IPH-926 lobular breast cancer cells are triple-negative but their microarray profile uncovers a luminal subtype

Optimized Modeling of Metastatic Triple-Negative Invasive Lobular Breast Carcinoma

Invasive lobular carcinoma (ILC) is a common breast cancer subtype that is often diagnosed at advanced stages and causes significant morbidity. Late-onset secondary tumor recurrence affects up to 30% of ILC patients, posing a therapeutic challenge if resistance to systemic therapy develops. Nonetheless, there is a lack of preclinical models for ILC, and the current models do not accurately reproduce the complete range of the disease. We created clinically relevant metastatic xenografts to address this gap by grafting the triple-negative IPH-926 cell line into mouse milk ducts. The resulting intraductal xenografts accurately recapitulate lobular carcinoma in situ (LCIS), invasive lobular carcinoma, and metastatic ILC in relevant organs. Using a panel of 15 clinical markers, we characterized the intratumoral heterogeneity of primary and metastatic lesions. Interestingly, intraductal IPH-926 xenografts express low but actionable HER2 and are not dependent on supplementation with the ovarian hormone estradiol for their growth. This model provides a valuable tool to test the efficiency of potential new ILC therapeutics, and it may help detect vulnerabilities within ILC that can be exploited for therapeutic targeting.

Atlas of Lobular Breast Cancer Models: Challenges and Strategic Directions

Invasive lobular carcinoma (ILC) accounts for up to 15% of all breast cancer (BC) cases and responds well to endocrine treatment when estrogen receptor α-positive (ER+) yet differs in many biological aspects from other ER+ BC subtypes. Up to 30% of patients with ILC will develop late-onset metastatic disease up to ten years after initial tumor diagnosis and may experience failure of systemic therapy. Unfortunately, preclinical models to study ILC progression and predict the efficacy of novel therapeutics are scarce. Here, we review the current advances in ILC modeling, including cell lines and organotypic models, genetically engineered mouse models, and patient-derived xenografts. We also underscore four critical challenges that can be addressed using ILC models: drug resistance, lobular tumor microenvironment, tumor dormancy, and metastasis. Finally, we highlight the advantages of shared experimental ILC resources and provide essential considerations from the perspective of the European Lobular Breast Cancer Consortium (ELBCC), which is devoted to better understanding and translating the molecular cues that underpin ILC to clinical diagnosis and intervention. This review will guide investigators who are considering the implementation of ILC models in their research programs.

Lobular Breast Cancer: Histomorphology and Different Concepts of a Special Spectrum of Tumors

Simple Summary

Invasive lobular breast cancer (ILC) is a special type of breast cancer (BC) that was first described in 1941. The diagnosis of ILC is made by microscopy of tumor specimens, which reveals a distinct morphology. This review recapitulates the developments in the microscopic assessment of ILC from 1941 until today. We discuss different concepts of ILC, provide an overview on ILC variants, and highlight advances which have contributed to a better understanding of ILC as a special histologic spectrum of tumors.

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.

Coexpression of PBX1 and EMP2 as Prognostic Biomarkers in Estrogen Receptor-Negative Breast Cancer via Data Mining

Previous studies revealed that PBX1 ranked the third in the differentially expressed genes about development and progression of breast cancer (BC). Nevertheless, the role of PBX1 contributing to progression of BC has been unevaluated. Here, on the basis of ONCOMINE and GOBO databases, we compared BC samples with normal controls about the expression of PBX1 in various types of cancers, as well as their related expression levels in cancer cell lines by Cancer Cell Line Encyclopedia (CCLE) analysis. It was also found that, when compared with normal controls, PBX1 was markedly higher expressed not only in BC samples but also in BC cell lines, and coexpressed with EMP2 by ONCOMINE and CCLE coexpression analysis, which was also expressed higher in BC samples and BC cell lines similarly. According to Kaplan-Meier plotter, we further explored the prognostic functions of PBX1 and EMP2 in different molecular subtypes of BC, respectively. We demonstrated that overexpression of PBX1 mRNA was correlated with worse survival in luminal B subtype BC, whereas increased EMP2 expression was associated with shorter relapse-free survival in estrogen receptor (ER)-negative patients. Combining with previous studies, we could make a conclusion that coexpression of PBX1 and EMP2 predicts poor prognosis in ER-negative BC, which could be effective biomarkers for BC.

Comparison of methods for the detection of outliers and associated biomarkers in mislabeled omics data

Background

Previous studies have reported that labeling errors are not uncommon in omics data. Potential outliers may severely undermine the correct classification of patients and the identification of reliable biomarkers for a particular disease. Three methods have been proposed to address the problem: sparse label-noise-robust logistic regression (Rlogreg), robust elastic net based on the least trimmed square (enetLTS), and Ensemble. Ensemble is an ensembled classification based on distinct feature selection and modeling strategies. The accuracy of biomarker selection and outlier detection of these methods needs to be evaluated and compared so that the appropriate method can be chosen.

Results

The accuracy of variable selection, outlier identification, and prediction of three methods (Ensemble, enetLTS, Rlogreg) were compared for simulated and an RNA-seq dataset. On simulated datasets, Ensemble had the highest variable selection accuracy, as measured by a comprehensive index, and lowest false discovery rate among the three methods. When the sample size was large and the proportion of outliers was ≤5%, the positive selection rate of Ensemble was similar to that of enetLTS. However, when the proportion of outliers was 10% or 15%, Ensemble missed some variables that affected the response variables.

Overall, enetLTS had the best outlier detection accuracy with false positive rates < 0.05 and high sensitivity, and enetLTS still performed well when the proportion of outliers was relatively large. With 1% or 2% outliers, Ensemble showed high outlier detection accuracy, but with higher proportions of outliers Ensemble missed many mislabeled samples. Rlogreg and Ensemble were less accurate in identifying outliers than enetLTS. The prediction accuracy of enetLTS was better than that of Rlogreg. Running Ensemble on a subset of data after removing the outliers identified by enetLTS improved the variable selection accuracy of Ensemble.

Conclusions

When the proportion of outliers is ≤5%, Ensemble can be used for variable selection. When the proportion of outliers is > 5%, Ensemble can be used for variable selection on a subset after removing outliers identified by enetLTS. For outlier identification, enetLTS is the recommended method. In practice, the proportion of outliers can be estimated according to the inaccuracy of the diagnostic methods used.

Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis

Colorectal cancer (CRC) is a prevalent malignant tumour type arising from the colon and rectum. The present study aimed to explore the molecular mechanisms of the development and progression of CRC. Initially, differentially expressed genes (DEGs) between CRC tissues and corresponding non-cancerous tissues were obtained by analysing the GSE15781 microarray dataset. The Database for Annotation, Visualization and Integrated Discovery was then utilized for functional and pathway enrichment analysis of the DEGs. Subsequently, a protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes and Proteins database and visualized by Cytoscape software. Furthermore, CytoNCA, a Cytoscape plugin, was used for centrality analysis of the PPI network to identify crucial genes. Finally, UALCAN was employed to validate the expression of the crucial genes and to estimate their effect on the survival of patients with colon cancer by Kaplan-Meier curves and log-rank tests. A total of 1,085 DEGs, including 496 upregulated and 589 downregulated genes, were screened out. The DEGs identified were enriched in various pathways, including ‘metabolic pathway’, ‘cell cycle’, ‘DNA replication’, ‘nitrogen metabolism’, ‘p53 signalling’ and ‘fatty acid degradation’. PPI network analysis suggested that interleukin-6, MYC, NOTCH1, inhibin subunit βA (INHBA), CDK1, cyclin (CCN)B1 and CCNA2 were crucial genes, and their expression levels were markedly upregulated. Survival analysis suggested that upregulated INHBA significantly decreased the survival probability of patients with CRC. Conversely, upregulation of CCNB1 and CCNA2 expression levels were associated with increased survival probabalities. The identified DEGs, particularly the crucial genes, may enhance the current understanding of the genesis and progression of CRC, and certain genes, including INHBA, CCNB1 and CCNA2, may be candidate diagnostic and prognostic markers, as well as targets for the treatment of CRC.

The Pivotal Roles of the Epithelial Membrane Protein Family in Cancer Invasiveness and Metastasis

The members of the family of epithelial membrane proteins (EMPs), EMP1, EMP2, and EMP3, possess four putative transmembrane domain structures and are composed of approximately 160 amino acid residues. EMPs are encoded by the growth arrest-specific 3 (GAS3)/peripheral myelin protein 22 kDa (PMP22) gene family. The GAS3/PMP22 family members play roles in cell migration, growth, and differentiation. Evidence indicates an association of these molecules with cancer progression and metastasis. Each EMP has pro- and anti-metastatic functions that are likely involved in the complex mechanisms of cancer progression. We have recently demonstrated that the upregulation of EMP1 expression facilitates cancer cell migration and invasion through the activation of a small GTPase, Rac1. The inoculation of prostate cancer cells overexpressing EMP1 into nude mice leads to metastasis to the lymph nodes and lungs, indicating that EMP1 contributes to metastasis. Pro-metastatic properties of EMP2 and EMP3 have also been proposed. Thus, targeting EMPs may provide new insights into their clinical utility. Here, we highlight the important aspects of EMPs in cancer biology, particularly invasiveness and metastasis, and describe recent therapeutic approaches.

Robust identification of target genes and outliers in triple-negative breast cancer data

Correct classification of breast cancer subtypes is of high importance as it directly affects the therapeutic options. We focus on triple-negative breast cancer which has the worst prognosis among breast cancer types. Using cutting edge methods from the field of robust statistics, we analyze Breast Invasive Carcinoma transcriptomic data publicly available from The Cancer Genome Atlas data portal. Our analysis identifies statistical outliers that may correspond to misdiagnosed patients. Furthermore, it is illustrated that classical statistical methods may fail to identify outliers due to their heavy influence, prompting the need for robust statistics. Using robust sparse logistic regression we obtain 36 relevant genes, of which ca. 60% have been previously reported as biologically relevant to triple-negative breast cancer, reinforcing the validity of the method. The remaining 14 genes identified are new potential biomarkers for triple-negative breast cancer. Out of these, JAM3, SFT2D2, and PAPSS1 were previously associated to breast tumors or other types of cancer. The relevance of these genes is confirmed by the new DetectDeviatingCells outlier detection technique. A comparison of gene networks on the selected genes showed significant differences between triple-negative breast cancer and non-triple-negative breast cancer data. The individual role of FOXA1 in triple-negative breast cancer and non-triple-negative breast cancer, and the strong FOXA1-AGR2 connection in triple-negative breast cancer stand out. The goal of our paper is to contribute to the breast cancer/triple-negative breast cancer understanding and management. At the same time it demonstrates that robust regression and outlier detection constitute key strategies to cope with high-dimensional clinical data such as omics data.

Lobular carcinoma in situ and invasive lobular breast cancer are characterized by enhanced expression of transcription factor AP-2β

Transcription factor AP-2β (TFAP2B) regulates embryonic organ development and is overexpressed in alveolar rhabdomyosarcoma, a rare childhood malignancy. Gene expression profiling has implicated AP-2β in breast cancer (BC). This study characterizes AP-2β expression in the mammary gland and in BC. AP-2β protein expression was assessed in the normal mammary gland epithelium, in various reactive, metaplastic and pre-invasive neoplastic lesions and in two clinical BC cohorts comprising >2000 patients. BCs from various genetically engineered mouse (GEM) models were also evaluated. Human BC cell lines served as functional models to study siRNA-mediated inhibition of AP-2β. The normal mammary gland epithelium showed scattered AP-2β-positive cells in the luminal cell layer. Various reactive and pre-invasive neoplastic lesions, including apocrine metaplasia, usual ductal hyperplasia and lobular carcinoma in situ (LCIS) showed enhanced AP-2β expression. Cases of ductal carcinoma in situ (DCIS) were more often AP-2β-negative (P<0.001). In invasive BC cohorts, AP-2β-positivity was associated with the lobular BC subtype (P<0.001), loss of E-cadherin (P<0.001), a positive estrogen receptor (ER) status (P<0.001), low Ki67 (P<0.001), low/intermediate Oncotype DX recurrence scores (P<0.001), and prolonged event-free survival (P=0.003). BCs from GEM models were all AP-2β-negative. In human BC cell lines, AP-2β expression was independent from ER-signaling. SiRNA-mediated inhibition of AP-2β diminished proliferation of lobular BC cell lines in vitro. In summary, AP-2β is a new mammary epithelial differentiation marker. Its expression is preferentially retained and enhanced in LCIS and invasive lobular BC and has prognostic implications. Our findings indicate that AP-2β controls tumor cell proliferation in this slow-growing BC subtype.

Breast Cancer and African Ancestry: Lessons Learned at the 10-Year Anniversary of the Ghana-Michigan Research Partnership and International Breast Registry

Women with African ancestry in western, sub-Saharan Africa and in the United States represent a population subset facing an increased risk of being diagnosed with biologically aggressive phenotypes of breast cancer that are negative for the estrogen receptor, the progesterone receptor, and the HER2/neu marker. These tumors are commonly referred to as triple-negative breast cancer. Disparities in breast cancer incidence and outcome related to racial or ethnic identity motivated the establishment of the International Breast Registry, on the basis of partnerships between the Komfo Anokye Teaching Hospital in Kumasi, Ghana, the University of Michigan Comprehensive Cancer Center in Ann Arbor, Michigan, and the Henry Ford Health System in Detroit, Michigan. This research collaborative has featured educational training programs as well as scientific investigations related to the comparative biology of breast cancer in Ghanaian African, African American, and white/European American patients. Currently, the International Breast Registry has expanded to include African American patients throughout the United States by partnering with the Sisters Network (a national African American breast cancer survivors' organization) and additional sites in Ghana (representing West Africa) as well as Ethiopia (representing East Africa). Its activities are now coordinated through the Henry Ford Health System International Center for the Study of Breast Cancer Subtypes. Herein, we review the history and results of this international program at its 10-year anniversary.

Breast Cancer Anti-Estrogen Resistance 4 (BCAR4) Drives Proliferation of IPH-926 lobular Carcinoma Cells

Background

Most breast cancers depend on estrogenic growth stimulation. Functional genetic screenings in in vitro cell models have identified genes, which override growth suppression induced by anti-estrogenic drugs like tamoxifen. Using that approach, we have previously identified Breast Cancer Anti-Estrogen Resistance 4 (BCAR4) as a mediator of cell proliferation and tamoxifen-resistance. Here, we show high level of expression and function of BCAR4 in human breast cancer.

Methods

BCAR4 mRNA expression was evaluated by (q)RT-PCR in a panel of human normal tissues, primary breast cancers and cell lines. A new antibody raised against C78-I97 of the putative BCAR4 protein and used for western blot and immunoprecipitation assays. Furthermore, siRNA-mediated gene silencing was implemented to study the function of BCAR4 and its downstream targets ERBB2/3.

Results

Except for placenta, all human normal tissues tested were BCAR4-negative. In primary breast cancers, BCAR4 expression was comparatively rare (10%), but associated with enhanced proliferation. Relative high BCAR4 mRNA expression was identified in IPH-926, a cell line derived from an endocrine-resistant lobular breast cancer. Moderate BCAR4 expression was evident in MDA-MB-134 and MDA-MB-453 breast cancer cells. BCAR4 protein was detected in breast cancer cells with ectopic (ZR-75-1-BCAR4) and endogenous (IPH-926, MDA-MB-453) BCAR4 mRNA expression. Knockdown of BCAR4 inhibited cell proliferation. A similar effect was observed upon knockdown of ERBB2/3 and exposure to lapatinib, implying that BCAR4 acts in an ERBB2/3-dependent manner.

Conclusion

BCAR4 encodes a functional protein, which drives proliferation of endocrine-resistant breast cancer cells. Lapatinib, a clinically approved EGFR/ERBB2 inhibitor, counteracts BCAR4-driven tumor cell growth, a clinical relevant observation.

Lobular breast cancer: molecular basis, mouse and cellular models

Infiltrating lobular breast cancer (ILC) is the most common special breast cancer subtype. With mutational or epigenetic inactivation of the cell adhesion molecule E-cadherin (CDH1) being confined almost exclusively to ILC, this tumor entity stands out from all other types of breast cancers. The molecular basis of ILC is linked to loss of E-cadherin, as evidenced by human CDH1 germline mutations and conditional knockout mouse models. A better understanding of ILC beyond the level of descriptive studies depends on physiologically relevant and functional tools. This review provides a detailed overview on ILC models, including well-characterized cell lines, xenograft tumors and genetically engineered mouse models. We consider advantages and limitations of these models and evaluate their representativeness for human ILC. The still incompletely defined mechanisms by which loss of E-cadherin drives malignant transformation are discussed based on recent findings in these models. Moreover, candidate genes and signaling pathways potentially involved in ILC development and progression as well as anticancer drug and endocrine resistance are highlighted.

IPH-926 lobular breast cancer cells are triple-negative but their microarray profile uncovers a luminal subtype

Human primary breast cancers and breast cancer cell lines are classified by microarray-defined molecular subtypes, which reflect differentiation characteristics. Estrogen receptor (ER) expression is indicative of the luminal molecular subtype. We have previously established IPH-926, the first well-characterized cell line from infiltrating lobular breast cancer. IPH-926 displays an ER/PR/ErbB2 triple-negative immunophenotype, which is due to a loss of ER expression in its in vivo clonal ancestry. Loss of ER might indicate a fundamental change of cellular differentiation and it is unclear whether a luminal subtype is preserved beyond ER conversion. Using Affymetrix microarray analysis, seven different classifier gene lists (PAM305, DISC256, TN1288, PAM50, UNC1300, LAB704, INT500) and a background population of 50 common mammary carcinoma cell lines, we have now determined the molecular subtype of IPH-926. Strikingly, the IPH-926 expression profile is highly consistent with a luminal subtype. It is nearest to luminal/ER-positive breast cancer cell lines and far apart from basal breast cancer cell lines. Quantitative real-time RT-PCR confirmed enhanced expression of luminal marker genes (AGR2, CLU, CA12, EMP2, CLDN3) and low or absent expression of basal marker genes (KRT5, CD44, CAV1, VIM). Moreover, IPH-926 lacked androgen receptor (AR) expression, a transcription factor previously associated with luminal-like gene expression in a subset of triple-negative or molecular apocrine breast cancers. In conclusion, IPH-926 is triple-negative but belongs to the luminal subtype. Luminal differentiation characteristics can be preserved beyond ER conversion and might not require a compensatory expression of AR.