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Journal ArticleDOI

Challenges translating breast cancer gene signatures into the clinic

TL;DR: The hurdles in the development and validation of molecular classification systems, and prognostic and predictive signatures based on microarray gene-expression profiling are discussed and it is suggested that similar challenges are likely to be encountered in translating next-generation sequencing data into clinically useful information.
Abstract: The advent of microarray-based gene-expression profiling a decade ago raised high expectations for rapid advances in breast cancer classification, prognostication and prediction. Despite the development of molecular classifications, and prognostic and predictive gene-expression signatures, microarray-based studies have not yielded definitive answers to many of the questions that remain germane for the successful implementation of personalized medicine. There are a lack of robust signatures to predict benefit from specific therapeutic agents and it is still not possible to predict prognosis or chemotherapy treatment response in specific disease subsets accurately, such as triple-negative breast cancer. We discuss the hurdles in the development and validation of molecular classification systems, and prognostic and predictive signatures based on microarray gene-expression profiling. We suggest that similar challenges are likely to be encountered in translating next-generation sequencing data into clinically useful information. Finally we highlight strategies for the development of clinically useful molecular predictors in the future.
Citations
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Journal ArticleDOI
TL;DR: In this paper, the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors are discussed, and a molecular classification system and prognostic multi-genene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice.

593 citations

01 Jan 2011
TL;DR: In this paper, the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors are discussed, and a molecular classification system and prognostic multi-genene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice.
Abstract: Microarray-based gene expression profiling has had a major effect on our understanding of breast cancer. Breast cancer is now perceived as a heterogeneous group of different diseases characterised by distinct molecular aberrations, rather than one disease with varying histological features and clinical behaviour. Gene expression profiling studies have shown that oestrogen-receptor (ER)-positive and ER-negative breast cancers are distinct diseases at the transcriptomic level, that additional molecular subtypes might exist within these groups, and that the prognosis of patients with ER-positive disease is largely determined by the expression of proliferation-related genes. On the basis of these principles, a molecular classification system and prognostic multigene classifiers based on microarrays or derivative technologies have been developed and are being tested in randomised clinical trials and incorporated into clinical practice. In this review, we focus on the conceptual effect and potential clinical use of the molecular classification of breast cancer, and discuss prognostic and predictive multigene predictors.

592 citations

Journal ArticleDOI
TL;DR: Envisaging tumor growth as a Darwinian tree with the trunk representing ubiquitous mutations and the branches representing heterogeneous mutations may help in drug discovery and the development of predictive biomarkers of drug response.
Abstract: Most advanced solid tumors remain incurable, with resistance to chemotherapeutics and targeted therapies a common cause of poor clinical outcome. Intratumor heterogeneity may contribute to this failure by initiating phenotypic diversity enabling drug resistance to emerge and by introducing tumor sampling bias. Envisaging tumor growth as a Darwinian tree with the trunk representing ubiquitous mutations and the branches representing heterogeneous mutations may help in drug discovery and the development of predictive biomarkers of drug response.

490 citations


Cites background from "Challenges translating breast cance..."

  • ...Tumors resistant to therapeutic agents usually bear a “convergent phenotype,” in which multiple di erent genetic and epigenetic aberrations may potentially cause resistance to a particular agent (5, 6)....

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Journal ArticleDOI
TL;DR: A review of the current relevant pre-clinical and clinical data is presented and the rationale for dual inhibition of these pathways in the treatment of BC patients is discussed.

324 citations

Journal ArticleDOI
TL;DR: The current status of blood-born biomarkers as surrogates for tissue-based biomarkers, and their burgeoning impact on the management of patients with breast cancer are discussed.
Abstract: Circulating blood biomarkers promise to become non-invasive real-time surrogates for tumour tissue-based biomarkers. Circulating biomarkers have been investigated as tools for breast cancer diagnosis, the dissection of breast cancer biology and its genetic and clinical heterogeneity, prognostication, prediction and monitoring of therapeutic response and resistance. Circulating tumour cells and cell-free plasma DNA have been analysed in retrospective studies, and the assessment of these biomarkers is being incorporated into clinical trials. As the scope of breast cancer intratumour genetic heterogeneity unravels, the development of robust and standardized methods for the assessment of circulating biomarkers will be essential for the realization of the potentials of personalized medicine. In this Review, we discuss the current status of blood-born biomarkers as surrogates for tissue-based biomarkers, and their burgeoning impact on the management of patients with breast cancer.

172 citations

References
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Journal ArticleDOI
17 Aug 2000-Nature
TL;DR: Variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals were characterized using complementary DNA microarrays representing 8,102 human genes, providing a distinctive molecular portrait of each tumour.
Abstract: Human breast tumours are diverse in their natural history and in their responsiveness to treatments. Variation in transcriptional programs accounts for much of the biological diversity of human cells and tumours. In each cell, signal transduction and regulatory systems transduce information from the cell's identity to its environmental status, thereby controlling the level of expression of every gene in the genome. Here we have characterized variation in gene expression patterns in a set of 65 surgical specimens of human breast tumours from 42 different individuals, using complementary DNA microarrays representing 8,102 human genes. These patterns provided a distinctive molecular portrait of each tumour. Twenty of the tumours were sampled twice, before and after a 16-week course of doxorubicin chemotherapy, and two tumours were paired with a lymph node metastasis from the same patient. Gene expression patterns in two tumour samples from the same individual were almost always more similar to each other than either was to any other sample. Sets of co-expressed genes were identified for which variation in messenger RNA levels could be related to specific features of physiological variation. The tumours could be classified into subtypes distinguished by pervasive differences in their gene expression patterns.

14,768 citations


"Challenges translating breast cance..." refers background in this paper

  • ...In breast cancer, a microarray-based study by the Stanford grou...

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Journal ArticleDOI
TL;DR: Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Abstract: The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.

10,791 citations


"Challenges translating breast cance..." refers result in this paper

  • ...Analysis of larger independent datasets subsequently confirmed the existence of similar but not identical subgroups, and demonstrated that ER-positive cancers could be further subdivided into at least two subgroups, luminal A and B, which correlated with a difference in prognosis...

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Journal ArticleDOI
31 Jan 2002-Nature
TL;DR: DNA microarray analysis on primary breast tumours of 117 young patients is used and supervised classification is applied to identify a gene expression signature strongly predictive of a short interval to distant metastases (‘poor prognosis’ signature) in patients without tumour cells in local lymph nodes at diagnosis, providing a strategy to select patients who would benefit from adjuvant therapy.
Abstract: Breast cancer patients with the same stage of disease can have markedly different treatment responses and overall outcome. The strongest predictors for metastases (for example, lymph node status and histological grade) fail to classify accurately breast tumours according to their clinical behaviour. Chemotherapy or hormonal therapy reduces the risk of distant metastases by approximately one-third; however, 70-80% of patients receiving this treatment would have survived without it. None of the signatures of breast cancer gene expression reported to date allow for patient-tailored therapy strategies. Here we used DNA microarray analysis on primary breast tumours of 117 young patients, and applied supervised classification to identify a gene expression signature strongly predictive of a short interval to distant metastases ('poor prognosis' signature) in patients without tumour cells in local lymph nodes at diagnosis (lymph node negative). In addition, we established a signature that identifies tumours of BRCA1 carriers. The poor prognosis signature consists of genes regulating cell cycle, invasion, metastasis and angiogenesis. This gene expression profile will outperform all currently used clinical parameters in predicting disease outcome. Our findings provide a strategy to select patients who would benefit from adjuvant therapy.

9,664 citations


"Challenges translating breast cance..." refers background in this paper

  • ...4,5 The strongest evidence for this does not come from the molecular-classification literature but from results obtained with prognostic gene signatures that were empirically developed to distinguish good-prognosis from poor-prognosis cancers (Oncotype DX® and MammaPrint®).(20,21) These signatures can be used to define which patients with ER-positive breast cancer should receive adjuvant chemotherapy....

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Journal ArticleDOI
03 Feb 2000-Nature
TL;DR: It is shown that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour.
Abstract: 12 Pathology and Microbiology, and 13 Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin's lymphoma, is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease. We proposed that this variability in natural history reflects unrecognized molecular heterogeneity in the tumours. Using DNA microarrays, we have conducted a systematic characterization of gene expression in B-cell malignancies. Here we show that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour. We identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation. One type expressed genes characteristic of germinal centre B cells ('germinal centre B-like DLBCL'); the second type expressed genes normally induced during in vitro activation of peripheral blood B cells ('activated B-like DLBCL'). Patients with germinal centre B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL. The molecular classification of tumours on the basis of gene expression can thus identify previously undetected and clinically significant subtypes of cancer.

9,493 citations


"Challenges translating breast cance..." refers methods in this paper

  • ...Similar approaches have been employed in the study of lymphomas...

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Journal ArticleDOI
TL;DR: The 10-year and 15-year effects of various systemic adjuvant therapies on breast cancer recurrence and survival are reported and it is found that the cumulative reduction in mortality is more than twice as big at 15 years as at 5 years after diagnosis.

6,309 citations

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