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Molecular sampling of prostate cancer: a dilemma for predicting disease progression.

Abstract：

BACKGROUND:Current prostate cancer prognostic models are based on pre-treatment prostate specific antigen (PSA) levels, biopsy Gleason score, and clinical staging but in practice are inadequate to accurately predict disease progression. Hence, we sought to develop a molecular panel for prostate cancer progression by reasoning that molecular profiles might further improve current clinical models. METHODS:We analyzed a Swedish Watchful Waiting cohort with up to 30 years of clinical follow up using a novel method for gene expression profiling. This cDNA-mediated annealing, selection, ligation, and extension (DASL) method enabled the use of formalin-fixed paraffin-embedded transurethral resection of prostate (TURP) samples taken at the time of the initial diagnosis. We determined the expression profiles of 6100 genes for 281 men divided in two extreme groups: men who died of prostate cancer and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several statistical and machine learning models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. RESULTS:Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. Additional computational analysis confirmed that molecular heterogeneity within both the lethal and indolent classes is widespread in prostate cancer as compared to other types of tumors. CONCLUSIONS:The determination of the molecularly dominant tumor nodule may be limited by sampling at time of initial diagnosis, may not be present at time of initial diagnosis, or may occur as the disease progresses making the development of molecular biomarkers for prostate cancer progression challenging.

journal_name

BMC Med Genomics

journal_title

BMC medical genomics

authors

Sboner A,Demichelis F,Calza S,Pawitan Y,Setlur SR,Hoshida Y,Perner S,Adami HO,Fall K,Mucci LA,Kantoff PW,Stampfer M,Andersson SO,Varenhorst E,Johansson JE,Gerstein MB,Golub TR,Rubin MA,Andrén O

doi

10.1186/1755-8794-3-8

subject

Has Abstract

pub_date

2010-03-16 00:00:00

pages

issn

1755-8794

pii

1755-8794-3-8

journal_volume

pub_type

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Molecular sampling of prostate cancer: a dilemma for predicting disease progression.