Dataset Information

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

ABSTRACT:

Background

Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.

Methods

Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively.

Results

Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error.

Conclusions

Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

SUBMITTER: Shipitsin M

PROVIDER: S-EPMC4453845 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

Shipitsin M M Small C C Choudhury S S Giladi E E Friedlander S S Nardone J J Hussain S S Hurley A D AD Ernst C C Huang Y E YE Chang H H Nifong T P TP Rimm D L DL Dunyak J J Loda M M Berman D M DM Blume-Jensen P P

British journal of cancer 20140717 6

<h4>Background</h4>Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.<h4>Methods</h4>Pr ...[more]

PMID: 25032733

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Project description: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 clinical 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. We analyzed a Swedish Watchful Waiting cohort (1977â1999) 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 or developed metastases and men who survived more than 10 years without metastases (lethals and indolents, respectively). Several models using clinical and molecular features were evaluated for their ability to distinguish lethal from indolent cases. Surprisingly, none of the predictive models using molecular profiles significantly improved over models using clinical variables only. We reasoned that tumor sampling might preclude the identification of the dominant metastatic nodule. 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. Thus 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 preventing the development of molecular biomarkers for prostate cancer progression. 281 cases from the population-based Swedish-Watchful Waiting cohort. The cohort consists of men with localized prostate cancer (clinical stage T1-T2, Mx, N0); Training set: first 186 samples; Validation cohort: remaining 95 cases from the same population.

Project description:BackgroundThe classification of diffuse malignant mesothelioma into epithelioid, biphasic, and sarcomatoid types is based on histologic patterns. The diagnosis is made on biopsies, and because of intratumoral heterogeneity, they may not be representative of the entire tumor. The number and volume of biopsies needed to reach diagnostic accuracy in diffuse malignant mesothelioma and their prognostic value remain unclear.MethodsThis study examined 759 consecutive patients with pleural diffuse malignant mesothelioma treated by pleurectomy/decortication or extrapleural pneumonectomy for the presence of epithelioid and/or sarcomatoid histology and classified both the presurgery biopsies (core-needle or thoracoscopic) and surgical resection specimens. The number and volume of biopsies were correlated with pre- and postsurgery histologies and overall survival.ResultsDiffuse malignant mesothelioma was classified as epithelioid (76%), biphasic (18%), sarcomatoid (5%), or indeterminate (1%) in biopsies and as epithelioid (64%), biphasic (32%), and sarcomatoid (4%) in surgical resection specimens (overall concordance, 80.6%). The positive likelihood ratios were 2.4, 13.6, and 90.1 for biopsies with epithelioid, biphasic, and sarcomatoid histologies, respectively. Concordant histologies between biopsies and resections were associated with a higher number of biopsies (median tissue blocks for concordant histologies vs discordant histologies, 3 vs 2; P < .002) but were less associated with a higher volume (median, 1.2 vs 1.1 cm3 ; P = .06). In a multivariate analysis, overall survival was independently predicted by histology in the resection specimen (P < .0001) but not in the biopsy (P = .09).ConclusionsIn contrast to epithelioid histology, sarcomatoid histology in biopsies is highly accurate. Despite intratumoral heterogeneity, the accuracy of histologic classification increases with the number of tissue blocks examined, emphasizing the diagnostic value of extensive sampling by presurgery biopsies.

Dataset Information

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

Background

Methods

Results

Conclusions

Publications

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

Similar Datasets

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