Predicting response and resistance to endocrine therapy

Miller, William R.; Larionov, Alexey; Anderson, Thomas; Walker, John R.; Krause, Andreas; Evans, Dean B.; Dixon, J. M.

doi:10.1002/cncr.23187

Cited by 23 publications

(20 citation statements)

References 32 publications

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“…The most consistently differentially expressed genes (with the lowest predicted FDRs) were seen for pre-versus post-treatment matched responding samples, supporting the rationale for identifying consistent changes in individuals. Analysis of neoadjuvant letrozole treatment in a previous study also suggested responding tumours have similar, more consistent gene expression profiles, whilst nonresponding (resistant) tumours have multiple patterns of gene changes [24,47].…”

Section: Discussionmentioning

confidence: 91%

Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer

Sabine

Sims

Macaskill

et al. 2010

Breast Cancer Res Treat

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There is growing evidence that uncontrolled activation of the PI3K/Akt/mTOR pathway contributes to the development and progression of breast cancer. Inhibition of this pathway has antitumour effects in preclinical studies and efficacy in combination with other agents in breast cancer patients. The aim of this study is to characterise the effects of pre-operative everolimus treatment in primary breast cancer patients and to identify potential molecular predictors of response. Twenty-seven patients with oestrogen receptor (ER)-positive breast cancer completed 11-14 days of neoadjuvant treatment with 5-mg everolimus. Core biopsies were taken before and after treatment and analysed using Illumina HumanRef-8 v2 Expression BeadChips. Changes in proliferation (Ki67) and phospho-AKT were measured on diagnostic core biopsies/resection samples embedded in paraffin by immunohistochemistry to determine response to treatment. Patients that responded to everolimus treatment with significant reductions in proliferation (fall in % Ki67 positive cells) also had significant decreases in the expression of genes involved in cell cycle (P = 8.70E-09) and p53 signalling (P = 0.01) pathways. Highly proliferating tumours that have a poor prognosis exhibited dramatic reductions in the expression of cell cycle genes following everolimus treatment. The genes that most clearly separated responding from nonresponding pre-treatment tumours were those involved with protein modification and dephosphorylation, including DYNLRB2, ERBB4, PTPN13, ULK2 and DUSP16. The majority of ER-positive breast tumours treated with everolimus showed a significant reduction in genes involved with proliferation, these may serve as markers of response and predict which patients will derive most benefit from mTOR inhibition.

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Section: Discussionmentioning

confidence: 91%

Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer

Sabine

Sims

Macaskill

et al. 2010

Breast Cancer Res Treat

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“…These have confirmed that aromatase inhibitor treatment is associated with changes in expression of genes classically associated with oestrogen regulation such as KIAA0101, ZWINT, TFF1 and IRS1, and cell cycle progression most notably mitotic phase proteins such as CDC2, CCNB1 and CKS2. Although more frequent in clinically responding tumours, these changes also occur in clinically non-responsive tumours [24,25]. As a consequence, they are unlikely to be reliable predictors of clinical response.…”

Section: Molecular Responsementioning

confidence: 91%

“…There have been recent key publications [21][22][23][24][25]. For example, early changes in gene expression have been identified by comparing microarray analyses from paired tumour core biopsies taken before and after 14 days' neoadjuvant treatment with letrozole [21][22][23].…”

Section: Molecular Responsementioning

confidence: 99%

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Clinical, pathological, proliferative and molecular responses associated with neoadjuvant aromatase inhibitor treatment in breast cancer

Miller

2010

The Journal of Steroid Biochemistry and Molecular Biology

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“…Gene expressions were measured by microarray in biopsies of breast cancer taken before treatment, after 2 weeks of neo-adjuvant letrozole and at surgery (after 3+ month of letrozole). Full data available in Miller et al [25] Changes in proliferative and classic oestrogen-responsive genes had no strong association with clinical response-although more frequent in clinically responding tumours, fall of these genes could be detected in both clinical responders and non-responders [48,144]. More recent interrogation of a similar dataset of letrozole-treated tumours has generated a 4-gene predictive index, which was validated on an independent neo-adjuvant anastrazole dataset [145].…”

Section: Signatures To Predict Neo-adjuvant Response To Aismentioning

confidence: 95%

Prediction of Response to Aromatase Inhibitors in Breast Cancer

Larionov

Miller

2015

Resistance to Targeted Anti-Cancer Therapeutics

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Aromatase inhibitors (AIs) are major treatment options for the management of patients with breast cancer. The drugs are effective and response rates can be high. However, resistance, either primary or acquired during treatment, may occur. Optimal clinical management requires accurate predictors of response to identify those tumours, which are most likely to respond (so sparing patients with resistant tumours needless side-effects of ineffective therapy). Currently, oestrogen receptor (ER) status is the only factor used routinely to select for treatment with aromatase inhibitors, but a substantial proportion of ER-positive tumours fails treatment. There is, therefore, an urgent need to identify additional markers by which accurately to predict clinical response on an individual basis. Whilst other markers (such as progesterone receptors or HER2) have some predictive powers, individually they have limited utility for routine use. The hope is that discovery strategies based on genome-wide searches will identify novel markers that can be used as predictive indices. Molecular phenotyping of individual tumours could then be used to decide not only which patients should be treated with AIs but whether AIs should be used alone or in combination or in sequence with other targeted agents in order that clinical benefits are maximized. This chapter will focus on utility of routinely assessed biomarkers, multi-component indices and gene signatures and outline the future perspectives in studies aimed to AI response prediction.

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Predicting response and resistance to endocrine therapy

Abstract: Selection for endocrine therapy requires the identification of markers that accurately predict response/resistance. In this report, the authors review their pub-

Cited by 23 publications

References 32 publications

Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer

Gene expression profiling of response to mTOR inhibitor everolimus in pre-operatively treated post-menopausal women with oestrogen receptor-positive breast cancer

Clinical, pathological, proliferative and molecular responses associated with neoadjuvant aromatase inhibitor treatment in breast cancer

Prediction of Response to Aromatase Inhibitors in Breast Cancer

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