Mass Spectrometry-based Proteomic Profiling of Lung Cancer (original) (raw)
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Biomarker discovery in lung cancer—promises and challenges of clinical proteomics
Mass Spectrometry Reviews, 2007
Lung cancer is a devastating illness with an overall poor prognosis. To effectively address this disease, early detection and novel therapeutics are required. Early detection of lung cancer is challenging, in part because of the lack of adequate tumor biomarkers. The goal of this review is to summarize the knowledge of current biomarkers in lung cancer, with a focus on important serum biomarkers. The current knowledge on the known serum cytokines and tumor biomarkers of lung cancer will be presented. Emerging trends and new findings in the search for novel diagnostic and therapeutic tumor biomarkers using proteomics technologies and platforms are emphasized, including recent advances in mass spectrometry to facilitate tumor biomarker discovery program in lung cancer. It is our hope that validation of these new research platforms and technologies will result in improved early detection, prognostication, and finally the treatment of lung cancer with potential novel molecularly targete...
Lung Cancer Proteomics: Recent Advances in Biomarker
2011
Lung cancer is the most common cause of cancer death in both men and women in Western countries, with a 5-year survival rate of 15%, which is among the lowest of all cancers. The high mortality from lung cancer is due not only to the late stage diagnosis but also to the lack of effective treatments even for patients diagnosed with stage I lung cancer. Therefore, there is an urgent need to identify new markers for early diagnosis and prognosis that could serve to open novel therapeutic avenues. Proteomics can represent an important tool for the identification of biomarkers and therapeutic targets for lung cancer since DNA-based biomarkers did not prove to have adequate sensitivity, specificity, and reproducibility. In this paper we will describe studies focused on the identification of new diagnostic, prognostic, and predictive markers for lung cancer, using proteomics technologies.
Lung Cancer Proteomics: Recent Advances in Biomarker Discovery
International Journal of Proteomics, 2011
Lung cancer is the most common cause of cancer death in both men and women in Western countries, with a 5-year survival rate of 15%, which is among the lowest of all cancers. The high mortality from lung cancer is due not only to the late stage diagnosis but also to the lack of effective treatments even for patients diagnosed with stage I lung cancer. Therefore, there is an urgent need to identify new markers for early diagnosis and prognosis that could serve to open novel therapeutic avenues. Proteomics can represent an important tool for the identification of biomarkers and therapeutic targets for lung cancer since DNA-based biomarkers did not prove to have adequate sensitivity, specificity, and reproducibility. In this paper we will describe studies focused on the identification of new diagnostic, prognostic, and predictive markers for lung cancer, using proteomics technologies.
Advances in proteomic strategies toward the early detection of lung cancer
Proceedings of the American Thoracic Society, 2011
Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this review we provide a critical assessment of the state of recent advances in proteomic approaches and the biological lessons they have yielded, with specific emphasis on the discovery of biomarker signatures for the early detection of lung cancer.
PROTEOMICS – Clinical Applications
PurposeLung cancer is the most common cause of death from cancer worldwide, largely due to late diagnosis. Thus, there is an urgent need to develop new approaches to improve the detection of early‐stage lung cancer, which would greatly improve patient survival.Experimental DesignThe quantitative protein expression profiles of microvesicles isolated from the sera from 46 lung cancer patients and 41 high‐risk non‐cancer subjects were obtained using a mass spectrometry method based on a peptide library matching approach.ResultsWe identified 33 differentially expressed proteins that allow discriminating the two groups. We also built a machine learning model based on serum protein expression profiles that can correctly classify the majority of lung cancer cases and that highlighted a decrease in the levels of Arysulfatase A (ARSA) as the most discriminating factor found in tumors.Conclusions and Clinical RelevanceOur study identified a preliminary, non‐invasive protein signature able to ...
Proteomics and mass spectrometry for cancer biomarker discovery
Biomarker insights, 2007
Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.
Plasma proteomic profiling: Search for lung cancer diagnostic and early detection markers
Oncology Reports, 2006
Environmental and occupational exposure to asbestos is among the established risk factors for lung cancer, the leading cause of cancer-related deaths in the United States. This link between exposure to asbestos and the excessive death rate from lung cancer was evident in a study of former workers of an asbestos pipe insulation manufacturing plant in Tyler, TX. We performed comparative proteomic profiling of plasma samples that were collected from nine patients within 12 months before death and their age-, raceand exposure-matched disease-free controls on strong anion exchange chips using surface-enhanced laser desorption ionization time-of-flight mass spectrometry. A distancedependent K-nearest neighbor (KNN) classification algorithm identified spectral features of m/z values 7558.9 and 15103.0 that were able to distinguish lung cancer patients from disease-free individuals with high sensitivity and specificity. The high correlation between the intensities of these two peaks (r=0.987) strongly suggests that they are the doubly and singly charged ions of the same protein product. Examination of these proteomic markers in the plasma samples of subjects from >5 years before death from lung cancer suggested that they are related to the early development of lung cancer. Validation of these biomarkers would have significant implications for the early detection of lung cancer and better management of high-risk patients.
The value of proteomics in lung cancer
Annals of translational medicine, 2015
Many studies have identified the prognostic and predictive value of proteins or peptides in lung cancer but most failed to provide strong evidence for their clinical applicability. The strongest predictive proteins seem to be fatty acid-binding protein heart (H-FABP), and the 8-peak mass spectrography signature of VeriStrat. When focusing on VeriStrat, a 'VeriStrat good' profile did not discriminate between chemotherapy and erlotinib. The 'VeriStrat poor' profile showed a better outcome to chemotherapy than to erlotinib. VeriStrat is a prognostic test and only the "poor profile" discriminates for the type of therapy that should be chosen. Whether it adds useful information in patients with advanced non-small cell lung cancer (NSCLC) and wild type EGFR mutations is still doubtful. The position of the VeriStrat test in clinical practice is still not clear and we are waiting for prospective studies where biomarker test are involved in clinical decision.
Molecular & Cellular Proteomics, 2011
A challenge in the treatment of lung cancer is the lack of early diagnostics. Here, we describe the application of monoclonal antibody proteomics for discovery of a panel of biomarkers for early detection (stage I) of non-small cell lung cancer (NSCLC). We produced large monoclonal antibody libraries directed against the natural form of protein antigens present in the plasma of NSCLC patients. Plasma biomarkers associated with the presence of lung cancer were detected via high throughput ELISA. Differential profiling of plasma proteomes of four clinical cohorts, totaling 301 patients with lung cancer and 235 healthy controls, identified 13 lung cancer-associated (p < 0.05) monoclonal antibodies. The monoclonal antibodies recognize five different cognate proteins identified using immunoprecipitation followed by mass spectrometry. Four of the five antigens were present in non-small cell lung cancer cells in situ. The approach is capable of generating independent antibodies against different epitopes of the same proteins, allowing fast translation to multiplexed sandwich assays. Based on these results, we have verified in two independent clinical collections a panel of five biomarkers for classifying patient disease status with a diagnostics performance of 77% sensitivity and 87% specificity. Combining CYFRA, an established cancer marker, with the panel resulted in a performance of 83% sensitivity at 95% specificity for stage I NSCLC. Molecular & Cellular Proteomics 10: 10.1074/ mcp.
Molecular & Cellular Proteomics, 2012
Advances in proteomic analysis of human samples are driving critical aspects of biomarker discovery and the identification of molecular pathways involved in disease etiology. Toward that end, in this report we are the first to use a standardized shotgun proteomic analysis method for in-depth tissue protein profiling of the two major subtypes of nonsmall cell lung cancer and normal lung tissues. We identified 3621 proteins from the analysis of pooled human samples of squamous cell carcinoma, adenocarcinoma, and control specimens. In addition to proteins previously shown to be implicated in lung cancer, we have identified new pathways and multiple new differentially expressed proteins of potential interest as therapeutic targets or diagnostic biomarkers, including some that were not identified by transcriptome profiling. Up-regulation of these proteins was confirmed by multiple reaction monitoring mass spectrometry. A subset of these proteins was found to be detectable and differentially present in the peripheral blood of cases and matched controls. Label-free shotgun proteomic analysis allows definition of lung tumor proteomes, identification of biomarker candidates, and potential targets for therapy. Molecular &