Identification of COL4A1 as a potential gene conferring trastuzumab resistance in gastric cancer based on bioinformatics analysis

Comprehensive analysis of the expression, prognostic, and immune infiltration for COL4s in stomach adenocarcinoma

BACKGROUND

Collagen (COL) genes, play a key role in tumor invasion and metastasis, are involved in tumor extracellular matrix (ECM)-receptor interactions and focal adhesion pathways. However, studies focusing on the diagnostic value of the COL4 family in stomach adenocarcinoma (STAD) are currently lacking.

METHODS

The TCGA database was employed to retrieve the clinical features and RNA sequencing expression profiles of patients with STAD. We conducted an investigation to examine the expression disparities between STAD and adjacent normal tissues. Kaplan-Meier survival analysis was utilized to assess their prognostic significance, while Spearman correlation analysis was employed to determine their association with immune checkpoint genes and immunomodulatory molecules. Furthermore, GO and KEGG analyses were performed on the COL4s-related genes, revealing potential biological pathways through gene set enrichment analysis (GSEA). Subsequently, we explored the extent of immune infiltration of the COL4 family in STAD using the TIMER database. Lastly, the expression levels of the COL4 family in STAD were further validated through quantitative PCR (qPCR) and western blot techniques.

RESULTS

The expression levels of COL4A1/2 were significantly upregulated, while COL4A5/6 were conspicuously downregulated in STAD. The survival analysis revealed that the upregulated COL4s indicated poorer overall survival, first progression and post-progression survival outcomes. Additionally, our findings demonstrated a positive correlation between the expressions of COL4A1/2/3/4 and the infiltration of immune cells, including CD8 + T cells, dendritic cells, macrophages, neutrophils and CD4 + T cells. Further correlation analysis uncovered a favorable association between the expression of COL4A1/2/3/4 and various crucial immunomodulatory molecules, immunological checkpoint molecules, and chemokines. Quantitative PCR analysis confirmed that the expression patterns of COL4A1/3/4/6 genes aligned with the finding from the TCGA database. However, gastric cancer cells exhibited downregulation of COL4A2. Consistently, the protein level of COL4A1 was elevated, whereas the protein level of COL4A2 was reduced in the gastric cancer cell lines.

CONCLUSION

COL4s could potentially serve as biomarkers for diagnosing and predicting the prognosis of STAD.

A Five-gene Signature based on MicroRNA for Predicting Prognosis and Immunotherapy in Stomach Adenocarcinoma

AIMS

We aimed to classify molecular subtypes and establish a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in Stomach adenocarcinoma (STAD).

BACKGROUND

STAD is a common diagnosed gastrointestinal malignancy and its heterogeneity is a big challenge that influences prognosis and precision therapies. Present study was designed to classify molecular subtypes and construct a prognostic gene signature based on miRNAs for the prognostic prediction and therapeutic response in STAD.

OBJECTIVE

The objective of this study is to investigate the molecular subtypes and prognostic model for STAD.

METHODS

A STAD specific miRNA-messenger RNA (mRNA) competing endogenous RNA (ceRNA) network was generated using the RNA-Seq and miRNA expression profiles from The Cancer Genome Atlas (TCGA) database, in which miRNA-related mRNAs were screened. Molecular subtypes were then determined using miRNA-related genes. Through univariate Cox analysis and multivariate regression analysis, a prognostic model was established in GSE84437 Train dataset and validated in GSE84437 Test, TCGA, GSE84437 and GSE66229 datasets. Immunotherapy datasets were employed for assessing the performance of the risk model. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was applied to validate the expression of hub genes used for the risk score signature.

RESULTS

We constructed a ceRNA network containing 84 miRNAs and 907 mRNAs and determined two molecular subtypes based on 26 genes from the intersection of TCGASTAD and GSE84437 datasets. Subtype S2 had poor prognosis, lower tumor mutational burden, higher immune score and lower response to immunotherapy. Subtype S1 was more sensitive to Sorafenib, Pyrimethamine, Salubrinal, Gemcitabine, Vinorelbine and AKT inhibitor VIII. Next, a five-gene signature was generated and its robustness was validated in Test and external datasets. This risk model also had a good prediction performance in immunotherapy datasets.

CONCLUSION

This study promotes the underlying mechanisms of miRNA-based genes in STAD and offers directions for classification. A five-gene signature accurately predicts the prognosis and helps therapeutic options.

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysis

AIM

Gastric cancer (GC) is one of the most diagnosed cancers worldwide. GC is a heterogeneous disease whose pathogenesis has not been entirely understood. Besides, the GC prognosis for patients remains poor. Hence, finding reliable biomarkers and therapeutic targets for GC patients is urgently needed.

METHODS

GSE54129 and GSE26942 datasets were downloaded from Gene Expression Omnibus (GEO) database to detect differentially expressed genes (DEGs). Then, gene set enrichment analyses and protein-protein interactions were investigated. Afterward, ten hub genes were identified from the constructed network of DEGs. Then, the expression of hub genes in GC was validated. Performing survival analysis, the prognostic value of each hub gene in GC samples was investigated. Finally, the databases were used to predict microRNAs that could regulate the hub genes. Eventually, top miRNAs with more interactions with the list of hub genes were introduced.

RESULTS

In total, 203 overlapping DEGs were identified between both datasets. The main enriched KEGG pathway was "Protein digestion and absorption." The most significant identified GO terms included "primary alcohol metabolic process," "basal part of cell," and "extracellular matrix structural constituent conferring tensile strength." Identified hub modules were COL1A1, COL1A2, TIMP1, SPP1, COL5A2, THBS2, COL4A1, MUC6, CXCL8, and BGN. The overexpression of seven hub genes was associated with overall survival. Moreover, among the list of selected miRNAs, hsa-miR-27a-3, hsa-miR-941, hsa-miR-129-2-3p, and hsa-miR-1-3p, were introduced as top miRNAs targeting more than five hub genes.

CONCLUSIONS

The present study identified ten genes associated with GC, which may help discover novel prognostic and diagnostic biomarkers as well as therapeutic targets for GC. Our results may advance the understanding of GC occurrence and progression.

Identification of Hub Genes Associated with Gastric Cancer via Bioinformatics Analysis and Validation Studies

Introduction

Hub genes related to the development of gastric cancer (GC) were identified based on bioinformatics methods. This study aimed to identify GC hub genes, explore the expression of genes in GC and their correlation with prognosis, so as to provide strategies for GC diagnosis and targeted therapy.

Methods

Two messenger RNA (mRNA) microarray datasets were downloaded from GEO database. These data were combined with TCGA database to obtain common DEGs between GC tissues and normal tissues. GO and KEGG pathway enrichment analysis was performed. Visualized PPI network analysis was performed by Cytoscape to further identify hub genes. GEPIA database was used to evaluate the prognostic value of hub genes. The online software Ualcan was applied to analyze the expression of the prognosis-related genes in cancer tissues and normal tissues from different perspectives of primary GC, TNM stage, nodal metastasis status and tumor grade. Immunohistochemical staining of GC tissues and normal tissues was performed to evaluate the expression of signature genes in GC.

Results

Eighty-four common differentially expressed genes (DEGs) in GC were identified. These genes were closely related to the P13K-Akt signal pathway and other signaling pathways. Ten hub genes were identified. Collagen type I alpha 1 (COL1A1) and collagen type IV alpha 1 (COL4A1) were significantly associated with poor prognosis of GC and were all positively correlated with T stage, distant metastasis, and TNM stage of GC. Immunohistochemistry revealed that the expression of these 2 genes was upregulated in GC tissues. These 2 genes expression was negatively related with 5-year survival rate of GC patients.

Conclusion

Ten highly expressed hub genes in GC tissue were mined by bioinformatics method. COL1A1 and COL4A1 were significantly associated with the prognosis of GC. This study provided a theoretical basis for the pathogenesis, clinical diagnosis and therapeutic targets of GC.

Identification and Validation of Signature Genes and Potential Therapy Targets of Inflammatory Bowel Disease and Periodontitis

Background

Inflammatory bowel disease (IBD) and periodontitis (PD) are correlated, although the pathogenic mechanism behind their correlation has not been clarified. This study aims to explore the common signature genes and potential therapeutic targets of IBD and PD using transcriptomic analysis.

Methods

The GEO database was used to download datasets of IBD and PD, and differential expression analysis was used to identify DEGs. We then conducted GO and KEGG enrichment analyses of the shared genes. Next, we applied 4 machine learning (ML) algorithms (GLM, RF, GBM, and SVM) to select the best prediction model for diagnosing the disease and obtained the hub genes of IBD and PD. The diagnostic value of the signature genes was verified by a validation set and qRT‒PCR experiments. Subsequently, immune cell infiltration in IBD samples and PD samples was analyzed by ssGSEA. Finally, we investigated and validated the response of hub genes to infliximab therapy.

Results

We identified 43 upregulated genes as shared genes by intersecting the DEGs of IBD and PD. Functional enrichment analysis suggested that the shared genes were closely associated with immunity and inflammation. The ML algorithm and qRT‒PCR results indicated that IGKC and COL4A1 were the hub genes with the most diagnostic value for IBD and PD. Subsequently, through immune infiltration analysis, CD4 T cells, NK cells and neutrophils were identified to play crucial roles in the pathogenesis of IBD and PD. Finally, through in vivo and in vitro experiments, we found that IGKC and COL4A1 were significantly downregulated during the treatment of patients with IBD using infliximab.

Conclusion

We investigated the potential association between IBD and PD using transcriptomic analysis. The IGKC and COL4A1 genes were identified as characteristic genes and novel intervention targets for these two diseases. Infliximab may be used to treat or prevent IBD and PD.

Identification of PTPN22 as a potential genetic biomarker for abdominal aortic aneurysm

Abdominal aortic aneurysm (AAA) is a severe life-threatening disease that is generally asymptomatic and is diagnosed at a very late stage. The genetic component underpinning AAA is considerable, with an estimated heritability of up to 70%. Therefore, identifying genetic biomarkers for AAA is valuable for predicting high-risk populations. We used integrative bioinformatics and cellular AAA model-based validation to reveal that the gene encoding protein tyrosine phosphatase non-receptor type 22 (PTPN22) may be a potentially useful diagnostic biomarker for AAA. Integrative bioinformatics analyses of clinical specimens showed that PTPN22 expression was consistently upregulated in aortic tissues and peripheral blood mononuclear cells (PBMCs) derived from patients with AAA. Moreover, transcriptomics data revealed that PTPN22 is a potential biomarker for AAA with limited diagnostic value in patients with thoracic aortic aneurysm/dissection. Single-cell RNA sequencing-based findings further highlight PTPN22 expression in aortic immune cells and vascular smooth muscle cells (VSMCs) is consistently upregulated in patients with AAA. A cellular AAA model was eventually employed to verify the increase in PTPN22 expression. Collectively, the results indicate that PTPN22 could be a potentially useful diagnostic biomarker for AAA.

Comprehensive Analysis of N6-Methyladenosine (m6A) RNA Methylation Regulators and Tumour Microenvironment Cell Infiltration Involving Prognosis and Immunotherapy in Gastroesophageal Adenocarcinomas

Objective

Gastroesophageal adenocarcinoma (GEA) is a high deadly and heterogeneous cancer. RNA N6-methyladenosine (m6A) modification plays a non-negligible role in shaping individual tumour microenvironment (TME) characterizations. However, the landscape and relationship of m6A modification patterns and TME cell infiltration features remain unknown in GEA.

Methods

In this study, we examined the TME of GEA using assessments of the RNA-sequencing data focusing on the distinct m6A modification patterns from the public databases. Intrinsic patterns of m6A modification were evaluated for associations with clinicopathological characteristics, underlying biological pathways, tumour immune cell infiltration, oncological outcomes, and treatment responses. The expression of key m6A regulators and module genes was validated by qRT-PCR analysis.

Results

We identified two distinct m6A modification patterns of GEA (cluster 1/2 subgroup), and correlated two subgroups with TME cell-infiltrating characteristics. Cluster 2 subgroup correlates with a poorer prognosis, downregulated PD-1 expression, higher risk scores, and distinct immune cell infiltration. In addition, PPI and WGCNA network analysis were integrated to identify key module genes closely related to immune infiltration of GEA to find immunotherapy markers. COL4A1 and COL5A2 in the brown module were significantly correlated to the prognosis, PD-1/L1 and CTLA-4 expression of GEA patients. Finally, a prognostic risk score was constructed using m6A regulator-associated signatures that represented an independent prognosis factor for GEA. Interestingly, COL5A2 expression was linked to the response to anti-PD-1 immunotherapy, m6A regulator expression, and risk score.

Conclusion

Our work identified m6A RNA methylation regulators as an important class of players in the malignant progression of GEA and were associated with the complexity of the TME. COL5A2 may be the potential biomarker which contributes to predicting the response to anti-PD-1 immunotherapy and patients' prognosis.

Association of Elevated Expression Levels of COL4A1 in Stromal Cells with an Immunosuppressive Tumor Microenvironment in Low-Grade Glioma, Pancreatic Adenocarcinoma, Skin Cutaneous Melanoma, and Stomach Adenocarcinoma

Aberrant expression of collagen type IV alpha chain 1 (COL4A1) can influence tumor cell behavior. To examine the association of COL4A1 expression in the tumor microenvironment (TME) with tumor progression, we performed bioinformatics analyses of The Cancer Genome Atlas RNA sequencing and RNA microarray datasets available in public databases and identified upregulated COL4A1 expression in most examined tumor types compared to their normal counterparts. The elevated expression of COL4A1 was correlated with low survival rates of patients with low-grade glioma, pancreatic adenocarcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, thus suggesting its potential use as a biomarker for the poor prognosis of these tumors. However, COL4A1 was mostly expressed in adjacent stromal cells, such as cancer-associated fibroblasts (CAFs) and endothelial cells. Additionally, COL4A1 expression was highly correlated with the signatures of CAFs and endothelial cells in all four tumor types. The expression of marker genes for the infiltration of pro-tumoral immune cells, such as Treg, M2, and TAM, and those of immunosuppressive cytokines exhibited very strong positive correlations with COL4A1 expression. Collectively, our data suggest that COL4A1 overexpression in stromal cells may be a potential regulator of tumor-supporting TME composition associated with poor prognosis.

Identification of potential core genes in gastric cancer using bioinformatics analysis

Background

Gastric cancer is the third leading cause of cancer-related mortality in China. Most patients with gastric cancer have no obvious early symptoms; thus, many of them are in the middle and late stages of gastric cancer at first diagnosis and miss the best treatment opportunity. Molecular targeted therapy is particularly important in changing this status quo.

Methods

Three microarray datasets (GSE29272, GSE33651, and GSE54129) were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using GEO2R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to analyze the functional features of these DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape software. The expressions of hub genes were evaluated based on Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the online Kaplan-Meier plotter survival analysis tool to evaluate the prognostic values of hub genes. The Target Scan database was used to predict microRNAs that could regulate the target gene, collagen type IV alpha 1 chain (COL4A1). The OncomiR database was used to analyze the expression levels of three microRNAs, as well as the relationships with tumor stage, grade, and prognosis.

Results

We identified 78 DEGs, including 53 upregulated genes and 25 downregulated genes. The DEGs were mainly enriched in extracellular matrix organization, extracellular structure organization, and response to wounding. Moreover, three KEGG pathways were markedly enriched, including focal adhesion, complement and coagulation cascades, and extracellular matrix (ECM)-receptor interaction. Among these 78 genes, we selected 10 hub genes. The overexpression levels of these hub genes were closely related to poor prognosis and the development of gastric cancer (except for COL3A1, LOX, and CXCL8). Moreover, we found that microRNA-29a-3p, miR-29b-3p, and miR-29c-3p were the potential microRNAs that could regulate the target gene, COL4A1.

Conclusions

Our results showed that FN1, COL1A1, TIMP1, COL1A2, SPARC, COL4A1, and SERPINE1 could contribute to the development of novel molecular targets and biomarker-driven treatments for gastric cancer.

Network Pharmacology-Based Study on the Active Component and Mechanism of the Anti-Gastric-Cancer Effect of Herba Sarcandrae

Background

Herba Sarcandrae is used in the clinical practice of traditional Chinese medicine to deal with gastric cancer. However, there are few studies on its precise mechanism.

Method

In this study, a network pharmacological approach was utilized to construct a molecular/target/pathway molecular regulatory network for the anti-gastric-cancer effect of Herba Sarcandrae. The active components of Herba Sarcandrae and their potential mechanisms were explored. Chemical components of the Herba Sarcandrae were identified through a database, and they were evaluated and screened based on oral bioavailability and drug similarity.

Results

Genes related to gastric cancer were found in the Gene Expression Omnibus (GEO) database, and gene targets related to anti-gastric-cancer were chosen by comparison. Using annotation, visualization, and a comprehensive discovery database, the function and related pathways of target genes were analyzed and screened. Cytoscape software was utilized to construct a component/target/pathway network for the antitumor effect of Herba Sarcandrae. Finally, 6 drug ingredients and 29 target genes related to gastric cancer were detected. IL-17 signaling pathway, NF-kappa B signaling pathway, and other signaling pathways were significantly enriched. Many signaling pathways that directly act on tumors and indirect pathways inhibit the development of gastric cancer.

Conclusion

This study provides a scientific basis for further elucidating the mechanism of the anti-gastric-cancer effect of Herba Sarcandrae.

COL4A1, negatively regulated by XPD and miR-29a-3p, promotes cell proliferation, migration, invasion and epithelial-mesenchymal transition in liver cancer cells

OBJECTIVE

Collagen type IV alpha 1 (COL4A1) exerts tumor-promoting functions in several tumors. However, its role in liver cancer remains not fully understood. Hence, this study aims to investigate the role of COL4A1 in regulating liver cancer cell behaviors and to validate its upstream regulatory mechanism.

METHODS

Expression of xeroderma pigmentosum D (XPD) and COL4A1 was examined by qRT-PCR and western blot. Cell proliferation, migration, and invasion were evaluated. The protein levels of N-cadherin, vimentin, and E-cadherin were determined by western blot to evaluate epithelial-mesenchymal transition (EMT). The interaction between miR-29a-3p and COL4A1 was analyzed by luciferase reporter assay.

RESULTS

COL4A1 overexpression significantly promoted cell proliferation, migration, invasion, and EMT in Hep3B cells. In contrast, COL4A1 silencing yielded the opposite effects in HepG2 cells. Expression of COL4A1 was increased, whereas expression of XPD and miR-29a-3p was decreased in HCC tissues compared to controls. COL4A1 mRNA level was negatively correlated with expression of XPD and miR-29a-3p in HCC tissues. Furthermore, XPD silencing-mediated up-regulation of COL4A1 expression was attenuated by miR-29a-3p mimic. Moreover, miR-29a-3p mimic inhibited Hep3B cell proliferation, migration, and invasion by directly targeting COL4A1.

CONCLUSION

COL4A1 is negatively regulated by XPD-miR-29a-3p axis and promotes liver cancer progression in vitro.

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.

High expression of TREM2 promotes EMT via the PI3K/AKT pathway in gastric cancer: bioinformatics analysis and experimental verification

Background: To date, the pathogenesis of gastric cancer (GC) remains unclear. We combined public database resources and bioinformatics analysis methods, explored some novel genes and verified the experiments to further understand the pathogenesis of GC and to provide a promising target for anti-tumor therapy. Methods: We downloaded the chip data related to GC from the Gene Expression Omnibus (GEO) database, extracted differentially expressed genes (DEGs), and then determined the key genes in the development of GC via PPI networks and model analysis. Functional annotation via GO and KEGG enrichment of DEGs was used to understand the latent roles of DEGs. The expression of the triggering receptor expressed on myeloid cells 2 (TREM2) gene in GC cell lines was verified via RT-PCR and western blotting. Moreover, the CCK-8, wound healing assay, and transwell migration and invasion assays were used to understand the changes in the proliferation, migration, and invasion abilities of GC cells after silencing TREM2. Western blotting verified the interaction between TREM2 and PI3K predict of the string website, as well as the effect of TREM2 on EMT. Finally, a lung metastasis model was used to explore the relationship between TREM2 and metastasis. Results: Our study identified 16 key genes, namely BGN, COL1A1, COL4A1, COL5A2, NOX4, SPARC, HEYL, SPP1, TIMP1, CTHRC1, TREM2, SFRP4, FBXO32, GPX3, KIF4A, and MMP9 genes associated with GC. The EMT-related pathway was the most significantly altered pathway. TREM2 expression was higher in GC cell lines and was remarkably associated with tumor invasion depth, TNM stage, histological grade, histological type, anatomic subdivision, and Helicobacter pylori state. Knockdown of TREM2 expression inhibited the proliferation, migration, and invasion of GC cells as well as the progression of EMT by PI3K/AKT signaling in vitro. In addition, lung metastasis were decreased in vivo. Conclusions: We identified some important genes associated with the progression of GC via public database analysis, explored and verified the effects of proto-oncogene TREM2 on EMT via the PI3K/AKT pathway. TREM2 may be a novel target in the GC therapy.

Molecular Mechanism of Resistance to Chemotherapy in Gastric Cancers, the Role of Autophagy

Gastric cancer (GC) is biologically and genetically heterogeneous with complex carcinogenesis at the molecular level. Despite the application of multiple approaches in the GC treatment, its 5-year survival is poor. A major limitation of anti-cancer drugs application is intrinsic or acquired resistance, especially to chemotherapeutical agents. It is known that the effectiveness of chemotherapy remains debatable and varies according to the molecular type of GC. Chemotherapy has an established role in the management of GC. Perioperative chemotherapy or postoperative chemotherapy is applied for localized ones. Most of the advanced GC patients have a poor response to treatment and unfavorable outcomes with standard therapies. Resistance substantially limits the depth and duration of clinical responses to targeted anticancer therapies. Through the use of complementary experimental approaches, investigators have revealed that cancer cells can achieve resistance through adaptation or selection driven by specific genetic, epigenetic, or microenvironmental alterations. Ultimately, these diverse alterations often lead to the activation of MAPK, AKT/mTOR, and Wnt/β-catenin signaling pathways that, when co-opted, enable cancer cells to survive drug treatments. We have summarized the mechanisms of resistance development to cisplatin, 5-fluorouracil, and multidrug resistance in the GC management. The complexity of molecular targets and components of signaling cascades altered in the resistance development results in the absence of significant benefits in GC treatment, and its efficacy remains low. The universal process responsible for the failure in the multimodal approach in GC treatment is autophagy. Its dual role in oncogenesis is the most unexplored issue. We have discussed the possible mechanism of autophagy regulation upon the action of endogenous factors and drugs. The experimental data obtained in the cultured GC cells need further verification. To overcome the cancer resistance and to prevent autophagy as the main reason of ineffective treatment, it is suggested the concept of the direct influence of autophagy molecular markers followed by the standard chemotherapy. Dozen of studies have focused on finding the rationale for the benefits of such complex therapy. The perspectives in the molecular-based management of GC are associated with the development of molecular markers predicting the protective autophagy initiation and search for novel targets of effective anticancer therapy.

Overexpression of GSE1 Related to Trastuzumab Resistance in Gastric Cancer Cells

Gastric cancer is one of the most prevalent human cancers with poor prognosis. Trastuzumab is a well-used targeted drug for gastric cancer with HER2 amplification. Trastuzumab resistance restrains the clinical use of trastuzumab. In this study, we reported human Gse1 coiled-coil protein (GSE1) promoted trastuzumab resistance in HER2-positive gastric cancer cells. Acquired trastuzumab-resistant gastric cancer cells overexpressed GSE1, and depletion of GSE1 decreased the trastuzumab resistance of trastuzumab-resistant gastric cancer cells. BCL-2 was a downstream gene positively regulated by GSE1 and also performed promoting the role of trastuzumab resistance in HER2-positive gastric cancer cells. A high level of GSE1 was associated with a high risk of tumor lymph node metastasis and higher clinical stage in HER2-positive gastric cancer patients. GSE1 was a potential target that could be used for HER2-positive gastric cancer therapy.

COL4A family: potential prognostic biomarkers and therapeutic targets for gastric cancer

Background

The type IV collagen alpha chain (COL4A) family is a major component of the basement membrane (BM) that has recently been found to be involved in tumor angiogenesis and progression. However, the expression levels and the exact roles of distinct COL4A family members in gastric cancer (GC) have not been completely understood.

Methods

Here, the expression levels of COL4As in GC and normal gastric tissues were calculated by using TCGA datasets and the predicted prognostic values by the GEPIA tool. Furthermore, the cBioPortal and Metascape tools were integrated to analyze the genetic alterations, correlations and potential functions of COL4As, and their frequently altered neighboring genes in GC.

Results

Notably, the expression levels of COL4A1/2/4 in GC were higher to those in normal gastric tissues, while the expression levels of COL4A3/5/6 were lower in GC than normal. Survival analysis revealed that lower expression levels of COL4A1/5 led to higher overall survival (OS) rate. Multivariate analysis using the Cox proportional-hazards model indicated that age, gender, pathological grade, metastasis and COL4A5 expression, are independent prognostic factors for OS. However, TNM stage, lymph node metastasis, Lauren’s classification, COL4A1-4 and COL4A6 were associated with poor OS but not independent prognostic factors. Function-enriched analysis of COL4As and their frequently altered neighboring genes was involved in tumor proliferation and metastasis in GC.

Conclusions

These results implied that COL4A1/2 were potential therapeutic targets for GC. COL4A3/4/6 might have an impact on gastric carcinogenesis and subsequent progression, whereas COL4A5 was an independent prognostic marker for GC.

Bioinformatics Analysis of Key Genes and circRNA-miRNA-mRNA Regulatory Network in Gastric Cancer

Gastric cancer (GC) is one of the most common malignancies in the world, with morbidity and mortality ranking second among all cancers. Accumulating evidences indicate that circular RNAs (circRNAs) are closely correlated with tumorigenesis. However, the mechanisms of circRNAs still remain unclear. This study is aimed at determining hub genes and circRNAs and analyzing their potential biological functions in GC. Expression profiles of mRNAs and circRNAs were downloaded from the Gene Expression Omnibus (GEO) data sets of GC and paracancer tissues. Differentially expressed genes (DEGs) and differentially expressed circRNAs (DE-circRNAs) were identified. The target miRNAs of DE-circRNAs and the bidirectional interaction between target miRNAs and DEGs were predicted. Functional analysis was performed, and the protein-protein interaction (PPI) network and the circRNA-miRNA-mRNA network were established. A total of 456 DEGs and 2 DE-circRNAs were identified with 3 mRNA expression profiles and 2 circRNA expression profiles. GO analysis indicated that DEGs were mainly enriched in extracellular matrix and cell adhesion, and KEGG confirmed that DEGs were mainly associated with focal adhesion, the PI3K-Akt signaling pathway, extracellular matrix- (ECM)- receptor interaction, and gastric acid secretion. 15 hub DEGs (BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, UBE2C, CCNB1, CD44, CXCL8, COL3A1, COL5A2, and THBS1) were identified from the PPI network. Furthermore, the survival analysis indicate that GC patients with a high expression of the following 9 hub DEGs, namely, BGN, COL1A1, COL1A2, FBN1, FN1, SPARC, SPP1, TIMP1, and UBE2C, had significantly worse overall survival. The circRNA-miRNA-mRNA network was constructed based on 1 circRNA, 15 miRNAs, and 45 DEGs. In addition, the 45 DEGs included 5 hub DEGs. These results suggested that hub DEGs and circRNAs could be implicated in the pathogenesis and development of GC. Our findings provide novel evidence on the circRNA-miRNA-mRNA network and lay the foundation for future research of circRNAs in GC.

Comprehensive Analysis of a circRNA-miRNA-mRNA Network to Reveal Potential Inflammation-Related Targets for Gastric Adenocarcinoma

Gastric cancer (GC) is the most common malignancy of the stomach. This study was aimed at elucidating the regulatory network of circRNA-miRNA-mRNA and identifying the precise inflammation-related targets in GC. The expression profiles of GSE83521, GSE78091, and GSE33651 were obtained from the GEO database. Interactions between miRNAs and circRNAs were investigated by the Circular RNA Interactome, and targets of miRNAs were predicted with miRTarBase. Then, a circRNA/miRNA/mRNA regulatory network was constructed. Also, functional enrichment analysis of selected differentially expressed genes (DEGs) was performed. The inflammation-/GC-related targets were collected in the GeneCards and GenLiP3 database, respectively. And a protein-protein interaction (PPI) network of DE mRNAs was constructed with STRING and Cytoscape to identify hub genes. The genetic alterations, neighboring gene networks, expression levels, and the poor prognosis of hub genes were investigated in cBioPortal, Oncomine, and Human Protein Atlas databases and Kaplan-Meier plotter, respectively. A total of 10 DE miRNAs and 33 DEGs were identified. The regulatory network contained 26 circRNAs, 10 miRNAs, and 1459 mRNAs. Functional enrichment analysis revealed that the selected 33 DEGs were involved in negative regulation of fat cell differentiation, response to wounding, extracellular matrix- (ECM-) receptor interaction, and regulation of cell growth pathways. THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were selected as inflammation-related hub genes of GC in the PPI network. The genetic alterations in these hub genes were related to amplification and missense mutations. Furthermore, the genes RYR2, ERBB2, PI3KCA, and HELZ2 were connected to hub genes in this study. The hub gene levels in clinical specimens were markedly upregulated in GC tissues and correlated with poor overall survival (OS). Our results suggest that THBS1, FN1, CALM1, COL4A1, CTGF, and IGFBP5 were associated with the pathogenesis of gastric carcinogenesis and may serve as biomarkers and inflammation-related targets for GC.

hsa_circ_0000520 influences herceptin resistance in gastric cancer cells through PI3K-Akt signaling pathway

Background

To investigate whether hsa_circ_0000520 affects Herceptin resistance in gastric cancer by regulating the PI3K‐AKT signaling.

Methods

The expression of hsa_circ_0000520 was detected by qRT‐PCR in gastric cancer tissues and cell lines. A Herceptin‐resistant gastric cancer cell was established. PcDNA and pcDNA‐hsa_circ_0000520 were transfected into NCI‐N87R cells and treated with Herceptin at a concentration of 10 μg/mL for 24 hours. MTT tested cell proliferation, and apoptosis was measured by flow cytometry. IGF‐1 treatment was used to activate PI3K‐Akt signaling. The expression levels of related proteins were detected.

Results

The expression of hsa_circ_0000520 was reduced in gastric cancer tissues and cell lines, and hsa_circ_0000520 in NCI‐N87R cells was significantly lower than that of NCI‐N87 cells. Compared with the CON group, the cell viability of the Herceptin group was significantly reduced, the apoptosis rate was significantly increased, the level of Bax protein was significantly increased, and the levels of Bcl‐2, p‐PI3K, and p‐Akt protein were significantly reduced. Compared with the Herceptin + pcDNA group, the cell viability of the Herceptin + hsa_circ_0000520 group was significantly reduced, the apoptosis rate was significantly increased, the level of Bax protein was significantly increased, and the levels of p‐PI3K and p‐Akt proteins were significantly reduced. After IGF‐1 treatment, the cell viability was significantly increased, the apoptosis rate was significantly reduced, the level of Bax protein was significantly reduced, and the level of Bcl‐2 protein was significantly increased.

Conclusion

Hsa_circ_0000520 overexpression may reverse the Herceptin resistance of gastric cancer cells by inhibiting the PI3K‐Akt signaling pathway.

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

Background

Gastric cancer is one of the most common malignant cancers worldwide. Despite substantial developments in therapeutic strategies, the five-year survival rate remains low. Therefore, novel biomarkers and therapeutic targets involved in the progression of gastric tumors need to be identified.

Methods

We obtained the mRNA microarray datasets GSE65801, GSE54129 and GSE79973 from the Gene Expression Omnibus database to acquire differentially expressed genes (DEGs). We used the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to analyze DEG pathways and functions, and the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape to obtain the protein-protein interaction (PPI) network. Next, we validated the hub gene expression levels using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA), and conducted stage expression and survival analysis.

Results

From the three microarray datasets, we identified nine major hub genes: COL1A1, COL1A2, COL3A1, COL5A2, COL4A1, FN1, COL5A1, COL4A2, and COL6A3.

Conclusion

Our study identified COL1A1 and COL1A2 as potential gastric cancer prognostic biomarkers.

TIMP1 Is A Potential Key Gene Associated With The Pathogenesis And Prognosis Of Ulcerative Colitis-Associated Colorectal Cancer

Purpose

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide. As a high-risk factor for CRC, ulcerative colitis (UC) has been demonstrated to lead to epithelial dysplasia, DNA damage, and eventually cancer. There are approximately 18% of patients with UC may develop CRC.

Patients and methods

The gene expression profiles were retrieved from the Gene Expression Omnibus. The Database for Annotation, Visualization and Integrated Discovery was employed to conduct gene annotations. Protein-protein interaction network was constructed by the Search Tool for the Retrieval of Interacting Genes, and further analysed by the Molecular Complex Detection. The correlation between TIMP1 and prognosis was evaluated by the Gene Expression Profiling Interactive Analysis. To predict the potential functions of TIMP1, the GeneMANIA, Coremine, and FunRich were employed. After transfection with small interfering RNA targeting TIMP1, cell proliferation, migration, and apoptosis were determined by CCK-8, scratch wound, and Annexin V-FITC/PI assays, respectively.

Results

TIMP1, consistently overexpressed in the initiation and progression of UC-associated CRC (ucaCRC), was identified to be a potential biomarker for the prognosis of patients with CRC. Experimental results showed knockdown of TIMP1 could increase the migration, while did not affect the proliferation and apoptosis of RKO cells. The role of TIMP1 in the malignant transformation of ucaCRC was confirmed by using the protein/gene interactions and biological process annotation and validated by analysing the transcription factors targeting TIMP1.

Conclusion

TIMP1 is consistently upregulated in the pathological process of ucaCRC and can be a potential biomarker for the worse prognosis of CRC.

Role of microRNAs in drug resistance of gastric cancer cells

Drug therapy is an important component of comprehensive treatments for gastric cancer (GC), but drug resistance of cancer cells often leads to treatment failure. It is significant to explore the drug resistance mechanism of GC cells. It has been reported that microRNAs (miRNAs) are closely related to drug resistance in GC. However, there are many kinds of microRNAs, which possess complex mechanisms and are not widely applied in clinical patients, so there are still many areas to be investigated about the relationship between microRNAs and drug resistance in GC. In this review, we review the role of miRNAs in the formation of drug resistance and discuss the existing problems and future directions.

A panel of collagen genes are associated with prognosis of patients with gastric cancer and regulated by microRNA-29c-3p: an integrated bioinformatics analysis and experimental validation

Background: The systematic expression characteristics and functions of collagen genes in gastric cancer (GC) have not been reported. Through public data integration, combined with bioinformatics analysis, we identified a panel of collagen genes overexpressed in GC. The functions of these genes were analyzed and validated in a GC-related cohort. microRNAs that may potentially target such genes were investigated in vitro. Methods: Four GC-related datasets retrieved from the Gene Expression Omnibus (GEO) were used to extract differentially expressed genes (DEGs) in GC. Functional annotation was performed to identify the potential roles of the identified DEGs. The association of candidate genes involved in the prognosis of GC patients (n=876) was determined using data provided by the Kaplan-Meier-plotter database, The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) repository, and a GC-related dataset (GSE15459). The expression characteristics of candidate genes and their associations with clinical parameters were validated in our in-house cohort (n=58). MicroRNAs able to target the identified candidate genes were predicted and confirmed using qRT-PCR, Western blotting, and dual-luciferase reporter assays in vitro. Results: After the integration of four GEO datasets, 76 DEGs were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that these DEGs were significantly enriched in ECM-related functions and pathways. A group of collagen genes was significantly upregulated in the GC tissues and constituted a protein-protein interaction network as important nodes. Some of these collagen genes were closely associated with poor prognosis in GC patients. Overexpression of COL1A1 and COL4A1 was confirmed in our in-house cohort, and this was related to prognosis and certain clinicopathological parameters. We found that microRNA-29c-3p could directly target COL1A1 and COL4A1 in BGC-823 cells. Conclusions: Collagen genes identified in this study were associated with patient prognosis in GC and may represent diagnostic markers or potential therapeutic targets. Aberrant expression of such candidate genes may be induced by microRNA-29c-3p.

Computational Drug Repositioning for Gastric Cancer using Reversal Gene Expression Profiles

Treatment of gastric cancer (GC) often produces poor outcomes. Moreover, predicting which GC treatments will be effective remains challenging. Computational drug repositioning using public databases is a promising and efficient tool for discovering new uses for existing drugs. Here we used a computational reversal of gene expression approach based on effects on gene expression signatures by GC disease and drugs to explore new GC drug candidates. Gene expression profiles for individual GC tumoral and normal gastric tissue samples were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in GC were determined with a meta-signature analysis. Profiles drug activity and drug-induced gene expression were downloaded from the ChEMBL and the LINCS databases, respectively. Candidate drugs to treat GC were predicted using reversal gene expression score (RGES). Drug candidates including sorafenib, olaparib, elesclomol, tanespimycin, selumetinib, and ponatinib were predicted to be active for treatment of GC. Meanwhile, GC-related genes such as PLOD3, COL4A1, UBE2C, MIF, and PRPF5 were identified as having gene expression profiles that can be reversed by drugs. These findings support the use of a computational reversal gene expression approach to identify new drug candidates that can be used to treat GC.

In silico analyses for potential key genes associated with gastric cancer

BACKGROUND

Understanding hub genes involved in gastric cancer (GC) metastasis could lead to effective approaches to diagnose and treat cancer. In this study, we aim to identify the hub genes and investigate the underlying molecular mechanisms of GC.

METHODS

To explore potential therapeutic targets for GC,three expression profiles (GSE54129, GSE33651, GSE81948) of the genes were extracted from the Gene Expression Omnibus (GEO) database. The GEO2R online tool was applied to screen out differentially expressed genes (DEGs) between GC and normal gastric samples. Database for Annotation, Visualization and Integrated Discovery was applied to perform Gene Ontology (GO) and KEGG pathway enrichment analysis. The protein-protein interaction (PPI) network of these DEGs was constructed using a STRING online software. The hub genes were identified by the CytoHubba plugin of Cytoscape software. Then, the prognostic value of these identified genes was verified by gastric cancer database derived from Kaplan-Meier plotter platform.

RESULTS

A total of 85 overlapped upregulated genes and 44 downregulated genes were identified. The majority of the DEGs were enriched in extracellular matrix organization, endodermal cell differentiation, and endoderm formation. Moreover, five KEGG pathways were significantly enriched, including ECM-receptor interaction, amoebiasis, AGE-RAGE signaling pathway in diabetic complications, focal adhesion, protein digestion and absorption. By combining the results of PPI network and CytoHubba, a total of nine hub genes including COL1A1, THBS1, MMP2, CXCL8, FN1, TIMP1, SPARC, COL4A1, and ITGA5 were selected. The Kaplan-Meier plotter database confirmed that overexpression levels of these genes were associated with reduced overall survival, except for THBS1 and CXCL8.

CONCLUSIONS

Our study suggests that COL1A1, MMP2, FN1, TIMP1, SPARC, COL4A1, and ITGA5 may be potential biomarkers and therapeutic targets for GC. Further study is needed to assess the effect of THBS1 and CXCL8 on GC.

Prediction of key genes and pathways involved in trastuzumab-resistant gastric cancer

Background

Trastuzumab has been prevailingly accepted as a beneficial treatment for gastric cancer (GC) by targeting human epidermal growth factor receptor 2 (HER2)-positive. However, the therapeutic resistance of trastuzumab remains a major obstacle, restricting the therapeutic efficacy. Therefore, identifying potential key genes and pathways is crucial to maximize the overall clinical benefits.

Methods

The gene expression profile GSE77346 was retrieved to identify the differentially expressed genes (DEGs) associated with the trastuzumab resistance in GC. Next, the DEGs were annotated by the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The DEGs-coded protein-protein interaction (PPI) networks and the prognostic values of the 20 hub genes were determined. Correlation of the hub genes were analyzed in The Cancer Genome Atlas. The prognostic values of hub genes were further validated by Kaplan-Meier (KM) plotter.

Results

A total of 849 DEGs were identified, with 374 in upregulation and 475 in downregulation. Epithelium development was the most significantly enriched term in biological processes while membrane-bounded vesicle was in cellular compartments and cell adhesion molecular binding was in molecular functions. Pathways in cancer and ECM-receptor interaction were the most significantly enriched for all DEGs. Among the PPI networks, 20 hub genes were defined, including CD44 molecule (CD44), HER-2, and cadherin 1 (CDH1). Six hub genes were associated with favorable OS while eight were associated with poor OS. Mechanistically, 2′-5′-oligoadenylate synthetase 1, 3 (OAS1, OAS3) and CDH1 featured high degrees and strong correlations with other hub genes.

Conclusions

This bioinformatics analysis identified key genes and pathways for potential targets and survival predictors for trastuzumab treatment in GC.

Electronic supplementary material

The online version of this article (10.1186/s12957-018-1475-6) contains supplementary material, which is available to authorized users.