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. 2023 Jul;200(2):293-304.
doi: 10.1007/s10549-023-06974-4. Epub 2023 May 24.

Vessel size as a marker of survival in estrogen receptor positive breast cancer

Vladan Milosevic  1 , Reidunn J Edelmann  2   3 , Ingeborg Winge  2 , Carina Strell  4 , Artur Mezheyeuski  4 , Gøril Knutsvik  2   3 , Cecilie Askeland  2   3 , Elisabeth Wik  2   3 , Lars A Akslen #  2   3 , Arne Östman #  2   5
Affiliations

Vessel size as a marker of survival in estrogen receptor positive breast cancer

Vladan Milosevic et al. Breast Cancer Res Treat. 2023 Jul.

Abstract

Purpose: Angiogenesis is crucial for tumor growth and is one of the hallmarks of cancer. In this study, we analyzed microvessel density, vessel median size, and perivascular a-SMA expression as prognostic biomarkers in breast cancer.

Methods: Dual IHC staining was performed where alpha-SMA antibodies were used together with antibodies against the endothelial cell marker CD34. Digital images of stainings were analyzed to extract quantitative data on vessel density, vessel size, and perivascular alpha-SMA status.

Results: The analyses in the discovery cohort (n = 108) revealed a statistically significant relationship between large vessel size and shorter disease-specific survival (p = 0.007, log-rank test; p = 0.01, HR 3.1; 95% CI 1.3-7.4, Cox-regression analyses). Subset analyses indicated that the survival association of vessel size was strengthened in ER + breast cancer. To consolidate these findings, additional analyses were performed on a validation cohort (n = 267) where an association between large vessel size and reduced survival was also detected in ER + breast cancer (p = 0.016, log-rank test; p = 0.02; HR 2.3, 95% CI 1.1-4.7, Cox-regression analyses).

Conclusion: Alpha-SMA/CD34 dual-IHC staining revealed breast cancer heterogeneity regarding vessel size, vessel density, and perivascular a-SMA status. Large vessel size was linked to shorter survival in ER + breast cancer.

Keywords: Alpha-SMA; Angiogenesis; CD34.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1
Fig. 1
A Intertumoral heterogeneity in vessel median size, vessel density, and fraction of a-SMA covered vessels in the “whole section” cohort. Double staining with CD34 and a-SMA showing examples of high and low cases regarding vessel size, vessel density, and fraction of a-SMA covered vessels between different cases in the “whole section” cohort. Variables were dichotomized as “low (0–50%)” group and “high (> 50%)” group, based on the median value. Size bars correspond to 100 μm. B Intertissue metric correlations. Spearman correlation coefficients representing associations between vessel median size, vessel density, and fraction of a-SMA covered vessels in the “whole section” cohort. *p < 0.05, **p < 0.001
Fig. 2
Fig. 2
Association of vessel median diameter and cumulative survival (breast cancer-related death as endpoint) in the “whole section” cohort. Vessel median size variable was dichotomized as “low (0–50%)” and “high (> 50%)” group based on the median value. Figure shows Kaplan–Meier curve for cumulative survival (breast cancer-related death as endpoint) represented on the base of the median defined dichotomous values (Log-Rank test, p = 0.007; Cox-regression analyses, p = 0.01, HR 3.1 (95% CI 1.3–7.4))
Fig. 3
Fig. 3
Impact of high vessel diameter on poor survival in different clinicopathologic subsets. HR and confidence intervals presented as the forest plot. *p < 0.05. p values are calculated based on Wald test; HR is based on cause-specific Cox-regression model
Fig. 4
Fig. 4
A Examples of breast cancer TMA cores with low-vessel median size (upper row) and high-vessel median size (lower row). Each case is represented by three cores belonging to the same case. Blue = a-SMA, red = CD34. The size bar corresponds to 100 μm. Arrows pointing to “Cavitary structures” [61]. B Association of vessel median diameter and cumulative survival (breast cancer related death as endpoint) in the ER + breast cancer “TMA” cohort. Vessel median size variable was dichotomized as “low (0–50%)” and “high (> 50%)” group based on the median value. Figures show Kaplan–Meier curve for cumulative survival (breast cancer related death as endpoint) represented on the base of the median defined dichotomous values. (Log-Rank test, p = 0.016; Cox-regression analyses (Wald test), p = 0.02; HR 2.3 (95% CI 1.1–4.7))
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