 17; p-value = 0.0028), but no differences in SOX2-OT expression were found in ESCC patients older than 50 years (n = 19; p-value = 0.1871) when compared to age-matched healthy individuals. The expression of SOX2-OT did not significantly differ between the two age groups of ESCC patients, ( p-value = 0.3420) [ Fig. 3 A ] . The gender differences between the two groups of ESCC patients were also not discernible ( p-value = 0.7961) in SOX2-OT expression. However, compared to healthy male individuals, male ESCC patients demonstrated a ~ 2.30-fold downregulation of SOX2-OT expression (n = 19; p-value = 0.0018) [ Figure 3 B ] , In contrast, there was no discernible difference in the expression of SOX2-OT between female ESCC patients and healthy females (n = 17; p = 0.1086) [ Fig. 3 B ] . In addition, ESCC patients with a history of tobacco use displayed a ~ 1.85-fold downregulation of SOX2-OT (n = 17; p-value = 0.0008), while non-smokers displayed a ~ 2.38-fold downregulation (n = 19; p-value = 0.0001) compared to healthy people [ Figure 3 C ]. Smokers and non-smokers with tumors did not differ significantly from one another ( p-value = 0.7961) [ Fig. 3 C ] . Similar to this, ESCC patients with a history of alcohol use showed a ~ 1.85-fold downregulation (n = 22; p-value = 0.0030), whereas patients who were not alcoholics showed a ~ 2.4-fold downregulation (n = 14; p-value = 0.0001) compared to healthy people [ Figure 3 D ] . As opposed to this, no distinction between the two groups of ESCC patients was seen ( p-value = 0.2370) [ Fig. 3 D ] . Further, patients with a history of using hot beverages displayed a ~ 2.03-fold downregulation (n = 22; p-value = 0.0055), whereas patients without a history of consuming hot beverages displayed a ~ 1.72-fold downregulation (n = 14; p-value = 0.0093) as compared to healthy individuals. ( p-value = 0.7067) [ Fig. 3 E ] There was no discernible difference between the two groups of ESCC patients. There were no discernible changes between the groups of ESCC patients when we assessed the expression of SOX2-OT with different tumor grades [ Fig. 3 F ]. However, The TNM stages (I + II) and (III + IV) of ESCC patients demonstrated a significant difference between the two groups of ESCC patients ( p-value = 0.0128) [ Fig. 3 G ]. In keeping with the previous section, we specifically looked at the relationships between the dysregulated levels of NEAT1 and the clinicopathological traits and lifestyle factors, including age, gender, smoking, drinking, consuming hot beverages, tumor grade, and TNM stages of ESCC patients. According to statistical analysis, we discovered no discernible difference between the expression of NEAT1 in ESCC patients between the ages of 18 and 50 (n = 16, p-value = 0.4077) compared to age-matched healthy individuals. However, compared to the healthy individuals, patients over 50 demonstrated a ~ 2.44-fold downregulation in NEAT1 expression (n = 18, p-value = 0.0106). Moreover, there was a significant downregulation of ~ 3.04-fold in the expression of NEAT1 between the two age groups of ESCC patients (p = 0.0078) [ Figure 4 A ] . Similarly, we could not observe any significant difference in the expression of NEAT1 in ESCC females (n = 17, p-value = 0.3479), whereas ~ 2.32-fold downregulation was noted in ESCC males (n = 17, p-value = 0.0023) compared to male healthy controls. However, no significant difference in the expression of NEAT1 was also observed between the two gender groups of ESCC patients ( p-value = 0.2083) [ Figure 4 B ] . Additionally, in ESCC patients having a history of tobacco smoking, it was determined that there is no significant difference in NEAT1 expression in tobacco smokers (n = 9, p-value = 0.2584) as compared to their matched healthy individuals. However, ~ 1.89-fold downregulation of NEAT1 was observed in non-tobacco smokers (n = 25, p-value = 0.0036) as compared to healthy individuals. In addition, no significant difference was detected in smoker ESCC patients compared to non-smoker ESCC patients ( p-value = 0.5700) [ Figure 4 C ] . Moreover, based on the alcoholic status of ESCC patients, NEAT1 was found to be ~ 2.31-fold downregulated (n = 15, p-value = 0.0017) in non-alcoholic patients, while no significant difference in the expression of NEAT1 was observed in ESCC patients with a history of alcohol consumption as compared to the healthy individuals (n = 19, p-value = 0.1188). Likewise, the difference was also non-significant between the two groups of ESCC patients ( p-value = 0.1757) [ Figure 4 D ]. Next, ESCC patients with a history of hot beverage consumption (n = 21, p-value = 0.0545), as well as patients with no history of hot beverage consumption (n = 13, p-value = 0.3215), did not show any significant differences in the expression levels of NEAT1 as compare to healthy individuals. However, ~ 1.49-fold downregulation on the expression of NEAT1 was observed between the two groups of ESCC patients ( p-value = 0.0055) [ Figure 4 E ]. Furthermore, the expression of NEAT1 was also evaluated with the numerous tumor grades of ESCC patients, and it was observed that there was a ~ 2.88-fold downregulation in the expression of NEAT1 in patients with unknown tumor grade as compared to the patients with well-differentiated tumor (n = 23, p-value = 0.0151). However, there were no significant differences among the other groups of ESCC patients [ Figure 4 F ]. Similar results were obtained for the two groups of ESCC patients with the TNM stage (I + II) and (III + IV), which could not show any significant differences in the expression levels of NEAT1 ( p-value = 0.3723) [ Figure 4 G ] . By comparing the ESCC patients' lifestyles to those of healthy people, the findings presented above lead us to the conclusion that SOX2-OT and NEAT1 expression levels are influenced by lifestyle and seldom by clinicopathological characteristics. 4.4 SOX2-OT and NEAT1 target miRNAs and regulate various cancer-associated signaling pathways As we know, cytoplasmic lncRNAs act as ceRNA by sponging miRNA activity in the human genome. In this regard, our group had recently shown two models of the molecular sponging mechanism by lncRNAs viz, unidirectional and bidirectional. Several online databases were used to screen the molecular targets of SOX2-OT and NEAT1 (see materials and methods). Interestingly, we observed fifty-three miRNA targets of SOX2-OT from RAID v2.0 ( http://www.rna-society.org/raid2/ ), fifty-seven miRNA targets from RNAInter ( http://www.rnainter.org/ ), and hundred miRNA targets from the DIANA ( https://diana.e-ce.uth.gr/home ) databases. According to the DIANA, RAID v2.0, and RNA Inter databases, SOX2-OT's putative miRNA targets include fourteen common miRNAs [ Figure 5 A ]. One hundred fifteen mRNA targets of has-miR-26a-5p predicted from Starbase ( http://starbase.sysu.edu.cn/ ), miRBD ( http://mirdb.org/ ), TargetScan ( http://www.targetscan.org/vert_72/ ) and RAID ( http://www.rna-society.org/raid2/ ) databases as shown in [ Figure 5 ]. Additionally, GO analysis was used to evaluate the miRNA- SOX2-OT axis's associated biological, molecular, cellular, and KEGG pathway activities. In each domain, we chose the top fifteen enriched GO phrases. Four of them were shown to participate in several biological processes, including cell migration, the mitotic cell cycle, cell cycle regulation, and the cell cycle process [ Figure 5 C ]. Similarly, cellular processes like microtubule organization and intracellular protein-containing complex are influenced by molecular processes, including protein dimerization activity, Guanyl nucleotide binding, and RNA binding [ Figure 5 D ]. Additionally, we demonstrated that KEGG pathways in cancer were enriched for RNA degradation, the mTOR signaling pathway, and ubiquitin-mediated proteolysis [ Figure 5 E ]. Next, we investigated the molecular targets of NEAT1. We observed 437 miRNA targets from the Starbase database, eight miRNA targets from the RNAInter database, and two miRNA targets from RAID v2.0. Two common miRNA targets were found to be hsa-miR-449b-5p and hsa-miR-106a-5p [Figure 6 A]. 97 mRNA targets of has-miR-449b-5p were predicted from Starbase, miRBD, Target Scan, and RAID databases, as shown in Fig. 6 B. In order to evaluate the linked biological, molecular, and cellular processes of the hsa-miR-449b-5p- NEAT1 axis, GO analysis was also used. The top 15 enriched GO items in each domain were chosen. Among them, hsa-miR-449b-5p and hsa-miR-106a-5p were discovered to be involved in several biological activities, such as the binding of transcription factors, the binding of kinase activity RNA, and cell adhesion molecule binding [ Figure 6 C ]. Similarly, miR-449b-5p and miR-106a-5p also affect cellular processes such as ribonucleoprotein complex, microtubule organizing, endoplasmic reticulum, mitochondrion, etc. [ Figure 6 D ] . Additionally, we found that miR-449b-5p and hsa-miR-106a-5p are enriched in the MAPK signaling pathway, endocytosis pathway, cell cycle, and regulation of actin cytoskeleton pathways in cancer [ Figure 6 E ]. Overall, the above data suggest that the downregulation of SOX2-OT and NEAT1 may be involved in the advancement of ESCC by targeting miRNAs and mRNAs by altering various pathways involved in carcinogenesis. 4.5 SOX2-OT and NEAT1 were regulated by Co-expression networks of mRNAs and lncRNAs Using co-expression networks, we found genes that are co-expressed with lncRNA and might serve as lncRNA targets. Based on this concept, we used Cytoscape and COXPRES db. Ver. 8.1 ( https://coxpresdb.jp/ ) to visualize the network of two lncRNAs ( SOX2-OT and NEAT1 ). Each lncRNA was found to have relationships with both mRNA and other lncRNAs in the network. Notably, seven lncRNAs SOX21 antisense divergent transcript 1 ( SOX21-AS1) , POU3F3 adjacent non-coding transcript 1 (PANTR1) , FEZF1 antisense RNA 1 (FEZF1-AS1) , long intergenic non-protein coding RNA 844 ( LINC00844) , sciatic injury induced lincRNA up regulator of SOX11 (SILC1) , long intergenic non-protein coding RNA 1896 (LINC01896) and ARHGEF26 antisense RNA 1 ( ARHGEF26-AS1) and forty four mRNAs, sex-determining region Y-box 2 (SOX2), SRY-box transcription factor 21(SOX21), sex-determining region Y-box 1 (SOX1), peripheral myelin protein 2 (PMP2), proteolipid protein 1 ( PLP1 ), fibroblast growth factor 12 ( FGF12 ), fatty acid binding protein 7 ( FABP7 ), aquaporin-4 (AQP4), receptor protein-tyrosine kinase ErbB-4 ( ERBB4 ), generalized anxiety disorder 2-item ( GAD-2 ), glutamate metabotropic receptor 3 (GRM3) and cell adhesion molecule 2 ( CADM2) etc. were anticipated to express alongside SOX2-OT. Among these, SOX2, SOX21, and SOX21-AS1 were co-expressed with SOX2-OT in the network in a direct manner. In addition, we found that several mRNAs, including SOX2, ZNF536 HESS, ASGL1, PRR18, AMER2, NKX6-2, TOX3, ASXL3, CXXC4, and ESRRG, were localised in the nucleus (as represented by purple balls) and four mRNAs were localised in the Plasma membrane (as shown by dark blue balls) [ Figure 7 A ] . Likewise, seventeen lncRNAs LINC00894 , ASMTL antisense RNA 1 (ASMTL-AS1), LINC00893, LOC107983998, LOC105373102, LOC107984338, LOC107984754, LOC100289230, LOC101928762 , PSMA3 antisense RNA 1 (PSMA3-AS1) , AP1G2 antisense RNA 1 (AP1G2-AS1), LINC01004, LOC107984203, LINC00115, LOC105374298, LINC01000 and LINC02603 co-expressed with NEAT1 on the network. Moreover, various mRNAs, RNA-binding region-containing protein 3 (RNPC3), zinc finger RANBP2-type containing 2 (ZRANB2), zinc finger C3H1 domain-containing protein (ZFC3H1), arginine and glutamate-rich 1 (ARGLU1), heterogeneous nuclear ribonucleoprotein A3 (HNRNPA3), amyloid-beta A4 precursor protein-binding family B member 3 (APBB3), heat shock transcription factor 4 (HSF4), SUGP2 and protein phosphatase 1 regulatory subunit 3B (PPP1R3B) etc., nine mRNAs ( RNPC3, ZRANB2, ZFC3H1, ARGLU1, HNRNPA3, APBB3, HSF4, SUGP2 and PPP1R3B ) localised in the nucleus (as shown by purple balls) and one mRNA, vacuole membrane protein 1 ( VMP1 ) were found to be localized in the plasma membrane (as shown by the dark blue ball) [ Figure 7 B ]. Altogether, our findings imply that dysregulation of the lncRNAs SOX2-OT and NEAT1 in ESCC simultaneously influences the expression of various other lncRNAs and mRNAs implicated in critical signaling pathways in the human biological system. By regulating the impacted gene expression along with SOX2-OT and NEAT1 , this method may assist in developing a potential therapeutic strategy. DISCUSSION Although detection methods for esophageal cancer have improved, its high incidence and mortality rate still persist [ 46 ]. Therefore, it is crucial to investigate the development of esophageal cancer and identify molecular markers linked to early detection and prognosis. Currently, ESCC diagnosis relies on invasive endoscopy and uncomfortable histopathological biopsy, underscoring the dire need for a blood-based circulating biomarker to enhance ESCC identification and management. Notably, as high-throughput transcriptome research becoming more common, innumerable lncRNAs have been revealed to play critical roles in cancer genesis. Because of their crucial roles in carcinogenesis, growth, progression and metastasis, lncRNAs can function as potential novel biomarkers or targets for cancer early detection and therapy [ 47 , 48 ]. Furthermore, when paired with numerous clinicopathological factors, the state of each individual patient can be determined with greater precision, allowing for more precise and tailored treatment formulation for each individual. In this respect, we demonstrated that lncRNAs SOX2-OT and NEAT1 significantly downregulated in ESCC patient's blood samples compared to healthy matched control samples (Fig. 1 ). Recent research has also shown that SOX2-OT and NEAT1 dysregulation is a major factor in the emergence of most malignancies, including NSCLC [ 49 , 50 ], triple-negative breast cancer (TNBC) [ 51 ] and ovarian cancer [ 52 ]. Numerous investigations in the field of cancer research have established the functions of SOX2-OT and NEAT1 [ 53 ]. For example, one group has demonstrated that by targeting the miR-369-3p/CFL2 axis, SOX2-OT accelerates cell division and migration in prostate cancer [ 26 ]. In a similar study, by modulating the miR-452-5p/HMGB3 axis, SOX2-OT knockdown delays the progression of prostate cancer in vivo [ 30 ]. Another ceRNA axis, SOX2-OT /miR-30d-5p/PDK1, involving SOX2-OT influences NSCLC cell proliferation, migration, and invasion [ 54 ]. The ERK signaling pathway and the miR192-5p/RAB2A axis are regulated by SOX2-OT [ 29 ]. SOX2-OT knockdown could increase apoptosis and decrease laryngeal cancer cell proliferation, migration, and invasion by focusing on miR-654 [ 28 ]. On the other hand, the etiology of numerous human malignancies is significantly influenced by NEAT1 [ 55 ]. In a study, it was shown that poorer clinicopathological lung cancer characteristics and its abnormal expression are tightly associated with each other [ 56 ]. NEAT1 , in accordance with another study, encourages lung cancer cells to proliferate and spread [ 57 ]. Moreover, NEAT1 was involved in the development of lung cancer and the invasion of cytotoxic T-cells by binding to DNA-methyltransferase 1 (DNMT1) and blocking the P53 and cGAS/STING pathways [ 58 ]. Interestingly, Teng et al. discovered that SOX2-OT is linked to specific clinical pathological parameters, including tumor size and lymph node metastasis [ 59 ]. In our investigation, we used blood samples from ESCC patients to investigate the diagnostic biomarkers SOX2-OT and NEAT1 . Based on the previously published data [ 6 ], we designed this investigation to discover potential blood-based biomarkers for ESCC diagnosis. Furthermore, it is well accepted that a number of extrinsic lifestyle factors, such as the consumption of hot beverages, the amount of fresh food and vegetables, and obesity, play a substantial part in the etiology of ESCC. In fact, earlier research found a relationship between their specific lifestyle choices and verified lncRNAs in cancer patients. Unfortunately, there is no evidence tying them to individuals with ESCC. We observed that SOX2-OT and NEAT1 have the potential to be used as clinical diagnostics, with Area under the ROC curve values of 0.736 [ Figure 2 A ] [95% CI = 0.6479 to 0.8737; p-value = 0.0001] and 0.638 [ Figure 2 B ] [95% CI = 0.5060 to 0.7717; p-value = 0.0490] respectively. As a result, we were curious to learn how the SOX2-OT and NEAT1 expressions related to the clinicopathological traits and lifestyle status of ESCC patients and the diagnostic and predictive potential of lncRNAs. Interestingly, we observed downregulated expression of SOX2-OT linked with the age (18 ≤ 50 years) of the ESCC patients compared to age-matched healthy individuals [ Figure 3 A ] , which suggests that the age below 50 years might affect the levels of SOX2-OT expressions. However, no difference was observed in SOX2-OT expression in the ESCC patients of two age groups [ Figure 3 A ] . Further, our study found that ESCC patient's gender (male) was associated with SOX2-OT expression compared to healthy individuals [ Figure 3 B ] . In contrast to healthy persons, we found that SOX2-OT expression was associated with ESCC patients who smoked, drank alcohol, used hot beverages, and were in advanced TNM stages. This finding suggests that these factors may influence SOX2-OT expression in ESCC patients [ Figure 3 C, 3 E, and 3 G ] . We could not detect any correlation between increasing tissue grades and SOX2-OT expression in the ESCC group [ Figure 3 F ] . Next, we analyzed the association of the dysregulated levels of NEAT1 with the clinicopathological characteristics and lifestyle factors. We found a downregulated expression of NEAT1 linked with age (> 50 years) of ESCC patients compared to age-matched individuals. Moreover, NEAT1 expression was significantly downregulated in ESCC patients of > 50 years age as compared to patients of < 50 years. In contrast to the healthy individuals, we found that NEAT1 expression was associated with ESCC patients' gender, who smoked and drank alcohol [Figure 4 B to 4 D ] . This suggests that these factors may modulate the expression of NEAT1 in ESCC patients, but these factors were not correlated within ESCC patients. We also observed that NEAT1 expression were correlated with ESCC patients who consumed hot beverages as compared to those who did not [ Figure 4 E ] . We could not detect any correlation between increasing tissue grade and TNM stages and NEAT1 expression in the ESCC group [ Figure 4 F to 4 G ]. Increasing evidence points to the possibility that lncRNAs could operate as molecular sponges, mimic miRNAs, and influence biological pathways by influencing the mRNA targets downstream of miRNAs [ 11 , 60 ], t hrough the sponging of miRNAs like miR-194-5p [ 61 ], members of the miR-200 family, miR-146b-5p [ 62 ], miR-146b-5p [ 50 ], miR-194-5p, and miR-122 [ 63 ], SOX2-OT and NEAT1 have been identified as oncogenes in a number of malignancies. In regard to this, we performed a bioinformatical analysis using an appropriate data set and predicted the miRNA targets (miR-26a-5p and miR-449b-5p) of lncRNAs SOX2-OT and NEAT1 respectively. Further, to better understand the molecular mechanism of SOX2-OT and NEAT1 in the development of ESCC, we were interested in identifying the downstream target genes of miR-26a-5p and miR-449b-5p. Most importantly, the combined use of SOX2-OT and NEAT1 results in a lower AUC value compared to their individual AUC values; hence, the diagnostic potential of SOX2-OT and NEAT1 as standalone entities is expected to exceed their collective efficacy in a combined diagnostic panel. We ascertained the complete profiling of circulating lncRNAs SOX2-OT and NEAT1 in order to validate a liquid biopsy biomarker for ESCC diagnosis in clinical settings. Conclusion, Future Aspects, and Limitations of the study This study provides evidence for the dysregulation of lncRNA SOX2-OT and NEAT1 in ESCC and its potential to be used as a diagnostic biomarker in the future. Furthermore, the moderate discriminatory power of SOX2-OT and NEAT1 in distinguishing ESCC patients from healthy individuals highlights its potential as a non-invasive biological marker. The association of SOX2-OT and NEAT1 expression with lifestyle factors suggests a possible link between lifestyle factors and lncRNAs ( SOX2-OT and NEAT1 ) dysregulation in ESCC. These findings indicate that lifestyle interventions may impact lncRNAs (SOX2-OT and NEAT1) expression and potentially influence ESCC development. However, further research is needed to elucidate the functional role of SOX2-OT and NEAT1 in ESCC and the underlying mechanisms. Additionally, larger studies involving diverse populations are warranted to validate the precise diagnostic potential of these lncRNAs and to explore their association with other clinicopathological characteristics of ESCC. Therefore, in this pilot study, SOX2-OT and NEAT1 have been identified as potential markers that can be used to detect ESCC in a non-invasive manner. This finding offers an alternative method to traditional tissue biopsy by utilizing circulating lncRNAs for diagnosing ESCC patients. However, to apply these results in clinical settings, conducting studies with larger cohort sizes and validating the identified molecular targets through luciferase reporter assay. Further research and experiments are needed to thoroughly understand the pathways associated with SOX2-OT and NEAT1. Declarations Ethics statement The studies involving human participants were reviewed and approved by the Ethics Review Board of Baba Farid University of Health Sciences, Faridkot (ERB/UCER/2019/4/17), and the Institutional Ethics Committee of Central University of Punjab, Bathinda (CUPB/IEC/2018/12). The patients/participants provided their written informed consent to participate in this study. Author Contributions: A.J. conceived the topic for this review. All the authors contributed to the article and approved the submitted version. Funding: Conflicts of Interest: The authors declare no conflict of interest. References Ferlay J, et al. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Aug, 2024 Reviews received at journal 07 Aug, 2024 Reviews received at journal 07 Aug, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers invited by journal 31 Mar, 2024 Editor assigned by journal 31 Mar, 2024 Submission checks completed at journal 31 Mar, 2024 First submitted to journal 20 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4134350","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286554483,"identity":"400608e4-0744-435d-a406-d5a58fb21658","order_by":0,"name":"Rajiv Ranjan Kumar","email":"","orcid":"","institution":"Non-Coding RNA and Cancer Biology Laboratory, Department of Zoology, Central University of Punjab, Bathinda 151401, Punjab, 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05:44:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4134350/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4134350/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54115334,"identity":"4bc65375-f165-4811-a5ce-80fa942fc66f","added_by":"auto","created_at":"2024-04-04 19:30:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54675,"visible":true,"origin":"","legend":"\u003cp\u003eExpression profile of lncRNAs in ESCC patient’s blood sample. \u003cstrong\u003e(A)\u003c/strong\u003e Normalized expression of \u003cem\u003eSOX2-OT\u003c/em\u003e (∆Ct values). \u003cstrong\u003e(B)\u003c/strong\u003eNormalized expression of \u003cem\u003eNEAT1\u003c/em\u003e (∆Ct values).\u003c/p\u003e","description":"","filename":"OnlineFigure1Final.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/f5b70e8562fec5517e42257f.png"},{"id":54115332,"identity":"99c099e0-d99c-4fcb-b83c-ca2205263368","added_by":"auto","created_at":"2024-04-04 19:30:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57824,"visible":true,"origin":"","legend":"\u003cp\u003eDiagnostic potential of lncRNAs in ESCC patient’s blood sample. \u003cstrong\u003e(A)\u003c/strong\u003e ROC Curve to demonstrate the diagnostic potential of \u003cem\u003eSOX2-OT\u003c/em\u003e. \u003cstrong\u003e(B)\u003c/strong\u003e ROC Curve to demonstrate the diagnostic potential of \u003cem\u003eNEAT1\u003c/em\u003e. \u003cstrong\u003e(C) \u003c/strong\u003eROC Curve to demonstrate the diagnostic potential of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003eas a panel.\u003c/p\u003e","description":"","filename":"OnlineFigure21.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/abf49911beaaf08809c59bd8.png"},{"id":54115333,"identity":"0af4df4b-ce4b-4bc8-a6e2-995bc63693fa","added_by":"auto","created_at":"2024-04-04 19:30:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":139138,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation of \u003cem\u003eSOX2-OT\u003c/em\u003eexpression with ESCC patients’ lifestyle status and clinicopathological characteristics compared to healthy individuals. \u003cstrong\u003e(A)\u003c/strong\u003e Age of ESCC patient. \u003cstrong\u003e(B)\u003c/strong\u003eGender of ESCC patients. \u003cstrong\u003e(C)\u003c/strong\u003e Tobacco smoking status of ESCC patients. \u003cstrong\u003e(D)\u003c/strong\u003eAlcoholic status of ESCC patients. \u003cstrong\u003e(E)\u003c/strong\u003eConsumption of hot beverages status. \u003cstrong\u003e(F)\u003c/strong\u003eHistopathological grading of the ESCC patients. \u003cstrong\u003e(G)\u003c/strong\u003e TNM staging of the ESCC patients. Bar graphs represents the normalized expression of \u003cem\u003eSOX2-OT\u003c/em\u003e in ESCC patients compared to healthy individuals. The data are expressed as mean ± SEM where *represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05, **represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.01, ***represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.001, and ****represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.0001 calculated using unpaired (Mann-Whitney test) and paired t-tests.\u003c/p\u003e","description":"","filename":"OnlineFigure31.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/517fdb2841e1e1ea000d281f.png"},{"id":54115337,"identity":"50739003-915e-43d4-8819-66fc92c07ab6","added_by":"auto","created_at":"2024-04-04 19:30:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98913,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation of \u003cem\u003eNEAT1\u003c/em\u003eexpression with ESCC patients’ lifestyle status and clinicopathological characteristics compared to healthy individuals. \u003cstrong\u003e(A)\u003c/strong\u003e Age of ESCC patient. \u003cstrong\u003e(B)\u003c/strong\u003eGender of ESCC patients. \u003cstrong\u003e(C)\u003c/strong\u003e Tobacco smoking status of ESCC patients. \u003cstrong\u003e(D)\u003c/strong\u003eAlcoholic status of ESCC patients. \u003cstrong\u003e(E)\u003c/strong\u003eConsumption of hot beverages status. \u003cstrong\u003e(F)\u003c/strong\u003eHistopathological grading of the ESCC patients. \u003cstrong\u003e(G)\u003c/strong\u003e TNM staging of the ESCC patients. Bar graphs represents the normalized expression of \u003cem\u003eNEAT1\u003c/em\u003e in ESCC patients compared to healthy individuals. The data are expressed as mean ± SEM where *represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05, **represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.01, ***represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.001, and ****represents \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.0001 calculated using unpaired (Mann-Whitney test) and paired t-tests.\u003c/p\u003e","description":"","filename":"OnlineFigure42.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/c3297c3e5448db99abfab7f6.png"},{"id":54115339,"identity":"1fa46fa6-d8a5-43a4-b8e2-00a3c0ae2d33","added_by":"auto","created_at":"2024-04-04 19:30:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":142437,"visible":true,"origin":"","legend":"\u003cp\u003eIn-silico target prediction for \u003cem\u003eSOX2-OT\u003c/em\u003eusing online databases. \u003cstrong\u003e(A)\u003c/strong\u003e 14 common miRNAs were predicted by the DIANA, RAID v2.0, and RNA Inter databases to be the likely miRNA targets of \u003cem\u003eSOX2-OT.\u003c/em\u003e \u003cstrong\u003e(B) \u003c/strong\u003e115 mRNA targets of hsa-miR-26a-5p predicted from Starbase, miRBD, Target Scan, and RAID databases. \u003cstrong\u003e(C-E) \u003c/strong\u003eGene Ontology molecular process, cellular process and KEGG pathway of predicted target hsa-miR-26a-5p of \u003cem\u003eSOX2-OT.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure51.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/95ac7ec84081b8e8a693ecdd.png"},{"id":54115336,"identity":"e2e061ad-096c-4b99-9e5e-546dbaec1332","added_by":"auto","created_at":"2024-04-04 19:30:54","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":149544,"visible":true,"origin":"","legend":"\u003cp\u003eIn-silico target prediction for \u003cem\u003eNEAT1\u003c/em\u003e using online databases. \u003cstrong\u003e(A)\u003c/strong\u003e 2 common miRNAs were predicted by the Starbase, RAID v2.0, and RNA Inter databases to be the likely miRNA targets of \u003cem\u003eNEAT1.\u003c/em\u003e \u003cstrong\u003e(B)\u003c/strong\u003e97 mRNA targets of hsa-miR-449b-5p were predicted from Starbase, miRBD, Target Scan and RAID databases. \u003cstrong\u003e(C-E) \u003c/strong\u003eGene Ontology molecular process, cellular process and KEGG pathway of predicted target hsa-miR-449b-5p of \u003cem\u003eNEAT1.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"OnlineFigure62.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/6711cac284c383b2db1ddfe4.png"},{"id":54115335,"identity":"b4bf4742-5813-49fe-8c1b-9d942173505f","added_by":"auto","created_at":"2024-04-04 19:30:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":161691,"visible":true,"origin":"","legend":"\u003cp\u003eCo-expression network of \u003cem\u003eSOX2-OT\u003c/em\u003eand \u003cem\u003eNEAT1\u003c/em\u003e. \u003cstrong\u003e(A) \u003c/strong\u003eA total\u003cstrong\u003e \u003c/strong\u003eof\u003cstrong\u003e \u003c/strong\u003eseven\u003cstrong\u003e \u003c/strong\u003elncRNAs and various mRNAs interact with \u003cem\u003eSOX2-OT\u003c/em\u003e. \u003cstrong\u003e(B) \u003c/strong\u003eA total of seventeen lncRNAs and various mRNAs interact with \u003cem\u003eNEAT1\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"OnlineFigure7.png","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/68ea7e68a8b868e16a01590c.png"},{"id":54116020,"identity":"e5e7bc1e-8498-4461-a880-4ec679d1ab25","added_by":"auto","created_at":"2024-04-04 19:38:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2105575,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4134350/v1/90661cb1-e266-422d-935c-413b64eb38dc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Significance of LncRNAs SOX2-OT and NEAT1 in Esophageal Squamous Cell Carcinoma","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eEsophageal cancer (EC) is the sixth most common cause of cancer-related deaths worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and is fourth in the North Indian population [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Histologically, EC is divided into Esophageal Squamous Cell Carcinoma (ESCC), which comprises of around 80% of cases, with the remaining subset being adenocarcinoma. Unfortunately, because of the asymptomatic nature of the disease, the overall five-year survival rate of advance-stage esophageal squamous cell carcinoma patients remains less than 30% [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, it has been reported that timely detection and proper therapeutic intervention can alleviate the five-year survival rate of cancer patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], which emphasizes the urgency of establishing biomarker-driven detection and therapeutic methods to revolutionize global EC management.\u003c/p\u003e \u003cp\u003eIn this context, we and others have previously demonstrated the utilities of non-coding RNAs (miRNAs and lncRNAs) as potent cancer biomarkers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Long non-coding RNAs (lncRNAs) exceeding 200 nucleotides are conserved across species and play a vital role in many physiological processes of our body. They naturally interact with proteins, DNA, and many types of RNA (including mRNA, miRNA, and others), showing their potential in complex physiological processes including tumorigenesis [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Accumulating studies have indicated that they modulate several cancer-related signaling pathways, including the Wnt/β-catenin, PI3K/Akt/mTOR, Janus kinase/signal transducers and activators of transcription (JAK/STAT3), mitogen-activated protein kinase 1 (MAPK1), nuclear factor-B (NF-B), and NOTCH pathways [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].Additionally, as competing endogenous RNAs (ceRNAs), lncRNAs may also be able to regulate mRNAs by competitively sponging with miRNAs [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and creating a network of lncRNA-miRNA-mRNA interactions specific to the tumor [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] Such networks have been investigated in various tumor types, including endometrial cancer [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], gastric cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and papillary renal cell carcinoma [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Likewise, numerous lncRNAs have been previously linked to ESCC, including \u003cem\u003eDNM3OS\u003c/em\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], \u003cem\u003eCCT1\u003c/em\u003e [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], \u003cem\u003eCASC9\u003c/em\u003e [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], \u003cem\u003eLINC00324\u003c/em\u003e and \u003cem\u003eLOC100507053\u003c/em\u003e [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], \u003cem\u003eSOX2-OT\u003c/em\u003e [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and \u003cem\u003eNEAT1\u003c/em\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, in one of our previous studies, we showed 296 differentially expressed lncRNAs, in which 137 were downregulated while 159 were upregulated in ESCC patients compared to healthy control blood samples [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Among all lncRNAs, SRY-box transcription factor 2 - overlapping transcript (\u003cem\u003eSOX2-OT\u003c/em\u003e) and Nuclear enriched abundant transcript 1 (NEAT1) were found to be significantly dysregulated in ESCC patient samples. LncRNA \u003cem\u003eSOX2-OT\u003c/em\u003e \u003cb\u003e(ENSG00000242808)\u003c/b\u003e is highly conserved and localized to the human chromosomal locus 3q26.33 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. It is located in the intron of the \u003cem\u003eSOX2-OT\u003c/em\u003e gene, which contains at least five exons and produces an mRNA-like transcript. Single-nucleotide polymorphisms (SNPs) in the \u003cem\u003eSOX2-OT\u003c/em\u003e gene have been associated with various diseases, such as mental illnesses, diabetic complications, and most importantly cancer [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. It has been shown to function as a ceRNA in multiple malignancies such as prostate cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], ovarian cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], lung cancer [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and laryngeal cancer [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] via modulating the \u003cem\u003eSOX2-OT\u003c/em\u003e/miRNA/mRNA axes through several signaling pathways [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Additionally, \u003cem\u003eNEAT1\u003c/em\u003e \u003cb\u003e(ENSG00000245532)\u003c/b\u003e is a large non-coding transcript that typically localizes in the nuclear paraspeckles [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], which are involved in different aspects of nuclear function [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], including functioning as a transcription factor and is transcribed from 11q13.1 loci [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Numerous human cancers, including breast cancer [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], colorectal cancer [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], liver cancer [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], gastric cancer [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], prostate cancer [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and glioma [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], have been linked to aberrant expression of \u003cem\u003eNEAT1\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eHowever, since there has been a lack of understanding of the precise roles of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC, as a pilot study, herein, we explored their regulatory and clinical potential in ESCC. We further observed that both \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e have significant diagnostic and prognostic potential in ESCC patients. Additionally, through the in-silico analysis, we demonstrated that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e are involved in sponging miRNAs (miR-26a-5p and miR-449b-5p) via mTOR and MAPK pathways. Moreover, we observed several cancer-related molecular signals interacting with \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e, which may be essential components controlling the development and progression of ESCC.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Clinical Sample Collection and Storage\u003c/h2\u003e \u003cp\u003e The approval for the present study was obtained from the Ethics Review Board of the Central University of Punjab and the Advanced Cancer Institute in Bathinda (CUPB/IEC/2018/12 and ERB/UCER/2019/4/17), which was carried out in line with the Declaration of Helsinki. According to the 8th edition of TNM staging developed by the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC), pathologists used tissue samples to identify ESCC patients. The Tempus Blood RNA Tube (Cat. No. 4342792; Applied Biosystems, CA, USA) was used by the phlebotomist to collect the peripheral blood samples (3 ml) from newly diagnosed ESCC patients (Age ≥ 18) and healthy persons (Age ≥ 18). During the period of sample collection, details about the patient's complete medical history, including age, gender, smoking status, alcohol intake, consumption of hot beverages, tumor grade, and TNM stages, were also acquired. The 50 blood samples from ESCC patients and a control group of age- and sex-matched healthy individuals using already predefined set inclusion and exclusion criteria [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 LncRNA Isolation and cDNA Synthesis\u003c/h2\u003e \u003cp\u003eTo investigate the expression levels of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in the blood samples of ESCC patients, we used a QIamp RNA Blood mini kit (Cat. No. 52304, Qiagen, Inc., Valencia, CA, USA) to isolate lncRNAs from 3 mL blood samples of ESCC patients and age- and sex-matched healthy controls by following the manufacturer’s protocol. We evaluated the RNA purity, concentration, and quality using a Nanodrop UV-Vis Spectrophotometer 2000cc (Thermo Fisher Scientific, CA, USA). We synthesized cDNA using the RT2 First Strand Kit (Cat. No.: 330404, Qiagen, Inc., Valencia, CA, USA) as described previously [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Expression analysis of candidate lncRNAs using quantitative Real-Time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eValidation of the \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e endogenous expression was done using RT2 SYBR Green Master mix (Qiagen), respective primers (Qiagen), and template (cDNA) according to the manufacturer’s protocol on a QIAquant 96; 5 plex qRT-PCR (S/N:3107V-3324269; Qiagen Inc). As a template, we utilized 2 µl of cDNA, 6.25 µl of iTaq Universal SYBR Green, and 1 µl of 10 µM lncRNA-specific primers from Qiagen Inc. The total reaction volume was maintained up to 12.5 µl using nuclease-free water. The qRT-PCR cycling parameters for both \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e were 95ºC for 10 minutes (holding stage), 95ºC for 5 seconds (denaturation), 60ºC for 1 minute (annealing), 72ºC for 2 minutes (melt curve), and increment of 2ºC upto 95ºC Every reaction was carried out three times. To determine the fold change values using the Livak technique, the Ct values of these lncRNAs were normalized using Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a reference gene. The normalized expression levels (∆Ct) of these lncRNAs were then used to construct scatter plots. The detailed methodology has been described in our previous paper [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Receiver operating characteristic (ROC) curve\u003c/h2\u003e \u003cp\u003eThe ROC curve is a statistical tool used to evaluate the discriminative power of a dichotomous diagnostic test [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The area under the receiver operating characteristic curves typically ranges from 0.5 to 1. The diagnostic effect is enhanced by the AUROC value's proximity to 1. The AUC values were categorized as poor, medium, or high accuracy for the ranges 0.5–0.7, 0.7–0.9, and \u0026gt; 0.9, respectively [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The diagnostic potential of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC patients was then assessed using ROC curves that were generated using the normalized Ct values.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 LncRNA target prediction and pathway enrichment analysis\u003c/h2\u003e \u003cp\u003eIt is well established that cytoplasmic lncRNA acts as a ceRNA by harbouring multiple miRNAs binding sites, thereby regulating their downstream targets by \"sponging\" those miRNAs [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Therefore, to predict the miRNA-mRNA targets of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e, we utilized the following databases: lncRnome (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genome.igib.res.in/lncRNome/\u003c/span\u003e\u003cspan address=\"http://genome.igib.res.in/lncRNome/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), RAID v2.0 (RNA Interactome) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rna-society.org/raid/\u003c/span\u003e\u003cspan address=\"http://www.rna-society.org/raid/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), Starbase (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://starbase.sysu.edu.cn/\u003c/span\u003e\u003cspan address=\"http://starbase.sysu.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), miRDB (microRNA database) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mirdb.org/\u003c/span\u003e\u003cspan address=\"http://mirdb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), TargetScan (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.targetscan.org/vert_72/\u003c/span\u003e\u003cspan address=\"http://www.targetscan.org/vert_72/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for used to confirm the expected targets of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1.\u003c/em\u003e Furthermore, the Kyoto Encyclopaedia of Genes and Genomes (KEGG) has been utilized to identify potential pathways altered by \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT-1\u003c/em\u003e in ESCC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Co-expression networks of lncRNAs and mRNAs\u003c/h2\u003e \u003cp\u003eCo-expression gene study was carried out using a co-express database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://coxpresdb.jp/\u003c/span\u003e\u003cspan address=\"https://coxpresdb.jp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Furthermore, using Cytoscape, a network of co-expressed genes was created. Additionally, we looked at the co-expressed genes' KEGG pathways and molecular locations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Statistical analysis\u003c/h2\u003e \u003cp\u003eWe utilized GraphPad Prism v8.0 (La Jolla, California, USA) for data analysis. The Mann-Whitney (non-parametric) test was used to assess differences in the expression levels of lncRNAs in cancer patients and healthy people's blood samples and expressed the data as ‘mean ± standard error mean (SEM)’. A student t-test was utilized in the remaining studies to evaluate the distinction between the two groups. Three independent times each sample was used to conduct each experiment in triplicate. In respect of statistical significance, the symbols ****, ***, **, and * represent \u003cem\u003ep-values\u003c/em\u003e less than 0.0001, 0.001, 0.01, and 0.05, respectively, while ‘ns’ stands for \u003cem\u003ep-values\u003c/em\u003e greater than 0.05, which are non-significant.\u003c/p\u003e \u003c/div\u003e "},{"header":"RESULTS","content":"\u003ch2\u003e4.1 LncRNAs differentially expressed in esophageal squamous cell carcinoma\u003c/h2\u003e\u003cp\u003ePreviously, our group had demonstrated 296 differentially expressed lncRNAs in ESCC patients’ blood samples that may have the potential to be utilized as liquid biopsy markers in ESCC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Taking clues from our previous study, herein, we have explored the expression of the \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e lncRNAs in ESCC (n = 50). We used qRT-PCR to assess the \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expression levels for this. Following 40 cycles of qRT-PCR, we observed that \u003cem\u003eSOX2-OT\u003c/em\u003e was expressed in only 36 out of 50 ESCC samples, and \u003cem\u003eNEAT1\u003c/em\u003e was expressed in 34 out of 50 ESCC samples. Further, we observed that \u003cem\u003eSOX2-OT\u003c/em\u003e was significantly downregulated (fold-change = 2.02, \u003cem\u003ep-value\u003c/em\u003e = 0.0001) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e in blood samples of ESCC patients compared to healthy matched individuals. Similarly, \u003cem\u003eNEAT1\u003c/em\u003e was \u003cem\u003ealso\u003c/em\u003e down-regulated (fold change = 1.79, \u003cem\u003ep-value\u003c/em\u003e = 0.0052) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e in ESCC blood samples compared to matched healthy individuals. The downregulation of both \u003cem\u003eSOX2-OT and NEAT1\u003c/em\u003e suggest that both lncRNAs may act as tumor suppressors in ESCC patients.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003ch2\u003e4.2 Downregulated \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e possess a good diagnostic potential in ESCC\u003c/h2\u003e\u003cp\u003eUsing GEPIA online tools, we first examined how \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e were expressed in relation to one another in esophageal squamous cell cancer. After that, we observed that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e have the potential to be used as clinical diagnostics, with Area under the ROC curve (AUC) values of 0.736 \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e [95% CI = 0.6479 to 0.8737; p-value = 0.0001] and 0.695 \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e [95% CI = 0.5701 to 0.8201; p-value = 0.0057] respectively. Additionally, we explored for the combined efficiency of the lncRNA \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e panel in diagnosing ESCC. We observed that the combined Area under the ROC curve (AUC) value came out to be 0.6217 (95% confidence interval [CI] = 0.5245 to 0.7189; \u003cem\u003ep-value\u003c/em\u003e = 0.0175]) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e]\u003c/b\u003e. The combined value of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e is lower than individual AUC values for \u003cem\u003eSOX2-OT and NEAT1\u003c/em\u003e. Therefore, we predict that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e individually may have a better diagnostic potential than being used as a combined diagnostic panel.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003ch2\u003e4.3 Association of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expression with the lifestyle and clinicopathological status of ESCC patients\u003c/h2\u003e\u003cp\u003eSince it is a well-known fact that some lifestyle factors affect the pathogenesis of ESCCs, our next goal was to assess how altered \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e levels related to the clinicopathological traits and lifestyle aspects of ESCC patients, including age, gender, tobacco use, alcohol use, consumption of hot drinks, tumor grade, and TNM stages. We found that ESCC patients' lifestyles and their clinicopathological features impacted \u003cem\u003eSOX2-OT\u003c/em\u003e expression more significantly than healthy persons.\u003c/p\u003e\u003cp\u003eNotably, we found a ~ 1.69-fold reduction in \u003cem\u003eSOX2-OT\u003c/em\u003e expression in ESCC patients aged 18 to 50 years (n = 17; \u003cem\u003ep-value\u003c/em\u003e = 0.0028), but no differences in \u003cem\u003eSOX2-OT\u003c/em\u003e expression were found in ESCC patients older than 50 years (n = 19; \u003cem\u003ep-value\u003c/em\u003e = 0.1871) when compared to age-matched healthy individuals. The expression of \u003cem\u003eSOX2-OT\u003c/em\u003e did not significantly differ between the two age groups of ESCC patients, (\u003cem\u003ep-value\u003c/em\u003e = 0.3420) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eThe gender differences between the two groups of ESCC patients were also not discernible (\u003cem\u003ep-value\u003c/em\u003e = 0.7961) in \u003cem\u003eSOX2-OT\u003c/em\u003e expression. However, compared to healthy male individuals, male ESCC patients demonstrated a ~ 2.30-fold downregulation of \u003cem\u003eSOX2-OT\u003c/em\u003e expression (n = 19; \u003cem\u003ep-value\u003c/em\u003e = 0.0018) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e, In contrast, there was no discernible difference in the expression of \u003cem\u003eSOX2-OT\u003c/em\u003e between female ESCC patients and healthy females (n = 17; p = 0.1086) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e. In addition, ESCC patients with a history of tobacco use displayed a ~ 1.85-fold downregulation of \u003cem\u003eSOX2-OT\u003c/em\u003e (n = 17; \u003cem\u003ep-value\u003c/em\u003e = 0.0008), while non-smokers displayed a ~ 2.38-fold downregulation (n = 19; \u003cem\u003ep-value\u003c/em\u003e = 0.0001) compared to healthy people \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e].\u003c/b\u003e Smokers and non-smokers with tumors did not differ significantly from one another (\u003cem\u003ep-value\u003c/em\u003e = 0.7961) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e]\u003c/b\u003e. Similar to this, ESCC patients with a history of alcohol use showed a ~ 1.85-fold downregulation (n = 22; \u003cem\u003ep-value\u003c/em\u003e = 0.0030), whereas patients who were not alcoholics showed a ~ 2.4-fold downregulation (n = 14; \u003cem\u003ep-value\u003c/em\u003e = 0.0001) compared to healthy people \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e]\u003c/b\u003e. As opposed to this, no distinction between the two groups of ESCC patients was seen (\u003cem\u003ep-value\u003c/em\u003e = 0.2370) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e]\u003c/b\u003e. Further, patients with a history of using hot beverages displayed a ~ 2.03-fold downregulation (n = 22; \u003cem\u003ep-value\u003c/em\u003e = 0.0055), whereas patients without a history of consuming hot beverages displayed a ~ 1.72-fold downregulation (n = 14; \u003cem\u003ep-value\u003c/em\u003e = 0.0093) as compared to healthy individuals. (\u003cem\u003ep-value\u003c/em\u003e = 0.7067) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE\u003cb\u003e]\u003c/b\u003e There was no discernible difference between the two groups of ESCC patients.\u003c/p\u003e\u003cp\u003eThere were no discernible changes between the groups of ESCC patients when we assessed the expression of \u003cem\u003eSOX2-OT\u003c/em\u003e with different tumor grades \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF\u003cb\u003e].\u003c/b\u003e However, The TNM stages (I + II) and (III + IV) of ESCC patients demonstrated a significant difference between the two groups of ESCC patients (\u003cem\u003ep-value\u003c/em\u003e = 0.0128) \u003cb\u003e[\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG\u003cb\u003e].\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn keeping with the previous section, we specifically looked at the relationships between the dysregulated levels of \u003cem\u003eNEAT1\u003c/em\u003e and the clinicopathological traits and lifestyle factors, including age, gender, smoking, drinking, consuming hot beverages, tumor grade, and TNM stages of ESCC patients.\u003c/p\u003e\u003cp\u003eAccording to statistical analysis, we discovered no discernible difference between the expression of NEAT1 in ESCC patients between the ages of 18 and 50 (n = 16, p-value = 0.4077) compared to age-matched healthy individuals. However, compared to the healthy individuals, patients over 50 demonstrated a ~ 2.44-fold downregulation in \u003cem\u003eNEAT1\u003c/em\u003e expression (n = 18, \u003cem\u003ep-value\u003c/em\u003e = 0.0106). Moreover, there was a significant downregulation of ~ 3.04-fold in the expression of \u003cem\u003eNEAT1\u003c/em\u003e between the two age groups of ESCC patients (p = 0.0078) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e. Similarly, we could not observe any significant difference in the expression of \u003cem\u003eNEAT1\u003c/em\u003e in ESCC females (n = 17, \u003cem\u003ep-value\u003c/em\u003e = 0.3479), whereas ~ 2.32-fold downregulation was noted in ESCC males (n = 17, \u003cem\u003ep-value\u003c/em\u003e = 0.0023) compared to male healthy controls. However, no significant difference in the expression of \u003cem\u003eNEAT1\u003c/em\u003e was also observed between the two gender groups of ESCC patients (\u003cem\u003ep-value\u003c/em\u003e = 0.2083) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e. Additionally, in ESCC patients having a history of tobacco smoking, it was determined that there is no significant difference in \u003cem\u003eNEAT1\u003c/em\u003e expression in tobacco smokers (n = 9, \u003cem\u003ep-value\u003c/em\u003e = 0.2584) as compared to their matched healthy individuals. However, ~ 1.89-fold downregulation of \u003cem\u003eNEAT1\u003c/em\u003e was observed in non-tobacco smokers (n = 25, \u003cem\u003ep-value\u003c/em\u003e = 0.0036) as compared to healthy individuals. In addition, no significant difference was detected in smoker ESCC patients compared to non-smoker ESCC patients (\u003cem\u003ep-value\u003c/em\u003e = 0.5700) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eMoreover, based on the alcoholic status of ESCC patients, \u003cem\u003eNEAT1\u003c/em\u003e was found to be ~ 2.31-fold downregulated (n = 15, \u003cem\u003ep-value\u003c/em\u003e = 0.0017) in non-alcoholic patients, while no significant difference in the expression of \u003cem\u003eNEAT1\u003c/em\u003e was observed in ESCC patients with a history of alcohol consumption as compared to the healthy individuals (n = 19, \u003cem\u003ep-value\u003c/em\u003e = 0.1188). Likewise, the difference was also non-significant between the two groups of ESCC patients (\u003cem\u003ep-value\u003c/em\u003e = 0.1757) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e].\u003c/b\u003e Next, ESCC patients with a history of hot beverage consumption (n = 21, \u003cem\u003ep-value\u003c/em\u003e = 0.0545), as well as patients with no history of hot beverage consumption (n = 13, \u003cem\u003ep-value\u003c/em\u003e = 0.3215), did not show any significant differences in the expression levels of \u003cem\u003eNEAT1\u003c/em\u003e as compare to healthy individuals. However, ~ 1.49-fold downregulation on the expression of \u003cem\u003eNEAT1\u003c/em\u003e was observed between the two groups of ESCC patients (\u003cem\u003ep-value\u003c/em\u003e = 0.0055) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e].\u003c/b\u003e Furthermore, the expression of \u003cem\u003eNEAT1\u003c/em\u003e was also evaluated with the numerous tumor grades of ESCC patients, and it was observed that there was a ~ 2.88-fold downregulation in the expression of \u003cem\u003eNEAT1\u003c/em\u003e in patients with unknown tumor grade as compared to the patients with well-differentiated tumor (n = 23, \u003cem\u003ep-value\u003c/em\u003e = 0.0151). However, there were no significant differences among the other groups of ESCC patients \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF\u003cb\u003e].\u003c/b\u003e Similar results were obtained for the two groups of ESCC patients with the TNM stage (I + II) and (III + IV), which could not show any significant differences in the expression levels of \u003cem\u003eNEAT1\u003c/em\u003e (\u003cem\u003ep-value\u003c/em\u003e = 0.3723) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eBy comparing the ESCC patients' lifestyles to those of healthy people, the findings presented above lead us to the conclusion that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expression levels are influenced by lifestyle and seldom by clinicopathological characteristics.\u003c/p\u003e\u003ch2\u003e4.4 \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e target miRNAs and regulate various cancer-associated signaling pathways\u003c/h2\u003e\u003cp\u003eAs we know, cytoplasmic lncRNAs act as ceRNA by sponging miRNA activity in the human genome. In this regard, our group had recently shown two models of the molecular sponging mechanism by lncRNAs viz, unidirectional and bidirectional. Several online databases were used to screen the molecular targets of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e (see materials and methods). Interestingly, we observed fifty-three miRNA targets of \u003cem\u003eSOX2-OT\u003c/em\u003e from RAID v2.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rna-society.org/raid2/\u003c/span\u003e\u003cspan address=\"http://www.rna-society.org/raid2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), fifty-seven miRNA targets from RNAInter (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rnainter.org/\u003c/span\u003e\u003cspan address=\"http://www.rnainter.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and hundred miRNA targets from the DIANA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diana.e-ce.uth.gr/home\u003c/span\u003e\u003cspan address=\"https://diana.e-ce.uth.gr/home\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases. According to the DIANA, RAID v2.0, and RNA Inter databases, \u003cem\u003eSOX2-OT's\u003c/em\u003e putative miRNA targets include fourteen common miRNAs \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e].\u003c/b\u003e One hundred fifteen mRNA targets of has-miR-26a-5p predicted from Starbase (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://starbase.sysu.edu.cn/\u003c/span\u003e\u003cspan address=\"http://starbase.sysu.edu.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), miRBD (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mirdb.org/\u003c/span\u003e\u003cspan address=\"http://mirdb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), TargetScan (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.targetscan.org/vert_72/\u003c/span\u003e\u003cspan address=\"http://www.targetscan.org/vert_72/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and RAID (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.rna-society.org/raid2/\u003c/span\u003e\u003cspan address=\"http://www.rna-society.org/raid2/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases as shown in \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e].\u003c/b\u003e Additionally, GO analysis was used to evaluate the miRNA-\u003cem\u003eSOX2-OT\u003c/em\u003e axis's associated biological, molecular, cellular, and KEGG pathway activities. In each domain, we chose the top fifteen enriched GO phrases. Four of them were shown to participate in several biological processes, including cell migration, the mitotic cell cycle, cell cycle regulation, and the cell cycle process \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u003cb\u003e].\u003c/b\u003e Similarly, cellular processes like microtubule organization and intracellular protein-containing complex are influenced by molecular processes, including protein dimerization activity, Guanyl nucleotide binding, and RNA binding \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u003cb\u003e].\u003c/b\u003e Additionally, we demonstrated that KEGG pathways in cancer were enriched for RNA degradation, the mTOR signaling pathway, and ubiquitin-mediated proteolysis \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE\u003cb\u003e].\u003c/b\u003e\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eNext, we investigated the molecular targets of \u003cem\u003eNEAT1.\u003c/em\u003e We observed 437 miRNA targets from the Starbase database, eight miRNA targets from the RNAInter database, and two miRNA targets from RAID v2.0. Two common miRNA targets were found to be hsa-miR-449b-5p and hsa-miR-106a-5p [Figure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA]. 97 mRNA targets of has-miR-449b-5p were predicted from Starbase, miRBD, Target Scan, and RAID databases, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB. In order to evaluate the linked biological, molecular, and cellular processes of the hsa-miR-449b-5p-\u003cem\u003eNEAT1\u003c/em\u003e axis, GO analysis was also used. The top 15 enriched GO items in each domain were chosen. Among them, hsa-miR-449b-5p and hsa-miR-106a-5p were discovered to be involved in several biological activities, such as the binding of transcription factors, the binding of kinase activity RNA, and cell adhesion molecule binding \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC\u003cb\u003e].\u003c/b\u003e Similarly, miR-449b-5p and miR-106a-5p also affect cellular processes such as ribonucleoprotein complex, microtubule organizing, endoplasmic reticulum, mitochondrion, etc. \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD\u003cb\u003e]\u003c/b\u003e. Additionally, we found that miR-449b-5p and hsa-miR-106a-5p are enriched in the MAPK signaling pathway, endocytosis pathway, cell cycle, and regulation of actin cytoskeleton pathways in cancer \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE\u003cb\u003e].\u003c/b\u003e\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eOverall, the above data suggest that the downregulation of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e may be involved in the advancement of ESCC by targeting miRNAs and mRNAs by altering various pathways involved in carcinogenesis.\u003c/p\u003e\u003ch2\u003e4.5 \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e were regulated by Co-expression networks of mRNAs and lncRNAs\u003c/h2\u003e\u003cp\u003eUsing co-expression networks, we found genes that are co-expressed with lncRNA and might serve as lncRNA targets. Based on this concept, we used Cytoscape and COXPRES db. Ver. 8.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://coxpresdb.jp/\u003c/span\u003e\u003cspan address=\"https://coxpresdb.jp/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to visualize the network of two lncRNAs (\u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e). Each lncRNA was found to have relationships with both mRNA and other lncRNAs in the network. Notably, seven lncRNAs SOX21 antisense divergent transcript 1 (\u003cem\u003eSOX21-AS1)\u003c/em\u003e, POU3F3 adjacent non-coding transcript 1 \u003cem\u003e(PANTR1)\u003c/em\u003e, FEZF1 antisense RNA 1 \u003cem\u003e(FEZF1-AS1)\u003c/em\u003e, long intergenic non-protein coding RNA 844 (\u003cem\u003eLINC00844)\u003c/em\u003e, sciatic injury induced lincRNA up regulator of SOX11 \u003cem\u003e(SILC1)\u003c/em\u003e, long intergenic non-protein coding RNA 1896 \u003cem\u003e(LINC01896)\u003c/em\u003e and ARHGEF26 antisense RNA 1 (\u003cem\u003eARHGEF26-AS1)\u003c/em\u003e and forty four mRNAs, sex-determining region Y-box 2 (SOX2), SRY-box transcription factor 21(SOX21), sex-determining region Y-box 1 (SOX1), peripheral myelin protein 2 (PMP2), proteolipid protein \u003cem\u003e1\u003c/em\u003e (\u003cem\u003ePLP1\u003c/em\u003e), fibroblast growth factor 12 (\u003cem\u003eFGF12\u003c/em\u003e), fatty acid binding protein 7 (\u003cem\u003eFABP7\u003c/em\u003e), aquaporin-4 (AQP4), receptor protein-tyrosine kinase ErbB-4 (\u003cem\u003eERBB4\u003c/em\u003e), generalized anxiety disorder 2-item (\u003cem\u003eGAD-2\u003c/em\u003e), glutamate metabotropic receptor 3 (GRM3) and cell adhesion molecule 2 (\u003cem\u003eCADM2)\u003c/em\u003e etc. were \u003cem\u003eanticipated to express alongside SOX2-OT.\u003c/em\u003e Among these, SOX2, SOX21, and \u003cem\u003eSOX21-AS1\u003c/em\u003e were co-expressed with \u003cem\u003eSOX2-OT\u003c/em\u003e in the network in a direct manner. In addition, we found that several mRNAs, including SOX2, ZNF536 HESS, ASGL1, PRR18, AMER2, NKX6-2, TOX3, ASXL3, CXXC4, and ESRRG, were localised in the nucleus (as represented by purple balls) and four mRNAs were localised in the Plasma membrane (as shown by dark blue balls) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eLikewise, seventeen lncRNAs \u003cem\u003eLINC00894\u003c/em\u003e, ASMTL antisense RNA 1 \u003cem\u003e(ASMTL-AS1), LINC00893, LOC107983998, LOC105373102, LOC107984338, LOC107984754, LOC100289230, LOC101928762\u003c/em\u003e, PSMA3 antisense RNA 1 \u003cem\u003e(PSMA3-AS1)\u003c/em\u003e, AP1G2 antisense RNA 1 \u003cem\u003e(AP1G2-AS1), LINC01004, LOC107984203, LINC00115, LOC105374298, LINC01000\u003c/em\u003e and \u003cem\u003eLINC02603\u003c/em\u003e co-expressed with \u003cem\u003eNEAT1\u003c/em\u003e on the network. Moreover, various mRNAs, RNA-binding region-containing protein 3 (RNPC3), zinc finger RANBP2-type containing 2 (ZRANB2), zinc finger C3H1 domain-containing protein (ZFC3H1), arginine and glutamate-rich 1 (ARGLU1), heterogeneous nuclear ribonucleoprotein A3 (HNRNPA3), amyloid-beta A4 precursor protein-binding family B member 3 (APBB3), heat shock transcription factor 4 (HSF4), SUGP2 and protein phosphatase 1 regulatory subunit 3B (PPP1R3B) etc., nine mRNAs (\u003cem\u003eRNPC3, ZRANB2, ZFC3H1, ARGLU1, HNRNPA3, APBB3, HSF4, SUGP2\u003c/em\u003e and \u003cem\u003ePPP1R3B\u003c/em\u003e) localised in the nucleus (as shown by purple balls) and one mRNA, vacuole membrane protein 1 (\u003cem\u003eVMP1\u003c/em\u003e) were found to be localized in the plasma membrane (as shown by the dark blue ball) \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB\u003cb\u003e].\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAltogether, our findings imply that dysregulation of the lncRNAs \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC simultaneously influences the expression of various other lncRNAs and mRNAs implicated in critical signaling pathways in the human biological system. By regulating the impacted gene expression along with \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e, this method may assist in developing a potential therapeutic strategy.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAlthough detection methods for esophageal cancer have improved, its high incidence and mortality rate still persist [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Therefore, it is crucial to investigate the development of esophageal cancer and identify molecular markers linked to early detection and prognosis. Currently, ESCC diagnosis relies on invasive endoscopy and uncomfortable histopathological biopsy, underscoring the dire need for a blood-based circulating biomarker to enhance ESCC identification and management. Notably, as high-throughput transcriptome research becoming more common, innumerable lncRNAs have been revealed to play critical roles in cancer genesis. Because of their crucial roles in carcinogenesis, growth, progression and metastasis, lncRNAs can function as potential novel biomarkers or targets for cancer early detection and therapy [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Furthermore, when paired with numerous clinicopathological factors, the state of each individual patient can be determined with greater precision, allowing for more precise and tailored treatment formulation for each individual.\u003c/p\u003e\u003cp\u003eIn this respect, we demonstrated that lncRNAs \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e significantly downregulated in ESCC patient's blood samples compared to healthy matched control samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Recent research has also shown that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e dysregulation is a major factor in the emergence of most malignancies, including NSCLC [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], triple-negative breast cancer (TNBC) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] and ovarian cancer [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Numerous investigations in the field of cancer research have established the functions of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. For example, one group has demonstrated that by targeting the miR-369-3p/CFL2 axis, \u003cem\u003eSOX2-OT\u003c/em\u003e accelerates cell division and migration in prostate cancer [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In a similar study, by modulating the miR-452-5p/HMGB3 axis, \u003cem\u003eSOX2-OT\u003c/em\u003e knockdown delays the progression of prostate cancer in vivo [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Another ceRNA axis, \u003cem\u003eSOX2-OT\u003c/em\u003e/miR-30d-5p/PDK1, involving \u003cem\u003eSOX2-OT\u003c/em\u003e influences NSCLC cell proliferation, migration, and invasion [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The ERK signaling pathway and the miR192-5p/RAB2A axis are regulated by \u003cem\u003eSOX2-OT\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. \u003cem\u003eSOX2-OT\u003c/em\u003e knockdown could increase apoptosis and decrease laryngeal cancer cell proliferation, migration, and invasion by focusing on miR-654 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. On the other hand, the etiology of numerous human malignancies is significantly influenced by \u003cem\u003eNEAT1\u003c/em\u003e [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn a study, it was shown that poorer clinicopathological lung cancer characteristics and its abnormal expression are tightly associated with each other [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. \u003cem\u003eNEAT1\u003c/em\u003e, in accordance with another study, encourages lung cancer cells to proliferate and spread [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Moreover, \u003cem\u003eNEAT1\u003c/em\u003e was involved in the development of lung cancer and the invasion of cytotoxic T-cells by binding to DNA-methyltransferase 1 \u003cem\u003e(DNMT1)\u003c/em\u003e and blocking the P53 and cGAS/STING pathways [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Interestingly, Teng et al. discovered that \u003cem\u003eSOX2-OT\u003c/em\u003e is linked to specific clinical pathological parameters, including tumor size and lymph node metastasis [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn our investigation, we used blood samples from ESCC patients to investigate the diagnostic biomarkers \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e. Based on the previously published data [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], we designed this investigation to discover potential blood-based biomarkers for ESCC diagnosis. Furthermore, it is well accepted that a number of extrinsic lifestyle factors, such as the consumption of hot beverages, the amount of fresh food and vegetables, and obesity, play a substantial part in the etiology of ESCC. In fact, earlier research found a relationship between their specific lifestyle choices and verified lncRNAs in cancer patients. Unfortunately, there is no evidence tying them to individuals with ESCC. We observed that \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e have the potential to be used as clinical diagnostics, with Area under the ROC curve values of 0.736 \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e [95% CI = 0.6479 to 0.8737; \u003cem\u003ep-value\u003c/em\u003e = 0.0001] and 0.638 \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e [95% CI = 0.5060 to 0.7717; \u003cem\u003ep-value\u003c/em\u003e = 0.0490] respectively.\u003c/p\u003e\u003cp\u003eAs a result, we were curious to learn how the \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expressions related to the clinicopathological traits and lifestyle status of ESCC patients and the diagnostic and predictive potential of lncRNAs. Interestingly, we observed downregulated expression of \u003cem\u003eSOX2-OT\u003c/em\u003e linked with the age (18 ≤ 50 years) of the ESCC patients compared to age-matched healthy individuals \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e, which suggests that the age below 50 years might affect the levels of \u003cem\u003eSOX2-OT\u003c/em\u003e expressions. However, no difference was observed in \u003cem\u003eSOX2-OT\u003c/em\u003e expression in the ESCC patients of two age groups \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e]\u003c/b\u003e. Further, our study found that ESCC patient's gender (male) was associated with \u003cem\u003eSOX2-OT\u003c/em\u003e expression compared to healthy individuals \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eIn contrast to healthy persons, we found that \u003cem\u003eSOX2-OT\u003c/em\u003e expression was associated with ESCC patients who smoked, drank alcohol, used hot beverages, and were in advanced TNM stages. This finding suggests that these factors may influence \u003cem\u003eSOX2-OT\u003c/em\u003e expression in ESCC patients \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG\u003cb\u003e]\u003c/b\u003e. We could not detect any correlation between increasing tissue grades and \u003cem\u003eSOX2-OT\u003c/em\u003e expression in the ESCC group \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF\u003cb\u003e]\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eNext, we analyzed the association of the dysregulated levels of \u003cem\u003eNEAT1\u003c/em\u003e with the clinicopathological characteristics and lifestyle factors. We found a downregulated expression of \u003cem\u003eNEAT1\u003c/em\u003e linked with age (\u0026gt; 50 years) of ESCC patients compared to age-matched individuals. Moreover, \u003cem\u003eNEAT1\u003c/em\u003e expression was significantly downregulated in ESCC patients of \u0026gt; 50 years age as compared to patients of \u0026lt; 50 years. In contrast to the healthy individuals, we found that \u003cem\u003eNEAT1\u003c/em\u003e expression was associated with ESCC patients' gender, who smoked and drank alcohol [Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB to \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e]\u003c/b\u003e. This suggests that these factors may modulate the expression of \u003cem\u003eNEAT1\u003c/em\u003e in ESCC patients, but these factors were not correlated within ESCC patients. We also observed that \u003cem\u003eNEAT1\u003c/em\u003e expression were correlated with ESCC patients who consumed hot beverages as compared to those who did not \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e]\u003c/b\u003e. We could not detect any correlation between increasing tissue grade and TNM stages and \u003cem\u003eNEAT1\u003c/em\u003e expression in the ESCC group \u003cb\u003e[\u003c/b\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF to \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG\u003cb\u003e].\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIncreasing evidence points to the possibility that lncRNAs could operate as molecular sponges, mimic miRNAs, and influence biological pathways by influencing the mRNA targets downstream of miRNAs [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], \u003cb\u003et\u003c/b\u003ehrough the sponging of miRNAs like miR-194-5p [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], members of the miR-200 family, miR-146b-5p [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], miR-146b-5p [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], miR-194-5p, and miR-122 [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e have been identified as oncogenes in a number of malignancies. In regard to this, we performed a bioinformatical analysis using an appropriate data set and predicted the miRNA targets (miR-26a-5p and miR-449b-5p) of lncRNAs \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e respectively. Further, to better understand the molecular mechanism of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in the development of ESCC, we were interested in identifying the downstream target genes of miR-26a-5p and miR-449b-5p. Most importantly, the combined use of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e results in a lower AUC value compared to their individual AUC values; hence, the diagnostic potential of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e as standalone entities is expected to exceed their collective efficacy in a combined diagnostic panel. We ascertained the complete profiling of circulating lncRNAs \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in order to validate a liquid biopsy biomarker for ESCC diagnosis in clinical settings.\u003c/p\u003e"},{"header":"Conclusion, Future Aspects, and Limitations of the study","content":"\u003cp\u003eThis study provides evidence for the dysregulation of lncRNA \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC and its potential to be used as a diagnostic biomarker in the future. Furthermore, the moderate discriminatory power of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in distinguishing ESCC patients from healthy individuals highlights its potential as a non-invasive biological marker. The association of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expression with lifestyle factors suggests a possible link between lifestyle factors and lncRNAs (\u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e) dysregulation in ESCC. These findings indicate that lifestyle interventions may impact lncRNAs \u003cem\u003e(SOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1)\u003c/em\u003e expression and potentially influence ESCC development. However, further research is needed to elucidate the functional role of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC and the underlying mechanisms. Additionally, larger studies involving diverse populations are warranted to validate the precise diagnostic potential of these lncRNAs and to explore their association with other clinicopathological characteristics of ESCC.\u003c/p\u003e\u003cp\u003eTherefore, in this pilot study, \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e have been identified as potential markers that can be used to detect ESCC in a non-invasive manner. This finding offers an alternative method to traditional tissue biopsy by utilizing circulating lncRNAs for diagnosing ESCC patients. However, to apply these results in clinical settings, conducting studies with larger cohort sizes and validating the identified molecular targets through luciferase reporter assay. Further research and experiments are needed to thoroughly understand the pathways associated with \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1.\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by the Ethics Review Board of Baba Farid University of Health Sciences, Faridkot (ERB/UCER/2019/4/17), and the Institutional Ethics Committee of Central University of Punjab, Bathinda (CUPB/IEC/2018/12). The patients/participants provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions: A.J.\u003c/strong\u003e conceived the topic for this review. All the authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerlay J, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang QL, et al. Global time trends in the incidence of esophageal squamous cell carcinoma. Clin Epidemiol. 2018;10:717\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRana MK, et al. Current Trends of Carcinoma: Experience of a Tertiary Care Cancer Center in North India. 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Mol Cancer. 2017;16(1):171.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"SOX2-OT, ESCC, NEAT1, AUC, ROC and clinical settings","lastPublishedDoi":"10.21203/rs.3.rs-4134350/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4134350/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite strides in diagnostic and therapeutic approaches for ESCC, patient survival rates remain relatively low. Recent studies highlight the pivotal role of long non-coding RNAs (lncRNAs) in regulating diverse cellular activities in humans. Dysregulated lncRNAs have emerged as potential diagnostic indicators across various cancers, including ESCC. However, further research is necessary to effectively leverage ESCC-associated lncRNAs in clinical settings. Understanding their clinical significance for ESCC diagnosis and their mechanisms can pave the way for more effective therapeutic strategies. Our qRT-PCR observations indicated significant downregulation of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in ESCC blood samples (\u003cem\u003eSOX2-OT\u003c/em\u003e down by ~\u0026thinsp;2.02-fold and \u003cem\u003eNEAT1\u003c/em\u003e down by ~\u0026thinsp;1.53-fold). The decreased expression of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e shows promise in differentiating ESCC patients from healthy individuals, as demonstrated by Receiver Operating Characteristics (ROC) curves and Area Under the Curve (AUC) values (AUC: \u003cem\u003eSOX2-OT\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.736, \u003cem\u003eNEAT1\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.621) for ESCC diagnosis. Subsequent investigations explored the relationship between aberrant \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e expression in ESCC patients and various clinicopathological features, including age, gender, smoking habits, alcohol consumption, hot beverage intake, tumor grade, and TNM stages. In-depth in-silico analysis unveiled the involvement of \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e in miRNA sponging through the mTOR and MAPK pathways. In contrast, co-expression network analysis identified genes co-expressed with these lncRNA targets. This groundwork lays the foundation for future endeavours aimed at identifying and predicting ESCC prognosis by leveraging \u003cem\u003eSOX2-OT\u003c/em\u003e and \u003cem\u003eNEAT1\u003c/em\u003e. By thoroughly investigating the functions of these lncRNAs, we aim to deepen our understanding of their potential as diagnostic markers and their role in facilitating effective therapeutic interventions for esophageal squamous cell carcinoma (ESCC) within clinical contexts.\u003c/p\u003e","manuscriptTitle":"Clinical Significance of LncRNAs SOX2-OT and NEAT1 in Esophageal Squamous Cell Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-04 19:30:48","doi":"10.21203/rs.3.rs-4134350/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-08T05:19:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-08T03:39:57+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-08T01:58:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199289237060518864153222405967590254693","date":"2024-08-08T00:03:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241475080730241273585796134400254346119","date":"2024-08-07T17:33:43+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-31T09:46:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-31T05:19:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-31T05:18:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2024-03-20T05:32:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d8eb32e4-80a2-4ecd-92d8-c547d24a822c","owner":[],"postedDate":"April 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-11-13T15:53:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-04 19:30:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4134350","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4134350","identity":"rs-4134350","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}