Dataset Information

Characterization of breast precancerous lesions and myoepithelial hyperplasia in sclerosing adenosis with apocrine metaplasia.

ABSTRACT: The identification as well as the molecular characterization of breast precancerous lesions in terms of increased risk of progression and/or recurrence is becoming a critical issue today as improved non-surgical procedures are detecting cancer at an earlier stage. The strategy we have been pursuing to identify early apocrine breast lesions is based on the postulate that invasive apocrine carcinomas evolve from epithelial cells in terminal duct lobular units (TDLUs) in a stepwise manner that involves apocrine metaplasia of normal breast epithelia, hyperplasia, atypia, and apocrine carcinoma in situ. First, we identify specific protein biomarkers for benign apocrine metaplasia and thereafter we search for biomarkers that are highly overexpressed by pure invasive apocrine carcinomas. Here we present studies in which we have used antibodies against components of a benign apocrine signature that includes 15-prostaglandin dehydrogenase (15-PGDH), a protein that is expressed by all benign apocrine lesions, and markers that are highly overexpressed by pure invasive apocrine carcinomas such as MRP14 (S100A9), psoriasin (S100A7), and p53 to identify precancerous lesions in sclerosing adenosis (SA) with apocrine metaplasia. The latter is a benign proliferative lesion of the breast that exhibits an increase in the size of the TDLUs and characterized by retained two-cell lining, and myoepithelial (ME) and stromal hyperplasia. SA with apocrine metaplasia, i.e. apocrine adenosis (AA), presents with a higher degree of atypical apocrine hyperplasia, and these lesions are believed to be precursors of apocrine carcinoma, in situ and invasive. Analysis of 24 selected SA samples with apocrine metaplasia revealed non-obligate putative apocrine precancerous lesions that displayed some, or in same cases all the three markers associated with pure invasive apocrine carcinomas. These studies also revealed p53 positive, non-apocrine putative precancerous lesions as well as novel phenotypes for ME and some luminal cells characterized by the expression of cytokeratin 15.

SUBMITTER: Celis JE

PROVIDER: S-EPMC5543858 | biostudies-literature | 2007 Jun

REPOSITORIES: biostudies-literature

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Characterization of breast precancerous lesions and myoepithelial hyperplasia in sclerosing adenosis with apocrine metaplasia.

Celis Julio E JE Moreira José M A JM Gromova Irina I Cabezón Teresa T Gromov Pavel P Shen Tao T Timmermans Vera V Rank Fritz F

Molecular oncology 20070314 1

The identification as well as the molecular characterization of breast precancerous lesions in terms of increased risk of progression and/or recurrence is becoming a critical issue today as improved non-surgical procedures are detecting cancer at an earlier stage. The strategy we have been pursuing to identify early apocrine breast lesions is based on the postulate that invasive apocrine carcinomas evolve from epithelial cells in terminal duct lobular units (TDLUs) in a stepwise manner that invo ...[more]

PMID: 19383289

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Project description:PurposeSclerosing adenosis (SA) is a benign lesion that could mimic breast carcinoma and be evaluated as malignancy by Breast Imaging-Reporting and Data System (BI-RADS) analysis. We aimed to construct and validate the performance of radiomic model based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) compared to BI-RADS analysis to identify SA.MethodsSixty-seven patients with invasive ductal carcinoma (IDC) and 58 patients with SA were included in this retrospective study from two institutions. The 125 patients were divided into a training cohort (n= 88) from institution I and a validation cohort from institution II (n=37). Dynamic contrast-enhanced sequences including one pre-contrast and five dynamic post-contrast series were obtained for all cases with different 3T scanners. Single-phase enhancement, multi-phase enhancement, and dynamic radiomic features were extracted from DCE-MRI. The least absolute shrinkage and selection operator (LASSO) logistic regression and cross-validation was performed to build the radscore of each single-phase enhancement and the final model combined multi-phase and dynamic radiomic features. The diagnostic performance of radiomics was evaluated by receiver operating characteristic (ROC) analysis and compared to the performance of BI-RADS analysis. The classification performance was tested using external validation.ResultsIn the training cohort, the AUCs of BI-RADS analysis were 0.71 (95%CI [0.60, 0.80]), 0.78 (95%CI [0.67, 0.86]), and 0.80 (95%CI [0.70, 0.88]), respectively. In single-phase analysis, the second enhanced phase radiomic signature achieved the highest AUC of 0.88 (95%CI [0.79, 0.94]) in distinguishing SA from IDC. Nine multi-phase radiomic features and two dynamic radiomic features showed the best predictive ability for final model building. The final model improved the AUC to 0.92 (95%CI [0.84, 0.97]), and showed statistically significant differences with BI-RADS analysis (p<0.05 for all). In the validation cohort, the AUC of the final model was 0.90 (95%CI [0.75, 0.97]), which was higher than all BI-RADS analyses and showed statistically significant differences with one of the BI-RADS analysis observers (p = 0.03).ConclusionsRadiomics based on DCE-MRI could show better diagnostic performance compared to BI-RADS analysis in differentiating SA from IDC, which may contribute to clinical diagnosis and treatment.

Project description:BackgroundSclerosing adenosis (SA) is a common proliferative benign lesion without atypia in the breast that may mimic invasive ductal carcinoma (IDC) on medical imaging, leading to it often being misdiagnosed and mistreated. Consequently, the purpose of this study was to assess the diagnostic value of multimodal ultrasound imaging in distinguishing SA from IDC.MethodsMultimodal ultrasound imaging, including automated breast volume scan (ABVS), elasticity imaging (EI), and color Doppler flow imaging (CDFI), were performed on 120 consecutive patients comprising 122 breast lesions (54 SA, 68 IDC). All lesions were pathologically confirmed. Multimodal ultrasound imaging features were compared between the two groups. Binary logistic regression analysis based on ABVS, EI, and CDFI was conducted to formulate a logistic regression equation for differentiating SA from IDC. The diagnostic performances of ABVS, EI, CDFI, and their combination were compared by the receiver operating characteristic (ROC) curve analysis.ResultsThe sensitivity, specificity, and accuracy of ABVS, EI, CDFI, and their combination in differentiating SA from IDC were, respectively, 75.00%, 72.22%, and 73.77%; 86.76%, 72.22%, and 80.33%; 73.53%, 64.81%, and 69.67%; and 88.24%, 74.07%, and 81.97%. Combining multimodal ultrasound imaging yielded an area under the curve (AUC) of 0.895 (95% confidence interval: 0.827-0.943), which was higher than that of ABVS, EI, and CDFI, with AUC values of 0.736, 0.795, and 0.692, respectively, and the difference was statistically significant (ABVS vs. combined model, P<0.001; CDFI vs. combined model, P<0.001; EI vs. combined model, P<0.001). There was no significant difference in the diagnostic efficacy among the three imaging modalities (ABVS vs. EI, P=0.266; ABVS vs. CDFI, P=0.4671; EI vs. CDFI, P=0.051). Compared with those in IDC, the calcification (16.67% vs. 57.35%; P<0.001) and retraction phenomena in the coronal planes (18.52% vs. 57.35%; P<0.001) were less common in patients with SA, while circumscribed margin (38.89% vs. 5.88%; P<0.001), vascularity grade 0-I (64.81% vs. 26.47%; P<0.001), and elasticity scores 1-3 (72.22% vs. 13.24%; P<0.001) were more frequently found in patients with SA. Patients with SA were significantly younger than were patients with IDC (43±11 vs. 54±11 years; P<0.001), and the lesion size was smaller in patients with SA than in those with IDC (median size 1.0 cm; interquartile range (IQR), 0.9 cm vs. median size 1.3 cm; IQR, 1.3 cm; P<0.001).ConclusionsThe preliminary results suggested that multimodal ultrasound imaging can improve the diagnostic accuracy of SA and provide additional information for differential diagnosis of SA and IDC.

Dataset Information

Characterization of breast precancerous lesions and myoepithelial hyperplasia in sclerosing adenosis with apocrine metaplasia.

Publications

Characterization of breast precancerous lesions and myoepithelial hyperplasia in sclerosing adenosis with apocrine metaplasia.

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