Differentially expressed long noncoding RNAs and regulatory mechanism of LINC02407 in human gastric adenocarcinoma

Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers

Colorectal cancer (CRC) and gastric cancer (GC) are major contributors to cancer-related mortality worldwide. Despite advancements in understanding molecular mechanisms and improved drug treatments, the overall survival rate for patients remains unsatisfactory. Metastasis and drug resistance are major challenges contributing to the high mortality rate in both CRC and GC. Recent research has shed light on the role of long noncoding RNAs (lncRNAs) in the development and progression of these cancers. LncRNAs regulate gene expression through various mechanisms, including epigenetic modifications and interactions with microRNAs (miRNAs) and proteins. They can serve as miRNA precursors or pseudogenes, modulating gene expression at transcriptional and post-transcriptional levels. Additionally, circulating lncRNAs have emerged as non-invasive biomarkers for the diagnosis, prognosis, and prediction of drug therapy response in CRC and GC. This review explores the intricate relationship between lncRNAs and CRC/GC, encompassing their roles in cancer development, progression, and chemoresistance. Furthermore, it discusses the potential of lncRNAs as therapeutic targets in these malignancies. The interplay between lncRNAs, miRNAs, and tumor microenvironment is also highlighted, emphasizing their impact on the complexity of cancer biology. Understanding the regulatory landscape and molecular mechanisms governed by lncRNAs in CRC and GC is crucial for the development of effective diagnostic and prognostic biomarkers, as well as novel therapeutic strategies. This review provides a comprehensive overview of the current knowledge and paves the way for further exploration of lncRNAs as key players in the management of CRC and GC.

HOXC Cluster Antisense RNA 3, a Novel Long Non-Coding RNA as an Oncological Biomarker and Therapeutic Target in Human Malignancies

HOXC cluster antisense RNA 3 (HOXC-AS3) is a novel long noncoding RNA (lncRNA) that exhibits aberrant expression patterns in various cancer types. Its expression is closely related to clinicopathological features, demonstrating significant clinical relevance across multiple tumors. And HOXC-AS3 plays multifaceted roles in tumor progression, impacting cell proliferation, apoptosis, migration, invasion, epithelial-mesenchymal transition (EMT), autophagy, senescence, tumor growth, and metastasis. In this review, we summarized and comprehensively analyzed the expression and clinical significance of HOXC-AS3 as a diagnostic and prognostic biomarker for malignancies. Additionally, we presented an in-depth update on HOXC-AS3's functions and regulatory mechanisms in cancer pathogenesis. This narrative review underscores the importance of HOXC-AS3 as a promising lncRNA candidate in cancer research and its potential as a predictive biomarker and therapeutic target in clinical applications.

Identification of potential LncRNAs as papillary thyroid carcinoma biomarkers based on integrated bioinformatics analysis using TCGA and RNA sequencing data

The roles and mechanisms of long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remain elusive. We obtained RNA sequencing (RNA-seq) data of surgical PTC specimens from patients with thyroid cancer (THCA; n = 20) and identified differentially expressed genes (DEGs) between cancer and cancer-adjacent tissue samples. We identified 2309 DEGs (1372 significantly upregulated and 937 significantly downregulated). We performed Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment, and protein-protein interaction network analyses and screened for hub lncRNAs. Using the same methods, we analyzed the RNA-seq data from THCA dataset in The Cancer Genome Atlas (TCGA) database to identify differentially expressed lncRNAs. We identified 15 key differentially expressed lncRNAs and pathways that were closely related to PTC. Subsequently, by intersecting the differentially expressed lncRNAs with hub lncRNAs, we identified LINC02407 as the key lncRNA. Assessment of the associated clinical characteristics and prognostic correlations revealed a close correlation between LINC02407 expression and N stage of patients. Furthermore, receiver operating characteristic curve analysis showed that LINC02407 could better distinguish between cancerous and cancer-adjacent tissues in THCA patients. In conclusion, our findings suggest that LINC02407 is a potential biomarker for PTC diagnosis and the prediction of lymph node metastasis.

The expression of long non-coding RNA LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2 in gastric cancer and their impacts on EMT

BACKGROUND

Epithelial cancers acquire the epithelial to mesenchymal transition (EMT), which leads tumor cells to invade and metastasize to adjacent and distant tissues. The mechanisms involved in EMT phenotype are controlled by numerous markers as well as signalling pathways. Recently, long non-coding RNAs (lncRNAs) were introduced that play the regulatory role in EMT via crosstalk with EMT-related transcription factors and signalling pathways. The present study aimed to investigate the expression of four lncRNAs in human GC and elucidate their probable role in EMT procedure and the pathogenesis of gastric cancer (GC).

METHODS

The expression profile of lncRNAs (LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2) and mRNAs (TWIST1, MMP13, MAML1, CD44s, and SALL4) between eighty-three GC and adjacent non-cancerous tissues were assessed by quantitative real-time PCR.

RESULTS

The significant downregulation of LINC00365 (66.3%) and RP11-354K4.2 (62.7%) were observed in GC samples; while the upregulation of LINC01389, RP11-138J23.1, TWIST1, MMP13, MAML1, CD44s, and SALL4 were found in 67.5%, 45.8%, 56.6%, 44.6%, 59%, 55.4%, and 62.7% tumors samples at the mRNA level, respectively. Dysregulation of these lncRNAs and EMT-related markers was significantly related to each other in a variety of clinicopathological features of patients (P < 0.05), indicating positive correlations between LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2 with EMT status in GC.

CONCLUSION

These EMT-regulating lncRNAs may play a key role in transforming gastric epithelial to mesenchymal phenotype and can be novel therapeutic targets for GC. Our results highlight the importance of discovering new lncRNAs involved in gastric carcinogenesis. Detailed molecular mechanisms of these noncoding-coding markers in GC are urgently required.

ADGRD1 as a Potential Prognostic and Immunological Biomarker in Non-Small-Cell Lung Cancer

ADGRD1 (GPR133), an adhesion G protein-coupled receptor (GPCR), has been linked to cancer. However, the prognostic value and regulatory function within non-small-cell lung cancer (NSCLC) is still unclear. This work adopted various bioinformatics methods, including publicly available databases as well as real-time PCR (RT-PCR), for detecting ADGRD1 expression level and investigating the correlation between ADGRD1 expression level and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), immune infiltrating cells, immune-related genes, and targeted regulation mechanisms in NSCLC. According to the results, ADGRD1 expression decreased within NSCLC, which might be the factor predicting prognosis of NSCLC. Meanwhile, ADGRD1 showed significant correlation with TMB and MSI, respectively, as well as immune cell infiltrating levels in lung adenocarcinoma (LUAD), which were primarily linked to macrophage M1, mast cell resting, T cell CD4 memory activated, and T cell CD4 memory resting and were associated with mast cell activated and mast cell resting in lung squamous cell carcinoma (LUSC). The most promising upstream regulation pathways of ADGRD1 were likely miR-142-5p, miR-93-5p, and miR-17-5p, which were overexpressed and associated with poor prognosis in NSCLC. ADGRD1 and immune-related genes correlated with ADGRD1 were shown to be enriched in "positive regulation of leukocyte activation," "external side of plasma membrane," "receptor ligand activity," and "cytokine-cytokine receptor interaction" pathways. ADGRD1 expression and regulation may be critical in determining NSCLC prognosis.

Mesangial Cell–Derived Exosomal miR-4455 Induces Podocyte Injury in IgA Nephropathy by Targeting ULK2

Growing evidence suggests that mesangial cells (MCs) play a crucial role in the pathogenesis of IgA nephropathy (IgAN) by secreting aIgA1. However, the mechanism by which MCs regulate podocyte injury remains unknown. This study demonstrated that MC-derived exosomes treated with aIgA1 induced podocyte injury in IgA nephropathy. miR-4455, which was significantly upregulated in aIgA1 treatment MC-derived exosomes, can be transferred from MCs to podocytes via exosomes. MC-derived exosomal miR-4455 induced podocyte injury. Mechanistically, exosomal miR-4455 directly targeted ULK2 to regulate LC3II/I and P62 levels, which mediates autophagy homeostasis. This study revealed that MC-derived exosomal miR-4455 is a key factor affecting podocyte injury and provides a series of potential therapeutic targets for treating IgA nephropathy.

An Immunity-Associated lncRNA Signature for Predicting Prognosis in Gastric Adenocarcinoma

Background

Gastric adenocarcinoma (GAD) is one of the most common tumors in the world and the prognosis is still very poor.

Objective

We sought to identify reliable prognostic biomarkers for the progression of GAD and the sensitivity to drug therapy.

Method

The RNA sequencing data of GAD was downloaded from the Cancer Genome Atlas (TCGA) database and used for analysis. Differentially expressed, immune-related lncRNA (DEIRlncRNA) was characterized by differential analysis and correlation analysis. Univariate Cox regression analysis was used to identify DEIRlncRNA associated with prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis allowed us to determine a signature composed of eight IRlncRNAs. Based on this signature, we further performed gene set enrichment analysis (GSEA) and somatic mutation analysis to evaluate the ability of this signature to predict prognosis.

Results

In total, 72 immune-related lncRNAs (DEIRlncRNAs) with prognostic value were identified. These lncRNAs were used to construct a model containing eight immune-related lncRNAs (8-IRlncRNAs). Based on this risk model, we divided GAD patients into high-risk and low-risk groups. The analysis showed that the prognosis of the two groups was different and that the high-risk group had worse overall survival (OS). Immune cell infiltration analysis showed that the proportion of memory B cells increased in the high-risk group while the proportion of macrophages M1, T cells, CD4 memory-activated cells, and T cell follicular helpers decreased. GSEA results showed that 8-IRlncRNA was significantly enriched in tumorigenesis pathways such as myc. The results of somatic mutation analysis showed that the CDH1 gene was significantly mutated in the high-risk group.

Conclusion

A prognostic signature of 8-IRlncRNAs in GAD was established and this signature was able to predict the prognosis of GAD patients.

Inhibition of ITGB1-DT expression delays the growth and migration of stomach adenocarcinoma and improves the prognosis of cancer patients using the bioinformatics and cell model analysis

BACKGROUND

The long non-coding RNA, integrin subunit beta 1 (ITGB1) divergent transcript (ITGB1-DT), is known to be involved in cancer progression and associated with the poor prognosis of cancer patients. At present, the role of ITGB1-DT in stomach adenocarcinoma (STAD) has not been reported.

METHODS

The expression level of ITGB1-DT was detected in normal gastric and STAD tissues from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. A receiver operating characteristic (ROC) analysis was used to evaluate the role of ITGB1-DT in diagnosing STAD. The relationship between ITGB1-DT overexpression and clinicopathological features, prognosis, and immune-infiltrated cells in STAD were explored using correlation, survival, and Cox regression analyses. A cell model of ITGB1-DT interference was constructed to explore the roles of ITGB1-DT on STAD cell proliferation and migration, and the signaling mechanism was investigated using Gene Set Enrichment Analysis (GSEA).

RESULTS

ITGB1-DT was expressed up-regulated in STAD tissues. ITGB1-DT overexpression was associated with the T stage, therapeutic effect, overall survival, progression-free interval status, and poor prognosis in STAD patients. ITGB1-DT overexpression was valuable in diagnosing STAD and a negative factor affecting the prognosis of STAD patients. Interference with ITGB1-DT expression inhibited STAD cell proliferation, invasion, and migration. GSEA results showed that ITGB1-DT may be involved in STAD progression through the insulin, p53, mechanistic target of rapamycin kinase (MTOR), and other signaling pathways. Overexpression of ITGB1-DT was significantly correlated with the levels of STAD B cells, T cells, T helper cells, CD8 T cells, cytotoxic cells, and other immune cells.

CONCLUSIONS

ITGB1-DT was overexpressed and associated with poor prognosis in STAD. Interference with ITGB1-DT expression may delay the progression of STAD to improve the prognosis of STAD patients.

KLRK1 as a prognostic biomarker for lung adenocarcinoma cancer

Lung cancer is one of the most common malignancy worldwide and causes estimated 1.6 million deaths each year. Cancer immunosurveillance has been found to play an important role in lung cancer and may be related with its prognosis. KLRK1, encoding NKG2D, is a homodimeric lectin-like receptor. However, there has not been one research of KLRK1 as a biomarker in lung cancer. Data including patients` clinical characteristics and RNAseq information of KLRK1 from TCGA were downloaded. A total of 1019 patients with lung cancer were included in this study, among which 407 patients were female and 611 patients were male. Evaluations of mRNA expression, diagnostic value by ROC (receiver operating characteristic) curves and prognostic value by survival curve, Cox model and subgroup analysis were performed. The level of KLRK1 expression in lung adenocarcinoma cancer tissues and normal lung tissues was detected by qRT-PCR. The CCK-8 assay investigated the proliferation rate and the wound healing assay assessed the migratory ability in vitro. The expression of KLRK1 in tumor was lower than that in normal tissue. KLRK1 expression was associated with gender, histologic grade, stage, T classification and vital status. Patients with high KLRK1 expression presented an improved overall survival (P = 0.0036) and relapse free survival (P = 0.0031). KLRK1 was found to have significant prognostic value in lung adenocarcinoma (P = 0.015), stage I/II (P = 0.03), older patients (P = 0.0052), and male (P = 0.0047) by subgroup overall survival analysis, and in lung adenocarcinoma (P = 0.0094), stage I/II (P = 0.0076), older patients (P = 0.0072), and male (P = 0.0033) by subgroup relapse free survival analysis. Lung adenocarcinoma cancer patients with high KLRK1 expression presented an improved overall survival (P = 0.015) and relapse free survival (P = 0.0094). In vitro studies indicated that KLRK1 inhibited tumor cell proliferation and migration. KLRK1 was an independent prognostic factor and high KLRK1 expression indicated a better overall and relapse free survival. KLRK1 may be a prognostic biomarker for lung adenocarcinoma cancer.

Expression and clinical significance of BDH1 in liver cancer

Liver cancer is a deadly disease with generally poor patient outcomes. BDH1 is a key enzyme that regulates the metabolism and synthesis of ketone bodies. This study sought to explore the prognostic relevance of BDH1 mRNA expression in liver cancer.We utilized the Cancer Genome Atlas datasets to analyze the relationship between BDH1 expression and clinical outcomes. We used Kaplan-Meier curves and Cox analyses to explore the relevance of BDH1 mRNA levels to patient prognosis. Further gene set enrichment analysis was conducted as a means of comparing differences in gene expression as a function of BDH1 expression.Liver cancer samples exhibited significantly decreased BDH1 mRNA expression, and that this downregulation was correlated with a number of clinicopathological variables including gender, histologic grade, stage, TNM classification, and both overall and relapse-free survival. We further determined that BDH1 mRNA expression was an independent predictor of liver cancer patient prognosis. A subsequent gene set enrichment analysis found genes affected by BDH1 expression to be those enriched in pathways relating to MYC and wnt/β-catenin signaling.Our preliminary findings demonstrate for the first time that low expression of BDH1 mRNA is a potentially valuable independent prognostic indicator for liver cancer detection.

LINC02535 promotes cell growth in poorly differentiated gastric cancer

Background

Abnormal long non‐coding RNA (lncRNA) expression plays important roles in gastric cancer. However, the functions of many lncRNAs in poorly differentiated gastric cancer (PDGC) remain unknown.

Methods

Three sets of paired tissues from patients with PDGC were used, and transcriptome sequencing was performed, followed by the construction and sequencing of a library and mapping of the reads. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and protein‐protein interaction (PPI) networks were analysed, and canonical pathway significance was calculated among the differentially expressed genes (DEGs; p < 0.05). Gene expression in 30 paired PDGC specimens and four cell lines was validated through quantitative PCR. Cell proliferation, migration, invasion, apoptosis, and wound healing were analysed.

Results

A total of 499 upregulated DEGs and 627 downregulated DEGs were identified between peritumoral and gastric cancer tissues. The proportions of positive and negative correlations between LINC02535 and the DEGs were 98.40% and 92.66%, respectively, while the Spearman's correlation coefficient was greater than 0.5. The PPI network showed that approximately 73.15% of the top five genes were directly correlated with LINC02535 according to the STRING database. Based on KEGG analysis, the functions of LINC02535 target genes were enriched in signalling pathways related to cancer cell growth. Furthermore, cell function studies showed that LINC02535 upregulation contributed to cell proliferation, migration, invasion, and wound healing and that its inhibition facilitated cell apoptosis.

Conclusion

LINC02535 expression was upregulated in PDGC and contributed to cell proliferation, migration, invasion and wound healing, whereas its inhibition in PDGC facilitated cell apoptosis.

Prognostic Significance and Related Mechanisms of Hexokinase 1 in Ovarian Cancer

Purpose

Ovarian cancer (OC) has the highest mortality among gynecological malignancies. Therefore, it is urgent to explore prognostic biomarkers to improve the survival of OC patients. One of the most prominent metabolic characteristics of cancer is effective glycolysis. Hexokinase 1 (HK1), as the first rate-limiting enzyme in glycolysis, is closely related to cancer progression. However, the role of HK1 in OC remains unclear.

Materials and Methods

The Cancer Genome Atlas (TCGA) database was used to detect the expression of HK1 in OC patients. The chi-squared test was performed to examine the correlations between HK1 and patients’ clinical characteristics. Survival analyses were undertaken to determine the relationship between HK1 and patient survival, while the univariate/multivariate Cox model was used to evaluate the role of HK1 in patient prognosis. Gene Set Enrichment Analysis (GSEA) was performed to ascertain the related signaling pathways of HK1. RT-qPCR was implemented to validate the mRNA expression of HK1 in OC cells. MTT was used to detect cell viability after adding 2DG and knocking down HK1 in OC cells. HK1 protein expression was examined by Western blotting. Glucose uptake, lactate production, and ATP assays were undertaken following knockdown of HK1 in OC cells. Colony formation assays were performed to determine OC cell proliferation after HK1 knockdown. Transwell and wound healing assays were carried out to detect the invasion and migration of OC cells after HK1 knockdown.

Results

We found that HK1 expression was increased in OC tissues and cells, and HK1 was related to the clinical characteristics of OC patients. Survival analysis revealed that OC patients in the HK1 overexpression group had poor survival. Moreover, univariant/multivariate analyses showed that HK1 may be an independent biomarker for the poor prognosis of OC patients. OC cell viability and proliferation decreased after knockdown of HK1. Consistently, glucose uptake, lactic acid production, ATP production, invasion, and migration were also decreased. Finally, GSEA enrichment analysis and Western blotting showed that HK1 was involved in MAPK/ERK signaling.

Conclusion

HK1 may be a biomarker for the poor prognosis of OC patients and a potential therapeutic target.

CircRNAs and LncRNAs in Osteoporosis

Osteoporosis is a systemic bone disease with bone fragility and increased fracture risk. The non-coding RNAs (ncRNAs) have appeared as important regulators of cellular signaling and pertinent human diseases. Studies have demonstrated that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) are involved in the progression of osteoporosis through a variety of pathways, and are considered as targets for the prophylaxis and treatment of osteoporosis. Based on an in-depth understanding of their roles and mechanisms in osteoporosis, we summarize the functions and molecular mechanisms of circRNAs and lncRNAs involved in the progression of osteoporosis and provide some new insights for the prognosis, diagnosis and treatment of osteoporosis.

Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach

Long noncoding RNAs (lncRNAs) play significant roles in various physiological and pathological processes via their interactions with biomolecules like DNA, RNA and protein. The existing in silico methods used for predicting the functions of lncRNA mainly rely on calculating the similarity of lncRNA or investigating whether an lncRNA can interact with a specific biomolecule or disease. In this work, we explored the functions of lncRNA from a different perspective: we presented a tool for predicting the interaction biomolecule type for a given lncRNA. For this purpose, we first investigated the main molecular mechanisms of the interactions of lncRNA-RNA, lncRNA-protein and lncRNA-DNA. Then, we developed an ensemble deep learning model: lncIBTP (lncRNA Interaction Biomolecule Type Prediction). This model predicted the interactions between lncRNA and different types of biomolecules. On the 5-fold cross-validation, the lncIBTP achieves average values of 0.7042 in accuracy, 0.7903 and 0.6421 in macro-average area under receiver operating characteristic curve and precision-recall curve, respectively, which illustrates the model effectiveness. Besides, based on the analysis of the collected published data and prediction results, we hypothesized that the characteristics of lncRNAs that interacted with DNA may be different from those that interacted with only RNA.

Diagnostic and prognostic value of HABP2 as a novel biomarker for endometrial cancer

BACKGROUND

Endometrial cancer is the fifth most common malignant disorder in women, with its incidence increasing. A biomarker with diagnostic and prognostic value remains to be found. The HABP2 protein, or Factor VII-activating protease, encodes a hyaluronic acid-binding protein.

METHODS

Patient data including clinical characteristics and RNAseq information of HABP2 was obtained from The Cancer Genome Atlas (TCGA), and analyzed by R statistic packages. A total of 370 women with endometrial cancer were enrolled in the study. To study the diagnostic value of HABP2 in patients with endometrial cancer, receiver operating characteristic (ROC) curves were plotted by the pROC package. To study the prognostic value of HABP2 in patients with endometrial cancer, the survival package in R was used and the Cox model was established.

RESULTS

HABP2 expression was lower in endometrial cancer compared with normal endometrial tissues. HABP2 showed moderate diagnostic value for endometrial cancer, with HBP2 expression associated with vital status, histologic grade, and residual tumor. HABP2 was an independent prognostic factor, with low HABP2 expression indicating a better overall survival.

CONCLUSIONS

HABP2 has diagnostic and prognostic value and maybe a novel biomarker for endometrial cancer.

The prognostic value of lncRNA SNHG4 and its potential mechanism in liver cancer

BACKGROUND AND OBJECT

Emerging evidence shows that non-coding RNA functions as new gene regulators and prognostic markers in several cancers, including liver cancer. Here, we focused on the small nucleolar RNA host gene 4 (SNHG4) in liver cancer prognosis based on The Cancer Genome Atlas (TCGA) data.

METHODS

The expression data and clinical information were downloaded from TCGA. Chi-square tests evaluated the correlation between SNHG4 expression and clinical parameters. Differences in survival between high and low expression groups (optic cutoff value determined by ROC) from Cox regression analysis were compared, and P-value was calculated by a log-rank test. Kaplan-Meier curves were compared with the log-rank test. GSEA and ceRNA network were conducted to explore the potential mechanism.

RESULTS

Data mining of lncRNA expression data for 371 patients with primary tumor revealed overexpression of SNHG4 in liver cancer. High SNHG4 expression was correlated with histological type (P = 0.01), histologic grade (P = 0.001), stage (P = 0.01), T classification (P = 0.004) and survival status (P = 0.013). Patients with high SNHG4 expression had poor overall survival and relapse-free survival compared with those with low SNHG4 expression. Multivariate analysis identified SNHG4 as an independent prognostic factor of poor survival in liver cancer. GSEA revealed related signaling pathway and ceRNA network explored the further mechanism.

CONCLUSION

High SNHG4 expression is an independent predictor of poor prognosis in liver cancer.

The Emerging Role of Adhesion GPCRs in Cancer

Aberrant expression, function, and mutation of G protein-coupled receptors (GPCRs) and their signaling partners, G proteins, have been well documented in many forms of cancer. These cell surface receptors and their endogenous ligands are implicated in all aspects of cancer including proliferation, angiogenesis, invasion, and metastasis. Adhesion GPCRs (aGPCRs) form the second largest family of GPCRs, most of which are orphan receptors with unknown physiological functions. This is mainly due to our limited insight into their structure, natural ligands, signaling pathways, and tissue expression profiles. Nevertheless, recent studies show that aGPCRs play important roles in cell adhesion to the extracellular matrix and cell-cell communication, processes that are dysregulated in cancer. Emerging evidence suggests that aGPCRs are implicated in migration, proliferation, and survival of tumor cells. We here review the role of aGPCRs in the five most common types of cancer (lung, breast, colorectal, prostate, and gastric) and emphasize the importance of further translational studies in this field.

Comprehensive multi-omics analysis identified core molecular processes in esophageal cancer and revealed GNGT2 as a potential prognostic marker

BACKGROUND

Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease remains elusive.

AIM

To investigate comprehensively the molecular process of esophageal cancer.

METHODS

Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer from The Cancer Genome Atlas data. Exacting gene interaction modules were generated, and hub genes in the module interaction network were found. Further, through survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related functions/pathways were identified to elucidate potential mechanisms in esophageal cancer.

RESULTS

A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding, and other biological processes as well as p53 signaling pathway, epidermal growth factor signaling pathway, and epidermal growth factor receptor signaling pathway. Transcription factors (including hypoxia inducible factor 1A) and non-coding RNAs (including colorectal differentially expressed and hsa-miR-330-3p) that significantly regulate dysfunction modules were identified. Survival analysis showed that G protein subunit gamma transducin 2 (GNGT2) was closely related to survival of esophageal cancer. DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Furthermore, the expression of GNGT2 was evaluated by quantitative real time polymerase chain reaction, and the results showed that GNGT2 expression was significantly upregulated in esophageal cancer patient samples and cell lines. Moreover, cell counting kit-8 assay revealed that GNGT2 could promote the proliferation of esophageal cancer cell lines.

CONCLUSION

This study not only revealed the potential regulatory factors involved in the development of esophageal cancer but also deepens our understanding of its underlying mechanism.