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Open accessJournal ArticleDOI: 10.15252/EMMM.202013180

Intraductal xenografts show lobular carcinoma cells rely on their own extracellular matrix and LOXL1.

05 Mar 2021-Embo Molecular Medicine (EMBO)-Vol. 13, Iss: 3
Abstract: Invasive lobular carcinoma (ILC) is the most frequent special histological subtype of breast cancer, typically characterized by loss of E-cadherin. It has clinical features distinct from other estrogen receptor-positive (ER+ ) breast cancers but the molecular mechanisms underlying its characteristic biology are poorly understood because we lack experimental models to study them. Here, we recapitulate the human disease, including its metastatic pattern, by grafting ILC-derived breast cancer cell lines, SUM-44 PE and MDA-MB-134-VI cells, into the mouse milk ducts. Using patient-derived intraductal xenografts from lobular and non-lobular ER+ HER2- tumors to compare global gene expression, we identify extracellular matrix modulation as a lobular carcinoma cell-intrinsic trait. Analysis of TCGA patient datasets shows matrisome signature is enriched in lobular carcinomas with overexpression of elastin, collagens, and the collagen modifying enzyme LOXL1. Treatment with the pan LOX inhibitor BAPN and silencing of LOXL1 expression decrease tumor growth, invasion, and metastasis by disrupting ECM structure resulting in decreased ER signaling. We conclude that LOXL1 inhibition is a promising therapeutic strategy for ILC.

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Topics: Invasive lobular carcinoma (69%), Lobular carcinoma (69%), Metastasis (54%) ... read more

7 results found

Open accessJournal ArticleDOI: 10.15252/EMMM.202013807
Abstract: Invasive lobular carcinoma (ILC) of the breast is a very common disease. Despite its prevalence, these tumors are relatively understudied. One reason for this is a relative lack of models for ILC. This challenge was addressed by Brisken and colleagues through development of an intraductal injection-based xenograft system for the study of ERα+ breast cancers, including both ILC and more common invasive ductal carcinoma (IDC; Sflomos et al, 2016). In this issue of EMBO Molecular Medicine, the same group have applied intraductal injection-based xenografts to identify novel tumor cell-specific transcriptional signatures in ILC (Sflomos et al, 2021). In doing so they found overexpression of lysyl oxidase-like 1 (LOXL1) to be both responsible for the frequently seen stiff collagen-rich extracellular matrix of lobular breast cancer and essential for their robust growth and metastatic dissemination in vivo, thereby identifying a novel therapeutic target.

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4 Citations

Open accessJournal ArticleDOI: 10.1007/S00018-021-03860-4
Abstract: 17β-estradiol controls post-natal mammary gland development and exerts its effects through Estrogen Receptor ERα, a member of the nuclear receptor family. ERα is also critical for breast cancer progression and remains a central therapeutic target for hormone-dependent breast cancers. In this review, we summarize the current understanding of the complex ERα signaling pathways that involve either classical nuclear “genomic” or membrane “non-genomic” actions and regulate in concert with other hormones the different stages of mammary development. We describe the cellular and molecular features of the luminal cell lineage expressing ERα and provide an overview of the transgenic mouse models impacting ERα signaling, highlighting the pivotal role of ERα in mammary gland morphogenesis and function and its implication in the tumorigenic processes. Finally, we describe the main features of the ERα-positive luminal breast cancers and their modeling in mice.

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Topics: Mammary gland morphogenesis (64%), Estrogen receptor (55%), Nuclear receptor (51%) ... read more

3 Citations

Open accessJournal ArticleDOI: 10.3390/CANCERS13153695
22 Jul 2021-Cancers
Abstract: Invasive lobular breast cancer (ILC) is the most common special histological type of breast cancer (BC). This review recapitulates developments in the histomorphologic assessment of ILC from its beginnings with the seminal work of Foote and Stewart, which was published in 1941, until today. We discuss different concepts of ILC and their implications. These concepts include (i) BC arising from mammary lobules, (ii) BC growing in dissociated cells and single files, and (iii) BC defined as a morpho-molecular spectrum of tumors with distinct histological and molecular characteristics related to impaired cell adhesion. This review also provides a comprehensive overview of ILC variants, their histomorphology, and differential diagnosis. Furthermore, this review highlights recent advances which have contributed to a better understanding of the histomorphology of ILC, such as the role of the basal lamina component laminin, the molecular specificities of triple-negative ILC, and E-cadherin to P-cadherin expression switching as the molecular determinant of tubular elements in CDH1-deficient ILC. Last but not least, we provide a detailed account of the tumor microenvironment in ILC, including tumor infiltrating lymphocyte (TIL) levels, which are comparatively low in ILC compared to other BCs, but correlate with clinical outcome. The distinct histomorphology of ILC clearly reflects a special tumor biology. In the clinic, special treatment strategies have been established for triple-negative, HER2-positive, and ER-positive BC. Treatment specialization for patients diagnosed with ILC is just in its beginnings. Accordingly, ILC deserves greater attention as a special tumor entity in BC diagnostics, patient care, and cancer research.

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2 Citations

Open accessPosted ContentDOI: 10.1101/2021.07.22.453458
A. Patrik1, Z. Yueyun1, C. Stibolt1, M. Sendurai2  +3 moreInstitutions (3)
26 Jul 2021-bioRxiv
Abstract: Estrogen receptor α-positive (ER+) breast cancers (BCs) represent more than 70% of all breast cancers and pose a particular clinical challenge because they recur up to decades after initial diagnosis and treatment. The mechanisms governing tumor cell dormancy and latent disease remain elusive due to a lack of adequate models. Here, we compare tumor progression of ER+ and triple-negative (TN) BC subtypes with a clinically relevant mouse intraductal xenografting approach (MIND). Both ER+ and TN BC cells disseminate already during the in situstage. However, TN disseminated tumor cells (DTCs) proliferate at the same rate as cells at the primary site and give rise to macro-metastases. ER+ DTCs have low proliferative indices, form only micro-metastases and lose epithelial characteristics. Expression of CDH1 is decreased whereas the mesenchymal marker VIM and the transcription factors, ZEB1/ZEB2, which control epithelial-mesenchymal plasticity (EMP) are increased. EMP is not detected earlier during ER+ BC development and not required for invasion or metastasis. In vivo, forced transition to the epithelial state through ectopic E-cadherin expression overcomes dormancy with increased growth of lung metastases. We conclude that EMP is essential for the generation of a dormant cell state and the development of latent disease. Targeting exit from EMP is of therapeutic potential.

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Topics: Tumor progression (54%), Estrogen receptor (53%), Metastasis (50%) ... read more

1 Citations

Posted ContentDOI: 10.1101/2021.10.22.464987
22 Oct 2021-bioRxiv
Abstract: The mechanisms triggering the transition from in situ tumors to invasive carcinomas are poorly understood. The process involves breaching tumor-containing basement membranes (BM) and cancer cell invasion into the tumor stroma. Myosin-X (MYO10) is a filopodia-inducing protein frequently overexpressed in metastatic breast cancer. Here, we investigated the contribution of MYO10 to invasive breast tumor progression. We found that downregulation of MYO10 expression reduces breast cancer cell protrusions and migration in vitro. In addition, it attenuates protrusive activity and cell motility in early-stage breast cancer xenografts, which is in line with MYO109s established pro-invasive function. However, MYO10 depletion also promoted the local dispersal of increasingly basal-like tumor cells into the tumor stroma in vivo, resembling the transition from in situ to invasive tumors. MYO10-depleted tumors exhibited compromised BM structures, which correlated with increased mRNA expression but the reduced assembly of BM proteins surrounding the xenograft. Furthermore, MYO10-depleted 3D spheroids were defective in extracellular matrix (ECM) assembly around the spheroids, indicating a functional role for MYO10 in ECM deposition. Altogether, our data support a model where tumor cell protrusive activity, induced by MYO10, contributes to anti-invasive ECM organization at the in situ stages of breast cancer but promotes cell motility in advanced invasive breast cancer.

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Topics: Metastatic breast cancer (56%), Breast cancer (56%), Extracellular matrix (55%) ... read more


74 results found

Open accessJournal ArticleDOI: 10.1073/PNAS.0506580102
Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

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26,320 Citations

Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTP616
01 Jan 2010-Bioinformatics
Abstract: Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (

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Topics: Bioconductor (64%)

21,575 Citations

Open accessJournal ArticleDOI: 10.1093/NAR/GKV007
Matthew E. Ritchie1, Belinda Phipson2, Di Wu3, Yifang Hu1  +4 moreInstitutions (5)
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

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Topics: Microarray databases (61%), Bioconductor (51%)

13,819 Citations

Open accessJournal ArticleDOI: 10.1038/35021093
17 Aug 2000-Nature
Abstract: Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

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13,640 Citations

Open accessJournal ArticleDOI: 10.1093/BIOINFORMATICS/BTT656
Yang Liao1, Gordon K. Smyth1, Wei Shi1Institutions (1)
01 Apr 2014-Bioinformatics
Abstract: MOTIVATION: Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. RESULTS: We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. AVAILABILITY AND IMPLEMENTATION: featureCounts is available under GNU General Public License as part of the Subread ( or Rsubread ( software packages.

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8,495 Citations