The genomic landscape of metastasis in treatment-naïve breast cancer models

Resf1 is a compound G4 quadruplex-associated tumor suppressor for triple negative breast cancer

Patients with ER-negative breast cancer have the worst prognosis of all breast cancer subtypes, often experiencing rapid recurrence or progression to metastatic disease shortly after diagnosis. Given that metastasis is the primary cause of mortality in most solid tumors, understanding metastatic biology is crucial for effective intervention. Using a mouse systems genetics approach, we previously identified 12 genes associated with metastatic susceptibility. Here, we extend those studies to identify Resf1, a poorly characterized gene, as a novel metastasis susceptibility gene in ER- breast cancer. Resf1 is a large, unstructured protein with an evolutionarily conserved intron-exon structure, but with poor amino acid conservation. CRISPR or gene trap mouse models crossed to the Polyoma Middle-T antigen genetically engineered mouse model (MMTV-PyMT) demonstrated that reduction of Resf1 resulted in a significant increase in tumor growth, a shortened overall survival time, and increased incidence and number of lung metastases, consistent with patient data. Furthermore, an analysis of matched tail and primary tissues revealed loss of the wildtype copy in tumor tissue, consistent with Resf1 being a tumor suppressor. Mechanistic analysis revealed a potential role of Resf1 in transcriptional control through association with compound G4 quadruplexes in expressed sequences, particularly those associated with ribosomal biogenesis. These results suggest that loss of Resf1 enhances tumor progression in ER- breast cancer through multiple alterations in both transcriptional and translational control.

SMARCD1 is a "Goldilocks" metastasis modifier

Breast cancer is the most frequently diagnosed cancer worldwide, constituting around 15% of all diagnosed cancers in 2023. The predominant cause of breast cancer-related mortality is metastasis to distant essential organs, and a lack of metastasis-targeted therapies perpetuates dismal outcomes for late-stage patients. However, through our use of meiotic genetics to study inherited transcriptional network regulation, we have identified a new class of "Goldilocks" genes that are promising candidates for the development of metastasis-targeted therapeutics. Building upon previous work that implicated the CCR4-NOT RNA deadenylase complex in metastasis, we now demonstrate that the RNA-binding proteins (RNA-BPs) NANOS1, PUM2, and CPSF4 also regulate metastatic potential. Using cell lines, 3D culture, mouse models, and clinical data, we pinpoint Smarcd1 mRNA as a key target of all three RNA-BPs. Strikingly, both high and low expression of Smarcd1 is associated with positive clinical outcomes, while intermediate expression significantly reduces the probability of survival. Applying the theory of "essential genes" from evolution, we identify an additional 50 genes that span several cellular processes and must be maintained within a discrete window of expression for metastasis to occur. In the case of Smarcd1, small perturbations in its expression level significantly reduce metastasis in laboratory mouse models and alter splicing programs relevant to the ER+/HER2-enriched breast cancer subtype. The identification of subtype-specific "Goldilocks" metastasis modifier genes introduces a new class of genes and potential catalogue of novel targets that, when therapeutically "nudged" in either direction, may significantly improve late-stage patient outcomes.

A Mouse-Specific Model to Detect Genes under Selection in Tumors

The mouse is a widely used model organism in cancer research. However, no computational methods exist to identify cancer driver genes in mice due to a lack of labeled training data. To address this knowledge gap, we adapted the GUST (Genes Under Selection in Tumors) model, originally trained on human exomes, to mouse exomes via transfer learning. The resulting tool, called GUST-mouse, can estimate long-term and short-term evolutionary selection in mouse tumors, and distinguish between oncogenes, tumor suppressor genes, and passenger genes using high-throughput sequencing data. We applied GUST-mouse to analyze 65 exomes of mouse primary breast cancer models and 17 exomes of mouse leukemia models. Comparing the predictions between cancer types and between human and mouse tumors revealed common and unique driver genes. The GUST-mouse method is available as an open-source R package on github.

Integrative multi-omic sequencing reveals the MMTV-Myc mouse model mimics human breast cancer heterogeneity

BACKGROUND

Breast cancer is a complex and heterogeneous disease with distinct subtypes and molecular profiles corresponding to different clinical outcomes. Mouse models of breast cancer are widely used, but their relevance in capturing the heterogeneity of human disease is unclear. Previous studies have shown the heterogeneity at the gene expression level for the MMTV-Myc model, but have only speculated on the underlying genetics.

METHODS

Tumors from the microacinar, squamous, and EMT histological subtypes of the MMTV-Myc mouse model of breast cancer underwent whole genome sequencing. The genomic data obtained were then integrated with previously obtained matched sample gene expression data and extended to additional samples of each histological subtype, totaling 42 gene expression samples. High correlation was observed between genetic copy number events and resulting gene expression by both Spearman's rank correlation coefficient and the Kendall rank correlation coefficient. These same genetic events are conserved in humans and are indicative of poor overall survival by Kaplan-Meier analysis. A supervised machine learning algorithm trained on METABRIC gene expression data was used to predict the analogous human breast cancer intrinsic subtype from mouse gene expression data.

RESULTS

Herein, we examine three common histological subtypes of the MMTV-Myc model through whole genome sequencing and have integrated these results with gene expression data. Significantly, key genomic alterations driving cell signaling pathways were well conserved within histological subtypes. Genomic changes included frequent, co-occurring mutations in KIT and RARA in the microacinar histological subtype as well as SCRIB mutations in the EMT subtype. EMT tumors additionally displayed strong KRAS activation signatures downstream of genetic activating events primarily ascribed to KRAS activating mutations, but also FGFR2 amplification. Analogous genetic events in human breast cancer showed stark decreases in overall survival. In further analyzing transcriptional heterogeneity of the MMTV-Myc model, we report a supervised machine learning model that classifies MMTV-Myc histological subtypes and other mouse models as being representative of different human intrinsic breast cancer subtypes.

CONCLUSIONS

We conclude the well-established MMTV-Myc mouse model presents further opportunities for investigation of human breast cancer heterogeneity.

RHAMM regulates MMTV-PyMT-induced lung metastasis by connecting STING-dependent DNA damage sensing to interferon/STAT1 pro-apoptosis signaling

BACKGROUND

RHAMM is a multifunctional protein that is upregulated in breast tumors, and the presence of strongly RHAMM+ve cancer cell subsets associates with elevated risk of peripheral metastasis. Experimentally, RHAMM impacts cell cycle progression and cell migration. However, the RHAMM functions that contribute to breast cancer metastasis are poorly understood.

METHODS

We interrogated the metastatic functions of RHAMM using a loss-of-function approach by crossing the MMTV-PyMT mouse model of breast cancer susceptibility with Rhamm-/- mice. In vitro analyses of known RHAMM functions were performed using primary tumor cell cultures and MMTV-PyMT cell lines. Somatic mutations were identified using a mouse genotyping array. RNA-seq was performed to identify transcriptome changes resulting from Rhamm-loss, and SiRNA and CRISPR/Cas9 gene editing was used to establish cause and effect of survival mechanisms in vitro.

RESULTS

Rhamm-loss does not alter initiation or growth of MMTV-PyMT-induced primary tumors but unexpectedly increases lung metastasis. Increased metastatic propensity with Rhamm-loss is not associated with obvious alterations in proliferation, epithelial plasticity, migration, invasion or genomic stability. SNV analyses identify positive selection of Rhamm-/- primary tumor clones that are enriched in lung metastases. Rhamm-/- tumor clones are characterized by an increased ability to survive with ROS-mediated DNA damage, which associates with blunted expression of interferon pathway and target genes, particularly those implicated in DNA damage-resistance. Mechanistic analyses show that ablating RHAMM expression in breast tumor cells by siRNA knockdown or CRISPR-Cas9 gene editing blunts interferon signaling activation by STING agonists and reduces STING agonist-induced apoptosis. The metastasis-specific effect of RHAMM expression-loss is linked to microenvironmental factors unique to tumor-bearing lung tissue, notably high ROS and TGFB levels. These factors promote STING-induced apoptosis of RHAMM+ve tumor cells to a significantly greater extent than RHAMM-ve comparators. As predicted by these results, colony size of Wildtype lung metastases is inversely related to RHAMM expression.

CONCLUSION

RHAMM expression-loss blunts STING-IFN signaling, which offers growth advantages under specific microenvironmental conditions of lung tissue. These results provide mechanistic insight into factors controlling clonal survival/expansion of metastatic colonies and has translational potential for RHAMM expression as a marker of sensitivity to interferon therapy.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Characterization of Mammary Tumors Arising from MMTV-PyVT Transgenic Mice

Among genetically engineered mouse models of breast cancer, MMTV-PyVT is a mouse strain in which the oncogenic polyoma virus middle T antigen is driven by the mouse mammary tumor virus promoter. The aim of the present study was to perform morphologic and genetic analyses of mammary tumors arising from MMTV-PyVT mice. To this end, mammary tumors were obtained at 6, 9, 12, and 16 weeks of age for histology and whole-mount analyses. We conducted whole-exome sequencing to identify constitutional and tumor-specific mutations, and genetic variants were identified using the GRCm38/mm10 mouse reference genome. Using hematoxylin and eosin analysis and whole-mount carmine alum staining, we demonstrated the progressive proliferation and invasion of mammary tumors. Frameshift insertions/deletions (indels) were noted in the Muc4. Mammary tumors showed small indels and nonsynonymous single-nucleotide variants but no somatic structural alterations or copy number variations. In summary, we validated MMTV-PyVT transgenic mice as a multistage model for mammary carcinoma development and progression. Our characterization may be used as a reference for guidance in future research.

Cancer metastasis chemoprevention prevents circulating tumour cells from germination

The war against cancer traces back to the signature event half-a-century ago when the US National Cancer Act was signed into law. The cancer crusade costs trillions with disappointing returns, teasing the possibility of a new breakthrough. Cure for cancer post-metastases still seems tantalisingly out of reach. Once metastasized, cancer-related death is extremely difficult, if not impossible, to be reversed. Here we present cancer pre-metastasis chemoprevention strategy that can prevent circulating tumour cells (CTCs) from initiating metastases safely and effectively, and is disparate from the traditional cancer chemotherapy and cancer chemoprevention. Deep learning of the biology of CTCs and their disseminating organotropism, complexity of their adhesion to endothelial niche reveals that if the adhesion of CTCs to their metastasis niche (the first and the most important part in cancer metastatic cascade) can be pharmaceutically interrupted, the lethal metastatic cascade could be prevented from getting initiated. We analyse the key inflammatory and adhesive factors contributing to CTC adhesion/germination, provide pharmacological fundamentals for abortifacients to intervene CTC adhesion to the distant metastasis sites. The adhesion/inhibition ratio (AIR) is defined for selecting the best cancer metastasis chemopreventive candidates. The successful development of such new therapeutic modalities for cancer metastasis chemoprevention has great potential to revolutionise the current ineffective post-metastasis treatments.

Elevated phosphorylation of EGFR in NSCLC due to mutations in PTPRH

The role of EGFR in lung cancer is well described with numerous activating mutations that result in phosphorylation and tyrosine kinase inhibitors that target EGFR. While the role of the EGFR kinase in non-small cell lung cancer (NSCLC) is appreciated, control of EGFR signaling pathways through dephosphorylation by phosphatases is not as clear. Through whole genome sequencing we have uncovered conserved V483M Ptprh mutations in PyMT induced tumors. Profiling the downstream events of Ptprh mutant tumors revealed AKT activation, suggesting a key target of PTPRH was EGFR tyrosine 1197. Given the role of EGFR in lung cancer, we explored TCGA data which revealed that a subset of PTPRH mutant tumors shared gene expression profiles with EGFR mutant tumors, but that EGFR mutations and PTPRH mutations were mutually exclusive. Generation of a PTPRH knockout NSCLC cell line resulted in Y1197 phosphorylation of EGFR, and a rescue with expression of wild type PTPRH returned EGFR phosphorylation to parental line values while rescue with catalytically dead PTPRH did not. A dose response curve illustrated that two human NSCLC lines with naturally occurring PTPRH mutations responded to EGFR tyrosine kinase inhibition. Osimertinib treatment of these tumors resulted in a reduction of tumor volume relative to vehicle controls. PTPRH mutation resulted in nuclear pEGFR as seen in immunohistochemistry, suggesting that there may also be a role for EGFR as a transcriptional co-factor. Together these data suggest mutations in PTPRH in NSCLC is inhibitory to PTPRH function, resulting in aberrant EGFR activity and ultimately may result in clinically actionable alterations using existing therapies.

One of the major genetic causes of lung cancer is EGFR activity. Traditionally this is caused by mutations in the EGFR receptor tyrosine kinase resulting in unchecked activity, which ultimately results in lung cancer. A series of tyrosine kinase inhibitors have been developed that treat these EGFR positive lung cancers, with remarkable efficacy. Here we describe work from a mouse model that revealed mutations in PTPRH, a phosphatase that we show dephosphorylates EGFR. We show that mutation or loss of wild type PTPRH results in elevated EGFR activity. Searching for similar mutations in human lung cancer revealed that 5% of all lung cancers had PTPRH mutations. Since activation of EGFR by mutation and loss of PTPRH function would be redundant, we tested and demonstrated that these events only occurred separately. Patient data revealed that a subset of PTPRH mutant lung cancer did have elevated EGFR activity. Testing two tumor lines from patients with naturally occurring PTPRH mutations revealed a sensitivity to EGFR inhibitors. The broad implications of this work are that there are a large number of lung cancer patients with PTPRH mutations that could potentially benefit from a revised treatment based on sequencing. Currently the PTPTRH mutations are not detected and these patients are treated with chemotherapy as a standard of care while they could potentially be more effectively treated with EGFR inhibitors. The ability to use EGFR inhibitors in PTPRH mutant lung cancers is a new area for investigation and is the primary impact of this research.

Stromal p53 Regulates Breast Cancer Development, the Immune Landscape, and Survival in an Oncogene-Specific Manner

Coevolution of tumor cells and adjacent stromal elements is a key feature during tumor progression; however, the precise regulatory mechanisms during this process remain unknown. Here, we show stromal p53 loss enhances oncogenic KrasG12D, but not ErbB2, driven tumorigenesis in murine mammary epithelia. Stroma-specific p53 deletion increases both epithelial and fibroblast proliferation in mammary glands bearing the KrasG12D oncogene in epithelia, while concurrently increasing DNA damage and/or DNA replication stress and decreasing apoptosis in the tumor cells proper. Normal epithelia was not affected by stromal p53 deletion. Tumors with p53-null stroma had a significant decrease in total, cytotoxic, and regulatory T cells; however, there was a significant increase in myeloid-derived suppressor cells, total macrophages, and M2-polarized tumor-associated macrophages, with no impact on angiogenesis or connective tissue deposition. Stroma-specific p53 deletion reprogrammed gene expression in both fibroblasts and adjacent epithelium, with p53 targets and chemokine receptors/chemokine signaling pathways in fibroblasts and DNA replication, DNA damage repair, and apoptosis in epithelia being the most significantly impacted biological processes. A gene cluster in p53-deficient mouse fibroblasts was negatively associated with patient survival when compared with two independent datasets. In summary, stroma-specific p53 loss promotes mammary tumorigenesis in an oncogene-specific manner, influences the tumor immune landscape, and ultimately impacts patient survival.

IMPLICATIONS

Expression of the p53 tumor suppressor in breast cancer tumor stroma regulates tumorigenesis in an oncogene-specific manner, influences the tumor immune landscape, and ultimately impacts patient survival.

Nuclear pore protein NUP210 depletion suppresses metastasis through heterochromatin-mediated disruption of tumor cell mechanical response

Mechanical signals from the extracellular microenvironment have been implicated in tumor and metastatic progression. Here, we identify nucleoporin NUP210 as a metastasis susceptibility gene for human estrogen receptor positive (ER+) breast cancer and a cellular mechanosensor. Nup210 depletion suppresses lung metastasis in mouse models of breast cancer. Mechanistically, NUP210 interacts with LINC complex protein SUN2 which connects the nucleus to the cytoskeleton. In addition, the NUP210/SUN2 complex interacts with chromatin via the short isoform of BRD4 and histone H3.1/H3.2 at the nuclear periphery. In Nup210 knockout cells, mechanosensitive genes accumulate H3K27me3 heterochromatin modification, mediated by the polycomb repressive complex 2 and differentially reposition within the nucleus. Transcriptional repression in Nup210 knockout cells results in defective mechanotransduction and focal adhesion necessary for their metastatic capacity. Our study provides an important role of nuclear pore protein in cellular mechanosensation and metastasis.

The involvement of nuclear pore proteins in cellular mechanosensing and metastasis is unclear. Here the authors identify that nuclear pore protein NUP210 promotes metastasis through the interaction with mechanotransducer LINC complex protein and chromatin to regulate mechanosensitive genes.

Modeling metastasis in mice: a closer look

Unraveling the multifaceted cellular and physiological processes associated with metastasis is best achieved by using in vivo models that recapitulate the requisite tumor cell-intrinsic and -extrinsic mechanisms at the organismal level. We discuss the current status of mouse models of metastasis. We consider how mouse models can refine our understanding of the underlying biological and molecular processes that promote metastasis, and we envisage how the application of new technologies will further enhance investigations of metastasis at single-cell resolution in the context of the whole organism. Our view is that investigations based on state-of-the-art mouse models can propel a holistic understanding of the biology of metastasis, which will ultimately lead to the discovery of new therapeutic opportunities.

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.

Methodological Advancements for Investigating Intra-tumoral Heterogeneity in Breast Cancer at the Bench and Bedside

There is a major need to overcome therapeutic resistance and metastasis that eventually arises in many breast cancer patients. Therapy resistant and metastatic tumors are increasingly recognized to possess intra-tumoral heterogeneity (ITH), a diversity of cells within an individual tumor. First hypothesized in the 1970s, the possibility that this complex ITH may endow tumors with adaptability and evolvability to metastasize and evade therapies is now supported by multiple lines of evidence. Our understanding of ITH has been driven by recent methodological advances including next-generation sequencing, computational modeling, lineage tracing, single-cell technologies, and multiplexed in situ approaches. These have been applied across a range of specimens, including patient tumor biopsies, liquid biopsies, cultured cell lines, and mouse models. In this review, we discuss these approaches and how they have deepened our understanding of the mechanistic origins of ITH amongst tumor cells, including stem cell-like differentiation hierarchies and Darwinian evolution, and the functional role for ITH in breast cancer progression. While ITH presents a challenge for combating tumor evolution, in-depth analyses of ITH in clinical biopsies and laboratory models hold promise to elucidate therapeutic strategies that should ultimately improve outcomes for breast cancer patients.