Prognosis In Human Breast Cancer Research Articles

Abstract A056: Lymph and liver metastasis in E2F5 conditional knockout mouse model

Abstract Alterations to normal development in mammary gland biology can result in tumor formation. Mammary development and functional processes are controlled by various transcription factors, including the E2Fs. Commonly known as cell cycle regulators, the E2Fs While the activator E2Fs are well studied, the function of the repressor E2Fs in mammary biology is not well known. This is due in part to the early lethality observed in the knockouts of E2F5. To predict a role for E2F5 in mammary developmental biology we queried scRNAseq data and generated a predictive gene signature. This demonstrated that there were functional stage specific expression patterns for E2F5, including virgin development and involution after lacation. Moreover, when we used the predictive signature for activity, we noted that low levels of E2F5 activity corresponded to a poor prognosis in human breast cancer. Based on these preliminary data we hypothesized that E2F5 played an essential role in mammary development and that loss could contribute to tumor biology. To test the premise that E2F5 had a role in mammary development, we generated a mammary epithelial specific knockout of E2F5. At 4 weeks of age, the outgrowth of the epithelium into the fat bad of the mammary gland of these mice significantly lagged behind the littermate controls. This demonstrated a clear role for E2F5 in development of the mammary gland. We also computationally predicted a role in involution and this was also confirmed through in vivo experiments. We noted accelerated involution with the loss of E2F5 following removal of pups. The second major hypothesis that we tested was that E2F5 had a role in tumor biology, and we planned to test this by interbreeding the E2F5 conditional knockout mice to various other strains. As we aged the E2F5 conditional knockout mice, we were surprised to note that mammary tumors formed after a long latency with the loss of E2F5 alone. These tumors were highly heterogeneous at both a histological and gene expression level, with samples clustering with each of the major human PAM50 subtypes of breast cancer. These tumors were also highly metastatic with lesions developing in the lungs, as many mouse models do. However, unlike most mouse models of breast cancer the E2F5 conditional knockout tumors also metastasized to the liver and lymph nodes. Given the extended latency of the model system, we transplanted the E2F5 conditional knockout tumors into syngeneic recipient mice. We repeatedly observed lymphatic metastases or liver metastases, dependent on the primary tumor. To enrich these tissue trophisms, we repeatedly implanted lymph or liver metastases into the mammary fat pad, resulting in significant enrichment. Preliminary RNAseq and Cut and Run have been completed to examine E2F5 specific gene expression alterations that lead to trophism and metastasis enrichment, with targets that are being currently validated. Since most genetically engineered mouse models have not been characterized to have lymph or liver metastasis, this work represents an important new model. Citation Format: Briana To, Jesus Garcia-Lerena, John Vusich, Carson Broeker, Jonathan Rennhack, Daniel Hollern, Eran Andrechek. Lymph and liver metastasis in E2F5 conditional knockout mouse model [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A056.

Kv 11.1 Expression Is Associated With Malignancy of Canine Mammary Gland Tumors.

The expression level of the voltage-dependent potassium channel Kv 11.1 was shown to be associated with the clinicopathological features, aggressiveness, and prognosis of human breast cancer. Canine mammary gland tumor (cMGT) is the most common tumor type in intact female dogs; however, the significance of Kv 11.1 in cMGT is unknown. The aim of this study was to identify Kv 11.1 expression in 57 benign and malignant cMGT tissues from dogs and to investigate the correlation of Kv 11.1 expression with the clinicopathological parameters and prognosis of cMGT. A total of 57 samples were collected from cMGTs surgically resected at the Veterinary Medical Teaching Hospital, Seoul National University and subjected to immunohistochemistry assay using rabbit anti-Kv 11.1 polyclonal antibody. Immunohistochemical staining results were evaluated as the sum of intensity and percentage scores. The correlation between immunohistochemistry scores and clinicopathological parameters was investigated. Immunohistochemical analysis revealed that Kv 11.1 immunoreactivity was higher in benign cMGTs than in malignant cMGTs. Kv 11.1 expression was significantly associated with tumor malignancy (p<0.001), tumor size (p<0.001), histological grade (p<0.05), and age at the time of mastectomy (p<0.05). This study presents the first evidence of Kv 11.1 expression in cMGTs and indicates an inverse correlation between Kv 11.1 expression and tumor malignancy. Kv 11.1 expression can be used as a prognostic biomarker and a tool for the management of cMGTs.

Unravelling 2022: The 15th Volume of Epigenomics

Unravelling 2022: The 15th Volume of <i>Epigenomics</i>

GPI: An indicator for immune infiltrates and prognosis of human breast cancer from a comprehensive analysis.

Glucose-6-phosphate isomerase (GPI) plays an important part in gluconeogenesis and glycolysis through the interconversion of d-glucose-6-phosphate and d-fructose-6-phosphate, and its clinical significance still remains unclear in breast cancer (BRCA). We analyzed the expressions of GPI in BRCA patients to determine prognostic values. Our results showed that the expression levels of GPI were upregulated in BRCA patients, and a high GPI expression is correlated with poor overall survival (OS) in BRCA. At the same time, a high GPI expression is correlated with poor clinicopathological characteristics, such as stage III, over 60 years old, N3, HER2 negative, and estrogen receptor (ER) positive. Further analysis of the influence of GPI on the prognosis of BRCA suggested that 50 genes and 10 proteins were positively correlated with GPI, and these genes and proteins were mainly involved in cell cycle signaling pathways. In addition, in this study, we observed that GPI was closely related to N 6-methyladenosine (m6A) RNA methylation modification and immune cell infiltration and ferroptosis-related gene expression in BRCA, and there was a difference in m6A RNA methylation alterations, immune cell infiltration, and ferroptosis-related gene expression between the high GPI expression group and the low GPI expression group. Finally, we found that GPI in BRCA had 2.6% gene alterations, and BRCA patients with gene alteration of GPI had a poor prognosis in disease-free survival (DFS). Altogether, our work strongly suggested that GPI may serve as a new prognostic biomarker for BRCA patients.

Association of Pathway Mutations With Survival in Taiwanese Breast Cancers.

Breast cancer is the most common invasive cancer in women worldwide. Next-generation sequencing (NGS) provides a high-resolution profile of cancer genome. Our study ultimately gives the insight for genetic screening to identify the minority of patients with breast cancer with a poor prognosis, who might benefit from the most intensive possible treatment. The detection of mutations can polish the traditional method to detect high-risk patients who experience poor prognosis, recurrence and death early. In total, 147 breast cancer tumors were sequenced with targeted sequencing using a RainDance Cancer Hotspot Panel. The average age of all 147 breast cancer patients in the study was 51.7 years, with a range of 21–77 years. The average sequencing depth was 5,222x (range 2,900x-8,633x), and the coverage was approximately 100%. A total of 235 variants in 43 genes were detected in 147 patients by high-depth Illumina sequencing. A total of 219 single nucleotide variations were found in 42 genes from 147 patients, and 16 indel mutations were found in 13 genes from 84 patients. After filtering with the 1000 Genomes database and for synonymous SNPs, we focused on 54 somatic functional point mutations. The functional point mutations contained 54 missense mutations in 22 genes. Additionally, mutation of genes within the RET, PTEN, CDH1, MAP2K4, NF1, ERBB2, RUNX1, PIK3CA, FGFR3, KIT, KDR, APC, SMO, NOTCH1, and FBXW7 in breast cancer patients were with poor prognosis. Moreover, TP53 and APC mutations were enriched in triple-negative breast cancer. APC mutations were associated with a poor prognosis in human breast cancer (log-rank P<0.001). Our study identified tumor mutation hotspot profiles in Taiwanese breast cancer patients, revealing new targetable gene mutations in Asian breast cancer patients.

Polyamine synthesis enzyme AMD1 is closely related to the tumorigenesis and prognosis of human breast cancer

Adenosylmethionine decarboxylase 1 (AMD1) has been implicated in carcinogenesis and tumor progression. However, the potential biomechanism and biological implications of AMD1 in breast cancer (BC) remain unclear. The purpose of this study was to investigate the effect of abnormal expression of AMD1 in BC. The expression of AMD1 in different human BC cell lines was studied by using western blotting and qRT–PCR. In vitro cell proliferation, clone formation, cell cycle and apoptosis assays were performed to explore the effect of AMD1 on cellular proliferation. Xenograft mouse models were established to elucidate the role of AMD1 in BC growth. The expression profiles of AMD1 in 28 pairs of BC tissues and adjacent noncancerous tissues (ANTs) were investigated by using western blotting and immunohistochemistry. The clinical implication and prognostic evaluation of AMD1 in BC were examined by excavating the online database. We found that the expression levels of AMD1 in BC cell lines were significantly higher than those in the normal human breast epithelial cell line MCF-10A. In addition, AMD1 potentiated proliferation, induced cell cycle progression and inhibited apoptosis in BC cells. Subcutaneous tumor xenografts also supported the promotive role of AMD1 in BC growth. We discovered that the level of AMD1 in BC tissues was significantly higher than that in ANTs. Using the online database, increased AMD1 was found to be associated with clinical indicators and predicted a poor prognosis in patients with BC. Our findings indicate that AMD1 elicits potent oncogenic effects on the malignant progression of BC. AMD1 might serve as a promising diagnostic biomarker and therapeutic target for patients with BC.

A comprehensive bioinformatic analysis of RanBP9 expression and its relation to prognosis in human breast cancer.

Aim: To explore the role of RanBP9 in breast cancer. Materials & methods: Oncomine, TIMER, GEPIA, UALCAN, c-BioPortal databases and tissue microarray analysiswere used in this study. Results: The expression level of RanBP9 is elevated in breast cancer tissues, which is associated with poor prognosis in breast cancer patients. RanBP9 exhibits genetic alterations and a decreased methylation level in cancer tissues. RanBP9 mayalso regulate cell cycle progression and is linked to tumor purity and the infiltrating levels of immune cells. Conclusions:RanBP9 may correlate with prognosis and immune infiltration in breast cancer, laying the foundation for future studies on the potential role of RanBP9 in breast cancer.

SHP-1 acts as a tumor suppressor by interacting with EGFR and predicts the prognosis of human breast cancer.

Objective:The aims of this study were to examine the prognostic value of SHP-1 in breast cancer, its roles in the regulation of breast cancer cell growth and metastasis, and the underlying mechanisms.Methods:Tumor specimens from 160 patients with breast cancer and 160 noncancerous tissues were used to examine the expression of SHP-1 and to analyze its association with overall survival through Kaplan–Meier and multivariate Cox regression analyses. RNA sequencing data and the expression and clinical importance of SHP-1 in breast cancer were evaluated with data from The Cancer Genome Atlas. In vitro and in vivo assays were performed to elucidate the effects of SHP-1 on breast cancer cell proliferation and invasion. Confocal immunofluorescence and GST pulldown assays were used to demonstrate the interaction between SHP-1 and epidermal growth factor receptor, as well as its downstream pathways. Immunohistochemistry and The Cancer Genome Atlas database were used to investigate the clinical association between SHP-1 and EGFR in human breast cancer.Results:SHP-1 expression was associated with better survival in patients with breast cancer, whereas SHP-1 expression was negatively correlated with EGFR in human breast cancer. Ectopic SHP-1 expression significantly suppressed breast cancer cell proliferation, migration, and invasion. SHP-1 knockdown induced a more invasive phenotype and accelerated cell growth. Mechanistically, EGFR, a protein directly interacting with SHP-1, mediates the SHP-1-induced inactivation of Ras/Erk/GSK3β signaling and its downstream effectors.Conclusions:SHP-1 is an important prognostic biomarker in patients with breast cancer, and the SHP-1-EGFR axis is a promising target for treatment.

Abstract 2920: A Diversity outbred (DO) mouse model reveals regulators of HER2-driven tumorigenesis

Abstract Although humans are heterogeneous, evaluation of tumorigenesis and immunotherapy has relied on the use of inbred mouse strains, which may lead to biased results. In order to investigate the effect(s) of genetic background on tumor incidence and immune response, we have taken a unique new approach to identify genes that are associated with tumor onset time &amp; tumor growth rate using Diversity Outbred (DO) mice. Specifically, we crossed DO female mice (J:DO, Jackson Labs) with BALB/NeuT (NeuT) mice to introduce a heterogeneous background in (BALBxDO) F1 NeuT mice. NeuT express transforming rat neu, the homologue of HER2, and develop spontaneous tumors in all 10 mammary glands between 14 and 19 weeks of age (woa). DO mice are generated by non-sibling crosses of 8 founder strains: A/J, C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, WSB/EiJ to encompass greater than 90% of murine polymorphic alleles. The genetic makeup of each F1 mouse is defined using 143,600 chromosomal markers (mostly SNP) in the Giga Mouse Universal Genotyping Array. SNP analysis identifies the origin of quantitative trait loci (QTL), using the R/QTL package. The program reads the GigaMUGA genotyping results to perform haplotype reconstruction and determine the founder strain haplotype of each marker locus. DO F1 mice have been successfully used to identify the critical role of MHC-IB, and NK cells, in generation of HER2 Ab response following vaccination of HER2 tolerant mice (Wei et al., 2020). In (BALBxDO) F1 NeuT female mice most spontaneous mammary tumors develop over a wider range of time from 9 to 23 woa. QTL analysis of tumor onset time revealed QTLs in chromosomes (Chr) 1 and X with peak LOD scores of 7.7 (p = 0.01) and 8.6 (p &amp;lt; 0.05), respectively. Tumor growth rate was associated with a QTL in Chr 10. More specifically, PWK and CAST haplotypes in these QTLs were associated with early and faster growing tumors. About 10-15 genes in the 3 QTLs contain missense SNP alterations unique to PWK and CAST, and the genes have been associated with human breast cancer prognosis. As an example, Mid2 identified in ChrX QTL interacts with BRCA1, and is negatively associated with patient survival using the TCGA BRCA database. Single cell RNA sequencing revealed that Mid2 is expressed in NeuT mammary tumor tissue. Studies are ongoing to determine the functional significance of candidate genes in HER2/neu mammary tumorigenesis. DO F1 QTL combined with scRNA transcriptomic analysis opens important new opportunities to define critical genes in cancer biology and immunotherapy, with the potential for novel intervention and disease prevention. Citation Format: Jennifer Jacob, Kuang Wei, Joyce D. Reyes, Cong-Cong Yin, Elizabeth Rondini, Qing-Sheng Mi, James Granneman, Prahlad Parajuli, K Wagner, Wei-Zen Wei. A Diversity outbred (DO) mouse model reveals regulators of HER2-driven tumorigenesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2920.

Overexpression of SOX2 is associated with poor prognosis in human breast cancer

SOX2 is a transcription factor that activates or suppresses genes involved in cellular differentiation, proliferation, and apoptosis. The deregulation of gene expression programs can lead to cancer initiation, promotion, and progression. The present study investigated SOX2 immunolocalization and expression in Invasive Ductal Carcinoma (IDC), and its correlation with clinical-pathological characteristics of the tumor. Immunohistochemical expression of SOX2 was evaluated in 19 cases of IDC and correlated with clinical-pathological tumor features. To investigate the correlation of SOX2 expression in IDC with other characteristics of human breast cancer, the same samples were also stained with immunohistochemical prognostic panels (estrogen and progesterone receptors, and HER-2). SOX2 overexpression was observed in 44% of the cases. Higher SOX2 expression was correlated with the worst lymph node status (p&lt;0.001) and with positive HER-2 immunostaining (p&lt;0,001). The present study demonstrated the association of SOX2 and tumors with worse TNM staging, as well as its overexpression in positive HER-2 tumors. In conclusion, SOX2 was identified as a potential biomarker for poor prognosis of human breast cancer. Further studies with higher patient numbers are necessary to investigate and help clarify the mechanisms underlying this association. Keywords: SOX2; HER-2; Breast cancer; IHC; Invasive ductal carcinoma; Prognosis.

Breast adipose tissue macrophages (BATMs) have a stronger correlation with breast cancer survival than breast tumor stroma macrophages (BTSMs)

BackgroundAn abundance of tumor-associated macrophages has been shown to be an independent prognostic factor for a poor prognosis of human breast cancer (BC). Adipose tissue accounts for the largest proportion of the breast and has also been identified as an independent indicator of poor survival in BC. This study aims to elucidate if the influence of adipose tissue in BC might be mediated by macrophages. The roles of macrophages in the breast tumor-stroma (breast tumor stroma macrophages, BTSM) and macrophages in the surrounding adipose tissue (breast adipose tissue macrophages, BATM) were explored separately.MethodsTwo hundred ninety-eight BC tissue samples were analyzed immunohistochemically. The number of macrophages was detected by CD68+ staining. The quantity of BATMs and BTSMs was correlated to clinical and pathological parameters as well as to disease-free survival (DFS) and overall survival (OS).ResultsThe amounts of BATMs and BTSMs strongly correlated with each other (r = 0.5, p = 2.98E−15). The quantity of BTSMs, but not of BATMs, was significantly associated with the BC molecular subtype (p = 0.000011), and all triple-negative BC tumors contained high amounts of BTSMs. BATMs were negatively associated with DFS (p = 0.0332). Both BATMs (p = 0.000401) and BTSMs (p = 0.021) were negatively associated with OS in the Kaplan-Meier analysis, but only BATMs remained an independent factor in the multivariate Cox-regression analysis (HR = 4.464, p = 0.004). Combining prostaglandin E2 receptor 3 (EP3)-expression and the quantity of BATMs, a subgroup with an extremely poor prognosis could be identified (median OS 2.31 years in the “high BATMs/low EP3” subgroup compared to 11.42 years in the most favorable “low BATMs/high EP3” subgroup, p = 0.000002).ConclusionOur findings suggest that BTSMs and BATMs seem to be involved differently in BC. Breast adipose tissue might contribute to the aggressiveness of BC via BATMs, which were independently associated with BC survival. BATMs’ role and occurrence might be functionally dependent on EP3, as a combination of both factors was strongly associated with survival. Targeting BATMs—eventually in combination with targeting the EP3-pathway—might be promising for future therapies.

Low Expression of the Polycomb Protein RING1 Predicts Poor Prognosis in Human Breast Cancer.

BackgroundTo date, breast cancer remains the most common malignant tumor in women. In recent years, a growing number of studies on polycomb proteins have been conducted. The Ring finger protein1 (RING1), an essential component of the polycomb family of proteins, plays vital roles in the tumorigenesis of various cancer types. However, further research is required in determining RING1 expression and prognostic value in breast cancer.MethodRING1 expression level in multiple cancer types was evaluated using the XENA and UALCAN databases. Real-time quantitative PCR (real-time qPCR) and immunohistochemistry (IHC) were used to confirm this expression. The prognostic value was analyzed using our follow-up data and the Kaplan–Meier plotter website. RING1 co-expressed genes and its promoter methylation level were calculated using the cBioPortal and UALCAN online tools. The gene ontology (GO) and the Kyoto encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using the DAVID online analysis tool.ResultRING1 expression was upregulated in CHOL (Bile Duct Cancer), ESCA (Esophageal Cancer), LIHC (Liver Cancer), and PCPG (Pheochromocytoma & Paraganglioma). However, its expression level was decreased in COAD (Colon Cancer), KICH (Kidney Chromophobe), KIRP (kidney papillary cell carcinoma), THCA (Thyroid Cancer), and BRCA (Breast carcinoma). RING1 low expression is an unfavorable prognostic factor in many cancer patients, especially in breast cancer patients. For breast cancer, the IHC result showed that RING1 protein expression significantly and negatively correlates with tumor size (P = 0.029), LNM (P = 0.017), TNM stage (P = 0.016), ER (P = 0.005), Ki67 (P = 0.015), and p53 status (P = 0.034). Moreover, the multivariate Cox regression model indicated that RING1 (P = 0.038) and ER (P = 0.029) expressions were independent prognostic markers for breast cancer. RING1 co-expressed genes were selected and included HDAC10, PIN1, CDK3, BAX, and BAD. GO analysis and KEGG pathway analyses revealed that RING1 related genes, were mainly enriched in “regulation of transcription”, “apoptotic process”, “protein transport”, “protein binding”, “Notch signaling pathway”, and “Homologous recombination”.ConclusionRING1 expression was downregulated in breast cancer, and its low expression was associated with worse disease outcomes. RING1 may act as a new prognostic biomarker for breast cancer.

Regulatory effect of the MAFG‑AS1/miR‑150‑5p/MYB axis on the proliferation and migration of breast cancer cells.

Long noncoding RNA (lncRNA) MAF BZIP transcription factor G antisense RNA 1 (MAFG-AS1) has been demonstrated to serve an important role in the progression of various types of cancer, whereas its role in breast cancer has not been fully elucidated. The present study aimed to explore the potential role and underlying mechanism of MAFG-AS1 in breast cancer. To achieve this, the expression of MAFG-AS1, microRNA (miR)-150-5p and MYB was detected by reverse transcription-quantitative PCR. The binding between miR-150-5p and MAFG-AS1 or MYB was verified using a luciferase reporter assay. Cell proliferation was analyzed by MTS, apoptosis and cell cycle were detected by Annexin V/propidium iodide, and cell migration was analyzed by wound healing assay. The results demonstrated that the expression levels of MAFG-AS1 were significantly upregulated in breast cancer tissues and cells compared with those in normal breast tissues and cells. High MAFG-AS1 expression promoted the proliferation, migration and epithelial-mesenchymal transition of breast cancer cells. By contrast, miR-150-5p expression was reduced in breast cancer tissues compared with that in healthy breast tissues, and low expression of miR-150-5p was associated with poor overall survival in patients with breast cancer. Bioinformatics and luciferase assay revealed that MAFG-AS1 served as a sponge of miR-150-5p, and that miR-150-5p bound to MYB. The functional rescue assay results demonstrated that MAFG-AS1 knockdown suppressed the proliferation and migration of breast cancer cells by regulating miR-150-5p, which in turn targeted MYB. In conclusion, the results of the present study demonstrated that MAFG-AS1 functioned as a novel oncogenic lncRNA in the development of human breast cancer via regulating the miR-150-5p/MYB axis, which suggested that MAFG-AS1 may be a novel biomarker for the diagnosis and prognosis of human breast cancer.

Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model.

Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the breast. Despite significant advances in the treatment of primary breast cancer in the last decade, there is a dire need to attempt of an accurate predictive model for breast cancer prognosis prediction. Researchers from various disciplines are working together to develop methods to save people from this fatal disease. A good predictive model can help in correct prognosis prediction of breast cancer. This accurate prediction can have several benefits like detection of cancer in the early stage, spare patients from getting unnecessary treatment and medical expenses related to it. Previous works rely mostly on uni-modal data (selected gene expression)for predictive model design. In recent years, however, multi-modal cancer data sets have become available (gene expression, copy number alteration and clinical). Motivated by the enhancement of deep-learning based models, in the current study, we propose to use some deep-learning based predictive models in a stacked ensemble framework to improve the prognosis prediction of breast cancer from available multi-modal data sets. One of the unique advantages of the proposed approach lies in the architecture of the model. It is a two-stage model. Stage one uses a convolutional neural network for feature extraction, while stage two uses the extracted features as input to the stack-based ensemble model. The predictive performance evaluated using different performance measures shows that this model produces better result than already existing approaches. This model results in AUC value of 0.93 and accuracy of 90.2 percent at medium stringency level (Specificity = 95 percent and threshold = 0.45). Keras 2.2.1, along with Tensorflow 1.12, is used for implementing the source code of the model. The source code can be downloaded from Github: https://github.com/nikhilaryan92/BreastCancer.

Abstract 2504: Modeling molecular development of breast cancer in canine mammary tumors

Abstract Malignancy in cancer is a consequence of the progressive accumulation of mutations in a tumor, with profound implications for drug selection and treatment. However, in human studies, inter-patient variability obscures molecular signatures of tumor progression because patients usually present with a single mammary tumor. In contrast, dogs frequently exhibit multiple naturally occurring mammary tumors in the same individual. Moreover, canine mammary tumors (CMTs) and human breast cancer have similar histopathological profiles and clinical presentation. We leverage the CMT model to elucidate genome-wide molecular changes clinically relevant in human breast cancer, focusing on signals underlying tumor development. We develop a robust, generally applicable, computational analysis framework (FREYA) for analysis of CMTs for comparative oncology. Using FREYA, we RNA profile 89 samples from 16 dogs, and demonstrate that CMTs recapitulate human breast cancer subtypes. We then extract molecular profiles of breast cancer progression at three distinct stages (normal, pre-malignant and malignant) and identify signatures of gene expression reflective of tumor progression. Focusing on the transitions to malignancy, we identify transcriptional patterns and biological pathways specific to malignant tumors and distinct from those characterizing pre-malignant tumors or normal tissue. We find that human breast cancer patients whose tumors exhibit strong CMT malignancy signatures have significantly decreased survival, indicative of the importance of the tumor progression processes identified in CMTs to human breast cancer prognosis. Altogether, our comprehensive genomic characterization demonstrates that CMTs are a powerful translational model of breast cancer, providing insights that inform our understanding of tumor development in humans. To catalyze and support similar analyses and use of the CMT model by other biomedical researchers, we publicly share all of our data and provide FREYA, a robust data processing pipeline and statistical analyses framework, at freya.flatironinstitute.org. Citation Format: Kiley Graim, Dmitriy Gorenshteyn, David G. Robinson, Nicholas J. Carriero, James Cahill, Rumela Chakrabarti, Michael H. Goldschmidt, Amy C. Durham, Julien Funk, John D. Storey, Vessela N. Kristensen, Chandra L. Theesfeld, Karin U. Sorenmo, Olga G. Troyanskaya. Modeling molecular development of breast cancer in canine mammary tumors [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2504.

Conditional Gene Targeting Reveals Cell Type-Specific Roles of the Lysosomal Protease Cathepsin L in Mammary Tumor Progression.

Background: Cathepsin L (Ctsl) is a cysteine protease mainly located within the endosomal/lysosomal cell compartment. High expression of Ctsl indicates poor prognosis in human breast cancer. However, the cell type-specific Ctsl functions responsible for this association remain elusive. Methods: Because constitutive Ctsl−/− mice develop a complex phenotype, we developed a conditional model allowing for cell type-specific inactivation of Ctsl in mammary epithelium or myeloid cells in the transgenic mouse mammary tumor virus (MMTV)-polyoma middle T (PyMT) breast cancer model. Results: Ctsl ablation in mammary epithelial cells resulted in delayed initiation and end-stage of cancers. The latter displayed large dead cell areas. Inducible in vitro deletion of Ctsl in MMTV-PyMT-derived breast cancer cells revealed expansion of the acidic cell compartment, alteration of intracellular amino acid levels, and impaired mTOR signaling. In consequence, Ctsl-deficient cells exhibited slow growth rates and high apoptosis susceptibility. In contrast to Ctsl-deficient mammary epithelium, selective knockout of Ctsl in myeloid cells had no effects on primary tumors, but promoted lung metastasis formation. Conclusions: Our cell type-specific in vivo analysis provides strong evidence for a cancer cell-intrinsic, tumor-promoting role of Ctsl in primary breast cancer, whereas metastasis is negatively regulated by Ctsl expressed by bone marrow-derived cells.

GLUT1/3/4 as novel biomarkers for the prognosis of human breast cancer.

BackgroundAnomalous expression of glucose transporters (GLUTs) has been observed in a variety of tumor tissues. Although GLUT factors have been shown to have prognostic value for some cancer types, detailed bioinformatics investigation of the factors contributing to the prognostic prediction for patients with breast cancer (BC) has not yet been performed.MethodsIn this study, we examined the transcription levels of GLUT1, GLUT3, and GLUT4 and their associations with prognostic clinical data in patients with BC from the ONCOMINE database, using gene expression profiling interactive analysis (GEPIA), Kaplan-Meier (KM) plotter, and cBioPortal online tools.ResultsThe transcription level of GLUT1 was significantly higher in the BC samples than in the normal tissues, whereas the levels of GLUT3 and GLUT4 were lower in the BC samples. The expression levels of GLUT1 and GLUT3 were associated with the cancer clinical stage. Consistently, survival analysis demonstrated that a high expression level of GLUT1 was associated with low relapse-free survival (RFS) in patients with BC, whereas high GLUT3 and GLUT4 levels predicted a longer RFS in these patients.ConclusionsOverall, these results suggest GLUT1 as an effective target of precision therapy, while GLUT3/4 are novel biomarkers for the prognosis of patients with BC.

Loss of ANCO1 repression at AIB1/YAP targets drives breast cancer progression.

Transcription factors critical for the transition of normal breast epithelium to ductal carcinoma insitu (DCIS) and invasive breast cancer are not clearly defined. Here, we report that the expression of a subset of YAP-activated and YAP-repressed genes in normal mammary and early-stage breast cancer cells is dependent on the nuclear co-activator AIB1. Gene expression, sequential ChIP, and ChIP-seq analyses show that AIB1 and YAP converge upon TEAD for transcriptional activation and repression. We find that AIB1-YAP repression of genes at the 1q21.3 locus is mediated by AIB1-dependent recruitment of ANCO1, a tumor suppressor whose expression is progressively lost during breast cancer progression. Reducing ANCO1 reverts AIB1-YAP-dependent repression, increases cell size, and enhances YAP-driven aberrant 3D growth. Loss of endogenous ANCO1 occurs during DCIS xenograft progression, a pattern associated with poor prognosis in human breast cancer. We conclude that increased expression of AIB1-YAP co-activated targets coupled with a loss of normal ANCO1 repression is critical to patterns of gene expression that mediate malignant progression of early-stage breast cancer.

A "NOTCH" Deeper into the Epithelial-To-Mesenchymal Transition (EMT) Program in Breast Cancer.

Notch signaling is a primitive signaling pathway having various roles in the normal origin and development of each multicellular organisms. Therefore, any aberration in the pathway will inevitably lead to deadly outcomes such as cancer. It has now been more than two decades since Notch was acknowledged as an oncogene in mouse mammary tumor virus-infected mice. Since that discovery, activated Notch signaling and consequent up-regulation of tumor-promoting Notch target genes have been observed in human breast cancer. Moreover, consistent over-expression of Notch ligands and receptors has been shown to correlate with poor prognosis in human breast cancer. Notch regulates a number of key processes during breast carcinogenesis, of which, one key phenomenon is epithelial–mesenchymal transition (EMT). EMT is a key process for large-scale cell movement during morphogenesis at the time of embryonic development. Cancer cells aided by transcription factors usurp this developmental program to execute the multi-step process of tumorigenesis and metastasis. In this review, we recapitulate recent progress in breast cancer research that has provided new perceptions into the molecular mechanisms behind Notch-mediated EMT regulation during breast tumorigenesis.

Transgelin-2 expression in breast cancer and its relationships with clinicopathological features and patient outcome.

Transgelin-2 is an actin-binding protein that is widely expressed in various tissues and organs of the body, and reportedly may participate in the development and progression of multiple cancers. However, the clinical significance of transgelin-2 still remains controversial. We, therefore, aimed to determine the expression of transgelin-2 in breast cancer as well as its correlation with the tumorigenesis, progression and prognosis of human breast cancer. We collected tissues of 58 breast cancer patients from our hospital and 1090 samples from The Cancer Genome Atlas (TCGA) database. X-tile software was used to divide the transgelin-2 mRNA expression level in the database, logistic regression model was used to identify independent factors influencing transgelin-2 mRNA expression, and then Cox regression and Kaplan-Meier analysis were used to find factors that influence survival of breast cancer. Transgelin-2 was significantly overexpressed in breast cancer tissues from our hospital and receiver operating characteristic (ROC) curve indicated that transgelin-2 may have diagnostic value. Meanwhile, estrogen receptor (ER) was in inverse correlation with transgelin-2 protein and mRNA expression, and transgelin-2 expression was positively correlated with Ki67 in breast cancer tissues. Logistic regression model revealed that TNM stage, ER and progesterone receptor (PR) status were independent factors for transgelin-2 mRNA expression. Patients with high transgelin-2 mRNA expression showed a poor survival and the trend was statistically significant only in ER-negative patients. Transgelin-2 was expressed significantly higher in breast cancer cells and correlated with some clinicopathological factors. High transgelin-2 expression might predict poor prognosis for ER-negative patients.