Clinical and molecular predictors of long-term response in HER2 positive metastatic breast cancer patients

Genomic insights and prognostic significance of novel biomarkers in pancreatic ductal adenocarcinoma: A comprehensive analysis

Pancreatic ductal adenocarcinoma (PDAC) is a highly prevalent digestive system malignancy, with a significant impact on public health, especially in the elderly population. The advent of the Human Genome Project has opened new avenues for precision medicine, allowing researchers to explore genetic markers and molecular targets for cancer diagnosis and treatment. Despite significant advances in genomic research, early diagnosis of pancreatic cancer remains elusive due to the lack of highly sensitive and specific markers. Therefore, there is a need for in-depth research to identify more precise and reliable diagnostic markers for pancreatic cancer. In this study, we utilized a combination of public databases from different sources to meticulously screen genes associated with prognosis in pancreatic cancer. We used gene differential analysis, univariate cox regression analysis, least absolute selection and shrinkage operator (LASSO) regression, and multivariate cox regression analysis to identify genes associated with prognosis. Subsequently, we constructed a scoring system, validated its validity using survival analysis and ROC analysis, and further confirmed its reliability by nomogram and decision curve analysis (DCA). We evaluated the diagnostic value of this scoring system for pancreatic cancer prognosis and validated the function of the genes using single cell data analysis. Our analysis identifies six genes, including GABRA3, IL20RB, CDK1, GPR87, TTYH3, and KCNA2, that were strongly associated with PDAC prognosis. Clinical prognostic models based on these genes showed strong predictive power not only in the training set but also in external datasets. Functional enrichment analysis revealed significant differences between high- and low-risk groups mainly in immune-related functions. Additionally, we explored the potential of the risk score as a marker for immunotherapy response and identified key factors within the tumor microenvironment. The single-cell RNA sequencing analysis further enriched our understanding of cell clusters and six hub genes expressions. This comprehensive investigation provides valuable insights into pancreatic PDAC and its intricate immune landscape. The identified genes and their functional significance underscore the importance of continued research into improving diagnosis and treatment strategies for PDAC.

The impact of genomic context on outcomes of solid cancer patients treated with genotype-matched targeted therapies: a comprehensive review

INTRODUCTION

A critical need in the field of genotype-matched targeted therapy in cancer is to identify patients unlikely to respond to precision medicines. This will manage expectations of individualised therapies and avoid clinical progression to a point where institution of alternative treatments might not be possible. We examined the evidence base of the impact of genomic context on which targeted alterations are inscribed to identify baseline biomarkers distinguishing those obtaining the expected response from those with less benefit from targeted therapies.

METHODS

A comprehensive narrative review was conducted: scoping searches were undertaken in PubMed, Cochrane Database of Systematic Reviews, and PROSPERO. Outcomes included in meta-analysis were progression-free and overall survival. Data were extracted from Kaplan-Meier and used to calculate hazard ratios. Studies presenting data on two molecular subcohorts (e.g. co-mutation versus no co-mutation) were included in fixed meta-analysis. Other studies were used for descriptive purposes.

RESULTS

The presence of concomitant driver mutations, higher tumour mutational burden (TMB), greater copy number burden, and APOBEC signatures significantly reduces benefits of targeted therapy in lung cancers in never smokers (LCINS - less than 100 cigarettes per lifetime) and breast cancer, cancers with low TMB. LCINS have significantly poorer outcomes if their cancers harbour p53 co-mutations, an effect also seen in human epidermal growth factor receptor 2-positive (HER2+) breast cancer patients (trastuzumab) and head and neck cancer patients [phosphoinositide 3-kinase (PI3K) inhibition]. PI3K co-alterations have less impact when targeting epidermal growth factor receptor mutations and anaplastic lymphoma kinase fusions, but significantly reduce the impact of targeting HER2 and MET amplifications. SMARCA4 co-mutations predict for poor outcome in patients treated with osimertinib and sotorasib. In BRAF-mutant melanoma, whilst there are no genomic features distinguishing exceptional responders from primary progressors, there are clear transcriptomic features dichotomising these outcomes.

CONCLUSION

To our knowledge, this is the most comprehensive review to date of the impact of genomic context on outcomes with targeted therapy. It represents a valuable resource informing progress towards contextualised precision medicine.

BRCA1 and NORE1A Form a Her2/Ras Regulated Tumor Suppressor Complex Modulating Senescence

BRCA1 is a tumor suppressor with a complex mode of action. Hereditary mutations in BRCA1 predispose carriers to breast cancer, and spontaneous breast cancers often exhibit defects in BRCA1 expression. However, haploinsufficiency or suppression of BRCA1 expression leads to defects in DNA repair, which can induce DNA damage responses, leading to senescence. Activating mutation or overexpression of the Her2 oncoprotein are also frequent drivers of breast cancer. Yet, over-activation of Her2, working through the RAS oncoprotein, can also induce senescence. It is thought that additional defects in the p53 and Rb tumor suppressor machinery must occur in such tumors to allow an escape from senescence, thus permitting tumor development. Although BRCA1 mutant breast cancers are usually Her2 negative, a significant percentage of Her2 positive tumors also lose their expression of BRCA1. Such Her2+/BRCA1- tumors might be expected to have a particularly high senescence barrier to overcome. An important RAS senescence effector is the protein NORE1A, which can modulate both p53 and Rb. It is an essential senescence effector of the RAS oncoprotein, and it is often downregulated in breast tumors by promotor methylation. Here we show that NORE1A forms a Her2/RAS regulated, endogenous complex with BRCA1 at sites of replication fork arrest. Suppression of NORE1A blocks senescence induction caused by BRCA1 inactivation and Her2 activation. Thus, NORE1A forms a tumor suppressor complex with BRCA1. Its frequent epigenetic inactivation may facilitate the transformation of Her2+/BRCA1- mediated breast cancer by suppressing senescence.

Response prediction in patients with gastric and esophagogastric adenocarcinoma under neoadjuvant chemotherapy using targeted gene expression analysis and next-generation sequencing in pre-therapeutic biopsies

OBJECTIVES

Perioperative chemo-(radio-) therapy is the accepted standard in European patients with locally advanced adenocarcinoma of the esophagogastric junction or stomach (AEG/AS). However, 30-85% of patients do not respond to this treatment. The aim of our study was the identification of predictive biomarkers in pre-therapeutic endoscopic tumor biopsies from patients with histopathologic response (Becker-1) versus non-response (Becker-2/3) to preoperative chemotherapy.

METHODS

Formalin-fixed paraffin-embedded biopsies from 36 Caucasian patients (Becker-1 n = 11, Becker-2 n = 7, Becker-3 n = 18) with AEG/AS, taken prior to neoadjuvant chemotherapy were selected. For RNA expression analysis, we employed the NanoString nCounter System. To identify genomic alterations like single nucleotide variants (SNV), copy number variation (CNV) and fusion events, we used Illumina TST170 gene panel. For HER2 and FGFR2 protein expression, immunostaining was performed. Furthermore, we analyzed the microsatellite instability (MSI) and Epstein-Barr virus (EBV) infection status by EBER in situ hybridization.

RESULTS

Heat map and principal component analyses showed no clustering by means of gene expression according to regression grade. Concerning two recently proposed predictive markers, our data showed equal distribution for MSI (Becker-1: 2; Becker-2: 1; Becker-3: 3; out of 29 tested) and EBV infection was rare (1/32). We could not reveal discriminating target genes concerning SNV, but found a higher mutational burden in non-responders versus responders and fusion (in 6/14) and CNV events (in 5/14) exclusively in Becker-3.

CONCLUSIONS

Although we could not identify discriminating target genes, our data suggest that molecular alterations are in general more prevalent in patients with AEG/AS belonging to the non-responding Becker group 3.

Identification of IL20RB as a Novel Prognostic and Therapeutic Biomarker in Clear Cell Renal Cell Carcinoma

Background

Clear cell renal cell carcinoma (ccRCC) is a type of life-threatening malignant tumor of the urinary system. IL20RB, interleukin 20 receptor subunit beta, is a cytokine receptor subunit coding gene and was initially found to play a vital role in human cancers, while its role in ccRCC still remains unclear.

Methods

In this work, we explored the prognostic value and therapeutic potential of IL20RB in ccRCC mainly by online tools. Firstly, we used UALCAN and GEPIA to explore the expression profile and prognostic value of IL20RB in various cancers; the expression profile in tumor cell lines was also analysed with CCLE and Expression Atlas. Then, we decided to focus on ccRCC for further analysis; we further demonstrated the significant correlation between expression and clinical features by GEPIA and UALCAN. In order to reveal the potential intrinsic mechanism responsible for the upregulation of IL20RB in ccRCC, we made genetic alternation analysis and methylation analysis. cBioPortal was used for genetic alternation analysis. UALCAN, MethSurv, and Xena were used for methylation analysis. To learn details of how IL20RB might function in ccRCC, we further conducted functional analysis and immune infiltration analysis. STRING and GSEA were used to do functional analysis. TIMER was used for immune infiltration analysis; KM plotter was used for survival analysis.

Results

Results show that IL20RB is upregulated in ccRCC, and low methylation may be responsible for its upregulation. Both high expression and low methylation of IL20RB predict worse survival, and both have a strong positive correlation with clinical characteristics. In addition, results indicate that there exists a crosstalk between IL20RB and neutrophils. Furthermore, the immune microenvironment could influence the prognosis predicting ability of IL20RB.

Conclusions

In conclusion, IL20RB plays an important role in ccRCC and is identified as a novel prognostic and potential therapeutic biomarker in ccRCC.

Understanding and overcoming tumor heterogeneity in metastatic breast cancer treatment

Rational development of targeted therapies has revolutionized metastatic breast cancer outcomes, although resistance to treatment remains a major challenge. Advances in molecular profiling and imaging technologies have provided evidence for the impact of clonal diversity in cancer treatment resistance, through the outgrowth of resistant clones. In this Review, we focus on the genomic processes that drive tumoral heterogeneity and the mechanisms of resistance underlying metastatic breast cancer treatment and discuss implications for future treatment strategies.

A graph convolutional neural network for gene expression data analysis with multiple gene networks

Spectral graph convolutional neural networks (GCN) are proposed to incorporate important information contained in graphs such as gene networks. In a standard spectral GCN, there is only one gene network to describe the relationships among genes. However, for genomic applications, due to condition- or tissue-specific gene function and regulation, multiple gene networks may be available; it is unclear how to apply GCNs to disease classification with multiple networks. Besides, which gene networks may provide more effective prior information for a given learning task is unknown a priori and is not straightforward to discover in many cases. A deep multiple graph convolutional neural network is therefore developed here to meet the challenge. The new approach not only computes a feature of a gene as the weighted average of those of itself and its neighbors through spectral GCNs, but also extracts features from gene-specific expression (or other feature) profiles via a feed-forward neural networks (FNN). We also provide two measures, the importance of a given gene and the relative importance score of each gene network, for the genes' and gene networks' contributions, respectively, to the learning task. To evaluate the new method, we conduct real data analyses using several breast cancer and diffuse large B-cell lymphoma datasets and incorporating multiple gene networks obtained from "GIANT 2.0" Compared with the standard FNN, GCN, and random forest, the new method not only yields high classification accuracy but also prioritizes the most important genes confirmed to be highly associated with cancer, strongly suggesting the usefulness of the new method in incorporating multiple gene networks.

Construction of a five-gene prognostic model based on immune-related genes for the prediction of survival in pancreatic cancer

Purpose: To identify differentially expressed immune-related genes (DEIRGs) and construct a model with survival-related DEIRGs for evaluating the prognosis of patients with pancreatic cancer (PC).

Methods: Six microarray gene expression datasets of PC from the Gene Expression Omnibus (GEO) and Immunology Database and Analysis Portal (ImmPort) were used to identify DEIRGs. RNA sequencing and clinical data from The Cancer Genome Atlas Program-Pancreatic Adenocarcinoma (TCGA-PAAD) database were used to establish the prognostic model. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to determine the final variables of the prognostic model. The median risk score was used as the cut-off value to classify samples into low- and high-risk groups. The prognostic model was further validated using an internal validation set of TCGA and an external validation set of GSE62452.

Results: In total, 142 DEIRGs were identified from six GEO datasets, 47 were survival-related DEIRGs. A prognostic model comprising five genes (i.e., ERAP2, CXCL9, AREG, DKK1, and IL20RB) was established. High-risk patients had poor survival compared with low-risk patients. The 1-, 2-, 3-year area under the receiver operating characteristic (ROC) curve of the model reached 0.85, 0.87, and 0.93, respectively. Additionally, the prognostic model reflected the infiltration of neutrophils and dendritic cells. The expression of most characteristic immune checkpoints was significantly higher in the high-risk group versus the low-risk group.

Conclusions: The five-gene prognostic model showed reliably predictive accuracy. This model may provide useful information for immunotherapy and facilitate personalized monitoring for patients with PC.

Prolonged Responses With Trastuzumab Emtasine Treatment of Human Epidermal Growth Factor Receptor 2-positive Metastatic Breast Cancer Refractory to Trastuzumab and Pertuzumab: Systematic Review of Evidence

Amplification of human epidermal growth factor receptor 2 (HER2) occurs in around 25% of breast cancers and has been associated with aggressive disease. Here, we summarize published evidence on efficacy and prolonged responses with trastuzumab emtansine (T-DM1) after first-line trastuzumab plus pertuzumab and provide possible factors related to prolonged responses to T-DM1. We conducted a literature search using PubMed, and articles that were published in English between July 1, 2012 and December 31, 2019 were included. A review of the bibliography included in the articles found was made. Nine articles were eligible; 2 were case reports, and the remaining 7 were nonexperimental studies, all retrospective. Five were multi-center works. The total number of patients was 796 (276 received pertuzumab). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was used for this systematic review. The population included was heterogeneous among studies according to hormone receptor status, de novo metastatic disease, number of metastatic sites, visceral involvement, brain metastasis, previous neoadjuvant or adjuvant trastuzumab, and line of therapy in which T-DM1 was administered. Less efficacy in terms of responses (overall response rate, 18%-33%) and progression-free survival (4-6 months) with second-line T-DM1, in patients pretreated with pertuzumab, was shown (if compared with the EMILIA trial). The results are more similar to those of the TH3RESA trial (very pretreated population). Prolonged treatments (6 months or more) were observed in at least 17% of cases. The efficacy of T-DM1 after a previous pertuzumab treatment is lower than if pertuzumab is not given, although prolonged responses are observed in this setting.

Comprehensive analysis of prognostic immune-related genes associated with the tumor microenvironment of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with a specific tumor immune microenvironment (TIME). Therefore, investigating prognostic immune-related genes (IRGs) that are closely associated with TIME to predict PDAC clinical outcomes is necessary. In the present study, 459 samples of PDAC from the Genotype-Tissue Expression database, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO) were included and a survival-associated module was identified using weighted gene co-expression network analysis. Based on the Cox regression analysis and least absolute shrinkage and selection operator analysis, four IRGs (2′-5′-oligoadenylate synthetase 1, MET proto-oncogene, receptor tyrosine kinase, interleukin 1 receptor type 2 and interleukin 20 receptor subunit β) were included in the prognostic model to calculate the risk score (RS), and patients with PDAC were divided into high- and low-RS groups. Kaplan-Meier survival and receiver operating characteristic curve analyses demonstrated that the low-RS group had significantly improved survival conditions compared with the high-RS group in TCGA training set. The prognostic function of the model was also validated using ICGC and GEO cohorts. To investigate the mechanism of different overall survival between the high- and low-RS groups, the present study included Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data and Cell Type Identification by Estimating Relative Subset of Known RNA Transcripts algorithms to investigate the state of the tumor microenvironment and immune infiltration inpatients in the cohort from TCGA. In summary, four genes associated with the TIME of PDAC were identified, which may provide a reference for clinical treatment.

Prognostic factors and survival outcomes according to tumor subtype in patients with breast cancer lung metastases

Background

Reports on the incidence and prognoses of lung metastases when diagnosing breast cancer patients with different subtypes are limited. Our study investigated the effect of molecular sub-typing stratification on the prognoses of lung metastatic breast caner patients.

Methods

Patients with breast cancer and lung metastases were identified from Surveillance, Epidemiology and End Results population-based data between 2010 and 2015. Univariate and multivariate Cox regression analyses were performed to identify risk factors and prognoses, overall survival (OS) and breast cancer-specific survival for patients with breast cancer lung metastases.

Results

We identified 6,516 patients with lung metastatic breast cancer, representing 1.7% of the entire cohort and 30.4% of the subset with metastatic disease. This included 2,940 hormone receptor (HR)+/HER2- patients, 852 HR+/HER2+ patients, 547 HR-/HER2+ patients and 983 triple-negative patients. The median OS for all lung metastatic patients was 13 months. Multivariate analysis revealed that those lung metastatic breast cancer patients of older age (>80), black race, with poorly differentiated tumors, carcinoma histology, triple-negative subtype, more metastatic sites and no surgery, and no chemotherapy showed significantly poor survival, both overall and breast cancer-specific.

Conclusions

Our findings show that molecular sub-type and more metastatic sites might have significant influence on the incidence and prognosis of breast cancer lung metastases. We also identified several prognostic factors that could guide therapy selection in the treatment of lung metastatic patients.

Herceptin-conjugated paclitaxel loaded PCL-PEG worm-like nanocrystal micelles for the combinatorial treatment of HER2-positive breast cancer

We have constructed Herceptin-conjugated, paclitaxel (PTX) loaded, PCL-PEG worm-like nanocrystal micelles (PTX@PCL-PEG-Herceptin) for the combinatorial therapy of HER2-positive breast cancer that exploit the specific targeting of Herceptin to HER2-positive breast cancer cells. Firstly, amphiphilic PCL₂₀₀₀-MPEG₂₀₀₀ and PCL₅₀₀₀-PEG₂₀₀₀-CHO were selected as the optimized matrix to wrap PTX that self-assembled into worm-like micelles with internal nanocrystal structures (PTX@PCL-PEG). Then the aldehydes of PCL₅₀₀₀-PEG₂₀₀₀-CHO exposed on the outside surface of PTX@PCL-PEG were utilized to react with the primary amines of Herceptin and formed stable, carbon-nitrogen single linkers (-C-N-) between the antibodies and nanoparticles. This study shows PTX@PCL-PEG-Herceptin remained relatively stable in the circulation and in the tumor microenvironment, and rapidly targeted and entered into the HER2-overexpressing tumor cells while sparing normal tissues from the toxic effects. PTX@PCL-PEG-Herceptin shrank the tumors and prolonged survival time in a SKBR-3-tumor-xenograft, nude mice model more effectively than TAXOL®, PTX@PCL-PEG, Herceptin+TAXOL® and Herceptin+PTX@PCL-PEG. Mechanistic studies showed that PTX@PCL-PEG-Herceptin entered into the HER2-positive tumor cells through the caveolin-mediated pathway. The conjugated Herceptin greatly enhanced the binding ability of the nanoparticle to the targeted SKBR-3 cells. This novel strategy provides a rational and simple antibody-conjugated-nanoparticle platform for the clinical application of combinatorial anticancer treatment.

Overexpression of interleukin-20 receptor subunit beta (IL20RB) correlates with cell proliferation, invasion and migration enhancement and poor prognosis in papillary renal cell carcinoma

Papillary renal cell carcinoma (PRCC) accounts for about 10 percent of all renal cell carcinomas, and the prognosis is poor for people with advanced disease. Interleukin-20 receptor subunit beta (IL20RB) is a single-pass type I membrane protein of the type II cytokine receptor family and is related to the pathogenesis of chronic inflammation and autoimmune diseases, including psoriasis, glaucoma, vitiligo, rheumatoid arthritis, and inflammatory bowel disease. However, little has been reported on IL20RB with respect to cancer, especially in PRCC. Thus, we performed this study to explore its biological characteristics in PRCC. Data from the TCGA database were used to analyze the expression and prognosis of IL20RB. qRT-PCR was used to detect the expression of IL20RB in PRCC cells in vitro. After knockdown of IL20RB with small interfering RNA (siRNA) technology, the proliferation, migration, and invasion of Ketr-3 cells and the expression of related proteins in the epithelial-mesenchymal transition (EMT) pathway were measured with Cell Counting Kit-8 (CCK-8), transwell, and western blot assays. The findings demonstrated that the expression of IL20RB was upregulated in both PRCC tissues and cells and that the high expression of IL20RB led to low overall survival (OS). Furthermore, after knockdown of IL20RB in vitro, the proliferation, migration, and invasion of Ketr-3 cells were reduced, and the expression of related proteins in the EMT pathway declined, suggesting that IL20RB plays a vital role in PRCC through the EMT pathway. These results reveal the biological significance of IL20RB in PRCC and provide new insight for future targeted drugs.

Emerging roles for multifunctional ion channel auxiliary subunits in cancer

Several superfamilies of plasma membrane channels which regulate transmembrane ion flux have also been shown to regulate a multitude of cellular processes, including proliferation and migration. Ion channels are typically multimeric complexes consisting of conducting subunits and auxiliary, non-conducting subunits. Auxiliary subunits modulate the function of conducting subunits and have putative non-conducting roles, further expanding the repertoire of cellular processes governed by ion channel complexes to processes such as transcellular adhesion and gene transcription. Given this expansive influence of ion channels on cellular behaviour it is perhaps no surprise that aberrant ion channel expression is a common occurrence in cancer. This review will focus on the conducting and non-conducting roles of the auxiliary subunits of various Ca2+, K+, Na+ and Cl- channels and the burgeoning evidence linking such auxiliary subunits to cancer. Several subunits are upregulated (e.g. Cavβ, Cavγ) and downregulated (e.g. Kvβ) in cancer, while other subunits have been functionally implicated as oncogenes (e.g. Navβ1, Cavα2δ1) and tumour suppressor genes (e.g. CLCA2, KCNE2, BKγ1) based on in vivo studies. The strengthening link between ion channel auxiliary subunits and cancer has exposed these subunits as potential biomarkers and therapeutic targets. However further mechanistic understanding is required into how these subunits contribute to tumour progression before their therapeutic potential can be fully realised.

Differential molecular pathways expression in HER2 positive early breast cancer according to hormone receptor status

PURPOSE

Hormone receptors (HR) status in HER2 + breast cancer (BC) is a recognized stratification factor with relevant clinical implication. According to HR expression, HER2 + BC show different clinical characteristics, treatment sensitivity and prognosis. The interaction between HR and HER2 pathways remains incompletely understood.

METHODS

Thirty-four HER2 + BC were included: 18 tumors with HER2+/HR + and 16 with HER2+/HR-. The expression of 770 genes and 13 molecular pathways were evaluated using Nanostring PanCancer Pathway panel performed on FFPE BC biopsies.

RESULTS

Gene expression analysis identified 127 genes with significantly different expression between the two cohorts. 83% of these genes were overexpressed in HER2+/HR- cohort. Globally, 23% of them belonged to PI3K pathway (41 genes), 15% to Trascriptional regulation (26 genes) and 12% to MAPK (22 genes). Regarding pathway expression, PI3K, MAPK and NOTCH were significantly differently expressed between the two groups (p = 0.003, p = 0.0018 and p = 0.02, respectively), all of them were overexpressed in HER2+/HR- tumors.

CONCLUSIONS

According to HR status, HER2 + tumors express different pathways profiles: the overexpression of PI3K, MAPK and NOTCH pathways in HER2+/HR- group could justify different survival outcomes and treatment sensitivity. The identification of tumor driver pathways may be a useful instrument for individualized pathway-directed therapies. Further clinical implications are warranted.

NOTCH3 expression is linked to breast cancer seeding and distant metastasis

Background

Development of distant metastases involves a complex multistep biological process termed the invasion-metastasis cascade, which includes dissemination of cancer cells from the primary tumor to secondary organs. NOTCH developmental signaling plays a critical role in promoting epithelial-to-mesenchymal transition, tumor stemness, and metastasis. Although all four NOTCH receptors show oncogenic properties, the unique role of each of these receptors in the sequential stepwise events that typify the invasion-metastasis cascade remains elusive.

Methods

We have established metastatic xenografts expressing high endogenous levels of NOTCH3 using estrogen receptor alpha-positive (ERα⁺) MCF-7 breast cancer cells with constitutive active Raf-1/mitogen-associated protein kinase (MAPK) signaling (vMCF-7^Raf-1) and MDA-MB-231 triple-negative breast cancer (TNBC) cells. The critical role of NOTCH3 in inducing an invasive phenotype and poor outcome was corroborated in unique TNBC cells resulting from a patient-derived brain metastasis (TNBC-M25) and in publicly available claudin-low breast tumor specimens collected from participants in the Molecular Taxonomy of Breast Cancer International Consortium database.

Results

In this study, we identified an association between NOTCH3 expression and development of metastases in ERα⁺ and TNBC models. ERα⁺ breast tumor xenografts with a constitutive active Raf-1/MAPK signaling developed spontaneous lung metastases through the clonal expansion of cancer cells expressing a NOTCH3 reprogramming network. Abrogation of NOTCH3 expression significantly reduced the self-renewal and invasive capacity of ex vivo breast cancer cells, restoring a luminal CD44^low/CD24^high/ERα^high phenotype. Forced expression of the mitotic Aurora kinase A (AURKA), which promotes breast cancer metastases, failed to restore the invasive capacity of NOTCH3-null cells, demonstrating that NOTCH3 expression is required for an invasive phenotype. Likewise, pharmacologic inhibition of NOTCH signaling also impaired TNBC cell seeding and metastatic growth. Significantly, the role of aberrant NOTCH3 expression in promoting tumor self-renewal, invasiveness, and poor outcome was corroborated in unique TNBC cells from a patient-derived brain metastasis and in publicly available claudin-low breast tumor specimens.

Conclusions

These findings demonstrate the key role of NOTCH3 oncogenic signaling in the genesis of breast cancer metastasis and provide a compelling preclinical rationale for the design of novel therapeutic strategies that will selectively target NOTCH3 to halt metastatic seeding and to improve the clinical outcomes of patients with breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1020-0) contains supplementary material, which is available to authorized users.