Abstract
Personalized therapy is “the right drug for the right patient at the right time”. Here we reported a case of personalized therapy using gene expression signature (GES) related drug discovery to treat a patient with drug-resistant metastases from breast-tumor. Methods: After mRNA obtained from metastatic liver tissue was performed by microarray, GES of genomic profiles were uncovered by bioinformatics tool and targeting drugs related with GES were mined by drug-bank. Several targeting-drugs approved by FDA were selected to treat the patient. Results: 1198 genes were uncovered for the higher expression by two-fold to compare normal liver specimens in which 10 of mined genes were identified as set-1 GES for metastasis and 16 of genes were uncovered as set-2 directly for primary breast tumor. Drug-bank platform were used to discover drugs for target set-1/2 genes. Eventually, medropxyoprogesterone (MPA) targeting set-I gene and doxorubicin targeting set-2 gene were selected for the patient because the two drugs have already been approved by FDA. After doxorubicin and MPA were administered, patient's metastatic-tumor showed complete response. Conclusions: We not only analyze genomic expression profiles but also discover sensitive compounds for drug-resistant tumor. We successfully select drugs approved by FDA to treat the patient.
Highlights
Clinical genome analysis has the ability to provide some information required for identification of genotype signature (GWAS), gene expression signature (GES) and drug discovery [1,2,3,4]
Enormous amounts of genomic analysis have been used for personalized therapy of different tumor diseases, genetic diseases and unknown rare diseases
We introduce a mining process from microarray data obtained from lonely liver metastatic tissue with downstream quantitative genomic analysis for identifying GES and discovering drugs related to GES
Summary
Clinical genome analysis has the ability to provide some information required for identification of genotype signature (GWAS), gene expression signature (GES) and drug discovery [1,2,3,4]. The Open Access Journal of Science and Technology in vivo sampling [5], a pair of pathological specimens such as a pair of tumor cells vs normal cells in situ sampling obtained from laser capture microscopy (LCM) [6, 7] or fresh cells from clinical specimens by ex vivo culture [8] Such clinical genomics database, when combined with quantitative genomic analysis, allow physicians and scientists to identify genotype signature, gene expression signature and discover drugs for patients with drug resistance in tumor disease or unknown treatment in genetic, neurological and rare diseases [9, 10]. Following a three-step process, that is, mining genomic expression profile, identifying gene expression signature and discovering specific drugs, a set of drugs targeting metastasis liver (set-1) and targeting primary tumor (set-2) are used for the patient
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