Journal: Frontiers in Immunology

Article Title: Inflammasome signaling proteins as biomarkers of COVID-19

doi: 10.3389/fimmu.2023.1014665

Figure Lengend Snippet: ROC of Inflammasome Biomarkers of active COVID-19 infection. ROC and AUC were calculated for each inflammasome signaling protein in the plasma of patients with an active COVID-19 infection (Positive) and healthy controls who never had a COVID-19 infection (Control). (A) Caspase-1: N: Control: 47, Positive: 29; (B) ASC: N: Control: 47, Positive: 29; (C) IL-1β: N: Control: 47, Positive: 29; and (D) IL-18: N: Control: 47, Positive: 29.

Article Snippet: JR and RWK are co-founders and managing members of InflamaCORE, LLC and have licensed patents on inflammasome proteins as biomarkers of injury and disease as well as on targeting inflammasome proteins for therapeutic purposes.

Techniques: Infection, Clinical Proteomics, Control

Journal: Frontiers in Immunology

Article Title: Inflammasome signaling proteins as biomarkers of COVID-19

doi: 10.3389/fimmu.2023.1014665

Figure Lengend Snippet: ROC of Inflammasome Biomarkers after recovery from COVID-19. ROC and AUC were calculated for each inflammasome signaling protein in the plasma of patients who recovered from an active COVID-19 infection (Positive) and healthy controls who never had a COVID-19 infection (Control). (A) Caspase-1: N: Control: 47, Recovered: 15; (B) ASC: N: Control: 47, Recovered: 16.

Article Snippet: JR and RWK are co-founders and managing members of InflamaCORE, LLC and have licensed patents on inflammasome proteins as biomarkers of injury and disease as well as on targeting inflammasome proteins for therapeutic purposes.

Techniques: Clinical Proteomics, Infection, Control

Journal: Frontiers in Immunology

Article Title: Inflammasome signaling proteins as biomarkers of COVID-19

doi: 10.3389/fimmu.2023.1014665

Figure Lengend Snippet: ROC Comparison among Inflammasome Biomarkers in COVID-19. (A) Correlation matrix using a Spearman correlation among biomarkers. (B) p-values of significance for the comparison among the biomarkers caspase-1, ASC, IL-1β and IL-18.

Article Snippet: JR and RWK are co-founders and managing members of InflamaCORE, LLC and have licensed patents on inflammasome proteins as biomarkers of injury and disease as well as on targeting inflammasome proteins for therapeutic purposes.

Techniques: Comparison

Journal: Cancers

Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

doi: 10.3390/cancers14143358

Figure Lengend Snippet: Hub genes as obtained from cytoHubba and MCODE plugins of Cytoscape.

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 Human Protein Atlas (HPA), and were bibliographically analyzed..

Techniques:

Journal: Cancers

Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

doi: 10.3390/cancers14143358

Figure Lengend Snippet: The key hub genes of our study are defined as the intersection of hub genes between PPI network analysis and WGCNA.

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 Human Protein Atlas (HPA), and were bibliographically analyzed..

Techniques:

Journal: Cancers

Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

doi: 10.3390/cancers14143358

Figure Lengend 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).

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 Human Protein Atlas (HPA), and were bibliographically analyzed..

Techniques:

Journal: Cancers

Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

doi: 10.3390/cancers14143358

Figure Lengend 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).

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 Human Protein Atlas (HPA), and were bibliographically analyzed..

Techniques: Gene Expression, Generated, Expressing, Control

Journal: Cancers

Article Title: An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer

doi: 10.3390/cancers14143358

Figure Lengend Snippet: The highlights of this study at a glance.

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 Human Protein Atlas (HPA), and were bibliographically analyzed..

Techniques: Microarray, Clinical Proteomics, Diagnostic Assay