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

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

Sboner, Andrea (författare): Department of Molecular Biophysics and Biochemistry, Yale University, New Haven CT, USA

Demichelis, Francesca (författare): Department of Pathology and LaboratoryMedicine, Weill Cornell Medical Center, New York, USA; Institute for Computational Biomedicine, Weill Cornell Medical Center, New York, USA

Calza, Stefano (författare): Karolinska Institutet,Karolinska Institute

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Pawitan, Yudi (författare): Karolinska Institutet,Karolinska Institute

Setlur, Sunita R (författare): Department of Pathology, Brigham and Women's Hospital, Boston MA, USA

Hoshida, Yujin (författare): The Broad Institute of MIT and Harvard, Cambridge MA, USA; The Dana Farber Cancer Institute, Boston MA, USA

Perner, Sven (författare): Department of Pathology and LaboratoryMedicine, Weill Cornell Medical Center, New York, USA

Adami, Hans-Olov (författare): Karolinska Institutet,Karolinska Institute

Fall, Katja, 1971- (författare): Karolinska Institutet,Karolinska Institute

A Mucci, Lorelei (författare): Harvard University,Harvard Medical School, Boston MA, USA; Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston MA, USA; Department of Epidemiology, Harvard School of Public Health, Boston MA, USA

Kantoff, Philip W (författare): Harvard Medical School, Boston MA, USA; The Dana Farber Cancer Institute, Boston MA, USA

Stampfer, Meir (författare): Harvard University,Harvard Medical School, Boston MA, USA; Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston MA, USA; Department of Epidemiology, Harvard School of Public Health, Boston MA, USA

Andersson, Swen-Olof, 1949- (författare): Department of Urology, Örebro University Hospital, Örebro, Sweden

Varenhorst, Eberhard (författare): Östergötlands Läns Landsting,Linköpings universitet,Urologi,Hälsouniversitetet,Urologiska kliniken i Östergötland,Department of Urology, Linköping University Hospital, Linköping, Sweden

Johansson, Jan-Erik (författare): Department of Urology, Örebro University Hospital, Örebro, Sweden

Gerstein, Mark B (författare): Department of Molecular Biophysics and Biochemistry, Yale University, New Haven CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven CT, USA; Department of Computer Science, Yale University, New Haven CT, USA

Golub, Todd R (författare): The Howard Hughes Medical Institute at The Broad Institute of MIT and Harvard, Cambridge MA, USA; The Broad Institute of MIT and Harvard, Cambridge MA, USA; The Dana Farber Cancer Institute, Boston MA, USA

Rubin, Mark A (författare): Medicine, Weill Cornell Medical Center, New York, USA; The Broad Institute of MIT and Harvard, Cambridge MA, USA

Andrén, Ove, 1963- (författare): Department of Urology, Örebro University Hospital, Örebro, Sweden

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2010-03-16
2010
Engelska.
Ingår i: BMC Medical Genomics. - London, United Kingdom : BioMed Central. - 1755-8794. ; 3:8

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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.

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MEDICIN OCH HÄLSOVETENSKAP: MEDICIN OCH HÄLS ...; och Klinisk medicin; och Cancer och onkol ...

Artiklar i publikationen: BMC Medical Geno ...

Av lärosätet: Linköpings universitet; Örebro universitet; Karolinska Institutet

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

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