ITGA2, LAMB3, and LAMC2 May Be the Potential Therapeutic Targets in Pancreatic Ductal Adenocarcinoma: an Integrated Bioinformatics Analysis

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most common form of pancreatic cancer with an abysmal prognosis rate over the last few decades. Early diagnosis and prevention could effectively combat this malignancy. Therefore, it is crucial to discover potential biomarkers to identify asymptomatic premalignant or early malignant tumors of PDAC. Gene expression analysis is a powerful technique to identify candidate biomarkers involved in disease progression. In the present study, five independent gene expression datasets, including 321 PDAC tissues and 208 adjacent non-cancerous tissue samples, were subjected to statistical and bioinformatics analysis. A total of 20 differentially expressed genes (DEGs) were identified in PDAC tissues compared to non-cancerous tissue samples. Gene ontology and pathway enrichment analysis showed that DEGs were mainly enriched in extracellular matrix (ECM), cell adhesion, ECM-receptor interaction, and focal adhesion signaling. The protein protein interaction network was constructed, and the hub genes were evaluated. Collagen type XII alpha 1 chain (COL12A1), fibronectin 1 (FN1), integrin subunit alpha 2 (ITGA2), laminin subunit beta 3 (LAMB3), laminin subunit gamma 2 (LAMC2), thrombospondin 2 (THBS2), and versican (VCAN) were identified as hub genes. The correlation analysis revealed that identified hub genes were significantly interconnected. Wherein COL12A1, FN1, ITGA2, LAMB3, LAMC2, and THBS2 were significantly associated with PDAC pathological stages. The Kaplan-Meier survival plots revealed that ITGA2, LAMB3, and LAMC2 expression were inversely correlated with a prolonged patient survival period. Furthermore, the Human Protein Atlas database was used to validate the expression and cellular origins of hub genes encoded proteins. The protein expression of hub genes was higher in pancreatic cancer tissue than in normal pancreatic tissue samples, wherein ITGA2, LAMB3, and LAMC2 were exclusively expressed in pancreatic cancer cells. Pancreatic cancer cell-specific expression of these three proteins may play pleiotropic roles in cancer progression. Our results collectively suggest that ITGA2, LAMB3, and LAMC2 could provide deep insights into pancreatic carcinogenesis molecular mechanisms and provide attractive therapeutic targets.

A comprehensive transcriptional signature in pancreatic ductal adenocarcinoma reveals new insights into the immune and desmoplastic microenvironment

“…Furthermore, laminins LAMBC2 and LAMB3 support cancer progression and resistance to gemcitabine -one of the main chemotherapeutics used in PDAC patients [61,62]. In general, the association with poor prognosis of the stroma signature is consistent with the one described in previous studies for each gene: CEACAM5 [63], CEACAM6 [64], FN1 [65], GJB2 [66], GPRC5A [67], LAMB3 [68,69], LAMC2 [68,69], SFN [70], SLC6A14 [71], TSPAN1 [72], VCAN [65]. The meta-analysis from transcriptomic studies allows a be er understanding of the PDAC environment.…”

PLK1-mediated phosphorylation of β-catenin enhances its stability and transcriptional activity for extracellular matrix remodeling in metastatic NSCLC

“…Laminin γ2 is a subunit of glycoprotein laminin 322 that forms a web-like structure, providing tensile strength to the basement membrane in ECM [45]. Laminin γ2 is identified as a metastatic marker with high expression in a number of cancers [45], including LUAD [23] and pancreatic ductal adenocarcinoma [46] because it enhances metastatic potential through integrin β1, ZEB1, and SNAI1-mediated EMT [23]. In addition, TSG6 is involved in ECM stability during EMT and cell migration as an HA binding protein, a main component of proteoglycans in the ECM, which is a central factor for the EMT of renal tubular epithelial cells in a CD44-dependent manner [25,26].…”

A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

“…Chan et al identified common driver genes for T2D and cardiovascular disease from genome-wide association studies within women from different ethnicities [12]. Other studies have also aimed to contribute to the understanding of molecular mechanism of pancreas-related disorders and provide therapeutic targets [13][14][15][16][17].…”

“…Chan et al identified common driver genes for T2D and cardiovascular disease from genome-wide association studies within women of different ethnicities [12]. Other studies have also contributed to the understanding of molecular mechanism of pancreas-related disorders and provide therapeutic targets [13][14][15][16][17]. Several computational methods have been developed for the identification of significant differentially expressed genes as inputs for enrichment analysis tools (e.g., Enrichr) to evaluate biological functions.…”