ArticleBMC cancer2010
Identification of an autoantibody panel to separate lung cancer from smokers and nonsmokers.
Article in BMC cancer, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00301119 (NYU Lung Cancer Biomarker Center), which is not on this map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
NYU Lung Cancer Biomarker Center
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis.PloS one · 2017Pooled it
- Anti-p53 Autoantibody Detection in Automatic Glass Capillary Immunoassay Platform for Screening of Oral Cavity Squamous Cell Carcinoma.Sensors (Basel, Switzerland) · 2020Article
- Blood based biomarkers beyond genomics for lung cancer screening.Translational lung cancer research · 2018Review
- Detection of anti-p53 autoantibodies in saliva using microfluidic chips for the rapid screening of oral cancer.RSC advances · 2018Article
- The state of the art in the development of a panel of biomarkers for the early detection of lung cancer.Journal of thoracic disease · 2018Article
- IMP2/IGF2BP2 expression, but not IMP1 and IMP3, predicts poor outcome in patients and high tumor growth rate in xenograft models of gallbladder cancer.Oncotarget · 2017Article
- Comparative Network Analysis of Patients with Non-Small Cell Lung Cancer and Smokers for Representing Potential Therapeutic Targets.Scientific reports · 2017Article
- Autoantibodies against oncogenic ERG protein in prostate cancer: potential use in diagnosis and prognosis in a panel with C-MYC, AMACR and HERV-K Gag.Genes & cancer · 2016Article
- IMP2/p62 induces genomic instability and an aggressive hepatocellular carcinoma phenotype.Cell death & disease · 2015Article
- Article
- Autoantibody profiling for lung cancer screening longitudinal retrospective analysis of CT screening cohorts.PloS one · 2014Article
- A blood-based proteomic classifier for the molecular characterization of pulmonary nodules.Science translational medicine · 2013Article
- Glycoproteomic analysis of bronchoalveolar lavage (BAL) fluid identifies tumor-associated glycoproteins from lung adenocarcinoma.Journal of proteome research · 2013Article
- Current readings: blood-based biomarkers for lung cancer.Seminars in thoracic and cardiovascular surgery · 2013Article
- Differential gene expression profile in PBMCs from subjects with AERD and ATA: a gene marker for AERD.Molecular genetics and genomics : MGG · 2012Article
- Autoantibody signatures: progress and perspectives for early cancer detection.Journal of cellular and molecular medicine · 2011Review
- Asthma-predictive genetic markers in gene expression profiling of peripheral blood mononuclear cells.Allergy, asthma & immunology research · 2011Article
- The grand challenge to decipher the cancer proteome.Nature reviews. Cancer · 2010Review
- Identification of autoantibodies to ECH1 and HNRNPA2B1 as potential biomarkers in the early detection of lung cancer.OncoimmunologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundSera from lung cancer patients contain autoantibodies that react with tumor associated antigens (TAAs) that reflect genetic over-expression, mutation, or other anomalies of cell cycle, growth, signaling, and metabolism pathways.
methodsWe performed immunoassays to detect autoantibodies to ten tumor associated antigens (TAAs) selected on the basis of previous studies showing that they had preferential specificity for certain cancers. Sera examined were from lung cancer patients (22); smokers with ground-glass opacities (GGOs) (46), benign solid nodules (55), or normal CTs (35); and normal non-smokers (36). Logistic regression models based on the antibody biomarker levels among the high risk and lung cancer groups were developed to identify the combinations of biomarkers that predict lung cancer in these cohorts.
resultsStatistically significant differences in the distributions of each of the biomarkers were identified among all five groups. Using Receiver Operating Characteristic (ROC) curves based on age, c-myc, Cyclin A, Cyclin B1, Cyclin D1, CDK2, and survivin, we obtained a sensitivity = 81% and specificity = 97% for the classification of cancer vs smokers(no nodules, solid nodules, or GGO) and correctly predicted 31/36 healthy controls as noncancer.
conclusionA pattern of autoantibody reactivity to TAAs may distinguish patients with lung cancer versus smokers with normal CTs, stable solid nodules, ground glass opacities, or normal healthy never smokers.
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