Mass Spectrometry-GUided Immunoassay DEvelopment (MS-GUIDE)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Sandra Goetze
PROVIDER: PXD016976 | panorama | Thu Apr 14 00:00:00 BST 2022
REPOSITORIES: PanoramaPublic
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Project description:Targeted proteomics dataset (PRM) investigating four potential biomarker candidates of high-grade serous ovarian carcinoma (FGL2, LGALS3BP, LTBP1, TIMP1) and the established biomarker CA125 in 212 serum samples taken from 34 HGSC patients during disease progression.
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Project description:Diagnosis of ovarian cancer at an early stage is the most important determinant of survival. Thus, there is a clear need for novel biomarkers to improve diagnostic and prognostics that may better inform on therapeutic strategies. We have conducted a discovery study using label-free quantitative mass spectrometry (LFQ) to identify potential biomarker candidates in urine from individual ovarian cancer patients. LFQ analyses identified 4394 proteins (16397 peptides) in urine samples (n=20), 23 of which were significantly elevated in the malignant patient group compared to patients with benign disease. To validate these changes, we used Parallel Reaction Monitoring (PRM) to investigate their abundance in an independent cohort (n=20) of patient urine samples. Seven of the ten proteins were significantly enriched in the ovarian cancer patient samples; amongst these were established ovarian cancer markers WFDC2 (HE4) and Mesothelin (MSLN), validating our approach. This is the first application of a LFQ-PRM workflow to identify and validate ovarian cancer-specific biomarkers in urine samples.
2018-02-15 | PXD007962 | Pride
Project description:The biological tumor samples (ie, breast tumor specimens) consisted of freshly frozen breast tumors from a population-based cohort of 315 women representing 65% of all breast cancers resected in Uppsala County, Sweden, from January 1, 1987 to December 31, 1989. Estrogen receptor status was determined by biochemical assay as part of the routine clinical procedure. An experienced pathologist determined the Elston-Ellis grades of the tumors, classifying the tumors into low, medium and high-grade tumors. The clinico-pathological characteristics accompanying each tumor include p53 status, ER status, tumor grade, lymph node status and patient age. Keywords: Tumor sample comparisons
2005-10-21 | GSE3494 | GEO
Project description:The biological tumor samples (ie, breast tumor specimens) consisted of freshly frozen breast tumors from a population-based cohort of 315 women representing 65% of all breast cancers resected in Uppsala County, Sweden, from January 1, 1987 to December 31, 1989. Estrogen receptor status was determined by biochemical assay as part of the routine clinical procedure. An experienced pathologist determined the Elston-Ellis grades of the tumors, classifying the tumors into low, medium and high-grade tumors. The clinico-pathological characteristics accompanying each tumor include p53 status, ER status, tumor grade, lymph node status and patient age. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.
2008-04-04 | E-GEOD-3494 | biostudies-arrayexpress
Project description:High grade serous ovarian carcinoma (HGSC) is the most common and lethal subtype of gynecologic malignancy in women. The current standard of treatment combines cytoreductive surgery and chemotherapy. Despite the efficacy of initial treatment, most patients develop cancer recurrence, and 70% of patients die within 5-years of initial diagnosis. CA125 is the current FDA-approved biomarker used in the clinic to monitor response to treatment and recurrence. Although increasing levels of CA125 precede clinical symptoms of recurrence, often second-look surgeries often reveal microscopic and macroscopic tumors present during remission. Here, we describe a novel strategy for the discovery of serum biomarkers aimed at earlier detection of cancer recurrence. We combined HGSC patient-derived xenograft models, chemoproteomic enrichment of N-glycosylated peptides and systematic development of targeted proteomics assays for rapid biomarker identification and orthogonal verification. The verification of candidates in two independent, longitudinal serum cohorts from HGSC patients (n=96 serum samples) identified four novel biomarker candidates for earlier detection of HGSC recurrence.
2018-08-27 | MSV000082853 | MassIVE
Project description:Ovarian cancer is the leading cause of death in gynecological diseases, and has been considered as one of the most fatal cancers due to lack of reliable detection strategy in the early stage. Therefore the capability to detect the morbidity initiation with an sensitive and effective approach is one of the most desirable goals for curing ovarian cancer. In this study, we used microarray technology for salivary mRNA biomarkers discovery, and evaluated the performance and translational utilities of discovered markers from a clinical study using an independent sample cohort . We used microarrays to profile and compare the gene expressions between ovairan cancer patient and matched controls, and identified seven down-regulated genes after the validation study. To find salivary transcriptomic biomarkers for ovarian cancer, salivary transcriptomes in 11 ovarian cancer patients and 11 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 array, and followed by t-test and fold-change analyses. The biomarker candidates selected from the microarray results were subjected to clinical validation using an independent sample cohort by RT-qPCR. The prediction power of biomarkers was analyzed by logistic regression approach
2011-05-12 | E-GEOD-29220 | biostudies-arrayexpress
Project description:Introduction Thoracic aortic aneurysms frequently go undetected until serious complications like acute dissections or ruptures arise. Therefore, this study aims to identify potential blood circulating biomarkers enabling an easy and early diagnosis of thoracic aortic disease. Methods Potential biomarker candidates were identified through two different techniques, untargeted and targeted proteomic as well as exosome analyses. The biomarker levels were compared between two patient groups with thoracic aortic aneurysms and two control groups without thoracic aortic disease. In total, 80 patients (TAA group (n=40) vs. control group (n=40)) were matched for untargeted and targeted proteome analysis, and 85 for exosome analysis (TAA group (n=42) vs. control group (n=43)), based on the availability of blood samples and excised aortic tissue. Levels of biomarker candidates were correlated with aortic diameter, patient age, and histological alterations in aortic tissue using linear and logistic regression models. Results The untargeted proteomic and exosome analysis identified 1,037 and 1,077 proteins, respectively, of which 11 and 28 proteins showed significant differences in concentration between the study groups. Of these, 9 proteins correlated with the aortic diameter: ACTN1 (Regression coefficient B=1.633, p<0.001), CRP (B=0.001, p=0.004), TGM3 (B=-0.293, p=0.010), KRT84 (B=-0.477, p=0.010), IGHG3 (-0.267, p=0.018), DPYSL2 (B=0.644, p=0.020), TSPAN8 (B-0.838, p=0.042), IGKV3D-11 (B=-0.242, p=0.046), and VDAC1 (B=-0.491, p=0.047). Moreover, IGKV3D-11 (B=-3.257, p=0.029), IGHG3 (B=-0.003, p=0.034), and APOC3 (B=-2.104, p=0.037) showed significant correlations with the grade of aortic medial layer degeneration. None of the proteins correlated with patient age. Conclusion The study identified 9 biomarker candidates correlating with the aortic diameter. To enable the clinical use for diagnosis and prognostic assessment, these biomarkers need to be validated in larger external cohorts.
2026-05-13 | PXD061606 | Pride
Project description:Pancreatic ductal adenocarcinoma (PDAC) suffers from lack of an effective diagnostic method, limiting improvement in patient survival. Although the FDA-approved biomarker CA19-9 has been used for detection and surveillance of PDAC, its clinical utility is generally regarded to be limited due to its suboptimal diagnostic performance. Liquid chromatography-mass spectrometry (LC-MS) has emerged as a burgeoning technology in clinical proteomics, and identified a plethora of protein biomarker candidates for PDAC. Yet few if any has successfully transitioned into clinical practice. This translational standstill is owed partly to the limited considerations of practical needs and perspectives of clinical implementation in the course of a biomarker pipeline, such as demonstrating analytical validity of proposed biomarkers, which is critical to turning research-grade assays to clinical-grade tests. Here, we developed a fit-for-purpose multi-marker panel for PDAC diagnosis by consolidating analytically robust biomarkers as well as employing a relatively simple LC-MS method. In the discovery phase, we systematically collected putative biomarkers from both in-house proteomics data and the large volume of literature documenting PDAC biomarkers. In the verification phase, we developed a multiple-reaction monitoring (MRM)-MS-based proteomic assay using surrogate peptides that passed stringent analytical validation criteria. Given the intended use of our panel (i.e., primary screening), we adopted a high-throughput protocol including short gradient (<10 min) and simple sample preparation (no depletion or enrichment steps). To further facilitate clinical implementation, we performed verification of our panel on serum samples, which are usually the preferred biospecimen available in clinical settings. We developed a stacking ensemble model based on our final panel of 12 protein biomarkers combined with CA19-9, which showed improved diagnostic performance compared to using CA19-9 alone (AUC 0.919 and 0.830, respectively). A large-scale clinical validation study is underway to demonstrate the clinical validity of our panel.
2024-08-12 | PXD048034 | Pride
Project description:Purpose: Advanced high-grade gastroenteropancreatic neuroendocrine neoplasm (GEP-NEN) are highly aggressive and heterogeneous epithelial malignancies with poor clinical outcomes. No therapeutic predictive biomarkers exist and representative preclinical models to study their biology are missing. Patient-derived (PD) tumoroids may enable fast ex vivo pharmacotyping and provide subsidiary biological information for more personalized therapy strategies in individual patients. Experimental Design: PD tumoroids were established from rare biobanked surgical resections of advanced high-grade GEP-NEN patients. Using targeted in vitro pharmacotyping and next-generation sequencing of patient samples and matching PD tumoroids, we profiled individual patients and compared treatment-induced molecular stress response and in vitro drug sensitivity to the clinical therapy response. Results: We demonstrate high success rates in culturing PD tumoroids of high-grade GEP-NENs within clinically meaningful timespans. PD tumoroids recapitulate biological key features of high-grade GEP-NEN and mimic clinical response to cisplatin and temozolomide in vitro. Moreover, investigating treatment-induced molecular stress responses in PD tumoroids in silico, we discovered and functionally validated Lysine demethylase 5A (KDM5A) and interferon-beta (IFNB1) as two vulnerabilities that act synergistically in combination with cisplatin and may present novel therapeutic options in high-grade GEP-NENs. Conclusion: Patient-derived tumoroids from high-grade GEP-NENs represent a relevant model to screen drug sensitivities of individual patients within clinically relevant timespans and provide novel functional insights into drug-induced stress responses. Clinical patient response to standard-of-care chemotherapeutics matches with drug sensitivities of PD tumoroids. Together, our findings provide a functional precision oncology approach for gathering patient-centered subsidiary treatment information that will potentially increase therapeutic opportunities in the framework of personalized medicine.
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Project description:Exosomes are an emerging source for biomarkers in various diseases. Prostate cancer is the most frequent cancer in men in industrialized countries. The only biomarker widely used is prostate specific antigen with its clinical relevance suffering from low specificity. To identify novel biomarker candidates for prostate cancer we isolated exosomes from the supernatant of malignant PC3 and benign PNT1A cells, grown under standard culture conditions, using sequential centrifugation and ultracentrifugation. Not to alter the cellular growth conditions an FBS-containing medium was used. As control this medium was also subjected to exosomen isolation. Exosome and control samples were analyzed on an LTQ-Orbitrap XL mass spectrometer and subsequently between 441 and 843 proteins per sample were identified by searching against the SwissProt database. 64 proteins exclusively found in PC3 exosomes were subjected to a scoring system, integrating data from five publicly accessible databases and literature search, to identify potential biomarker candidates. Among these the epithelial tight junction protein claudin-3 achieved the highest score. Retests under serum-free conditions using immunoblotting and immunogold-labeling confirmed the expression of claudin-3 on PC3 exosomes. Levels of circulating claudin-3 directly determined from blood plasma, without prior isolation of exosomes, using ELISA were significantly higher (p=0,038) in metastatic prostate cancer patients (n=15) compared to controls with histologically proven benign prostate hyperplasia (n=15). Our results for the first time describe claudin-3 as a potential biomarker candidate in prostate cancer, easily detectably using liquid biopsies, without need for laborious isolation of exosomes. Further studies including larger patient cohorts in different clinical states of prostate cancer are needed to validate our findings.
2017-04-13 | PXD003651 | Pride