Dataset Information

Expression of ribosomal proteins in normal and cancerous human prostate tissue.

ABSTRACT: Few quantifiable tissue biomarkers for the diagnosis and prognosis of prostate cancer exist. Using an unbiased, quantitative approach, this study evaluates the potential of three proteins of the 40S ribosomal protein complex as putative biomarkers of malignancy in prostate cancer. Prostate tissue arrays, constructed from 82 patient samples (245 tissue cores, stage pT3a or pT3b), were stained for antibodies against three ribosomal proteins, RPS19, RPS21 and RPS24. Semi-automated Ox-DAB signal quantification using ImageJ software revealed a significant change in expression of RPS19, RPS21 and RPS24 in malignant vs non-malignant tissue (p<0.0001). Receiver operating characteristics curves were calculated to evaluate the potential of each protein as a biomarker of malignancy in prostate cancer. Positive likelihood ratios for RPS19, RPS21 and RPS24 were calculated as 2.99, 4.21, and 2.56 respectively, indicating that the overexpression of the protein is correlated with the presence of disease. Triple-labelled, quantitative, immunofluorescence (with RPS19, RPS21 and RPS24) showed significant changes (p<0.01) in the global intersection coefficient, a measure of how often two fluorophore signals intersect, for RPS19 and RPS24 only. No change was observed in the co-localization of any other permutations of the three proteins. Our results show that RPS19, RPS21 or RPS24 are upregulated in malignant tissue and may serve as putative biomarkers for prostate cancer.

SUBMITTER: Arthurs C

PROVIDER: S-EPMC5634644 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Expression of ribosomal proteins in normal and cancerous human prostate tissue.

Arthurs Callum C Murtaza Bibi Nazia BN Thomson Calum C Dickens Kerry K Henrique Rui R Patel Hitendra R H HRH Beltran Mariana M Millar Michael M Thrasivoulou Christopher C Ahmed Aamir A

PloS one 20171010 10

Few quantifiable tissue biomarkers for the diagnosis and prognosis of prostate cancer exist. Using an unbiased, quantitative approach, this study evaluates the potential of three proteins of the 40S ribosomal protein complex as putative biomarkers of malignancy in prostate cancer. Prostate tissue arrays, constructed from 82 patient samples (245 tissue cores, stage pT3a or pT3b), were stained for antibodies against three ribosomal proteins, RPS19, RPS21 and RPS24. Semi-automated Ox-DAB signal qua ...[more]

PMID: 29016636

Similar Datasets

Project description:BackgroundMulticompartmental modeling outperforms conventional diffusion-weighted imaging (DWI) in the assessment of prostate cancer. Optimized multicompartmental models could further improve the detection and characterization of prostate cancer.PurposeTo optimize multicompartmental signal models and apply them to study diffusion in normal and cancerous prostate tissue in vivo.Study typeRetrospective.SubjectsForty-six patients who underwent MRI examination for suspected prostate cancer; 23 had prostate cancer and 23 had no detectable cancer.Field strength/sequence3T multishell diffusion-weighted sequence.AssessmentMulticompartmental models with 2-5 tissue compartments were fit to DWI data from the prostate to determine optimal compartmental apparent diffusion coefficients (ADCs). These ADCs were used to compute signal contributions from the different compartments. The Bayesian Information Criterion (BIC) and model-fitting residuals were calculated to quantify model complexity and goodness-of-fit. Tumor contrast-to-noise ratio (CNR) and tumor-to-background signal intensity ratio (SIR) were computed for conventional DWI and multicompartmental signal-contribution maps.Statistical testsAnalysis of variance (ANOVA) and two-sample t-tests (α = 0.05) were used to compare fitting residuals between prostate regions and between multicompartmental models. T-tests (α = 0.05) were also used to assess differences in compartmental signal-fraction between tissue types and CNR/SIR between conventional DWI and multicompartmental models.ResultsThe lowest BIC was observed from the 4-compartment model, with optimal ADCs of 5.2e-4, 1.9e-3, 3.0e-3, and >3.0e-2 mm2 /sec. Fitting residuals from multicompartmental models were significantly lower than from conventional ADC mapping (P < 0.05). Residuals were lowest in the peripheral zone and highest in tumors. Tumor tissue showed the largest reduction in fitting residual by increasing model order. Tumors had a greater proportion of signal from compartment 1 than normal tissue (P < 0.05). Tumor CNR and SIR were greater on compartment-1 signal maps than conventional DWI (P < 0.05) and increased with model order.Data conclusionThe 4-compartment signal model best described diffusion in the prostate. Compartmental signal contributions revealed by this model may improve assessment of prostate cancer. Level of Evidence 3 Technical Efficacy Stage 3 J. MAGN. RESON. IMAGING 2021;53:628-639.

Dataset Information

Expression of ribosomal proteins in normal and cancerous human prostate tissue.

Publications

Expression of ribosomal proteins in normal and cancerous human prostate tissue.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets