scholarly journals HSP90 Inhibition Synergizes with Cisplatin to Eliminate Basal-like Pancreatic Ductal Adenocarcinoma Cells

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6163
Author(s):  
Katharina M. Ewers ◽  
Shilpa Patil ◽  
Waltraut Kopp ◽  
Jürgen Thomale ◽  
Tabea Quilitz ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Predictive Biomarkers ◽  
Hsp90 Inhibitor ◽  
Ductal Adenocarcinoma ◽  
Ovarian Cancer Cells ◽  
Hsp90 Inhibitors ◽  
Hsp90 Inhibition ◽  
Platinum Sensitive

To improve the treatment of pancreatic ductal adenocarcinoma (PDAC), a promising strategy consists of personalized chemotherapy based on gene expression profiles. Investigating a panel of PDAC-derived human cell lines, we found that their sensitivities towards cisplatin fall in two distinct classes. The platinum-sensitive class is characterized by the expression of GATA6, miRNA-200a, and miRNA-200b, which might be developable as predictive biomarkers. In the case of resistant PDAC cells, we identified a synergism of cisplatin with HSP90 inhibitors. Mechanistic explanations of this synergy include the degradation of Fanconi anemia pathway factors upon HSP90 inhibition. Treatment with the drug combination resulted in increased DNA damage and chromosome fragmentation, as we have reported previously for ovarian cancer cells. On top of this, HSP90 inhibition also enhanced the accumulation of DNA-bound platinum. We next investigated an orthotopic syngeneic animal model consisting of tumors arising from KPC cells (LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre, C57/BL6 genetic background). Here again, when treating established tumors, the combination of cisplatin with the HSP90 inhibitor onalespib was highly effective and almost completely prevented further tumor growth. We propose that the combination of platinum drugs and HSP90 inhibitors might be worth testing in the clinics for the treatment of cisplatin-resistant PDACs.

scholarly journals Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

2020 ◽  
Author(s):  
Huatian Luo ◽  
Da-qiu Chen ◽  
Jing-jing Pan ◽  
Zhang-wei Wu ◽  
Can Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Ductal Adenocarcinoma ◽  
Hub Genes ◽  
Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes. Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival. Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis. Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

scholarly journals A Network-Based Approach for Identification of Subtype-Specific Master Regulators in Pancreatic Ductal Adenocarcinoma

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 155
Author(s):  
Yuchen Zhang ◽  
Lina Zhu ◽  
Xin Wang
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Network Inference ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Regulatory Mechanism ◽  
Expression Profiles ◽  
Strong Association ◽  
Predictive Biomarkers ◽  
Integrative Analysis ◽  
Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC), the predominant subtype of pancreatic cancer, has been reported with equal mortality and incidence for decades. The lethality of PDAC is largely due to its late presentation, when surgical resection is no longer an option. Similar to other major malignancies, it is now clear that PDAC is not a single disease, posing a great challenge to precise selection of patients for optimized adjuvant therapy. A representative study found that PDAC comprises four distinct molecular subtypes: squamous, pancreatic progenitor, immunogenic, and aberrantly differentiated endocrine exocrine (ADEX). However, little is known about the molecular mechanisms underlying specific PDAC subtypes, hampering the design of novel targeted agents. In this study we performed network inference that integrates miRNA expression and gene expression profiles to dissect the miRNA regulatory mechanism specific to the most aggressive squamous subtype of PDAC. Master regulatory analysis revealed that the particular subtype of PDAC is predominantly influenced by miR-29c and miR-192. Further integrative analysis found miR-29c target genes LOXL2, ADAM12 and SERPINH1, which all showed strong association with prognosis. Furthermore, we have preliminarily revealed that the PDAC cell lines with high expression of these miRNA target genes showed significantly lower sensitivities to multiple anti-tumor drugs. Together, our integrative analysis elucidated the squamous subtype-specific regulatory mechanism, and identified master regulatory miRNAs and their downstream genes, which are potential prognostic and predictive biomarkers.

Identification of gene expression profiles in pancreatic ductal adenocarcinoma. Clinical implications

Pancreatology ◽  
2013 ◽  
Vol 13 (4) ◽  
pp. e5
Author(s):  
M.C. Gómez Mateo ◽  
L. Sabater Ortí ◽  
J.F. Chaves Martínez ◽  
A.B. García García ◽  
J. Sastre Belloch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Ductal Adenocarcinoma ◽  
Clinical Implications

scholarly journals Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

2020 ◽  
Author(s):  
Huatian Luo ◽  
Da-qiu Chen ◽  
Jing-jing Pan ◽  
Zhang-wei Wu ◽  
Can Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Ductal Adenocarcinoma ◽  
Hub Genes ◽  
Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes.Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival.Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis.Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

scholarly journals Erratum to: Gene expression profiles of microdissected pancreatic ductal adenocarcinoma

2012 ◽  
Vol 460 (5) ◽  
pp. 543-543
Author(s):  
Robert Grützmann ◽  
Melanie Foerder ◽  
Ingo Alldinger ◽  
Eike Staub ◽  
Thomas Brümmendorf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Ductal Adenocarcinoma

Gene expression profiles of microdissected pancreatic ductal adenocarcinoma

2003 ◽  
Vol 443 (4) ◽  
pp. 508-517 ◽  
Author(s):  
Robert Gr�tzmann ◽  
Melanie Foerder ◽  
Ingo Alldinger ◽  
Eike Staub ◽  
Thomas Br�mmendorf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Ductal Adenocarcinoma
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