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

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.


Participants
Thirteen postmenopausal participants (mean age, 62 ± [SD] 6 years) with ER + invasive ductal carcinoma and 13 age-matched postmenopausal healthy controls (mean age, 65 ± 5 years) participated in the study.Controls were recruited subsequent to participants with breast cancer and were approximately age-matched with a discrepancy less than 5 years for each participant.Participants undergoing breast conservation surgery, with tumour size larger than 10 mm in diameter on mammography, with no previous malignancies, chemotherapy or radiotherapy prior to surgery were eligible.Participants with diabetes or on statins or cholesterol control drugs were excluded.Controls were not at population risk of breast cancer or at high risk (Fig. 1).The purpose of this study is to understand the role of peri-tumoural lipid composition in postmenopausal participant in preparation for future studies into hormonal therapy, hence breast density was not controlled during recruitment.However, breast density decreases with age 23 and the current study was conducted in postmenopausal women.Subsequently only one participant and two controls with dense breast were included.

Clinical procedure
All participants underwent fasting blood tests 24 , and the samples were prepared 25 and batch-processed 26 at the Clinical Biochemistry Department of National Health Service Grampian for C-reactive protein (CRP) 27 and a full lipid profile (total cholesterol, triglycerides, high density lipoprotein (HDL), low density lipoprotein (LDL) and total cholesterol to HDL ratio).Standard clinical histopathological examination was subsequently performed to determine histological tumour size, grade and Nottingham Prognostic Index 28 .Immunostaining was conducted in a single batch for tumour cellular proliferation marker Ki-67 29 and pro-inflammatory marker CD163 antibody on tumour-associated macrophages 22 with positive controls in breast tissue, appendix and tonsil and assessed quantitatively by a consultant pathologist (EH) with 20 years of experience in breast pathology.All 13 participants completed MRI scans.The post-surgery pathologic report showed one participant with mostly ductal carcinoma in situ (DCIS); we were unable to define the peri-tumoural region, and this participant was therefore excluded from analyses.

Lipid composition mapping
All images were acquired on a 3T whole-body clinical MRI scanner (Achieva TX, Philips Healthcare, Best, Netherlands), using a 16-channel breast coil for signal detection and a body coil for uniform transmission.Both T 1 -and T 2 -weighted anatomical images were acquired from all participants with additional diffusion-weighted images performed in patients to support tumour localisation, however administration of the contrast agent was not included in the study.T 1 -weighted images were acquired using a fast field echo sequence, with echo time of 2.9 ms, repetition time of 5.7 ms, matrix of 192 × 192, pixel size of 1.25 × 1.25 mm 2 , slice thickness of 2 mm.T 2 -weighted images were acquired using a turbo spin echo sequence, with echo time of 60 ms, repetition time of 5000 ms, matrix of 192 × 192, pixel size of 1.25 × 1.25 mm 2 , slice thickness of 2 mm.Diffusion-weighted images were acquired using a pulsed gradient spin echo sequence, with two b values of 0 and 800 s/mm 2 , echo time of 60 ms, repetition time of 4000 ms, matrix of 96 × 96, pixel size of 2.5 × 2.5 mm 2 , slice thickness of 4 mm.Lipid composition images were acquired from one breast (diseased breast in patients and left breast in healthy controls) using a two-dimensional CSEI sequence 18,19 with 174 echoes, an initial echo time of 1.14 ms, echo spacing of 1.14 ms, repetition time of 200 ms, flip angle of 15°, matrix of 64 × 64, pixel size of 3.75 × 3.75 mm 2 , slice thickness of 4 mm and 30 slices.The total acquisition time was 3.5 min.

Image analysis
Image analysis was conducted in MATLAB (R2020a, MathWorks Inc., Natick, MA, USA) and ImageJ (v1.52p,National Institute of Health, Bethesda, MD, USA) 30 .The maps showing the number of double bonds in triglycerides were computed from a subset of raw data (first 16 echoes) 18 prior to the calculation of quantitative maps of MUFA, PUFA and SFA as a percentage of the total amount of lipids 18,19 .Tumour boundary was delineated in all slices of tumour region of interest on the first echo of lipid composition images, with reference to anatomical and diffusion-weighted images, by a consultant radiologist with 15 years of experience in breast MRI examinations.Stringent measures were undertaken during the delineation of tumours and generation of the peri-tumoural regions.The dilation of the tumour region of interest, extraction of the peri-tumoural region and subsequent processing of the lipid composition maps were predefined with automated scripts.Consistent with previous clinical breast imaging studies analysing tumour microenvironment 31,32 , the peri-tumoural region was defined as an outward extension of 15 mm (4 voxels) from the tumour boundary forming a three-dimensional rim around the tumour (Peri-P; see Fig. 2).Our definition of the peri-tumoural region adopted the half way point from published literature, from a thickness of 9-12 mm 32 to a thickness of 20 mm 31 .
The whole breast was defined as containing only adipose and fibroglandular tissue in controls (WB-C), with further exclusion of the tumour in participants (WB-P).The chest cavity and the subcutaneous fat were removed www.nature.com/scientificreports/from images in all participants and controls.Adipose voxels with lipid signals comprising over 60% of the total signal within regions of interest (the peri-tumoural region and the whole breast) were extracted from lipid composition maps for histogram analysis, in accordance with our prior ex vivo study to ensure adequate signalto-noise ratio for the accuracy of lipid quantification 21 .The spatial heterogeneities (mean, median, skewness, entropy and kurtosis) 11,33 were subsequently computed based on histogram distribution for each lipid constituent, using the formulae published in our prior study 21 .Skewness indicates the deviation of a distribution from the normal distribution and has both polarity and magnitude.The polarity gives an indication of the relative position of mean and median, while the magnitude estimates the distance between the two.A system with random distribution of a single chemical constituent would assume a Gaussian symmetric bell shape with skewness at zero.

Sample size and power calculation
The effect size was based on an ex vivo study 21 considering the values of spatial heterogeneity of lipid composition in peri-tumoural breast adipose tissue.The mean of peri-tumoural MUFA in tumours with low and high grading scores was 0.40 ± 0.01 and 0.38 ± 0.02 respectively.Using standardised mean difference Cohen's d, the estimated effect size was 1.2.The effect size was considered a conservative estimation and anticipated to be higher for comparison between participants and controls.With the average variance at 25% from our previous clinical data, we determined that a sample size of 12 participants per group has 80% power to detect a difference between participants and controls at a two-sided α = 0.05 significance level.

Statistical analysis
All statistical analyses were performed in the R software (v3.6.3,The R Foundation for Statistical Computing, Vienna, Austria) using 'stats' and 'Hmisc' packages.Mann Whitney U tests were performed to compare the spatial heterogeneity of lipid constituents in the whole breast of participants versus controls (WB-P vs WB-C), and in the peri-tumoural region in participants versus the whole breast in controls (Peri-P vs WB-C).Wilcoxon signed rank paired tests were performed to assess the difference in lipid constituents in the peri-tumoural region compared with the whole breast in participants (Peri-P vs WB-P).The Spearman's rank correlation coefficients (r s ) and 95% confidence intervals (CI) were used to assess correlations between the spatial heterogeneity of each lipid constituent in the peri-tumoural region and tumour size, proliferative activity marker Ki-67 and proinflammatory marker CD163 antibody on tumour-associated macrophages.P < 0.017 was considered to indicate a statistically significant difference for 3-group comparisons, after Bonferroni correction to avoid Type I errors in the multiplicity of statistical analysis.

Correlation between peri-tumoural region and tumour size
The correlation between peri-tumoural lipid composition and tumour size is shown in Table 4; all correlation was nonsignificant.

Discussion
In this in vivo investigation of peri-tumoural spatial heterogeneity of lipid composition in women with breast cancer, lipid composition maps acquired from MRI scans showed significant differences in mean, median, skewness and entropy of all lipid constituents between the peri-tumoural region and the whole breast in participants.The results demonstrated that the quantity and spatial distribution of peri-tumoural lipid composition were altered in postmenopausal women with ER + breast cancer, providing potential clinical markers to further the evidence from cellular and ex vivo studies.The difference in peri-tumoural MUFA in comparison to the whole breast in controls indicated the potential critical role of MUFA during tumour initiation.The degree of lipid deregulation was associated with CD163 antibody on tumour-associated macrophages, indicating the deployment of lipid in the peri-tumoural region as a dynamic process of inflammation during tumour progression.Since MUFA showed significant differences in all the measures of peri-tumoural spatial heterogeneity compared with the whole breast in participants, MUFA might be the primary end product in lipid deregulation in the tumour microenvironment.Specifically, the lower mean and median of peri-tumoural MUFA compared with the whole breast suggests a tumour induced local reduction in MUFA.Both the polarity and magnitude of skewness have respective physical meaning in the context of this work.In the scenario of two pools (healthy and diseased), the polarity would indicate the dominant pool, while the magnitude indicating the balance between the two.We hence point out the polarity and magnitude in the results to allow a more direct conceptualisation of the underlying biological processes.The negative skewness for MUFA in both participants and controls indicates the distribution peaking at a higher value and extending further into lower values, while the lower magnitude of skewness in the peri-tumoural region indicates a more balanced distribution centred at a lower www.nature.com/scientificreports/mean than the whole breast.Therefore, the tumour may induce regional reduction of MUFA in the breast within the adipose tissue adjacent to the tumour.The lower kurtosis and higher entropy of MUFA in the peri-tumoural region compared with the whole breast in participants indicate a more highly concentrated non-random distribution with less outliers and a more heterogeneous distribution, respectively 11,33 .It has been shown that there was a greater activity of the stearoyl-coenzyme-A desaturase-1 in ER + breast cancer cells than in ER-cells to Table 4. Correlations between peri-tumoural monounsaturated, polyunsaturated and saturated fatty acids (MUFA, PUFA, SFA) in participants and tumour size and histopathological markers.The Spearman's rank correlation coefficients (r s ) and 95% confidence intervals (CI) for peri-tumoural lipid constituents with tumour size, proliferative activity marker Ki-67 and pro-inflammatory marker CD163 antibody on tumour-associated macrophages are shown.*Denotes a statistically significant correlation since the confidence interval does not contain the null hypothesis value (0).

Spatial heterogeneity measures
Participants  34 .Thus, both the incorporation of MUFA into the tumour core to support membrane synthesis 35 and infiltration of breast carcinoma cells into peri-tumoural adipocytes 36 may lead to widespread MUFA reduction and heterogeneous spread 37 .The negative association between MUFA skewness in the peri-tumoural region and the CD163 antibody on tumour-associated macrophages suggests that spatial distribution of MUFA might impact pro-inflammatory activities.There were significant differences in all spatial heterogeneity measures of PUFA, except for kurtosis; therefore, PUFA might be the secondary end product in lipid deregulation in the peri-tumoural region.The lower mean and median of PUFA in the peri-tumoural region compared with the whole breast in participants suggests increased uptake of exogenous PUFA to sustain the higher demand from tumour proliferation 38 and pro-inflammatory eicosanoid synthesis 36 .The positive skewness across groups indicates the distribution peaking at a lower value and extending into higher values, while the higher magnitude of skewness in the peri-tumoural region indicates more unbalanced distribution with a lower mean than the whole breast.The lower entropy of PUFA in the peritumoural region compared with the whole breast in participants indicates a more homogeneous distribution.PUFA remodels lipid droplets adjacent to the endoplasmic reticulum nuclear membrane to perturb the extracellular matrix architecture in MCF-7 (Luminal A, ER +) breast cancer cell lines with comparable impact on MDA-MB-231 (TNBC, ER-) cells 39 .The association between PUFA entropy in the peri-tumoural region with the CD163 antibody on tumour-associated macrophages suggests that PUFA may be involved in pro-inflammatory activities 36 , and may therefore be a critical surrogate for inflammation.
The elevated mean and median of SFA in the peri-tumoural region compared with the whole breast in participants suggests an extrusion of SFA from the tumour, with subsequent reduction in lipotoxicity and increased membrane rigidity for enhanced survival advantage 40 , as well as resistance to cancer therapies 41 .The positive skewness for SFA across groups indicates the distribution peaking at a lower value and extending into higher values, while the lower magnitude of skewness in the peri-tumoural region indicates a more balanced distribution centred at a higher mean than the whole breast.The lower entropy of SFA in the peri-tumoural region compared with the whole breast in participants indicates a more homogeneous distribution, potentially due to the uniform export of SFA across the tumour boundary 21,41 .An increased release of SFA in the tumour microenvironment stimulates macrophages to manufacture pro-inflammatory mediators, including cyclooxygenase-2 and tumour necrosis factor alpha 42 , leading to enhanced aromatase expression in adipocytes and sustained oestrogen biosynthesis for tumour progression 43,44 .However, MCF-7 cells are less sensitive to SFA modulation during nuclear membrane remodeling compared with MDA-MB-231 cells 39 .The association between SFA skewness in the peri-tumoural region and the CD163 antibody on tumour-associated macrophages suggests that SFA export might not only alleviate cell apoptosis but further support pro-inflammatory activities 41 .Therefore, the spatial heterogeneity of peri-tumoural SFA may reflect underlying inflammation, with the potential to become biomarkers for early diagnosis and response to therapy since an elevated level of macrophages is associated with higher recurrence and poorer prognosis 45 .
This prospective study adopted strict inclusion criteria to minimise the impact of confounding factors and answer a focused research question.All participants had invasive ductal carcinoma, with Luminal A or Luminal B ER + breast cancer, stage 2A or 2B.Given that less than 3 groups were analysed, correlation analyses were not conducted on peri-tumoural lipid composition within tumour type or stage categories.Lipid composition maps were acquired from a single breast to ensure optimal shimming and high image quality, and the classification of the peri-tumoural region in participants was well-defined, yielding consistency in comparisons.A comparison between the peri-tumoural region and the whole breast in controls answered a secondary research question on the potential of aberration in lipid composition as a clinical research tool for early diagnosis, with the ultimate aim to detect anomaly in the whole breast of women with a high risk of breast cancer.Our study had limitations.First, this was a prospective study with a small cohort, and future large cohort studies are required to demonstrate the effectiveness of lipid composition as biomarkers for early diagnosis.Second, the investigation was a prospective study with recruitment of consecutive participants, with one participant and two controls with dense breast.Future cohort to focus on women with high density of the breast will be valuable.Third, this was not an interventional study, and the contribution of small but significant changes in heterogeneity of lipid composition will require future interventional studies to ascertain the clinical value of the imaging markers for determining the efficacy of hormonal therapy in postmenopausal patients with ER + breast cancer 46 .Fourth, a comparison between the peri-tumoural region and the whole breast in controls might be impacted by extreme values, although represented a tangible step forward in comparison to loosely defined regions of interest 6,7 .A refined reference to account for specific breast tissue and anatomy other than the whole breast may be devised in a future study to enhance our understanding of the role of lipids in breast cancer.

Conclusion
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.

Figure 1 .
Figure 1.Flowchart of two-group cross sectional research study design.Thirteen postmenopausal patients with oestrogen receptor-positive, invasive ductal carcinoma and 13 age-matched healthy controls were eligible at initial screening and were consented into the study.All participants and controls underwent fasting blood tests on serum full lipid profile (total cholesterol, triglycerides, high density lipoprotein (HDL), low density lipoprotein (LDL) and total cholesterol to HDL ratio) and C-reactive protein (CRP) prior to chemical shiftencoded imaging on a clinical 3T MRI scanner.Fat mapping image analysis was conducted to compute spatial heterogeneity of lipid constituents in the peri-tumoural region (Peri-P) and the whole breast of participants and controls (WB-P, WB-C).Mann Whitney U or Wilcoxon signed rank paired statistical tests were subsequently performed to compare values between the locations.MUFA monounsaturated fatty acids, PUFA polyunsaturated fatty acids, SFA saturated fatty acids.

Figure 2 .
Figure 2. Peri-tumoural and whole breast lipid composition maps, obtained from MRI scans, in a typical participant (65-year-old woman with oestrogen receptor-positive breast cancer) and a control participant (overlaid on anatomical image).(a-c) MUFA, PUFA and SFA maps in the whole breast of a control participant (WB-C).(d-f) MUFA, PUFA and SFA maps in the peri-tumoural region of a participant (Peri-P).(g-i) MUFA, PUFA and SFA maps in the whole breast of a participant (WB-P).For the control participant, the mid-sagittal slice is shown.For the participant, the slice at the greatest dimension of the tumour (central grey area) is shown.MUFA monounsaturated fatty acids, PUFA polyunsaturated fatty acids, SFA saturated fatty acids.

Figure 3 .
Figure 3.The group difference in (a) mean, (b) median, (c) skewness, (d) entropy and (e) kurtosis of MUFA, PUFA, SFA in the whole breast of control participants (WB-C) (n = 13), the peri-tumoural region (Peri-P) (n = 12) and the whole breast of participants (WB-P) (n = 12).Each dot represents a peri-tumoural or whole breast mean fraction or spatial heterogeneity, and the dots are organised in three columns corresponding to locations.All spatial heterogeneities are shown in boxplots to indicate the minimum, 25th percentile, median, 75th percentile and maximum.Mann Whitney U (participants versus control participants) and Wilcoxon signed rank paired (within participants) tests were performed between the groups.Statistical significant p values are marked by *(< .017after Bonferroni correction for multiple comparisons), **(< .01),***(< .001).'ns': not significant.MUFA monounsaturated fatty acids, PUFA polyunsaturated fatty acids, SFA saturated fatty acids.

Table 1 .
Characteristics of study participants.Descriptive statistics of controls and participants with breast cancer are shown for each group and the entire cohort.Unless otherwise noted, values are expressed as mean ± SD.Mann Whitney U tests and Fisher's exact test were conducted for group comparisons.CRP C-reactive protein, HDL high-density lipoproteins, LDL low-density lipoproteins.

Table 2 .
Tumour histology in participants with breast cancer.Histopathological findings for participants with breast cancer are shown, with quantitative data expressed as mean ± SD or median (interquartile range) and qualitative data expressed as number of positive observations.Range and group percentage are also shown respectively.Nottingham Prognostic Index is calculated using the formula: Vol.:(0123456789) Scientific Reports | (2024) 14:4699 | https://doi.org/10.1038/s41598-024-55458-ywww.nature.com/scientificreports/

Table 3 .
Peri-tumoural and whole breast monounsaturated, polyunsaturated and saturated fatty acids (MUFA, PUFA, SFA).The mean, median, skewness, entropy and kurtosis of lipid constituents were compared between participants and healthy controls.Mann Whitney U tests were conducted for comparisons 'Peri-P versus WB-C' and 'WB-P versus WB-C' .Wilcoxon signed rank paired tests were conducted for comparison 'Peri-P versus WB-P' .*Denotes a statistically significant difference after Bonferroni correction for multiple comparisons (p < .017).