Mammographic Density and Expression of the Genes Involved in the de novo Cholesterol Biosynthesis Mammographic density and cholesterol biosynthesis

Danila Coradini (1)
(1) Laboratory of Medical Statistics and Biometry, Department of Clinical Sciences and Community Health, Campus Cascina Rosa, University of Milan, Italy, Italy

Abstract

Background: This in silico study investigated the association between the local biosynthesis of cholesterol and mammographic density, the major risk of developing breast cancer, as a function of the three cellular components of breast tissue (epithelium, fatty, and non-fatty stroma).


Methods: The study compared the expression of 7 genes (HMGCR, FDPS, FDFT1, GGPS1, SQLE, LSS, and SREBF2) involved in the de novo cholesterol biosynthesis, first, according to the radiological density (dense vs. non-dense breast) and, then, according to the cellular components of breast tissue, regardless the radiological classification.


Results: HMGCR, SQLE, and SBREF2 were significantly more expressed in radiologically dense than in non-dense breasts (-1.70 vs. -1.41, P=0.0028; -1.20 vs. -1.11, P=0.0501; -3.63 vs. -3.31 P=0.0003; -0.92 vs. -0.76, P=0.0271, respectively). When the samples were reclassified based on their cellular components as highly fatty and highly non-fatty, HMGCR, SQLE, and SBREF2 were significantly more expressed in highly non-fatty samples (-1.48 vs. -1.94, P<0.0001; -3.39 vs. -4.18, P<0.0001; -0.77 vs. -0.94, P=0.0103, respectively) whereas LSS was overexpressed in high fatty ones (0.28 vs. -0.60, P<0.0001). Besides, while in the highly non-fatty subgroup SREBF2 was positively associated with both HMGCR (r=0.53, P<0.0001) and SQLE (r=0.73, P<0.0001), in the highly fatty subgroup these positive correlations disappeared (SREBF2*HMGCR: r=-0.19, P=0.3026) or substantially decreased (SREBF2*SQLE: r=0.41, P=0.0173).


Conclusion: Findings provide a compelling biological explanation for the clinical evidence that women with radiologically dense breasts are at a higher risk of developing cancer compared to those with non-dense breasts because of the prevalence of non-fatty tissue, where the altered expression of genes leading to an increased cholesterol production, can contribute to the transformation of epithelial cells, and support the use of mammographic density as a reliable surrogate marker to identify women who may benefit from a preventive treatment aimed at reducing cholesterol production.

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References

Boyd NF, Guo H, Martin LJ, Sun L, Stone J, Fishell E, et al. Mammographic density and the risk and detection of breast cancer. N Engl J Med. 2007;356(3):227-36. doi: 10.1056/ NEJMoa062790.

McCormack VA, dos Santos SI. Breast density and parenchymal patterns as markers of breast cancer risk: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2006;15:1159-69. doi: 10.1158/1055- 9965.EPI- 06- 0034.

Chlebowski RT, Hendrix SL, Langer RD, Stefanick ML, Gass M, Lane D, et al. Influence of estrogen plus progestin on breast cancer and mammography in healthy postmenopausal women: the women’s health initiative randomized trial. JAMA. 2003;289:3243-53. doi: 10.1001/jama.289.24.3243.

Martin LJ, Boyd NF. Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence. Breast Cancer Res. 2008;10(1):201. doi: 10.1186/bcr1831.

Maller O, Martinson H, Schedin P. Extracellular matrix composition reveals complex and dynamic stromal–epithelial interactions in the mammary gland. J Mammary Gland Biol Neoplasia. 2010;15(3):301-18. doi: 10.1007/s10911-010-9189-6.

Warren R, Lakhani SR. Can the stroma provide the clue to the cellular basis for mammographic density? Breast Cancer Res. 2003;5(5):225-7. doi: 10.1186/bcr642.

Boyd NF, Martin LJ, Bronskill M, Yaffe MJ, Duric N, Minkin S. Breast tissue composition and susceptibility to breast cancer. J Natl Cancer Inst. 2010;102:1224-37. doi: 10.1093/jnci/djq239.

Pettersson A, Hankinson SE, Willett WC, Lagiou P, Trichopoulos D, Tamimi RM. Nondense mammographic area and risk of breast cancer. Breast Cancer Res. 2011;13:R100. doi: 10.1186/bcr3041.

Lin SJ, Cawson J, Hill P, Haviv I, Jenkins M, Hopper JL, et al. Image-guided sampling reveals increased stroma and lower glandular complexity in mammographically dense breast tissue. Breast Cancer Res Treat. 2011;128(2):505-16. doi: 10.1007/s10549-011-1346-0.

Ghosh K, Brandt KR, Reynolds C, Scott CG, Pankratz VS, Riehle DL, et al. Tissue composition of mammographically dense and non-dense breast tissue. Breast Cancer Res Treat. 2012;131:267-75. doi: 10.1007/s10549- 011- 1727- 4.

Coradini, D. Interaction of de novo cholesterol biosynthesis and Hippo signaling pathway in ductal carcinoma in situ (DCIS) — Comparison with the corresponding normal breast epithelium. Transl Breast Cancer Res. 2023;4:26. doi: 10.21037/tbcr-23-42.

Coradini D, Ambrogi F, Infante G. Cholesterol de novo biosynthesis in paired samples of breast cancer and adjacent histologically normal tissue: association with proliferation index, tumor grade, and recurrence-free survival. Arch Breast Cancer. 2023;10:187-99. doi: 10.32768/abc.2023102187-199.

Coradini D, Ambrogi F. Cholesterol de novo biosynthesis: a promising target to overcome the resistance to aromatase inhibitors in postmenopausal patients with ER-positive breast cancer. Explor Med. 2023;4:1079-93. doi: 10.37349/emed.2023.00196.

Sun X, Gierach GL, Sandhu R, Williams T, Midkiff BR, Lissowska J, et al. Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer. Clin Cancer Res. 2013;19:4972-82. doi: 10.1158/1078-0432.CCR-13-0029.

Sun X, Sandhu R, Figueroa JD, Gierach GL, Sherman ME, Troester MA. Benign breast tissue composition in breast cancer patients: association with risk factors, clinical variables, and gene expression. Cancer Epidemiol Biomarkers Prev. 2014;23:2810-8. doi: 10.1158/1055-9965.EPI-14-0507.

Bjarnadottir O, Romero Q, Bendahl PO, Jirström K, Rydén L, Loman, N, et al. Targeting HMG-CoA reductase with statins in a window-of-opportunity breast cancer trial. Breast Cancer Res Treat. 2013;138:499-508. doi: 10.1007/s10549-013-2473-6.

Beckwitt CH, Brufsky A, Oltvai ZN, Wells A. Statin dugs to reduce breast cancer recurrence and mortality. Breast Cancer Res. 2018;20:144. doi: 10.1186/s13058-018-1066-z.

Stein EA, Bays H, O'Brien D, Pedicano J, Piper E, Spezzi A. Lapaquistat acetate: development of a squalene synthase inhibitor for the treatment of hypercholesterolemia. Circulation. 2011;123:1974-85. doi: 10.1161/CIRCULATIONAHA.110.975284.

Authors

Danila Coradini
danila.coradini@gmail.com (Primary Contact)
1.
Coradini D. Mammographic Density and Expression of the Genes Involved in the de novo Cholesterol Biosynthesis: Mammographic density and cholesterol biosynthesis. Arch Breast Cancer [Internet]. [cited 2024 Jul. 14];11(3). Available from: https://www.archbreastcancer.com/index.php/abc/article/view/955

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