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Sökning: WFRF:(Luider Theo M.)

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1.
  • Liu, Ning Qing, et al. (författare)
  • Comparative proteome analysis revealing an 11-protein signature for aggressive triple-negative breast cancer
  • Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 1460-2105. ; 106:2
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Clinical outcome of patients with triple-negative breast cancer (TNBC) is highly variable. This study aims to identify and validate a prognostic protein signature for TNBC patients to reduce unnecessary adjuvant systemic therapy.METHODS: Frozen primary tumors were collected from 126 lymph node-negative and adjuvant therapy-naive TNBC patients. These samples were used for global proteome profiling in two series: an in-house training (n = 63) and a multicenter test (n = 63) set. Patients who remained free of distant metastasis for a minimum of 5 years after surgery were defined as having good prognosis. Cox regression analysis was performed to develop a prognostic signature, which was independently validated. All statistical tests were two-sided.RESULTS: An 11-protein signature was developed in the training set (median follow-up for good-prognosis patients = 117 months) and subsequently validated in the test set (median follow-up for good-prognosis patients = 108 months) showing 89.5% sensitivity (95% confidence interval [CI] = 69.2% to 98.1%), 70.5% specificity (95% CI = 61.7% to 74.2%), 56.7% positive predictive value (95% CI = 43.8% to 62.1%), and 93.9% negative predictive value (95% CI = 82.3% to 98.9%) for poor-prognosis patients. The predicted poor-prognosis patients had higher risk to develop distant metastasis than the predicted good-prognosis patients in univariate (hazard ratio [HR] = 13.15; 95% CI = 3.03 to 57.07; P = .001) and multivariable (HR = 12.45; 95% CI = 2.67 to 58.11; P = .001) analysis. Furthermore, the predicted poor-prognosis group had statistically significantly more breast cancer-specific mortality. Using our signature as guidance, more than 60% of patients would have been exempted from unnecessary adjuvant chemotherapy compared with conventional prognostic guidelines.CONCLUSIONS: We report the first validated proteomic signature to assess the natural course of clinical TNBC.
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2.
  • De Marchi, Tommaso, et al. (författare)
  • Annexin-A1 and caldesmon are associated with resistance to tamoxifen in estrogen receptor positive recurrent breast cancer
  • Ingår i: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:3, s. 3098-3110
  • Tidskriftsartikel (refereegranskat)abstract
    • Tamoxifen therapy resistance constitutes a major cause of death in patients with recurrent estrogen receptor (ER) positive breast cancer. Through high resolution mass spectrometry (MS), we previously generated a 4-protein predictive signature for tamoxifen therapy outcome in recurrent breast cancer. ANXA1 and CALD1, which were not included in the classifier, were however the most differentially expressed proteins. We first evaluated the clinical relevance of these markers in our MS cohort, followed by immunohistochemical (IHC) staining on an independent set of tumors incorporated in a tissue microarray (TMA) and regression analysis in relation to time to progression (TTP), clinical benefit and objective response. In order to assess which mechanisms ANXA1 and CALD1 might been involved in, we performed Ingenuity pathway analysis (IPA) on ANXA1 and CALD1 correlated proteins in our MS cohort. ANXA1 (Hazard ratio [HR] = 1.83; 95% confidence interval [CI]: 1.22-2.75; P = 0.003) and CALD1 (HR = 1.57; 95% CI: 1.04-2.36; P = 0.039) based patient stratification showed significant association to TTP, while IHC staining on TMA showed that both ANXA1 (HR = 1.82; 95% CI: 1.12-3.00; P = 0.016) and CALD1 (HR = 2.29; 95% CI: 1.40-3.75; P = 0.001) expression was associated with shorter TTP independently of traditional predictive factors. Pearson correlation analysis showed that the majority of proteins correlated to ANXA1 also correlated with CALD1. IPA indicated that ANXA1 and CALD1 were associated with ER-downregulation and NFκB signaling. We hereby report that ANXA1 and CALD1 proteins are independent markers for tamoxifen therapy outcome and are associated to fast tumor progression.
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3.
  • De Marchi, Tommaso, et al. (författare)
  • Targeted MS Assay Predicting Tamoxifen Resistance in Estrogen-Receptor-Positive Breast Cancer Tissues and Sera
  • Ingår i: Journal of Proteome Research. - : The American Chemical Society (ACS). - 1535-3893. ; 15:4, s. 42-1230
  • Tidskriftsartikel (refereegranskat)abstract
    • We recently reported on the development of a 4-protein-based classifier (PDCD4, CGN, G3BP2, and OCIAD1) capable of predicting outcome to tamoxifen treatment in recurrent, estrogen-receptor-positive breast cancer based on high-resolution MS data. A precise and high-throughput assay to measure these proteins in a multiplexed, targeted fashion would be favorable to measure large numbers of patient samples to move these findings toward a clinical setting. By coupling immunoprecipitation to multiple reaction monitoring (MRM) MS and stable isotope dilution, we developed a high-precision assay to measure the 4-protein signature in 38 primary breast cancer whole tissue lysates (WTLs). Furthermore, we evaluated the presence and patient stratification capabilities of our signature in an independent set of 24 matched (pre- and post-therapy) sera. We compared the performance of immuno-MRM (iMRM) with direct MRM in the absence of fractionation and shotgun proteomics in combination with label-free quantification (LFQ) on both WTL and laser capture microdissected (LCM) tissues. Measurement of the 4-proteins by iMRM showed not only higher accuracy in measuring proteotypic peptides (Spearman r: 0.74 to 0.93) when compared with MRM (Spearman r: 0.0 to 0.76) but also significantly discriminated patient groups based on treatment outcome (hazard ratio [HR]: 10.96; 95% confidence interval [CI]: 4.33 to 27.76; Log-rank P < 0.001) when compared with LCM (HR: 2.85; 95% CI: 1.24 to 6.54; Log-rank P = 0.013) and WTL (HR: 1.16; 95% CI: 0.57 to 2.33; Log-rank P = 0.680) LFQ-based predictors. Serum sample analysis by iMRM confirmed the detection of the four proteins in these samples. We hereby report that iMRM outperformed regular MRM, confirmed our previous high-resolution MS results in tumor tissues, and has shown that the 4-protein signature is measurable in serum samples.
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4.
  • De Marchi, Tommaso, et al. (författare)
  • The advantage of laser-capture microdissection over whole tissue analysis in proteomic profiling studies
  • Ingår i: Proteomics. - : John Wiley and Sons Inc.. - 1615-9861. ; 16:10, s. 85-1474
  • Tidskriftsartikel (refereegranskat)abstract
    • Laser-capture microdissection (LCM) offers a reliable cell population enrichment tool and has been successfully coupled to MS analysis. Despite this, most proteomic studies employ whole tissue lysate (WTL) analysis in the discovery of disease biomarkers and in profiling analyses. Furthermore, the influence of tissue heterogeneity in WTL analysis, nor its impact in biomarker discovery studies have been completely elucidated. In order to address this, we compared previously obtained high resolution MS data from a cohort of 38 breast cancer tissues, of which both LCM enriched tumor epithelial cells and WTL samples were analyzed. Label-free quantification (LFQ) analysis through MaxQuant software showed a significantly higher number of identified and quantified proteins in LCM enriched samples (3404) compared to WTLs (2837). Furthermore, WTL samples displayed a higher amount of missing data compared to LCM both at peptide and protein levels (p-value < 0.001). 2D analysis on co-expressed proteins revealed discrepant expression of immune system and lipid metabolisms related proteins between LCM and WTL samples. We hereby show that LCM better dissected the biology of breast tumor epithelial cells, possibly due to lower interference from surrounding tissues and highly abundant proteins. All data have been deposited in the ProteomeXchange with the dataset identifier PXD002381 (http://proteomecentral.proteomexchange.org/dataset/PXD002381).
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5.
  • Liu, Ning Qing, et al. (författare)
  • Quantitative proteomic analysis of microdissected breast cancer tissues : comparison of label-free and SILAC-based quantification with shotgun, directed, and targeted MS approaches
  • Ingår i: Journal of Proteome Research. - : The American Chemical Society (ACS). - 1535-3893. ; 12:10, s. 41-4627
  • Tidskriftsartikel (refereegranskat)abstract
    • Quantitative proteomics plays an important role in validation of breast-cancer-related biomarkers. In this study, we systematically compared the performance of label-free quantification (LFQ) and SILAC with shotgun and directed methods for quantifying breast-cancer-related markers in microdissected tissues. We show that LFQ leads to slightly higher coefficient of variation (CV) for protein quantification (median CV = 16.3%) than SILAC quantification (median CV = 13.7%) (P < 0.0001), but LFQ method enables ∼60% more protein quantification and is also more reproducible (∼20% more proteins were quantified in all replicate samples). Furthermore, we describe a method to accurately quantify multiple proteins within one pathway, that is, "focal adhesion pathway", in trace amounts of breast cancer tissues using a SILAC-based SRM assay. Using this SILAC-based SRM assay, we precisely quantified five "focal adhesion" proteins with good quantitative precision (CV range: 2.4-5.9%) in replicate whole tissue lysate samples and replicate microdissected samples (CV range: 5.8-16.1%). Our results show that in microdissected breast cancer tissues LFQ in combination with shotgun proteomics performed the best overall and is therefore suitable for both biomarker discovery and validation in these types of specimens. The SILAC-based SRM method can be used for the development of clinically relevant protein assays in tumor biopsies.
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6.
  • De Marchi, Tommaso, et al. (författare)
  • 4-protein signature predicting tamoxifen treatment outcome in recurrent breast cancer
  • Ingår i: Molecular Oncology. - : Elsevier. - 1574-7891. ; 10:1, s. 24-39
  • Tidskriftsartikel (refereegranskat)abstract
    • Estrogen receptor (ER) positive tumors represent the majority of breast malignancies, and are effectively treated with hormonal therapies, such as tamoxifen. However, in the recurrent disease resistance to tamoxifen therapy is common and a major cause of death. In recent years, in-depth proteome analyses have enabled identification of clinically useful biomarkers, particularly, when heterogeneity in complex tumor tissue was reduced using laser capture microdissection (LCM). In the current study, we performed high resolution proteomic analysis on two cohorts of ER positive breast tumors derived from patients who either manifested good or poor outcome to tamoxifen treatment upon recurrence. A total of 112 fresh frozen tumors were collected from multiple medical centers and divided into two sets: an in-house training and a multi-center test set. Epithelial tumor cells were enriched with LCM and analyzed by nano-LC Orbitrap mass spectrometry (MS), which yielded >3000 and >4000 quantified proteins in the training and test sets, respectively. Raw data are available via ProteomeXchange with identifiers PXD000484 and PXD000485. Statistical analysis showed differential abundance of 99 proteins, of which a subset of 4 proteins was selected through a multivariate step-down to develop a predictor for tamoxifen treatment outcome. The 4-protein signature significantly predicted poor outcome patients in the test set, independent of predictive histopathological characteristics (hazard ratio [HR] = 2.17; 95% confidence interval [CI] = 1.15 to 4.17; multivariate Cox regression p value = 0.017). Immunohistochemical (IHC) staining of PDCD4, one of the signature proteins, on an independent set of formalin-fixed paraffin-embedded tumor tissues provided and independent technical validation (HR = 0.72; 95% CI = 0.57 to 0.92; multivariate Cox regression p value = 0.009). We hereby report the first validated protein predictor for tamoxifen treatment outcome in recurrent ER-positive breast cancer. IHC further showed that PDCD4 is an independent marker.
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7.
  • De Marchi, Tommaso, et al. (författare)
  • Global proteomic characterization of microdissected estrogen receptor positive breast tumors
  • Ingår i: Data in Brief. - : Elsevier. - 2352-3409. ; 5, s. 399-402
  • Tidskriftsartikel (refereegranskat)abstract
    • We here describe two proteomic datasets deposited in ProteomeXchange via PRIDE partner repository [1] with dataset identifiers PXD000484 (defined as "training") and PXD000485 (defined as "test") that have been used for the development of a tamoxifen outcome predictive signature [2]. Both datasets comprised 56 fresh frozen estrogen receptor (ER) positive primary breast tumor specimens derived from patients who received tamoxifen as first line therapy for recurrent disease. Patient groups were defined based on time to progression (TTP) after start of tamoxifen therapy (6 months cutoff): 32 good and 24 poor treatment outcome patients were comprised in the training set, respectively. The test set included 41 good and 15 poor treatment outcome patients. All specimens were subjected to laser capture microdissection (LCM) to enrich for epithelial tumor cells prior to high resolution mass spectrometric (MS) analysis. Protein identification and label-free quantification (LFQ) were performed with MaxQuant software package [3]. A total of 3109 and 4061 proteins were identified and quantified in the training and test set, respectively. We here present the first public proteomic dataset analyzing ER positive recurrent breast cancer by LCM coupled to high resolution MS.
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8.
  • Rosenling, Therese, et al. (författare)
  • The Impact of Delayed Storage on the Measured Proteome and Metabolome of Human Cerebrospinal Fluid
  • 2011
  • Ingår i: Clinical Chemistry. - 0009-9147 .- 1530-8561. ; 57:12, s. 1703-1711
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Because cerebrospinal fluid (CSF) is in close contact with diseased areas in neurological disorders, it is an important source of material in the search for molecular biomarkers. However, sample handling for CSF collected from patients in a clinical setting might not always be adequate for use in proteomics and metabolomics studies. METHODS: We left CSF for 0, 30, and 120 min at room temperature immediately after sample collection and centrifugation/removal of cells. After tryptic digestion at 2 laboratories by nanoLC Orbitrap-MS and chipLC QTOF-MS, CSF proteomes were analyzed. Metabolome analysis was performed at 3 laboratories by NMR, GC-MS, and LC-MS. Targeted analyses of cystatin C and albumin were performed by LC-MS/MS in the selected reaction monitoring mode. RESULTS: We did not find significant changes in the measured proteome and metabolome of CSF stored at room temperature after centrifugation, except for 2 peptides and 1 metabolite, 2,3,4-trihydrobutanoic acid, of 5780 identified peptides and 93 identified metabolites. A sensitive protein stability marker, cystatin C, was not affected. CONCLUSIONS: The measured proteome and metabolome of centrifuged, human CSF is stable at room temperature for up to 2 hours. We cannot exclude, however, that changes undetectable with our current methodology, such as denaturation or proteolysis, might occur due to sample handling conditions. The stability we observed gives laboratory personnel at the collection site sufficient time to aliquot samples before freezing and storage at -80 °C.
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9.
  • Stoop, Marcel P, et al. (författare)
  • Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples.
  • 2010
  • Ingår i: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 9:9, s. 2063-75
  • Tidskriftsartikel (refereegranskat)abstract
    • The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.
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10.
  • Rosenling, Therese, 1980-, et al. (författare)
  • The effect of preanalytical factors on stability of the proteome and selected metabolites in cerebrospinal fluid (CSF).
  • 2009
  • Ingår i: Journal of Proteome Research. - 1535-3893 .- 1535-3907. ; 8:12, s. 5511-22
  • Tidskriftsartikel (refereegranskat)abstract
    • To standardize the use of cerebrospinal fluid (CSF) for biomarker research, a set of stability studies have been performed on porcine samples to investigate the influence of common sample handling procedures on proteins, peptides, metabolites and free amino acids. This study focuses at the effect on proteins and peptides, analyzed by applying label-free quantitation using microfluidics nanoscale liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (chipLC-MS) as well as matrix-assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FT-ICR-MS) and Orbitrap LC-MS/MS to trypsin-digested CSF samples. The factors assessed were a 30 or 120 min time delay at room temperature before storage at -80 degrees C after the collection of CSF in order to mimic potential delays in the clinic (delayed storage), storage at 4 degrees C after trypsin digestion to mimic the time that samples remain in the cooled autosampler of the analyzer, and repeated freeze-thaw cycles to mimic storage and handling procedures in the laboratory. The delayed storage factor was also analyzed by gas chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) for changes of metabolites and free amino acids, respectively. Our results show that repeated freeze/thawing introduced changes in transthyretin peptide levels. The trypsin digested samples left at 4 degrees C in the autosampler showed a time-dependent decrease of peak areas for peptides from prostaglandin D-synthase and serotransferrin. Delayed storage of CSF led to changes in prostaglandin D-synthase derived peptides as well as to increased levels of certain amino acids and metabolites. The changes of metabolites, amino acids and proteins in the delayed storage study appear to be related to remaining white blood cells. Our recommendations are to centrifuge CSF samples immediately after collection to remove white blood cells, aliquot, and then snap-freeze the supernatant in liquid nitrogen for storage at -80 degrees C. Preferably samples should not be left in the autosampler for more than 24 h and freeze/thaw cycles should be avoided if at all possible.
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