Clinical Usefulness of Serum CYFRA 21–1 in Patients with Colorectal Cancer

Lee, Jai Hyuen

doi:10.1007/s13139-013-0218-4

Cited by 16 publications

(12 citation statements)

References 31 publications

(40 reference statements)

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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).…”

Section: Discussionmentioning

confidence: 99%

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%

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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“…Although most of these are on track, the majority are still kept under strict and massive revision. Substantial attention is paid to relative abundance of carcinoembryonic antigen (CEA, sensitivity 50-80%, specificity above 80%) in combination with serum amyloid A (SAA) (sensitivity of 100%, specificity 83-100%) and also carbohydrate antigens CA 19-9 (sensitivity of 47.8%, specificity 90.1%), CA 125 (sensitivity of 57.1%, specificity 92% among CEA-negative patients), CA 72-4 (sensitivity of 50%, specificity 86%), and protein CYFRA21-1 (sensitivity up to 18.2% and 42.3% in stages A and B according to the modified Dukes' classifications) [3][4][5][6][7][8][9][10]. Nevertheless, the specificity for CRC diagnosis is questionable, since their presence and alterations are likewise associated with the development of squamous cell and hepatocellular carcinoma, lung, and bladder cancer [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Revelation of Proteomic Indicators for Colorectal Cancer in Initial Stages of Development

et al. 2020

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Background: Colorectal cancer (CRC) at a current clinical level is still hardly diagnosed, especially with regard to nascent tumors, which are typically asymptotic. Searching for reliable biomarkers of early diagnosis is an extremely essential task. Identification of specific post-translational modifications (PTM) may also significantly improve net benefits and tailor the process of CRC recognition. We examined depleted plasma samples obtained from 41 healthy volunteers and 28 patients with CRC at different stages to conduct comparative proteome-scaled analysis. The main goal of the study was to establish a constellation of protein markers in combination with their PTMs and semi-quantitative ratios that may support and realize the distinction of CRC until the disease has a poor clinical manifestation. Results: Proteomic analysis revealed 119 and 166 proteins for patients in stages I–II and III–IV, correspondingly. Plenty of proteins (44 proteins) reflected conditions of the immune response, lipid metabolism, and response to stress, but only a small portion of them were significant (p < 0.01) for distinguishing stages I–II of CRC. Among them, some cytokines (Clusterin (CLU), C4b-binding protein (C4BP), and CD59 glycoprotein (CD59), etc.) were the most prominent and the lectin pathway was specifically enhanced in patients with CRC. Significant alterations in Inter-alpha-trypsin inhibitor heavy chains (ITIH1, ITIH2, ITIH3, and ITIH4) levels were also observed due to their implication in tumor growth and the malignancy process. Other markers (Alpha-1-acid glycoprotein 2 (ORM2), Alpha-1B-glycoprotein (A1BG), Haptoglobin (HP), and Leucine-rich alpha-2-glycoprotein (LRG1), etc.) were found to create an ambiguous core involved in cancer development but also to exactly promote tumor progression in the early stages. Additionally, we identified post-translational modifications, which according to the literature are associated with the development of colorectal cancer, including kininogen 1 protein (T327-p), alpha-2-HS-glycoprotein (S138-p) and newly identified PTMs, i.e., vitamin D-binding protein (K75-ac and K370-ac) and plasma protease C1 inhibitor (Y294-p), which may also contribute and negatively impact on CRC progression. Conclusions: The contribution of cytokines and proteins of the extracellular matrix is the most significant factor in CRC development in the early stages. This can be concluded since tumor growth is tightly associated with chronic aseptic inflammation and concatenated malignancy related to loss of extracellular matrix stability. Due attention should be paid to Apolipoprotein E (APOE), Apolipoprotein C1 (APOC1), and Apolipoprotein B-100 (APOB) because of their impact on the malfunction of DNA repair and their capability to regulate mTOR and PI3K pathways. The contribution of the observed PTMs is still equivocal, but a significant decrease in the likelihood between modified and native proteins was not detected confidently.

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“…In non-small cell lung cancer Lee et al 16 reported that tumor size and histological grade were correlated with CYFRA21-1 levels. In colorectal cancer Lee 17 found that serum CYFRA21-1 was not correlated with lymph node involvement, histological grade, clinical stage or tumor size. In the present study, we found that high levels of CYFRA21-1 in serum of breast cancer patients were significantly correlated with tumor size.…”

Section: Discussionmentioning

confidence: 99%

Serum CYFRA 21-1 in Egyptian women with breast cancer

Ebied

Abdel-Rehim

El-Benhawy

et al. 2017

Alexandria Journal of Medicine

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Introduction: Cytokeratin fragment 21.1 (CYFRA 21.1) assay detects a serum fragment of cytokeratin 19 (CK19) and is employed in the diagnosis and management of lung cancer, particularly of squamous cell histotype. Breast carcinoma has been demonstrated to express CK19 fragments in the primary and metastatic lesions and CK19 mRNA is detectable in peripheral blood from patients affected by breast cancer. Aim of the work: The aim of the present study was to evaluate the clinical significance of serum CYFRA21-1 in patients with breast cancer by analyzing the correlation between serum CYFRA21-1 titers, clinicopathological factors and prognosis in comparison with serum CA15.3 and CEA tested in the same samples. Subjects and methods: This study included 60 breast cancer patients and 25 healthy females as control group. Three blood samples were drawn from each patient, before surgery, two weeks after surgery and after 6 cycles of chemotherapy. One blood sample was drawn from each subject of control group. Serum was separated and kept frozen till used for estimation of CYFRA21-1 by enzyme linked immunosorbent assay (ELISA) and serum CA15.3 and CEA by immunoradiometric assay (IRMA). Results: Serum CYFRA21-1 was highly elevated in breast cancer patients than in controls and was significantly associated with tumor size, clinical stage and axillary lymph node involvement. Serum CYFRA21-1 was superior to CA15.3 and CEA as a diagnostic marker for breast cancer using ROC curve analysis. Higher levels of serum CYFRA21-1 and CA15.3 were significantly associated with poor prognosis in primary breast cancer patients. Conclusions: The measurement of serum CYFRA 21-1 in breast cancer patients may be useful for detecting disease relapse and for assessing surgical and chemotherapeutic efficacy. Further prospective studies using greater number of patients are required to confirm our findings.

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Clinical Usefulness of Serum CYFRA 21–1 in Patients with Colorectal Cancer

Abstract: This study showed that CYFRA 21-1 could be a useful and dependable tumor marker for pretreatment and recurrent colorectal cancer. Further prospective studies on its usefulness with respect to the prognosis and utility of combined tumor markers are needed.

Cited by 16 publications

References 31 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

Revelation of Proteomic Indicators for Colorectal Cancer in Initial Stages of Development

Serum CYFRA 21-1 in Egyptian women with breast cancer

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