Introduction: PDAC is an extremely aggressive tumor with a poor prognosis and remarkable therapeutic resistance. The dense extracellular matrix (ECM) which characterizes PDAC progression is considered a fundamental determinant of chemoresistance, with major contributions from mechanical factors. This study combined biomechanical and pharmacological approaches to evaluate the role of the cell-adhesion molecule ITGA2, a key regulator of ECM, in PDAC resistance to gemcitabine. Methods: The prognostic value of ITGA2 was analysed in publicly available databases and tissue-microarrays of two cohorts of radically resected and metastatic patients treated with gemcitabine. PANC-1 and its gemcitabine-resistant clone (PANC-1R) were analysed by RNA-sequencing and label-free proteomics. The role of ITGA2 in migration, proliferation, and apoptosis was investigated using hydrogel-coated wells, siRNA-mediated knockdown and overexpression, while collagen-embedded spheroids assessed invasion and ECM remodeling. Results: High ITGA2 expression correlated with shorter progression-free and overall survival, supporting its impact on prognosis and the lack of efficacy of gemcitabine treatment. These findings were corroborated by transcriptomic and proteomic analyses showing that ITGA2 was upregulated in the PANC-1R clone. The aggressive behavior of these cells was significantly reduced by ITGA2 silencing both in vitro and in vivo, while PANC-1 cells growing under conditions resembling PDAC stiffness acquired resistance to gemcitabine, associated to increased ITGA2 expression. Collagen-embedded spheroids of PANC-1R showed a significant matrix remodeling and spreading potential via increased expression of CXCR4 and MMP2. Additionally, overexpression of ITGA2 in MiaPaCa-2 cells triggered gemcitabine resistance and increased proliferation, both in vitro and in vivo, associated to upregulation of phospho-AKT. Conclusions: ITGA2 emerged as a new prognostic factor, highlighting the relevance of stroma mechanical properties as potential therapeutic targets to counteract gemcitabine resistance in PDAC.
Background: Pancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on the identification of new biomarkers for the early diagnosis of PDAC and prediction of patient survival. Genome-wide RNA and microRNA sequencing were used using bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs) followed by validation in additional cohort of PDAC patients. Methods: genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA) to identify DEGs. We used Kaplan-Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest, (RF), Max Voting, Adaboost, Gradient boosting machines (GBM) and Extreme Gradient Boosting (XGB) techniques were used and Gradient boosting machines (GBM) were selected with 100 % accuracy for analysis. Moreover, protein-protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs and a combination of these obtained from machine learning algorithms and survival analysis. Results: Machine learning results showed 23 genes with negative regulation, 5 genes with positive regulation, 7 microRNAs with negative regulation and 20 microRNAs with positive regulation in PDAC. Key genes BMF, FRMD4A, ADAP2, PPP1R17, and CACNG3 had the highest coefficient in the advanced stages of disease. In addition, the survival analysis results showed decreased expression of hsa.miR.642a, hsa.mir.363, CD22, BTNL9 and CTSW and overexpression of hsa.miR.153.1, hsa.miR.539, hsa.miR.412 reduced survival rate. CTSW was identified as a novel genetic marker and this was validated using RT-PCR. Conclusion: Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in pathogenesis of the diseases can be used for detection of patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value of CTSW in PDAC.
Background: Intra-abdominal adhesions are severe complications which occur after abdominal surgery. Currently, no specific anti-adhesive medications can completely prevent Intra-abdominal adhesion formation. Therefore, recent studies are exploring new approaches for preventing this complication. Anti-inflammatory properties of Trigonella foenum-graecum L. (Fenugreek) have been reported in various studies. In this experiment, a murine model was used to evaluate the potential anti-adhesive activity of Fenugreek in vivo. Objective: This experiment aimed to examine the anti-adhesive activity of Fenugreek in the prevention of postsurgical Intra-abdominal adhesions. Methods: We have adhered to the ARRIVE guidelines during these experimental studies. After abdominal surgery, for nine days, Fenugreek (400 mg/kg) was given by gavage to male Wistar rats (n=6). Following that, all animals were sacrificed to assess the anti-inflammatory and anti-fibrotic effects of Fenugreek using Hematoxylin & eosin staining and Masson’s trichrome staining. Results: Our results showed that Fenugreek hydro-alcoholic extract could significantly reduce the adhesion band formation based on Nari and Leach Scoring system (P < 0.01). The histological assessment also represented less inflammatory cell infiltration and less collagen deposition in the treatment group than in the positive control group (P < 0.01). Conclusion: This study showed that Fenugreek extract could attenuate post-surgical adhesion band formation by inhibiting pathological responses (Inflammation and fibrosis) following surgery.
Cytochrome P450 (CYP450) enzyme has been shown to be expressed in colorectal cancer (CRC) and its dysregulation is linked to tumor progression and a poor prognosis. Here we investigated the therapeutic potential of targeting CYP450 using lopinavir/ritonavir in CRC. The integrative systems biology method and RNAseq were utilized to investigate the differential levels of genes associated with patients with colorectal cancer. The antiproliferative activity of lopinavir/ritonavir was evaluated in both monolayer and 3-dimensional (3D) models, followed by wound-healing assays. The effectiveness of targeting CYP450 was examined in a mouse model, followed by histopathological analysis, biochemical tests (MDA, SOD, thiol, and CAT), and RT-PCR. The data of dysregulation expressed genes (DEG) revealed 1268 upregulated and 1074 down-regulated genes in CRC. Among the top-score genes and dysregulated pathways, CYPs were detected and associated with poor prognosis of patients with CRC. Inhibition of CYP450 reduced cell proliferation via modulating survivin, Chop, CYP13a, and induction of cell death, as detected by AnnexinV/PI staining. This agent suppressed the migratory behaviors of cells by induction of E-cadherin. Moreover, lopinavir/ritonavir suppressed tumor growth and fibrosis, which correlated with a reduction in SOD/thiol levels and increased MDA levels. Our findings illustrated the therapeutic potential of targeting the CYP450 using lopinavir/ritonavir in colorectal cancer, supporting future investigations on this novel therapeutic approach for the treatment of CRC.
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