Application of proteomics in non-small-cell lung cancer

Cho, William C.

doi:10.1586/14789450.2016.1121813

Cited by 18 publications

(12 citation statements)

References 24 publications

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“…Predictive markers of drug resistance, lung cancer diagnosis, and prognostic markers in lung cancer have also been discovered by quantitative proteomics analysis [37]. …”

Section: Applications Of Quantitative Proteomics In Lung Cancermentioning

confidence: 99%

Quantitative proteomics in lung cancer

Cheung

Juan

2017

J Biomed Sci

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Lung cancer is the most common cause of cancer-related death worldwide, less than 7% of patients survive 10 years following diagnosis across all stages of lung cancer. Late stage of diagnosis and lack of effective and personalized medicine reflect the need for a better understanding of the mechanisms that underlie lung cancer progression. Quantitative proteomics provides the relative different protein abundance in normal and cancer patients which offers the information for molecular interactions, signaling pathways, and biomarker identification. Here we introduce both theoretical and practical applications in the use of quantitative proteomics approaches, with principles of current technologies and methodologies including gel-based, label free, stable isotope labeling as well as targeted proteomics. Predictive markers of drug resistance, candidate biomarkers for diagnosis, and prognostic markers in lung cancer have also been discovered and analyzed by quantitative proteomic analysis. Moreover, construction of protein networks enables to provide an opportunity to interpret disease pathway and improve our understanding in cancer therapeutic strategies, allowing the discovery of molecular markers and new therapeutic targets for lung cancer.

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“…Predictive markers of drug resistance, lung cancer diagnosis, and prognostic markers in lung cancer have also been discovered by quantitative proteomics analysis [37]. …”

Section: Applications Of Quantitative Proteomics In Lung Cancermentioning

confidence: 99%

Quantitative proteomics in lung cancer

Cheung

Juan

2017

J Biomed Sci

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“…For example, as the sixth most common cancer and the second leading cause of cancer death in the world, liver cancer is closely associated with the body's immune system that could either evacuate the abnormally growing cells or attack healthy liver cells causing inflammation and liver damage (35,36). We searched our database with ‘Liver cancer’ and found 53 AAg genes.…”

Section: Data Search and Navigationmentioning

confidence: 99%

AAgAtlas 1.0: a human autoantigen database

et al. 2016

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Autoantibodies refer to antibodies that target self-antigens, which can play pivotal roles in maintaining homeostasis, distinguishing normal from tumor tissue and trigger autoimmune diseases. In the last three decades, tremendous efforts have been devoted to elucidate the generation, evolution and functions of autoantibodies, as well as their target autoantigens. However, reports of these countless previously identified autoantigens are randomly dispersed in the literature. Here, we constructed an AAgAtlas database 1.0 using text-mining and manual curation. We extracted 45 830 autoantigen-related abstracts and 94 313 sentences from PubMed using the keywords of either ‘autoantigen’ or ‘autoantibody’ or their lexical variants, which were further refined to 25 520 abstracts, 43 253 sentences and 3984 candidates by our bio-entity recognizer based on the Protein Ontology. Finally, we identified 1126 genes as human autoantigens and 1071 related human diseases, with which we constructed a human autoantigen database (AAgAtlas database 1.0). The database provides a user-friendly interface to conveniently browse, retrieve and download human autoantigens as well as their associated diseases. The database is freely accessible at http://biokb.ncpsb.org/aagatlas/. We believe this database will be a valuable resource to track and understand human autoantigens as well as to investigate their functions in basic and translational research.

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“…Study made on few direct tumor tissues was performed on the paraffin blocks prepared within formol by the pathology, and there is a probability of the protein structures being denatured. [ 24 ] These approaches are the most important limitation of these studies to demonstrate the accurate proteomic structure. Most of the proteins described in studies done previously are molecules related to the dynamic processes such as inflammation, cell differentiation, proliferation, and apoptosis.…”

Section: Discussionmentioning

confidence: 99%

Chaperonin (HSP60) and annexin-2 are candidate biomarkers for non-small cell lung carcinoma

et al. 2017

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Background:Lung cancer is responsible of 12.4% and 17.6% of all newly diagnosed cancer cases and mortality due to cancer, respectively, and 5-year survival rate despite all improved treatment options is 15%. This survival rate reaches 66% in the Stage 1 and surgically treated patients. Early diagnosis which could not be definitely and commonly achieved yet is extremely critical in obtaining high survival rate in this disease. For this reason; proteomic differences were evaluated using matrix assisted laser desorption ionization (MALDI) mass spectrometry in the subgroups of lung adenocarcinoma and squamous cell carcinoma.Methods:Fresh tissue samples of 36 malignant cases involving 83.3% (n = 30) men and 16.7% (n = 6) women patients were distributed into 2 groups as early and end stage lung cancer and each group were composed of subgroups including 18 squamous cell carcinoma (9 early stage cases, 9 end stage cases) and 18 adenocarcinoma cases (9 early stage cases, 9 end stage cases). The fresh tissues obtained from the tumoral and matched normal sites after surgical intervention. The differences in protein expression levels were determined by comparing proteomic changes in each patient.Results:In the subgroups of advanced stage adenocarcinoma; tumoral tissue revealed differences in expression of 2 proteins compared with normal parenchymal tissue. Of those; difference in protein expression in heat shock protein 60 (HSP60) was found statistically significant (P = 0.0001). Subgroups of early and advanced stage squamos cell carcinoma have differed in certain 20 protein expression of normal tissue and diseased squamos cell carcinoma. Of those, increased protein expression level of only annexin-2 protein was found statistically significant (P = 0.002). No significant difference was detected in early and advanced stage protein expressions of the tumoral tissues in the subgroups of adenocarcinoma and squamous cell carcinoma.Conclusions:We conclude that with respect to early diagnosis of lung cancer that HSP60 and annexin-2 proteins are the important biomarkers in the subgroups of adenocarcinoma and squamous cell carcinoma. We also consider that these 2 proteins are molecules which may provide critical contribution in evaluation of prognosis, metastatic potential, response to treatment, and in establishment of differential diagnosis between adenocarcinoma and squamous cell carcinoma.

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Application of proteomics in non-small-cell lung cancer

Cited by 18 publications

References 24 publications

Quantitative proteomics in lung cancer

Quantitative proteomics in lung cancer

AAgAtlas 1.0: a human autoantigen database

Chaperonin (HSP60) and annexin-2 are candidate biomarkers for non-small cell lung carcinoma

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