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Interplay between AIB1 genotypes and radiotherapy in a Swedish population-based breast cancer cohort

Wiberg, Alexandra LU ; Ebbesen, Louise LU ; Godina, Christopher LU orcid ; Isaksson, Karolin LU and Jernström, Helena LU (2026) In Discover Oncology 17(1).
Abstract

Purpose: Host factors, including genetic factors, are underutilized in breast cancer treatment selection. This study aimed to investigate AIB1 genotypes as pharmacogenetic markers for adjuvant breast cancer treatment. The prognostic impact of three functional polymorphisms associated with altered mRNA expression rs6094752 (low expression), rs2230782 (low expression) and rs2076546 (high expression) was studied in different treatment groups. Methods: AIB1 genotyping was performed using iPLEX™ on 576 breast cancer patients included 2002 − 2008 in Lund, Sweden, who were followed for up to 15 years. Clinicopathological data was obtained from questionnaires and patient charts. Diplotypes were constructed. Survival analyses were conducted with... (More)

Purpose: Host factors, including genetic factors, are underutilized in breast cancer treatment selection. This study aimed to investigate AIB1 genotypes as pharmacogenetic markers for adjuvant breast cancer treatment. The prognostic impact of three functional polymorphisms associated with altered mRNA expression rs6094752 (low expression), rs2230782 (low expression) and rs2076546 (high expression) was studied in different treatment groups. Methods: AIB1 genotyping was performed using iPLEX™ on 576 breast cancer patients included 2002 − 2008 in Lund, Sweden, who were followed for up to 15 years. Clinicopathological data was obtained from questionnaires and patient charts. Diplotypes were constructed. Survival analyses were conducted with Kaplan-Meier curves, Log-Rank tests and multivariable Cox regression. Results: The most common AIB1 diplotypes were CGA_CGA (61.4%), CGA_CCA (16.4%), and CGA_CGG (12.0%). The remaining diplotypes were classified as ‘Rare’. Any breast cancer event was reported in 144 patients. There were significant interactions between radiotherapy and CGA_CGA (Pinteraction=0.033) or CGA_CCA (Pinteraction=0.017) on prognosis. In the 226 non-radiotherapy-treated patients, CGA_CGA carriers had the best prognosis, and CGA_CCA carriers the worst prognosis, with two-fold risk of breast cancer events in CGA_CCA compared with CGA_CGA carriers. In the 350 radiotherapy-treated patients, CGA_CGA was not associated with prognosis while CGA_CCA conferred 40% lower event risk. No other significant interactions between AIB1 diplotypes and chemotherapy, tamoxifen or aromatase inhibitors on prognosis were observed. Conclusion: AIB1 genotypes conferred differential prognostic impact depending on adjuvant radiotherapy. If confirmed, AIB1 merits further evaluation as a putative pharmacogenetic marker to identify patients that benefit the most from radiotherapy.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Adjuvant treatment, AIB1 genotypes, Breast cancer, Prognosis
in
Discover Oncology
volume
17
issue
1
article number
159
publisher
Springer Science and Business Media B.V.
external identifiers
  • scopus:105028694312
  • pmid:41483282
ISSN
2730-6011
DOI
10.1007/s12672-025-04370-6
language
English
LU publication?
yes
id
68db6a0e-07f0-43b6-91c4-3cc5191f0f4b
date added to LUP
2026-02-17 13:27:11
date last changed
2026-02-18 03:37:11
@article{68db6a0e-07f0-43b6-91c4-3cc5191f0f4b,
  abstract     = {{<p>Purpose: Host factors, including genetic factors, are underutilized in breast cancer treatment selection. This study aimed to investigate AIB1 genotypes as pharmacogenetic markers for adjuvant breast cancer treatment. The prognostic impact of three functional polymorphisms associated with altered mRNA expression rs6094752 (low expression), rs2230782 (low expression) and rs2076546 (high expression) was studied in different treatment groups. Methods: AIB1 genotyping was performed using iPLEX™ on 576 breast cancer patients included 2002 − 2008 in Lund, Sweden, who were followed for up to 15 years. Clinicopathological data was obtained from questionnaires and patient charts. Diplotypes were constructed. Survival analyses were conducted with Kaplan-Meier curves, Log-Rank tests and multivariable Cox regression. Results: The most common AIB1 diplotypes were CGA_CGA (61.4%), CGA_CCA (16.4%), and CGA_CGG (12.0%). The remaining diplotypes were classified as ‘Rare’. Any breast cancer event was reported in 144 patients. There were significant interactions between radiotherapy and CGA_CGA (P<sub>interaction</sub>=0.033) or CGA_CCA (P<sub>interaction</sub>=0.017) on prognosis. In the 226 non-radiotherapy-treated patients, CGA_CGA carriers had the best prognosis, and CGA_CCA carriers the worst prognosis, with two-fold risk of breast cancer events in CGA_CCA compared with CGA_CGA carriers. In the 350 radiotherapy-treated patients, CGA_CGA was not associated with prognosis while CGA_CCA conferred 40% lower event risk. No other significant interactions between AIB1 diplotypes and chemotherapy, tamoxifen or aromatase inhibitors on prognosis were observed. Conclusion: AIB1 genotypes conferred differential prognostic impact depending on adjuvant radiotherapy. If confirmed, AIB1 merits further evaluation as a putative pharmacogenetic marker to identify patients that benefit the most from radiotherapy.</p>}},
  author       = {{Wiberg, Alexandra and Ebbesen, Louise and Godina, Christopher and Isaksson, Karolin and Jernström, Helena}},
  issn         = {{2730-6011}},
  keywords     = {{Adjuvant treatment; AIB1 genotypes; Breast cancer; Prognosis}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{Springer Science and Business Media B.V.}},
  series       = {{Discover Oncology}},
  title        = {{Interplay between AIB1 genotypes and radiotherapy in a Swedish population-based breast cancer cohort}},
  url          = {{http://dx.doi.org/10.1007/s12672-025-04370-6}},
  doi          = {{10.1007/s12672-025-04370-6}},
  volume       = {{17}},
  year         = {{2026}},
}