Nested polymerase chain reaction technique for the detection of Gpc3 and Afp mRNA in liver cancer micrometastases

Luo, Jiayou; Yang, Keda; Wen, Yanguang

doi:10.4238/gmr16018947

Cited by 6 publications

(2 citation statements)

References 19 publications

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“…CA-125, CA-153, and CYFRA21-1 are closely related to OM (P < 0.05). Meanwhile, AFP has been associated with liver cancer [30], and CEA is a broad-spectrum tumor marker used to assess the progression and prognosis of colorectal cancer [31], breast cancer [32], and lung cancer [33]. Its specificity and sensitivity are limited, and CEA only has auxiliary value in diagnosis.…”

Section: Discussionmentioning

confidence: 99%

CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis

Li¹,

Yuan²,

Zou³

et al. 2020

J. Cancer

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Despite recent improvements in diagnosis and therapy, lung cancer remains the most common malignant tumor in males, with high morbidity and mortality. As the annual incidence continues to increase worldwide, the prognosis for male patients with lung cancer remains unsatisfactory. Interestingly, smoking is associated with lung cancer and ocular lesions by altering risk factors such as carbohydrate antigen (CA)-125, CA-153 and cytokeratin-19 fragment (CYFRA21-1). A diagnostic standard for serum biomarker levels of ocular metastasis (OM) in males with lung cancer is therefore urgently needed. In this retrospective analysis, we examined the relationship between smoking preference and OM in male patients with lung cancer to identify an independent prognostic factor or establish a quantitative indicated standard for OM using the clinical indexes from 2238 cases of male lung cancer. The combination of CA-125, CA-153 and CYFRA21-1 could help diagnose OM in male lung cancer patients. This finding might lead to more timely diagnosis and effective therapies.

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Section: Discussionmentioning

confidence: 99%

CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis

Li¹,

Yuan²,

Zou³

et al. 2020

J. Cancer

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“…The current diagnosis of extrahepatic metastasis of PHC mainly relies on biomarkers, biopsy, and imaging scanning. Several biomarkers had been proposed as predictors, such as alpha-fetoprotein (AFP) mRNA, glypican-3, CK19, CD44, and vascular endothelial growth factor [7–9]. However, their pragmatic value remains controversial so that they still not serve for the clinical applications.…”

Section: Introductionmentioning

confidence: 99%

Pretreatment risk management of a novel nomogram model for prediction of thoracoabdominal extrahepatic metastasis in primary hepatic carcinoma

Hu¹,

Wang²,

Zhang³

et al. 2019

J Transl Med

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Background Extrahepatic metastasis is the independent risk factor of poor survival of primary hepatic carcinoma (PHC), and most occurs in the chest and abdomen. Currently, there is still no available method to predict thoracoabdominal extrahepatic metastasis in PHC. In this study, a novel nomogram model was developed and validated for prediction of thoracoabdominal extrahepatic metastasis in PHC, thereby conducted individualized risk management for pretreatment different risk population. Methods The nomogram model was developed in a primary study that consisted of 330 consecutive pretreatment patients with PHC. Large-scale datasets were extracted from clinical practice. The nomogram was based on the predictors optimized by data dimension reduction through Lasso regression. The prediction performance was measured by the area under the receiver operating characteristic (AUROC), and calibrated to decrease the overfit bias. Individualized risk management was conducted by weighing the net benefit of different risk population via decision curve analysis. The prediction performance was internally and independently validated, respectively. An independent-validation study using a separate set of 107 consecutive patients. Results Four predictors from 55 high-dimensional clinical datasets, including size, portal vein tumor thrombus, infection, and carbohydrate antigen 125, were incorporated to develop a nomogram model. The nomogram demonstrated valuable prediction performance with AUROC of 0.830 (0.803 in internal-validation, and 0.773 in independent-validation, respectively), and fine calibration. Individual risk probability was visually scored. Weighing the net benefit, threshold probability was classified for three-independent risk population, which was < 19.9%, 19.9–71.8% and > 71.8%, respectively. According to this classification, pretreatment risk management was based on a treatment-flowchart for individualized clinical decision-making. Conclusions The proposed nomogram is a useful tool for pretreatment risk management of thoracoabdominal extrahepatic metastasis in PHC for the first time, and may handily facilitate timely individualized clinical decision-making for different risk population. Electronic supplementary material The online version of this article (10.1186/s12967-019-1861-z) contains supplementary material, which is available to authorized users.

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Highly sensitive electrochemical aptasensor for Glypican-3 based on reduced graphene oxide-hemin nanocomposites modified on screen-printed electrode surface

Feng

Shi

et al. 2021

Bioelectrochemistry

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Nested polymerase chain reaction technique for the detection of Gpc3 and Afp mRNA in liver cancer micrometastases

Cited by 6 publications

References 19 publications

CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis

CA-125, CA-153, and CYFRA21-1 as clinical indicators in male lung cancer with ocular metastasis

Pretreatment risk management of a novel nomogram model for prediction of thoracoabdominal extrahepatic metastasis in primary hepatic carcinoma

Highly sensitive electrochemical aptasensor for Glypican-3 based on reduced graphene oxide-hemin nanocomposites modified on screen-printed electrode surface

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