scholarly journals Analytical Validation of Serum Proteomic Profiling for Diagnosis of Prostate Cancer: Sources of Sample Bias

2008 ◽  
Vol 54 (1) ◽  
pp. 44-52 ◽  
Author(s):  
Dale McLerran ◽  
William E Grizzle ◽  
Ziding Feng ◽  
William L Bigbee ◽  
Lionel L Banez ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Protein Profiling ◽  
Proteomic Profiling ◽  
Serum Samples ◽  
Test Set ◽  
Decision Algorithm ◽  
Validation Test ◽  
Using Data ◽  
Stage 1 ◽  
And Control

Abstract Background: This report and a companion report describe a validation of the ability of serum proteomic profiling via SELDI-TOF mass spectrometry to detect prostatic cancer. Details of this 3-stage process have been described. This report describes the development of the algorithm and results of the blinded test for stage 1. Methods: We derived the decision algorithm used in this study from the analysis of serum samples from patients with prostate cancer (n = 181) and benign prostatic hyperplasia (BPH) (n = 143) and normal controls (n = 220). We also derived a validation test set from a separate, geographically diverse set of serum samples from 42 prostate cancer patients and 42 controls without prostate cancer. Aliquots were subjected to randomization and blinded analysis, and data from each laboratory site were subjected to the decision algorithm and decoded. Results: Using the data collected from the validation test set, the decision algorithm was unsuccessful in separating cancer from controls with any predictive utility. Analysis of the experimental data revealed potential sources of bias. Conclusion: The ability of the decision algorithm to successfully differentiate between prostate cancer, BPH, and control samples using data derived from serum protein profiling was compromised by bias.

Serum Protein Profiling Distinguishes BCR-ABL+ CML from Normal and Neutrophilia Cases.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 4871-4871
Author(s):  
Azim M. Mohamedali ◽  
Satyaji Sahu ◽  
Nicholas Shaun B. Thomas ◽  
Ghulam J. Mufti
Keyword(s):  
Serum Proteins ◽  
Peptide Mass Fingerprinting ◽  
Protein Profiling ◽  
Sample Collection ◽  
Serum Samples ◽  
Metal Affinity ◽  
Peptide Mass ◽  
Sds Page ◽  
And Control ◽  
Normal Controls

Abstract We sought to identify additional biomarkers for chronic myelogenous leukaemia (CML) that could be an aid to early diagnosis and also yield novel antigens for immunotherapy. To this end, we screened patient serum samples at presentation against hematologically normal controls as well as patients with neutrophilia using Surface Enhanced Laser Desorption/Ionization technology (SELDI; Ciphergen ProteinChip series 4000). A total of 84 retrospective and prospective serum samples were analysed: presentation −28, reactive neutrophilia (>15x109 neutrophils/L) − 24 and hematopoietic normal controls − 33. Patients were initially screened by routine cytogenetics and in some cases with qPCR for the BCR-ABL breakpoint. The sera samples were evaluated on 4 different array surfaces and the Immobilised Metal Affinity (IMAC) array was chosen as it bound serum proteins that distinguished CML from normal controls. As little as 1 μl serum was sufficient for each analysis. Biomarker artefacts due to variations in sample collection procedures were ruled out by analysing sera (n=4) from each group at the time of collection and 3 and 6 hours post collection. There were no significant differences in any of the biomarkers at any of the time points. The spectrum of proteins obtained from each of the 84 serum samples was averaged from duplicate runs per experiment. Using the Ciphergen Express program, a panel of 5 proteins were significantly differentially expressed in CML versus the reactive neutrophilia and normal hematopoietic controls (p<0.001). These proteins were identified by a combination of purification techniques using Q HyperD F columns, desalting using reverse phase C-18 beads and isolating the biomarker by 1D-SDS PAGE. The biomarkers were identified by peptide mass fingerprinting and confirmed by Tandem MS sequencing. These were Albumin fragment − 2.8Kd (p< 3.5 x 10−5, ROC=0.78), Fibrinogen fragments − 5.3Kd (p< 6.25 x 10−10, ROC=0.07) and 5.9Kd (p< 9.6 x 10−8, ROC=0.14), Complement 3a precursor fragment − 8.9Kd (p< 0.0015, ROC= 0.70), Platelet basic protein precursor − 10.2Kd (p< 1.5 x 10−4, ROC=0.73) and Lysozyme − 14.6Kd (p=0, ROC=0.92). Biomarkers 3, 4 and 5 were also verified by antibody capture experiments using NP-20 arrays. In a blinded test set of sera, CML, normal and neutrophilia samples were correctly classified 27/28 (96%), 32/32 (100%), 20/24 (83%) respectively using a combination of the 5.3Kd, 10.2 Kd and the 14.6 Kd markers (Biomaker Pattern software). The algorithm correctly classified 21 new samples as CML (7/8) and control (10/13). The 1/8 CML was misclassified for technical reasons. Therefore, a small number of serum biomarkers in as little as 1 μl serum can be used to distinguish between patients with CML and neutrophilia or hematopoietic normal controls. Similar analyses may be applicable to other more heterogeneous hematological malignancies.

scholarly journals Pre-analytical-related variability influencing serum peptide profiles demonstrated in a mass spectrometry-based search for colorectal and prostate cancer biomarkers.

2013 ◽  
Vol 60 (3) ◽  
Author(s):  
Jakub Karczmarski ◽  
Tymon Rubel ◽  
Michal Mikula ◽  
Jan Wolski ◽  
Andrzej Rutkowski ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
Complement C3 ◽  
Blood Proteins ◽  
Healthy Individuals ◽  
Clotting Time ◽  
Serum Samples ◽  
Colonoscopic Examination ◽  
Apolipoprotein A ◽  
And Control

Although the degradome, which comprises proteolytic fragments of blood proteins, presents a potential source of diagnostic biomarkers, studies on cancer peptide biomarkers have provided inconsistent conclusions. In the present study, we reevaluated the usefulness of serum degradome analyses for searching peptide cancer biomarker candidates. Particular attention was paid to pre-analytical factors influencing the variability of determined peptide levels, including clotting time and control group selection. Studies were conducted on 44 and 86 serum samples collected from cancer patients and healthy individuals, respectively, using liquid chromatography electrospray ionization mass spectrometry (LC-ESI-MS)-based analyses. We identified 1373 unique peptides, nearly 40% of which originated from five blood proteins: fibrinogen alpha chain, apolipoprotein A-IV (APOA4), complement C3, apolipoprotein A-I, and alpha-1-antitrypsin. A set of 118 and 88 peptides exhibited highly significant differences (adjusted p-value ≤ 0.01 and fold change ≥ 2) in pair-wise comparisons of control vs. prostate cancer and control vs. colorectal cancer, respectively, with 37 peptides displaying a consistent direction of change for these pair-wise comparisons. The levels of 67 peptides differed significantly in serum samples collected from healthy individuals immediately prior to colonoscopy and those who underwent colonoscopic examination at least four weeks earlier. Of them, 49 peptides originated from APOA4. Whereas earlier studies, including ours, have utilized fragments of fibrinopeptide A (FPA) to distinguish cancer from healthy cases, here we show that their absolute abundance is a sensitive indicator of clotting time. These observations may have implications for future serum peptidome studies since these issues have not previously been recognized.

scholarly journals SELDI-TOF MS Whole Serum Proteomic Profiling with IMAC Surface Does Not Reliably Detect Prostate Cancer

2008 ◽  
Vol 54 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Dale McLerran ◽  
William E Grizzle ◽  
Ziding Feng ◽  
Ian M Thompson ◽  
William L Bigbee ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Sample Selection ◽  
Companion Paper ◽  
Proteomic Profiling ◽  
Decision Algorithm ◽  
Bodily Fluids ◽  
Spectral Peaks ◽  
Detect Prostate Cancer ◽  
Negative Controls ◽  
Tof Ms

Abstract Background: The analysis of bodily fluids using SELDI-TOF MS has been reported to identify signatures of spectral peaks that can be used to differentiate patients with a specific disease from normal or control patients. This report is the 2nd of 2 companion articles describing a validation study of a SELDI-TOF MS approach with IMAC surface sample processing to identify prostatic adenocarcinoma. Methods: We sought to derive a decision algorithm for classification of prostate cancer from SELDI-TOF MS spectral data from a new retrospective sample cohort of 400 specimens. This new cohort was selected to minimize possible confounders identified in the previous study described in the companion paper. Results: The resulting new classifier failed to separate patients with prostate cancer from biopsy-negative controls; nor did it separate patients with prostate cancer with Gleason scores <7 from those with Gleason scores ≥7. Conclusions: In this, the 2nd stage of our planned validation process, the SELDI-TOF MS–based protein expression profiling approach did not perform well enough to advance to the 3rd (prospective study) stage. We conclude that the results from our previous studies—in which differentiation between prostate cancer and noncancer was demonstrated—are not generalizable. Earlier study samples likely had biases in sample selection that upon removal, as in the present study, resulted in inability of the technique to discriminate cancer from noncancer cases.

scholarly journals DNA tetrahedron-mediated immune-sandwich assay for rapid and sensitive detection of PSA through a microfluidic electrochemical detection system

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Dezhi Feng ◽  
Jing Su ◽  
Yi Xu ◽  
Guifang He ◽  
Chenguang Wang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Reaction Time ◽  
Electrochemical Detection ◽  
Detection System ◽  
Detection Performance ◽  
Pdms Layer ◽  
Microfluidic Chips ◽  
Serum Samples ◽  
Gold Nanoflowers ◽  
Dna Tetrahedron

AbstractProstate-specific antigen (PSA) is the most widely used biomarker for the early diagnosis of prostate cancer. Existing methods for PSA detection are burdened with some limitations and require improvement. Herein, we developed a novel microfluidic–electrochemical (μFEC) detection system for PSA detection. First, we constructed an electrochemical biosensor based on screen-printed electrodes (SPEs) with modification of gold nanoflowers (Au NFs) and DNA tetrahedron structural probes (TSPs), which showed great detection performance. Second, we fabricated microfluidic chips by DNA TSP-Au NF-modified SPEs and a PDMS layer with designed dense meandering microchannels. Finally, the μFEC detection system was achieved based on microfluidic chips integrated with the liquid automatic conveying unit and electrochemical detection platform. The μFEC system we developed acquired great detection performance for PSA detection in PBS solution. For PSA assays in spiked serum samples of the μFEC system, we obtained a linear dynamic range of 1–100 ng/mL with a limit of detection of 0.2 ng/mL and a total reaction time <25 min. Real serum samples of prostate cancer patients presented a strong correlation between the “gold-standard” chemiluminescence assays and the μFEC system. In terms of operation procedure, cost, and reaction time, our method was superior to the current methods for PSA detection and shows great potential for practical clinical application in the future.

scholarly journals THU0296 PROTEIN PROFILING IN INDIVIDUALS BEFORE ONSET OF ANCA-ASSOCIATED VASCULITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 376.2-376
Author(s):  
E. Berglin ◽  
A. Esberg ◽  
J. Dahlqvist ◽  
J. Sjöwall ◽  
A. Lundquist ◽  
...  
Keyword(s):  
Immune System ◽  
Growth Factor ◽  
Random Forest ◽  
Symptom Onset ◽  
Partial Least Square ◽  
Protein Profiling ◽  
Serum Samples ◽  
Anca Associated Vasculitis ◽  
Significant Difference ◽  
Novel Biomarkers

Background:Etiology and pathogenesis of ANCA-associated vasculitis (AAV) is multifactorial and understanding of the processes leading from a healthy immune system to autoimmunity and on to debut of symptoms in AAV is rudimentary.Objectives:To identify inflammatory proteins related to the early processes preceding AAV development, and potential novel biomarkers, using large-scale protein analysesMethods:The Swedish National Patient Register of in-patient carevand the Swedish Cause of Death Register with discharge diagnosis from ICD-9 and-10 for AAV were co-analysed with the registers of 4 different blood biobanks to identify AAV individuals with available samples predating onset of symptom. Of the pre-AAV cases 86 (36 male, 50 female; mean age (SD); 51.9 (16.9) years) were identified with at least one plasma or serum sample (28 plasma, and 100 serum) pre-dating symptom onset (mean (SD); -4.3 (3.1) years), and 14 had 2-3 samples. Serum and plasma control samples matched for sex, age and sampling date were identified (n=198; 82 male, 116 female; mean age (SD); 51.9±15.9 years). The samples were analysed for levels of 92 proteins using proximity extension assay (OLINK inflammation panel, SciLifeLab, Uppsala, Sweden). Data were analysed using routine statistical methods, random forest and Partial Least square-discriminant analysis (PLS-DA).Results:As previously described for the assay significant difference between plasma and serum samples were observed both in pre-AAV individuals and controls. In pre-AAV plasma samples significantly increased concentrations of interleukin (IL)-2, chemokine ligand (CCL)-4, fibroblast growth factor (FGF)21, IL-4 and CCL20 were found closer to symptom onset, (<5 years) than later (> 5 years) and compared with controls. In serum tumor necrosis factor receptor superfamily member (TNFRSF)9, CXCL9, osteoprotegerin and vascular endothelial growth factor-A were significantly increased <5 years before onset vs. later (>5 years) and compared with controls. PLS-DA score scattered plot separated the pre-AAV individuals from healthy controls (R2=0.26), with significantly increased levels of CCL23, CXCL5, and matrix metalloproteinases-1 (MMP-1),transforming growth factor-ß, orosomucoid, en-rage (S100A12) and IL-7 and decreased FGF-19 level in serum. Binary logistic regression analyses comparing tertiles for these proteins confirmed significantly increased odds ratios for disease development of CCL23, CXCL5 and MMP-1. The findings were confirmed in random forest analysis where these factors were among the 20 most discriminatory factors between pre-symptomatic AAV and controls.Conclusion:In serum samples collected years before symptom onset of AAV, proteins involved in immune system activation were increased, suggesting that the inflammatory process is initiated long before clinical manifestations of the disease appear. These findings propose the elevated proteins as novel biomarkers for disease progression.References:[1]Watts et al. Ann Rheum Dis 2007;66:222-22Acknowledgments:Vasculitis Foundation, USADisclosure of Interests:Ewa Berglin: None declared, Anders Esberg: None declared, Johanna Dahlqvist: None declared, Johanna Sjöwall: None declared, Anders Lundquist: None declared, Kristina Lejon: None declared, Ingegerd Johansson: None declared, Aladdin J Mohammad Speakers bureau: lecture fees from Roche and Elli Lilly Sweden, PI (GiACTA study), Solbritt Rantapää Dahlqvist: None declared

Proteomic profiling the molecular signatures of plectranthoic acid in prostate cancer cells

2021 ◽  
pp. 104311
Author(s):  
Nosheen Akhtar ◽  
Sumra Wajid Abbasi ◽  
Samina Rubnawaz ◽  
Laila Jafri ◽  
Rehana Rani
Keyword(s):  
Prostate Cancer ◽  
Cancer Cells ◽  
Molecular Signatures ◽  
Proteomic Profiling ◽  
Prostate Cancer Cells

scholarly journals Mast Cell-Derived SAMD14 is a Novel Regulator of the Human Prostate Tumor Microenvironment

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1237
Author(s):  
Linda K. H. Teng ◽  
Brooke A. Pereira ◽  
Shivakumar Keerthikumar ◽  
Cheng Huang ◽  
Birunthi Niranjan ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Extracellular Matrix ◽  
Tumor Microenvironment ◽  
Suppressor Gene ◽  
Prostate Tumor ◽  
Human Prostate ◽  
Proteomic Profiling ◽  
Putative Tumor Suppressor Gene ◽  
Invasion And Migration ◽  
And Migration

Mast cells (MCs) are important cellular components of the tumor microenvironment and are significantly associated with poor patient outcomes in prostate cancer and other solid cancers. The promotion of tumor progression partly involves heterotypic interactions between MCs and cancer-associated fibroblasts (CAFs), which combine to potentiate a pro-tumor extracellular matrix and promote epithelial cell invasion and migration. Thus far, the interactions between MCs and CAFs remain poorly understood. To identify molecular changes that may alter resident MC function in the prostate tumor microenvironment, we profiled the transcriptome of human prostate MCs isolated from patient-matched non-tumor and tumor-associated regions of fresh radical prostatectomy tissue. Transcriptomic profiling revealed a distinct gene expression profile of MCs isolated from prostate tumor regions, including the downregulation of SAMD14, a putative tumor suppressor gene. Proteomic profiling revealed that overexpression of SAMD14 in HMC-1 altered the secretion of proteins associated with immune regulation and extracellular matrix processes. To assess MC biological function within a model of the prostate tumor microenvironment, HMC-1-SAMD14+ conditioned media was added to co-cultures of primary prostatic CAFs and prostate epithelium. HMC-1-SAMD14+ secretions were shown to reduce the deposition and alignment of matrix produced by CAFs and suppress pro-tumorigenic prostate epithelial morphology. Overall, our data present the first profile of human MCs derived from prostate cancer patient specimens and identifies MC-derived SAMD14 as an important mediator of MC phenotype and function within the prostate tumor microenvironment.

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