Dataset Information

Distinguishing adrenal cortical carcinomas and adenomas: a study of clinicopathological features and biomarkers.

ABSTRACT:

Aims

To determine clinicopathological criteria and molecular markers helpful in distinguishing adrenocortical carcinomas (ACCs) from adrenocortical adenomas (ACAs).

Methods and results

We analysed retrospectively the clinical and pathological features of 50 adrenal cortical tumours, and tested the expression of miR483-3p by in-situ hybridization as well as the expression of IGF2 and Smad4 by immunohistochemistry. We found that tumour size, tumour weight, hormonal function and the Weiss system are all high-efficacy criteria for differentiating malignant from benign tumours (P < 0.001). MiR483-3p was overexpressed in 68% (17 of 25) of ACCs compared to 12% (three of 25) of ACAs (P < 0.05). Using a combination of miR483-3p and Smad4 improved diagnostic accuracy. Molecular markers were then tested in an independent set of 15 borderline tumours. We confirmed that the combined use of miR483-3p and Smad4 immunochemistry can complement the Weiss score in the diagnosis of ACC in cases that display borderline histology.

Conclusions

Tumour size, tumour weight, hormonal function and the Weiss system are useful clinicopathological criteria that can result in accurate diagnosis of most ACCs and ACAs. In challenging cases, miR483-3p and Smad4 expression may help in distinguishing these two entities.

SUBMITTER: Wang C

PROVIDER: S-EPMC4282325 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Publications

Distinguishing adrenal cortical carcinomas and adenomas: a study of clinicopathological features and biomarkers.

Wang Cuiping C Sun Yang Y Wu Huanwen H Zhao Dachun D Chen Jie J

Histopathology 20131123 4

<h4>Aims</h4>To determine clinicopathological criteria and molecular markers helpful in distinguishing adrenocortical carcinomas (ACCs) from adrenocortical adenomas (ACAs).<h4>Methods and results</h4>We analysed retrospectively the clinical and pathological features of 50 adrenal cortical tumours, and tested the expression of miR483-3p by in-situ hybridization as well as the expression of IGF2 and Smad4 by immunohistochemistry. We found that tumour size, tumour weight, hormonal function and the ...[more]

PMID: 24102952

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Project description:BackgroundThere remains a demand for a practical method of identifying lipid-poor adrenal lesions.PurposeTo explore the predictive value of computed tomography (CT) features combined with demographic characteristics for lipid-poor adrenal adenomas and nonadenomas.Materials and methodsWe retrospectively recruited patients with lipid-poor adrenal lesions between January 2015 and August 2021 from two independent institutions as follows: Institution 1 for the training set and the internal validation set and Institution 2 for the external validation set. Two radiologists reviewed CT images for the three sets. We performed a least absolute shrinkage and selection operator (LASSO) algorithm to select variables; subsequently, multivariate analysis was used to develop a generalized linear model. The probability threshold of the model was set to 0.5 in the external validation set. We calculated the sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for the model and radiologists. The model was validated and tested in the internal validation and external validation sets; moreover, the accuracy between the model and both radiologists were compared using the McNemar test in the external validation set.ResultsIn total, 253 patients (median age, 55 years [interquartile range, 47-64 years]; 135 men) with 121 lipid-poor adrenal adenomas and 132 nonadenomas were included in Institution 1, whereas another 55 patients were included in Institution 2. The multivariable analysis showed that age, male, lesion size, necrosis, unenhanced attenuation, and portal venous phase attenuation were independently associated with adrenal adenomas. The clinical-image model showed AUCs of 0.96 (95% confidence interval [CI]: 0.91, 0.98), 0.93 (95% CI: 0.84, 0.97), and 0.86 (95% CI: 0.74, 0.94) in the training set, internal validation set, and external validation set, respectively. In the external validation set, the model showed a significantly and non-significantly higher accuracy than reader 1 (84% vs. 65%, P = 0.031) and reader 2 (84% vs. 69%, P = 0.057), respectively.ConclusionsOur clinical-image model displayed good utility in differentiating lipid-poor adrenal adenomas. Further, it showed better diagnostic ability than experienced radiologists in the external validation set.

Dataset Information

Distinguishing adrenal cortical carcinomas and adenomas: a study of clinicopathological features and biomarkers.

Aims

Methods and results

Conclusions

Publications

Distinguishing adrenal cortical carcinomas and adenomas: a study of clinicopathological features and biomarkers.

Similar Datasets

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