Extracellular Matrix–receptor Interaction Signaling Genes Associated with Inferior Breast Cancer Survival

Yeh, Ming-Hsin; Tzeng, Yau-Jin; Fu, Ting‐Ying; You, Jinmao; Chang, Hong‐Tai; Ger, Luo‐Ping

doi:10.21873/anticanres.12764

Cited by 52 publications

(43 citation statements)

References 29 publications

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“…Therefore, CCND1 may be an attractive therapeutic target in cancer. The FOXJ1 gene was o verexpressed in the anaplastic ependymoma cases in our study and has been reported to have the highest levels in posterior fossa ependymoma group B tumors [22]. The highly expressed genes in this research, such as BOC, PRC1, RFX2, FOSL1, EPHA2, and IGF2BP1, were reported as potential therapeutic molecular targets of ependymoma [23].…”

Section: Methodssupporting

confidence: 60%

The potentially therapeutic targets of pediatric anaplastic ependymoma by transcriptome profiling

Wang

Sun

Liu

et al. 2021

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Ependymoma (EPN) is a type of tumor that occurs in the central nervous system of children and adults. EPN produces resistance to chemotherapy, and there are no targeted drugs available for a proper cure. Therefore, the use of high-throughput sequencing technologies to elucidate pathogenic mechanisms is of prime importance to identify potential tumor target genes helpful for developing effective therapeutic approaches against EPN. With this objective, we used RNA-seq analysis to identify differentially expressed genes (DEGs) and pathways in 4 pairs of EPN tissues and adjacent tissues. In total, we found 5445 differentially expressed genes. The synaptic vesicle cycle and extracellular matrix (ECM) receptor interaction pathways were highly enriched in the ependymoma group. Nine differentially expressed genes (SNAP25, GRM4, CELSR1, LAMA1, WNT5A, ROR2, CCND1, EPHB2, FOXJ1) were randomly verified by RT-qPCR, supporting the authenticity of our sequencing results. This study provides global gene information and some new potential biomarkers for the diagnosis and therapeutic targets of ependymoma.

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Section: Methodssupporting

confidence: 60%

The potentially therapeutic targets of pediatric anaplastic ependymoma by transcriptome profiling

Wang

Sun

Liu

et al. 2021

neo

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“…The extracellular matrix (ECM), composed of polysaccharides and brous proteins, is an important structural component of the tumor microenvironment. Previous studies have shown that dysregulation of the extracellular matrixreceptor interaction signaling pathway plays a vital role in regulating tumor invasion and metastasis [30] . Not only that, focal adhesion (FA) promotes cell traction by associating the ECM bound to the transmembrane integrin molecule with the actin cytoskeleton, which also plays an important role in cell migration dynamics [31,32] .…”

Section: Discussionmentioning

confidence: 99%

Identification of key biomarkers and functional pathways in osteosarcomas with lung metastasis: Evidence from bioinformatics analysis

Liu

Zhou

2020

Preprint

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Background: In osteosarcoma, the lung is the most common metastatic organ. Intensive work has been made to illuminate the pathogeny, but the specific metastatic mechanism remains unclear. Thus, we conducted the study to seek to find the key genes and critical functional pathways associated with progression and treatment in osteosarcoma with lung metastasis.Methods: Two independent datasets (GSE14359 and GSE85537) were screened out from the Gene Expression Omnibus (GEO) database and the overlapping differentially expressed genes (DEGs) were identified using GEO2R online platform. Subsequently, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted using DAVID. Meanwhile, the protein-protein interaction (PPI) network constructed by STRING was visualized using Cytoscape. Afterwards, the key module and hub genes were extracted from the PPI network using the MCODE and cytoHubba plugin. Moreover, the raw data obtained from GSE73166 and GSE21257 was applied to verify the expression differences and conduct the survival analyses of hub genes, respectively. Finally, the interaction network of miRNAs and hub genes constructed by ENCORI was visualized using Cytoscape.Results: A total of 364 DEGs were identified, comprising 96 downregulated genes and 268 upregulated genes, which were mainly involved in cancer-associated pathways, adherens junction, ECM-receptor interaction, focal adhesion, MAPK signaling pathway. Subsequently, 10 hub genes were obtained and survival analysis demonstrated SKP2 and ASPM were closely related to poor prognosis of patients with osteosarcoma. Finally, hsa-miR-340-5p were found to be most closely associated with these hub genes according to the interaction network of miRNAs and hub genes.Conclusion: The key genes and functional pathways identified in the study may contribute to understanding the molecular mechanisms involved in the carcinogenesis and progression of osteosarcoma with lung metastasis, and provide potential diagnostic and therapeutic targets.

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“…As shown in Fig. 2B, KEGG pathway enrichment analysis found twelve signi cantly enriched pathways related to cancer progression, such as PI3K-Akt signaling pathway [23,24], ECM-receptor interaction [25,26] and p53 signaling pathway [27,28]. The results indicated that these DEGs played key roles in multiple cancer-related pathways, and further indicated that the DMSs might be involved in LUAD progression by regulating the corresponding gene expression.…”

Section: Functional Enrichment Of Dmgsmentioning

confidence: 84%

A Methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

Wang

Zhou

Xia

et al. 2020

Preprint

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Background DNA methylation alteration is frequently observed in Lung adenocarcinoma (LUAD) and may play important roles in carcinogenesis, diagnosis, and prognosis. Thus, this study aimed to construct a reliable methylation-based nomogram, guiding prognostic classification screening and personalized medicine for LUAD patients. Method: The DNA methylation data, gene expression data and corresponding clinical information of lung adenocarcinoma samples were extracted from The Cancer Genome Atlas (TCGA) database. Differentially methylated sites (DMSs) and differentially expressed genes (DEGs) were obtained and then calculated expression correlation by pearson correlation coefficient. Functional enrichment analysis and Protein-protein interaction network were used to explore the biological roles of aberrant methylation genes. A prognostic risk score model was constructed using univariate Cox and LASSO analysis and was assessed in an independent cohort. A methylation-based nomogram that included the risk score and the clinical risk factors was developed, which was evaluated by concordance index and calibration curves. Result We identified a total of 1362 DMSs corresponding to 471 DEGs with significant negative correlation, including 752 hypermethylation sites and 610 hypomethylation sites. Univariate cox regression analysis showed that 59 DMSs were significantly associated with overall survival. Using LASSO method, we constructed a three-DMSs signature that was independent predictive of prognosis in the training cohort. Patients in high-risk group had a significant shorter overall survival than patients in low-risk group classified by three-DMSs signature (log-rank p = 1.9E-04). Multivariate cox regression analysis proved that the three-DMSs signature was an independent prognostic factor for LUAD in TCGA-LUAD cohort (HR = 2.29, 95%CI: 1.47–3.57, P = 2.36E-04) and GSE56044 cohort (HR = 2.16, 95%CI: 1.19–3.91, P = 0.011). Furthermore, a nomogram, combining the risk score with clinical risk factors, was developed with C-indexes of 0.71 and 0.70 in TCGA-LUAD and GSE56044 respectively. Conclusions The present study established a robust three-DMSs signature for the prediction of overall survival and further developed a nomogram that could be a clinically available guide for personalized treatment of LUAD patients.

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Extracellular Matrix–receptor Interaction Signaling Genes Associated with Inferior Breast Cancer Survival

Abstract: These findings suggest that HMMR and SDC1 involved in the ECM-receptor interaction signaling pathway could act as effective independent prognostic biomarkers for breast ductal carcinoma.

Cited by 52 publications

References 29 publications

The potentially therapeutic targets of pediatric anaplastic ependymoma by transcriptome profiling

The potentially therapeutic targets of pediatric anaplastic ependymoma by transcriptome profiling

Identification of key biomarkers and functional pathways in osteosarcomas with lung metastasis: Evidence from bioinformatics analysis

A Methylation-based nomogram for predicting survival in patients with lung adenocarcinoma

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