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Randomized Controlled Trial
. 2019 Dec 31;22(1):2.
doi: 10.1186/s13058-019-1223-z.

Impact of aromatase inhibitor treatment on global gene expression and its association with antiproliferative response in ER+ breast cancer in postmenopausal patients

Affiliations
Randomized Controlled Trial

Impact of aromatase inhibitor treatment on global gene expression and its association with antiproliferative response in ER+ breast cancer in postmenopausal patients

Qiong Gao et al. Breast Cancer Res. .

Abstract

Background: Endocrine therapy reduces breast cancer mortality by 40%, but resistance remains a major clinical problem. In this study, we sought to investigate the impact of aromatase inhibitor (AI) therapy on gene expression and identify gene modules representing key biological pathways that relate to early AI therapy resistance.

Methods: Global gene expression was measured on pairs of core-cut biopsies taken at baseline and at surgery from 254 patients with ER-positive primary breast cancer randomised to receive 2-week presurgical AI (n = 198) or no presurgical treatment (control n = 56) from the POETIC trial. Data from the AI group was adjusted to eliminate artefactual process-related changes identified in the control group. The response was assessed by changes in the proliferation marker, Ki67.

Results: High baseline ESR1 expression associated with better AI response in HER2+ tumours but not HER2- tumours. In HER2- tumours, baseline expression of 48 genes associated with poor antiproliferative response (p < 0.005) including PERP and YWHAQ, the two most significant, and the transcription co-regulators (SAP130, HDAC4, and NCOA7) which were among the top 16 most significant. Baseline gene signature scores measuring cell proliferation, growth factor signalling (ERBB2-GS, RET/GDNF-GS, and IGF-1-GS), and immune activity (STAT1-GS) were significantly higher in poor AI responders. Two weeks of AI caused downregulation of genes involved in cell proliferation and ER signalling, as expected. Signature scores of E2F activation and TP53 dysfunction after 2-week AI were associated with poor AI response in both HER2- and HER2+ patients.

Conclusions: There is a high degree of heterogeneity in adaptive mechanisms after as little as 2-week AI therapy; however, all appear to converge on cell cycle regulation. Our data support the evaluation of whether an E2F signatures after short-term exposure to AI may identify those patients most likely to benefit from the early addition of CDK4/6 inhibitors.

Trial registration: ISRCTN, ISRCTN63882543, registered on 18 December 2007.

Keywords: Aromatase inhibition; Breast cancer; Oestrogen receptor; Residual proliferation; Resistance; Signatures.

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Conflict of interest statement

MD and LAM receive academic funding from Pfizer, Puma Biotechnology Inc., and AstraZeneca. MD receives honoraria from Myriad Genetics and speaker’s bureau of Roche; is a consultant and advisory board member of Radius, GTx, and Orion Pharma; and has received remuneration from the ICR rewards to Inventors Schemes. MCUC has a patent: US Patent No. 9,631,239 with royalties paid. All other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
a POETIC schema, study design POETIC Trial PeriOperative Endocrine Therapy for Individualised Care. b Individual Ki67 changes in HER2− (n = 159) AI-treated groups. c Individual Ki67 changes in HER2+ (n = 26) AI-treated groups. The boxes indicate the median and interquartile ranges
Fig. 2
Fig. 2
Heatmap (Pearson, complete) of 129 genes whose baseline expression is significantly different (p < 0.001) between CCCA and noCCCA based on 155 HER2− of the 178 AI-treated samples. The gene expression across 155 samples was centred and scaled. Red denotes the gene expression in a sample is greater than the mean, blue denotes less than the mean. The tumours are ordered according to the residual level of Ki67
Fig. 3
Fig. 3
Volcano plot highlighting the genes that were identified differentially expressed (p < 0.005) after AI treatment. Based on the difference of the expression mean changes (log2(Surgery/Baseline)) of paired samples between AI-treated and control. a Nine hundred ninety genes (n = 363 upregulated, n = 627 downregulated) in HER2− tumours (902 annotated genes). Number of AI-treated pairs, n = 135; control pairs, n = 46. b Eighty genes (n = 20 upregulated, n = 60 downregulated) in HER2+ tumours (71 annotated genes). Number of AI-treated pairs, n = 22; control pairs, n = 8. The p values range from 1 to a limited minimum value of 1.0E−07 was shown on the y-axis in a scale of −log10(p value)
Fig. 4
Fig. 4
Unsupervised hierarchical clustering (Pearson, ward.D2) of 902 genes whose expression was significantly regulated after 2 weeks of treatment in HER2− tumours. And the overrepresented pathways (FDR < 5%) identified by pathway analysis (IPA). a The relative change in the gene expression across 134 HER2− tumours was standardised (centred and scaled). Red denotes the standardised z-score > 0, an increase in gene expression in a tumour after AI treatment compared to the average “relative changes” of the gene across all the 134 tumours; blue denotes the standardised z-score < 0, a decrease in gene expression in a tumour after AI treatment compared to the average “relative changes” of the gene across all the 134 tumours. b The 25 canonical pathways were significantly enriched (FDR < 5%). Positive z-score shown in orange colour specifies activated pathways; negative z-score shown in blue colour specifies inhibited pathways after AI treatment

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