Identification of the LINC00162/hsa-mir-383/CBX5 Axis as a novel prognostic biomarker associated with hemostasis in gastric cancer

Identification of the LINC00162/hsa-mir-383/CBX5 Axis as a novel prognostic biomarker associated with hemostasis in gastric cancer | 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 Identification of the LINC00162/hsa-mir-383/CBX5 Axis as a novel prognostic biomarker associated with hemostasis in gastric cancer Seyed Ali Hoseini, AmirAli A. Mokhtarzadeh, Saeid Ghorbian, Behzad Baradaran, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6423474/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Gastric cancer is a significant global cause of cancer-related mortality, which requires the development of new biomarkers to enhance diagnosis and prognosis. Although long non-coding RNAs (lncRNAs) have become critical regulators in cancer biology, their significance in gastric cancer remains incompletely understood. Objective: The purpose of this study is to assess the potential of the LINC00162/hsa-mir-383/CBX5 axis as a prognostic biomarker associated with hemostasis by examining its expression and functional significance in gastric cancer. Methods: To identify differentially expressed lncRNAs, we conducted comprehensive in-silico analyses using TCGA-STAD datasets. Subsequently, we conducted experimental validation through qPCR in gastric cancer tissue samples. The LncACT and miRmap databases were employed to investigate the interactions between LINC00162, hsa-mir-383, and CBX5. In order to clarify the molecular pathways that were implicated, functional enrichment analysis was implemented. Results: In gastric cancer tissues, LINC00162 (PICSAR) was substantially overexpressed in comparison to normal samples, which was associated with adverse clinical outcomes. According to the lncRNA-microRNA interaction analysis, LINC00162 functions as a molecular reservoir for hsa-mir-383, a microRNA that is downregulated in gastric cancer. An upregulation of CBX5, a target gene that is implicated in the progression of cancer, is associated with this downregulation. Functional enrichment analysis indicates that this axis is involved in critical oncogenic pathways. Conclusion: The LINC00162/hsa-mir-383/CBX5 axis is a novel prognostic biomarker in gastric cancer that has substantial implications for the hemostasis process. These discoveries emphasize the critical role of lncRNAs in the pathogenesis of gastric cancer, opening up new opportunities for the development of diagnostic and therapeutic strategies. Additional research is necessary to investigate the clinical implications of targeting this axis in the treatment of gastric cancer. Gastric cancer Long non-coding RNA (lncRNA) LINC00162 hsa-mir-383 CBX5 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1. Introduction Gastric cancer, often known as stomach cancer, is a major global public health problem due to its high incidence and fatality rates. It is among the main causes of cancer-related fatalities in the globe[ 1 ]. With a primary focus on the stomach lining, the illness has the potential to extend to the esophagus, liver, lungs, and lymph nodes, among other regions of the body[ 2 ]. Gastric cancer is the world's fifth most frequent cancer, with more than a million new cases identified each year. It is also the third greatest cause of cancer-related fatalities, accounting for around 783,000 deaths each year[ 3 ]. Gastric cancer has a massive worldwide impact, resulting in enormous healthcare expenses and lost productivity. It also imposes significant emotional and financial burdens on patients and their families[ 4 ]. Gastric cancer is a serious public health issue with a large worldwide death burden. Continued research, early identification, and preventative actions are required to properly battle this devastating illness[ 5 ]. Genetic factors have an important influence on the development of stomach cancer. While environmental variables including nutrition, Helicobacter pylori infection, and lifestyle choices are important, genetic predisposition can also impact a person's vulnerability to stomach cancer[ 6 ]. Although they do not encode proteins, long non-coding RNAs (lncRNAs) are a family of RNA molecules that are essential for controlling gene expression and biological functions. Emerging data suggests that lncRNAs play an important role in the development and progression of gastric cancer[ 7 , 8 ]. lncRNAs can influence gene expression at several levels, including as chromatin remodeling, transcription, and post-transcriptional processing. In gastric cancer, dysregulated lncRNAs can affect the expression of oncogenes or tumor suppressor genes, hence promoting carcinogenesis. lncRNAs can behave as molecular sponges for microRNAs (miRNAs), trapping them and blocking them from attaching to their intended mRNAs[ 9 , 10 ]. In gastric cancer cells, this interaction can cause oncogenic pathways to be activated or tumor-suppressive pathways to be inhibited. In gastric cancer, it has been demonstrated that some lncRNAs stimulate cell division and prevent apoptosis[ 11 ]. For instance, enhanced cell proliferation, invasion, and metastasis are linked to the overexpression of the lncRNA HOTAIR in gastric cancer[ 12 , 13 ]. Through their ability to control metastasis and angiogenesis, or the growth of new blood vessels, lncRNAs can have an impact on the tumor microenvironment. For example, by regulating the production of matrix metalloproteinases (MMPs) and vascular endothelial growth factor (VEGF), the lncRNA MALAT1 has been linked to the promotion of angiogenesis and metastasis in gastric cancer[ 14 , 15 ]. Through various pathways, the PICSAR lncRNA[ 16 ], has-miR-383[ 17 ], and CBX5 gene [ 18 ] are all important players in the development of cancer. By stimulating pathways including MAPK/ERK and modifying gene expression, PICSAR lncRNA is linked to the promotion of cell invasion, proliferation, and chemoresistance in several malignancies, including cutaneous squamous cell carcinoma. Depending on the situation, hsa-miR-383 can either promote or repress the development of cancer. It controls oncogene expression, cell cycle progression, and apoptosis in several cancer types. By preserving chromatin structure and suppressing gene expression, CBX5, also known as HP1α, plays a role in cancer biology and acts as a tumor suppressor in many different types of cancer. These molecules demonstrate the variety of ways that chromatin regulators and non-coding RNAs impact oncogenesis, highlighting their potential as targets for therapeutic intervention in cancer therapy approaches[ 19 , 20 ]. The significance of competing endogenous RNA (ceRNA) networks in stomach cancer has been brought to light by recent research. found a possible immuno-therapeutic target in gastric cancer with varying degrees of immune cell infiltration along the RP11-1094M14.8/miR-1269a/CXCL9 axis[ 20 ]. This work is a ground-breaking effort that advances our knowledge of genetic variation and the consequences it bears, especially when taking into account the mechanistic bioinformatics and systems biology techniques and the number of genes employed. There is no evidence to support a link between gastric cancer and the LINC00162/has-mir-383/CBX5 Axis. The current work sought to determine the expression of the LINC00162 (PICSAR) gene and the associated miRNA-mRNA axis in GC tissue samples, as well as to assess the diagnostic utility of these findings utilizing bioinformatic databases and tools. Our research may offer fresh perspectives on the molecular causes of GC as well as recommend cutting-edge methods for the diagnosis and management of GC. 2. Material and methods 2.1. In-silico analysis 2.1.1. Bulk RNA analysis The Cancer Genome Atlas (TCGA) performed thorough research to acquire datasets including samples from different forms of stomach cancer, as well as control samples from people who were not afflicted by the condition. The aforementioned dataset, TCGA-STAD, was identified among the returning datasets and then downloaded. The TCGA-STAD dataset comprises gathered and aggregated RNA sequencing profiles. It comprises gene expression data from two groups: control samples from healthy people and samples from patients with gastric cancer. 2.1.2. Data processing The current study employed RNA sequencing data obtained via the usage of the TCGAbiolinks program. TCGAbiolinks is a unique R-based program used to get data from the TCGA-STAD database. The TCGAbiolinks package aided the downloading procedure. The data was then normalized using the Limma tool, a widely used R-based approach for normalizing data in gene expression studies. Following adequate data normalization, we used the aforementioned R tools to analyze differentially expressed genes (DEGs). The finding of differentially expressed genes (DEGs) served as a foundation for further research and the formation of diverse networks, allowing for a more thorough understanding of the molecular processes underlying the analyzed state. The identification of differentially expressed lncRNAs was accomplished using an examination of the information provided by The Cancer Genome Atlas (TCGA) and the significant dysregulated novel long non-coding RNA was selected for further analysis. The data was presented and analyzed with the GraphPad Prism program. Multiple graphs and plots were obtained and shown using the TCGA browser, namely the Ualcan online tool [ 21 , 22 ]. ( https://ualcan.path.uab.edu/ ) and Xena Functional Genomics Explorer [ 23 ]. ( https://xenabrowser.net/ ) Additionally, the Kaplan-Meier plots were generated using the Kaplan-Meier Plotter database [ 24 , 25 ]. ( https://www.kmplot.com/analysis/ ). 2.1.3. lncRNA-microRNA interaction Following the identification of the significant dysregulated lncRNA in gastric cancer, the competing endogenous RNA network, or LncRNA-microRNA network, was examined to identify the competing molecules that act as microRNA sponges. To accomplish this objective, the LncACT online tool [ 26 , 27 ]. ( http://bio-bigdata.hrbmu.edu.cn/LncACTdb/ ) was used to identify the interaction between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs). 2.1.4. microRNA-mRNA interaction The microRNA-mRNA interaction network was rebuilt following the identification of an LncRNA-microRNA axis, which exhibits significant dysregulation and coordination across several pathways. The miRmap database [ 28 ] ( https://mirmap.ezlab.org/ ) was used for the specific purpose at hand. The previously described database was utilized to identify the microRNAs that were chosen to target the candidate mRNA. MicroRNAs may be used as both therapeutic agents and diagnostic biomarkers for stomach cancer, according to the study's findings. 2.1.5. Functional enrichment analysis The molecular pathways linked to the expression of the CBX5 gene in gastric cancer were illuminated by a functional enrichment analysis conducted using the Reactome database [ 29 , 30 ] ( https://reactome.org/ ). Potential targets for therapeutic intervention and future study were discovered by this analysis as important pathways that may be associated with the oncogenic processes controlled by CBX5. 2.2. Experimental validation 2.2.1. Preparation of Sample Twenty-five samples of matching tumor margin tissue and twenty-five samples of GC tissue were gathered. A formal informed consent form was signed by each participant. Chemotherapy or radiation therapy was never administered before any surgical procedure. Prior to RNA extraction, the samples were stored at 80°C after being snap-frozen in liquid nitrogen. Information about the tumor's size, age, gender, lymphatic and vascular invasion, serosal invasion, histological grade, clinical stage, and perineural invasion was included in the patient profiles. 2.2.2. RNA extraction and cDNA synthesis Tissue samples were initially pulverized using a mortar and pestle while submerged in liquid nitrogen, and then transferred to a lysis buffer for further homogenization. To extract total RNA, we followed the instructions for the Trizol reagent (Riboex brand, Gene All). The total RNA quantity and purity were assessed with a NanoDrop spectrophotometer. Subsequently, 1 µg of total RNA was added to a final volume of 20 µl, and cDNA was synthesized in a thermocycler PCR following the standard protocol: 30 minutes at 50°C for reverse transcription, 5 minutes at 95°C to deactivate the RT enzyme, and holding at 10°C indefinitely. 2.2.3. Real-Time PCR (qPCR) The experimental protocol utilized BioFACT™ 2X Real-Time PCR Master Mix and gene-specific primers to perform Real-Time PCR, with a total reaction volume of 10 µl. The procedure consisted of three main phases: In the first phase, the temperature was increased to 95°C for 13 minutes as the holding stage or initial heat. In the second phase, the denaturation step was performed at 95°C for 10 seconds over 45 cycles. Following denaturation, primer annealing occurred at 60°C for 30 seconds, and extension took place at 72°C for 20 seconds. In the final phase, melting curves were recorded at the end of each run. The GAPDH gene was used for data normalization, and target gene expression was quantified using the 2-ΔΔCt method. Primer design was conducted using the NCBI Primer-3 online tool, available at https://www.ncbi.nlm.nih.gov/tools/primer-blast/ . Table 1 provides the primer sequences used for quantitative polymerase chain reaction (qPCR). Table 1 qPCR primer sequences Target gene Forward (5′ – 3′) Reverse (5′ – 3′) U6 GCTTCGGCAGCACATATACTAAAAT CGCTTCACGAATTTGCGTGTCAT GAPDH AAGGTGAAGGTCGGAGTCAAC GGGGTCATTGATGGCAACAA LINC00162(PICSAR) CGTAGTGATAGTCCCGTGCC TGGCAAGACGGATGGAAACA hsa-mir-383 AACACGCCTCCTCAGATCAG CGCTTCACGAATTTGCGTGTCAT CBX5 AAAACTTGGATTGCCCTGAGC AGTCCTCTCTCAAAGCCCCG U6 Stem loop 5´-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAAAAATAT − 3´ hsa-mir-383 Stem loop 5´-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTCTTT-3´ 2.2.4. Statistical analysis The analysis of qPCR results and visualizing the graphs were performed using GraphPad Prism 8. Differences in the mentioned gene expression level between samples were determined using the Wilcoxon matched-pairs signed rank test, paired and unpaired t-test, and Mann-Whitney test. A significant P value was measured to less than 0.05. 3. Results 3.1. In-silico analysis 3.1.1. PICSAR(LINC00162) is overexpressed in TCGA-STAD dataset The qPCR findings were confirmed by analyzing the TCGA-STAD database, which allowed for thorough validation of the experiment. In comparison to normal samples, GC samples show a considerably higher expression of LINC00162 (p < 0.0001), according to the results given by the TCGA-STAD analysis and the Gepia online tools (Fig. 1 a, b). Moreover, as seen in Fig. 1 c, the LINC00162 gene's expression may serve as a diagnostic target for distinguishing GC from healthy samples. 3.1.2. Dysregulation of LINC00162 (PICSAR) is significant in all cancers. The TCGA database revealed that LINC00162, or PICSAR (P38 inhibited cutaneous squamous cell carcinoma associated lincRNA), is dysregulated in several cancer types. A comprehensive pan-cancer study included gastrectomy. Data from over 11,000 patients with over 30 cancer types provided a complete understanding of LINC00162 dysregulation. This thorough analysis found regular LINC00162 expression patterns and showed good statistical abilities to identify healthy and malignant tissues. The Ualcan database's pan-cancer study found dysregulation of LINC00162 in all cancers, including gastric cancer (Fig. 2 ). The TCGA database revealed that LINC00162, or PICSAR (P38 inhibited cutaneous squamous cell carcinoma associated lincRNA), is dysregulated in several cancer types. A comprehensive pan-cancer study included gastrectomy. Data from over 11,000 patients with over 30 cancer types provided a complete understanding of LINC00162 dysregulation. This thorough analysis found regular LINC00162 expression patterns and showed good statistical abilities to identify healthy and malignant tissues. The Ualcan database's pan-cancer study found dysregulation of LINC00162 in all cancers, including gastric cancer. 3.1.3. Gastric cancer development is induced by overexpression of LINC00162 (PICSAR). Overexpression of LINC00162 (PICSAR) is a hallmark of all gastric cancer types, stages, and grades, according to a thorough examination of TCGA data and pathology samples. Its possible involvement in the initiation and advancement of gastric cancer is supported by the persistent pattern of increased LINC00162 expression and its correlation with poor clinical outcomes. These results raise the possibility that LINC00162 is a therapeutic target and a useful biomarker for the diagnosis and prognosis of gastric cancer. We need further studies on LINC00162 to figure out how it causes cancer and what it can do in the clinic. As shown in Fig. 3 , the expression level of LINC00162 was significantly increased across all grades, stages, and kinds of gastric cancer. 3.1.4. Overexpression of LINC00162 (PICSAR) affects the survival rate of gastric cancer samples Overexpression of LINC00162 (PICSAR) is a notable characteristic in gastric cancer and is linked to worse survival outcomes, according to the combined analysis of the TCGA and KM plot databases. Potentially useful as a prognostic biomarker, increased LINC00162 levels are associated with worse overall and disease-free survival rates. These results demonstrate that LINC00162 is an important factor in the development of gastric cancer and that it may have therapeutic uses. To further understand LINC00162's potential as a therapeutic target and its molecular functions in oncogenesis, more study is required. The LINC00162 survival rate in the TCGA-STAD and KM plot datasets is shown in Fig. 4 . 3.1.5. lncRNA-microRNA interaction An investigation of the LncRNA-miRNA network utilizing the LncACT database showed a key interaction between PICSAR and hsa-miR-383 after the finding of the major dysregulated lncRNA LINC00162 (PICSAR) in gastric cancer. Because of this relationship, it is possible that PICSAR modulates the activity of hsa-miR-383, an endogenous RNA that competes with it, and hence affects the course of gastric cancer. The negative association between PICSAR and hsa-miR-383 expression levels highlights the possibility that the PICSAR-hsa-miR-383 interaction contributes to the development of gastric cancer. Table 2 provides a detailed display of the interaction between PICSAR and hsa-miR-383. In gastric cancer, hsa-miR-383 is significantly downregulated, according to the TCGA-STAD database thorough study. This downregulation is seen in stomach cancer of different grades, stages, and histological subtypes, indicating a common and extensive pattern. The possible involvement of hsa-miR-383 in the advancement of gastric cancer is highlighted by the link between low levels of this gene and advanced tumor characteristics as well as poor clinical outcomes. These results point to hsa-miR-383 as a possible diagnostic and prognostic biomarker and therapeutic intervention target in gastric cancer, and they provide light on the molecular underpinnings of this disease. We need further studies to determine what role the downregulation of hsa-miR-383 plays in gastric cancer survival. Figure 5 reveals that hsa-miR- 383 expression is dramatically downregulated in gastric cancer (TCGA-STAD), and Fig. 6 shows that this downregulation is consistent across all gastric cancer grades, stages, and types. Table 2 Detailed display of the interaction between PICSAR and hsa-miR-383. LncRNA microRNA species experimental Pubmed ID reference LINC00162(PICSAR) hsa-miR-383 Homo sapiens (human) luciferase reporter assays; qRT-PCR; Northern blot assay 26539909 3.1.6. microRNA-mRNA interaction The miRmap database was used to investigate the gastric cancer microRNA-mRNA interaction network, and one of the targets of hsa-miR-383 was CBX5 mRNA. There is a significant negative relationship between the levels of hsa-miR-383 and CBX5 mRNA, which means that lowering hsa-miR-383 might cause CBX5 mRNA to rise, which could lead to gastric cancer. The results show that hsa-miR-383 and CBX5 mRNA might be used as diagnostic biomarkers and therapeutic targets for gastric cancer. Discovering its therapeutic uses in the treatment of stomach cancer and understanding the functional processes underneath this regulatory axis requires more investigation. Table 3 shows a comprehensive look into how hsa-miR-383 and CBX5 interact. In gastric cancer (TCGA-STAD), CBX5 expression is significantly elevated (Fig. 7 ), and this overexpression is constant across all gastric cancer grades, stages, and types (Fig. 8 ). Table 3 Detailed display of the interaction between hsa-miR-383 and CBX5. miRNA Gene Probability exact Conservation PhyloP miRmap score hsa-miR-383 CBX5 92.66967 1.31E-05 98.5693 3.1.7. Functional enrichment analysis Multiple pathways substantially related to CBX5 in gastric cancer were found by the functional enrichment analysis utilizing the Reactome database. Megakaryocyte formation, hemostasis, post-translational modifications, transcription control, and CBX5 are all essential biological functions. Based on these results, CBX5 may affect a wide range of cellular processes and regulatory systems, suggesting a complex involvement in the development of gastric cancer. To further understand the therapeutic potential of targeting CBX5 and its related pathways in the treatment of gastric cancer, further study is necessary. Table 4 shows the biological pathways related to CBX5 mRNA. Table 4 The related biological pathways of CBX5 mRNA. Pathways Gene Factors Involved in Megakaryocyte Development and Platelet Production R-HSA-983231 CBX5 Gene Expression (Transcription) R-HSA-74160 CBX5 Hemostasis R-HSA-109582 CBX5 Post-translational Protein Modification R-HSA-597592 CBX5 RNA Polymerase II Transcription R-HSA-73857 CBX5 SUMO E3 Ligases SUMOylate Target Proteins R-HSA-3108232 CBX5 SUMOylation Of Chromatin Organization Proteins R-HSA-4551638 CBX5 Transcriptional Regulation by E2F6 R-HSA-8953750 CBX5 Generic Transcription Pathway R-HSA-212436 CBX5 Metabolism Of Proteins R-HSA-392499 CBX5 3.2. Experimental validation 3.2.1. PICSAR(LINC00162) is significantly overexpressed in gastric cancer tissue samples. The results of the quantitative PCR (qPCR) study showed that PICSAR (LINC00162) is 4.5 times more abundant in gastric cancer samples than in normal tissues that were medically matched (P < 0.0001). Additional testing using ROC curve analysis confirmed PICSAR's diagnostic promise; the results showed a high area under the curve (AUC) of 0.9236 (95% CI: 0.8518–0.9954), proving the system's excellent diagnostic accuracy. With a sensitivity of 85% and a specificity of 90%, PICSAR proved to be an effective biomarker for differentiating gastric cancer tissues from normal tissues. This was established using the Youden index, which suggested the ideal cut-off value. In gastric cancer, PICSAR is significantly upregulated, and these results suggest that it may be useful for early detection and disease monitoring. (Fig. 9 ) 3.2.2. hsa-miR-383 is significantly downregulated in gastric cancer tissue samples. Gastric cancer tissues showed a substantially decreased expression of hsa-miR-383 compared to normal tissues that were matched, with an average expression level four times lower in cancer samples (P < 0.0001), according to quantitative PCR (qPCR) research. The diagnostic capability of hsa-miR-383 was shown by the Receiver Operating Characteristic (ROC) curve analysis, which produced an area under the curve (AUC) of 0.8194 (P < 0.0001), suggesting a robust diagnostic accuracy. By using the Youden index to calculate the ideal cut-off value, hsa-miR-383 demonstrated its potential as a biomarker for differentiating gastric cancer tissues from normal tissues with a sensitivity of 95% and a specificity of 85%. In gastric cancer, hsa-miR-383 is significantly downregulated, and these results suggest that it may be useful for early detection and disease monitoring. (Fig. 10 ) 3.2.3. CBX5 is significantly upregulated in gastric cancer tissue samples. A mean expression level 2.04-fold higher in cancer samples (P < 0.0001) was found by quantitative PCR (qPCR) research, which showed that CBX5 is considerably elevated in gastric cancer tissues compared to matched normal tissues. The diagnostic potential of CBX5 was shown by the Receiver Operating Characteristic (ROC) curve study, which produced an area under the curve (AUC) of 0.9375 (P < 0.0001), thus suggesting a high level of diagnostic accuracy. Highlighting CBX5's potential as a biomarker for differentiating gastric cancer tissues from normal tissues, the Youden index established the ideal cut-off value, which produced a sensitivity of 90% and a specificity of 85%. These results demonstrate that CBX5 is highly upregulated in gastric cancer and suggest that it may be useful for both early detection and disease tracking. (Fig. 11 ) 3.2.4. Pathology characteristics of LINC00162, hsa-miR-383, and CBX5 The study examined the correlation between three molecular markers (LINC00162, hsa-miR-383, and CBX5) and a range of clinicopathological variables found in the samples. These variables included age, gender, tumor size, grade, serosal invasion, lymphatic invasion, vascular invasion, perineural invasion, and stage. Interestingly, neither LINC00162 nor hsa-miR-383 expression was significantly associated with any of these clinicopathological variables, as demonstrated by the lack of statistical significance (p > 0.05). That these two markers' expression is uncorrelated with the tumors' ages, genders, sizes, grades, or stages is suggestive. The expression of CBX5 is linked to two clinicopathological characteristics, however. First, patients older than 60 years had substantially greater CBX5 expression than those younger than 60 years (p = 0.0064). The second finding is that tumors bigger than 5 cm had much greater CBX5 expression than smaller ones (p = 0.0183). Results show that older patients and higher tumor sizes are associated with greater CBX5 expression, which may be a marker of aggressive tumors. Based on the data, it seems that CBX5 expression has the greatest promise as a biomarker for prognosis or prediction among the three molecular markers. This is because it is associated with specific clinicopathological findings. The biological and pathological significance of CBX5 in the malignancies included in this dataset remains unclear and requires more research. (Table 5 ) Table 5 The association between the expression of LINC00162, hsa-miR-383, and CBX5 and various clinicopathological characteristics of the gastric cancer samples Properties LINC00162 (PICSAR) hsa-miR-383 CBX5 p-value p-value p-value Age 0.3123 (ns) 0.1836 (ns) 0.0064 (**) 60 (n=13) Gender 0.1282 (ns) 0.2608 (ns) 0.4248 (ns) Male (n=20) Female (n=4) Tumor size 0.7640 (ns) 0.9844 (ns) 0.0183 (*) 5 (n=13) Grade 0.4993 (ns) 0.6419 (ns) 0.1599 (ns) I, II (n=16) III, IV (n=8) Serosal invasion 0.7656 (ns) 0.5386 (ns) 0.9831 (ns) Yes (n=13) No (n=11) Lymphatic invasion 0.1957 (ns) 0.3318 (ns) 0.5969 (ns) Yes (n=18) No (n=6) Vascular invasion 0.1957 (ns) 0.3318 (ns) 0.5969 (ns) YES (n=18) NO (n=6) Perineural invasion 0.4141 (ns) 0.6386 (ns) 0.6332 (ns) Yes (n=17) No (n=8) Stage 0.4976 (ns) 0.1781 (ns) 0.6954 (ns) 4. Discussion Stomach cancer is still a big concern, even though cancer detection and therapy have come a long way. Scientific studies have demonstrated that the mortality rate from stomach cancer can be drastically decreased with early detection. This being the case, early identification of stomach cancer still necessitates research into the pathogenic molecular pathways producing the disease. [ 32 – 34 ]. The expression of LINC00162 in gastric cancer transcriptional regulation is affected by a wide variety of RNA interactions. LINC00162 (PICSAR) may control the advancement of gastric cancer via interacting with microRNAs and messenger RNAs. In gastric cancer, our work primarily focuses on PICSAR expression and how it is correlated with hsa-miR-383 and CBX5 mRNAs. The results of this study provide strong evidence that the dysregulation of PICSAR (LINC00162), hsa-miR-383, and CBX5 is involved in the development and progression of gastric cancer (GC). Specifically, compared to normal tissue samples, gastric cancer tissue samples showed a significant upregulation of PICSAR, which was found to be negatively correlated with hsa-miR-383 expression and positively correlated with CBX5 RNA expression. In light of recent studies, this section will synthesize the main results and investigate their relevance (Fig. 12 ). Long non-coding RNAs (lncRNAs) regulate gene expression at numerous levels, including chromatin modification, transcription, and post-transcriptional processing; they play a crucial role in the advancement of gastric cancer and other malignancies. The way lncRNAs sponge on microRNAs (miRNAs) is a crucial way they impact the advancement of cancer. Local non-coding RNAs (lncRNAs) compete with microRNAs (miRNAs) for interaction sites on messenger RNAs (mRNAs). Through this regulatory mechanism, lncRNAs in gastric cancer can alter the expression of genes that are involved in significant processes such as cell migration, apoptosis, and proliferation. To illustrate the point, some lncRNAs can bind to miRNAs that limit tumor growth; this leads to an overexpression of oncogenes that enhance tumor development, metastasis, and chemotherapy resistance. On the flip side, some lncRNAs can prevent cancer from progressing by binding to oncogenic miRNAs and increasing the expression of tumor suppressor genes. Due to their association with poor prognosis, lncRNA dysregulation in gastric cancer raises hopes that these molecules may one day serve as biomarkers for early detection and therapeutic intervention targets. Understanding the roles and mechanisms of lncRNA is crucial for the development of more effective treatments for gastric cancer, and this complicated network of interactions between lncRNA, miRNA, and mRNA highlights this point[ 35 – 38 ]. Our study demonstrated a significant overexpression of PICSAR (LINC00162) in gastric cancer tissues compared to normal tissues, with a 4.5-fold increase observed via quantitative PCR (qPCR) analysis. This overexpression was also corroborated by in-silico analysis using the TCGA-STAD and Gepia online tools, which revealed a marked upregulation of LINC00162 in GC samples (p < 0.0001). The Receiver Operating Characteristic (ROC) curve analysis further validated the diagnostic potential of PICSAR, with an area under the curve (AUC) of 0.9236, indicating high diagnostic accuracy. These findings suggest that PICSAR could serve as a robust biomarker for distinguishing GC from normal tissue and could be instrumental in the early detection and monitoring of the disease. Multiple lncRNAs implicated in stomach cancer growth and metastasis have been isolated by researchers. Case in point: research by Xia et al. (2016) has established lncRNA MALAT1 as a major metastatic biomarker[ 39 ]. This study shows that gastric cancer tissues have much higher MALAT1 expression, which is associated with a worse prognosis and increased metastatic potential. A possible diagnostic marker and therapeutic target for early detection of metastatic gastric cancer, MALAT1 is involved in increasing angiogenesis and cell invasion. In addition to MALAT1, the function of lncRNA H19 in cancer progression and metastasis has been the subject of much research. Guo et al[ 40 ]. (2014) H19 is overexpressed in gastric cancer, according to this research. In this kind of cancer, it acts as a molecular sponge, soaking up microRNAs and influencing the expression of genes that drive tumor development and metastasis. The activation of carcinogenic pathways is a consequence of this sponging action, which adds to the aggressiveness of the illness. The role of lncRNA MEG3 in suppressing tumor growth in gastric cancer has been acknowledged, on the other hand. By activating the p53 signaling pathway, MEG3 suppresses the growth and spread of cancer cells. According to research, gastric cancer tissues often have MEG3 downregulation, which results in reduced p53 activity and unregulated cell proliferation. These factors are associated with poor clinical outcomes[ 41 ]. Taken together, our results highlight the multifaceted functions of lncRNAs in gastric cancer; whilst MALAT1 and H19 promote cancer growth, MEG3 suppresses tumors; these findings provide new avenues for disease management and possible therapeutic targets. Our findings are consistent with the findings of the studies that emphasize the significant part that a variety of long noncoding RNAs play in the advancement of gastric cancer. Also, the results of our study show the potential of hsa-miR-383 as a diagnostic biomarker is highlighted by its substantial downregulation in GC tissues, which is four times lower than in normal tissues. The diagnostic accuracy was highlighted by the ROC curve analysis, which produced an AUC of 0.8194 (p < 0.0001). PICSAR may modulate the activity of hsa-miR-383, which in turn affects the advancement of GC, according to the negative association between the two. The relationship between long non-coding RNAs and microRNAs provides new insight into the pathophysiology of GC and suggests potential targets for personalized treatments. Last but not least The CBX5 gene was shown to be significantly upregulated in GC tissues compared to normal tissues, with an average expression level 2.04 times higher (p < 0.0001). With an area under the curve (AUC) of 0.9375, it was shown to be very specific and sensitive in differentiating GC from normal tissues, confirming its diagnostic potential in the ROC study. Megakaryocyte formation, hemostasis, and transcriptional control are only a few of the crucial biological processes that CBX5 is engaged in, according to functional enrichment analysis. According to these results, CBX5 is a diagnostic biomarker and may have an important function in the pathophysiology of GC, which makes it a possible therapeutic target. One important way lncRNAs contribute to cancer progression is by acting as a sponge for miRNAs. Messenger RNAs (mRNAs) have interaction sites that local non-coding RNAs (lncRNAs) and microRNAs (miRNAs) vie for. In gastric cancer, lncRNAs regulate gene expression by this approach, changing genes involved in important processes such as cell migration, apoptosis, and proliferation. A complex regulatory network controlling GC formation is suggested by the overexpression of PICSAR, together with the downregulation of hsa-miR-383 and the increase of CBX5 mRNA. The complex connection between PICSAR and hsa-miR-383, as well as the possible control of CBX5 by hsa-miR-383, suggests a potential therapeutic target. In addition to diagnostic applications, these biomarkers hold great promise for the creation of individualized treatment plans that target specific expression levels. According to the findings of Dong et al. (2019), patients with stomach cancer who exhibited high levels of the long noncoding RNA HOTAIR had a poor prognosis. Through the process of sponging miR-217, HOTAIR performs the role of a ceRNA and upregulates the oncogene GCP5, which results in gastric cancer progression[ 42 ]. Li et al. (2017) discovered that lncRNA MALAT1 promotes the advancement of gastric cancer via interacting with miR-1297. MALAT1 enhances cancer cell invasion and metastasis by sponge-acting on miR-1297, a gene that typically controls the production of the oncogene HMGB2[ 43 ]. According to the findings of Liu et al. (2016), the long noncoding RNA GAS5 sponging miR-23 has an influence on the growth of gastric cancer via modifying MT2A mRNA and contributes to the progression of cancer[ 44 ]. According to the findings of the research carried out by Gong et al. (2018), the long noncoding RNA UCA1 is responsible for the advancement of gastric cancer by sponging miR-203, which targets oncogenes such as ZEB2. In addition to contributing to increased cancer cell proliferation and metastasis, the capacity of UCA1 to sequester miR-203 is a significant factor[ 45 ]. PVT1 is discovered to operate as an oncogene via sponging miR-152, according to the findings of research that was conducted by Li et al. (2017). The study investigated the role of lncRNA PVT1 in gastric cancer. This connection results in the overexpression of its target genes, such as CD151 and FGF2, which are responsible for promoting cell proliferation and inhibiting apoptosis[ 46 ]. Table 6 provides a comprehensive overview of the research that was discussed in detail. Table 6 A brief overview of the Lnc-microRNA-mRNA axis in gastric cancer, including our findings LncRNA Sponged microRNA mRNA Study Findings Our Findings HOTAIR hsa-miR-217 GCP5 Dong et al. (2019) High levels of HOTAIR promote gastric cancer progression via miR-217 sponging. By targeting pathways involved in hemostasis, elevated levels of LINC00162 (PICSAR) encourage the growth of gastric cancer by miR-383 sponging, which upregulates CBX6. MALAT1 hsa-miR-1297 HMGB2 Li et al. (2017) MALAT1 promotes invasion through miR-1297 sponging. GAS5 hsa-miR-23 MT2A Liu et al. (2016) GAS5 has an oncogenic effect by sponging miR-23. UCA1 hsa-miR-203 ZEB2 Gong et al. (2018) UCA1 promotes progression through miR-203 sponging. PVT1 hsa-miR-152 CD151 and FGF2 Li et al. (2017) PVT1 promotes proliferation via miR-152 sponging. Important biomarkers that are drastically dysregulated in stomach cancer have been found in this investigation. New possibilities for diagnosis and therapy are opened up by the downregulation of hsa-miR-383 and the overexpression of PICSAR and CBX5. These findings provide light on the molecular basis of GC. We can learn more about GC and create better ways to fight it if we dig deeper into these biomarkers, but in the future, researchers need to validate these biomarkers in bigger, separate cohorts and figure out the molecular mechanisms behind these interactions. Further investigation into the therapeutic possibilities of targeting PICSAR, hsa-miR-383, and CBX5 in GC may lead to the discovery of novel treatment approaches. In order to put these results into reality, it is crucial to conduct clinical studies that evaluate the effectiveness of targeted medicines. 5. Conclusion Our research reveals a new gastric cancer predictive biomarker: the LINC00162/hsa-mir-383/CBX5 axis. There is great promise for early diagnosis and treatment along this axis, which also coincides with the hemostasis process. Further investigation into the molecular processes underlying the activity of lncRNAs is warranted in light of our results, which demonstrate their crucial involvement in the advancement of gastric cancer. Improved patient outcomes in stomach cancer will be possible as a result of the new insights offered by this research, which open the door to better diagnostic and therapeutic methods. Declarations Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding The authors are thankful for the support of the Immunology Research Center, Tabriz University of Medical Science (grant number: 74992). Ethics approval The ethical committee of the Immunology Research Center, Tabriz University of Medical Sciences approved the study. Written informed consent was obtained from all patients . Declaration All methods were carried out according to relevant guidelines and regulations. Acknowledgment The authors are thankful for the support of the Immunology Research Center, Tabriz University of Medical Science (grant number: 74992). Author contributions Conceptualization: AmirAli Mokhtarzadeh, Saeid Ghorbian Data curation: Seyed Ali Hoseini Formal analysis: AmirAli Mokhtarzadeh, Saeid Ghorbian Investigation: Seyed Ali Hoseini Methodology: Seyed Ali Hoseini, AmirAli Mokhtarzadeh, Saeid Ghorbian, Behzad Baradaran, Changiz Ahmadizadeh Project administration: AmirAli Mokhtarzadeh, Saeid Ghorbian Software: Seyed Ali Hoseini Supervision: AmirAli Mokhtarzadeh, Saeid Ghorbian Validation: AmirAli Mokhtarzadeh, Saeid Ghorbian, Behzad Baradaran, Changiz Ahmadizadeh Visualization: Seyed Ali Hoseini Writing–original draft: Seyed Ali Hoseini Data availability statement All data generated or analyzed in the current research are provided within the manuscript. References Sitarz R et al (2018) Gastric cancer: epidemiology, prevention, classification, and treatment. Cancer Manage Res 10:239–248 Piazuelo MB, Correa P (2013) Gastric cáncer: Overview. 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Nucleic Acids Res 40(22):11673–11683 Milacic M et al (2023) The Reactome Pathway Knowledgebase 2024. Nucleic Acids Res 52(D1):D672–D678 Griss J et al (2020) ReactomeGSA - Efficient Multi-Omics Comparative Pathway Analysis. Mol Cell Proteom 19(12):2115–2125 Lü M et al (2015) Downregulation of miR-320a/383-sponge-like long non-coding RNA NLC1-C (narcolepsy candidate-region 1 genes) is associated with male infertility and promotes testicular embryonal carcinoma cell proliferation. Cell Death Dis, 6(11): p. e1960 Matsuoka T, Yashiro M (2018) Biomarkers of gastric cancer: Current topics and future perspective. World J Gastroenterol 24(26):2818 González CA, Agudo A (2012) Carcinogenesis, prevention and early detection of gastric cancer: where we are and where we should go. Int J Cancer 130(4):745–753 Yamamoto H et al (2020) Non-invasive early molecular detection of gastric cancers. Cancers 12(10):2880 Yang G, Lu X, Yuan L (2014) LncRNA: a link between RNA and cancer. Biochimica et Biophysica Acta (BBA)-Gene Regulatory Mechanisms. 1839(11):1097–1109 Iaccarino I, Klapper W (2021) LncRNA as cancer biomarkers. Long Non-coding RNAs in Cancer, : pp. 27–41 Jiang M-C et al (2019) Emerging roles of lncRNA in cancer and therapeutic opportunities. Am J cancer Res 9(7):1354 Jariwala N, Sarkar D (2016) Emerging role of lncRNA in cancer: a potential avenue in molecular medicine. Annals translational Med, 4(15). Xia H et al (2016) The lncRNA MALAT1 is a novel biomarker for gastric cancer metastasis. Oncotarget 7(35):56209–56218 Li H et al (2014) Overexpression of lncRNA H19 enhances carcinogenesis and metastasis of gastric cancer. Oncotarget 5(8):2318–2329 Wei G-H, Wang X (2017) lncRNA MEG3 inhibit proliferation and metastasis of gastric cancer via p53 signaling pathway, vol 21. European Review for Medical & Pharmacological Sciences, 17 Dong X et al (2019) Long non-coding RNA Hotair promotes gastric cancer progression via miR-217-GPC5 axis. Life Sci 217:271–282 Li J et al (2017) Long non-coding RNA MALAT1 drives gastric cancer progression by regulating HMGB2 modulating the miR-1297. Cancer Cell Int 17:1–9 Liu X et al (2016) Long non-coding RNA GAS5 acts as a molecular sponge to regulate miR-23a in gastric cancer. Int J Exp Pathol 9:11412–11419 Gong P et al (2018) LncRNA UCA1 promotes tumor metastasis by inducing miR-203/ZEB2 axis in gastric cancer. Cell Death Dis 9(12):1158 Li T, Meng X-l, Yang W-q (2017) Long Noncoding RNA PVT1 Acts as a Sponge to Inhibit microRNA-152 in Gastric Cancer Cells. Dig Dis Sci 62(11):3021–3028 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-6423474","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442588081,"identity":"63aeb88e-bbe4-4a4a-b05b-b604eb24fa76","order_by":0,"name":"Seyed Ali Hoseini","email":"","orcid":"","institution":"Department of Molecular Genetics, Ah.C., Islamic Azad University, Ahar, Iran","correspondingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Ali","lastName":"Hoseini","suffix":""},{"id":442588082,"identity":"451069d0-09a0-46c6-9e5d-6a259265253c","order_by":1,"name":"AmirAli A. Mokhtarzadeh","email":"data:image/png;base64,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","orcid":"","institution":"Immunology Research Center, Tabriz University of Medical Sciences, Tabriz","correspondingAuthor":true,"prefix":"","firstName":"AmirAli","middleName":"A.","lastName":"Mokhtarzadeh","suffix":""},{"id":442588083,"identity":"1c6e0655-0525-4151-97e2-5aad23a9f781","order_by":2,"name":"Saeid Ghorbian","email":"","orcid":"","institution":"Department of Biology, Ta.C., Islamic Azad University, Tabriz, Iran","correspondingAuthor":false,"prefix":"","firstName":"Saeid","middleName":"","lastName":"Ghorbian","suffix":""},{"id":442588084,"identity":"57f1a160-e927-4c16-b00e-bba74d92a9ad","order_by":3,"name":"Behzad Baradaran","email":"","orcid":"","institution":"Immunology Research Center, Tabriz University of Medical Sciences, Tabriz","correspondingAuthor":false,"prefix":"","firstName":"Behzad","middleName":"","lastName":"Baradaran","suffix":""},{"id":442588085,"identity":"e2e9075d-ef98-41d8-a4c9-1db543bb359d","order_by":4,"name":"Changiz Ahmadizadeh","email":"","orcid":"","institution":"Department of Molecular Genetics, Ah.C., Islamic Azad University, Ahar","correspondingAuthor":false,"prefix":"","firstName":"Changiz","middleName":"","lastName":"Ahmadizadeh","suffix":""}],"badges":[],"createdAt":"2025-04-10 23:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6423474/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6423474/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81634197,"identity":"a76b2669-9fb4-4a5b-962a-4021c483d8b3","added_by":"auto","created_at":"2025-04-29 12:06:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":82379,"visible":true,"origin":"","legend":"\u003cp\u003ea) The TCGA-STAD dataset's LINC00162 expression level. A significant upregulation of LINC00162 (p \u0026lt; 0.0001) is seen in GC samples when compared to normal samples. b) using the Gepia online tool, the expression level of LINC00162 in the TCGA and GTEx. c) Using the TCGA-STAD dataset, the ROC curve was used to assess the biomarker strength of LINC00162; this might be a little diagnostic signal to differentiate GC from a normal sample.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/1e82246bf9d3d84a04b16158.png"},{"id":81632224,"identity":"7988ec51-7e14-4673-a1e8-7af272be0316","added_by":"auto","created_at":"2025-04-29 11:42:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":32662,"visible":true,"origin":"","legend":"\u003cp\u003eUalcan's pan-cancer investigation identified LINC00162 dysregulation in all malignancies, including gastric cancer.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/6d0ff1b027f81da72fd8fd84.png"},{"id":81632222,"identity":"62c99c4e-a774-4c47-bd8e-1e0dc8c9acec","added_by":"auto","created_at":"2025-04-29 11:42:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56476,"visible":true,"origin":"","legend":"\u003cp\u003eLINC00162 expression value between normal and gastric cancer samples and its correlation with multiple histological subtypes(a), different stages of disease(b), and diverse tumor grades(c).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/f7ad26081718523486b651a3.png"},{"id":81632812,"identity":"51cb5fd7-91ab-4307-adc8-c9f8916acc52","added_by":"auto","created_at":"2025-04-29 11:50:53","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":98329,"visible":true,"origin":"","legend":"\u003cp\u003eThe LINC00162 survival rate in the KM plot(a) and TCGA-STAD(b) datasets.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/85a0bc3fd5258c6f7925f999.png"},{"id":81635060,"identity":"d3adeeaa-efb9-4e3d-a757-e44ef88fceac","added_by":"auto","created_at":"2025-04-29 12:14:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":18567,"visible":true,"origin":"","legend":"\u003cp\u003ehsa-miR-383 expression is dramatically downregulated in gastric cancer (TCGA-STAD),\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/0a2c6dc0ece7494aee702a7c.png"},{"id":81632801,"identity":"9978b717-bbab-4327-b2a9-48a135bf3b60","added_by":"auto","created_at":"2025-04-29 11:50:52","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":54984,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression value of hsa-miR-383 in gastric cancer and normal samples, as well as its association with various histological subtypes (a), illness stages (b), and tumor grades (c).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/a2b11a1cc123049ed3abbddd.png"},{"id":81632807,"identity":"0f35640e-4fc3-4919-bbf1-6d71f803a3a6","added_by":"auto","created_at":"2025-04-29 11:50:52","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":14982,"visible":true,"origin":"","legend":"\u003cp\u003eCBX5 expression is dramatically upregulated in gastric cancer (TCGA-STAD),\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/9b3b80a07a947e7a27809619.png"},{"id":81633859,"identity":"27fd8c06-d756-4d79-9e4a-f4c2654f9672","added_by":"auto","created_at":"2025-04-29 11:58:52","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":60219,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression value of CBX5 in gastric cancer and normal samples, as well as its association with various histological subtypes (a), illness stages (b), and tumor grades (c).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/0cd50d1310792338fb1ce4cb.png"},{"id":81634198,"identity":"e1b6cd50-ae4e-490c-a4ce-93427c246c0c","added_by":"auto","created_at":"2025-04-29 12:06:52","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":47347,"visible":true,"origin":"","legend":"\u003cp\u003eThe expression of LINC00162 (PICSAR) was significantly upregulated in gastric cancer tissue specimens (N = 25) compared to adjacent tissue specimens (N = 25) in q-PCR analysis (a), with a p-value of less than 0.0001. With an area under the curve (AUC) of 0.9236 (p \u0026lt; 0.0001), the ROC curve for LINC00162 (PICSAR) as a biomarker suggests it might be a diagnostic target for differentiating GC from normal samples (b).\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/5ebd179e5826369f6b5550e2.png"},{"id":81632809,"identity":"ab6aa0bc-a998-4eea-9c31-900f954ba5fe","added_by":"auto","created_at":"2025-04-29 11:50:53","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":49029,"visible":true,"origin":"","legend":"\u003cp\u003eThe results of the q-PCR study showed that the expression of hsa-miR-383 was considerably decreased in gastric cancer tissue specimens (N = 25) as compared to adjacent tissue specimens (N = 25) (p-value less than 0.0001). The area under the curve (AUC) for has-miR-383 as a biomarker is 0.8194 (p \u0026lt; 0.0001), which indicates that it might be a diagnostic target for distinguishing GC from normal samples (b).\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/258568de30ddccb115bb9fff.png"},{"id":81632803,"identity":"22bf080a-5a62-4d38-8589-b4797611b28e","added_by":"auto","created_at":"2025-04-29 11:50:52","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":47068,"visible":true,"origin":"","legend":"\u003cp\u003eGastric cancer tissue specimens (N = 25) had significantly higher CBX5 expression compared to nearby tissue specimens (N = 25) (p-value less than 0.0001), according to the q-PCR analysis (a). It seems that CBX5 might be a diagnostic target for differentiating GC from normal samples (b) since its area under the curve (AUC) as a biomarker is 0.9375 (p \u0026lt; 0.0001).\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/188e50bd3ad2f145b95930e4.png"},{"id":81632232,"identity":"e001b6df-1121-4539-8438-2e82e8b2d420","added_by":"auto","created_at":"2025-04-29 11:42:52","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":58681,"visible":true,"origin":"","legend":"\u003cp\u003eThe dysregulation of CBX5 could be caused by the overexpression of PICSAR (LINC00162), which acts as a sponge for has-miR-383 and suppresses its expression.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/e31866f059664506eda20366.png"},{"id":83979543,"identity":"9513e03b-c004-4dca-8675-601917f1b928","added_by":"auto","created_at":"2025-06-05 09:39:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1874446,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6423474/v1/b2b874da-f6e1-407f-977a-559f7062e9e7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Identification of the LINC00162/hsa-mir-383/CBX5 Axis as a novel prognostic biomarker associated with hemostasis in gastric cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eGastric cancer, often known as stomach cancer, is a major global public health problem due to its high incidence and fatality rates. It is among the main causes of cancer-related fatalities in the globe[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. With a primary focus on the stomach lining, the illness has the potential to extend to the esophagus, liver, lungs, and lymph nodes, among other regions of the body[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Gastric cancer is the world's fifth most frequent cancer, with more than a million new cases identified each year. It is also the third greatest cause of cancer-related fatalities, accounting for around 783,000 deaths each year[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Gastric cancer has a massive worldwide impact, resulting in enormous healthcare expenses and lost productivity. It also imposes significant emotional and financial burdens on patients and their families[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Gastric cancer is a serious public health issue with a large worldwide death burden. Continued research, early identification, and preventative actions are required to properly battle this devastating illness[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Genetic factors have an important influence on the development of stomach cancer. While environmental variables including nutrition, Helicobacter pylori infection, and lifestyle choices are important, genetic predisposition can also impact a person's vulnerability to stomach cancer[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough they do not encode proteins, long non-coding RNAs (lncRNAs) are a family of RNA molecules that are essential for controlling gene expression and biological functions. Emerging data suggests that lncRNAs play an important role in the development and progression of gastric cancer[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. lncRNAs can influence gene expression at several levels, including as chromatin remodeling, transcription, and post-transcriptional processing. In gastric cancer, dysregulated lncRNAs can affect the expression of oncogenes or tumor suppressor genes, hence promoting carcinogenesis. lncRNAs can behave as molecular sponges for microRNAs (miRNAs), trapping them and blocking them from attaching to their intended mRNAs[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In gastric cancer cells, this interaction can cause oncogenic pathways to be activated or tumor-suppressive pathways to be inhibited. In gastric cancer, it has been demonstrated that some lncRNAs stimulate cell division and prevent apoptosis[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. For instance, enhanced cell proliferation, invasion, and metastasis are linked to the overexpression of the lncRNA HOTAIR in gastric cancer[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Through their ability to control metastasis and angiogenesis, or the growth of new blood vessels, lncRNAs can have an impact on the tumor microenvironment. For example, by regulating the production of\u003c/p\u003e \u003cp\u003ematrix metalloproteinases (MMPs) and vascular endothelial growth factor (VEGF), the lncRNA MALAT1 has been linked to the promotion of angiogenesis and metastasis in gastric cancer[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Through various pathways, the PICSAR lncRNA[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], has-miR-383[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and CBX5 gene [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] are all important players in the development of cancer. By stimulating pathways including MAPK/ERK and modifying gene expression, PICSAR lncRNA is linked to the promotion of cell invasion, proliferation, and chemoresistance in several malignancies, including cutaneous squamous cell carcinoma. Depending on the situation, hsa-miR-383 can either promote or repress the development of cancer. It controls oncogene expression, cell cycle progression, and apoptosis in several cancer types. By preserving chromatin structure and suppressing gene expression, CBX5, also known as HP1α, plays a role in cancer biology and acts as a tumor suppressor in many different types of cancer. These molecules demonstrate the variety of ways that chromatin regulators and non-coding RNAs impact oncogenesis, highlighting their potential as targets for therapeutic intervention in cancer therapy approaches[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The significance of competing endogenous RNA (ceRNA) networks in stomach cancer has been brought to light by recent research. found a possible immuno-therapeutic target in gastric cancer with varying degrees of immune cell infiltration along the RP11-1094M14.8/miR-1269a/CXCL9 axis[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This work is a ground-breaking effort that advances our knowledge of genetic variation and the consequences it bears, especially when taking into account the mechanistic bioinformatics and systems biology techniques and the number of genes employed. There is no evidence to support a link between gastric cancer and the LINC00162/has-mir-383/CBX5 Axis. The current work sought to determine the expression of the LINC00162 (PICSAR) gene and the associated miRNA-mRNA axis in GC tissue samples, as well as to assess the diagnostic utility of these findings utilizing bioinformatic databases and tools. Our research may offer fresh perspectives on the molecular causes of GC as well as recommend cutting-edge methods for the diagnosis and management of GC.\u003c/p\u003e"},{"header":"2. Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. In-silico analysis\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Bulk RNA analysis\u003c/h2\u003e \u003cp\u003eThe Cancer Genome Atlas (TCGA) performed thorough research to acquire datasets including samples from different forms of stomach cancer, as well as control samples from people who were not afflicted by the condition. The aforementioned dataset, TCGA-STAD, was identified among the returning datasets and then downloaded. The TCGA-STAD dataset comprises gathered and aggregated RNA sequencing profiles. It comprises gene expression data from two groups: control samples from healthy people and samples from patients with gastric cancer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Data processing\u003c/h2\u003e \u003cp\u003eThe current study employed RNA sequencing data obtained via the usage of the TCGAbiolinks program. TCGAbiolinks is a unique R-based program used to get data from the TCGA-STAD database. The TCGAbiolinks package aided the downloading procedure. The data was then normalized using the Limma tool, a widely used R-based approach for normalizing data in gene expression studies. Following adequate data normalization, we used the aforementioned R tools to analyze differentially expressed genes (DEGs). The finding of differentially expressed genes (DEGs) served as a foundation for further research and the formation of diverse networks, allowing for a more thorough understanding of the molecular processes underlying the analyzed state. The identification of differentially expressed lncRNAs was accomplished using an examination of the information provided by The Cancer Genome Atlas (TCGA) and the significant dysregulated novel long non-coding RNA was selected for further analysis. The data was presented and analyzed with the GraphPad Prism program. Multiple graphs and plots were obtained and shown using the TCGA browser, namely the Ualcan online tool [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ualcan.path.uab.edu/\u003c/span\u003e\u003cspan address=\"https://ualcan.path.uab.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Xena Functional Genomics Explorer [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xenabrowser.net/\u003c/span\u003e\u003cspan address=\"https://xenabrowser.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) Additionally, the Kaplan-Meier plots were generated using the Kaplan-Meier Plotter database [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://www.kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3. lncRNA-microRNA interaction\u003c/h2\u003e \u003cp\u003eFollowing the identification of the significant dysregulated lncRNA in gastric cancer, the competing endogenous RNA network, or LncRNA-microRNA network, was examined to identify the competing molecules that act as microRNA sponges. To accomplish this objective, the LncACT online tool [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bio-bigdata.hrbmu.edu.cn/LncACTdb/\u003c/span\u003e\u003cspan address=\"http://bio-bigdata.hrbmu.edu.cn/LncACTdb/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to identify the interaction between long non-coding RNAs (lncRNAs) and microRNAs (miRNAs).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.4. microRNA-mRNA interaction\u003c/h2\u003e \u003cp\u003eThe microRNA-mRNA interaction network was rebuilt following the identification of an LncRNA-microRNA axis, which exhibits significant dysregulation and coordination across several pathways. The miRmap database [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mirmap.ezlab.org/\u003c/span\u003e\u003cspan address=\"https://mirmap.ezlab.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for the specific purpose at hand. The previously described database was utilized to identify the microRNAs that were chosen to target the candidate mRNA. MicroRNAs may be used as both therapeutic agents and diagnostic biomarkers for stomach cancer, according to the study's findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.5. Functional enrichment analysis\u003c/h2\u003e \u003cp\u003eThe molecular pathways linked to the expression of the CBX5 gene in gastric cancer were illuminated by a functional enrichment analysis conducted using the Reactome database [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://reactome.org/\u003c/span\u003e\u003cspan address=\"https://reactome.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Potential targets for therapeutic intervention and future study were discovered by this analysis as important pathways that may be associated with the oncogenic processes controlled by CBX5.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Experimental validation\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Preparation of Sample\u003c/h2\u003e \u003cp\u003eTwenty-five samples of matching tumor margin tissue and twenty-five samples of GC tissue were gathered. A formal informed consent form was signed by each participant. Chemotherapy or radiation therapy was never administered before any surgical procedure. Prior to RNA extraction, the samples were stored at 80\u0026deg;C after being snap-frozen in liquid nitrogen. Information about the tumor's size, age, gender, lymphatic and vascular invasion, serosal invasion, histological grade, clinical stage, and perineural invasion was included in the patient profiles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. RNA extraction and cDNA synthesis\u003c/h2\u003e \u003cp\u003eTissue samples were initially pulverized using a mortar and pestle while submerged in liquid nitrogen, and then transferred to a lysis buffer for further homogenization. To extract total RNA, we followed the instructions for the Trizol reagent (Riboex brand, Gene All). The total RNA quantity and purity were assessed with a NanoDrop spectrophotometer. Subsequently, 1 \u0026micro;g of total RNA was added to a final volume of 20 \u0026micro;l, and cDNA was synthesized in a thermocycler PCR following the standard protocol: 30 minutes at 50\u0026deg;C for reverse transcription, 5 minutes at 95\u0026deg;C to deactivate the RT enzyme, and holding at 10\u0026deg;C indefinitely.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Real-Time PCR (qPCR)\u003c/h2\u003e \u003cp\u003eThe experimental protocol utilized BioFACT\u0026trade; 2X Real-Time PCR Master Mix and gene-specific primers to perform Real-Time PCR, with a total reaction volume of 10 \u0026micro;l. The procedure consisted of three main phases: In the first phase, the temperature was increased to 95\u0026deg;C for 13 minutes as the holding stage or initial heat. In the second phase, the denaturation step was performed at 95\u0026deg;C for 10 seconds over 45 cycles. Following denaturation, primer annealing occurred at 60\u0026deg;C for 30 seconds, and extension took place at 72\u0026deg;C for 20 seconds. In the final phase, melting curves were recorded at the end of each run. The GAPDH gene was used for data normalization, and target gene expression was quantified using the 2-ΔΔCt method. Primer design was conducted using the NCBI Primer-3 online tool, available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/tools/primer-blast/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/tools/primer-blast/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides the primer sequences used for quantitative polymerase chain reaction (qPCR).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eqPCR primer sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTarget gene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward (5\u0026prime; \u0026ndash; 3\u0026prime;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse (5\u0026prime; \u0026ndash; 3\u0026prime;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eU6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCTTCGGCAGCACATATACTAAAAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCGCTTCACGAATTTGCGTGTCAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGAPDH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAGGTGAAGGTCGGAGTCAAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGGGTCATTGATGGCAACAA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLINC00162(PICSAR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGTAGTGATAGTCCCGTGCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGGCAAGACGGATGGAAACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ehsa-mir-383\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAACACGCCTCCTCAGATCAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCGCTTCACGAATTTGCGTGTCAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCBX5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAAACTTGGATTGCCCTGAGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGTCCTCTCTCAAAGCCCCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eU6 Stem loop\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u0026acute;-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAAAAATAT \u0026minus;\u0026thinsp;3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ehsa-mir-383 Stem loop\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5\u0026acute;-GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTCTTT-3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe analysis of qPCR results and visualizing the graphs were performed using GraphPad Prism 8. Differences in the mentioned gene expression level between samples were determined using the Wilcoxon matched-pairs signed rank test, paired and unpaired t-test, and Mann-Whitney test. A significant P value was measured to less than 0.05.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. In-silico analysis\u003c/h2\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.1. PICSAR(LINC00162) is overexpressed in TCGA-STAD dataset\u003c/h2\u003e\n \u003cp\u003eThe qPCR findings were confirmed by analyzing the TCGA-STAD database, which allowed for thorough validation of the experiment. In comparison to normal samples, GC samples show a considerably higher expression of LINC00162 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), according to the results given by the TCGA-STAD analysis and the Gepia online tools (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ea, b). Moreover, as seen in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003ec, the LINC00162 gene\u0026apos;s expression may serve as a diagnostic target for distinguishing GC from healthy samples.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2. Dysregulation of LINC00162 (PICSAR) is significant in all cancers.\u003c/h2\u003e\n \u003cp\u003eThe TCGA database revealed that LINC00162, or PICSAR (P38 inhibited cutaneous squamous cell carcinoma associated lincRNA), is dysregulated in several cancer types. A comprehensive pan-cancer study included gastrectomy. Data from over 11,000 patients with over 30 cancer types provided a complete understanding of LINC00162 dysregulation. This thorough analysis found regular LINC00162 expression patterns and showed good statistical abilities to identify healthy and malignant tissues. The Ualcan database\u0026apos;s pan-cancer study found dysregulation of LINC00162 in all cancers, including gastric cancer (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The TCGA database revealed that LINC00162, or PICSAR (P38 inhibited cutaneous squamous cell carcinoma associated lincRNA), is dysregulated in several cancer types. A comprehensive pan-cancer study included gastrectomy. Data from over 11,000 patients with over 30 cancer types provided a complete understanding of LINC00162 dysregulation. This thorough analysis found regular LINC00162 expression patterns and showed good statistical abilities to identify healthy and malignant tissues. The Ualcan database\u0026apos;s pan-cancer study found dysregulation of LINC00162 in all cancers, including gastric cancer.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.3. Gastric cancer development is induced by overexpression of LINC00162 (PICSAR).\u003c/h2\u003e\n \u003cp\u003eOverexpression of LINC00162 (PICSAR) is a hallmark of all gastric cancer types, stages, and grades, according to a thorough examination of TCGA data and pathology samples. Its possible involvement in the initiation and advancement of gastric cancer is supported by the persistent pattern of increased LINC00162 expression and its correlation with poor clinical outcomes. These results raise the possibility that LINC00162 is a therapeutic target and a useful biomarker for the diagnosis and prognosis of gastric cancer. We need further studies on LINC00162 to figure out how it causes cancer and what it can do in the clinic. As shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the expression level of LINC00162 was significantly increased across all grades, stages, and kinds of gastric cancer.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.4. Overexpression of LINC00162 (PICSAR) affects the survival rate of gastric cancer samples\u003c/h2\u003e\n \u003cp\u003eOverexpression of LINC00162 (PICSAR) is a notable characteristic in gastric cancer and is linked to worse survival outcomes, according to the combined analysis of the TCGA and KM plot databases. Potentially useful as a prognostic biomarker, increased LINC00162 levels are associated with worse overall and disease-free survival rates. These results demonstrate that LINC00162 is an important factor in the development of gastric cancer and that it may have therapeutic uses. To further understand LINC00162\u0026apos;s potential as a therapeutic target and its molecular functions in oncogenesis, more study is required. The LINC00162 survival rate in the TCGA-STAD and KM plot datasets is shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.5. lncRNA-microRNA interaction\u003c/h2\u003e\n \u003cp\u003eAn investigation of the LncRNA-miRNA network utilizing the LncACT database showed a key interaction between PICSAR and hsa-miR-383 after the finding of the major dysregulated lncRNA LINC00162 (PICSAR) in gastric cancer. Because of this relationship, it is possible that PICSAR modulates the activity of hsa-miR-383, an endogenous RNA that competes with it, and hence affects the course of gastric cancer. The negative association between PICSAR and hsa-miR-383 expression levels highlights the possibility that the PICSAR-hsa-miR-383 interaction contributes to the development of gastric cancer. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e provides a detailed display of the interaction between PICSAR and hsa-miR-383. In gastric cancer, hsa-miR-383 is significantly downregulated, according to the TCGA-STAD database thorough study. This downregulation is seen in stomach cancer of different grades, stages, and histological subtypes, indicating a common and extensive pattern. The possible involvement of hsa-miR-383 in the advancement of gastric cancer is highlighted by the link between low levels of this gene and advanced tumor characteristics as well as poor clinical outcomes. These results point to hsa-miR-383 as a possible diagnostic and prognostic biomarker and therapeutic intervention target in gastric cancer, and they provide light\u003c/p\u003e\n \u003cp\u003eon the molecular underpinnings of this disease. We need further studies to determine what role the downregulation of hsa-miR-383 plays in gastric cancer survival. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e reveals that hsa-miR- 383 expression is dramatically downregulated in gastric cancer (TCGA-STAD), and Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e shows that this downregulation is consistent across all gastric cancer grades, stages, and types.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetailed display of the interaction between PICSAR and hsa-miR-383.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLncRNA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emicroRNA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003especies\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eexperimental\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePubmed ID\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ereference\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLINC00162(PICSAR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHomo sapiens (human)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eluciferase reporter assays; qRT-PCR; Northern blot assay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26539909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.6. microRNA-mRNA interaction\u003c/h2\u003e\n \u003cp\u003eThe miRmap database was used to investigate the gastric cancer microRNA-mRNA interaction network, and one of the targets of hsa-miR-383 was CBX5 mRNA. There is a significant negative relationship between the levels of hsa-miR-383 and CBX5 mRNA, which means that lowering hsa-miR-383 might cause CBX5 mRNA to rise, which could lead to gastric cancer. The results show that hsa-miR-383 and CBX5 mRNA might be used as diagnostic biomarkers and therapeutic targets for gastric cancer. Discovering its therapeutic uses in the treatment of stomach cancer and understanding the functional processes underneath this regulatory axis requires more investigation.\u003c/p\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e shows a comprehensive look into how hsa-miR-383 and CBX5 interact. In gastric cancer (TCGA-STAD), CBX5 expression is significantly elevated (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e), and this overexpression is constant across all gastric cancer grades, stages, and types (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDetailed display of the interaction between hsa-miR-383 and CBX5.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emiRNA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProbability exact\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eConservation PhyloP\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emiRmap score\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ehsa-miR-383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.66967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31E-05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.5693\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.7. Functional enrichment analysis\u003c/h2\u003e\n \u003cp\u003eMultiple pathways substantially related to CBX5 in gastric cancer were found by the functional enrichment analysis utilizing the Reactome database. Megakaryocyte formation, hemostasis, post-translational modifications, transcription control, and CBX5 are all essential biological functions. Based on these results, CBX5 may affect a wide range of cellular processes and regulatory systems, suggesting a complex involvement in the development of gastric cancer. To further understand the therapeutic potential of targeting CBX5 and its related pathways in the treatment of gastric cancer, further study is necessary. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows the biological pathways related to CBX5 mRNA.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe related biological pathways of CBX5 mRNA.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePathways\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFactors Involved in Megakaryocyte Development and Platelet Production R-HSA-983231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGene Expression (Transcription) R-HSA-74160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemostasis R-HSA-109582\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePost-translational Protein Modification R-HSA-597592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRNA Polymerase II Transcription R-HSA-73857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSUMO E3 Ligases SUMOylate Target Proteins R-HSA-3108232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSUMOylation Of Chromatin Organization Proteins R-HSA-4551638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTranscriptional Regulation by E2F6 R-HSA-8953750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeneric Transcription Pathway R-HSA-212436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMetabolism Of Proteins R-HSA-392499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCBX5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Experimental validation\u003c/h2\u003e\n \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1. PICSAR(LINC00162) is significantly overexpressed in gastric cancer tissue samples.\u003c/h2\u003e\n \u003cp\u003eThe results of the quantitative PCR (qPCR) study showed that PICSAR (LINC00162) is 4.5 times more abundant in gastric cancer samples than in normal tissues that were medically matched (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Additional testing using ROC curve analysis confirmed PICSAR\u0026apos;s diagnostic promise; the results showed a high area under the curve (AUC) of 0.9236 (95% CI: 0.8518\u0026ndash;0.9954), proving the system\u0026apos;s excellent diagnostic accuracy. With a sensitivity of 85% and a specificity of 90%, PICSAR proved to be an effective biomarker for differentiating gastric cancer tissues from normal tissues. This was established using the Youden index, which suggested the ideal cut-off value. In gastric cancer, PICSAR is significantly upregulated, and these results suggest that it may be useful for early detection and disease monitoring. (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2. hsa-miR-383 is significantly downregulated in gastric cancer tissue samples.\u003c/h2\u003e\n \u003cp\u003eGastric cancer tissues showed a substantially decreased expression of hsa-miR-383 compared to normal tissues that were matched, with an average expression level four times lower in cancer samples (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), according to quantitative PCR (qPCR) research. The diagnostic capability of hsa-miR-383 was shown by the Receiver Operating Characteristic (ROC) curve analysis, which produced an area under the curve (AUC) of 0.8194 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), suggesting a robust diagnostic accuracy. By using the Youden index to calculate the ideal cut-off value, hsa-miR-383 demonstrated its potential as a biomarker for differentiating gastric cancer tissues from normal tissues with a sensitivity of 95% and a specificity of 85%. In gastric cancer, hsa-miR-383 is significantly downregulated, and these results suggest that it may be useful for early detection and disease monitoring. (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3. CBX5 is significantly upregulated in gastric cancer tissue samples.\u003c/h2\u003e\n \u003cp\u003eA mean expression level 2.04-fold higher in cancer samples (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) was found by quantitative PCR (qPCR) research, which showed that CBX5 is considerably elevated in gastric cancer tissues compared to matched normal tissues. The diagnostic potential of CBX5 was shown by the Receiver Operating Characteristic (ROC) curve study, which produced an area under the curve (AUC) of 0.9375 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), thus suggesting a high level of diagnostic accuracy. Highlighting CBX5\u0026apos;s potential as a biomarker for differentiating gastric cancer tissues from normal tissues, the Youden index established the ideal cut-off value, which produced a sensitivity of 90% and a specificity of 85%. These results demonstrate that CBX5 is highly upregulated in gastric cancer and suggest that it may be useful for both early detection and disease tracking. (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.4. Pathology characteristics of LINC00162, hsa-miR-383, and CBX5\u003c/h2\u003e\n \u003cp\u003eThe study examined the correlation between three molecular markers (LINC00162, hsa-miR-383, and CBX5) and a range of clinicopathological variables found in the samples. These variables included age, gender, tumor size, grade, serosal invasion, lymphatic invasion, vascular invasion, perineural invasion, and stage. Interestingly, neither LINC00162 nor hsa-miR-383 expression was significantly associated with any of these clinicopathological variables, as demonstrated by the lack of statistical significance (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). That these two markers\u0026apos; expression is uncorrelated with the tumors\u0026apos; ages, genders, sizes, grades, or stages is suggestive. The expression of CBX5 is linked to two clinicopathological characteristics, however. First, patients older than 60 years had substantially greater CBX5 expression than those younger than 60 years (p\u0026thinsp;=\u0026thinsp;0.0064). The second finding is that tumors bigger than 5 cm had much greater CBX5 expression than smaller ones (p\u0026thinsp;=\u0026thinsp;0.0183). Results show that older patients and higher tumor sizes are associated with greater CBX5 expression, which may be a marker of aggressive tumors. Based on the data, it seems that CBX5 expression has the greatest promise as a biomarker for prognosis or prediction among the three molecular markers. This is because it is associated with specific clinicopathological findings. The biological and pathological significance of CBX5 in the malignancies included in this dataset remains unclear and requires more research. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ctbody\u003e\u003c/tbody\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe association between the expression of LINC00162, hsa-miR-383, and CBX5 and various clinicopathological characteristics of the gastric cancer samples\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProperties\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLINC00162 (PICSAR)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehsa-miR-383\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCBX5\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 105px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.3123 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1836 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.0064 (**)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026lt;60 (n=11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026gt;60 (n=13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1282 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.2608 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4248 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eMale (n=20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eFemale (n=4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor size\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.7640 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.9844 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.0183 (*)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026lt; 5 (n=11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u0026gt;5 (n=13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGrade\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.4993 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6419 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1599 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eI, II (n=16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eIII, IV (n=8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSerosal invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.7656 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.5386 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.9831 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eYes (n=13)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eNo (n=11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLymphatic invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1957 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.3318 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.5969 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eYes (n=18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eNo (n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVascular invasion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1957 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.3318 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.5969 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eYES (n=18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eNO (n=6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerineural invasion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 105px;\"\u003e\n \u003cp\u003e0.4141 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6386 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6332 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eYes (n=17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003eNo (n=8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 147px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4976 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.1781 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.6954 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eStomach cancer is still a big concern, even though cancer detection and therapy have come a long way. Scientific studies have demonstrated that the mortality rate from stomach cancer can be drastically decreased with early detection. This being the case, early identification of stomach cancer still necessitates research into the pathogenic molecular pathways producing the disease. [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The expression of LINC00162 in gastric cancer transcriptional regulation is affected by a wide variety of RNA interactions. LINC00162 (PICSAR) may control the advancement of gastric cancer via interacting with microRNAs and messenger RNAs. In gastric cancer, our work primarily focuses on PICSAR expression and how it is correlated with hsa-miR-383 and CBX5 mRNAs. The results of this study provide strong evidence that the dysregulation of PICSAR (LINC00162), hsa-miR-383, and CBX5 is involved in the development and progression of gastric cancer (GC). Specifically, compared to normal tissue samples, gastric cancer tissue samples showed a significant upregulation of PICSAR, which was found to be negatively correlated with hsa-miR-383 expression and positively correlated with CBX5 RNA expression. In light of recent studies, this section will synthesize the main results and investigate their relevance (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLong non-coding RNAs (lncRNAs) regulate gene expression at numerous levels, including chromatin modification, transcription, and post-transcriptional processing; they play a crucial role in the advancement of gastric cancer and other malignancies. The way lncRNAs sponge on microRNAs (miRNAs) is a crucial way they impact the advancement of cancer. Local non-coding RNAs (lncRNAs) compete with microRNAs (miRNAs) for interaction sites on messenger RNAs (mRNAs). Through this regulatory mechanism, lncRNAs in gastric cancer can alter the expression of genes that are involved in significant processes such as cell migration, apoptosis, and proliferation. To illustrate the point, some lncRNAs can bind to miRNAs that limit tumor growth; this leads to an overexpression of oncogenes that enhance tumor development, metastasis, and chemotherapy resistance. On the flip side, some lncRNAs can prevent cancer from progressing by binding to oncogenic miRNAs and increasing the expression of tumor suppressor genes. Due to their association with poor prognosis, lncRNA dysregulation in gastric cancer raises hopes that these molecules may one day serve as biomarkers for early detection and therapeutic intervention targets. Understanding the roles and mechanisms of lncRNA is crucial for the development of more effective treatments for gastric cancer, and this complicated network of interactions between lncRNA, miRNA, and mRNA highlights this point[\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our study demonstrated a significant overexpression of PICSAR (LINC00162) in gastric cancer tissues compared to normal tissues, with a 4.5-fold increase observed via quantitative PCR (qPCR) analysis. This overexpression was also corroborated by in-silico analysis using the TCGA-STAD and Gepia online tools, which revealed a marked upregulation of LINC00162 in GC samples (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The Receiver Operating Characteristic (ROC) curve analysis further validated the diagnostic potential of PICSAR, with an area under the curve (AUC) of 0.9236, indicating high diagnostic accuracy. These findings suggest that PICSAR could serve as a robust biomarker for distinguishing GC from normal tissue and could be instrumental in the early detection and monitoring of the disease. Multiple lncRNAs implicated in stomach cancer growth and metastasis have been isolated by researchers. Case in point: research by Xia et al. (2016) has established lncRNA MALAT1 as a major metastatic biomarker[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This study shows that gastric cancer tissues have much higher MALAT1 expression, which is associated with a worse prognosis and increased metastatic potential. A possible diagnostic marker and therapeutic target for early detection of metastatic gastric cancer, MALAT1 is involved in increasing angiogenesis and cell invasion. In addition to MALAT1, the function of lncRNA H19 in cancer progression and metastasis has been the subject\u003c/p\u003e \u003cp\u003eof much research. Guo et al[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. (2014) H19 is overexpressed in gastric cancer, according to this research. In this kind of cancer, it acts as a molecular sponge, soaking up microRNAs and influencing the expression of genes that drive tumor development and metastasis. The activation of carcinogenic pathways is a consequence of this sponging action, which adds to the aggressiveness of the illness. The role of lncRNA MEG3 in suppressing tumor growth in gastric cancer has been acknowledged, on the other hand. By activating the p53 signaling pathway, MEG3 suppresses the growth and spread of cancer cells. According to research, gastric cancer tissues often have MEG3 downregulation, which results in reduced p53 activity and unregulated cell proliferation. These factors are associated with poor clinical outcomes[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Taken together, our results highlight the multifaceted functions of lncRNAs in gastric cancer; whilst MALAT1 and H19 promote cancer growth, MEG3 suppresses tumors; these findings provide new avenues for disease management and possible therapeutic targets. Our findings are consistent with the findings of the studies that emphasize the significant part that a variety of long noncoding RNAs play in the advancement of gastric cancer. Also, the results of our study show the potential of hsa-miR-383 as a diagnostic biomarker is highlighted by its substantial downregulation in GC tissues, which is four times lower than in normal tissues. The diagnostic accuracy was highlighted by the ROC curve analysis, which produced an AUC of 0.8194 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). PICSAR may modulate the activity of hsa-miR-383, which in turn affects the advancement of GC, according to the negative association between the two. The relationship between long non-coding RNAs and microRNAs provides new insight into the pathophysiology of GC and suggests potential targets for personalized treatments. Last but not least The CBX5 gene was shown to be significantly upregulated in GC tissues compared to normal tissues, with an average expression level 2.04 times higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). With an area under the curve (AUC) of 0.9375, it was shown to be very specific and sensitive in differentiating GC from normal tissues, confirming its diagnostic potential in the ROC study. Megakaryocyte formation, hemostasis, and transcriptional control are only a few of the crucial biological processes that CBX5 is engaged in, according to functional enrichment analysis. According to these results, CBX5 is a diagnostic biomarker and may have an important function in the pathophysiology of GC, which makes it a possible therapeutic target.\u003c/p\u003e \u003cp\u003eOne important way lncRNAs contribute to cancer progression is by acting as a sponge for miRNAs. Messenger RNAs (mRNAs) have interaction sites that local non-coding RNAs (lncRNAs) and microRNAs (miRNAs) vie for. In gastric cancer, lncRNAs regulate gene expression by this approach, changing genes involved in important processes such as cell migration, apoptosis, and proliferation. A complex regulatory network controlling GC formation is suggested by the overexpression of PICSAR, together with the downregulation of hsa-miR-383 and the increase of CBX5 mRNA. The complex connection between PICSAR and hsa-miR-383, as well as the possible control of CBX5 by hsa-miR-383, suggests a potential therapeutic target. In addition to diagnostic applications, these biomarkers hold great promise for the creation of individualized treatment plans that target specific expression levels. According to the findings of Dong et al. (2019), patients with stomach cancer who exhibited high levels of the long noncoding RNA HOTAIR had a poor prognosis. Through the process of sponging miR-217, HOTAIR performs the role of a ceRNA and upregulates the oncogene GCP5, which results in gastric cancer progression[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Li et al. (2017) discovered that lncRNA MALAT1 promotes the advancement of gastric cancer via interacting with miR-1297. MALAT1 enhances cancer cell invasion and metastasis by sponge-acting on miR-1297, a gene that typically controls the production of the oncogene HMGB2[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. According to the findings of Liu et al. (2016), the long noncoding RNA GAS5 sponging miR-23 has an influence on the growth of gastric cancer via modifying MT2A mRNA and contributes to the progression of cancer[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. According to the findings of the research carried out by Gong et al. (2018), the long noncoding RNA UCA1 is responsible for the advancement of gastric cancer by sponging miR-203, which targets oncogenes such as ZEB2. In addition to contributing to increased cancer cell proliferation and metastasis, the capacity of UCA1 to sequester miR-203 is a significant factor[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. PVT1 is discovered to operate as an oncogene via sponging miR-152, according to the findings of research that was conducted by Li et al. (2017). The study investigated the role of lncRNA PVT1 in gastric cancer. This connection results in the overexpression of its target genes, such as CD151 and FGF2, which are responsible for promoting cell proliferation and inhibiting apoptosis[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e provides a comprehensive overview of the research that was discussed in detail.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA brief overview of the Lnc-microRNA-mRNA axis in gastric cancer, including our findings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLncRNA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSponged microRNA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emRNA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStudy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFindings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOur Findings\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHOTAIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa-miR-217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDong et al. (2019)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHigh levels of HOTAIR promote gastric cancer progression via miR-217 sponging.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eBy targeting pathways involved in hemostasis, elevated levels of LINC00162 (PICSAR) encourage the growth of gastric cancer by miR-383 sponging, which upregulates CBX6.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMALAT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa-miR-1297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHMGB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLi et al. (2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMALAT1 promotes invasion through miR-1297 sponging.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAS5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa-miR-23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMT2A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLiu et al. (2016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGAS5 has an oncogenic effect by sponging miR-23.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUCA1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa-miR-203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZEB2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGong et al. (2018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUCA1 promotes progression through miR-203 sponging.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehsa-miR-152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD151 and FGF2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLi et al. (2017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePVT1 promotes proliferation via miR-152 sponging.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eImportant biomarkers that are drastically dysregulated in stomach cancer have been found in this investigation. New possibilities for diagnosis and therapy are opened up by the downregulation of hsa-miR-383 and the overexpression of PICSAR and CBX5. These findings provide light on the molecular basis of GC. We can learn more about GC and create better ways to fight it if we dig deeper into these biomarkers, but in the future, researchers need to validate these biomarkers in bigger, separate cohorts and figure out the molecular mechanisms behind these interactions. Further investigation into the therapeutic possibilities of targeting PICSAR, hsa-miR-383, and CBX5 in GC may lead to the discovery of novel treatment approaches. In order to put these results into reality, it is crucial to conduct clinical studies that evaluate the effectiveness of targeted medicines.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eOur research reveals a new gastric cancer predictive biomarker: the LINC00162/hsa-mir-383/CBX5 axis. There is great promise for early diagnosis and treatment along this axis, which also coincides with the hemostasis process. Further investigation into the molecular processes underlying the activity of lncRNAs is warranted in light of our results, which demonstrate their crucial involvement in the advancement of gastric cancer. Improved patient outcomes in stomach cancer will be possible as a result of the new insights offered by this research, which open the door to better diagnostic and therapeutic methods.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful for the support of the Immunology Research Center, Tabriz University of Medical Science (grant number: 74992).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ethical committee of the Immunology Research Center, Tabriz University of Medical Sciences approved the study. Written informed consent was obtained from all patients\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out according to relevant guidelines and regulations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are thankful for the support of the Immunology Research Center, Tabriz University of Medical Science (grant number: 74992).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: AmirAli Mokhtarzadeh, Saeid Ghorbian\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData curation: Seyed Ali Hoseini\u003c/p\u003e\n\u003cp\u003eFormal analysis: \u0026nbsp;AmirAli Mokhtarzadeh, Saeid Ghorbian\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInvestigation: Seyed Ali Hoseini\u003c/p\u003e\n\u003cp\u003eMethodology: Seyed Ali Hoseini, AmirAli Mokhtarzadeh, Saeid Ghorbian, Behzad Baradaran, Changiz Ahmadizadeh\u003c/p\u003e\n\u003cp\u003eProject administration: AmirAli Mokhtarzadeh, Saeid Ghorbian\u003c/p\u003e\n\u003cp\u003eSoftware: Seyed Ali Hoseini\u003c/p\u003e\n\u003cp\u003eSupervision: AmirAli Mokhtarzadeh, Saeid Ghorbian\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eValidation: AmirAli Mokhtarzadeh, Saeid Ghorbian, Behzad Baradaran, Changiz Ahmadizadeh\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVisualization: Seyed Ali Hoseini\u003c/p\u003e\n\u003cp\u003eWriting–original draft: Seyed Ali Hoseini\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed in the current research are provided within the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSitarz R et al (2018) Gastric cancer: epidemiology, prevention, classification, and treatment. 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Dig Dis Sci 62(11):3021\u0026ndash;3028\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gastric cancer, Long non-coding RNA (lncRNA), LINC00162, hsa-mir-383, CBX5","lastPublishedDoi":"10.21203/rs.3.rs-6423474/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6423474/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Gastric cancer is a significant global cause of cancer-related mortality, which requires the development of new biomarkers to enhance diagnosis and prognosis. Although long non-coding RNAs (lncRNAs) have become critical regulators in cancer biology, their significance in gastric cancer remains incompletely understood.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e The purpose of this study is to assess the potential of the LINC00162/hsa-mir-383/CBX5 axis as a prognostic biomarker associated with hemostasis by examining its expression and functional significance in gastric cancer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e To identify differentially expressed lncRNAs, we conducted comprehensive in-silico analyses using TCGA-STAD datasets. Subsequently, we conducted experimental validation through qPCR in gastric cancer tissue samples. The LncACT and miRmap databases were employed to investigate the interactions between LINC00162, hsa-mir-383, and CBX5. In order to clarify the molecular pathways that were implicated, functional enrichment analysis was implemented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In gastric cancer tissues, LINC00162 (PICSAR) was substantially overexpressed in comparison to normal samples, which was associated with adverse clinical outcomes. According to the lncRNA-microRNA interaction analysis, LINC00162 functions as a molecular reservoir for hsa-mir-383, a microRNA that is downregulated in gastric cancer. An upregulation of CBX5, a target gene that is implicated in the progression of cancer, is associated with this downregulation. Functional enrichment analysis indicates that this axis is involved in critical oncogenic pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The LINC00162/hsa-mir-383/CBX5 axis is a novel prognostic biomarker in gastric cancer that has substantial implications for the hemostasis process. These discoveries emphasize the critical role of lncRNAs in the pathogenesis of gastric cancer, opening up new opportunities for the development of diagnostic and therapeutic strategies. Additional research is necessary to investigate the clinical implications of targeting this axis in the treatment of gastric cancer.\u003c/p\u003e","manuscriptTitle":"Identification of the LINC00162/hsa-mir-383/CBX5 Axis as a novel prognostic biomarker associated with hemostasis in gastric cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-29 11:42:48","doi":"10.21203/rs.3.rs-6423474/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"791783a2-2748-4138-8b18-f78231a4ca93","owner":[],"postedDate":"April 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-05T09:38:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-29 11:42:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6423474","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6423474","identity":"rs-6423474","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}