Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Sai Man Cheung* (Corresponding Author), Kwok Shing Chan, Wenshu Zhou, Ehab Husain, Tanja Gagliardi, Yazan Masannat, Jiabao He

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Deregulation of lipid composition in adipose tissue adjacent to breast tumour is observed in ex vivo and animal models. Novel non-invasive magnetic resonance imaging (MRI) allows rapid lipid mapping of the human whole breast. We set out to elucidate the spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive (ER +) breast cancer. Thirteen participants (mean age, 62 ± [SD] 6 years) with ER + breast cancer and 13 age-matched postmenopausal healthy controls were scanned on MRI. The number of double bonds in triglycerides was computed from MRI images to derive lipid composition maps of monounsaturated, polyunsaturated, and saturated fatty acids (MUFA, PUFA, SFA). The spatial heterogeneity measures (mean, median, skewness, entropy and kurtosis) of lipid composition in the peri-tumoural region and the whole breast of participants and in the whole breast of controls were computed. The Ki-67 proliferative activity marker and CD163 antibody on tumour-associated macrophages were assessed histologically. Mann Whitney U or Wilcoxon tests and Spearman’s coefficients were used to assess group differences and correlations, respectively. For comparison against the whole breast in participants, peri-tumoural MUFA had a lower mean (median (IQR), 0.40 (0.02), p <.001), lower median (0.42 (0.02), p <.001), a negative skewness with lower magnitude (− 1.65 (0.77), p =.001), higher entropy (4.35 (0.64), p =.007) and lower kurtosis (5.13 (3.99), p =.001). Peri-tumoural PUFA had a lower mean (p <.001), lower median (p <.001), a positive skewness with higher magnitude (p =.005) and lower entropy (p =.002). Peri-tumoural SFA had a higher mean (p <.001), higher median (p <.001), a positive skewness with lower magnitude (p <.001) and lower entropy (p =.012). For comparison against the whole breast in controls, peri-tumoural MUFA had a negative skewness with lower magnitude (p =.01) and lower kurtosis (p =.009), however there was no difference in PUFA or SFA. CD163 moderately correlated with peri-tumoural MUFA skewness (rs = −.64), PUFA entropy (rs =.63) and SFA skewness (rs =.59). There was a lower MUFA and PUFA while a higher SFA, and a higher heterogeneity of MUFA while a lower heterogeneity of PUFA and SFA, in the peri-tumoural region in comparison with the whole breast tissue. The degree of lipid deregulation was associated with inflammation as indicated by CD163 antibody on macrophages, serving as potential marker for early diagnosis and response to therapy.

Original languageEnglish
Article number4699
Number of pages12
JournalScientific Reports
Volume14
DOIs
Publication statusPublished - 26 Feb 2024

Bibliographical note

Funding Information:
This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2016 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarship and is currently funded by Cancer Research UK (C68628/A28312). The funding sources were not involved in the study design, in the collection, analysis and interpretation of data, in the writing of the report nor in the decision to submit the article for publication.

Data Availability Statement

The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Keywords

  • Breast cancer
  • Heterogeneity
  • Inflammation
  • Lipid composition
  • Oestrogen receptor

Fingerprint

Dive into the research topics of 'Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer'. Together they form a unique fingerprint.

Cite this