Identifying multiple collagen gene family members as potential gastric cancer biomarkers using integrated bioinformatics analysis

Analysis of miRNAs in Osteogenesis imperfecta Caused by Mutations in COL1A1 and COL1A2: Insights into Molecular Mechanisms and Potential Therapeutic Targets

Osteogenesis imperfecta (OI) is a group of connective tissue disorders leading to abnormal bone formation, mainly due to mutations in genes encoding collagen type I (Col I). Osteogenesis is regulated by a number of molecules, including microRNAs (miRNAs), indicating their potential as targets for OI therapy. The goal of this study was to identify and analyze the expression profiles of miRNAs involved in bone extracellular matrix (ECM) regulation in patients diagnosed with OI type I caused by mutations in COL1A1 or COL1A2. Primary skin fibroblast cultures were used for DNA purification and sequence analysis, followed by analysis of miRNA expression. Sequencing analysis revealed mutations of the COL1A1 or COL1A2 genes in all OI patients, including four previously unreported. Amongst the 40 miRNAs analyzed, 9 were identified exclusively in OI cells and 26 in both OI patients and the controls. In the latter case, the expression of six miRNAs (hsa-miR-10b-5p, hsa-miR-19a-3p, hsa-miR-19b-3p, has-miR-204-5p, has-miR-216a-5p, and hsa-miR-449a) increased, while four (hsa-miR-129-5p, hsa-miR-199b-5p, hsa-miR-664a-5p, and hsa-miR-30a-5p) decreased significantly in OI cells in comparison to their expression in the control cells. The identified mutations and miRNA expression profiles shed light on the intricate processes governing bone formation and ECM regulation, paving the way for further research and potential therapeutic advancements in OI and other genetic diseases related to bone abnormality management.

Identification of survival-associated biomarkers based on three datasets by bioinformatics analysis in gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most common malignant tumors with poor prognosis in terms of advanced stage. However, the survival-associated biomarkers for GC remains unclear.

AIM

To investigate the potential biomarkers of the prognosis of patients with GC, so as to provide new methods and strategies for the treatment of GC.

METHODS

RNA sequencing data from The Cancer Genome Atlas (TCGA) database of STAD tumors, and microarray data from Gene Expression Omnibus (GEO) database (GSE19826, GSE79973 and GSE29998) were obtained. The differentially expressed genes (DEGs) between GC patients and health people were picked out using R software (x64 4.1.3). The intersections were underwent between the above obtained co-expression of differential genes (co-DEGs) and the DEGs of GC from Gene Expression Profiling Interactive Analysis database, and Gene Ontology (GO) analysis, Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis, Gene Set Enrichment Analysis (GSEA), Protein-protein Interaction (PPI) analysis and Kaplan-Meier Plotter survival analysis were performed on these DEGs. Using Immunohistochemistry (IHC) database of Human Protein Atlas (HPA), we verified the candidate Hub genes.

RESULTS

With DEGs analysis, there were 334 co-DEGs, including 133 up-regulated genes and 201 down-regulated genes. GO enrichment analysis showed that the co-DEGs were involved in biological process, cell composition and molecular function pathways. KEGG enrichment analysis suggested the co-DEGs pathways were mainly enriched in ECM-receptor interaction, protein digestion and absorption pathways, etc. GSEA pathway analysis showed that co-DEGs mainly concentrated in cell cycle progression, mitotic cell cycle and cell cycle pathways, etc. PPI analysis showed 84 nodes and 654 edges for the co-DEGs. The survival analysis illustrated 11 Hub genes with notable significance for prognosis of patients were screened. Furtherly, using IHC database of HPA, we confirmed the above candidate Hub genes, and 10 Hub genes that associated with prognosis of GC were identified, namely BGN, CEP55, COL1A2, COL4A1, FZD2, MAOA, PDGFRB, SPARC, TIMP1 and VCAN.

CONCLUSION

The 10 Hub genes may be the potential biomarkers for predicting the prognosis of GC, which can provide new strategies and methods for the diagnosis and treatment of GC.

ENTPD1-AS1–miR-144-3p-mediated high expression of COL5A2 correlates with poor prognosis and macrophage infiltration in gastric cancer

BACKGROUND

Gastric cancer (GC) is a malignant tumor with high morbidity and mortality. Expression of COL5A2 is significantly elevated in GC. Abnormal expression of noncoding RNAs (ncRNAs) have been found in GC, including microRNA (miRNA) and long noncoding RNA (lncRNA). Competing endogenous RNA network plays an important regulatory role in GC. However, its specific regulatory mechanism has not been elucidated.

AIM

To gain insight into the ncRNA regulatory mechanism and immune microenvironment related to COL5A2 in GC.

METHODS

RNA sequencing data and clinical information from The Cancer Genome Atlas data portal were used to analyze the expressions of COL5A2, miRNA and lncRNA related to the prognosis of GC. Cox regression analysis and Kyoto Encyclopedia of Genes and Genomes analysis were performed to assess the risk factors and relevant function of COL5A2. StarBase was used to predict the interaction of miRNA–lncRNA or miRNA–mRNA in GC. The relationship between COL5A2, miR-144-3p and ENTPD1-AS1 were verified by dual luciferase reporter assay. The association of COL5A2 with immune cell infiltration were analyzed using the Tumor Immune Estimation Resource database and single sample gene set enrichment analysis. The expression of COL5A2 and macrophages in paired GC tissues were detected by immunohistochemical staining.

RESULTS

We verified that the upregulation of COL5A2 expression was associated with the prognosis of GC and was an independent risk factor for GC. miR-144-3p was downregulated and correlated with the prognosis of GC. miR-144-3p regulated the expression of COL5A2 through direct interaction with COL5A2. ENTPD1-AS1 was elevated in GC and competitively bound to miR-144-3p, thus inhibiting the expression of miR-144-3p. ENTPD1-AS1 enhanced the expression of COL5A2 through sponging miR-144-3p. Compared to paired normal tissue, COL5A2 expression was upregulated at the protein level, especially in the middle and late stages of GC. The high expression of COL5A2 was positively linked to macrophage infiltration in GC.

CONCLUSION

COL5A2 regulated by ENTPD1-AS1–miR-144-3p was associated with poor prognosis and macrophage infiltration in GC. This could be a new biomarker and therapeutic target in GC.

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosis

Introduction

Gastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.

Methods

Datasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.

Results and disscussion

KEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.

PI3K/AKT/mTOR inhibitors as potential extracellular matrix modulators for targeting EMT subtype gastric tumors

Targeting the extracellular matrix (ECM) is considered as a promising strategy in cancer therapeutics. This study was designed to identify the potential ECM modulators for gastric cancer therapeutics. Exploration of the expression profiles of gastric tumors revealed the elevated expression of ECM genes in gastric tumor tissues compared to the adjacent normal tissues with increased expression in diffuse subtype gastric tumors and specifically in epithelial to mesenchymal transition (EMT) molecular subtype tumors. Consensus ECM gene set was derived from the expression profiles of gastric tumors. The correlative analysis was performed between the expression pattern of the ECM gene set and the drug sensitivity pattern of a panel of drugs across gastric cancer cell lines. Negative correlation between the expression of ECM genes and sensitivity of a number of drugs targeting PI3K/mTOR signaling, chromatin histone acetylation and ABL signaling was observed. These pathways are known for their role in cell-mediated adhesion, differentiation and epithelial to mesenchymal transition. The current results reveal the possibility of using PI3K/AKT/mTOR modulators for targeted gastric cancer therapy in patients with dysregulated ECM.

Up-regulation of collagen type V alpha 2 (COL5A2) promotes malignant phenotypes in gastric cancer cell via inducing epithelial-mesenchymal transition (EMT)

Recent studies have reported that collagen type V alpha 2 (COL5A2) is a hub gene and associated with the prognosis of gastric cancer (GC) patients, playing an important role in GC. In this study, we aim to fathom out the biological roles of COL5A2 and its relevant mechanism in GC. Oncomine, gene expression profiling interactive analysis, and UALCAN were used to explore the effects of COL5A2 on GC. Cell counting kit-8 assay, colony formation assay, and transwell assay were conducted to investigate the biological behaviors of GC cell lines AGS and SGC-7901. Quantitative reverse transcription polymerase chain reaction and western blot were performed to determine gene and protein expressions. COL5A2 expression was up-regulated and negatively correlated with survival percentage of GC patients. COL5A2 expression was notably elevated in high stage and high grade of GC. Down-regulation of COL5A2 inhibited proliferation, migration, and invasion of AGS and SGC-7901 cells. COL5A2 induced epithelial-mesenchymal transition (EMT) by promoting the expressions of mesenchymal markers (SNAI1, SNAI2, TWIST, VIM, and MMP2), thereby facilitating the malignant phenotypes of GC. COL5A2 plays an oncogenic role in GC and has potential to predict the progression and prognosis of GC patients.

The involvement of collagen family genes in tumor enlargement of gastric cancer

Extracellular matrix (ECM) not only serves as a support for tumor cell but also regulates cell-cell or cell-matrix cross-talks. Collagens are the most abundant proteins in ECM. Several studies have found that certain collagen genes were overexpressed in gastric cancer (GC) tissues and might serve as potential biomarkers and therapeutic targets in GC patients. However, the expression patterns of all collagen family genes in GC tissue and their functions are still not clear. With RNA sequencing (RNA-Seq) data, microarray data, and corresponding clinical data obtained from TCGA, GTEx, and GEO databases, bioinformatics analyses were performed to investigate the correlation between the expression patterns of collagen family genes and GC progression. We found that quite many of the collagen family genes were overexpressed in GC tissues. The increase in mRNA expression of most of these overexpressed collagen genes happened between T1 and T2 stage, which indicates the significance of collagens in tumor enlargement of GC. Notably, the mRNA expressions of these differentially expressed collagens genes were highly positively correlated. The elevated expression of a large number of collagen genes in early T stage might greatly change the composition and structure organization of ECM, contributing to ECM remodeling in GC progression.

The Emerging Role of MTHFD Family Genes in Regulating the Tumor Immunity of Oral Squamous Cell Carcinoma

Objective

To investigate the function and regulatory mechanisms of methylenetetrahydrofolate dehydrogenase (MTHFD) family genes in oral squamous cell carcinoma (OSCC), especially focus on their regulating role in tumor immunity.

Methods

The publicly available data from the TCGA database were used to investigate the expression pattern and regulatory role of MTHFD family genes in OSCC. More importantly, the involvement of MTHFD family genes in tumor immunity was investigated in terms of immune and stromal cell infiltration in tumor microenvironment, tumor-infiltrating immune cells, and immunomodulatory genes (e.g., immunoinhibitory genes and immunostimulatory genes). Statistical analysis was performed using R software packages and public web servers.

Results

MTHFD family genes were considerably upregulated in OSCC as compared with normal oral tissue. Patients with high MTHFD2 expression presented worse survival outcomes than those with low MTHFD2 expression. Functional enrichment analysis showed that the top 100 positively and negatively correlated genes of the MTHFD family genes were significantly enriched in several KEGG pathways, including cell cycle, spliceosome, DNA replication, and Th17 cell differentiation. As a result of tumor immunity analysis, MTHFD2L expression was found to be negatively related to the Estimate-Stromal-Immune score in OSCC; however, there was no statistical significance between the Estimate-Stromal-Immune score and MTHFD1, MTHFD1L, or MTHFD2 in OSCC. Additionally, MTHFD family genes were found to be significantly positively correlated with tumor-infiltrating immune cells, including Treg and Th17 cells. Moreover, MTHFD family genes were significantly correlated with several immune inhibitory genes such as CD274 and CTLA4 and several immune-stimulatory genes such as CXCL12, CXCR4, and TMIGD2.

Conclusion

Given the expression pattern, prognostic value, biological functions, and involvement in tumor immunity, MTHFD family genes could serve as potential therapeutic biomarkers in targeting tumor immunity in oral cancer.

Collagen Family and Other Matrix Remodeling Proteins Identified by Bioinformatics Analysis as Hub Genes Involved in Gastric Cancer Progression and Prognosis

Gastric cancer has remained in the top five cancers for over ten years, both in terms of incidence and mortality due to the shortage of biomarkers for disease follow-up and effective therapies. Aiming to fill this gap, we performed a bioinformatics assessment on our data and two additional GEO microarray profiles, followed by a deep analysis of the 40 differentially expressed genes identified. PPI network analysis and MCODE plug-in pointed out nine upregulated hub genes coding for proteins from the collagen family (COL12A1, COL5A2, and COL10A1) or involved in the assembly (BGN) or degradation of collagens (CTHRC1), and also associated with cell adhesion (THBS2 and SPP1) and extracellular matrix degradation (FAP, SULF1). Those genes were highly upregulated at the mRNA and protein level, the increase being correlated with pathological T stages. The high expression of BGN (p = 8 × 10⁻¹²), THBS2 (p = 1.2 × 10⁻⁶), CTHRC1 (p = 1.1 × 10⁻⁴), SULF1 (p = 3.8 × 10⁻⁴), COL5A1 (p = 1.3 × 10⁻⁴), COL10A1 (p = 5.7 × 10⁻⁴), COL12A1 (p = 2 × 10⁻³) correlated with poor overall survival and an immune infiltrate based especially on immunosuppressive M2 macrophages (p-value range 4.82 × 10⁻⁷–1.63 × 10⁻¹³). Our results emphasize that these genes could be candidate biomarkers for GC progression and prognosis and new therapeutic targets.

Identification of circRNA Biomarker for Gastric Cancer through Integrated Analysis

Gastric cancer (GC) is one of the most common malignant tumors and ranks third in cancer mortality globally. Although, a lot of advancements have been made in diagnosis and treatment of gastric cancer, there is still lack of ideal biomarker for the diagnosis and treatment of gastric cancer. Due to the poor prognosis, the survival rate is not improved much. Circular RNAs (circRNAs) are single-stranded RNAs with a covalently closed loop structure that don't have the 5'-3' polarity and a 3' polyA tail. Because of their circular structure, circRNAs are more stable than linear RNAs. Previous studies have found that circRNAs are involved in several biological processes like cell cycle, proliferation, apoptosis, autophagy, migration and invasion in different cancers, and participate in some molecular mechanisms including sponging microRNAs (miRNAs), protein translation and binding to RNA-binding proteins. Several studies have reported that circRNAs play crucial role in the occurrence and development of different types of cancers. Although, some studies have reported several circRNAs in gastric cancer, more studies are needed in searching new biomarkers for gastric cancer diagnosis and treatment. Here, we investigated potential circRNA biomarkers for GC using next-generation sequencing (NGS) data collected from 5 paired GC samples. A total of 45,783 circRNAs were identified in all samples and among them 478 were differentially expressed (DE). The gene ontology (GO) analysis of the host genes of the DE circRNAs showed that some genes were enriched in several important biological processes, molecular functions and cellular components. The Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis revealed that some host genes were enriched in several GC related pathways. The circRNA-miRNA-gene interaction network analysis showed that two circRNAs circCEACAM5 and circCOL1A1 were interacted with gastric cancer related miRNAs, and their host genes were also the important therapeutic and prognostic biomarkers for GC. The experimental results also validated that these two circRNAs were DE in GC compared to adjacent normal tissues. Overall, our findings suggest that these two circRNAs circCEACAM5 and circCOL1A1 might be the potential biomarkers for the diagnosis and treatment of GC.

PDGFRB is a potential prognostic biomarker and correlated with immune infiltrates in gastric cancer

Gastric cancer (GC) is a common cancer with high mortality and morbidity rates worldwide. Although medical and surgical treatments have improved, the mechanisms of the progression of GC remain unclear. Platelet-derived growth factor receptor-β (PDGFRB) plays a pivotal role in angiogenesis and tumor cell proliferation and has been suggested as a prognostic marker of cancer. This study aimed to explore the relationship of PDGFRB expression with clinicopathologic characteristics, immune cell infiltration status, and prognosis in GC. In this study, we visualized the expression and prognostic values of PDGFRB in GC using the Oncomine, UALCAN, GEPIA, and Kaplan-Meier Plotter databases. And then we explored the potential relationships between PDGFRB expression and the levels of immune cell infiltration using the TIMER, GEPIA databases and CIBERSORT algorithm. Furthermore, LinkedOmics analysis was performed to explore the functions for PDGFRB. The results showed close correlations between PDGFRB and immune cell infiltration especially M2 Macrophage infiltration in GC. High PDGFRB expression was related to poor outcomes in GC. High PDGFRB expression can negatively affect GC prognosis by promoting angiogenesis and modulating the tumor immune microenvironment. These results strongly suggest that PDGFRB can be used as a prognostic biomarker of GC and provide novel insights into possible immunotherapeutic targets.

A tumour-resident Lgr5+ stem-cell-like pool drives the establishment and progression of advanced gastric cancers

Gastric cancer is among the most prevalent and deadliest of cancers globally. To derive mechanistic insight into the pathways governing this disease, we generated a Claudin18-IRES-CreERT2 allele to selectively drive conditional dysregulation of the Wnt, Receptor Tyrosine Kinase and Trp53 pathways within the gastric epithelium. This resulted in highly reproducible metastatic, chromosomal-instable-type gastric cancer. In parallel, we developed orthotopic cancer organoid transplantation models to evaluate tumour-resident Lgr5⁺ populations as functional cancer stem cells via in vivo ablation. We show that Cldn18 tumours accurately recapitulate advanced human gastric cancer in terms of disease morphology, aberrant gene expression, molecular markers and sites of distant metastases. Importantly, we establish that tumour-resident Lgr5⁺ stem-like cells are critical to the initiation and maintenance of tumour burden and are obligatory for the establishment of metastases. These models will be invaluable for deriving clinically relevant mechanistic insights into cancer progression and as preclinical models for evaluating therapeutic targets.

Differential Expression of COL1A1, COL1A2, COL6A3, and SULF1 as Prognostic Biomarkers in Gastric Cancer

Background

Gastric cancer (GC) is among the most prevalent cancers globally. As such, there is a need to explore the mechanism underlying its pathogenesis and identify potential biomarkers for its prognosis.

Methods

ONCOMINE was used to screen differentially expressed genes between GC and normal gastric mucosa. GEPIA was used to analyze the expression and correlation of candidate genes in tumor node metastasis (TNM) stage. STRING was used to construct protein interaction network. Kaplan-Meier plotter was used to analyze survival. TIMER was used to evaluate the association between candidate genes and immune cell infiltration.

Results

From the ONCOMINE database, we found COL1A1, COL1A2, COL6A3, and SULF1 genes were significantly upregulated in stomach adenocarcinomas. There was a considerable correlation between the expression of COL1A1 (p = 0.029), COL1A2 (p = 0.004), COL6A3 (p = 0.002), SULF1 (p = 0.001), and the TNM stage. COL1A1 was positively correlated with ERBB2 (R = -0.037, p = 0.46), while the other three genes were negatively correlated with ERBB2 (p > 0.05). The Kaplan-Meier plotter showed that low transcriptional levels of COL1A1 (p = 0.0020), COL1A2 (p = 0.0015), COL6A3 (p = 0.0015), and SULF1 (p = 0.0016) in gastric cancer patients were remarkably related to longer overall survival. In addition, there was a close relationship between chemokine expression and infiltration of the six immune cell types: B cells, macrophages, CD4+ T cells, CD8+ T cells, dendritic cells, and neutrophils, implying that the genes acted as indicators of both prognosis and immune status.

Conclusion

Our findings implicate COL1A1, COL1A2, COL6A3, and SULF1 as candidate biomarkers for the prognosis of gastric cancer.

Upregulation of HOXC9 generates interferon-gamma resistance in gastric cancer by inhibiting the DAPK1/RIG1/STAT1 axis

Clinical reports indicate that gastric cancer (GC) has a high mortality rate, but its pathological mechanism remains poorly understood. This work integrated bioinformatics analysis with experimental verification to explore novel biomarkers of gastric cancer. First, weighted gene coexpression network analysis was applied to screen significant genes correlated with GC development. Gene set enrichment analysis was also used to unearth the most relevant biological functions of significant genes. As a result, we discovered homeobox C9 (HOXC9) as a novel oncogene in GC, primarily through negatively regulating immune response. High expression of HOXC9 predicted a poor prognosis in GC patients, and knocking down HOXC9 efficiently enhanced the interferon‐gamma (IFNγ)‐dependent apoptosis in two GC cell lines as well as organoids from patients. Furthermore, cleaved caspase‐3/7 and phosphorylated signal transducer and activator of transcription 1 (p‐STAT1) were also significantly enhanced in HOXC9 knockdown cells and organoids treated with IFNγ. Mechanistically, we found that HOXC9 inhibited the death‐associated protein kinase 1 (DAPK1) and its downstream retinoic acid‐inducible gene‐I (RIG1) to generate GC IFNγ resistance. In summary, we identified and confirmed that HOXC9 generates IFNγ resistance in GC by inhibiting the DAPK1/RIG1/p‐STAT1 axis.

Current Insights on the Diverse Structures and Functions in Bacterial Collagen-like Proteins

The dearth of knowledge on the diverse structures and functions in bacterial collagen-like proteins is in stark contrast to the deep grasp of structures and functions in mammalian collagen, the ubiquitous triple-helical scleroprotein that plays a central role in tissue architecture, extracellular matrix organization, and signal transduction. To fill and highlight existing gaps due to the general paucity of data on bacterial CLPs, we comprehensively reviewed the latest insight into their functional and structural diversity from multiple perspectives of biology, computational simulations, and materials engineering. The origins and discovery of bacterial CLPs were explored. Their genetic distribution and molecular architecture were analyzed, and their structural and functional diversity in various bacterial genera was examined. The principal roles of computational techniques in understanding bacterial CLPs' structural stability, mechanical properties, and biological functions were also considered. This review serves to drive further interest and development of bacterial CLPs, not only for addressing fundamental biological problems in collagen but also for engineering novel biomaterials. Hence, both biology and materials communities will greatly benefit from intensified research into the diverse structures and functions in bacterial collagen-like proteins.

Identification of Core Prognosis-Related Candidate Genes in Chinese Gastric Cancer Population Based on Integrated Bioinformatics

Background

Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. There are great geographical differences in the incidence of GC, and somatic mutation rates of driver genes are also different. The present study is aimed at screening core prognosis-related candidate genes in Chinese gastric cancer population based on integrated bioinformatics for the early diagnosis and prognosis of GC.

Methods

In the present study, the differentially expressed genes (DEGs) in GC were identified using four microarray datasets from the Gene Expression Omnibus (GEO) database. The samples of these datasets were all from China. Functional enrichment analysis of DEGs was conducted to evaluate the underlying molecular mechanisms involved in GC. Protein-protein interaction (PPI) network and cytoHubba were performed to determine hub genes associated with GC. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the hub genes.

Results

A total of 240 DEGs were obtained through the RRA method, including 80 upregulated genes and 160 downregulated genes. Upregulated genes were mainly enriched in extracellular matrix organization, extracellular matrix, and extracellular matrix structural constituent. The downregulated genes were mainly enriched in digestion, extracellular space, and oxidoreductase activity. The KEGG pathway enrichment analysis showed that the upregulated genes were mainly associated with ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. And downregulated genes were mainly associated with the metabolism of xenobiotics by cytochrome P450, metabolic pathways, and gastric acid secretion. The transcriptional and translational expression levels of the genes including COL1A1, COL5A2, COL12A1, and VCAN were higher in GC tissues than normal tissues.

Conclusion

A total of four genes including COL1A1, COL5A2, COL12A1, and VCAN were considered potential GC biomarkers in the Chinese population. And ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway were revealed to be important mechanisms of GC. Our findings provide novel insights into the occurrence and progression of GC in the Chinese population.

Analysis of Cyclin-Dependent Kinase 1 as an Independent Prognostic Factor for Gastric Cancer Based on Statistical Methods

OBJECTIVE

The aim of this study was to investigate the expression of cyclin-dependent kinase 1 (CDK1) in gastric cancer (GC), evaluate its relationship with the clinicopathological features and prognosis of GC, and analyze the advantage of CDK1 as a potential independent prognostic factor for GC.

METHODS

The Cancer Genome Atlas (TCGA) data and corresponding clinical features of GC were collected. First, the aim gene was selected by combining five topological analysis methods, where the gene expression in paracancerous and GC tissues was analyzed by Limma package and Wilcox test. Second, the correlation between gene expression and clinical features was analyzed by logistic regression. Finally, the survival analysis was carried out by using the Kaplan-Meier. The gene prognostic value was evaluated by univariate and multivariate Cox analyses, and the gene potential biological function was explored by gene set enrichment analysis (GSEA).

RESULTS

CDK1 was selected as one of the most important genes associated with GC. The expression level of CDK1 in GC tissues was significantly higher than that in paracancerous tissues, which was significantly correlated with pathological stage and grade. The survival rate of the CDK1 high expression group was significantly lower than that of the low expression group. CDK1 expression was significantly correlated with overall survival (OS). CDK1 expression was mainly involved in prostate cancer, small cell lung cancer, and GC and was enriched in the WNT signaling pathway and T cell receptor signaling pathway.

CONCLUSION

CDK1 may serve as an independent prognostic factor for GC. It is also expected to be a new target for molecular targeted therapy of GC.

Identification of Potential Core Genes Associated With the Progression of Stomach Adenocarcinoma Using Bioinformatic Analysis

Purpose

Stomach adenocarcinoma (STAD) is one of the most frequently diagnosed cancer in the world with both high mortality and high metastatic capacity. Therefore, the present study aimed to investigate novel therapeutic targets and prognostic biomarkers that can be used for STAD treatment.

Materials and Methods

We acquired four original gene chip profiles, namely GSE13911, GSE19826, GSE54129, and GSE65801 from the Gene Expression Omnibus (GEO). The datasets included a total of 114 STAD tissues and 110 adjacent normal tissues. The GEO2R online tool and Venn diagram software were used to discriminate differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enriched pathways were also performed for annotation and visualization with DEGs. The STRING online database was used to identify the functional interactions of DEGs. Subsequently, we selected the most significant DEGs to construct the protein-protein interaction (PPI) network and to reveal the core genes involved. Finally, the Kaplan-Meier Plotter online database and Gene Expression Profiling Interactive Analysis (GEPIA) were used to analyze the prognostic information of the core DEGs.

Results

A total of 114 DEGs (35 upregulated and 79 downregulated) were identified, which were abnormally expressed in the GEO datasets. GO analysis demonstrated that the majority of the upregulated DEGs were significantly enriched in collagen trimer, cell adhesion, and identical protein binding. The downregulated DEGs were involved in extracellular space, digestion, and inward rectifier potassium channel activity. Signaling pathway analysis indicated that upregulated DEGs were mainly enriched in receptor interaction, whereas downregulated DEGs were involved in gastric acid secretion. A total of 80 DEGs were screened into the PPI network complex, and one of the most important modules with a high degree was detected. Furthermore, 10 core genes were identified, namely COL1A1, COL1A2, FN1, COL5A2, BGN, COL6A3, COL12A1, THBS2, CDH11, and SERPINH1. Finally, the results of the prognostic information further demonstrated that all 10 core genes exhibited significantly higher expression in STAD tissues compared with that noted in normal tissues.

Conclusion

The multiple molecular mechanisms of these novel core genes in STAD are worthy of further investigation and may reveal novel therapeutic targets and biomarkers for STAD treatment.

Crosstalk Between Cancer Associated Fibroblasts and Cancer Cells in Scirrhous Type Gastric Cancer

Gastric cancer (GC) is the third leading cause among all cancer deaths globally. Although the treatment outcome of GC has improved, the survival of patients with GC at stages III and IV remains unsatisfactory. Among several types of GC, scirrhous type GC (SGC) shows highly aggressive growth and invasive activity, leading to frequent peritoneal metastasis. SGC is well known to accompany abundant stromal cells that compose the tumor microenvironment (TME) along with the produced extracellular matrix (ECM) and secreted factors. One of the main stromal components is cancer associated fibroblast (CAF). In the SGC microenvironment, CAFs are a source of various secreted factors, including fibroblast growth factors (FGFs), which mediate prominent tumor-stimulating activity. In turn, cancer cells also secrete numerous factors, which can activate and educate CAFs. Current findings suggest that cancer cells and stromal cells communicate interactively via the soluble factors, the ECM, and likely also by exosomes. In this review, we focus on the soluble factors mediating communication between cancer cells and CAFs in SGC, and consider how they are related to the modulation of TME and the high rate of peritoneal metastasis. At last, we discuss the perspectives on targeting these communication pathways for improved future treatment.