Validation of transcriptome signature reversion for drug repurposing in oncology.

Transcriptome signature reversion (TSR) has been extensively proposed and used to discover new indications for existing drugs (i.e. drug repositioning, drug repurposing) for various cancer types.

Influence of batch effect correction methods on drug induced differential gene expression profiles.

Background: Batch effects were not accounted for in most of the studies of computational drug repositioning based on gene expression signatures. It is unknown how batch effect removal methods impact the results of signature-based drug repositioning. Herein, we conducted differential analyses on the Connectivity Map (CMAP) database using several batch effect correction methods to evaluate the influence of batch effect correction methods on computational drug repositioning using microarray data and compare several batch effect correction methods.

Transcriptome Signature Reversion as a Method to Reposition Drugs Against Cancer for Precision Oncology.

Transcriptome signature reversion (TSR) has been hypothesized as a promising method for discovery and use of existing noncancer drugs as potential drugs in the treatment of cancer (i.e., drug repositioning, drug repurposing).

The impact of estimated tumour purity on gene expression-based drug repositioning of Clear Cell Renal Cell Carcinoma samples.

To find new potentially therapeutic drugs against clear cell Renal Cell Carcinoma (ccRCC), within drugs currently prescribed for other diseases (drug repositioning), we previously searched for drugs which are expected to bring the gene expression of 500 + ccRCC samples from The Cancer Genome Atlas closer to that of healthy kidney tissue samples. An inherent limitation of this bulk RNA-seq data is that tumour samples consist of a varying mixture of cancerous and non-cancerous cells, which influences differential gene expression analyses. Here, we investigate whether the drug repositioning candidates are expected to target the genes dysregulated in ccRCC cells by studying the association with tumour purity.

Personalised drug repositioning for Clear Cell Renal Cell Carcinoma using gene expression.

Reversal of cancer gene expression is predictive of therapeutic potential and can be used to find new indications for existing drugs (drug repositioning). Gene expression reversal potential is currently calculated, in almost all studies, by pre-aggregating all tumour samples into a single group signature or a limited number of molecular subtype signatures. Here, we investigate whether drug repositioning based on individual tumour sample gene expression signatures outperforms the use of tumour group and subtype signatures.

A Genetic Polymorphism in Is Associated with Overall Survival in Sunitinib-Treated Patients with Clear Cell Metastatic Renal Cell Carcinoma.

The survival of patients with clear cell metastatic renal cell carcinoma (cc-mRCC) has improved substantially since the introduction of tyrosine kinase inhibitors (TKI). With the fact that TKIs interact with immune responses, we investigated whether polymorphisms of genes involved in immune checkpoints are related to the clinical outcome of cc-mRCC patients treated with sunitinib as first TKI. Twenty-seven single-nucleotide polymorphisms (SNP) in (PD-L1), (PD-1), and were tested for a possible association with progression-free survival (PFS) and overall survival (OS) in a discovery cohort of 550 sunitinib-treated cc-mRCC patients.