Transcriptomic dynamics of breast cancer progression in the MMTV-PyMT mouse model

Leveraging preclinical models of metastatic breast cancer

Women that present to the clinic with established breast cancer metastases have limited treatment options. Yet, the majority of preclinical studies are actually not directed at developing treatment regimens for established metastatic disease. In this review we will discuss the current state of preclinical macro-metastatic breast cancer models, including, but not limited to syngeneic GEMM, PDX and xenografts. Challenges within these models which are often overlooked include fluorophore-immunogenic neoantigens, differences in experimental vs spontaneous metastasis and tumor heterogeneity. Furthermore, due to cell plasticity in the tumor immune microenvironment (TIME) of the metastatic landscape, the treatment efficacy of newly approved immune checkpoint blockade (ICB) may differ in metastatic sites as compared to primary localized tumors.

Modeling cancer progression: an integrated workflow extending data-driven kinetic models to bio-mechanical PDE models

Computational modeling of cancer can help unveil dynamics and interactions that are hard to replicate experimentally. Thanks to the advancement in cancer databases and data analysis technologies, these models have become more robust than ever. There are many mathematical models which investigate cancer through different approaches, from sub-cellular to tissue scale, and from treatment to diagnostic points of view. In this study, we lay out a step-by-step methodology for a data-driven mechanistic model of the tumor microenvironment. We discuss data acquisition strategies, data preparation, parameter estimation, and sensitivity analysis techniques. Furthermore, we propose a possible approach to extend mechanistic ordinary differential equation models to PDE models coupled with mechanical growth. The workflow discussed in this article can help understand the complex temporal and spatial interactions between cells and cytokines in the tumor microenvironment and their effect on tumor growth.

Investigating the Role of Heparanase in Breast Cancer Development Utilising the MMTV-PyMT Murine Model of Mammary Carcinoma

Breast cancer is the second most common human malignancy and is a major global health burden. Heparanase (HPSE) has been widely implicated in enhancing the development and progression of solid tumours, including breast cancer. In this study, the well-established spontaneous mammary tumour-developing MMTV-PyMT murine model was utilised to examine the role of HPSE in breast cancer establishment, progression, and metastasis. The use of HPSE-deficient MMTV-PyMT (MMTV-PyMTxHPSE^-/-) mice addressed the lack of genetic ablation models to investigate the role of HPSE in mammary tumours. It was demonstrated that even though HPSE regulated mammary tumour angiogenesis, mammary tumour progression and metastasis were HPSE-independent. Furthermore, there was no evidence of compensatory action by matrix metalloproteinases (MMPs) in response to the lack of HPSE expression in the mammary tumours. These findings suggest that HPSE may not play a significant role in the mammary tumour development of MMTV-PyMT animals. Collectively, these observations may have implications in the clinical setting of breast cancer and therapy using HPSE inhibitors.

Global Down-regulation of Gene Expression Induced by Mouse Mammary Tumor Virus (MMTV) in Normal Mammary Epithelial Cells

Mouse mammary tumor virus (MMTV) is a betaretrovirus that causes breast cancer in mice. The mouse mammary epithelial cells are the most permissive cells for MMTV, expressing the highest levels of virus upon infection and being the ones later transformed by the virus due to repeated rounds of infection/superinfection and integration, leading eventually to mammary tumors. The aim of this study was to identify genes and molecular pathways dysregulated by MMTV expression in mammary epithelial cells. Towards this end, mRNAseq was performed on normal mouse mammary epithelial cells stably expressing MMTV, and expression of host genes was analyzed compared with cells in its absence. The identified differentially expressed genes (DEGs) were grouped on the basis of gene ontology and relevant molecular pathways. Bioinformatics analysis identified 12 hub genes, of which 4 were up-regulated (Angp2, Ccl2, Icam, and Myc) and 8 were down-regulated (Acta2, Cd34, Col1a1, Col1a2, Cxcl12, Eln, Igf1, and Itgam) upon MMTV expression. Further screening of these DEGs showed their involvement in many diseases, especially in breast cancer progression when compared with available data. Gene Set Enrichment Analysis (GSEA) identified 31 molecular pathways dysregulated upon MMTV expression, amongst which the PI3-AKT-mTOR was observed to be the central pathway down-regulated by MMTV. Many of the DEGs and 6 of the 12 hub genes identified in this study showed expression profile similar to that observed in the PyMT mouse model of breast cancer, especially during tumor progression. Interestingly, a global down-regulation of gene expression was observed, where nearly 74% of the DEGs in HC11 cells were repressed by MMTV expression, an observation similar to what was observed in the PyMT mouse model during tumor progression, from hyperplasia to adenoma to early and late carcinomas. Comparison of our results with the Wnt1 mouse model revealed further insights into how MMTV expression could lead to activation of the Wnt1 pathway independent of insertional mutagenesis. Thus, the key pathways, DEGs, and hub genes identified in this study can provide important clues to elucidate the molecular mechanisms involved in MMTV replication, escape from cellular anti-viral response, and potential to cause cell transformation. These data also validate the use of the MMTV-infected HC11 cells as an important model to study early transcriptional changes that could lead to mammary cell transformation.

Breast cancer plasticity is restricted by a LATS1-NCOR1 repressive axis

Breast cancer, the most frequent cancer in women, is generally classified into several distinct histological and molecular subtypes. However, single-cell technologies have revealed remarkable cellular and functional heterogeneity across subtypes and even within individual breast tumors. Much of this heterogeneity is attributable to dynamic alterations in the epigenetic landscape of the cancer cells, which promote phenotypic plasticity. Such plasticity, including transition from luminal to basal-like cell identity, can promote disease aggressiveness. We now report that the tumor suppressor LATS1, whose expression is often downregulated in human breast cancer, helps maintain luminal breast cancer cell identity by reducing the chromatin accessibility of genes that are characteristic of a "basal-like" state, preventing their spurious activation. This is achieved via interaction of LATS1 with the NCOR1 nuclear corepressor and recruitment of HDAC1, driving histone H3K27 deacetylation near NCOR1-repressed "basal-like" genes. Consequently, decreased expression of LATS1 elevates the expression of such genes and facilitates slippage towards a more basal-like phenotypic identity. We propose that by enforcing rigorous silencing of repressed genes, the LATS1-NCOR1 axis maintains luminal cell identity and restricts breast cancer progression.

Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation

We are rapidly approaching a future in which cancer patient digital twins will reach their potential to predict cancer prevention, diagnosis, and treatment in individual patients. This will be realized based on advances in high performance computing, computational modeling, and an expanding repertoire of observational data across multiple scales and modalities. In 2020, the US National Cancer Institute, and the US Department of Energy, through a trans-disciplinary research community at the intersection of advanced computing and cancer research, initiated team science collaborative projects to explore the development and implementation of predictive Cancer Patient Digital Twins. Several diverse pilot projects were launched to provide key insights into important features of this emerging landscape and to determine the requirements for the development and adoption of cancer patient digital twins. Projects included exploring approaches to using a large cohort of digital twins to perform deep phenotyping and plan treatments at the individual level, prototyping self-learning digital twin platforms, using adaptive digital twin approaches to monitor treatment response and resistance, developing methods to integrate and fuse data and observations across multiple scales, and personalizing treatment based on cancer type. Collectively these efforts have yielded increased insights into the opportunities and challenges facing cancer patient digital twin approaches and helped define a path forward. Given the rapidly growing interest in patient digital twins, this manuscript provides a valuable early progress report of several CPDT pilot projects commenced in common, their overall aims, early progress, lessons learned and future directions that will increasingly involve the broader research community.

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells' location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells' diffusion and immune cells' influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes' diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

Interrelated Oncogenic Viruses and Breast Cancer

Breast Cancer is a multifactorial disease and recent evidence that viruses have a greater role in its aetiology and pathophysiology than previously hypothesized, has garnered a lot of attention in the past couple of years. After the role of Mouse Mammary Tumour Virus (MMTV) in the oncogenesis of breast cancer has been proved in mice, search for similar viruses found quite a plausible relation of Human Papilloma Virus (HPV), Epstein–Barr virus (EBV), and Bovine Leukaemia Virus (BLV) with breast cancer. However, despite practical efforts to provide some clarity in this issue, the evidence that viruses cause breast cancer still remains inconclusive. Therefore, this article aims to clarify some ambiguity and elucidate the correlation of breast cancer and those particular viruses which are found to bring about the development of tumorigenesis by a previous infection or by their own oncogenic ability to manipulate the molecular mechanisms and bypass the immune system of the human body. Although many studies have reported, both, the individual and co-existing presence of HPV, EBV, MMTV, and BLV in patient sample tissues, particularly in Western women, and proposed oncogenic mechanisms, majority of the collective survey of literature fails to provide a delineated and strong conclusive evidence that viruses do, in fact, cause breast cancer. Measures to prevent these viral infections may curb breast cancer cases, especially in the West. More studies are needed to provide a definite conclusion.

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model's parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

Targeting the ILK/YAP axis by LFG-500 blocks epithelial-mesenchymal transition and metastasis

Metastasis is the main cause of mortality in patients with cancer. Epithelial-mesenchymal transition (EMT), a crucial process in cancer metastasis, is an established target for antimetastatic drug development. LFG-500, a novel synthetic flavonoid, has been revealed as a potential antitumor agent owing to its various activities, including modulation of EMT in the inflammatory microenvironment. Here, using a transforming growth factor beta (TGF-β)-induced EMT models, we found that LFG-500 inhibited EMT-associated migration and invasion in human breast cancer, MCF-7, and lung adenocarcinoma, A549, cell lines, consistent with the observed downregulation of YAP activity. Further studies demonstrated that LGF-500-induced suppression of YAP activation was mediated by integrin-linked kinase (ILK), suggesting that the ILK/YAP axis might be feasible target for anti-EMT and antimetastatic treatments, which was verified by a correlation analysis with clinical data and tumor specimens. Hence, our data support the use of LGF-500 as an antimetastatic drug in cancer therapy and provide evidence that the ILK/YAP axis is a feasible biomarker of cancer progression and a promising target for repression of EMT and metastasis in cancer therapy.

Transcriptome analysis of heterogeneity in mouse model of metastatic breast cancer

Background

Cancer metastasis is a complex process involving the spread of malignant cells from a primary tumor to distal organs. Understanding this cascade at a mechanistic level could provide critical new insights into the disease and potentially reveal new avenues for treatment. Transcriptome profiling of spontaneous cancer models is an attractive method to examine the dynamic changes accompanying tumor cell spread. However, such studies are complicated by the underlying heterogeneity of the cell types involved. The purpose of this study was to examine the transcriptomes of metastatic breast cancer cells using the well-established MMTV-PyMT mouse model.

Methods

Organ-derived metastatic cell lines were harvested from 10 female MMTV-PyMT mice. Cancer cells were isolated and sorted based on the expression of CD44^low/EpCAM^high or CD44^high/EpCAM^high surface markers. RNA from each cell line was extracted and sequenced using the NextSeq 500 Illumina platform. Tissue-specific genes were compared across the different metastatic and primary tumor samples. Reads were mapped to the mouse genome using STAR, and gene expression was quantified using RSEM. Single-cell RNA-seq (scRNA-seq) was performed on select samples using the ddSeq platform by BioRad and analyzed using Seurat v3.2.3. Monocle2 was used to infer pseudo-time progression.

Results

Comparison of RNA sequencing data across all cell populations produced distinct gene clusters. Differential gene expression patterns related to CD44 expression, organ tropism, and immunomodulatory signatures were observed. scRNA-seq identified expression profiles based on tissue-dependent niches and clonal heterogeneity. These cohorts of data were narrowed down to identify subsets of genes with high expression and known metastatic propensity. Dot plot analyses further revealed clusters expressing cancer stem cell and cancer dormancy markers. Changes in relevant genes were investigated across pseudo-time and tissue origin using Monocle2. These data revealed transcriptomes that may contribute to sub-clonal evolution and treatment evasion during cancer progression.

Conclusions

We performed a comprehensive transcriptome analysis of tumor heterogeneity and organ tropism during breast cancer metastasis. These data add to our understanding of metastatic progression and highlight targets for breast cancer treatment. These markers could also be used to image the impact of tumor heterogeneity on metastases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01468-x.

MYO10 drives genomic instability and inflammation in cancer

Genomic instability is a hallmark of human cancer; yet the underlying mechanisms remain poorly understood. Here, we report that the cytoplasmic unconventional Myosin X (MYO10) regulates genome stability, through which it mediates inflammation in cancer. MYO10 is an unstable protein that undergoes ubiquitin-conjugating enzyme H7 (UbcH7)/β-transducin repeat containing protein 1 (β-TrCP1)–dependent degradation. MYO10 is upregulated in both human and mouse tumors and its expression level predisposes tumor progression and response to immune therapy. Overexpressing MYO10 increased genomic instability, elevated the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING)–dependent inflammatory response, and accelerated tumor growth in mice. Conversely, depletion of MYO10 ameliorated genomic instability and reduced the inflammation signaling. Further, inhibiting inflammation or disrupting Myo10 significantly suppressed the growth of both human and mouse breast tumors in mice. Our data suggest that MYO10 promotes tumor progression through inducing genomic instability, which, in turn, creates an immunogenic environment for immune checkpoint blockades.

miR-21 Plays a Dual Role in Tumor Formation and Cytotoxic Response in Breast Tumors

Simple Summary

miR-21 is an oncogenic microRNA that has been associated with breast tumor growth and metastasis in vitro and is also noted to be upregulated by cytotoxic stressors in model systems and in breast cancer patients who have undergone radiation. In the present study, our findings demonstrate the novel role of miR-21 in vivo for breast cancer initiation and metastases, and in sensitizing tumor cells to cytotoxic therapy by upregulating the FAS/FASL signaling pathway.

Abstract

Breast cancer (BrCa) relies on specific microRNAs to drive disease progression. Oncogenic miR-21 is upregulated in many cancers, including BrCa, and is associated with poor survival and treatment resistance. We sought to determine the role of miR-21 in BrCa tumor initiation, progression and treatment response. In a triple-negative BrCa model, radiation exposure increased miR-21 in both primary tumor and metastases. In vitro, miR-21 knockdown decreased survival in all BrCa subtypes in the presence of radiation. The role of miR-21 in BrCa initiation was evaluated by implanting wild-type miR-21 BrCa cells into genetically engineered mouse models where miR-21 was intact, heterozygous or globally ablated. Tumors were unable to grow in the mammary fat pads of miR-21^−/− mice, and grew in ~50% of miR-21^+/− and 100% in miR-21^+/+ mice. The contribution of miR-21 to progression and metastases was tested by crossing miR-21^−/− mice with mice that spontaneously develop BrCa. The global ablation of miR-21 significantly decreased the tumorigenesis and metastases of BrCa, while sensitizing tumors to radio- and chemotherapeutic agents via Fas/FasL-dependent apoptosis. Therefore, targeting miR-21 alone or in combination with various radio or cytotoxic therapies may represent novel and efficacious therapeutic modalities for the future treatment of BrCa patients.

Insights from transgenic mouse models of PyMT-induced breast cancer: recapitulating human breast cancer progression in vivo

Breast cancer is associated with the second highest cancer-associated deaths worldwide. Therefore, understanding the key events that determine breast cancer progression, modulation of the tumor-microenvironment and metastasis, which is the main cause of cancer-associated death, are of great importance. The mammary specific polyomavirus middle T antigen overexpression mouse model (MMTV-PyMT), first published in 1992, is the most commonly used genetically engineered mouse model (GEMM) for cancer research. Mammary lesions arising in MMTV-PyMT mice follow similar molecular and histological progression as human breast tumors, making it an invaluable tool for cancer researchers and instrumental in understanding tumor biology. In this review, we will highlight key studies that demonstrate the utility of PyMT derived GEMMs in understanding the molecular basis of breast cancer progression, metastasis and highlight its use as a pre-clinical tool for therapeutic discovery.

Loss of Fbxw7 triggers mammary tumorigenesis associated with E2F/c-Myc activation and Trp53 mutation

Fbw7 is a tumor suppressor that regulates the degradation of oncogenic substrates such as c-Jun, c-Myc, Notch1 intracellular domain (ICD), and cyclin E by functioning as the substrate recognition protein in the Skp1-Cullin-F-box (SCF) ubiquitin ligase complex. Consequently, low expression or loss of FBXW7 in breast cancer has been hypothesized to result in the accumulation of oncogenic transcription factors that are master regulators of proliferation, apoptosis, and ultimately transformation. Despite this, the direct effect of Fbw7 loss on mammary gland morphology and tumorigenesis has not been examined. Here, we demonstrate that conditional deletion of Fbxw7 in murine mammary tissue initiates breast tumor development and also results in lactation and involution defects. Further, while Fbxw7 loss results in the overexpression of Notch1-ICD, c-Jun, cyclin E, and c-Myc, the downstream transcription factor pathways associated with c-Myc and cyclin E are the most dysregulated, including at the single-cell level. These pathways are dysregulated early after Fbxw7 loss, and their sustained loss results in tumorigenesis and reinforced c-Myc and cyclin E-E2F pathway disruption. We also find that loss of Fbxw7 is linked to the acquisition of Trp53 mutations, similar to the mutational spectrum observed in patients. Our results demonstrate that the loss of Fbxw7 promotes the acquisition of Trp53 mutations and that the two cooperate in breast tumor development. Targeting c-Myc, E2F, or p53 may therefore be a beneficial treatment strategy for FBXW7-altered breast cancer patients.

Multi-color clonal tracking reveals intra-stage proliferative heterogeneity during mammary tumor progression

Despite major progress in breast cancer research, the functional contribution of distinct cancer cell clones to malignant tumor progression and metastasis remains largely elusive. We have assessed clonal heterogeneity within individual primary tumors and metastases and also during the distinct stages of malignant tumor progression using clonal tracking of cancer cells in the MMTV-PyMT mouse model of metastatic breast cancer. Comparative gene expression analysis of clonal subpopulations reveals a substantial level of heterogeneity across and also within the various stages of breast carcinogenesis. The intra-stage heterogeneity is primarily manifested by differences in cell proliferation, also found within invasive carcinomas of luminal A-, luminal B-, and HER2-enriched human breast cancer. Surprisingly, in the mouse model of clonal tracing of cancer cells, chemotherapy mainly targets the slow-proliferative clonal populations and fails to efficiently repress the fast-proliferative populations. These insights may have considerable impact on therapy selection and response in breast cancer patients.

TILRR (FREM1 isoform 2) is a prognostic biomarker correlated with immune infiltration in breast cancer

In atherosclerosis, upregulated TILRR (FREM1 isoform 2) expression increases immune cell infiltration. We hypothesized that TILRR expression is also correlated with cancer progression. By analyzing data from Oncomine and the Tumor Immune Estimation Resource, we found that TILRR mRNA expression was significantly lower in breast cancer tissue than adjacent normal tissue. Kaplan-Meier survival analysis and immunohistochemical staining revealed shortened overall survival and disease-free survival in patients with low TILRR expression. TILRR transcript expression was positively correlated with immune score, immune cell biomarkers and the expression of CXCL10 and CXCL11. TILRR expression was also positively correlated with CD8+ and CD4+ T-cell infiltration. These correlations were verified using the ESTIMATE algorithm, gene set enrichment analysis and Q-PCR. We concluded that impaired TILRR expression is correlated with breast cancer prognosis and immune cell infiltration.

Metastasis-Specific Gene Expression in Autochthonous and Allograft Mouse Mammary Tumor Models: Stratification and Identification of Targetable Signatures

Breast cancer metastasis is a leading cause of cancer-related death of women in the United States. A hurdle in advancing metastasis-targeted intervention is the phenotypic heterogeneity between primary and secondary lesions. To identify metastasis-specific gene expression profiles we performed RNA-sequencing of breast cancer mouse models; analyzing metastases from models of various drivers and routes. We contrasted the models and identified common, targetable signatures. Allograft models exhibited more mesenchymal-like gene expression than genetically engineered mouse models (GEMM), and primary culturing of GEMM-derived metastatic tissue induced mesenchymal-like gene expression. In addition, metastasis-specific transcriptomes differed between tail vein and orthotopic injection of the same cell line. Gene expression common to models of spontaneous metastasis included sildenafil response and nicotine degradation pathways. Strikingly, in vivo sildenafil treatment significantly reduced metastasis by 54%, while nicotine significantly increased metastasis by 46%. These data suggest that (i) actionable metastasis-specific pathways can be readily identified, (ii) already available drugs may have great potential to alleviate metastatic incidence, and (iii) metastasis may be influenced greatly by lifestyle choices such as the choice to consume nicotine products. In summary, while mouse models of breast cancer metastasis vary in ways that must not be ignored, there are shared features that can be identified and potentially targeted therapeutically. IMPLICATIONS: The data we present here exposes critical variances between preclinical models of metastatic breast cancer and identifies targetable pathways integral to metastatic spread. VISUAL OVERVIEW: http://mcr.aacrjournals.org/content/molcanres/18/9/1278/F1.large.jpg.

QuaDMutNetEx: a method for detecting cancer driver genes with low mutation frequency

BACKGROUND

Cancer is caused by genetic mutations, but not all somatic mutations in human DNA drive the emergence or growth of cancers. While many frequently-mutated cancer driver genes have already been identified and are being utilized for diagnostic, prognostic, or therapeutic purposes, identifying driver genes that harbor mutations occurring with low frequency in human cancers is an ongoing endeavor. Typically, mutations that do not confer growth advantage to tumors - passenger mutations - dominate the mutation landscape of tumor cell genome, making identification of low-frequency driver mutations a challenge. The leading approach for discovering new putative driver genes involves analyzing patterns of mutations in large cohorts of patients and using statistical methods to discriminate driver from passenger mutations.

RESULTS

We propose a novel cancer driver gene detection method, QuaDMutNetEx. QuaDMutNetEx discovers cancer drivers with low mutation frequency by giving preference to genes encoding proteins that are connected in human protein-protein interaction networks, and that at the same time show low deviation from the mutual exclusivity pattern that characterizes driver mutations occurring in the same pathway or functional gene group across a cohort of cancer samples.

CONCLUSIONS

Evaluation of QuaDMutNetEx on four different tumor sample datasets show that the proposed method finds biologically-connected sets of low-frequency driver genes, including many genes that are not found if the network connectivity information is not considered. Improved quality and interpretability of the discovered putative driver gene sets compared to existing methods shows that QuaDMutNetEx is a valuable new tool for detecting driver genes. QuaDMutNetEx is available for download from https://github.com/bokhariy/QuaDMutNetExunder the GNU GPLv3 license.

Integrative Analyses of Multilevel Omics Reveal Preneoplastic Breast to Possess a Molecular Landscape That is Globally Shared with Invasive Basal-Like Breast Cancer (Running Title: Molecular Landscape of Basal-Like Breast Cancer Progression)

To characterize molecular changes accompanying the stepwise progression to breast cancer and to identify functional target pathways, we performed miRNA and RNA sequencing using MCF10A cell lines based model system that replicates the multi-step progression involving normal, preneoplastic, ductal carcinoma in situ, and invasive carcinoma cells, where the carcinoma most resemble the basal-like subgroup of human breast cancers. These analyses suggest that 70% of miRNA alterations occurred during the initial progression from normal to a preneoplastic stage. Most of these early changes reflected a global upregulation of miRNAs. This was consistent with a global increase in the miRNA-processing enzyme DICER, which was upregulated as a direct result of loss of miRNA let-7b-5p. Several oncogenic and tumor suppressor pathways were also found to change early, prior to histologic stigmata of cancer. Our finding that most genomic changes in the progression to basal-like breast cancer occurred in the earliest stages of histologic progression has implications for breast cancer prevention and selection of appropriate control tissues in molecular studies. Furthermore, in support of a functional significance of let-7b-5p loss, we found its low levels to predict poor disease-free survival and overall survival in breast cancer patients.

Type I Interferon Regulates a Coordinated Gene Network to Enhance Cytotoxic T Cell-Mediated Tumor Killing

Type I interferons (IFN), which activate many IFN-stimulated genes (ISG), are known to regulate tumorigenesis. However, little is known regarding how various ISGs coordinate with one another in developing antitumor effects. Here, we report that the ISG UBA7 is a tumor suppressor in breast cancer. UBA7 encodes an enzyme that catalyzes the covalent conjugation of the ubiquitin-like protein product of another ISG (ISG15) to cellular proteins in a process known as "ISGylation." ISGylation of other ISGs, including STAT1 and STAT2, synergistically facilitates production of chemokine-receptor ligands to attract cytotoxic T cells. These gene-activation events are further linked to clustering and nuclear relocalization of STAT1/2 within IFN-induced promyelocytic leukemia (PML) bodies. Importantly, this coordinated ISG-ISGylation network plays a central role in suppressing murine breast cancer growth and metastasis, which parallels improved survival in patients with breast cancer. These findings reveal a cooperative IFN-inducible gene network in orchestrating a tumor-suppressive microenvironment. SIGNIFICANCE: We report a highly cooperative ISG network, in which UBA7-mediated ISGylation facilitates clustering of transcription factors and activates an antitumor gene-expression program. These findings provide mechanistic insights into immune evasion in breast cancer associated with UBA7 loss, emphasizing the importance of a functional ISG-ISGylation network in tumor suppression.This article is highlighted in the In This Issue feature, p. 327.

Splice switching an oncogenic ratio of SmgGDS isoforms as a strategy to diminish malignancy

The chaperone protein SmgGDS promotes cell-cycle progression and tumorigenesis in human breast and nonsmall cell lung cancer. Splice variants of SmgGDS, named SmgGDS-607 and SmgGDS-558, facilitate the activation of oncogenic members of the Ras and Rho families of small GTPases through membrane trafficking via regulation of the prenylation pathway. SmgGDS-607 interacts with newly synthesized preprenylated small GTPases, while SmgGDS-558 interacts with prenylated small GTPases. We determined that cancer cells have a high ratio of SmgGDS-607:SmgGDS-558 (607:558 ratio), and this elevated ratio is associated with reduced survival of breast cancer patients. These discoveries suggest that targeting SmgGDS splicing to lower the 607:558 ratio may be an effective strategy to inhibit the malignant phenotype generated by small GTPases. Here we report the development of a splice-switching oligonucleotide, named SSO Ex5, that lowers the 607:558 ratio by altering exon 5 inclusion in SmgGDS pre-mRNA (messenger RNA). Our results indicate that SSO Ex5 suppresses the prenylation of multiple small GTPases in the Ras, Rho, and Rab families and inhibits ERK activity, resulting in endoplasmic reticulum (ER) stress, the unfolded protein response, and ultimately apoptotic cell death in breast and lung cancer cell lines. Furthermore, intraperitoneal (i.p.) delivery of SSO Ex5 in MMTV-PyMT mice redirects SmgGDS splicing in the mammary gland and slows tumorigenesis in this aggressive model of breast cancer. Taken together, our results suggest that the high 607:558 ratio is required for optimal small GTPase prenylation, and validate this innovative approach of targeting SmgGDS splicing to diminish malignancy in breast and lung cancer.

LATS1 and LATS2 suppress breast cancer progression by maintaining cell identity and metabolic state

In luminal B tumors LATS2 depletion results in metabolic rewiring whereas LATS1 depletion promotes the expression of basal-like features.

Deregulated activity of LArge Tumor Suppressor (LATS) tumor suppressors has broad implications on cellular and tissue homeostasis. We examined the consequences of down-regulation of either LATS1 or LATS2 in breast cancer. Consistent with their proposed tumor suppressive roles, expression of both paralogs was significantly down-regulated in human breast cancer, and loss of either paralog accelerated mammary tumorigenesis in mice. However, each paralog had a distinct impact on breast cancer. Thus, LATS2 depletion in luminal B tumors resulted in metabolic rewiring, with increased glycolysis and reduced peroxisome proliferator-activated receptor γ (PPARγ) signaling. Furthermore, pharmacological activation of PPARγ elicited LATS2-dependent death in luminal B-derived cells. In contrast, LATS1 depletion augmented cancer cell plasticity, skewing luminal B tumors towards increased expression of basal-like features, in association with increased resistance to hormone therapy. Hence, these two closely related paralogs play distinct roles in protection against breast cancer; tumors with reduced expression of either LATS1 or LATS2 may rewire signaling networks differently and thus respond differently to anticancer treatments.

Gene expression profile and cancer-associated pathways linked to progesterone receptor isoform a (PRA) predominance in transgenic mouse mammary glands

Background

Progesterone receptor (PR) is expressed from a single gene as two isoforms, PRA and PRB. In normal breast human tissue, PRA and PRB are expressed in equimolar ratios, but isoform ratio is altered during malignant progression, usually leading to high PRA:PRB ratios. We took advantage of a transgenic mouse model where PRA isoform is predominant (PRA transgenics) and identified the key transcriptional events and associated pathways underlying the preneoplastic phenotype in mammary glands of PRA transgenics as compared with normal wild-type littermates.

Methods

The transcriptomic profiles of PRA transgenics and wild-type mammary glands were generated using microarray technology. We identified differentially expressed genes and analyzed clustering, gene ontology (GO), gene set enrichment analysis (GSEA), and pathway profiles. We also performed comparisons with publicly available gene expression data sets of human breast cancer.

Results

We identified a large number of differentially expressed genes which were mainly associated with metabolic pathways for the PRA transgenics phenotype while inflammation- related pathways were negatively correlated. Further, we determined a significant overlap of the pathways characterizing PRA transgenics and those in breast cancer subtypes Luminal A and Luminal B and identified novel putative biomarkers, such as PDHB and LAMB3.

Conclusion

The transcriptional targets identified in this study should facilitate the formulation or refinement of useful molecular descriptors for diagnosis, prognosis, and therapy of breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4550-z) contains supplementary material, which is available to authorized users.

Global expression profiling and pathway analysis of mouse mammary tumor reveals strain and stage specific dysregulated pathways in breast cancer progression

It is believed that the alteration of tissue microenvironment would affect cancer initiation and progression. However, little is known in terms of the underlying molecular mechanisms that would affect the initiation and progression of breast cancer. In the present study, we use two murine mammary tumor models with different speeds of tumor initiation and progression for whole genome expression profiling to reveal the involved genes and signaling pathways. The pathways regulating PI3K-Akt signaling and Ras signaling were activated in Fvb mice and promoted tumor progression. Contrastingly, the pathways regulating apoptosis and cellular senescence were activated in Fvb.B6 mice and suppressed tumor progression. We identified distinct patterns of oncogenic pathways activation at different stages of breast cancer, and uncovered five oncogenic pathways that were activated in both human and mouse breast cancers. The genes and pathways discovered in our study would be useful information for other researchers and drug development.

Transcriptome profiling of the interconnection of pathways involved in malignant transformation and response to hypoxia

In tumor tissues, hypoxia is a commonly observed feature resulting from rapidly proliferating cancer cells outgrowing their surrounding vasculature network. Transformed cancer cells are known to exhibit phenotypic alterations, enabling continuous proliferation despite a limited oxygen supply. The four-step isogenic BJ cell model enables studies of defined steps of tumorigenesis: the normal, immortalized, transformed, and metastasizing stages. By transcriptome profiling under atmospheric and moderate hypoxic (3% O₂) conditions, we observed that despite being highly similar, the four cell lines of the BJ model responded strikingly different to hypoxia. Besides corroborating many of the known responses to hypoxia, we demonstrate that the transcriptome adaptation to moderate hypoxia resembles the process of malignant transformation. The transformed cells displayed a distinct capability of metabolic switching, reflected in reversed gene expression patterns for several genes involved in oxidative phosphorylation and glycolytic pathways. By profiling the stage-specific responses to hypoxia, we identified ASS1 as a potential prognostic marker in hypoxic tumors. This study demonstrates the usefulness of the BJ cell model for highlighting the interconnection of pathways involved in malignant transformation and hypoxic response.

Epigenetic alterations to Polycomb targets precede malignant transition in a mouse model of breast cancer

Malignant breast cancer remains a major health threat to women of all ages worldwide and epigenetic variations on DNA methylation have been widely reported in cancers of different types. We profiled DNA methylation with ERRBS (Enhanced Reduced Representation Bisulfite Sequencing) across four main stages of tumor progression in the MMTV-PyMT mouse model (hyperplasia, adenoma/mammary intraepithelial neoplasia, early carcinoma and late carcinoma), during which malignant transition occurs. We identified a large number of differentially methylated cytosines (DMCs) in tumors relative to age-matched normal mammary glands from FVB mice. Despite similarities, the methylation differences of the premalignant stages were distinct from the malignant ones. Many differentially methylated loci were preserved from the first to the last stage throughout tumor progression. Genes affected by methylation gains were enriched in Polycomb repressive complex 2 (PRC2) targets, which may present biomarkers for early diagnosis and targets for treatment.

Subunits of human condensins are potential therapeutic targets for cancers

The main role of condensins is to regulate chromosome condensation and segregation during cell cycles. Recently, it has been suggested in the literatures that subunits of condensin I and condensin II are involved in some human cancers. This paper will first briefly discuss discoveries of human condensins, their components and structures, and their multiple cellular functions. This will be followed by reviews of most recent studies on subunits of human condensins and their dysregulations or mutations in human cancers. It can be concluded that many of these subunits have potentials to be novel targets for cancer therapies. However, hCAP-D2, a subunit of human condensin I, has not been directly documented to be associated with any human cancers to date. This review hypothesizes that hCAP-D2 can also be a potential therapeutic target for human cancers, and therefore that all subunits of human condensins are potential therapeutic targets for human cancers.

Angiopoietin-1 deficiency increases tumor metastasis in mice

Background

Angipoietin-1 activation of the tyrosine kinase receptor Tek expressed mainly on endothelial cells leads to survival and stabilization of endothelial cells. Studies have shown that Angiopoietin-1 counteracts permeability induced by a number of stimuli. Here, we test the hypothesis that loss of Angiopoietin-1/Tek signaling in the vasculature would increase metastasis.

Methods

Angiopoietin-1 was deleted in mice just before birth using floxed Angiopoietin-1 and Tek mice crossed to doxycycline-inducible bitransgenic ROSA-rtTA/tetO-Cre mice. By crossing Angiopoietin-1 knockout mice to the MMTV-PyMT autochthonous mouse breast cancer model, we investigated primary tumor growth and metastasis to the lung. Furthermore, we utilized B16F10 melanoma cells subcutaneous and experimental lung metastasis models in Angiopoietin-1 and Tek knockout mice.

Results

We found that primary tumor growth in MMTV-PyMT mice was unaffected, while metastasis to the lung was significantly increased in Angiopoietin-1 knockout MMTV-PyMT mice. In addition, angiopoietin-1 deficient mice exhibited a significant increase in lung metastasis of B16F10 melanoma cells, compared to wild type mice 3 weeks after injection. Additional experiments showed that this was likely an early event due to increased attachment or extravasation of tumor cells, since seeding of tumor cells was significantly increased 4 and 24 h post tail vein injection. Finally, using inducible Tek knockout mice, we showed a significant increase in tumor cell seeding to the lung, suggesting that Angiopoietin-1/Tek signaling is important for vascular integrity to limit metastasis.

Conclusions

This study show that loss of the Angiopoietin-1/Tek vascular growth factor system leads to increased metastasis without affecting primary tumor growth.