scholarly journals Drug Repositioning Based on the Reversal of Gene Expression Signatures Identifies TOP2A as a Therapeutic Target for Rectal Cancer

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5492
Author(s):  
Robson Francisco Carvalho ◽  
Luisa Matos do Canto ◽  
Sarah Santiloni Cury ◽  
Torben Frøstrup Hansen ◽  
Lars Henrik Jensen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rectal Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Topoisomerase Ii ◽  
Drug Repositioning ◽  
Gene Copy ◽  
Common Disease ◽  
Topoisomerase Ii Inhibitors ◽  
Gene Expression Signatures

Rectal cancer is a common disease with high mortality rates and limited therapeutic options. Here we combined the gene expression signatures of rectal cancer patients with the reverse drug-induced gene-expression profiles to identify drug repositioning candidates for cancer therapy. Among the predicted repurposable drugs, topoisomerase II inhibitors (doxorubicin, teniposide, idarubicin, mitoxantrone, and epirubicin) presented a high potential to reverse rectal cancer gene expression signatures. We showed that these drugs effectively reduced the growth of colorectal cancer cell lines closely representing rectal cancer signatures. We also found a clear correlation between topoisomerase 2A (TOP2A) gene copy number or expression levels with the sensitivity to topoisomerase II inhibitors. Furthermore, CRISPR-Cas9 and shRNA screenings confirmed that loss-of-function of the TOP2A has the highest efficacy in reducing cellular proliferation. Finally, we observed significant TOP2A copy number gains and increased expression in independent cohorts of rectal cancer patients. These findings can be translated into clinical practice to evaluate TOP2A status for targeted and personalized therapies based on topoisomerase II inhibitors in rectal cancer patients.

scholarly journals Insulin-like Growth Factor Receptor 1 (IGF1R) Gene Copy Number Is Associated With Survival in Operable Non–Small-Cell Lung Cancer: A Comparison Between IGF1R Fluorescent In Situ Hybridization, Protein Expression, and mRNA Expression

2010 ◽  
Vol 28 (13) ◽  
pp. 2174-2180 ◽  
Author(s):  
Rafal Dziadziuszko ◽  
Daniel T. Merrick ◽  
Samir E. Witta ◽  
Adelita D. Mendoza ◽  
Barbara Szostakiewicz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Factor ◽  
Protein Expression ◽  
Squamous Cell ◽  
Copy Number ◽  
Gene Copy Number ◽  
Growth Factor Receptor ◽  
Gene Copy ◽  
Cell Versus

PurposeThe purpose of this study was to characterize insulin-like growth factor-1 receptor (IGF1R) protein expression, mRNA expression, and gene copy number in surgically resected non–small-cell lung cancers (NSCLC) in relation to epidermal growth factor receptor (EGFR) protein expression, patient characteristics, and prognosis.Patients and MethodsOne hundred eighty-nine patients with NSCLC who underwent curative pulmonary resection were studied (median follow-up, 5.3 years). IGF1R protein expression was evaluated by immunohistochemistry (IHC) with two anti-IGF1R antibodies (n = 179). EGFR protein expression was assessed with PharmDx kit. IGF1R gene expression was evaluated using quantitative reverse transcription polymerase chain reaction (qRT-PCR) from 114 corresponding fresh-frozen samples. IGF1R gene copy number was assessed by fluorescent in situ hybridization using customized probes (n = 181).ResultsIGF1R IHC score was higher in squamous cell carcinomas versus other histologies (P < .001) and associated with stage (P = .03) but not survival (P = .46). IGF1R and EGFR protein expression showed significant correlation (r = 0.30; P < .001). IGF1R gene expression by qRT-PCR was higher in squamous cell versus other histologies (P = .006) and did not associate with other clinical features nor survival (P = .73). Employing criteria previously established for EGFR copy number, patients with IGF1R amplification/high polysomy (n = 48; 27%) had 3-year survival of 58%, patients with low polysomy (n = 87; 48%) had 3-year survival of 47% and patients with trisomy/disomy (n = 46; 25%) had 3-year survival of 35%, respectively (P = .024). Prognostic value of high IGF1R gene copy number was confirmed in multivariate analysis.ConclusionIGF1R protein expression is higher in squamous cell versus other histologies and correlates with EGFR expression. IGF1R protein and gene expression does not associate with survival, whereas high IGF1R gene copy number harbors positive prognostic value.

scholarly journals In situ analysis of FGFR2 mRNA and comparison with FGFR2 gene copy number by dual-color in situ hybridization in a large cohort of gastric cancer patients

2017 ◽  
Vol 21 (3) ◽  
pp. 401-412 ◽  
Author(s):  
Yasutoshi Kuboki ◽  
Christoph A. Schatz ◽  
Karl Koechert ◽  
Sabine Schubert ◽  
Janine Feng ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
In Situ Hybridization ◽  
Cancer Patients ◽  
Copy Number ◽  
Gene Copy Number ◽  
In Situ Analysis ◽  
Gene Copy ◽  
Fgfr2 Gene ◽  
Gastric Cancer Patients

scholarly journals PS4DR: A multimodal workflow for identification and prioritization of drugs based on pathway signatures

2020 ◽  
Author(s):  
Mhammad Asif Emon ◽  
Daniel Domingo-Fernández ◽  
Charles Tapley Hoyt ◽  
Martin Hofmann-Apitius
Keyword(s):  
Gene Expression ◽  
Genome Wide Association Study ◽  
Drug Repositioning ◽  
Heterogeneous Data ◽  
New Drugs ◽  
Gwas Data ◽  
Drug Candidates ◽  
Gene Expression Signatures ◽  
Approved Drugs ◽  
Fda Approved Drugs

Abstract Background: During the last decade, there has been a surge towards computational drug repositioning owing to constantly increasing -omics data in the biomedical research field. While numerous existing methods focus on the integration of heterogeneous data to propose candidate drugs, it is still challenging to substantiate their results with mechanistic insights of these candidate drugs. Therefore, there is a need for more innovative and efficient methods which can enable better integration of data and knowledge for drug repositioning. Results: Here, we present a customizable workflow ( PS4DR) which not only integrates high-throughput data such as genome-wide association study (GWAS) data and gene expression signatures from disease and drug perturbations but also takes pathway knowledge into consideration to predict drug candidates for repositioning. We have collected and integrated publicly available GWAS data and gene expression signatures for several diseases and hundreds of FDA-approved drugs or those under clinical trial in this study. Additionally, different pathway databases were used for mechanistic knowledge integration in the workflow. Using this systematic consolidation of data and knowledge, the workflow computes pathway signatures that assist in the prediction of new indications for approved and investigational drugs. Conclusion: We showcase PS4DR with applications demonstrating how this tool can be used for repositioning and identifying new drugs as well as proposing drugs that can simulate disease dysregulations. We were able to validate our workflow by demonstrating its capability to predict FDA-approved drugs for their known indications for several diseases. Further, PS4DR returned many potential drug candidates for repositioning that were backed up by epidemiological evidence extracted from scientific literature. Source code is freely available at https://github.com/ps4dr/ps4dr .

Shared DNA-based copy number with divided methylation changes differentiate and clinically associate early stage pancreatic cancer tumors.

2021 ◽  
Vol 39 (3_suppl) ◽  
pp. 434-434
Author(s):  
Eva Chao ◽  
Kyaw Lwin Aung ◽  
Qi Xu ◽  
William H. Matsui ◽  
Jeanne Kowalski
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Overall Survival ◽  
Clinical Outcomes ◽  
Copy Number ◽  
Cancer Biology ◽  
Early Stage ◽  
Molecular Taxonomy ◽  
Unmet Need ◽  
Gene Copy

434 Background: There is no known molecular taxonomy of pancreatic cancer that can guide therapeutic strategies. Understanding the fundamental molecular mechanism underlying pancreatic cancer biology remains an unmet need. We explore the extent to which combinations of DNA-based molecular changes in copy number (CN) and methylation separate early stage PAAD tumors and associated with survival outcomes. Methods: We performed genome-wide combined cluster analyses on DNA-based CN and methylation changes using TCGA data. We examined cluster associations with clinical outcomes by comparing in months (mos), Kaplan--Meier estimated overall survival (OS) and disease-free interval (DFI) using a log-rank test. We performed additional comparisons among CN-Methylation derived clusters with respect to PAAD phenotypes. Results: Using 78 early stage pancreatic cancer tumors from TCGA with CN, methylation and clinical outcomes data, we identified two patient clusters with distinct gene copy number signatures that when combined with three methylation signatures, resulted in three additional clusters. Thus, the same gene CN signature, when combined with different methylation signatures, further differentiated tumors into sub-clusters with varying levels of associations with clinical outcome. Among them, analogous to current gene-expression based subtypes, we also identified an immune-rich subtype that was associated with improved overall survival (n=21, median OS=16mos; DFI=16mos), and an extracellular matrix (ECM)-rich with worse survival (n=19, median OS=12mos; DFI=8mos). Unlike previous expression subtypes, we identified another metabolic-enriched subtype with the same worse median OS and DFI, differentiated by methylation with the ECM-rich subtype. The improved OS cluster had a signature of CN neutral and increased methylation, while the poor cluster had a signature of CN gains and increased methylation among a set of genes distinct from the improved cluster. No significant differences in age, site, microsatellite instability and KRAS status among clusters were noted. Notably, in a multivariable model that included gene expression-based subtypes, only our DNA-level subtypes remained significantly associated with overall survival. Conclusions: While RNA-level changes often display large variations, DNA-level changes are more robust. Copy number changes appear to separate tumors into poor and improved prognosis clusters, while methylation appears to inform on the further separation of poor prognosis into various levels. A DNA-based molecular taxonomy for early stage pancreatic cancer could prove invaluable when used in combination with methylation-based circulating tumor DNA assays for clinical trial monitoring of tumor responses.

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