Dataset Information

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers.

ABSTRACT:

Background

Lower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker.

Methods

Within- and between-subject variability of MALDI-TOF/MS-based peptidomic urine and serum analyses were evaluated in 20 and 15 healthy donors, respectively. Normalizations and approaches for accounting below limit of detection (LOD) values were utilized to enhance reproducibility, while Monte Carlo experiments were performed to verify whether measurement error can be dealt with LOD data. Post-prostatic massage urine and serum samples from 148 LUTS patients were analysed using MALDI-TOF/MS. Regression-calibration and simulation and extrapolation methods were used to derive the unbiased association between peptidomic features and PCa.

Results

Although the median normalized peptidomic variability was 24.9%, the within- and between-subject variability showed that median normalization, LOD adjustment, and log₂ data transformation were the best combination in terms of reliability; in measurement error conditions, intraclass correlation coefficient was a reliable estimate when the LOD/2 was substituted for below LOD values. In the patients studied, 43 peptides were shared by the urine and serum, and several features were found to be associated with PCa. Only few serum features, however, show statistical significance after the multiple testing procedures were completed. Two serum fragmentation patterns corresponded to the complement C4-A.

Conclusions

MALDI-TOF/MS serum peptidome profiling was more efficacious with respect to post-prostatic massage urine analysis in discriminating PCa.

SUBMITTER: Padoan A

PROVIDER: S-EPMC6060548 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers.

Padoan Andrea A Basso Daniela D Zambon Carlo-Federico CF Prayer-Galetti Tommaso T Arrigoni Giorgio G Bozzato Dania D Moz Stefania S Zattoni Filiberto F Bellocco Rino R Plebani Mario M

Clinical proteomics 20180725

<h4>Background</h4>Lower urinary tract symptoms (LUTS) and prostate specific antigen-based parameters seem to have only a limited utility for the differential diagnosis of prostate cancer (PCa). MALDI-TOF/MS peptidomic profiling could be a useful diagnostic tool for biomarker discovery, although reproducibility issues have limited its applicability until now. The current study aimed to evaluate a new MALDI-TOF/MS candidate biomarker.<h4>Methods</h4>Within- and between-subject variability of MALD ...[more]

PMID: 30065622

Similar Datasets

Project description:Matrix‑assisted laser desorption/ionization time‑of‑flight mass spectrometry (MALDI‑TOF‑MS) was employed to analyze differential serum and urine peptides in patients with small cell lung cancer (SCLC) and healthy individuals, and SCLC diagnostic classification models were constructed. Serum and urine samples from 72 patients with SCLC, age‑ and gender‑matched with 72 healthy individuals, were divided into training and testing sets in a 3:1 ratio. Serum and urine peptides were extracted using copper ion‑chelating nanomagnetic beads, and mass spectra were obtained using MALDI‑TOF‑MS. Peptide spectra for the training set were analyzed, and the classification model was constructed using ClinProTools (CPT). The testing set was used for blinded model validation. For training‑set sera, 122 differential peptide signal peaks with a mass of 0.8‑10 kDa were observed, and 19 peptides showed significantly different expression [P<0.0005; area under curve (AUC) ≥0.80]. CPT screened 5 peptide peaks (0.8114, 0.83425, 1.86655, 4.11133 and 5.81192 kDa) to construct the classification model. The testing set was used for the blinded validation, which had 95.0% sensitivity and 90.0% specificity. For the training‑set urine, 132 differential peptide signal peaks with m/z ratios of 0.8‑10 kDa were observed, and 8 peptides had significantly different expression (P<0.0005; AUC ≥0.80). Then, 5 peaks (1.0724, 2.37692, 2.7554, 4.75475 and 4.7949 kDa) were used for classification model construction. The testing set was used for 36 blinded validation, which had 85.0% sensitivity and 80.0% specificity. Among the differential peptides, 3 had the same significant peaks at 2.3764, 0.8778 and 0.8616 kDa, identified as fibrinogen α, glucose‑6‑phosphate isomerase and cyclin‑dependent kinase‑1, respectively. The present study highlighted the differences that exist in serum and urine peptides between patients with SCLC and healthy individuals. Serum and urine peptide diagnostic classification models could be constructed using MALDI‑TOF‑MS, and showed high sensitivity and specificity.

Project description:Biomarkers are urgently required to support current histological staging to provide additional accuracy in stratifying colorectal cancer (CRC) patients according to risk of spread to properly assign adjuvant chemotherapy after surgery. Chemotherapy is given to patients with stage III to reduce the risk of recurrence but is controversial in stage II patients. Up to 25% of stage II patients will relapse within 5 years after tumor removal and when this occurs cure is seldom possible. The aim of this study was to identify protein biomarkers to stratify risk of spread of CRC patients. Laser micro-dissection was used to isolate cancer cells from primary colorectal tumors of stage II patients which did or did not metastasize within 5 years after surgical resection. Protein expression differences between two groups of tumors were profiled by 2D-DIGE with saturation CyDye labeling and identified using MALDI-TOF mass spectrometry. Evaluation of protein candidates was conducted using tissue micro array (TMA) immunohistochemistry on 125 colorectal tumor tissue samples of different stages. A total of 55 differentially expressed proteins were identified. Ten protein biomarkers were chosen based on p value and ratio between non metastasized and metastazised groups and evaluated on 125 tissues using TMA immunohistochemistry. Expression of HLAB, protein 14-3-3?, LTBP3, ADAMTS2, JAG2 and NME2 on tumour cells was significantly associated with clinical parameters related to tumour progression, invasion and metastasis. Kaplan-Meier survival curve showed strong expression of six proteins was associated with good CRC specific survival. Expression of HLAB, ADAMTS2, LTBP3, JAG2 and NME2 on tumour cells, was associated with tumour progression and invasion, metastasis and CRC specific survival may serve as potential biomarkers to stratify CRC patients into low and high risk of tumour metastasis. Combined methods of laser microdissection, 2D DIGE with saturation labelling and MALDI-TOF MS proved to be resourceful techniques capable of identifying protein biomarkers to predict risk of spread of CRC to liver.

Project description:BACKGROUND:Identification of predictive molecular alterations in lung adenocarcinoma is essential for accurate therapeutic decisions. Although several molecular approaches are available, a number of issues, including tumor heterogeneity, frequent material scarcity, and the large number of loci to be investigated, must be taken into account in selecting the most appropriate technique. MALDI-TOF mass spectrometry (MS), which allows multiplexed genotyping, has been adopted in routine diagnostics as a sensitive, reliable, fast, and cost-effective method. Our aim was to test the reliability of this approach in detecting targetable mutations in non-small cell lung cancer (NSCLC). In addition, we also analyzed low-quality samples, such as cytologic specimens, that often, are the unique source of starting material in lung cancer cases, to test the sensitivity of the system. METHODS:We designed a MS-based assay for testing 158 mutations in the EGFR, KRAS, BRAF, ALK, PIK3CA, ERBB2, DDR2, AKT, and MEK1 genes and applied it to 92 NSCLC specimens and 13 liquid biopsies from another subset of NSCLC patients. We also tested the sensitivity of the method to distinguish low represented mutations using serial dilutions of mutated DNA. RESULTS:Our panel is able to detect the most common NSCLC mutations and the frequency of the mutations observed in our cohort was comparable to literature data. The assay identifies mutated alleles at frequencies of 2.5-10%. In addition, we found that the amount of DNA template was irrelevant to efficiently uncover mutated alleles present at high frequency. However, when using less than 10 ng of DNA, the assay can detect mutations present in at least 10% of the alleles. Finally, using MS and a commercial kit for RT-PCR we tested liquid biopsy from 13 patients with identified mutations in cancers and detected the mutations in 4 (MS) and in 5 samples (RT-PCR). CONCLUSIONS:MS is a powerful method for the routine predictive tests of lung cancer also using low quality and scant tissues. Finally, after appropriate validation and improvement, MS could represent a promising and cost-effective strategy for monitoring the presence and percentage of the mutations also in non-invasive sampling.

Project description:BackgroundLC-MALDI-TOF/TOF analysis is a potent tool in biomarkers discovery characterized by its high sensitivity and high throughput capacity. However, methods based on MALDI-TOF/TOF for biomarkers discovery still need optimization, in particular to reduce analysis time and to evaluate their reproducibility for peak intensities measurement. The aims of this methodological study were: (i) to optimize and critically evaluate each step of urine biomarker discovery method based on Nano-LC coupled off-line to MALDI-TOF/TOF, taking full advantage of the dual decoupling between Nano-LC, MS and MS/MS to reduce the overall analysis time; (ii) to evaluate the quantitative performance and reproducibility of nano-LC-MALDI analysis in biomarker discovery; and (iii) to evaluate the robustness of biomarkers selection.ResultsA pool of urine sample spiked at increasing concentrations with a mixture of standard peptides was used as a specimen for biological samples with or without biomarkers. Extraction and nano-LC-MS variabilities were estimated by analyzing in triplicates and hexaplicates, respectively. The stability of chromatographic fractions immobilised with MALDI matrix on MALDI plates was evaluated by successive MS acquisitions after different storage times at different temperatures.Low coefficient of variation (CV%: 10-22%) and high correlation (R2 > 0.96) values were obtained for the quantification of the spiked peptides, allowing quantification of these peptides in the low fentomole range, correct group discrimination and selection of "specific" markers using principal component analysis. Excellent peptide integrity and stable signal intensity were found when MALDI plates were stored for periods of up to 2 months at +4 degrees C. This allowed storage of MALDI plates between LC separation and MS acquisition (first decoupling), and between MS and MSMS acquisitions while the selection of inter-group discriminative ions is done (second decoupling). Finally the recording of MSMS spectra to obtain structural information was focused only on discriminative ions in order to minimize analysis time.ConclusionContrary to other classical approaches with direct online coupling of chromatographic separation and on the flight MS and/or MSMS data acquisition for all detected analytes, our dual decoupling strategy allowed us to focus on the most discriminative analytes, giving us more time to acquire more replicates of the same urine samples thus increasing detection sensitivity and mass precision.

Dataset Information

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers.

Background

Methods

Results

Conclusions

Publications

MALDI-TOF peptidomic analysis of serum and post-prostatic massage urine specimens to identify prostate cancer biomarkers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets