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. 2021 Nov;190(2):295-305.
doi: 10.1007/s10549-021-06377-3. Epub 2021 Sep 15.

Impact of the menstrual cycle on commercial prognostic gene signatures in oestrogen receptor-positive primary breast cancer

Affiliations

Impact of the menstrual cycle on commercial prognostic gene signatures in oestrogen receptor-positive primary breast cancer

Ben P Haynes et al. Breast Cancer Res Treat. 2021 Nov.

Abstract

Purpose: Changes occur in the expression of oestrogen-regulated and proliferation-associated genes in oestrogen receptor (ER)-positive breast tumours during the menstrual cycle. We investigated if Oncotype® DX recurrence score (RS), Prosigna® (ROR) and EndoPredict® (EP/EPclin) prognostic tests, which include some of these genes, vary according to the time in the menstrual cycle when they are measured.

Methods: Pairs of test scores were derived from 30 ER-positive/human epidermal growth factor receptor-2-negative tumours sampled at two different points of the menstrual cycle. Menstrual cycle windows were prospectively defined as either W1 (days 1-6 and 27-35; low oestrogen and low progesterone) or W2 (days 7-26; high oestrogen and high or low progesterone).

Results: The invasion module score of RS was lower (- 10.9%; p = 0.098), whereas the ER (+ 16.6%; p = 0.046) and proliferation (+ 7.3%; p = 0.13) module scores were higher in W2. PGR expression was significantly increased in W2 (+ 81.4%; p = 0.0029). Despite this, mean scores were not significantly different between W1 and W2 for any of the tests and the two measurements showed high correlation (r = 0.72-0.93). However, variability between the two measurements led to tumours being assigned to different risk categories in the following proportion of cases: RS 22.7%, ROR 27.3%, EP 13.6% and EPclin 13.6%.

Conclusion: There are significant changes during the menstrual cycle in the expression of some of the genes and gene module scores comprising the RS, ROR and EP/EPclin scores. These did not affect any of the prognostic scores in a systematic fashion, but there was substantial variability in paired measurements.

Keywords: Breast cancer; Hormone receptors; Menstrual cycle; Oestrogen-regulated genes; Prognostic signatures.

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Conflict of interest statement

Mitch Dowsett received lecture fees from NanoString Technologies and served on an Agilent advisory board.

Figures

Fig. 1
Fig. 1
Changes in a RS, ROR, EP & EPclin scores and b % risk estimates of distant relapse, in paired tumour samples taken in W1 (low oestrogen and progesterone) vs. W2 (high oestrogen ± progesterone). Dotted lines indicate cut-points between risk categories
Fig. 2
Fig. 2
Comparison of changes in a RS, ROR, EP & EPclin scores and b % risk estimates of distant relapse, in paired tumour samples taken either in W1 (low oestrogen and progesterone) vs. W2 (high oestrogen ± progesterone) or in the same window
Fig. 3
Fig. 3
Changes in RS module scores in paired tumour samples taken in W1 (low oestrogen and progesterone) vs. W2 (high oestrogen ± progesterone). Tumours classified as low risk (RS < 18) are indicated in green, those at intermediate risk (RS 18–31) in yellow and those at high risk (RS > 31) in red
Fig. 4
Fig. 4
Change in % risk of distant relapse estimates between W1 (low oestrogen and progesterone) and W2 (high oestrogen ± progesterone) of the menstrual cycle for ROR, RS, EP and EPclin; a comparison and b correlation of changes. Concordant low-risk tumours indicated in green, concordant high-risk tumours in red and discordant risk tumours in orange (fully discordant) or yellow (no change in risk vs. low or high risk)

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