col3a1 biomarker (Human Protein Atlas)
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Col3a1 Biomarker, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer
Journal: Cancers
doi: 10.3390/cancers14143358
Figure Legend Snippet: Hub genes as obtained from cytoHubba and MCODE plugins of Cytoscape.
Techniques Used:
Figure Legend Snippet: The key hub genes of our study are defined as the intersection of hub genes between PPI network analysis and WGCNA.
Techniques Used:
Figure Legend Snippet: Univariate Cox regression analysis of the survival-associated hub genes in BCa patients (HR: hazard ratio, CI: confidence interval, * p -value < 0.05, ** p -value < 0.01, *** p -value < 0.001, **** p -value < 0.0001).
Techniques Used:
Figure Legend Snippet: The gene expression level analysis of the ANXA5 and COL3A1 in BCa patients for non-papillary and papillary subtypes, generated using the GEPIA2 platform. The red boxes represent the mRNA expression levels in BCa subtype tissues and the gray boxes represent the expression levels in control bladder tissues from patients of the TCGA-BCa and GTEx cohorts. * indicates statistical significance applying p -value < 0.05 and |log 2 FC| < 1 as cut-off criteria (TPM: transcript count per million).
Techniques Used: Gene Expression, Generated, Expressing, Control
Figure Legend Snippet: The highlights of this study at a glance.
Techniques Used: Microarray, Clinical Proteomics, Diagnostic Assay
Related Articles
Microarray:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Protein-Protein interactions:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Clinical Proteomics:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Diagnostic Assay:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Gene Expression:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Generated:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Expressing:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using Control:Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer Article Snippet: The analysis of the merged microarray meta-dataset, comprising of 410 BCa and 196 healthy urinary bladder tissue samples from 18 independent datasets, revealed 815 robust differentially expressed genes (DEGs). A total of 61 key hub genes resulted from DEG-based protein–protein interaction (PPI) and weighted gene co-expression (WGCNA) network analyses. A subset of key hub genes, namely AURKB , CCNB2 , CDC45 , CDCA8 , CDT1 , CENPU , COL3A1 , GINS2 , KIF20A , MCM4 , PBK , PLK4 , SDC1 , SPP1 , TOP2A , TTK , and UBE2C , were found to be differentially expressed in the urine of BCa patients. A subset of key hub genes, namely ANXA5 , ASPM , CD34 , CDC20 , CDT1 , COL4A5 , COL6A1 , ECT2 , HJURP , MCM2 , and VEGFA , were found to be differentially expressed in the blood plasma of BCa patients. Bioinformatics tools and machine learning techniques were utilized to reveal and assess the diagnostic, prognostic, and predictive value of the identified key hub genes. A three-gene signature prognostic model for BCa patients, including COL3A1 , FOXM1 , and PLK4 , was built and demonstrated high performance. A six-gene signature predictive model regarding MIBC patients’ response to neoadjuvant chemotherapy, including ANXA5 , CD44 , NCAM1 , SPP1 , CDCA8 , and KIF14 , was developed and showed satisfactory performance. Overall, nine genes, namely ANXA5 , CDT1 , COL3A1 , SPP1 , VEGFA , CDCA8 , HJURP , TOP2A , and COL6A1 , were identified as potential prognostic and therapeutic target biomarkers for BCa, they were immunohistochemically validated using |