Preneoplasia of the Breast and Molecular Landscape

Alvarado‐Cabrero, Isabel; Valencia-Cedillo, Raquel; Estevez-Castro, Rafael

doi:10.1016/j.arcmed.2020.09.011

Cited by 5 publications

(2 citation statements)

References 38 publications

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“…Carcinogenesis in the breast is a complex pathological process of the female reproductive system. Due to the occurrence of different types of breast cancer, diverse onset and dynamics are attributed to its progression and the regulation of tumor growth and metastatic dissemination (Alvarado-Cabrero et al 2020). A central feature in breast cancer is the deregulation of cell homeostasis and microenvironment, associated with tumor development (Zhang et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Mammary carcinoma in aged gerbil mothers after endocrine disruption in pregnancy and lactation

Ruiz

Colleta

Leonel

et al. 2021

Endocrine-Related Cancer

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Compounds that trigger breast cancer onset and establishment are of great interest in biological research. Endocrine disruptors are relevant because they initiate carcinogenesis by changing endocrine pathways. Bisphenol A (BPA), as a ubiquitous xenoestrogen, is largely associated with dysfunctions in the female reproductive system and associated organs. This study proposes an investigation of the mammary gland (MG) in aged Mongolian gerbil (Meriones unguiculatus) mothers after their exposure to BPA in two windows of morphophysiological plasticity: pregnancy and lactation. A low dose (50 μg/kg), and a high dose (5000 μg/kg) were considered and results showed few differences between them. As expected, we observed contrasts among control and BPA-exposed MG. The control groups presented a regressive phase with high apoptotic activity and elastic stroma. However, BPA damaged mammary tissue and provoked multifocal carcinoma development supported by an apparent epithelial-mesenchymal transition (EMT) and reactive stroma establishment. BPA remodeled stromal fibers deposition and enhanced the recruitment of tumor-associated cells, contributing to a tumoral microenvironment. Overexpression of TGF-β1 was induced by BPA in the epithelial compartment of exposed MG and increased expression of metalloproteinases (MMP-2, MMP-3, MMP-9) was present in carcinoma cells. In conclusion, exposure of mothers to BPA during the gestational/lactational window of susceptibility leads to carcinogenic impacts with aging.

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Section: Introductionmentioning

confidence: 99%

Mammary carcinoma in aged gerbil mothers after endocrine disruption in pregnancy and lactation

Ruiz

Colleta

Leonel

et al. 2021

Endocrine-Related Cancer

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“…CCLs include columnar cell hyperplasia and FEA. FEA has a neoplastic gene alteration than that in normal mammary glands [27][28][29]. Additionally, CCLs, including columnar cell hyperplasia, have similar neoplastic genetic alterations [30,31].…”

Section: Experiments 3: Ccls Vs Normal Distinguishing Ccls and Normal Mammary Glandsmentioning

confidence: 99%

Machine learning-based image analysis for accelerating the diagnosis of complicated preneoplastic and neoplastic ductal lesions in breast biopsy tissues

Sato

Maki

Yamanaka

et al. 2021

Breast Cancer Res Treat

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Purpose: Diagnosis of breast preneoplastic and neoplastic lesions is di cult due to their similar morphology in breast biopsy specimens. To diagnose these lesions, pathologists perform immunohistochemical analysis and consult with expert breast pathologists. These additional examinations are time-consuming and expensive. Arti cial intelligence (AI)-based image analysis has recently improved, and may help in ordinal pathological diagnosis. Here, we showed the signi cance of machine learning-based image analysis of breast preneoplastic and neoplastic lesions for facilitating high-throughput diagnosis.Methods: Images were obtained from normal mammary glands, hyperplastic lesions, preneoplastic lesions and neoplastic lesions, such as usual ductal hyperplasia (UDH), columnar cell lesion (CCL), ductal carcinoma in situ (DCIS), and DCIS with comedo necrosis (comedo DCIS) in breast biopsy specimens.The original enhanced convoluted neural network (CNN) system was used for analyzing the pathological images.Results: The AI-based image analysis provided the following area under the curve values (AUC): normal lesion vs. DCIS, 0.9902; DCIS vs. comedo DCIS, 0.9942; normal lesion vs. CCL, 0.9786; and UDH vs. DCIS, 1.000. Multiple comparison analysis showed precision and recall scores similar to those of single comparison analysis. Based on the Gradient-weighted Class Activation Mapping (Grad-CAM) used to visualize the important regions re ecting the result of CNN analysis, the ratio of stromal tissue in the whole weighted area was signi cantly higher in UDH and CCL than that in DCIS.Conclusions: These analyses may provide a more accurate and rapid pathological diagnosis of patients. Moreover, Grad-CAM identi es uncharted important histological characteristics for newer pathological ndings and targets of research for understanding diseases.

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Atypical ductal or lobular hyperplasia, lobular carcinoma in-situ, flat epithelial atypia, and future risk of developing breast cancer: Systematic review and meta-analysis

Baker,

Noguchi,

Marinovich

et al. 2024

The Breast

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Preneoplasia of the Breast and Molecular Landscape

Cited by 5 publications

References 38 publications

Mammary carcinoma in aged gerbil mothers after endocrine disruption in pregnancy and lactation

Mammary carcinoma in aged gerbil mothers after endocrine disruption in pregnancy and lactation

Machine learning-based image analysis for accelerating the diagnosis of complicated preneoplastic and neoplastic ductal lesions in breast biopsy tissues

Atypical ductal or lobular hyperplasia, lobular carcinoma in-situ, flat epithelial atypia, and future risk of developing breast cancer: Systematic review and meta-analysis

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