A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that “ECM-receptor interaction”, “PI3K-Akt signaling pathway”, and “focal adhesion” are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.

In biotechnology, SAMs and NC hydrogels of functional nanomaterials are of high interest as 2D and 3D cell culture systems, respectively, to mimic natural ECM and to control cell behaviors. Advanced biotechnological approaches often use nanoscale topography together with suitable surface functionalization, as a model of ECM, to control cell behaviors and tissue formation. SAMs of NMs are effective ECM models as 2D surfaces due to their larger nanostructured surface areas which provide higher molecular density by functionalization on a planar substrate than molecular SAMs. Additionally, NC hydrogels, produced by cross-linking of organic polymers with NMs, are excellent candidates as 3D cell culture systems owing to their optical, cell-compatibility and the extraordinary mechanical properties.

The high sensitivity of the QCM sensor is combined with selectivity of receptor–ligand interactions to construct a biosensor which would discriminate breast cancer cells with high metastatic power from those of low or no metastatic potential to develop a simple, fast and efficient system to be used in breast cancer diagnosis.

Decreased perfusion at the bladder neck, the Framingham scores in severe OAB, and the correlation between them suggest that OAB microvascular disease may be a component of systemic atherosclerosis rather than a separate process.

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