Which cyclin E prevails as prognostic marker for breast cancer? Results from a retrospective study involving 635 lymph node-negative breast cancer patients

Repurposing propofol for breast cancer therapy through promoting apoptosis and arresting cell cycle

Breast cancer is the most prevalent cancer among women worldwide, characterized by a high mortality rate and propensity for metastasis. Although surgery is the standard treatment for breast cancer, there is still no effective method to inhibit tumor metastasis and improve the prognosis of patients with breast cancer after surgery. Propofol, one of the most widely used intravenous anesthetics in surgery, has exhibited a positive association with improved survival outcomes in patients with breast cancer post‑surgery. However, the underlying molecular mechanism remains to be elucidated. The present study revealed that triple negative breast cancer cells, MDA‑MB‑231 and 4T1, exposed to propofol exhibited a significant decrease in cell viability. Notably, propofol exhibited minimal cytotoxic effects on HUVECs under the same conditions. Furthermore, propofol significantly inhibited the migration and invasion ability of MDA‑MB‑231 and 4T1 cells. Propofol promoted apoptosis in 4T1 cells through upregulation of Bax and cleaved caspase 3, while downregulating B‑cell lymphoma‑extra large. Concomitantly, propofol induced cell cycle arrest of 4T1 cells by downregulating cyclin E2 and phosphorylated cell division cycle 6. Furthermore, propofol exhibited excellent anticancer efficacy in a 4T1 breast cancer allograft mouse model. The present study sheds light on the potential of propofol as an old medicine with a novel use for breast cancer treatment.

Identification of Novel Diagnostic and Prognostic Gene Signature Biomarkers for Breast Cancer Using Artificial Intelligence and Machine Learning Assisted Transcriptomics Analysis

BACKGROUND

Breast cancer (BC) is one of the most common female cancers. Clinical and histopathological information is collectively used for diagnosis, but is often not precise. We applied machine learning (ML) methods to identify the valuable gene signature model based on differentially expressed genes (DEGs) for BC diagnosis and prognosis.

METHODS

A cohort of 701 samples from 11 GEO BC microarray datasets was used for the identification of significant DEGs. Seven ML methods, including RFECV-LR, RFECV-SVM, LR-L1, SVC-L1, RF, and Extra-Trees were applied for gene reduction and the construction of a diagnostic model for cancer classification. Kaplan-Meier survival analysis was performed for prognostic signature construction. The potential biomarkers were confirmed via qRT-PCR and validated by another set of ML methods including GBDT, XGBoost, AdaBoost, KNN, and MLP.

RESULTS

We identified 355 DEGs and predicted BC-associated pathways, including kinetochore metaphase signaling, PTEN, senescence, and phagosome-formation pathways. A hub of 28 DEGs and a novel diagnostic nine-gene signature (COL10A, S100P, ADAMTS5, WISP1, COMP, CXCL10, LYVE1, COL11A1, and INHBA) were identified using stringent filter conditions. Similarly, a novel prognostic model consisting of eight-gene signatures (CCNE2, NUSAP1, TPX2, S100P, ITM2A, LIFR, TNXA, and ZBTB16) was also identified using disease-free survival and overall survival analysis. Gene signatures were validated by another set of ML methods. Finally, qRT-PCR results confirmed the expression of the identified gene signatures in BC.

CONCLUSION

The ML approach helped construct novel diagnostic and prognostic models based on the expression profiling of BC. The identified nine-gene signature and eight-gene signatures showed excellent potential in BC diagnosis and prognosis, respectively.

Identification of Candidate Genes in Breast Cancer Induced by Estrogen Plus Progestogens Using Bioinformatic Analysis

Menopausal hormone therapy (MHT) was widely used to treat menopause-related symptoms in menopausal women. However, MHT therapies were controversial with the increased risk of breast cancer because of different estrogen and progestogen combinations, and the molecular basis behind this phenomenon is currently not understood. To address this issue, we identified differentially expressed genes (DEGs) between the estrogen plus progestogens treatment (EPT) and estrogen treatment (ET) using the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) data. As a result, a total of 96 upregulated DEGs were first identified. Seven DEGs related to the cell cycle (CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3) were validated by RT-qPCR. Specifically, these seven DEGs were increased in EPT compared to ET (p < 0.05) and had higher expression levels in breast cancer than adjacent normal tissues (p < 0.05). Next, we found that estrogen receptor (ER)-positive breast cancer patients with a higher CNNE2 expression have a shorter overall survival time (p < 0.05), while this effect was not observed in the other six DEGs (p > 0.05). Interestingly, the molecular docking results showed that CCNE2 might bind to 17β-estradiol (−6.791 kcal/mol), progesterone (−6.847 kcal/mol), and medroxyprogesterone acetate (−6.314 kcal/mol) with a relatively strong binding affinity, respectively. Importantly, CNNE2 protein level could be upregulated with EPT and attenuated by estrogen receptor antagonist, acolbifene and had interactions with cancer driver genes (AKT1 and KRAS) and high mutation frequency gene (TP53 and PTEN) in breast cancer patients. In conclusion, the current study showed that CCNE2, CDCA5, RAD51, TCF19, KNTC1, MCM10, and NEIL3 might contribute to EPT-related tumorigenesis in breast cancer, with CCNE2 might be a sensitive risk indicator of breast cancer risk in women using MHT.

Biomarkers for Cyclin-Dependent Kinase 4/6 Inhibitors in the Treatment of Hormone Receptor-Positive/Human Epidermal Growth Factor Receptor 2-Negative Advanced/Metastatic Breast Cancer: Translation to Clinical Practice

PURPOSE

Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have emerged as effective treatments for patients with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) advanced/metastatic breast cancer (mBC). Dedicated research efforts have been undertaken to find predictive biomarkers of response or resistance to these therapies although no molecular biomarkers for mBC have reached the clinic so far. This review aims to summarize and evaluate the performance of biomarkers in predicting progression-free survival in phase II and III clinical trials of CDK4/6 inhibitors in HR+/HER2- mBC.

METHODS

For this narrative review, a structured literature search of PubMed, Embase, and the Cochrane library (CENTRAL) was performed. Phase II or III clinical trials of a CDK4/6 inhibitor in patients with HR+/HER2- mBC reporting on at least one molecular biomarker analysis of progression-free survival were included. Publications and selected conference abstracts were included up until November 2021.

RESULTS

Twenty-two articles reporting biomarker results of 12 clinical trials were included. Retinoblastoma protein status and cyclin E1 mRNA expression were promising baseline biomarkers, whereas PIK3CA circulating tumor DNA ratio on treatment relative to baseline, change in plasma thymidine kinase activity, and circulating tumor cell count were potential dynamic biomarkers of response. A number of biomarkers were unsuccessful, despite a strong mechanistic rationale, and others are still being explored.

CONCLUSION

Our review of clinical trials showed that there are a number of promising biomarkers at baseline and several dynamic biomarkers that might predict response to CDK4/6 inhibitors. Validation of these findings and assessment of clinical utility are crucial to make the final translation to clinical practice. Better understanding of disease heterogeneity and further elucidation of resistance mechanisms could inform future studies of rationally selected biomarkers.

Circulating Exosomal microRNAs as Predictive Biomarkers of Neoadjuvant Chemotherapy Response in Breast Cancer

Background: Neoadjuvant chemotherapy (NACT) is an increasingly used approach for treatment of breast cancer. The pathological complete response (pCR) is considered a good predictor of disease-specific survival. This study investigated whether circulating exosomal microRNAs could predict pCR in breast cancer patients treated with NACT. Method: Plasma samples of 20 breast cancer patients treated with NACT were collected prior to and after the first cycle. RNA sequencing was used to determine microRNA profiling. The Cancer Genome Atlas (TCGA) was used to explore the expression patterns and survivability of the candidate miRNAs, and their potential targets based on the expression levels and copy number variation (CNV) data. Results: Three miRNAs before that NACT (miR-30b, miR-328 and miR-423) predicted pCR in all of the analyzed samples. Upregulation of miR-127 correlated with pCR in triple-negative breast cancer (TNBC). After the first NACT dose, pCR was predicted by exo-miR-141, while miR-34a, exo-miR182, and exo-miR-183 predicted non-pCR. A significant correlation between the candidate miRNAs and the overall survival, subtype, and metastasis in breast cancer, suggesting their potential role as predictive biomarkers of pCR. Conclusions: If the miRNAs identified in this study are validated in a large cohort of patients, they might serve as predictive non-invasive liquid biopsy biomarkers for monitoring pCR to NACT in breast cancer.

Oncogenic and Tumor Suppressive Components of the Cell Cycle in Breast Cancer Progression and Prognosis

Cancer, a disease of inappropriate cell proliferation, is strongly interconnected with the cell cycle. All cancers consist of an abnormal accumulation of neoplastic cells, which are propagated toward uncontrolled cell division and proliferation in response to mitogenic signals. Mitogenic stimuli include genetic and epigenetic changes in cell cycle regulatory genes and other genes which regulate the cell cycle. This suggests that multiple, distinct pathways of genetic alterations lead to cancer development. Products of both oncogenes (including cyclin-dependent kinase (CDKs) and cyclins) and tumor suppressor genes (including cyclin-dependent kinase inhibitors) regulate cell cycle machinery and promote or suppress cell cycle progression, respectively. The identification of cyclins and CDKs help to explain and understand the molecular mechanisms of cell cycle machinery. During breast cancer tumorigenesis, cyclins A, B, C, D1, and E; cyclin-dependent kinase (CDKs); and CDK-inhibitor proteins p16, p21, p27, and p53 are known to play significant roles in cell cycle control and are tightly regulated in normal breast epithelial cells. Following mitogenic stimuli, these components are deregulated, which promotes neoplastic transformation of breast epithelial cells. Multiple studies implicate the roles of both types of components-oncogenic CDKs and cyclins, along with tumor-suppressing cyclin-dependent inhibitors-in breast cancer initiation and progression. Numerous clinical studies have confirmed that there is a prognostic significance for screening for these described components, regarding patient outcomes and their responses to therapy. The aim of this review article is to summarize the roles of oncogenic and tumor-suppressive components of the cell cycle in breast cancer progression and prognosis.

Long Non-coding RNA SENP3-EIF4A1 Functions as a Sponge of miR-195-5p to Drive Triple-Negative Breast Cancer Progress by Overexpressing CCNE1

Triple-negative breast cancer (TNBC) has high malignancy and limited treatment, so novel molecular therapeutic targets are urgently needed. Cyclin E1 (CCNE1) promotes progression in breast cancer, but its role and inherent mechanisms in TNBC are yet to be elucidated. Competing endogenous RNA (ceRNA) may be a potential mechanism. CCNE1 was selected though bioinformatics and clinical samples, and cell lines were utilized to verify CCNE1 expression by qRT-PCR and western blot. Predicting tools provided potential miR-195-5p and SENP3-EIF4A1 and tested from multilevel. Functional experiments were conducted in vitro and in vivo. Luciferase reporter assay and RNA immunoprecipitation experiments were implemented to ensure the interaction between miR-195-5p and SENP3-EIF4A1/CCNE1 in TNBC. Bioinformatics found DNA hypermethylation of miR-195-5p and preliminarily verified. Mechanistically, SENP3-EIF4A1-miR-195-5p-associated ceRNA could drive TNBC progress though regulating CCNE1. DNA hypermethylation of miR-195-5p might be another reason. In summary, SENP3-EIF4A1-miR-195-5p-CCNE1 axis promotes TNBC progress and may contribute to the novel diagnosis and treatment of TNBC.

Antibiotic tigecycline inhibits cell proliferation, migration and invasion via down-regulating CCNE2 in pancreatic ductal adenocarcinoma

Recently, many researches have reported that antibiotic tigecycline has significant effect on cancer treatment. However, biomedical functions and molecular mechanisms of tigecycline in human pancreatic ductal adenocarcinoma (PDAC) remain unclear. In the current study, we tried to assess the effect of tigecycline in PDAC cells. AsPC‐1 and HPAC cells were treated with indicated concentrations of tigecycline for indicated time, and then, MTT, BrdU and soft agar assay were used to test cell proliferation. The effect of tigecycline on cell cycle and cellular apoptosis was tested by cytometry. Migration and invasion were detected by wound healing assay and transwell migration/invasion assay. Expressions of cell cycle‐related and migration/invasion‐related protein were determined by using Western blot. The results revealed that tigecycline observably suppressed cell proliferation by inducing cell cycle arrest at G0/G1 phase and blocked cell migration/invasion via holding back the epithelial‐mesenchymal transition (EMT) process in PDAC. In addition, tigecycline also remarkably blocked tumorigenecity in vivo. Furthermore, the effects of tigecycline alone or combined with gemcitabine in vitro or on PDAC xenografts were also performed. The results showed that tigecycline enhanced the chemosensitivity of PDAC cells to gemcitabine. Interestingly, we found CCNE2 expression was declined distinctly after tigecycline treatment. Then, CCNE2 was overexpressed to rescue tigecycline‐induced effect. The results showed that CCNE2 overexpression significantly rescued tigecycline‐inhibited cell proliferation and migration/invasion. Collectively, we showed that tigecycline inhibits cell proliferation, migration and invasion via down‐regulating CCNE2, and tigecycline might be used as a potential drug for PDAC treatment alone or combined with gemcitabine.

miR-3687 Overexpression Promotes Bladder Cancer Cell Growth by Inhibiting the Negative Effect of FOXP1 on Cyclin E2 Transcription

Cyclin E2, a member of the cyclin family, is a key cell cycle-related protein. This protein plays essential roles in cancer progression, and, as such, an inhibitor of cyclin E2 has been approved to treat several types of cancers. Even so, mechanisms underlying how to regulate cyclin E2 expression in cancer remain largely unknown. In the current study, miR-3687 was upregulated in clinical bladder cancer (BC) tumor tissues, The Cancer Genome Atlas (TCGA) database, and human BC cell lines. Inhibition of miR-3687 expression significantly reduced human BC cell proliferation in vitro and tumor growth in vivo, which coincided with the induction of G₀/G₁ cell cycle arrest and downregulation of cyclin E2 protein expression. Interestingly, overexpression of cyclin E2 reversed the inhibition of BC proliferation induced by miR-3687. Mechanistic studies suggested that miR-3687 binds to the 3' UTR of foxp1 mRNA, downregulates FOXP1 protein expression, and in turn promotes the transcription of cyclin E2, thereby promoting the growth of BC cells. Collectively, the current study not only establishes a novel regulatory axis of miR-3687/FOXP1 regarding regulation of cyclin E2 expression in BC cells, but also provides strong suggestive evidence that miR-3687 and FOXP1 may be promising targets in therapeutic strategies for human BC.

Prognostic Values of CCNE1 Amplification and Overexpression in Cancer Patients: A Systematic Review and Meta-analysis

A number of studies revealed that CCNE1 copy number amplification and overexpression (on mRNA or protein expression level) were associated with prognosis of diverse cancers, however, the results were inconsistent among studies. So we conducted this systematic review and meta-analysis to investigate the prognostic values of CCNE1 amplification and overexpression in cancer patients. PubMed, Cochrane library, Embase, CNKI and WanFang database (last update by February 15, 2018) were searched for literatures. A total of 20 studies were included and 5 survival assessment parameters were measured in this study, which included overall survival (OS), progression free survival (PFS), recurrence free survival (RFS), cancer specific survival (CSS) and distant metastasis free survival (DMFS). Pooled analyses showed that CCNE1 amplification might predict poor OS (HR=1.59, 95% CI: 1.05-2.40, p=0.027) rather than PFS (HR=1.49, 95% CI: 0.83-2.67, p=0.177) and RFS (HR=0.982, 95% CI: 0.2376-4.059, p=0.9801) in various cancers; CCNE1 overexpression significantly correlated with poor OS (HR=1.52, 95% CI: 1.05-2.20, p=0.027), PFS (HR=1.20, 95% CI: 1.07-1.34, p=0.001) and DMFS (HR=1.62, 95% CI: 1.09-2.40, p=0.017) rather than RFS (HR=1.68, 95% CI: 0.81-3.50, p=0.164) and CSS (HR=1.54, 95% CI: 0.74-3.18, p=0.246). On the whole, these results indicated CCNE1 amplification and overexpression were associated with poor survival of patients with cancer, suggesting that CCNE1 might be an effective prognostic signature for cancer patients.

Molecular Profiling and Significance of Circulating Tumor Cell Based Genetic Signatures

Cancer kills by metastasizing beyond the primary site. Early detection, surgical intervention and other treatments have improved the survival rates of patients with cancer, however, once metastasis occurs, responses to conventional therapies become significantly less effective, and this remains the leading cause of death. Circulating tumor cells (CTCs) are tumor cells that have preferentially disseminated from the primary tumor mass into the hematological system, and are en route to favorable distant sites where if they survive, can develop into metastases. They may be the earliest detectable cells with metastatic ability, and are gaining increasing attention because of their prognostic value in many types of cancers including breast, prostate, colon and lung. Recent technological advances have removed barriers that previously hindered the detection and isolation of these rare cells from blood, and have exponentially improved the genetic resolution at which we can characterize signatures that define CTCs. Some of the most significant observations from such examinations are described here. Firstly, aberrations that were thought to be unique to CTCs are detected at subclonal frequencies within primary tumors with measurable heterogeneity, indicating pre-existing genetic signatures for metastasis. Secondly, these subclonal events are enriched in CTCs and metastases, pointing towards the selection of a more 'fit' component of tumor cells with survival advantages. Lastly, this component of cancer cells may also be the chemoresistant portion that escapes systemic treatment, or acquires resistance during progression of the disease. The future of cancer management may include a standardized method of measuring intratumor heterogeneity of the primary as well as matched CTCs. This will help identify and target rare aberrations within primary tumors that make them more adept to disseminate, and also to monitor the development of treatment resistant subclones as cancer progresses.

Inhibition of E2F1 activity and cell cycle progression by arsenic via retinoblastoma protein

The regulation of cell cycle progression by steroid hormones and growth factors is important for maintaining normal cellular processes including development and cell proliferation. Deregulated progression through the G1/S and G2/M cell cycle transitions can lead to uncontrolled cell proliferation and cancer. The transcription factor E2F1, a key cell cycle regulator, targets genes encoding proteins that regulate cell cycle progression through the G1/S transition as well as proteins important in DNA repair and apoptosis. E2F1 expression and activity is inhibited by inorganic arsenic (iAs) that has a dual role as a cancer therapeutic and as a toxin that leads to diseases including cancer. An understanding of what underlies this dichotomy will contribute to understanding how to use iAs as a more effective therapeutic and also how to treat cancers that iAs promotes. Here, we show that quiescent breast adenocarcinoma MCF-7 cells treated with 17-β estradiol (E2) progress through the cell cycle, but few cells treated with E2 + iAs progress from G1 into S-phase due to a block in cell cycle progression. Our data support a model in which iAs inhibits the dissociation of E2F1 from the tumor suppressor, retinoblastoma protein (pRB) due to changes in pRB phosphorylation which leads to decreased E2F1 transcriptional activity. These findings present an explanation for how iAs can disrupt cell cycle progression through E2F1-pRB and has implications for how iAs acts as a cancer therapeutic as well as how it may promote tumorigenesis through decreased DNA repair.

Down-regulation of SOSTDC1 promotes thyroid cancer cell proliferation via regulating cyclin A2 and cyclin E2

Sclerostin domain containing protein 1 (SOSTDC1) is down-regulated and acts as a tumor suppressor in some kinds of cancers. However, the expression pattern and biological significance of SOSTDC1 in thyroid cancer are largely unknown. We demonstrated that SOSTDC1 was significantly down-regulated in thyroid cancer. Ectopic over-expression of SOSTDC1 inhibited proliferation and induced G1/S arrest in thyroid cancer cells. Moreover, SOSTDC1 over-expression suppressed the growth of tumor xenografts in nude mice. We also found that elevated SOSTDC1 led to inhibition of cyclin A2 and cyclin E2. Together, our results demonstrate that SOSTDC1 is down-regulated in thyroid cancer and might be a potential therapeutic target in the treatment of thyroid cancer.

The importance of p53 pathway genetics in inherited and somatic cancer genomes

Decades of research have shown that mutations in the p53 stress response pathway affect the incidence of diverse cancers more than mutations in other pathways. However, most evidence is limited to somatic mutations and rare inherited mutations. Using newly abundant genomic data, we demonstrate that commonly inherited genetic variants in the p53 pathway also affect the incidence of a broad range of cancers more than variants in other pathways. The cancer-associated single nucleotide polymorphisms (SNPs) of the p53 pathway have strikingly similar genetic characteristics to well-studied p53 pathway cancer-causing somatic mutations. Our results enable insights into p53-mediated tumour suppression in humans and into p53 pathway-based cancer surveillance and treatment strategies.

Novel Molecular Markers for Breast Cancer

The use of molecular biomarkers assures that breast cancer (BC) patients receive optimal treatment. Established biomarkers, such as estrogen receptor, progesterone receptor, HER2, and Ki67, have been playing significant roles in the subcategorization of BC to predict the prognosis and decide the specific therapy to each patient. Antihormonal therapy using 4-hydroxytamoxifen or aromatase inhibitors have been employed in patients whose tumor cells express hormone receptors, while monoclonal antibody to HER2 has been administered to HER2-positive BCs. Although new therapeutic agents have been developed in the past few decades, many patients still die of the disease due to relapse; thus, novel molecular markers that predict therapeutic failure and those that can be targets for specific therapy are expected. We have chosen four of such molecules by reviewing recent publications, which are cyclin E, B-Myb, Twist, and DMP1β. The oncogenicity of these molecules has been demonstrated in vivo and/or in vitro through studies using transgenic mice or siRNAs, and their expressions have been shown to be associated with shortened overall or disease-free survival of BC patients. The former three molecules have been shown to accelerate epithelial-mesenchymal transition that is often associated with cancer stem cell-ness and metastasis; all these four can be novel therapeutic targets as well. Thus, large prospective studies employing immunohistochemistry will be needed to establish the predictive values of these molecules in patients with BC.

Cyclin E amplification, over-expression, and relapse-free survival in HER-2-positive primary breast cancer

Cyclin E is a well-characterized cell cycle regulator and an amplified oncogene in breast cancer. Over-expression of cyclin E has generally been associated with poor survival. Recent studies have shown an interaction between HER-2 (ERBB2) and cyclin E, but the exact mechanism is unknown. Interestingly, cyclin E over-expression has been associated with trastuzumab resistance. We studied cyclin E over-expression, CCNE1 amplification, and relapse-free survival in HER-2-positive primary breast cancers treated with and without trastuzumab therapy. Formalin-fixed paraffin-embedded tissue samples from 202 HER-2-positive breast carcinomas were studied. Expression levels of cyclin E and proliferation marker Ki-67 were determined using immunohistochemistry. Chromogenic in situ hybridization (CISH) with a gene-specific bacterial artificial chromosome (BAC) probe was used to analyze presence of CCNE1 amplification. Majority of HER-2-positive breast carcinomas exhibited nuclear staining for cyclin E protein. Cyclin E was highly expressed (≥50 % cells) in 37 % of cases. Incidence of CCNE1 amplification (≥6 gene copies/cell or clusters) was 8 %. Cyclin E amplification and over-expression were strongly associated with each other, grade, hormone receptors, and Ki-67. Neither high cyclin E expression nor CCNE1 amplification was associated with relapse-free survival (RFS) irrespective of short-term (9-week regimen) adjuvant trastuzumab therapy. These results confirm cyclin E and HER-2 gene co-amplification in a fraction of HER-2-positive breast cancers. Cyclin E is frequently over-expressed but appears to have limited value as a prognostic or predictive factor in HER-2-positive breast cancer regardless of trastuzumab therapy.

Large-scale RNA-Seq Transcriptome Analysis of 4043 Cancers and 548 Normal Tissue Controls across 12 TCGA Cancer Types

The Cancer Genome Atlas (TCGA) has accrued RNA-Seq-based transcriptome data for more than 4000 cancer tissue samples across 12 cancer types, translating these data into biological insights remains a major challenge. We analyzed and compared the transcriptomes of 4043 cancer and 548 normal tissue samples from 21 TCGA cancer types, and created a comprehensive catalog of gene expression alterations for each cancer type. By clustering genes into co-regulated gene sets, we identified seven cross-cancer gene signatures altered across a diverse panel of primary human cancer samples. A 14-gene signature extracted from these seven cross-cancer gene signatures precisely differentiated between cancerous and normal samples, the predictive accuracy of leave-one-out cross-validation (LOOCV) were 92.04%, 96.23%, 91.76%, 90.05%, 88.17%, 94.29%, and 99.10% for BLCA, BRCA, COAD, HNSC, LIHC, LUAD, and LUSC, respectively. A lung cancer-specific gene signature, containing SFTPA1 and SFTPA2 genes, accurately distinguished lung cancer from other cancer samples, the predictive accuracy of LOOCV for TCGA and GSE5364 data were 95.68% and 100%, respectively. These gene signatures provide rich insights into the transcriptional programs that trigger tumorigenesis and metastasis, and many genes in the signature gene panels may be of significant value to the diagnosis and treatment of cancer.

Identification of sample-specific regulations using integrative network level analysis

Background

Histologically similar tumors even from the same anatomical position may still show high variability at molecular level hindering analysis of genome-wide data. Leveling the analysis to a gene regulatory network instead of focusing on single genes has been suggested to overcome the heterogeneity issue although the majority of the network methods require large datasets. Network methods that are able to function at a single sample level are needed to overcome the heterogeneity and sample size issues.

Methods

We present a novel network method, Differentially Expressed Regulation Analysis (DERA) that integrates expression data to biological network information at a single sample level. The sample-specific networks are subsequently used to discover samples with similar molecular functions by identification of regulations that are shared between samples or are specific for a subgroup.

Results

We applied DERA to identify key regulations in triple negative breast cancer (TNBC), which is characterized by lack of estrogen receptor, progesterone receptor and HER2 expression and has poorer prognosis than the other breast cancer subtypes. DERA identified 110 core regulations consisting of 28 disconnected subnetworks for TNBC. These subnetworks are related to oncogenic activity, proliferation, cancer survival, invasiveness and metastasis. Our analysis further revealed 31 regulations specific for TNBC as compared to the other breast cancer subtypes and thus form a basis for understanding TNBC. We also applied DERA to high-grade serous ovarian cancer (HGS-OvCa) data and identified several common regulations between HGS-OvCa and TNBC. The performance of DERA was compared to two pathway analysis methods GSEA and SPIA and our results shows better reproducibility and higher sensitivity in a small sample set.

Conclusions

We present a novel method called DERA to identify subnetworks that are similarly active for a group of samples. DERA was applied to breast cancer and ovarian cancer data showing our method is able to identify reliable and potentially important regulations with high reproducibility. R package is available at http://csbi.ltdk.helsinki.fi/pub/czliu/DERA/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1265-2) contains supplementary material, which is available to authorized users.

MicroRNA-16 modulates HuR regulation of cyclin E1 in breast cancer cells

RNA binding protein (RBPs) and microRNAs (miRNAs or miRs) are post-transcriptional regulators of gene expression that are implicated in development of cancers. Although their individual roles have been studied, the crosstalk between RBPs and miRNAs is under intense investigation. Here, we show that in breast cancer cells, cyclin E1 upregulation by the RBP HuR is through specific binding to regions in the cyclin E1 mRNA 3' untranslated region (3'UTR) containing U-rich elements. Similarly, miR-16 represses cyclin E1, dependent on its cognate binding sites in the cyclin E1 3'UTR. Evidence in the literature indicates that HuR can regulate miRNA expression and recruit or dissociate RNA-induced silencing complexes (RISC). Despite this, miR-16 and HuR do not affect the other’s expression level or binding to the cyclin E1 3'UTR. While HuR overexpression partially blocks miR-16 repression of a reporter mRNA containing the cyclin E1 3'UTR, it does not block miR-16 repression of endogenous cyclin E1 mRNA. In contrast, miR-16 blocks HuR-mediated upregulation of cyclin E1. Overall our results suggest that miR-16 can override HuR upregulation of cyclin E1 without affecting HuR expression or association with the cyclin E1 mRNA.

Identification of genomic signatures in circulating tumor cells from breast cancer

Levels of circulating tumor cells (CTCs) in blood have prognostic value in early and metastatic breast cancer. CTCs also show varying degrees of concordance with molecular markers of primary tumors they originate from. It is expected that individual cells reflect the heterogeneity and evolution of tumor cells as they acquire new functions and differential responses to chemotherapy. However, a degree of commonality is also plausible, highlighting alterations that allow tumor cells to perform CTC-defining activities such as invasion and intravasation. Using a matched tumor-normal approach, we performed high-resolution copy number profiling of CTCs from breast cancer to identify occult changes occurring during progression to metastasis. We identified a signature of recurrent gain in CTCs, consisting of 90 minimal common regions (MCRs) of copy number gain. These were predominantly found across chromosome 19 and were identified at low frequencies (3-4%) in 787 primary breast carcinomas examined. CTC genomic signatures clustered into two groups independent of subtype: a dormancy-related signature with 16 MCRs (AKT2, PTEN, CADM2); and a tumor-aggressiveness related signature with 358 MCRs (ANGPTL4, BSG, MIR-373). There were two MCRs in common between the groups on 19q13 and 21q21, containing genes involved in resistance to anoikis, TGFβ-signaling and metastasis (TFF3, LTBP4, NUMBL). Furthermore, a region harboring the ERBB2 gene was gained in a majority of patients. Regions 20q13 and 15q24 were associated with distant metastasis. The distinctiveness of CTC signatures highlights cell populations with different functional or metastatic potential. Such novel targets could help to specifically identify and block dissemination.

Global gene expression profiling identifies ALDH2, CCNE1 and SMAD3 as potential prognostic markers in upper tract urothelial carcinoma

Background

Current knowledge about the molecular properties and prognostic markers of upper tract urothelial carcinoma (UTUC) is sparse and often based on bladder urothelial carcinoma (UC), which is thought to share common risk factors with UTUC. However, studies have suggested that differences exist regarding tumor behavior and molecular biology of these cancers, comprehensive investigations are needed to guide the clinical management of UTUC. In recent years, massively parallel sequencing has allowed insights into the biology of many cancers, and molecular prognostic markers based on this approach are rapidly emerging. The goal of this study was to characterize the gene expression patterns of UTUC using massively parallel sequencing, and identify potential molecular markers for prognosis in patients with UTUC.

Methods

We compared the genome-wide mRNA expression profile of cancer and matched normal tissues from 10 patients with UTUC to identify significantly deregulated genes. We also examined the protein levels of prognostic marker candidates in 103 patients with UTUC, and tested the association of these markers with overall survival using Kaplan-Meier model and Cox regression.

Results

Functional enrichment of significantly deregulated genes revealed that expression patterns of UTUC were characterized by disorders of cell proliferation and metabolism. And we also compared the expression profile of UTUC with that of bladder UC. Our results highlighted both shared (e.g. disorders of cell cycling and growth signal transduction) and tumor-specific (e.g. abnormal metabolism in UTUC and disruptions of adhesion pathways in bladder UC) features of these two cancers. Importantly, we identified that low protein expression of ALDH2 while high CCNE1 and SMAD3 were significantly associated with increased depth (*P <0.05) and lower overall survival (***P <0.0001) in an independent set of 103 patients. Multivariate Cox regression revealed that all these three genes were independent prognostic indicators in patients with UTUC (***P <0.001).

Conclusions

In conclusion, our study characterized the comprehensive expression profile of UTUC and highlighted both commons and differences in expression patterns between UTUC and bladder UC. And we, for the first time, revealed that ALDH2, CCNE1 and SMAD3 are associated with prognosis in patients with UTUC.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2407-14-836) contains supplementary material, which is available to authorized users.

Refinement of breast cancer risk prediction with concordant leading edge subsets from prognostic gene signatures

Several prognostic signatures have been identified for breast cancer. However, these signatures vary extensively in their gene compositions, and the poor concordance of the risk groups defined by the prognostic signatures hinders their clinical applicability. Breast cancer risk prediction was refined with a novel approach to finding concordant genes from leading edge analysis of prognostic signatures. Each signature was split into two gene sets, which contained either up-regulated or down-regulated genes, and leading edge analysis was performed within each array study for all up-/down-regulated gene sets of the same signature from all training datasets. Consensus of leading edge subsets among all training microarrays was used to synthesize a predictive model, which was then tested in independent studies by partial least squares regression. Only a small portion of six prognostic signatures (Amsterdam, Rotterdam, Genomic Grade Index, Recurrence Score, and Hu306 and PAM50 of intrinsic subtypes) was significantly enriched in the leading edge analysis in five training datasets (n = 2,380), and that the concordant leading edge subsets (43 genes) could identify the core signature genes that account for the enrichment signals providing prognostic power across all assayed samples. The proposed concordant leading edge algorithm was able to discriminate high-risk from low-risk patients in terms of relapse-free or distant metastasis-free survival in all training samples (hazard ratios: 1.84-2.20) and in three out of four independent studies (hazard ratios: 3.91-8.31). In some studies, the concordant leading edge subset remained a significant prognostic factor independent of clinical ER, HER2, and lymph node status. The present study provides a statistical framework for identifying core consensus across microarray studies with leading edge analysis, and a breast cancer risk predictive model was established.

CCAT2, a novel long non-coding RNA in breast cancer: expression study and clinical correlations

The clinical outcome of BC patients receiving the same treatment is known to vary considerably and thus, there is a compelling need to identify novel biomarkers that can select the patients that would benefit most from a given therapy and can predict the clinical outcome. The aim of this study was to determine the prognostic value of CCAT2, a novel long ncRNA recently characterized by our group and overlapping SNP rs6983267, in BC patients. We first evaluated by RT-qPCR and ISH the expression of CCAT2 in normal breast tissue and BC tissue and further analyzed CCAT2 expression in an independent set of 997 primary BC with regard to clinical, histological, pathological and other biological factors. Also, we explored the possibility of CCAT2 adding to the prognostic value of multivariate models that already included the traditional prognostic factors. Finally, we identified in in vitro models the impact of CCAT2 expression and SNP rs6983267 genotype on cell migration and chemoresistance. Our results revealed that although overexpressed in BCs in two out of three sets of patients, and having the highest expression in lymph node negative (LNN) disease, CCAT2 expression levels are informative solely for a subgroup of BC patients, namely for patients with LNP disease that have received adjuvant CMF chemotherapy. For this subgroup high levels of CCAT2 suggest the patients will not benefit from CMF containing adjuvant chemotherapy (shorter MFS and OS). Additionally, we found that CCAT2 upregulates cell migration and downregulates chemosensitivity to 5'FU in a rs6983267-independent manner.

Mechanisms associated with resistance to tamoxifen in estrogen receptor-positive breast cancer (review)

Anti-estrogens such as tamoxifen are widely used in the clinic to treat estrogen receptor-positive breast tumors. Patients with estrogen receptor-positive breast cancer initially respond to treatment with anti-hormonal agents such as tamoxifen, but remissions are often followed by the acquisition of resistance and, ultimately, disease relapse. The development of a rationale for the effective treatment of tamoxifen-resistant breast cancer requires an understanding of the complex signal transduction mechanisms. In the present study, we explored some mechanisms associated with resistance to tamoxifen, such as pharmacologic mechanisms, loss or modification in estrogen receptor expression, alterations in co-regulatory proteins and the regulation of the different signaling pathways that participate in different cellular processes such as survival, proliferation, stress, cell cycle, inhibition of apoptosis regulated by the Bcl-2 family, autophagy, altered expression of microRNA, and signaling pathways that regulate the epithelial-mesenchymal transition in the tumor microenvironment. Delineation of the molecular mechanisms underlying the development of resistance may aid in the development of treatment strategies to enhance response and compromise resistance.

Network-based inference framework for identifying cancer genes from gene expression data

Great efforts have been devoted to alleviate uncertainty of detected cancer genes as accurate identification of oncogenes is of tremendous significance and helps unravel the biological behavior of tumors. In this paper, we present a differential network-based framework to detect biologically meaningful cancer-related genes. Firstly, a gene regulatory network construction algorithm is proposed, in which a boosting regression based on likelihood score and informative prior is employed for improving accuracy of identification. Secondly, with the algorithm, two gene regulatory networks are constructed from case and control samples independently. Thirdly, by subtracting the two networks, a differential-network model is obtained and then used to rank differentially expressed hub genes for identification of cancer biomarkers. Compared with two existing gene-based methods (t-test and lasso), the method has a significant improvement in accuracy both on synthetic datasets and two real breast cancer datasets. Furthermore, identified six genes (TSPYL5, CD55, CCNE2, DCK, BBC3, and MUC1) susceptible to breast cancer were verified through the literature mining, GO analysis, and pathway functional enrichment analysis. Among these oncogenes, TSPYL5 and CCNE2 have been already known as prognostic biomarkers in breast cancer, CD55 has been suspected of playing an important role in breast cancer prognosis from literature evidence, and other three genes are newly discovered breast cancer biomarkers. More generally, the differential-network schema can be extended to other complex diseases for detection of disease associated-genes.

Prognostic value of cyclin E expression in breast cancer: a meta-analysis

Cyclin E is an important regulator of cell cycle progression. Various studies examined the relationship between cyclin E overexpression with the clinical outcome in patients with breast cancer but yielded conflicting results. Electronic databases updated to May 2013 were searched to find relevant studies. A meta-analysis was conducted with eligible studies which quantitatively evaluated the relationship between cyclin E overexpression and survival of patients with breast cancer. Survival data were aggregated and quantitatively analyzed. We conducted a final analysis of 7,759 patients from 23 eligible studies and evaluated the correlation between cyclin E overexpression and survival in patients with breast cancer. Combined hazard ratios suggested that cyclin E overexpression had an unfavorable impact on overall survival (OS) (hazard ratio (HR) = 1.30, 95% confidence interval (CI), 1.12-1.49) and breast cancer-specific survival (BCSS) (HR = 1.48, 95% CI, 1.03-1.93), but not disease-free survival (HR = 1.11; 95% CI, 0.96-1.27) in patients with breast cancer. Significantly, risks were found among stage I-II breast cancer for (HR = 1.75; 95% CI, 1.30-2.19). Cyclin E overexpression is associated with poor OS and BCSS in breast cancer.

Luteolin sensitises drug-resistant human breast cancer cells to tamoxifen via the inhibition of cyclin E2 expression

Luteolin is a flavonoid that has been identified in many plant tissues and exhibits chemopreventive or chemosensitising properties against human breast cancer. However, the oncogenic molecules in human breast cancer cells that are inhibited by luteolin treatment have not been identified. This study found that the level of cyclin E2 (CCNE2) mRNA was higher in tumour cells (4.89-fold, (∗)P=0.005) than in normal paired tissue samples as assessed using real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis (n=257). Further, relatively high levels of CCNE2 protein expression were detected in tamoxifen-resistant (TAM-R) MCF-7 cells. These results showed that the level of CCNE2 protein expression was specifically inhibited in luteolin-treated (5μM) TAM-R cells, either in the presence or absence of 4-OH-TAM (100nM). Combined treatment with 4-OH-TAM and luteolin synergistically sensitised the TAM-R cells to 4-OH-TAM. The results of this study suggest that luteolin can be used as a chemosensitiser to target the expression level of CCNE2 and that it could be a novel strategy to overcome TAM resistance in breast cancer patients.

Differences in degradation lead to asynchronous expression of cyclin E1 and cyclin E2 in cancer cells

Cyclin E1 is expressed at the G 1/S phase transition of the cell cycle to drive the initiation of DNA replication and is degraded during S/G2M. Deregulation of its periodic degradation is observed in cancer and is associated with increased proliferation and genomic instability. We identify that in cancer cells, unlike normal cells, the closely related protein cyclin E2 is expressed predominantly in S phase, concurrent with DNA replication. This occurs at least in part because the ubiquitin ligase component that is responsible for cyclin E1 downregulation in S phase, Fbw7, fails to effectively target cyclin E2 for proteosomal degradation. The distinct cell cycle expression of the two E-type cyclins in cancer cells has implications for their roles in genomic instability and proliferation and may explain their associations with different signatures of disease.

MicroRNAs and metastasis-related gene expression in Egyptian breast cancer patients

AIM AND BACKGROUND

MicroRNAs (miRNAs) are a class of naturally occurring small noncoding RNAs that regulate gene expression, cell growth, differentiation and apoptosis by targeting mRNAs for translational repression or cleavage. The present study was conducted to study miRNAs in Egyptian breast cancer (BC) and their relation to metastasis, tumor invasion and apoptosis in addition to their association with the ER and PR statuses.

METHODS

Real Time RT-PCR was performed to identify the miRNA expression level of eight miRNAs and eight metastatic-related genes in 40 breast cancer samples and their adjacent non-neoplastic tissues. The expression levels of each miRNA relative to U6 RNA were determined. Also, miRNA expression profiles of the BC and their corresponding ANT were evaluated.

RESULTS

The BC patients showed an up-regulation in miRNAs (mir-155, mir-10, mir-21 and mir-373) with an upregulation in MMP2, MMp9 and VEGF genes. We found down regulation in mir-17p, mir-126, mir-335, mir-30b and also TIMP3, TMP1 and PDCD4 genes in the cancer tissue compared to the adjacent non-neoplastic tissues. Mir -10b, mir -21, mir-155 and mir373 and the metastatic genes MMP2, MMP9 and VEGF were significantly associated with an increase in tumor size (P<0.05). No significant difference was observed between any of the studied miRNAs regarding lymph node metastasis. Mir-21 was significantly over-expressed in ER-/PR- cases.

CONCLUSION

Specific miRNAs (mir-10, mir-21, mir-155, mir-373, mir-30b, mir-126, mir-17p, mir-335) are associated with tumor metastasis and other clinical characteristics for BC, facilitating identification of individuals who are at risk.

High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes

INTRODUCTION

The TWIST homolog 1 (TWIST1) is a transcription factor that induces epithelial to mesenchymal transition (EMT), a key process in metastasis. The purpose of this study was to investigate whether TWIST1 expression predicts disease progression in a large breast cancer cohort with long-term clinical follow-up, and to reveal the biology related to TWIST1 mediated disease progression.

METHODS

TWIST1 mRNA expression level was analyzed by quantitative real-time reverse polymerase chain reaction (RT-PCR) in 1,427 primary breast cancers. In uni- and multivariate analysis using Cox regression, TWIST1 mRNA expression level was associated with metastasis-free survival (MFS), disease-free survival (DFS) and overall survival (OS). Separate analyses in lymph node-negative patients (LNN, n = 778) who did not receive adjuvant systemic therapy, before and after stratification into estrogen receptor (ER)-positive (n = 552) and ER-negative (n = 226) disease, were also performed. The association of TWIST1 mRNA with survival endpoints was assessed using Kaplan-Meier analysis. Using gene expression arrays, genes showing a significant Spearman rank correlation with TWIST1 were used to identify overrepresented Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated biological pathways.

RESULTS

Increased mRNA expression level of TWIST1 analyzed as a continuous variable in both uni- and multivariate analysis was associated with shorter MFS in all patients (hazard ratio (HR): 1.17, 95% confidence interval, (95% CI):1.09 to 1.26; and HR: 1.17, 95% CI: 1.08 to 1.26; respectively), in LNN patients (HR: 1.22, 95% CI: 1.09 to 1.36; and HR: 1.21, 95% CI: 1.07 to 1.36; respectively) and in the ER-positive subgroup of LNN patients (HR: 1.34, 95% CI: 1.17 to 1.53; and HR: 1.32, 95% CI: 1.14 to 1.53; respectively). Similarly, high TWIST1 expression was associated with shorter DFS and OS in all patients and in the LNN/ER-positive subgroup. In contrast, no association of TWIST1 mRNA expression with MFS, DFS or OS was observed in ER-negative patients. Genes highly correlated with TWIST1 were significantly enriched for cell adhesion and ECM-related signaling pathways. Furthermore, TWIST1 mRNA was highly expressed in tumor stroma and positively related to tumor stromal content (P <0.001).

CONCLUSIONS

TWIST1 mRNA expression is an independent prognostic factor for poor prognosis in LNN/ER-positive breast cancer. The biological associations suggest an involvement of the tumor microenvironment in TWIST1's adverse role in breast cancer.

Antiproliferative effects of artemisinin on human breast cancer cells requires the downregulated expression of the E2F1 transcription factor and loss of E2F1-target cell cycle genes

Artemisinin, a sesquiterpene phytolactone derived from Artemisia annua, is a potent antimalarial compound with promising anticancer properties, although the mechanism of its anticancer signaling is not well understood. Artemisinin inhibited proliferation and induced a strong G1 cell cycle arrest of cultured MCF7 cells, an estrogen-responsive human breast cancer cell line that represents an early-stage cancer phenotype, and effectively inhibited the in-vivo growth of MCF7 cell-derived tumors from xenografts in athymic nude mice. Artemisinin also induced a growth arrest of tumorigenic human breast cancer cell lines with preneoplastic and late stage cancer phenotypes, but failed to arrest the growth of a nontumorigenic human mammary cell line. Concurrent with the cell cycle arrest of MCF7 cells, artemisinin selectively downregulated the transcript and protein levels of the CDK2 and CDK4 cyclin-dependent kinases, cyclin E, cyclin D1, and the E2F1 transcription factor. Analysis of CDK2 promoter-luciferase reporter constructs showed that the artemisinin ablation of CDK2 gene expression was accounted for by the loss of CDK2 promoter activity. Chromatin immunoprecipitation revealed that artemisinin inhibited E2F1 interactions with the endogenous MCF7 cell CDK2 and cyclin E promoters. Moreover, constitutive expression of exogenous E2F1 prevented the artemisinin-induced cell cycle arrest and downregulation of CDK2 and cyclin E gene expression. Taken together, our results demonstrate that the artemisinin disruption of E2F1 transcription factor expression mediates the cell cycle arrest of human breast cancer cells and represents a critical transcriptional pathway by which artemisinin controls human reproductive cancer cell growth.

Stemness gene expression profile analysis in human umbilical cord mesenchymal stem cells

Umbilical cord mesenchymal stem cells (UC-MSCs) have several advantages for clinical therapy: the material is easily obtainable, the donation procedure is painless and there is low risk of viral contamination. UC-MSCs play important roles in tissue regeneration, tissue damage repair, autoimmune disease and graft-versus-host disease. In this study, we investigated the normal mRNA expression profile of UC-MSCs, and analyzed the candidate proteins responsible for the signaling pathway that may affect the differentiation characteristics of UC-MSCs. UC-MSCs were isolated by mincing UC samples into fragments and placing them in growth medium in a six-well plate. The immunophenotype characteristics and multilineage differentiation potential of the UC-MSCs were measured by flow cytometry and immunohistochemical assays. In addition, the pathway-focused gene expression profile of UC-MSCs was compared with those of normal or tumorous cells by realtime quantitative polymerase chain reaction. We successfully isolated and cultured UC-MSCs and analyzed the appropriate surface markers and their capacity for osteogenic, adipogenic and neural differentiation. In total, 168 genes focusing on signal pathways were examined. We found that the expression levels of some genes were much higher or lower than those of control cells, either normal or tumorous. UC-MSCs exhibit a unique mRNA expression profile of pathway-focused genes, especially some stemness genes, which warrants further investigation.

MiR-137 targets estrogen-related receptor alpha and impairs the proliferative and migratory capacity of breast cancer cells

ERRα is an orphan nuclear receptor emerging as a novel biomarker of breast cancer. Over-expression of ERRα in breast tumor is considered as a prognostic factor of poor clinical outcome. The mechanisms underlying the dysexpression of this nuclear receptor, however, are poorly understood. MicroRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play important roles in tumor initiation and progression. In the present study, we have identified that the expression of ERRα is regulated by miR-137, a potential tumor suppressor microRNA. The bioinformatics search revealed two putative and highly conserved target-sites for miR-137 located within the ERRα 3'UTR at nt 480-486 and nt 596-602 respectively. Luciferase-reporter assay demonstrated that the two predicted target sites were authentically functional. They mediated the repression of reporter gene expression induced by miR-137 in an additive manner. Moreover, ectopic expression of miR-137 down-regulated ERRα expression at both protein level and mRNA level, and the miR-137 induced ERRα-knockdown contributed to the impaired proliferative and migratory capacity of breast cancer cells. Furthermore, transfection with miR-137 mimics suppressed at least two downstream target genes of ERRα-CCNE1 and WNT11, which are important effectors of ERRα implicated in tumor proliferation and migration. Taken together, our results establish a role of miR-137 in negatively regulating ERRα expression and breast cancer cell proliferation and migration. They suggest that manipulating the expression level of ERRα by microRNAs has the potential to influence breast cancer progression.

Inference of tumor phylogenies from genomic assays on heterogeneous samples

Tumorigenesis can in principle result from many combinations of mutations, but only a few roughly equivalent sequences of mutations, or "progression pathways," seem to account for most human tumors. Phylogenetics provides a promising way to identify common progression pathways and markers of those pathways. This approach, however, can be confounded by the high heterogeneity within and between tumors, which makes it difficult to identify conserved progression stages or organize them into robust progression pathways. To tackle this problem, we previously developed methods for inferring progression stages from heterogeneous tumor profiles through computational unmixing. In this paper, we develop a novel pipeline for building trees of tumor evolution from the unmixed tumor data. The pipeline implements a statistical approach for identifying robust progression markers from unmixed tumor data and calling those markers in inferred cell states. The result is a set of phylogenetic characters and their assignments in progression states to which we apply maximum parsimony phylogenetic inference to infer tumor progression pathways. We demonstrate the full pipeline on simulated and real comparative genomic hybridization (CGH) data, validating its effectiveness and making novel predictions of major progression pathways and ancestral cell states in breast cancers.

Functional characterization of the 19q12 amplicon in grade III breast cancers

INTRODUCTION

The 19q12 locus is amplified in a subgroup of oestrogen receptor (ER)-negative grade III breast cancers. This amplicon comprises nine genes, including cyclin E1 (CCNE1), which has been proposed as its 'driver'. The aim of this study was to identify the genes within the 19q12 amplicon whose expression is required for the survival of cancer cells harbouring their amplification.

METHODS

We investigated the presence of 19q12 amplification in a series of 313 frozen primary breast cancers and 56 breast cancer cell lines using microarray comparative genomic hybridisation (aCGH). The nine genes mapping to the smallest region of amplification on 19q12 were silenced using RNA interference in phenotypically matched breast cancer cell lines with (MDA-MB-157 and HCC1569) and without (Hs578T, MCF7, MDA-MB-231, ZR75.1, JIMT1 and BT474) amplification of this locus. Genes whose silencing was selectively lethal in amplified cells were taken forward for further validation. The effects of cyclin-dependent kinase 2 (CDK2) silencing and chemical inhibition were tested in cancer cells with and without CCNE1 amplification.

RESULTS

19q12 amplification was identified in 7.8% of ER-negative grade III breast cancer. Of the nine genes mapping to this amplicon, UQCRFS1, POP4, PLEKHF1, C19ORF12, CCNE1 and C19ORF2 were significantly over-expressed when amplified in primary breast cancers and/or breast cancer cell lines. Silencing of POP4, PLEKHF1, CCNE1 and TSZH3 selectively reduced cell viability in cancer cells harbouring their amplification. Cancer cells with CCNE1 amplification were shown to be dependent on CDK2 expression and kinase activity for their survival.

CONCLUSIONS

The 19q12 amplicon may harbour more than a single 'driver', given that expression of POP4, PLEKHF1, CCNE1 and TSZH3 is required for the survival of cancer cells displaying their amplification. The observation that cancer cells harbouring CCNE1 gene amplification are sensitive to CDK2 inhibitors provides a rationale for the testing of these chemical inhibitors in a subgroup of patients with ER-negative grade III breast cancers.

The inference of breast cancer metastasis through gene regulatory networks

Understanding the mechanisms of gene regulation during breast cancer is one of the most difficult problems among oncologists because this regulation is likely comprised of complex genetic interactions. Given this complexity, a computational study using the Bayesian network technique has been employed to construct a gene regulatory network from microarray data. Although the Bayesian network has been notified as a prominent method to infer gene regulatory processes, learning the Bayesian network structure is NP hard and computationally intricate. Therefore, we propose a novel inference method based on low-order conditional independence that extends to the case of the Bayesian network to deal with a large number of genes and an insufficient sample size. This method has been evaluated and compared with full-order conditional independence and different prognostic indices on a publicly available breast cancer data set. Our results suggest that the low-order conditional independence method will be able to handle a large number of genes in a small sample size with the least mean square error. In addition, this proposed method performs significantly better than other methods, including the full-order conditional independence and the St. Gallen consensus criteria. The proposed method achieved an area under the ROC curve of 0.79203, whereas the full-order conditional independence and the St. Gallen consensus criteria obtained 0.76438 and 0.73810, respectively. Furthermore, our empirical evaluation using the low-order conditional independence method has demonstrated a promising relationship between six gene regulators and two regulated genes and will be further investigated as potential breast cancer metastasis prognostic markers.

High miR-26a and low CDC2 levels associate with decreased EZH2 expression and with favorable outcome on tamoxifen in metastatic breast cancer

For patients with metastatic breast cancer, we previously described that increased EZH2 expression levels were associated with an adverse outcome to tamoxifen therapy. Main objective of the present study is to investigate miR-26a and miR-101 levels, which both target EZH2, for their association with molecular pathways and with efficacy of tamoxifen as first-line monotherapy for metastatic breast cancer. Expression levels were measured using quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) in primary breast cancer specimens of 235 estrogen receptor-α (ER)-positive patients. Pathway analysis was performed on microarray data available for 65 of these tumors. Logistic regression and Cox uni- and multivariate analysis were performed to relate expression levels with clinical benefit and time to progression (TTP). Increasing levels of miR-26a were significantly (P < 0.005) associated with both clinical benefit and prolonged TTP, whereas miR-101 was not. Cell cycle regulation and CCNE1 and CDC2 were the only significant overlapping pathway and genes differentially expressed between tumors with high and low levels of miR-26a and EZH2, respectively. In addition, increasing mRNA levels of CCNE1 (P < 0.05) and CDC2 (P < 0.001) were related to poor outcome. Multivariate analysis revealed miR-26a and CDC2 as an optimal set of markers associated with outcome on tamoxifen therapy, independently of traditional predictive factors. To summarize, only miR-26a levels are related with treatment outcome. Cell cycle regulation is the only overlapping pathway linked to miR-26a and EZH2 levels. Low mRNA levels of EZH2, CCNE1, and CDC2, and high levels of miR-26a are associated with favorable outcome on tamoxifen.

Patient-specific data fusion defines prognostic cancer subtypes

Different data types can offer complementary perspectives on the same biological phenomenon. In cancer studies, for example, data on copy number alterations indicate losses and amplifications of genomic regions in tumours, while transcriptomic data point to the impact of genomic and environmental events on the internal wiring of the cell. Fusing different data provides a more comprehensive model of the cancer cell than that offered by any single type. However, biological signals in different patients exhibit diverse degrees of concordance due to cancer heterogeneity and inherent noise in the measurements. This is a particularly important issue in cancer subtype discovery, where personalised strategies to guide therapy are of vital importance. We present a nonparametric Bayesian model for discovering prognostic cancer subtypes by integrating gene expression and copy number variation data. Our model is constructed from a hierarchy of Dirichlet Processes and addresses three key challenges in data fusion: (i) To separate concordant from discordant signals, (ii) to select informative features, (iii) to estimate the number of disease subtypes. Concordance of signals is assessed individually for each patient, giving us an additional level of insight into the underlying disease structure. We exemplify the power of our model in prostate cancer and breast cancer and show that it outperforms competing methods. In the prostate cancer data, we identify an entirely new subtype with extremely poor survival outcome and show how other analyses fail to detect it. In the breast cancer data, we find subtypes with superior prognostic value by using the concordant results. These discoveries were crucially dependent on our model's ability to distinguish concordant and discordant signals within each patient sample, and would otherwise have been missed. We therefore demonstrate the importance of taking a patient-specific approach, using highly-flexible nonparametric Bayesian methods.

Clinical significance of the nuclear receptor co-regulator DC-SCRIPT in breast cancer: an independent retrospective validation study

Introduction

In this study we aimed to validate the prognostic value of DC-SCRIPT mRNA expression in a large independent breast cancer cohort. In addition, since DC-SCRIPT is a transcriptional co-regulator of nuclear receptors, we explored its prognostic value in relation to estrogen-receptor-α (ESR1) and -β (ESR2) and evaluated its predictive value for response to tamoxifen treatment.

Methods

DC-SCRIPT mRNA levels were measured by real-time PCR in 1,505 primary invasive breast cancers and associated with outcome (disease-free survival (DFS), metastasis-free survival (MFS) and overall survival (OS)) using univariate and multivariable Cox regression analysis. Logistic and Cox regressions were used to associate DC-SCRIPT levels with clinical benefit and progression-free survival (PFS) for 296 patients treated with first-line systemic tamoxifen for advanced disease.

Results

In univariate and multivariable analysis higher DC-SCRIPT levels were associated with a favorable outcome for both the entire cohort and patients with lymph node-negative (LNN) disease that did not receive adjuvant therapy (DFS, MFS and OS; all, P < 0.001). This association was most pronounced in small (pT1) tumors, in ESR1-positive tumors and in tumors with low ESR2 expression. For first-line endocrine therapy for advanced disease no predictive association was seen with clinical benefit or PFS.

Conclusions

This study provides a higher level of evidence that DC-SCRIPT is indeed an independent, pure prognostic, factor for primary breast cancer and shows that DC-SCRIPT mRNA expression is most informative for either ESR1-positive and/or ESR2-low pT1 tumors.

Three-dimensional collagen represses cyclin E1 via β1 integrin in invasive breast cancer cells

The behavior of breast epithelial cells is influenced by their microenvironment which includes stromal cells and extracellular matrix (ECM). During cancer progression, the tissue microenvironment fails to control proliferation and differentiation, resulting in uncontrolled growth and invasion. Upon invasion, the ECM encountered by breast cancer cells changes from primarily laminin and collagen IV to primarily collagen I. We show here that culturing invasive breast cancer cells in 3-dimensional (3D) collagen I inhibits proliferation through direct regulation of cyclin E1, a G(1)/S regulator that is overexpressed in breast cancer. When the breast cancer cell line MDA-MB-231 was cultured within 3D collagen I gels, the G(1)/S transition was inhibited as compared to cells cultured on conventional 2D collagen or plastic dishes. Cells in 3D collagen downregulated cyclin E1 protein and mRNA, with no change in cyclin D1 level. Cyclin D1 was primarily cytoplasmic in 3D cultures, and this was accompanied by decreased phosphorylation of Rb, a nuclear target for both cyclin E1- and cyclin D1-associated kinases. Positive regulators of cyclin E1 expression, the transcription factor c-Myc and cold-inducible RNA binding protein (CIRP), were decreased in 3D collagen cultures, while the collagen I receptor β1 integrin was greatly increased. Inhibition of β1 integrin function rescued proliferation and cyclin E1 expression as well as c-Myc expression and Rb phosphorylation, but cyclin D1 remained cytoplasmic. We conclude that cyclin E1 is repressed independent of effects on cyclin D1 in a 3D collagen environment and dependent on β1 integrin interaction with collagen I, reducing proliferation of invasive breast cancer cells.

MicroRNA-30c expression level is an independent predictor of clinical benefit of endocrine therapy in advanced estrogen receptor positive breast cancer

MicroRNAs (miRNAs) are small RNA molecules that modulate gene expression and which have been implicated in cancer. We evaluated whether five candidate predictive miRNAs, derived from a pilot study in which 249 miRNAs were assayed, were associated with clinical benefit of tamoxifen therapy in advanced breast cancer. These five miRNAs were measured in an independent series of 246 estrogen receptor (ER)-positive primary breast tumors of patients who received tamoxifen for advanced disease by quantitative Real Time PCR. Univariate analysis showed that higher expression levels of hsa-miR-30a-3p, hsa-miR-30c, and hsa-miR-182 were significantly associated with benefit of tamoxifen treatment and with longer PFS (all P-values <0.01). In multivariate analysis, corrected for the traditional predictive factors, only hsa-miRNA-30c was an independent predictor (P-value <0.01). Finally, in an attempt to understand the biology connected to this miRNA, Global testing pathway analysis showed an association of hsa-miRNA-30c expression with HER and RAC1 signaling pathways. We identified hsa-miRNA-30c as an independent predictor for clinical benefit of tamoxifen therapy in patients with advanced breast cancer. Assessment of tumor levels and connected pathways could be helpful to improve treatment strategies.

Distinct and redundant functions of cyclin E1 and cyclin E2 in development and cancer

The highly conserved E-type cyclins are core components of the cell cycle machinery, facilitating the transition into S phase through activation of the cyclin dependent kinases, and assembly of pre-replication complexes on DNA. Cyclin E1 and cyclin E2 are assumed to be functionally redundant, as cyclin E1-/- E2-/- mice are embryonic lethal while cyclin E1-/- and E2-/- single knockout mice have primarily normal phenotypes. However more detailed studies of the functions and regulation of the E-cyclins have unveiled potential additional roles for these proteins, such as in endoreplication and meiosis, which are more closely associated with either cyclin E1 or cyclin E2. Moreover, expression of each E-cyclin can be independently regulated by distinct transcription factors and microRNAs, allowing for context-specific expression. Furthermore, cyclins E1 and E2 are frequently expressed independently of one another in human cancer, with unique associations to signatures of poor prognosis. These data imply an absence of co-regulation of cyclins E1 and E2 during tumorigenesis and possibly different contributions to cancer progression. This is supported by in vitro data identifying divergent regulation of the two genes, as well as potentially different roles in vivo.

CITED2 and NCOR2 in anti-oestrogen resistance and progression of breast cancer

Background:

Endocrine therapies of breast cancer are effective but ultimately fail because of the development of treatment resistance. We have previously revealed several genes leading to tamoxifen resistance in vitro by retroviral insertion mutagenesis. To understand the manner in which these genes yield tamoxifen resistance, their effects on global gene expression were studied and those genes resulting in a distinct gene expression profile were further investigated for their clinical relevance.

Methods:

Gene expression profiles of 69 human breast cancer cell lines that were made tamoxifen resistant through retroviral insertion mutagenesis were obtained using oligonucleotide arrays and analysed with bioinformatic tools. mRNA levels of NCOR2 and CITED2 in oestrogen receptor-positive breast tumours were determined by quantitative RT–PCR. mRNA levels were evaluated for association with metastasis-free survival (MFS) in 620 patients with lymph node-negative primary breast cancer who did not receive systemic adjuvant therapy, and with clinical benefit in 296 patients receiving tamoxifen therapy for recurrent breast cancer.

Results:

mRNA expression profiles of most tamoxifen-resistant cell lines were strikingly similar, except for the subgroups of cell lines in which NCOR2 or CITED2 were targeted by the retrovirus. Both NCOR2 and CITED2 mRNA levels were associated with MFS, that is, tumour aggressiveness, independently of traditional prognostic factors. In addition, high CITED2 mRNA levels were predictive for a clinical benefit from first-line tamoxifen treatment in patients with advanced disease.

Conclusions:

Most retrovirally targeted genes yielding tamoxifen resistance in our cell lines do not impose a distinctive expression profile, suggesting that their causative role in cell growth may be accomplished by post-transcriptional processes. The associations of NCOR2 and CITED2 with outcome in oestrogen receptor-positive breast cancer patients underscore the clinical relevance of functional genetic screens to better understand disease progression, which may ultimately lead to the development of improved treatment options.

Analysis of breast cancer related gene expression using natural splines and the Cox proportional hazard model to identify prognostic associations

Many studies correlating gene expression data to clinical parameters assume a linear increase or decrease of the clinical parameter under investigation with the expression of a gene. We have studied genes encoding important breast cancer-related proteins using a model for survival-type data that is based on natural splines and the Cox proportional hazard model, thereby removing the linearity assumption. Expression data of 16 genes were studied in relation to metastasis-free probability in a cohort of 295 consecutive breast cancer patients treated at The Netherlands Cancer Institute. The independent predictive power for disease outcome of the 16 individual genes was tested in a multivariable model with known clinical and pathological risk factors. There is a linear relationship between increasing expression and a higher or lower hazard for distant metastasis for ESR1, ERBB4, VEGF, CCNE2, EZH2, and UPA; for ERBB2, ERBB3, CCND1, CCNE1, EED, CXCR4, CCR7, SDF1, and PAI1 there is no clear increase or decrease; and for EGFR there seems to be a non-linear relation. Multivariable analysis showed that the 70-gene prognosis profile outperforms all the other variables in the model (hazard-rate 5.4, 95% CI 2.5-11.7; P = 0.000018). EGFR-expression seems to have a non-linear relation with disease outcome, indicating that lower but also higher expression of EGFR are associated with worse outcome compared to intermediate expression levels; the other genes show no or a linear relation.

Genome-wide identification of direct target genes implicates estrogen-related receptor alpha as a determinant of breast cancer heterogeneity

Estrogen-related receptor alpha (ERRalpha) is an orphan nuclear receptor, the expression of which correlates with negative prognosis in breast cancer. ERRalpha shares functional features with the estrogen receptor alpha (ERalpha) and its activity is modulated by the ERBB2 signaling pathway. Using genome-wide binding sites location analyses in ERalpha-positive and ERalpha-negative breast cancer cell lines, we show that ERRalpha and ERalpha display strict binding site specificity and maintain independent mechanisms of transcriptional activation. Nonetheless, ERRalpha and ERalpha coregulate a small subset of common target genes via binding either to a dual-specificity binding site or to distinct cognate binding sites located within the extended promoter region of the gene. Although ERRalpha signaling in breast cancer cells is mostly independent of ERalpha, the small fraction of common ERRalpha/ERalpha targets comprises genes with high relevance to breast tumor biology, including genes located within the ERBB2 amplicon and GATA3. Finally, unsupervised hierarchical clustering based on the expression profiling of ERRalpha direct target genes in human breast tumors revealed four main clusters that recapitulate established tumor subtypes. Taken together, the identification and functional characterization of the ERRalpha transcriptional network implicate ERRalpha signaling as a determinant of breast cancer heterogeneity.