Dataset Information

Olaparib-Induced Purpuric Drug Eruption in a Patient with Castration-Resistant Prostate Cancer.

ABSTRACT: Olaparib is recently approved as an anti-tumor agent for several cancers, including castration-resistant prostate cancer, which inhibits poly (adenosine diphosphate-ribose) polymerase, a DNA repair factor. Since olaparib is a newly approved drug, there are few reports of skin disorders that may be triggered by olaparib administration. In this report, we present a case with an olaparib-induced drug eruption presenting multiple purpuras on the patient's fingers and fingertips. The present case suggests that olaparib might induce purpura as nonallergic drug eruption.

SUBMITTER: Sekine M

PROVIDER: S-EPMC10294207 | biostudies-literature | 2023 Jan-Dec

REPOSITORIES: biostudies-literature

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Olaparib-Induced Purpuric Drug Eruption in a Patient with Castration-Resistant Prostate Cancer.

Sekine Mana M Terui Hitoshi H Fujimura Taku T Asano Yoshihide Y

Case reports in oncology 20230101 1

Olaparib is recently approved as an anti-tumor agent for several cancers, including castration-resistant prostate cancer, which inhibits poly (adenosine diphosphate-ribose) polymerase, a DNA repair factor. Since olaparib is a newly approved drug, there are few reports of skin disorders that may be triggered by olaparib administration. In this report, we present a case with an olaparib-induced drug eruption presenting multiple purpuras on the patient's fingers and fingertips. The present case sug ...[more]

PMID: 37384205

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Project description:Purpose: The effectiveness of poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitor olaparib for metastatic castration-resistant prostate cancer (MCRPC) with multiple loss-of-function alterations in genes that are involved in DNA repair has been demonstrated. We aimed to evaluate the cost-effectiveness of genomic test-directed olaparib on MCRPC from the US payer perspective. Methods: A partitioned survival model was adopted to project the disease course of MCRPC had at least one gene alteration in BRCA1, BRCA2 and ATM (Scenario A) and has alterations in any of all 15 prespecified genes (Scenario B) after next-generation sequencing test. The efficacy and toxicity data were gathered from the PROfound trial. Clinical probabilities related to survival were estimated from the reported survival probabilities in each PROfound group. Cost and health preference data were derived from the literature. The incremental cost-effectiveness ratio (ICER) was measured. Subgroup analysis and sensitivity analysis were performed for exploring the model uncertainties. Results: Olaparib yielded an additional 0.063 and 0.068 of quality-adjusted life year (QALY) with the augmented cost of $7,382 and saved the cost of $ 1,980 compared to standard care in scenario A and B, respectively, which yielded an ICER of $116,903/QALY and a cost-saving option. The lower weekly cost related to olaparib treatment led to the dominant findings in scenario B. The varied results between scenario A and B could be partly explained by different the number need to screen for identifying eligible patients who could be administered with olaparib, which sharply augmented the costs of the olaparib arm in scenario A. Subgroup analysis and sensitivity analysis revealed the results were generally robust in both of two scenarios. Conclusion: The genomic test-directed olaparib is a preferred option compared with standard care strategy for men with MCRPC who had any of all 15 prespecified genes.

Project description:Purpose: Most prostate cancers (PCs) initially respond to androgen deprivation therapy (ADT), but eventually many PC patients develop castration resistant PC (CRPC). Currently, available drugs that have been approved for the treatment of CRPC patients are limited. Computational drug repositioning methods using public databases represent a promising and efficient tool for discovering new uses for existing drugs. The purpose of the present study is to predict drug candidates that can treat CRPC using a computational method that integrates publicly available gene expression data of tumors from CRPC patients, drug-induced gene expression data and drug response activity data. Methods: Gene expression data from tumoral and normal or benign prostate tissue samples in CRPC patients were downloaded from the Gene Expression Omnibus (GEO) and differentially expressed genes (DEGs) in CRPC were determined with a meta-signature analysis by a metaDE R package. Additionally, drug activity data were downloaded from the ChEMBL database. Furthermore, the drug-induced gene expression data were downloaded from the LINCS database. The reversal relationship between the CRPC and drug gene expression signatures as the Reverse Gene Expression Scores (RGES) were computed. Drug candidates to treat CRPC were predicted using summarized scores (sRGES). Additionally, synergic effects of drug combinations were predicted with a Target Inhibition interaction using the Minimization and Maximization Averaging (TIMMA) algorithm. Results: The drug candidates of sorafenib, olaparib, elesclomol, tanespimycin, and ponatinib were predicted to be active for the treatment of CRPC. Meanwhile, CRPC-related genes, in this case MYL9, E2F2, APOE, and ZFP36, were identified as having gene expression data that can be reversed by these drugs. Additionally, lenalidomide in combination with pazopanib was predicted to be most potent for CRPC. Conclusion: These findings support the use of a computational reversal gene expression approach to identify new drug and drug combination candidates that can be used to treat CRPC.

Dataset Information

Olaparib-Induced Purpuric Drug Eruption in a Patient with Castration-Resistant Prostate Cancer.

Publications

Olaparib-Induced Purpuric Drug Eruption in a Patient with Castration-Resistant Prostate Cancer.

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