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A genetic-based approach to personalized prostate cancer screening and treatment.

ABSTRACT: PURPOSE OF REVIEW:Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening. RECENT FINDINGS:There are now almost 100 genetic variants, called single nucleotide polymorphisms (SNPs) that have been recently found to be associated with the risk of developing prostate cancer. In addition, some of these prostate cancer risk SNPs have also been found to influence prostate specific antigen (PSA) expression levels and potentially aggressive disease. SUMMARY:Incorporation of panels of prostate cancer risk SNPs into clinical practice offers potential to provide improvements in patient selection for prostate cancer screening; PSA interpretation (e.g. by correcting for the presence of SNPs that influence PSA expression levels; decision for biopsy (using prostate cancer risk SNPs); and possibly the decision for treatment. A proposed clinical algorithm incorporating these prostate cancer risk SNPs is discussed.

SUBMITTER: Helfand BT

PROVIDER: S-EPMC4281884 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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A genetic-based approach to personalized prostate cancer screening and treatment.

Helfand Brian T BT Catalona William J WJ Xu Jianfeng J

Current opinion in urology 20150101 1

<h4>Purpose of review</h4>Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening.<h4>Recent ...[more]

PMID: 25405931

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Project description:Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient's surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated. Gene expression profiling experiments were conducted for 25 patient-derived xenograft glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.

Dataset Information

A genetic-based approach to personalized prostate cancer screening and treatment.

Publications

A genetic-based approach to personalized prostate cancer screening and treatment.

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