The combination of CTCs and CEA can help guide the management of patients with SPNs suspected of being lung cancer

Zheng, Jian; Liu, Yanan; Zhao, Yong; He, Mudan; Xiao, Hui

doi:10.1186/s12885-020-6524-1

Cited by 23 publications

(18 citation statements)

References 31 publications

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“…In this study, the results revealed that the combination of conventional CEA values with CTC counts (i.e., number of CD45 neg EpCAM pos CTCs or CD45 neg EpCAM neg cells) can significantly discriminate CRC’s advanced or metastatic status ( Figure 5 , Figure 6 and Figure 7 and Table 3 and Table 4 ). These findings are also similar to those of other studies [ 31 , 32 , 33 ]. First, Aggarwal et al observed that the performance of cancer prognosis among metastatic CRC patients can be distinguished by a combination of the CEA level and baseline CTC count with a cutoff point of 3/per 7.5 mL, suggesting that the performance of the CEA level could be improved by combining it with the CTC marker [ 31 ].…”

Section: Discussionsupporting

confidence: 93%

“…First, Aggarwal et al observed that the performance of cancer prognosis among metastatic CRC patients can be distinguished by a combination of the CEA level and baseline CTC count with a cutoff point of 3/per 7.5 mL, suggesting that the performance of the CEA level could be improved by combining it with the CTC marker [ 31 ]. Zheng et al noticed that the combination of the CTC count with the CEA level could be a tool with high diagnostic efficacy for early lung cancer diagnosis [ 32 ]. Shi et al proved that CTCs expressing MAGE3 (melanoma-associated antigen 3), survivin, and CEA were predictive of cryosurgery’s efficacy in unresectable hepatocellular carcinoma [ 33 ].…”

Section: Discussionmentioning

confidence: 99%

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Enhancing Prediction Performance by Add-On Combining Circulating Tumor Cell Count, CD45neg EpCAMneg Cell Count on Colorectal Cancer, Advance, and Metastasis

Chiu

Hsieh

You

et al. 2021

Cancers

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Conventional circulating tumor cell (CTC) enumeration could ignore the CTCs more relevant to cancer metastasis. Thus, negative selection CTC enumeration was proposed, by which information on two cellular biomarkers (numbers of CTCs and CD45neg EpCAMneg cells) can be obtained. By combining this approach with the conventional biomarker carcinoembryonic antigen (CEA), this study aimed to explore whether any combination of these biomarkers could improve the predictive performance for colorectal cancer (CRC) or its status. In this work, these two cell populations in healthy donors and CRC patients were quantified. Results revealed that enumeration of these two cell populations was able to discriminate healthy donors from CRC patients, even patients with non-advanced CRC. Moreover, the combination of the two cell populations showed improved performance (AUROC: 0.893) for CRC prediction over the use of only one population. Compared with CEA alone, the combination of the three biomarkers increased the performance (AUROC) for advanced CRC prediction from 0.643 to 0.727. Compared with that of CEA alone for metastatic CRC prediction, the AUROC was increased from 0.780 to 0.837 when the CTC count was included. Overall, this study demonstrated that the combination of these two cellular biomarkers with CEA improved the predictive performance for CRC and its status.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Enhancing Prediction Performance by Add-On Combining Circulating Tumor Cell Count, CD45neg EpCAMneg Cell Count on Colorectal Cancer, Advance, and Metastasis

Chiu

Hsieh

You

et al. 2021

Cancers

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“…The results show that there was little difference in the individual detection efficacy between these markers, and the AUC values were all less than 0.6, suggesting that they were not suitable as biomarkers for the diagnosis of lung cancer. In some studies, the CEA expression level was shown to have a certain application value in the determination of pulmonary nodule benignity and malignancy ( 11 , 33 , 34 ), while in this study, it was not shown to have an application value. This may be because serum CEA expression levels in patients with pulmonary nodules < 2 cm tend to be within a normal detection threshold range.…”

Section: Discussioncontrasting

confidence: 56%

Combination of CT and telomerase-positive circulating tumor cells improves diagnosis of small pulmonary nodules

et al. 2021

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BACKGROUND Early diagnosis and treatment are key to the long-term survival of lung cancer patients. Although CT has significantly contributed to the early diagnosis of lung cancer, there are still consequences of excessive or delayed treatment. By improving the sensitivity and specificity of circulating tumor cell (CTC) detection, a solution was proposed for differentiating benign from malignant pulmonary nodules. METHODS In this study, we used telomerase reverse transcriptase–based (TERT-based) CTC detection (TBCD) to distinguish benign from malignant pulmonary nodules < 2 cm and compared this method with the pathological diagnosis as the gold standard. FlowSight and FISH were used to confirm the CTCs detected by TBCD. RESULTS Our results suggest that CTCs based on TBCD can be used as independent biomarkers to distinguish benign from malignant nodules and are significantly superior to serum tumor markers. When the detection threshold was 1, the detection sensitivity and specificity of CTC diagnosis were 0.854 and 0.839, respectively. For pulmonary nodules ≤ 1 cm and 1–2 cm, the sensitivity and specificity of CTCs were both higher than 77%. Additionally, the diagnostic ability of CTC-assisted CT was compared by CT detection. The results show that CT combined with CTCs could significantly improve the differentiation ability of benign and malignant nodules in lung nodules < 2 cm and that the sensitivity and specificity could reach 0.899 and 0.839, respectively. CONCLUSION TBCD can effectively diagnose pulmonary nodules and be used as an effective auxiliary diagnostic scheme for CT diagnosis. FUNDING National Key Research and Development Project grant nos. 2019YFC1315700 and 2017YFC1308702, CAMS Initiative for Innovative Medicine grant no. 2017-I2M-1-005, and National Natural Science Foundation of China grant no. 81472013.

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“…The degree of serum CEA increase is related to the extent of cancer focus, and its dynamic changes can reflect the patient's response to treatment and prognosis. Patients with a progressive increase in the measured value tend to have a poor prognosis, while patients with firstly decreased and then increased values are mostly experiencing signs of tumor recurrence (Zheng et al, 2020). Glutathione-S-transferaseπ (GST-π) is significantly increased in patients with NSCLC.…”

Section: Introductionmentioning

confidence: 99%

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

Xing

Zhang

et al. 2020

Front. Mol. Biosci.

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Background: The development of human tumors is associated with the abnormal expression of various functional genes, and a massive tumor-based database needs to be deeply mined. Based on a multigene prediction model, access to urgent prognosis of patients has become possible. Materials and Methods: We selected three RNA expression profiles (GSE32863, GSE10072, and GSE43458) from the lung adenocarcinoma (LUAD) database of the Gene Expression Omnibus (GEO) and analyzed the differentially expressed genes (DEGs) between tumor and normal tissue using GEO2R program. After that, we analyzed the transcriptome data of 479 LUAD samples (54 normal tissue samples and 425 cancer tissue samples) and their clinical follow-up data from the (TCGA) database. Kaplan-Meier (KM) curve and receiver operating characteristic (ROC) were used to assess the prediction model. Multivariate Cox analysis was used to identify independent predictors. TCGA pancreatic adenocarcinoma datasets were used to establish a nomogram model. Results: We found 98 significantly prognosis-related genes using KM and COX analysis, among which six genes were found to be the DEGs in GEO. Using multivariate analysis, it was found that a single gene could not be used as an independent predictor of prognosis. However, the risk score calculated by weighting these six genes could serve as an independent prognosis predictor. COX analysis performed with multiple covariates such as age, gender, tumor stage, and TNM typing showed that risk score could still be utilized as an independent risk factor for patient survival rate (p = 0.013) and had an applicable reliability (area under the curve, AUC = 0.665). By combining risk score and various clinical features, the nomogram model was constructed, which had been proven to have high consistency for the prediction of 3-and 5-year survival rate (concordance = 0.751) and high accuracy as tested by ROC (AUC = 0.71;AUC = 0.708). Conclusion: We proposed a method to predict the prognosis of LUAD by weighting multiple genes and constructed a nomogram model suitable for the prognostic evaluation of LUAD, which could provide a new tool for the identification of therapeutic targets and the efficacy evaluation of LUAD.

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The combination of CTCs and CEA can help guide the management of patients with SPNs suspected of being lung cancer

Cited by 23 publications

References 31 publications

Enhancing Prediction Performance by Add-On Combining Circulating Tumor Cell Count, CD45neg EpCAMneg Cell Count on Colorectal Cancer, Advance, and Metastasis

Enhancing Prediction Performance by Add-On Combining Circulating Tumor Cell Count, CD45neg EpCAMneg Cell Count on Colorectal Cancer, Advance, and Metastasis

Combination of CT and telomerase-positive circulating tumor cells improves diagnosis of small pulmonary nodules

Identification of Key Genes in Lung Adenocarcinoma and Establishment of Prognostic Mode

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