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Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

ABSTRACT: Early detection of prostate cancer (PC) using prostate-specific antigen (PSA) in blood reduces PC-death among unscreened men. However, due to modest specificity of PSA at commonly used cut-offs, there are urgent needs for additional biomarkers contributing enhanced risk classification among men with modestly elevated PSA.Recombinant antibody microarrays were applied for protein expression profiling of 80 plasma samples from routine PSA-measurements, a priori divided into four risk groups, based on levels of total and %free PSA.The results demonstrated that plasma protein profiles could be identified that pin-pointed PC (a malignant biomarker signature) and most importantly that showed moderate to high correlation with biochemically defined PC risk groups. Notably, the data also implied that the risk group with midrange PSA and low %free PSA, a priori known to be heterogeneous, could be further stratified into two subgroups, more resembling the lowest and highest risk groups, respectively.In this pilot study, we have shown that plasma protein biomarker signatures, associated with risk groups of PC, could be identified from crude plasma samples using affinity proteomics. This approach could in the longer perspective provide novel opportunities for improved risk classification of PC patients.

SUBMITTER: Nordstrom M

PROVIDER: S-EPMC4532381 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

Nordström Malin M Wingren Christer C Rose Carsten C Bjartell Anders A Becker Charlotte C Lilja Hans H Borrebaeck Carl A K CA

Proteomics. Clinical applications 20141022 11-12

<h4>Purpose</h4>Early detection of prostate cancer (PC) using prostate-specific antigen (PSA) in blood reduces PC-death among unscreened men. However, due to modest specificity of PSA at commonly used cut-offs, there are urgent needs for additional biomarkers contributing enhanced risk classification among men with modestly elevated PSA.<h4>Experimental design</h4>Recombinant antibody microarrays were applied for protein expression profiling of 80 plasma samples from routine PSA-measurements, a ...[more]

PMID: 25196118

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Project description:BackgroundThe association of circulating lipids with clinical outcomes of drug-resistant castration-resistant prostate cancer (DR-CRPC) is not fully understood. While it is known that increases in select lipids correlate to decreased survival, neither the mechanisms mediating these alterations nor the correlation of resistance to drug treatments is well characterized.MethodsThis gap-in-knowledge was addressed using in vitro models of non-cancerous, hormone-sensitive, CRPC and drug-resistant cell lines combined with quantitative LC-ESI-Orbitrap-MS (LC-ESI-MS/MS) lipidomic analysis and subsequent analysis such as Metaboanalyst and Lipid Pathway Enrichment Analysis (LIPEA).ResultsSeveral lipid regulatory pathways were identified that are associated with Docetaxel resistance in prostate cancer (PCa). These included those controlling glycerophospholipid metabolism, sphingolipid signaling and ferroptosis. In total, 7460 features were identified as being dysregulated between the cell lines studied, and 21 lipid species were significantly altered in drug-resistant cell lines as compared to nonresistant cell lines. Docetaxel resistance cells (PC3-Rx and DU145-DR) had higher levels of phosphatidylcholine (PC), oxidized lipid species, phosphatidylethanolamine (PE), and sphingomyelin (SM) as compared to parent control cells (PC-3 and DU-145). Alterations were also identified in the levels of phosphatidic acid (PA) and diacylglyceride (DAG), whose levels are regulated by Lipin (LPIN), a phosphatidic acid phosphatase that converts PA to DAG. Data derived from cBioPortal demonstrated a population of PCa patients expressing mutations aligning with amplification of LPIN1, LPIN2 and LPIN3 genes. Lipin amplification in these genes correlated to decreased survival in these patients. Lipin-1 mRNA expression also showed a similar trend in PCa patient data. Lipin-1, but not Lipin-2 or - 3, was detected in several prostate cancer cells, and was increased in 22RV1 and PC-3 cell lines. The increased expression of Lipin-1 in these cells correlated with the level of PA.ConclusionThese data identify lipids whose levels may correlate to Docetaxel sensitivity and progression of PCa. The data also suggest a correlation between the expression of Lipin-1 in cells and patients with regards to prostate cancer cell aggressiveness and patient survivability. Ultimately, these data may be useful for identifying markers of lethal and/or metastatic prostate cancer.

Project description:Prostate cancer (PCa) is a common malignancy and a leading cause of cancer death among men in the United States with African-American (AA) men having the highest incidence and mortality rates. Given recent results from admixture mapping and genome-wide association studies for PCa in AA men, it is clear that many risk alleles are enriched in men with West African genetic ancestry.A total of 77 ancestry informative markers (AIMs) within surrounding candidate gene regions were genotyped and haplotyped using Pyrosequencing in 358 unrelated men enrolled in a PCa genetic association study at the Howard University Hospital between 2000 and 2004. Sequence analysis of promoter region single-nucleotide polymorphisms (SNPs) to evaluate disruption of transcription factor-binding sites was conducted using in silico methods.Eight AIMs were significantly associated with PCa risk after adjusting for age and West African ancestry. SNP rs1993973 (intervening sequences) had the strongest association with PCa using the log-additive genetic model (P=0.002). SNPs rs1561131 (genotypic, P=0.007), rs1963562 (dominant, P=0.01) and rs615382 (recessive, P=0.009) remained highly significant after adjusting for both age and ancestry. We also tested the independent effect of each significantly associated SNP and rs1561131 (P=0.04) and rs1963562 (P=0.04) remained significantly associated with PCa development. After multiple comparisons testing using the false discovery rate, rs1993973 remained significant. Analysis of the rs156113-, rs1963562-rs615382l and rs1993973-rs585224 haplotypes revealed that the least frequently found haplotypes in this population were significantly associated with a decreased risk of PCa (P=0.032 and 0.0017, respectively).The approach for SNP selection utilized herein showed that AIMs may not only leverage increased linkage disequilibrium in populations to identify risk and protective alleles, but may also be informative in dissecting the biology of PCa and other health disparities.

Dataset Information

Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

Publications

Identification of plasma protein profiles associated with risk groups of prostate cancer patients.

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