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Prognostic and predictive biomarkers in breast cancer: Past, present and future

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Abstract

Following a diagnosis of breast cancer, the most immediate challenges in patient management are the determination of prognosis and identification of the most appropriate adjuvant systemic therapy. Determining prognosis can best be addressed with a combination of traditional clinicopathological prognostic factors, biomarkers such as HER2/neu and specific multigene genes tests. Amongst the best validated prognostic multigene tests are uPA/PAI1, Oncotype DX and MammaPrint. Oncotype DX and MammaPrint, may be used for predicting outcome and aiding adjunct therapy decision making in patients with ER-positive, HER2-negative breast cancers that are either lymph node-negative or node positive (1–3 metastatic nodes), while uPA/PAI-1 may be similarly used in ER-positive, lymph node-negative patients. For selecting likely response to endocrine therapy, both estrogen receptors (ER) and progesterone receptors (PR) should be measured. On the other hand, for identifying likely response to anti-HER2 therapy, determination of HER2 gene amplification or overexpression is necessary. To identify new prognostic and predictive biomarkers for breast cancer, current research is focusing on tumor and circulating DNA (ctDNA) and RNA (e.g., micro RNAs) and circulating tumor cells. A promising ctDNA biomarker is the mutational status of ER (ESR1) for predicting the emergence of resistance to aromatase inhibitors. Challenges for future research include the identification of biomarkers for predicting response to radiotherapy and specific forms of chemotherapy.

Introduction

Following a diagnosis of invasive breast cancer, one of the most immediate challenges is to identify who should or should not receive adjuvant treatment, especially adjuvant chemotherapy. If the decision is to administer adjuvant therapy, the next challenge is to identify the most suitable therapy or combination of therapies for a given patient. Addressing the first challenge can be aided by prognostic factors/biomarkers while addressing the second challenge can be helped with predictive biomarkers. The aim of this article is to discuss how prognostic and predictive biomarkers help optimize therapy decision making in patients with newly diagnosed breast cancer. First however, we briefly review the contribution of the traditional prognostic factors for the management of patients with early breast cancer.

Section snippets

Traditional prognostic factors

With so much emphasis being placed on molecular prognostic tests in recent years, the important contribution of the traditional clinical/pathological factors (Table 1) tends to be forgotten. Of the factors listed in Table 1, the most widely used are the number of regional lymph nodes with metastases, tumor size and tumor grade [1], [2]. Despite the availability of multiple molecular tests in recent years, these factors continue to be mandatory for determining prognosis and aiding therapy

Molecular prognostic biomarkers

Although the number of lymph node metastases, tumor size and tumor grade all supply independent prognostic information in patients with newly diagnosed breast cancer, it is widely accepted that these factors alone are inadequate for optimum patient management, especially as we move towards the era of personalized treatment [15], [16]. Consequently, in recent years, a substantial amount of research has been devoted to the development and validation of molecular biomarkers that can provide not

Predictive biomarkers

In contrast to prognostic biomarkers which predict the risk of disease recurrence, predictive biomarkers help identify upfront those patients that are likely to respond or be resistant to specific therapies. Of all the common cancers, breast cancer has led the way in the use of therapy predictive biomarkers. For example, the measurement of estrogen and progesterone receptors (ER, PR) to predict response to endocrine therapy entered clinical use over 40 years ago while measurement of HER2 for

The need for development of an advanced technology: DNA and RNA genotyping techniques

Due to the genetic and epigenetic origin of cancer the need for more rapidly and accurately sequencing DNA and RNA and to better investigate the transcriptional machinery has strongly emerged. In a relatively short time huge progress in the available techniques as well as the related computational biology has been made. All these techniques which have been applied to samples from tissue and recently from peripheral blood (PB) samples as well have had a great impact in discovering at genetic and

Investigational prognostic and predictive biomarkers

In the last years, many investigations using the new techniques have been carried out. In tissue the expression of single or multiple (genetic signature) genes or single or multiple (cluster, micro-RNA signature) micro-RNAs (mi-RNAs) and in peripheral blood (PB) mi-RNAs, circulating tumor cells (CTCs) and circulating tumor DNA (ct DNA) have been detected. Moreover, in serum/plasma miRNAs benefit from the advantage to be highly stable [119]. In some instances, databases have been a helpful tool

Challenges for future research

Although substantial progress has been made in the identification and validation of prognostic and predictive biomarkers for breast, several major challenges remain. These include identification and validation of biomarkers for:

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    Predicting response to specific forms of chemotherapy.

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    Identifying patients likely to develop severe chemotherapy-related toxicity.

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    Predicting response to radiotherapy.

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    Enhancing the positive predictive value of ER.

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    Selecting patients that preferentially benefit from an

Conclusion

Breast cancer has led the way in the introduction of prognostic and predictive biomarkers for cancer patients. Over 40 years ago, ER was first introduced for predicting response to endocrine therapy. Twenty years later, HER2 became available for identifying patients likely to benefit from trastuzumab and later to other forms of anti-HER2 therapy. In the last decade, several multigene signatures have been proposed for identifying patients with early breast cancer whose prognosis is so good, that

Conflicts of interest

MJD is a clinical advisor to OncoMark and Atturos.

Acknowledgements

MJD wishes to thank Science Foundation Ireland, Strategic Research Cluster Award (08/SRC/B1410) to Molecular Therapeutics for Cancer Ireland (MTCI), the BREAST-PREDICT (CCRC13GAL) program of the Irish Cancer Society and the Clinical Cancer Research Trust for funding his work.

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