The online version of this article (https://doi.org/10.1186/s13058-018-1040-9) contains supplementary material, which is available to authorized users.
Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0–5-year and 5–10-year follow-up separately are more prognostic than a single signature optimised for 10 years.
Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2− samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2− tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0–10, 0–5 and 5–10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449.
Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set.
The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2− breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected.
Additional file 1: Methods. Additional methods. (DOCX 21 kb)13058_2018_1040_MOESM1_ESM.docx
Additional file 2: Table S1. List of 585 candidate genes. Table S2. List and identifiers for the 747-patient microarray expression data cohort. Table S3. List of 454 Affymetrix probes studied. Table S4. List of 212 genes significantly prognostic (p < 0.01) in any of the three time periods in the microarray data. Table S5. List of 88 genes by multivariable selections in any of the three time periods in the microarray data. Nodal status was used as a covariate in the regressions. Table S6. List of 17 genes manually removed from the multivariable list. Table S7. List of 29 genes added to the candidate list. Table S8. Details of the 100-probe NanoString code set used in TransATAC. Table S9. HRs, CIs and p values for the 92 genes assessed in TransATAC in univariate analyses. (XLSX 130 kb)13058_2018_1040_MOESM2_ESM.xlsx
Additional file 3: Figure S1. Forest plot of HRs and CIs for the 92 genes assessed in TransATAC in univariate analyses. Asterisk denotes significance. (PDF 1497 kb)13058_2018_1040_MOESM3_ESM.pdf
Additional file 4: Table S10. Likelihood ratio (LR) χ2 and p values for CTS and 10-year signature in three groups of POLAR validation set for 0–5 and 5–10 years of follow-up. Both univariate and multivariable analyses are presented for years 0–10, years 0–5, and years 5–10 separately. LR test based on Cox proportional hazards models for univariate and multivariable analyses. Differences in LR values (ΔLRχ2) were used. CTS was used as a covariate in the multivariable regressions. POLAR Molecular Predictors Of early versus LAte Recurrence in ER-positive breast cancer, CTS Clinical Treatment Score. (DOCX 15 kb)13058_2018_1040_MOESM4_ESM.docx
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- Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer
Adam R. Brentnall
Maggie Chon U. Cheang
- BioMed Central
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