Prognostic impact of serum CYFRA 21–1 in patients with advanced lung adenocarcinoma: a retrospective study

Ono, Akira; Takahashi, Toshiaki; Mori, Keita; Akamatsu, Hiroaki; Shukuya, Takehito; Taira, Tetsuhiko; Kenmotsu, Hirotsugu; Naito, Tateaki; Murakami, Haruyasu; Nakajima, Takashi; Endo, Masahiro; Yamamoto, Nobuyuki

doi:10.1186/1471-2407-13-354

Cited by 47 publications

(40 citation statements)

References 50 publications

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“…It is a unique epitope from a polypeptide and abundantly elaborated following cell death, whose diagnostic utility and prognostic relevance have been demonstrated in stomach cancer, colorectal cancer, breast cancer, and cervical cancer (Gaarenstroom et al, 1995;Lee, 2013;Wang et al, 2013;Gwak et al, 2014). Having been classified into 20 subtypes based on isoelectric point and differences in the molecular mass which was determined by 2-dimensional electrophoresis, Cyfra21-1 is a useful auxiliary biomarker in the diagnosis of NSCLC, and it has been reported that it has particularly high specificity for the diagnosis of lung squamous cell carcinoma (Ono et al, 2013). Therefore based on NSE, CEA and Cyfra21-1, the GEP1 accuracy is outstanding than GEP2 and GEP3.…”

Section: Discussionmentioning

confidence: 99%

“…Serum LDH levels have been correlated with poor prognosis and resistance to chemotherapy and radiotherapy in various neoplastic diseases (Zhao et al, 2013). Serum Cyfra21-1 is one of the most important serum markers in the diagnosis of nonsmall cell lung cancer (NSCLC), especially squamous-cell carcinoma (Ono et al, 2013;Wang et al, 2013). So, based on CEA and NSE, we set up three GEP models -GEP1 (CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP).…”

Section: Biomarker Selectionmentioning

confidence: 99%

“…Lung cancer may spreads to other organs and spreading to the brain can cause headache, vomiting, psychosis, unilateral limb paresthesia and visual impairment. In spite of the progress and efforts we made in treatment and diagnosis of lung cancer patients, the diagnosis of overall survival at five years is only 15%, and more than 75% patients at the time of diagnosis is already presenting with advanced stage of disease when therapeutic options are very limited (Patz et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Lung Cancer Based on Serum Biomarkers by Gene Expression Programming Methods

Chen²,

Cui³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool -gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are requentlyused lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.

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Section: Discussionmentioning

confidence: 99%

Section: Biomarker Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of Lung Cancer Based on Serum Biomarkers by Gene Expression Programming Methods

Chen²,

Cui³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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“…CYFRA 21-1 (fragment of cytokeratin 19) has been demonstrated as clinically useful in prognostication and monitoring of the patients with lung cancer. Elevated pretreatment values of CYFRA 21-1 in NSCLC patients reported to be associated with unfavorable prognosis [62]. Decreasing concentrations of CYFRA 21-1 in NSCLC predict objective response to treatment in advanced disease [63].…”

Section: Prognostic Biomarkersmentioning

confidence: 99%

Proteomics biomarkers for non-small cell lung cancer

Kiśluk

Ciborowski

Niemira

et al. 2014

Journal of Pharmaceutical and Biomedical Analysis

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“…Accelerated CK19 degradation occurs in neoplastically transformed epithelial cells as a result of increased protease activity of caspase 3, which is a regulator of the apoptosis cascade, and fragments are released into the blood. This leads to an increase in the serum CYFRA21-1 level, which can be recognized by two monoclonal antibodies [8]. CYFRA21-1 has been identified as a potential tumor marker for the diagnosis and prognosis of non-small-cell lung cancer (NSCLC).…”

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confidence: 99%

Serum CYFRA21-1 as an effective tumor biomarker for patients with nasopharyngeal carcinoma

Song¹,

WANG²,

WANG³

et al. 2015

neo

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We investigated if the serum cytokeratin 19 fragment 21.1 (CYFRA21-1) level was elevated in nasopharyngeal carcinoma (NPC) and can function as a biomarker for detection and monitoring of NPC. Three hundred and one study subjects were divided into two groups: the NPC group (n=126) and healthy control group (n=175). Serum CYFRA21-1 levels were measured before and after treatment using a chemiluminescent immunoassay, and its association with tumor stage and the clinical objective responses were analyzed. Receiver operating characteristic (ROC) curve analysis was performed to discriminate patients with NPC from the healthy controls. The pretreatment serum CYFRA21-1 level was significantly elevated in patients with NPC compared with the healthy controls (5.07±1.98 ng/ml vs 2.36±1.21 ng/ml, p<0.001), and it declined significantly after the entire treatment (2.14±0.72 ng/ml, p<0.001). The serum CYFRA21-1 level of patients with a classification of T3-4 was significantly higher than that of those with class T1-2 (5.64±2.23 ng/ml vs 4.62±1.64 ng/ml, p=0.006), and that of patients with clinical stage III-IV was higher than clinical stage I-II (5.31±2.02 vs 4.04±1.37 ng/ml, p=0.003). The AUC, sensitivity and specificity of elevated serum CYFRA21-1 in patients with NPC was 0.91, 0.83 and 0.89 respectively. In conclusion, the serum CYFRA21-1 level could be a reliable and effective biomarker for the detection and monitoring of NPC tumor progression.

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Prognostic impact of serum CYFRA 21–1 in patients with advanced lung adenocarcinoma: a retrospective study

Cited by 47 publications

References 50 publications

Prediction of Lung Cancer Based on Serum Biomarkers by Gene Expression Programming Methods

Prediction of Lung Cancer Based on Serum Biomarkers by Gene Expression Programming Methods

Proteomics biomarkers for non-small cell lung cancer

Serum CYFRA21-1 as an effective tumor biomarker for patients with nasopharyngeal carcinoma

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