Circulating levels of PCSK9, ANGPTL3 and Lp(a) in stage III breast cancers

Abstract

Background / synopsis: Cholesterol and lipids play an important role in sustaining tumor growth and metastasis in a large variety of cancers. ANGPTL3 and PCSK9 modify circulating cholesterol levels, thus availability of lipids to peripheral cells. Little is known on the role, if any, of circulating lipid-related factors such as PCSK9, ANGPTL3 and lipoprotein (a) in cancers.

Objective/purpose: To compare circulating levels of PCSK9, ANGPTL3, and Lp(a) in women with stage III breast cancer versus women with premalignant or benign breast lesions.

Methods: Twenty-three plasma samples from women diagnosed with a stage III breast cancer (ductal, lobular or mixed) were matched for age with twenty-three plasma samples from women bearing premalignant (stage 0, n = 9) or benign (n = 14) breast lesions. The lipid profile (Apo B, total cholesterol, HDL cholesterol and triglycerides levels) and Lp(a) were measured on a Roche Modular analytical platform, whereas LDL levels were calculated with the Friedewald formula. ANGPTL3 and PCSK9 plasma levels were quantitated by ELISA. All statistical analyses were performed using SAS software version 9.4.

Results: PCSK9 levels were significantly higher in women with stage III breast cancer compared to age-matched counterparts presenting a benign lesion (95.9 ± 27.1 ng/mL vs. 78.5 ± 19.3 ng/mL, p < 0.05, n = 14). Moreover, PCSK9 levels positively correlated with breast disease severity (benign, stage 0, stage III) (Rho = 0.34, p < 0.05, n = 46). In contrast, ANGPTL3 and Lp(a) plasma levels did not display any association with breast disease status and lipids did not correlate with disease severity.

Conclusion: In this small cohort of 46 women, PCSK9 levels tended to increase with the severity of the breast disease. Given that PCSK9 plays an important role in maintaining cholesterolemia, and a potential role in tumor evasion, present results warrant further investigation into a possible association between PCSK9 levels and breast cancer severity in larger cohorts of women.

Keywords: ANGPTL3; Breast cancer; Cancer progression; Endogenous lipid metabolism; Lipoprotein(a); PCSK9.

Fig. 1

ANGPTL3, Lp(a) and PCSK9 distributions between control and stage III breast cancer groups. Boxplots represent the plasma levels of each circulating factor with median and interquartile range. Dotted lines connect age-matched individuals. Student T-test and Wilcoxon signed rank test did not yield any significant difference between stage III breast cancer and control plasma level distributions (p > 0.05). Stage III constituted the case group (n = 23). Control group combined benign pathology of the breast (n = 14) with stage 0 breast cancers (n = 9)

Fig. 2

A ANGPTL3 and (B) Lp(a) circulating level distributions after control group stratification. Distributions between benign disease of the breast (n = 14), stage 0 (n = 9) and stage III (n = 23) breast tumor groups are represented as box plots. No significant difference was found following group comparison with ANOVA or Kruskal − Wallis

Fig. 3

PCSK9 levels comparison between benign disease of the breast, stage 0 and stage III groups. A ANOVA analysis of PCSK9 levels between the three groups indicated an increase of PCSK9 with severity of the breast disease that did not reach statistical significance (p = 0.056). B Two-group comparison with Student T-test between benign disease of the breast and stage III breast tumor groups yielded a significant difference (p < 0.05) with higher PCSK9 levels in stage III breast cancer subgroup (95.9 ± 27.1 ng/mL, n = 14) compared to age-matched benign group (78.5 ± 19.3 ng/mL, n = 14). Dotted lines connect age-matched invididuals

Fig. 4

Correlation between all variables under study in the entire cohort. Relationship between age, body mass index (BMI), Insulin, C-peptide, triglycerides (Trig), Total cholesterol (Chol), HDL-cholesterol (HDL-C), non-HDL cholesterol (non-HDL), LDL-cholesterol (LDL-C), apolipoprotein B100 (Apo B), ANGPTL3, lipoprotein (a) (Lp(a)), and PCSK9 were assessed in the entire cohort. A Matrix on the left represents Spearman Rho correlation coefficients. Dark grey is indicative either of a Rho coefficient close to + 1 (positive correlation) or a Rho coefficient closer to -1 (negative correlation). White indicates an absence of correlation (coefficient equal to 0). B Matrix on the right displays the corresponding p-value for each Rho coefficient on the left. As expected, C-peptide, insulin and triglycerides show a significant correlation with BMI scores. Other statistically significant correlations include: LDL-C and its core protein Apo B, non-HDL cholesterol and LDL-C, non-HDL cholesterol and Apo B levels. Neither PCSK9, ANGPTL3 nor lipoprotein (a) show significant correlation with the rest of the lipid panel components. ANGPTL3 levels, however, appear to be significantly associated, at least partially (Rho = 0.30), with age (p-value = 0.04, n = 46)