A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva.
Ontology highlight
ABSTRACT:
SUBMITTER: Kawahara R
PROVIDER: S-EPMC4703492 | biostudies-literature | 2016 Jan
REPOSITORIES: biostudies-literature
Publications
A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva.
Kawahara Rebeca R Bollinger James G JG Rivera César C Ribeiro Ana Carolina P AC Brandão Thaís Bianca TB Paes Leme Adriana F AF MacCoss Michael J MJ
Proteomics 20151215 1
Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Usi ...[more]
Similar Datasets
Project description:Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by selected reaction monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
| S-EPMC6731088 | biostudies-literature
Project description:We have compiled from literature and other sources a list of 1261 proteins believed to be differentially expressed in human cancer. These proteins, only some of which have been detected in plasma to date, represent a population of candidate plasma biomarkers that could be useful in early cancer detection and monitoring given sufficiently sensitive specific assays. We have begun to prioritize these markers for future validation by frequency of literature citations, both total and as a function of time. The candidates include proteins involved in oncogenesis, angiogenesis, development, differentiation, proliferation, apoptosis, hematopoiesis, immune and hormonal responses, cell signaling, nucleotide function, hydrolysis, cellular homing, cell cycle and structure, the acute phase response and hormonal control. Many have been detected in studies of tissue or nuclear components; nevertheless we hypothesize that most if not all should be present in plasma at some level. Of the 1261 candidates only 9 have been approved as "tumor associated antigens" by the FDA. We propose that systematic collection and large-scale validation of candidate biomarkers would fill the gap currently existing between basic research and clinical use of advanced diagnostics.
| S-EPMC2716785 | biostudies-literature
Project description:Oral cancer is one of the most common cancers worldwide, and there are currently no biomarkers approved for aiding its management. Although many potential oral cancer biomarkers have been discovered, very few have been verified in body fluid specimens in parallel to evaluate their clinical utility. The lack of appropriate multiplexed assays for chosen targets represents one of the bottlenecks to achieving this goal. In the present study, we develop a peptide immunoaffinity enrichment-coupled multiple reaction monitoring-mass spectrometry (SISCAPA-MRM) assay for verifying multiple reported oral cancer biomarkers in saliva. We successfully produced 363 clones of mouse anti-peptide monoclonal antibodies (mAbs) against 36 of 49 selected targets, and characterized useful mAbs against 24 targets in terms of their binding affinity for peptide antigens and immuno-capture ability. Comparative analyses revealed that an equilibrium dissociation constant (KD ) cut-off value < 2.82 × 10-9 m could identify most clones with an immuno-capture recovery rate >5%. Using these mAbs, we assembled a 24-plex SISCAPA-MRM assay and optimized assay conditions in a 25-μg saliva matrix background. This multiplexed assay showed reasonable precision (median coefficient of variation, 7.16 to 32.09%), with lower limits of quantitation (LLOQ) of <10, 10-50, and >50 ng/ml for 14, 7 and 3 targets, respectively. When applied to a model saliva sample pooled from oral cancer patients, this assay could detect 19 targets at higher salivary levels than their LLOQs. Finally, we demonstrated the utility of this assay for quantification of multiple targets in individual saliva samples (20 healthy donors and 21 oral cancer patients), showing that levels of six targets were significantly altered in cancer compared with the control group. We propose that this assay could be used in future studies to compare the clinical utility of multiple oral cancer biomarker candidates in a large cohort of saliva samples.
| S-EPMC5629267 | biostudies-literature
Project description:Colon cancer is an aggressive tumor form with a poor prognosis. This study reports a comparative proteomic analysis performed by using two-dimensional differential in-gel electrophoresis (2D-DIGE) between 26 pooled colon cancer surgical tissues and adjacent non-tumoral tissues, to identify potential target proteins correlated with carcinogenesis. The DAVID functional classification tool revealed that most of the differentially regulated proteins, acting both intracellularly and extracellularly, concur across multiple cancer steps. The identified protein classes include proteins involved in cell proliferation, apoptosis, metabolic pathways, oxidative stress, cell motility, Ras signal transduction, and cytoskeleton. Interestingly, networks and pathways analysis showed that the identified proteins could be biologically inter-connected to the tumor-host microenvironment, including innate immune response, platelet and neutrophil degranulation, and hemostasis. Finally, transgelin (TAGL), here identified for the first time with four different protein species, collectively down-regulated in colon cancer tissues, emerged as a top-ranked biomarker for colorectal cancer (CRC). In conclusion, our findings revealed a different proteomic profiling in colon cancer tissues characterized by the deregulation of specific pathways involved in hallmarks of cancer. All of these proteins may represent promising novel colon cancer biomarkers and potential therapeutic targets, if validated in larger cohorts of patients.
| S-EPMC7247674 | biostudies-literature
Project description:Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS.
| S-EPMC4791256 | biostudies-literature
Project description:This is a pilot study. We are trying to detect potential salivary biomarkers in mice with a pancreatic tumor. Global gene expression profiling has shown great promise in high-throughput biomarker discovery for early disease detection in body fluids such as saliva, which is accessible, cost-effective, and non-invasive. However, this goal has not been fully realized because saliva, like many clinical samples, contains partially fragmented and degraded RNAs that are difficult to amplify and detect with prevailing technologies. Here, using nanogram scale salivary RNA as a proof-of-principle example, we describe our progress with a novel poly-A tail independent mRNA amplification strategy combined with the Affymetrix GeneChip Exon arrays. We defined a Salivary Exon Core Transcriptome (SECT) with highly similar expression profiles in healthy individuals verified by quantitative PCR. Informatics analysis of SECT provided important mechanistic insight to their potential origin and function. Finally we demonstrated the diagnostic potential of true exon level expression profiling approach with salivary exon biomarkers that accurately discriminated gender in healthy individuals. Recent studies have demonstrated that discriminatory salivary biomarkers can be readily detected upon the development of systemic diseases such as pancreatic cancer, breast cancer, lung cancer and ovarian cancer. However, the utility of salivary biomarkers for the detection of systemic diseases has been undermined due to the absence of biological and mechanistic rationale why distal diseases from the oral cavity would lead to the development of discriminatory biomarkers in saliva. Here, we examine the hypothesis that pancreatic tumor-derived exosomes are mechanistically involved in the development of pancreatic cancer-discriminatory salivary transcriptomic biomarkers. We first developed a pancreatic cancer mouse model that yielded discriminatory salivary biomarkers by implanting the mouse pancreatic cancer cell line Pan02 into the pancreas of the syngeneic host C57BL/6. The role of pancreatic cancer-derived exosomes in the development of discriminatory salivary biomarkers was then tested by engineered a Pan02 cell line that is suppressed for exosome biogenesis, implanted into the C56BL/6 mouse and examine if the discriminatory salivary biomarker profile was ablated or disrupted. Suppression of exosome biogenesis results in the ablation of discriminatory salivary biomarker development. This study supports that tumor-derived exosomes provide a mechanism in the development of discriminatory biomarkers in saliva and distal systemic diseases. We analyzed saliva from 6 healthy mice and 6 mice with a pancreatic tumor using the Affymetrix Mouse Exon Genome 430 2.0 platform. Array data was processed by dChip. No techinical replicates were performed.
2013-06-12 | E-GEOD-47811 | biostudies-arrayexpress
Project description:BackgroundHead and neck squamous cell cancer (HNSCC) is the most common cancer associated with chewing tobacco, in the world. As this is divided in to sites and subsites, it does not make it to top 10 cancers. The most common subsite is the oral cancer. At the time of diagnosis, more than 50% of patients with oral squamous cell cancers (OSCC) had advanced disease, indicating the lack of availability of early detection and risk assessment biomarkers. The new protein biomarker development and discovery will aid in early diagnosis and treatment which lead to targeted treatment and ultimately a good prognosis.MethodsThis systematic review was performed as per PRISMA guidelines. All relevant studies assessing characteristics of oral cancer and proteomics were considered for analysis. Only human studies published in English were included, and abstracts, incomplete articles, and cell line or animal studies were excluded.ResultsA total of 308 articles were found, of which 112 were found to be relevant after exclusion. The present review focuses on techniques of cancer proteomics and discovery of biomarkers using these techniques. The signature of protein expression may be used to predict drug response and clinical course of disease and could be used to individualize therapy with such knowledge.ConclusionsProspective use of these markers in the clinical setting will enable early detection, prediction of response to treatment, improvement in treatment selection, and early detection of tumor recurrence for disease monitoring. However, most of these markers for OSCC are yet to be validated.
| S-EPMC8555221 | biostudies-literature
Project description:The high complexity and large dynamic range of blood plasma proteins currently prohibit the sensitive and high-throughput profiling of disease and control plasma proteome sample sets large enough to reliably detect disease indicating differences. To circumvent these technological limitations we describe here a new two-stage strategy for the mass spectrometry (MS) assisted discovery, verification and validation of disease biomarkers. In an initial discovery phase N-linked glycoproteins with distinguishable expression patterns in primary normal and diseased tissue are detected and identified. In the second step the proteins identified in the initial phase are subjected to targeted MS analysis in plasma samples, using the highly sensitive and specific selected reaction monitoring (SRM) technology. Since glycosylated proteins, such as those secreted or shed from the cell surface are likely to reside and persist in blood, the two-stage strategy is focused on the quantification of tissue derived glycoproteins in plasma. The focus on the N-glycoproteome not only reduces the complexity of the analytes, but also targets an information-rich subproteome which is relevant for remote sensing of diseases in the plasma. The N-glycoprotein based biomarker discovery and validation workflow reviewed here allows for the robust identification of protein candidate panels that can finally be selectively monitored in the blood plasma at high sensitivity in a reliable, non-invasive and quantitative fashion.
| S-EPMC2753590 | biostudies-literature
Project description:This is a pilot study. We are trying to detect potential salivary biomarkers in mice with a pancreatic tumor. Global gene expression profiling has shown great promise in high-throughput biomarker discovery for early disease detection in body fluids such as saliva, which is accessible, cost-effective, and non-invasive. However, this goal has not been fully realized because saliva, like many clinical samples, contains partially fragmented and degraded RNAs that are difficult to amplify and detect with prevailing technologies. Here, using nanogram scale salivary RNA as a proof-of-principle example, we describe our progress with a novel poly-A tail independent mRNA amplification strategy combined with the Affymetrix GeneChip Exon arrays. We defined a Salivary Exon Core Transcriptome (SECT) with highly similar expression profiles in healthy individuals verified by quantitative PCR. Informatics analysis of SECT provided important mechanistic insight to their potential origin and function. Finally we demonstrated the diagnostic potential of true exon level expression profiling approach with salivary exon biomarkers that accurately discriminated gender in healthy individuals. Recent studies have demonstrated that discriminatory salivary biomarkers can be readily detected upon the development of systemic diseases such as pancreatic cancer, breast cancer, lung cancer and ovarian cancer. However, the utility of salivary biomarkers for the detection of systemic diseases has been undermined due to the absence of biological and mechanistic rationale why distal diseases from the oral cavity would lead to the development of discriminatory biomarkers in saliva. Here, we examine the hypothesis that pancreatic tumor-derived exosomes are mechanistically involved in the development of pancreatic cancer-discriminatory salivary transcriptomic biomarkers. We first developed a pancreatic cancer mouse model that yielded discriminatory salivary biomarkers by implanting the mouse pancreatic cancer cell line Pan02 into the pancreas of the syngeneic host C57BL/6. The role of pancreatic cancer-derived exosomes in the development of discriminatory salivary biomarkers was then tested by engineered a Pan02 cell line that is suppressed for exosome biogenesis, implanted into the C56BL/6 mouse and examine if the discriminatory salivary biomarker profile was ablated or disrupted. Suppression of exosome biogenesis results in the ablation of discriminatory salivary biomarker development. This study supports that tumor-derived exosomes provide a mechanism in the development of discriminatory biomarkers in saliva and distal systemic diseases.
2013-06-12 | GSE47811 | GEO
Project description:The development and progression of oral cavity squamous cell carcinoma (OSCC) involves complex cellular mechanisms that contribute to the low five-year survival rate of approximately 20% among diagnosed patients. However, the biological processes essential to tumor progression are not completely understood. Therefore, detecting alterations in the salivary proteome may assist in elucidating the cellular mechanisms modulated in OSCC and improve the clinical prognosis of the disease. The proteome of whole saliva and salivary extracellular vesicles (EVs) from patients with OSCC and healthy individuals were analyzed by LC-MS/MS and label-free protein quantification. Proteome data analysis was performed using statistical, machine learning and feature selection methods with additional functional annotation. Biological processes related to immune responses, peptidase inhibitor activity, iron coordination and protease binding were overrepresented in the group of differentially expressed proteins. Proteins related to the inflammatory system, transport of metals and cellular growth and proliferation were identified in the proteome of salivary EVs. The proteomics data were robust and could classify OSCC with 90% accuracy. The saliva proteome analysis revealed that immune processes are related to the presence of OSCC and indicate that proteomics data can contribute to determining OSCC prognosis.
| S-EPMC4633731 | biostudies-literature