Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer

Volinia, Stefano; Croce, Carlo M.

doi:10.1073/pnas.1304977110

Cited by 138 publications

(113 citation statements)

References 33 publications

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“…Our study suggests that some of these functions in TNBC may be regulated by this specific subset of miRNAs. miR-103 and miR-107 have earlier been implicated in EMT and DNA repair, and associated with metastasis and poor outcome in breast cancer (17)(18)(19). miR-652 has been demonstrated to identify stage I-II breast cancer patients and to correlate with TP53, suggesting a potential role for this miRNA as prognostic biomarker (20).…”

Section: Discussionmentioning

confidence: 99%

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Sahlberg

Bottai

Naume

et al. 2015

Clinical Cancer Research

187

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Purpose: Triple-negative breast cancers (TNBC) are associated with high risk of early tumor recurrence and poor outcome. Common prognostic biomarkers give very restricted predictive information of tumor recurrences in TNBC. Human serum contains stably expressed microRNAs (miRNAs), which have been discovered to predict prognosis in patients with cancer. The purpose of this study was to identify circulating biomarkers able to predict clinical outcome in TNBC.Experimental Design: We performed genome-wide serum miRNA expression and real-time PCR analyses to investigate the ability of miRNAs in predicting tumor relapse in serum samples from 60 primary TNBC. Patients were divided into training and testing cohorts.Results: By Cox regression analysis, we identified a four-miRNA signature (miR-18b, miR-103, miR-107, and miR-652) that predicted tumor relapse and overall survival. This miRNA signature was further validated in an independent cohort of 70 TNBC. A high-risk signature score was developed and significantly associated with tumor recurrence and reduced survival. Multivariate Cox regression models indicated that the risk score based on the four-miRNA signature was an independent prognostic classifier of patients with TNBC.Conclusions: This signature may serve as a minimally invasive predictor of tumor relapse and overall survival for patients with TNBC. This prediction model may ultimately lead to better treatment options for patients with TNBC.

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Section: Discussionmentioning

confidence: 99%

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Sahlberg

Bottai

Naume

et al. 2015

Clinical Cancer Research

187

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“…Expression levels of a number of miRNAs, which are either positively or inversely associated with metastatic status, disease-free time and overall survival of breast cancer patients have been identified [225][226][227][228][229][230][231][232][233][234][235][236][237][238][239][240] and are detailed in Table 3. The most relevant miRNA with prognostic value in breast cancer is miR-210, the aforementioned oncogenic miRNA implicated in the DCIS-to-IDC transition.…”

Section: Translational Implications Of Ncrnas In Breast Cancermentioning

confidence: 99%

Noncoding RNAs in breast cancer

Lo¹,

Wolfson²,

Zhou³

et al. 2015

Briefings in Functional Genomics

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The mammalian transcriptome has recently been revealed to encompass a large number of noncoding RNAs (ncRNAs) that play a variety of important regulatory roles in gene expression and other biological processes. MicroRNAs (miRNAs), the best studied of the short noncoding RNAs (sncRNAs), have been extensively characterized with regard to their biogenesis, function and importance in tumorigenesis. Another class of sncRNAs called piwi-interacting RNAs (piRNAs) has also gained attention recently in cancer research owing to their critical role in stem cell regulation. Long noncoding RNAs (lncRNAs) of >200 nucleotides in length have recently emerged as key regulators of developmental processes, including mammary gland development. lncRNA dysregulation has also been implicated in the development of various cancers, including breast cancer. In this review, we describe and discuss the roles of sncRNAs (including miRNAs and piRNAs) and lncRNAs in the initiation and progression of breast tumorigenesis, with a focus on outlining the molecular mechanisms of oncogenic and tumor-suppressor ncRNAs. Moreover, the current and potential future applications of ncRNAs to clinical breast cancer research are also discussed, with an emphasis on ncRNA-based diagnosis, prognosis and future therapeutics.

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“…Analysis of circulating miRNAs in the serum of 60 treatment naive primary ductal TNBC patients gave rise to the development of a signature of 4 miRNAs (miR-18b, miR-103, miR-107 and miR-652) capable of distinguishing tumours from patients with early relapse from those without recurrence, making this signature a potential risk predictor for MED [53]. Interestingly, three of the four miRNAs have been linked with tumour mechanisms in breast cancer, miR-103 and miR-107 have been implicated in DNA repair and epithelial to mesenchymal transition, whilst ER is a target of miR-18b [54][55][56][57].…”

Section: Circulating Micrornas As Markers and Predictors Of Metastasismentioning

confidence: 99%

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

Inns

James

2015

The Breast

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Inns, Joseph and James, Victoria (2015) Circulating microRNAs for the prediction of metastasis in breast cancer patients diagnosed with early stage disease. The Breast, 24 (4). pp. 364-369. ISSN 1532-3080 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/36999/1/YBRST_2141_edit_report.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the University of Nottingham End User licence and may be reused according to the conditions of the licence. For more details see: http://eprints.nottingham.ac.uk/end_user_agreement.pdf A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk IntroductionBreast cancer is the second most common malignancy diagnosed worldwide, accounting for approximately 23% of all cancer diagnoses per year and 465,000 cancer-related deaths [1]. These cases will include early stage disease, local recurrence or metastasis in patients previously treated with a curative intent, and advanced stage disease, characterised by the significant spread of the cancer within the breast or systemically [1,2]. The metastatic cascade initiates with localised invasion of surrounding tissue, followed by systemic spread via the blood and lymphatic system and finally dissemination of tumour cells to other organs [3]. At the point of diagnosis up to 5% of patients present with metastatic disease and of those patients who show no lymph-node involvement at diagnosis, approximately 30% will develop metastases [4,5]. This subset of individuals who potentially have metastasis of early disease (MED) represent an at risk group, who may benefit from additional monitoring and augmented treatment strategies. We currently need markers to distinguish these patients from those who do not go on to develop disease recurrence. Clinical staging and molecular classificationClinical staging is essential for establishing surgical approaches and treatment regimes. The current TNM system assess primary tumour size and extent of invasion (T), the absence or presence of palpable axillary lymph nodes and indications of local invasion (N), and evidence of distant metastasis (M) [6]. The TNM system is further supplemented by the allocation of stages I-V depending on size and metastatic spread [6]. Molecular factors are also employed to assist prognosis and direct treatment strategies. Breast cancers are categorised based on the expression of oestrogen and progesterone receptors (ER and PR) and the receptor tyrosine kinase erbB-2 (ERBB2 or HER2). Further categorisation defines four molecular subtypes [Refs. 33,34]: luminal A whi...

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Prognostic microRNA/mRNA signature from the integrated analysis of patients with invasive breast cancer

Cited by 138 publications

References 33 publications

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Noncoding RNAs in breast cancer

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

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