Prediction of lymph node involvement in breast cancer from primary tumor tissue using gene expression profiling and miRNAs

Exploring the time-dependent regulatory potential of microRNAs in breast cancer cells treated with proteasome inhibitors

PURPOSE

Breast cancer (BrCa) is a predominant type of cancer with a disparate molecular nature. MicroRNAs (miRNAs) have emerged as promising key players in the regulation of pathological processes in BrCa. Proteasome inhibitors (PIs) emerged as promising anticancer agents for several human malignancies, including BrCa, inhibiting the function of the proteasome. Aiming to shed light on the miRNA regulatory effect in BrCa after treatment with PIs, we used two PIs, namely bortezomib and carfilzomib.

MATERIALS AND METHODS

Four BrCa cell lines of distinct molecular subtypes were treated with these PIs. Cell viability and IC50 concentrations were determined. Total RNA was extracted, polyadenylated, and reversely transcribed. Next, the levels of specific miRNAs with a significant role in BrCa were determined using relative quantification, and their regulatory effect was assessed.

RESULTS

High heterogeneity was discovered in the levels of miRNAs in the four cell lines, after treatment. The miRNA levels fluctuate with distinct patterns, in 24, 48, or 72 hours. Interestingly, miR-1-3p, miR-421-3p, and miR-765-3p appear as key molecules, as they were found deregulated, in almost all combinations of cell lines and PIs. In the SK-BR-3 cell line, the majority of the miRNAs were significantly downregulated in treated compared to untreated cells, with miR-21-5p being the only one upregulated. Finally, various significant biological processes, molecular functions, and pathways were predicted to be affected.

CONCLUSIONS

The diversity of pathways predicted to be affected by the diversity in miRNA expression after treatment with PIs paves the way for the recognition of new regulatory axes in BrCa.

Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer

Cervical lymph node metastasis is the leading cause of poor prognosis in oral tongue squamous cell carcinoma and also occurs in the early stages. The current clinical diagnosis depends on a physical examination that is not enough to determine whether micrometastasis remains. The transcriptome profiling technique has shown great potential for predicting micrometastasis by capturing the dynamic activation state of genes. However, there are several technical challenges in using transcriptome data to model patient conditions: (1) An Insufficient number of samples compared to the number of genes, (2) Complex dependence between genes that govern the cancer phenotype, and (3) Heterogeneity between patients between cohorts that differ geographically and racially. We developed a computational framework to learn the subnetwork representation of the transcriptome to discover network biomarkers and determine the potential of metastasis in early oral tongue squamous cell carcinoma. Our method achieved high accuracy in predicting the potential of metastasis in two geographically and racially different groups of patients. The robustness of the model and the reproducibility of the discovered network biomarkers show great potential as a tool to diagnose lymph node metastasis in early oral cancer.

Screening of miRNAs associated with lymph node metastasis in Her-2-positive breast cancer and their relationship with prognosis

The aim of this study was to identify some biomarkers for predicting lymph node metastasis and prognosis of human epidermal growth factor receptor 2 (Her-2)-positive breast cancer (BC). We analyzed correlations between microRNAs (miRNAs) and the prognosis of patients with BC based on data collected from The Cancer Genome Atlas (TCGA) database. The expression levels of miR-455, miR-143, and miR-99a were measured in clinical samples of Her-2-positive BC patients with different degrees of lymph node metastasis. We investigated the impacts of overexpressed miR-455 on the proliferation and invasiveness of MDA-MB-453 cells and measured its effects on the expression of long non-coding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) by quantitative real-time polymerase chain reaction (qRT-PCR). The expression of miR-455 was significantly and positively correlated to the prognosis and overall survival (OS) of the BC (P=0.028), according to TCGA information. The expression level of miR-455 was positively correlated with OS and relapse-free survival (RFS) of patients with Her-2-positive BC, and was negatively correlated with the number of metastatic lymph nodes (P<0.05). Transwell assay suggested that MDA-MB-453 cells became much less invasive (P<0.01) after being transfected with miR-455 mimics. During the qRT-PCR, the expression level of MALAT1 declined significantly after transfection (P<0.01). Overexpressed miR-455 significantly inhibited the proliferation and migration of MDA-MB-453 cells and the expression of MALAT1. We conclude that miR-455 may be a useful potential biomarker for forecasting lymph node metastasis and the prognosis of Her-2-positive BC patients. miR-455 may play an important role in lymph node metastasis of BC by interacting with MALAT1.

Evaluating the transcriptional fidelity of cancer models

BACKGROUND

Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investigation; however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors.

METHODS

We developed a machine learning-based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient-derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence.

RESULTS

We have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient-derived xenografts and cell lines in four out of five tumor types. However, several patient-derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity.

CONCLUSIONS

CancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as a freely downloadable R package ( https://github.com/pcahan1/cancerCellNet ) and as a web application ( http://www.cahanlab.org/resources/cancerCellNet_web ) that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

Gene expression comparison between primary estrogen receptor-positive and triple-negative breast cancer with paired axillary lymph node metastasis

The aim of this study is to characterize and compare changes in gene expression patterns of paired axillary lymph node (ALN) metastases from estrogen receptor (ER)-positive and triple-negative (TNBC) primary breast cancer (PBC). Patients with stage 2-3 PBC with macrometastasis to an ALN were selected. Gene expression of 2567 cancer-associated genes was analyzed with the HTG EdgeSeq system coupled with the Illumina Next Generation Sequencing (NGS) platform. Changes in gene expression between ER/PR-positive, HER2-negative PBC, and their paired ALN metastases were compared with TNBC and their paired ALN metastases. Fourteen pairs of ER-positive and paired ALN metastasis were analyzed. Compared with the PBC, ALN metastasis had 673 significant differentially expressed genes, including 348 upregulated genes and 325 downregulated genes. Seventeen pairs of TNBC and paired ALN metastasis were analyzed. ALN metastasis had 257 significant differentially expressed genes, including 123 upregulated genes and 134 downregulated genes. When gene expression of the ALN for ER-positive PBC was compared to that of TNBC, 97 genes were upregulated in both, and 115 genes were similarly downregulated. Common upregulated genes were associated with cell death, necrosis, and homeostasis. Common downregulated genes were those of migration, degradation of extracellular matrix, and invasion. Although ER-positive PBC and TNBC have a distinct gene expression profiles and distinct changes from PBC to ALN metastases, a significant number of genes are similarly up- or downregulated. Understanding the role of these common genomic changes may provide clues to understanding the metastatic process itself.

MicroRNA-1291 Is Associated With Locoregional Metastases in Patients With Early-Stage Breast Cancer

Evidence that microRNAs (miRNAs) regulate the various steps of metastasis is increasing. Several studies have looked at the miRNA expression profile in primary breast tumors but few have compared primary tumor and sentinel lymph node (SLN) metastasis. We correlated the expression of miRNAs with the SLN status and the outcome of axillary lymph node dissection (ALND) in 60 patients with early breast cancer. We profiled the expression of miRNAs in paired breast tumor samples and SLNs using the NextSeq500 Illumina platform and key findings were validated by qPCR. MultiMiR Bioconductor and Reactome pathways analysis were performed to identify target genes and signaling pathways affected by altered expressed miRNAs. Our results show that nine miRNAs were differentially expressed in tumor tissues (q ≤ 0.05). In tumor samples, a 13.5-fold up-regulation of miR-7641-2 (q < 0.001) and a 2.9-fold down-regulation of miR-1291 (q < 0.001) were associated with tumors with positive SLNs. However, only down-regulation of miR-1291 (q = 0.048) remained significant in paired SLNs samples. Interestingly, a 10.5 up-regulation of miR-1291 in SLNs samples was associated with additional axillary lymph node involvement (q < 0.001). The enrichment analyses showed that canonical and non-canonical WNT pathways and negative regulation of various receptor tyrosine kinases signaling pathways were targets of miR-1291 and supports the role of miR-1291 as a tumor suppressor gene (TSG). Further studies are warranted to investigate the use of miR-1291 as a surrogate biomarker of SLN node metastasis in patients with early-stage breast cancer.

Impact of Bone Marrow miR-21 Expression on Acute Myeloid Leukemia T Lymphocyte Fragility and Dysfunction

BACKGROUND

Acute myeloid leukemia (AML) is a hematopoietic malignancy in which antitumor immunity is impaired. The therapeutic management of AML requires understanding the mechanisms involved in the fragility and immune dysfunction of AML T lymphocytes.

METHODS

In this study, T lymphocytes from healthy donors (HD) and AML patients were used. Extracellular vesicles (EVs) from leukemic cells were screened for their microRNA content and impact on T lymphocytes. Flow cytometry, transcriptomic as well as lentiviral transduction techniques were used to carry out the research.

RESULTS

We observed increased cell death of T lymphocytes from AML patients. EVs from leukemia myeloid cell lines harbored several miRNAs, including miR-21, and were able to induce T lymphocyte death. Compared to that in HD, miR-21 was overexpressed in both the bone marrow fluid and infiltrating T lymphocytes of AML patients. MiR-21 induces T lymphocyte cell death by upregulating proapoptotic gene expression. It also increases the immunosuppressive profile of T lymphocytes by upregulating the IL13, IL4, IL10, and FoxP3 genes.

CONCLUSIONS

Our results demonstrate that miR-21 plays a significant role in AML T lymphocyte dysfunction and apoptosis. Targeting miR-21 may be a novel approach to restore the efficacy of the immune response against AML.

Development of Prediction Model Including MicroRNA Expression for Sentinel Lymph Node Metastasis in ER-Positive and HER2-Negative Breast Cancer

BACKGROUND

The aim of our study is to find microRNAs (miRNAs) associated with sentinel lymph node metastasis (SLNM) and to develop a prediction model for SLNM in ER-positive and HER2-negative (ER+/HER2-) breast cancer.

PATIENTS AND METHODS

In the present study, only ER+/HER2- primary breast cancer was considered. The discovery set for SLNM-associated miRNAs included 10 tumors with and 10 tumors without SLNM. The training and validation sets both included 100 tumors. miRNA expression in tumors was examined comprehensively by miRNA microarray in the discovery set and by droplet digital PCR in the training and validation sets.

RESULTS

In the discovery set, miR-98, miR-22, and miR-223 were found to be significantly (P < 0.001, fold-change > 2.5) associated with SLNM. In the training set, we constructed the prediction model for SLNM using miR-98, tumor size, and lymphovascular invasion (LVI) with high accuracy (AUC, 0.877). The accuracy of this prediction model was confirmed in the validation set (AUC, 0.883), and it outperformed the conventional Memorial Sloan Kettering Cancer Center nomogram. In situ hybridization revealed the localization of miR-98 expression in tumor cells.

CONCLUSIONS

We developed a prediction model consisting of miR-98, tumor size, and LVI for SLNM with high accuracy in ER+/HER2- breast cancer. This model might help decide the indication for SLN biopsy in this subtype.

Gene expression comparison between primary triple-negative breast cancer and paired axillary and sentinel lymph node metastasis

Few studies examine the genomics of axillary lymph node (ALN) metastasis in triple-negative breast cancer (TNBC). The aim was to characterize and compare gene expression patterns of primary breast cancers and paired ALN metastases. Patients with stage 2-3 ER/PR negative, HER2 negative TNBC with ALN macrometastasis without neo-adjuvant therapy were selected. Tumor-specific area was isolated from breast and ALN tissue sections. Gene expression of 2567 cancer-associated genes was analyzed with the HTG EdgeSeq system coupled with Illumina next-generation sequencing (NGS). Seventeen pairs of TNBC and autologous ALN metastasis were analyzed. Compared with the primary, ALN metastasis had 257 statistically significant differentially expressed genes, including 123 upregulated genes and 134 downregulated genes. Notably, there was an upregulation of anti-apoptosis and survival signaling genes (BIRC3, TCL1A, FLT3, and VCAM1) in the ALN metastasis. There was also an upregulation of chemotaxis genes (CCL19, CCL21, CXCL13, and TNFSF11). The most striking feature is the downregulation of genes known to regulate cell microenvironment interaction (MMP2, MMP 3, MMP 7, MMP 11, MMP14, COL1A1, COL1A2, COL3A1, COL5A1, COL5A2, COL6A6, COL11A1, and COL17A1). In TNBC, ALN metastases have a distinct gene expression profile. Genes associated with anti-apoptosis, survival responses, and chemotaxis are upregulated, and genes associated with regulation of extracellular matrix are downregulated when compared to autologous primary cancer. TNBC cells metastatic to lymph nodes undergo a change in order to metastasize and survive in the new microenvironment, which may lead to insights into the metastatic process.

Prediction of Lymph Node Metastasis in Breast Cancer by Gene Expression and Clinicopathological Models: Development and Validation within a Population-Based Cohort

PURPOSE

More than 70% of patients with breast cancer present with node-negative disease, yet all undergo surgical axillary staging. We aimed to define predictors of nodal metastasis using clinicopathological characteristics (CLINICAL), gene expression data (GEX), and mixed features (MIXED) and to identify patients at low risk of metastasis who might be spared sentinel lymph node biopsy (SLNB).Experimental Design: Breast tumors (n = 3,023) from the population-based Sweden Cancerome Analysis Network-Breast initiative were profiled by RNA sequencing and linked to clinicopathologic characteristics. Seven machine-learning models present the discriminative ability of N0/N+ in development (n = 2,278) and independent validation cohorts (n = 745) stratified as ER⁺HER2^-, HER2⁺, and TNBC. Possible SLNB reduction rates are proposed by applying CLINICAL and MIXED predictors.

RESULTS

In the validation cohort, the MIXED predictor showed the highest area under ROC curves to assess nodal metastasis; AUC = 0.72. For the subgroups, the AUCs for MIXED, CLINICAL, and GEX predictors ranged from 0.66 to 0.72, 0.65 to 0.73, and 0.58 to 0.67, respectively. Enriched proliferation metagene and luminal B features were noticed in node-positive ER⁺HER2^- and HER2⁺ tumors, while upregulated basal-like features were observed in node-negative TNBC tumors. The SLNB reduction rates in patients with ER⁺HER2^- tumors were 6% to 7% higher for the MIXED predictor compared with the CLINICAL predictor accepting false negative rates of 5% to 10%.

CONCLUSIONS

Although CLINICAL and MIXED predictors of nodal metastasis had comparable accuracy, the MIXED predictor identified more node-negative patients. This translational approach holds promise for development of classifiers to reduce the rates of SLNB for patients at low risk of nodal involvement.

Decreased Expression of MicroRNA-107 in B Lymphocytes of Patients with Antibody-Mediated Renal Allograft Rejection

MicroRNAs (miRNAs) are small noncoding RNA molecules that participate in normal B cell lineage development through posttranscriptional gene regulation. Antibody-mediated renal allograft rejection (ABMR) is emerging as one of the most common serious threats to renal transplant patients. In this study, we explored the role of miRNAs in the pathogenesis of ABMR. The differentially expressed miRNAs were identified by Affymetrix miRNA microarray analysis using B lymphocytes from 5 recipients and 5 volunteers. Based on quantitative RT-PCR, the expression levels of miR-107 were lower in the B lymphocytes from recipients than in those from volunteers. Computational analysis predicted that 3'-untranslated region of the autophagy-related protein 12 (ATG12) mRNA was targeted by miR-107, and we identified ATG12 as a target of miR-107 by Luciferase assay. Importantly, the expression levels of ATG12 in B lymphocytes of recipients were higher than those in the volunteer group, and miR-107 mimic significantly decreased ATG12 expression and formation of autolysosomes in B lymphocytes of recipients. Furthermore, we observed that levels of autophagy in B lymphocytes of transplant recipients were higher than those in B cells from volunteers. These findings suggest that miR-107 may contribute to the regulation of autophagy via targeting ATG12. Lastly, treatment with an miR-107 mimic caused the decrease in the secretion of IgG and IgM antibodies from B lymphocytes of transplant recipients, indicating that deregulated miR-107 could be involved in the pathogenesis of ABMR. Taken together, we propose that decreased miR-107 expression is associated with autophagy activation in B lymphocytes from patients with ABMR.

miRNA in a multiomic context for diagnosis, treatment monitoring and personalized management of metastatic breast cancer

Metastatic breast cancer is characterized by aggressive spreading to distant organs. Despite huge multilevel research, there are still several important challenges that have to be clarified in the management of this disease. Therefore, recent investigations have implemented a modern, multiomic approach with the aim of identifying specific biomarkers for not only early detection but also to predict treatment responses and metastatic spread. Specific attention is paid to short miRNAs, which regulate gene expression at the post-transcriptional level. Aberrant miRNA expression could initiate cancer development, cell proliferation, invasion, migration, metastatic spread or drug resistance. An miRNA signature is, therefore, believed to be a promising biomarker and prediction tool that could be utilized in all phases of carcinogenesis. This article offers comprehensive information about miRNA profiles useful for diagnostic and treatment purposes that may sufficiently advance breast cancer management and improve individual outcomes in the near future.

Unravelling site-specific breast cancer metastasis: a microRNA expression profiling study

Distant metastasis is still the main cause of death from breast cancer. MicroRNAs (miRs) are important regulators of many physiological and pathological processes, including metastasis. Molecular breast cancer subtypes are known to show a site-specific pattern of metastases formation. In this study, we set out to determine the underlying molecular mechanisms of site-specific breast cancer metastasis by microRNA expression profiling.

To identify a miR signature for metastatic breast carcinoma that could predict metastatic localization, we compared global miR expression in 23 primary breast cancer specimens with their corresponding multiple distant metastases to ovary (n=9), skin (n=12), lung (n=10), brain (n=4) and gastrointestinal tract (n=10) by miRCURY microRNA expression arrays. For validation, we performed quantitative real-time (qRT) PCR on the discovery cohort and on an independent validation cohort of 29 primary breast cancer specimens and their matched metastases.

miR expression was highly patient specific and miR signatures in the primary tumor were largely retained in the metastases, with the exception of several differentially expressed, location specific miRs. Validation with qPCR demonstrated that hsa-miR-106b-5p was predictive for the development of lung metastases. In time, the second metastasis often showed a miR upregulation compared to the first metastasis.

This study discovered a metastatic site-specific miR and found miR expression to be highly patient specific. This may lead to novel biomarkers predicting site of distant metastases, and to adjuvant, personalized targeted therapy strategies that could prevent such metastases from becoming clinically manifest.

MicroRNA expression profiles in benign prostatic hyperplasia

Although alterations in microRNA (miRNA) expression have been previously investigated prostate cancer, the expression of miRNAs specifically in benign prostate hyperplasia (BPH) of the prostatic stroma remains to be fully elucidated. In the present study, miRNAs and gene expression profiles were investigated using microarray analysis and reverse transcription quantitative‑polymerase chain reaction (RT‑qPCR) in BPH tissue to clarify the associations between miRNA expression and target genes. Prostate tissue samples from five patients with BPH and five healthy men were analyzed using human Affymetrix miRNA and mRNA microarrays and differentially expressed miRNAs were validated using RT‑qPCR with 30 BPH and 5 healthy control samples. A total of 8 miRNAs, including miRNA (miR)‑96‑5p, miR‑1271‑5p, miR‑21‑3p, miR‑96‑5p, miR‑181a‑5p, miR‑143‑3p, miR‑4428 and miR‑106a‑5p were upregulated and 8 miRNAs (miR‑16‑5p, miR‑19b‑5p, miR‑940, miR‑25, miR‑486‑3p, miR‑30a‑3p, let‑7c and miR‑191) were downregulated. Additionally, miR‑96‑5p was demonstrated to have an inhibitory effect on the mRNA expression levels of the following genes: Mechanistic target of rapamycin (MTOR), RPTOR independent companion of MTOR complex 2, syntaxin 10, autophagy‑related protein 9A, zinc finger E‑box binding homeobox 1, caspase 2 and protein kinase c ε. Additionally, 16 differentially expressed miRNAs were identified using RT‑qPCR analysis. This preliminary study provides a solid basis for a further functional study to investigate the underlying regulatory mechanisms of BPH.

Gene expression information improves reliability of receptor status in breast cancer patients

Immunohistochemical (IHC) determination of receptor status in breast cancer patients is frequently inaccurate. Since it directs the choice of systemic therapy, it is essential to increase its reliability.

We increase the validity of IHC receptor expression by additionally considering gene expression (GE) measurements. Crisp therapeutic decisions are based on IHC estimates, even if they are borderline reliable. We further improve decision quality by a responsibility function, defining a critical domain for gene expression. Refined normalization is devised to file any newly diagnosed patient into existing data bases. Our approach renders receptor estimates more reliable by identifying patients with questionable receptor status. The approach is also more efficient since the rate of conclusive samples is increased. We have curated and evaluated gene expression data, together with clinical information, from 2880 breast cancer patients. Combining IHC with gene expression information yields a method more reliable and also more efficient as compared to common practice up to now.

Several types of possibly suboptimal treatment allocations, based on IHC receptor status alone, are enumerated. A ‘therapy allocation check’ identifies patients possibly miss-classified. Estrogen: false negative 8%, false positive 6%. Progesterone: false negative 14%, false positive 11%. HER2: false negative 2%, false positive 50%. Possible implications are discussed.

We propose an ‘expression look-up-plot’, allowing for a significant potential to improve the quality of precision medicine.

Methods are developed and exemplified here for breast cancer patients, but they may readily be transferred to diagnostic data relevant for therapeutic decisions in other fields of oncology.

NanoString-based breast cancer risk prediction for women with sclerosing adenosis

Purpose

Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA.

Methods

The study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation.

Results

Gene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67).

Conclusions

Our results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available.

Electronic supplementary material

The online version of this article (doi:10.1007/s10549-017-4441-z) contains supplementary material, which is available to authorized users.

Metastatic breast cancer: the potential of miRNA for diagnosis and treatment monitoring

Breast cancer affects approximately 12 % women worldwide and results in 14 % of all cancer-related fatalities. Breast cancer is commonly categorized into one of four main subtypes (luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) positive and basal), indicating molecular characteristics and informing treatment regimes. The most severe form of breast cancer is metastasis, when the tumour spreads from the breast tissue to other parts of the body. Significantly, the primary tumour subtype affects rates and sites of metastasis. Currently, up to 5 % of patients present with incurable metastasis, with an additional 10–15 % of patients going on to develop metastasis within 3 years of diagnosis. MicroRNAs (miRNAs) are short 21–25 long nucleotides that have been shown to significantly affect gene expression. Currently, >2000 miRNAs have been identified and significantly, specific miRNAs have been found associated with diseases states. Importantly, miRNAs are found circulating in the blood, presenting an opportunity to use these circulating disease-related miRNAs as biomarkers. Clearly, the identification of circulating miRNA specific to metastatic breast cancer presents a unique opportunity for early disease identification and for monitoring disease burden. Currently however, few groups have identified miRNA associated with metastatic breast cancer. Here, we review the literature surrounding the identification of metastatic miRNA in breast cancer patients, highlighting key areas where miRNA biomarker discovery could be beneficial, identifying key concepts, recognizing critical areas requiring further research and discussing potential problems.

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer

Background:

Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities.

Methods:

We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We also included patient-matched non-cancerous thyroid and lymph node samples as controls to address some limits of previous studies.

Results:

The transcriptomes of patient-matched primary tumours and metastases were more similar than those of unrelated metastases/primary pairs, as previously reported in other organ systems. This similarity partly reflected patient background. Lymphoid tissues in the metastases confounded the comparison of patient-matched primary tumours and metastases. We circumvented this with an original data adjustment, revealing a differential expression of stroma-related gene signatures also regulated in other organs. The comparison of N0 vs N+ primary tumours uncovered a signal irreproducible across independent data sets. This signal was also detectable when comparing the non-cancerous thyroid tissues adjacent to N0 and N+ tumours, suggesting a cohort-specific bias also likely present in previous similarly sized studies. Classification of N0 vs N+ yielded an accuracy of 63%, but additional statistical controls absent in previous studies revealed that this is explainable by chance alone. We used large data sets from The Cancer Genome Atlas: N0 vs N+ classification was not better than random for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Conclusions:

The clinical potential of gene expression to predict nodal metastases seems limited for most cancers.

Circulating microRNAs for the prediction of metastasis in breast cancer patients diagnosed with early stage disease

Breast cancer is the second most common malignancy diagnosed in women worldwide. The greatest cause of breast cancer mortality is development of metastasis. For many women metastasis is an early event in breast cancer which goes undetected until its presentation, thus there is an urgent need for the development of biomarkers to predict those patients at greatest risk. The expression of a group of small non-coding RNAs, termed microRNAs, has been shown to be altered in tumours. Furthermore, microRNAs identified as being highly expressed in breast cancer tumours can also be detected in the circulation. Circulating microRNAs are an emerging field of biomarker research which have the benefit of being able to be obtained non-invasively and analysed rapidly and relatively cheaply. Here the potential use of circulating miRNAs to detect metastasis in discussed and the current barriers to their progression to the clinic.

Generalized monotone incremental forward stagewise method for modeling count data: application predicting micronuclei frequency

The cytokinesis-block micronucleus (CBMN) assay can be used to quantify micronucleus (MN) formation, the outcome measured being MN frequency. MN frequency has been shown to be both an accurate measure of chromosomal instability/DNA damage and a risk factor for cancer. Similarly, the Agilent 4×44k human oligonucleotide microarray can be used to quantify gene expression changes. Despite the existence of accepted methodologies to quantify both MN frequency and gene expression, very little is known about the association between the two. In modeling our count outcome (MN frequency) using gene expression levels from the high-throughput assay as our predictor variables, there are many more variables than observations. Hence, we extended the generalized monotone incremental forward stagewise method for predicting a count outcome for high-dimensional feature settings.

Meta-analysis of the differentially expressed breast cancer-related microRNA expression profiles

MicroRNAs (miRNAs), as non-coding RNA molecules, play an important role in regulating gene expression in cancer development. Meta-analysis was used to screen overlapping differentially expressed miRNAs (DEmiRNAs) in three studies. The miRanda was used to identify target genes related to overlapping DEmiRNAs. These Gene Ontology (GO) and Encyclopaedia of Genes and Genomes (KEGG) database were applied to further predict the function of these target genes. As a result, we obtained seven overlapping miRNAs and six significantly over-represented GO terms closely related to breast cancer. After KEGG pathways analysis, a total of seven key target genes were involved in the Wnt signalling pathway (p = 0.0002). Our findings from this study suggest that the altered levels of miRNAs might have great potential to serve as novel, non-invasive biomarkers for early detection of breast cancer.

Incidence and prediction of invasive disease and nodal metastasis in preoperatively diagnosed ductal carcinoma in situ

For breast cancer patients with a preoperative diagnosis of ductal carcinoma in situ (DCIS), sentinel lymph node (SN) biopsy has been proposed as an axillary staging procedure in selected patients with a higher likelihood of having occult invasive lesions. With detailed histological examination of primary tumors and molecular whole-node analysis of SNs, we aimed to validate whether this selective application accurately identifies patients with SN metastasis. The subjects were 336 patients with a preoperative needle-biopsy diagnosis of DCIS who underwent SN biopsy using the one-step nucleic acid amplification assay in the period 2009–2011. The incidence and preoperative predictors of upstaging to invasive disease on final pathology and SN metastasis, and their correlation, were investigated. Of the 336 patients, 113 (33.6%) had invasive disease, and 6 (1.8%) and 17 (5.0%) had macro- and micrometastasis in axillary nodes respectively. Of the 113 patients with invasive disease, 4 (3.5%) and 9 (8.0%) had macro- and micrometastasis. Predictors of invasive disease included palpability, mammographic mass, and calcifications (spread >20 mm), and intraductal solid structure, but no predictor was found for SN metastasis. Therefore, even though occult invasive disease was found at final pathology, most of the patients had no metastasis or only micrometastasis in axillary nodes. Predictors of invasive disease and SN metastasis were not completely consistent, so the selective SN biopsy for patients with a higher risk of invasive disease may not accurately identify those with SN metastasis. More accurate application of SN biopsy is required for patients with a preoperative diagnosis of DCIS.

Identification of distinct miRNA target regulation between breast cancer molecular subtypes using AGO2-PAR-CLIP and patient datasets

BACKGROUND

Various microRNAs (miRNAs) are up- or downregulated in tumors. However, the repression of cognate miRNA targets responsible for the phenotypic effects of this dysregulation in patients remains largely unexplored. To define miRNA targets and associated pathways, together with their relationship to outcome in breast cancer, we integrated patient-paired miRNA-mRNA expression data with a set of validated miRNA targets and pathway inference.

RESULTS

To generate a biochemically-validated set of miRNA-binding sites, we performed argonaute-2 photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (AGO2-PAR-CLIP) in MCF7 cells. We then defined putative miRNA-target interactions using a computational model, which ranked and selected additional TargetScan-predicted interactions based on features of our AGO2-PAR-CLIP binding-site data. We subselected modeled interactions according to the abundance of their constituent miRNA and mRNA transcripts in tumors, and we took advantage of the variability of miRNA expression within molecular subtypes to detect miRNA repression. Interestingly, our data suggest that miRNA families control subtype-specific pathways; for example, miR-17, miR-19a, miR-25, and miR-200b show high miRNA regulatory activity in the triple-negative, basal-like subtype, whereas miR-22 and miR-24 do so in the HER2 subtype. An independent dataset validated our findings for miR-17 and miR-25, and showed a correlation between the expression levels of miR-182 targets and overall patient survival. Pathway analysis associated miR-17, miR-19a, and miR-200b with leukocyte transendothelial migration.

CONCLUSIONS

We combined PAR-CLIP data with patient expression data to predict regulatory miRNAs, revealing potential therapeutic targets and prognostic markers in breast cancer.

Hide and seek: tell-tale signs of breast cancer lurking in the blood

Breast cancer treatment is improving due to the introduction of new drugs, guided by molecular testing of the primary tumour for mutations/oncogenic drivers (e.g. HER2 gene amplification). However, tumour tissue is not always available for molecular analysis, intra-tumoural heterogeneity is common and the "cancer genome" is known to evolve with time, particularly following treatment as resistance develops. After resection, those patients with only residual micrometastases are likely to be cured but those with radiologically detectable overt disease are not. Thus, the discovery of blood test(s) that could (1) alert clinicians to early primary or recurrent disease and (2) monitor response to treatment could impact significantly on mortality. Towards this, we and others have focused on molecular profiling of circulating nucleic acids isolated from plasma, both cell-free DNA (cfDNA) and microRNAs, and the relationship of these to circulating tumour cells (CTCs). This review considers the utility of each as circulating biomarkers in breast cancer with particular emphasis on the bioinformatic tools available to support molecular profiling.

Prediction of heterogeneous differential genes by detecting outliers to a Gaussian tight cluster

Background

Heterogeneously and differentially expressed genes (hDEG) are a common phenomenon due to bio-logical diversity. A hDEG is often observed in gene expression experiments (with two experimental conditions) where it is highly expressed in a few experimental samples, or in drug trial experiments for cancer studies with drug resistance heterogeneity among the disease group. These highly expressed samples are called outliers. Accurate detection of outliers among hDEGs is then desirable for dis- ease diagnosis and effective drug design. The standard approach for detecting hDEGs is to choose the appropriate subset of outliers to represent the experimental group. However, existing methods typically overlook hDEGs with very few outliers.

Results

We present in this paper a simple algorithm for detecting hDEGs by sequentially testing for potential outliers with respect to a tight cluster of non- outliers, among an ordered subset of the experimental samples. This avoids making any restrictive assumptions about how the outliers are distributed. We use simulated and real data to illustrate that the proposed algorithm achieves a good separation between the tight cluster of low expressions and the outliers for hDEGs.

Conclusions

The proposed algorithm assesses each potential outlier in relation to the cluster of potential outliers without making explicit assumptions about the outlier distribution. Simulated examples and and breast cancer data sets are used to illustrate the suitability of the proposed algorithm for identifying hDEGs with small numbers of outliers.

Amplification and high-level expression of heat shock protein 90 marks aggressive phenotypes of human epidermal growth factor receptor 2 negative breast cancer

Introduction

Although human epidermal growth factor receptor 2 (HER2) positive or estrogen receptor (ER) positive breast cancers are treated with clinically validated anti-HER2 or anti-estrogen therapies, intrinsic and acquired resistance to these therapies appears in a substantial proportion of breast cancer patients and new therapies are needed. Identification of additional molecular factors, especially those characterized by aggressive behavior and poor prognosis, could prioritize interventional opportunities to improve the diagnosis and treatment of breast cancer.

Methods

We compiled a collection of 4,010 breast tumor gene expression data derived from 23 datasets that have been posted on the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. We performed a genome-scale survival analysis using Cox-regression survival analyses, and validated using Kaplan-Meier Estimates survival and Cox Proportional-Hazards Regression survival analyses. We conducted a genome-scale analysis of chromosome alteration using 481 breast cancer samples obtained from The Cancer Genome Atlas (TCGA), from which combined expression and copy number data were available. We assessed the correlation between somatic copy number alterations and gene expression using analysis of variance (ANOVA).

Results

Increased expression of each of the heat shock protein (HSP) 90 isoforms, as well as HSP transcriptional factor 1 (HSF1), was correlated with poor prognosis in different subtypes of breast cancer. High-level expression of HSP90AA1 and HSP90AB1, two cytoplasmic HSP90 isoforms, was driven by chromosome coding region amplifications and were independent factors that led to death from breast cancer among patients with triple-negative (TNBC) and HER2-/ER+ subtypes, respectively. Furthermore, amplification of HSF1 was correlated with higher HSP90AA1 and HSP90AB1 mRNA expression among the breast cancer cells without amplifications of these two genes. A collection of HSP90AA1, HSP90AB1 and HSF1 amplifications defined a subpopulation of breast cancer with up-regulated HSP90 gene expression, and up-regulated HSP90 expression independently elevated the risk of recurrence of TNBC and poor prognosis of HER2-/ER+ breast cancer.

Conclusions

Up-regulated HSP90 mRNA expression represents a confluence of genomic vulnerability that renders HER2 negative breast cancers more aggressive, resulting in poor prognosis. Targeting breast cancer with up-regulated HSP90 may potentially improve the effectiveness of clinical intervention in this disease.

Circulating micro-RNAs as potential blood-based markers for early stage breast cancer detection

Introduction

MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls.

Methods

We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718).

Results

Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202.

Conclusions

MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use.

miRNA expression profiling using Illumina Universal BeadChips

We have developed a highly sensitive, specific, and reproducible method for microRNA (miRNA) expression profiling, using BeadArray technology. This method incorporates an enzyme-assisted specificity step, a solid-phase primer extension to distinguish between members of miRNA families. In addition, a universal PCR is used to amplify all targets prior to array hybridization. Using this method, highly reproducible miRNA expression profiles were generated with 100-200 ng total RNA input. The method has a 3.5-4 log (10(5)-10(9) molecules) dynamic range and is able to detect 1.2- to 1.3-fold differences between samples. Expression profiles generated by this method are highly comparable to those obtained with RT-PCR (R (2) = 0.85-0.90) and direct sequencing (R = 0.87-0.89). This method should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.

Noncanonical TGF-β signaling during mammary tumorigenesis

Breast cancer is a heterogeneous disease comprised of at least five major tumor subtypes that coalesce as the second leading cause of cancer death in women in the United States. Although metastasis clearly represents the most lethal characteristic of breast cancer, our understanding of the molecular mechanisms that govern this event remains inadequate. Clinically, ~30% of breast cancer patients diagnosed with early-stage disease undergo metastatic progression, an event that (a) severely limits treatment options, (b) typically results in chemoresistance and low response rates, and (c) greatly contributes to aggressive relapses and dismal survival rates. Transforming growth factor-β (TGF-β) is a pleiotropic cytokine that regulates all phases of postnatal mammary gland development, including branching morphogenesis, lactation, and involution. TGF-β also plays a prominent role in suppressing mammary tumorigenesis by preventing mammary epithelial cell (MEC) proliferation, or by inducing MEC apoptosis. Genetic and epigenetic events that transpire during mammary tumorigenesis conspire to circumvent the tumor suppressing activities of TGF-β, thereby permitting late-stage breast cancer cells to acquire invasive and metastatic phenotypes in response to TGF-β. Metastatic progression stimulated by TGF-β also relies on its ability to induce epithelial-mesenchymal transition (EMT) and the expansion of chemoresistant breast cancer stem cells. Precisely how this metamorphosis in TGF-β function comes about remains incompletely understood; however, recent findings indicate that the initiation of oncogenic TGF-β activity is contingent upon imbalances between its canonical and noncanonical signaling systems. Here we review the molecular and cellular contributions of noncanonical TGF-β effectors to mammary tumorigenesis and metastatic progression.