Journal of Mammary Gland Biology and Neoplasia最新文献_第10页

Breast Cancer Response to Therapy: Can microRNAs Lead the Way? 乳腺癌对治疗的反应:microrna能引领潮流吗?

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-06-01 Epub Date: 2021-01-21 DOI: 10.1007/s10911-021-09478-3

Nina Petrović, Irina Nakashidze, Milica Nedeljković

{"title":"Breast Cancer Response to Therapy: Can microRNAs Lead the Way?","authors":"Nina Petrović, Irina Nakashidze, Milica Nedeljković","doi":"10.1007/s10911-021-09478-3","DOIUrl":"https://doi.org/10.1007/s10911-021-09478-3","url":null,"abstract":"Breast cancer (BC) is a leading cause of death among women with malignant diseases. The selection of adequate therapies for highly invasive and metastatic BCs still represents a major challenge. Novel combinatorial therapeutic approaches are urgently required to enhance the efficiency of BC treatment. Recently, microRNAs (miRNAs) emerged as key regulators of the complex mechanisms that govern BC therapeutic resistance and susceptibility. In the present review we aim to critically examine how miRNAs influence BC response to therapies, or how to use miRNAs as a basis for new therapeutic approaches. We summarized recent findings in this rapidly evolving field, emphasizing the challenges still ahead for the successful implementation of miRNAs into BC treatment while providing insights for future BC management.The goal of this review was to propose miRNAs, that might simultaneously improve the efficacy of all four therapies that are the backbone of current BC management (radio-, chemo-, targeted, and hormone therapy). Among the described miRNAs, miR-21 and miR-16 emerged as the most promising, closely followed by miR-205, miR-451, miR-182, and miRNAs from the let-7 family. miR-21 inhibition might be the best choice for future improvement of invasive BC treatment.New therapeutic strategies of miRNA-based agents alongside current standard treatment modalities could greatly benefit BC patients. This review represents a guideline on how to navigate this elaborate puzzle.","PeriodicalId":16413,"journal":{"name":"Journal of Mammary Gland Biology and Neoplasia","volume":"26 2","pages":"157-178"},"PeriodicalIF":2.5,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10911-021-09478-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38768001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

A Comparative Review of the Extrinsic and Intrinsic Factors Regulating Lactose Synthesis. 调节乳糖合成的外因与内因的比较研究进展。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-06-01 Epub Date: 2021-06-14 DOI: 10.1007/s10911-021-09491-6

Anna Sadovnikova, Sergio C Garcia, Russell C Hovey

引用次数: 5

Cancer-Associated Fibroblasts in the Breast Tumor Microenvironment. 乳腺肿瘤微环境中癌症相关成纤维细胞的研究

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-06-01 Epub Date: 2021-01-04 DOI: 10.1007/s10911-020-09475-y

María Belén Giorello, Francisco Raúl Borzone, Vivian Labovsky, Flavia Valeria Piccioni, Norma Alejandra Chasseing

引用次数: 17

Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features. 通过分析上下文特征，深度学习使组织学图像中的单个异种移植物细胞分类成为可能。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-06-01 Epub Date: 2021-05-17 DOI: 10.1007/s10911-021-09485-4

Quentin Juppet, Fabio De Martino, Elodie Marcandalli, Martin Weigert, Olivier Burri, Michael Unser, Cathrin Brisken, Daniel Sage

{"title":"Deep Learning Enables Individual Xenograft Cell Classification in Histological Images by Analysis of Contextual Features.","authors":"Quentin Juppet, Fabio De Martino, Elodie Marcandalli, Martin Weigert, Olivier Burri, Michael Unser, Cathrin Brisken, Daniel Sage","doi":"10.1007/s10911-021-09485-4","DOIUrl":"https://doi.org/10.1007/s10911-021-09485-4","url":null,"abstract":"Patient-Derived Xenografts (PDXs) are the preclinical models which best recapitulate inter- and intra-patient complexity of human breast malignancies, and are also emerging as useful tools to study the normal breast epithelium. However, data analysis generated with such models is often confounded by the presence of host cells and can give rise to data misinterpretation. For instance, it is important to discriminate between xenografted and host cells in histological sections prior to performing immunostainings. We developed Single Cell Classifier (SCC), a data-driven deep learning-based computational tool that provides an innovative approach for automated cell species discrimination based on a multi-step process entailing nuclei segmentation and single cell classification. We show that human and murine cell contextual features, more than cell-intrinsic ones, can be exploited to discriminate between cell species in both normal and malignant tissues, yielding up to 96% classification accuracy. SCC will facilitate the interpretation of H&E- and DAPI-stained histological sections of xenografted human-in-mouse tissues and it is open to new in-house built models for further applications. SCC is released as an open-source plugin in ImageJ/Fiji available at the following link: https://github.com/Biomedical-Imaging-Group/SingleCellClassifier .","PeriodicalId":16413,"journal":{"name":"Journal of Mammary Gland Biology and Neoplasia","volume":"26 2","pages":"101-112"},"PeriodicalIF":2.5,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10911-021-09485-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39002480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The Cellular Organization of the Mammary Gland: Insights From Microscopy. 乳腺的细胞组织:从显微镜观察。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 Epub Date: 2021-04-09 DOI: 10.1007/s10911-021-09483-6

Caleb A Dawson, Jane E Visvader

{"title":"The Cellular Organization of the Mammary Gland: Insights From Microscopy.","authors":"Caleb A Dawson, Jane E Visvader","doi":"10.1007/s10911-021-09483-6","DOIUrl":"https://doi.org/10.1007/s10911-021-09483-6","url":null,"abstract":"Despite rapid advances in our knowledge of the cellular heterogeneity and molecular regulation of the mammary gland, how these relate to 3D cellular organization remains unclear. In addition to hormonal regulation, mammary gland development and function is directed by para- and juxtacrine signaling among diverse cell-types, particularly the immune and mesenchymal populations. Precise mapping of the cellular landscape of the breast will help to decipher this complex coordination. Imaging of thin tissue sections has provided foundational information about cell positioning in the mammary gland and now technological advances in tissue clearing and subcellular-resolution 3D imaging are painting a more complete picture. In particular, confocal, light-sheet and multiphoton microscopy applied to intact tissue can fully capture cell morphology, position and interactions, and have the power to identify spatially rare events. This review will summarize our current understanding of mammary gland cellular organization as revealed by microscopy. We focus on the mouse mammary gland and cover a broad range of immune and stromal cell types at major developmental stages and give insights into important tissue niches and cellular interactions.","PeriodicalId":16413,"journal":{"name":"Journal of Mammary Gland Biology and Neoplasia","volume":"26 1","pages":"71-85"},"PeriodicalIF":2.5,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10911-021-09483-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25591321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Retraction Note to: Circ-TFCP2L1 Promotes the Proliferation and Migration of Triple Negative Breast Cancer through Sponging miR-7 by Inhibiting PAK1. 注:Circ-TFCP2L1通过抑制PAK1海绵化miR-7促进三阴性乳腺癌的增殖和迁移。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 DOI: 10.1007/s10911-021-09481-8

Qian Wang, Zhouxiao Li, Yun Hu, Wubin Zheng, Weiwei Tang, Changyuan Zhai, Zhutong Gu, Jing Tao, Hanjin Wang

引用次数: 0

An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment. 出生后小鼠乳腺的综合单细胞转录组图谱允许发现新的腔室发育轨迹。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 Epub Date: 2021-04-28 DOI: 10.1007/s10911-021-09488-1

Martín E García Solá, Micaela Stedile, Inés Beckerman, Edith C Kordon

{"title":"An Integrative Single-cell Transcriptomic Atlas of the Post-natal Mouse Mammary Gland Allows Discovery of New Developmental Trajectories in the Luminal Compartment.","authors":"Martín E García Solá, Micaela Stedile, Inés Beckerman, Edith C Kordon","doi":"10.1007/s10911-021-09488-1","DOIUrl":"https://doi.org/10.1007/s10911-021-09488-1","url":null,"abstract":"The mammary gland is a highly dynamic organ which undergoes periods of expansion, differentiation and cell death in each reproductive cycle. Partly because of the dynamic nature of the gland, mammary epithelial cells (MECs) are extraordinarily heterogeneous. Single cell RNA-seq (scRNA-seq) analyses have contributed to understand the cellular and transcriptional heterogeneity of this complex tissue. Here, we integrate scRNA-seq data from three foundational reports that have explored the mammary gland cell populations throughout development at single-cell level using 10× Chromium Drop-Seq. We center our analysis on post-natal development of the mammary gland, from puberty to post-involution. The new integrated study corresponds to RNA sequences from 53,686 individual cells, which greatly outnumbers the three initial data sets. The large volume of information provides new insights, as a better resolution of the previously detected Procr+ stem-like cell subpopulation or the identification of a novel group of MECs expressing immune-like markers. Moreover, here we present new pseudo-temporal trajectories of MEC populations at two resolution levels, that is either considering all mammary cell subtypes or focusing specifically on the luminal lineages. Interestingly, the luminal-restricted analysis reveals distinct expression patterns of various genes that encode milk proteins, suggesting specific and non-redundant roles for each of them. In summary, our data show that the application of bioinformatic tools to integrate multiple scRNA-seq data-sets helps to describe and interpret the high level of plasticity involved in gene expression regulation throughout mammary gland post-natal development.","PeriodicalId":16413,"journal":{"name":"Journal of Mammary Gland Biology and Neoplasia","volume":"26 1","pages":"29-42"},"PeriodicalIF":2.5,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10911-021-09488-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38919586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Characterization of Gene Expression Signatures for the Identification of Cellular Heterogeneity in the Developing Mammary Gland. 鉴定发育中乳腺细胞异质性的基因表达特征。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 Epub Date: 2021-05-14 DOI: 10.1007/s10911-021-09486-3

Samantha Henry, Marygrace C Trousdell, Samantha L Cyrill, Yixin Zhao, Mary J Feigman, Julia M Bouhuis, Dominik A Aylard, Adam Siepel, Camila O Dos Santos

{"title":"Characterization of Gene Expression Signatures for the Identification of Cellular Heterogeneity in the Developing Mammary Gland.","authors":"Samantha Henry, Marygrace C Trousdell, Samantha L Cyrill, Yixin Zhao, Mary J Feigman, Julia M Bouhuis, Dominik A Aylard, Adam Siepel, Camila O Dos Santos","doi":"10.1007/s10911-021-09486-3","DOIUrl":"10.1007/s10911-021-09486-3","url":null,"abstract":"The developing mammary gland depends on several transcription-dependent networks to define cellular identities and differentiation trajectories. Recent technological advancements that allow for single-cell profiling of gene expression have provided an initial picture into the epithelial cellular heterogeneity across the diverse stages of gland maturation. Still, a deeper dive into expanded molecular signatures would improve our understanding of the diversity of mammary epithelial and non-epithelial cellular populations across different tissue developmental stages, mouse strains and mammalian species. Here, we combined differential mammary gland fractionation approaches and transcriptional profiles obtained from FACS-isolated mammary cells to improve our definitions of mammary-resident, cellular identities at the single-cell level. Our approach yielded a series of expression signatures that illustrate the heterogeneity of mammary epithelial cells, specifically those of the luminal fate, and uncovered transcriptional changes to their lineage-defined, cellular states that are induced during gland development. Our analysis also provided molecular signatures that identified non-epithelial mammary cells, including adipocytes, fibroblasts and rare immune cells. Lastly, we extended our study to elucidate expression signatures of human, breast-resident cells, a strategy that allowed for the cross-species comparison of mammary epithelial identities. Collectively, our approach improved the existing signatures of normal mammary epithelial cells, as well as elucidated the diversity of non-epithelial cells in murine and human breast tissue. Our study provides a useful resource for future studies that use single-cell molecular profiling strategies to understand normal and malignant breast development.","PeriodicalId":16413,"journal":{"name":"Journal of Mammary Gland Biology and Neoplasia","volume":"26 1","pages":"43-66"},"PeriodicalIF":2.5,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s10911-021-09486-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38993529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Connecting the Dots: Mammary Gland and Breast Cancer at Single Cell Resolution. 连接点:乳腺和乳腺癌的单细胞分辨率。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 Epub Date: 2021-06-14 DOI: 10.1007/s10911-021-09492-5

Renée van Amerongen, Edith C Kordon, Zuzana Koledova

引用次数: 2

Behind the Scenes of the Human Breast Cell Atlas Project. 人类乳腺细胞图谱项目的幕后。

IF 2.5 4区医学

Journal of Mammary Gland Biology and Neoplasia Pub Date : 2021-03-01 Epub Date: 2021-04-29 DOI: 10.1007/s10911-021-09482-7

Renée van Amerongen

引用次数: 4