Imaging the main molecular biological subtypes of breast cancer: comparison of mammographic data and histological findings

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Abstract

Background. Breast cancer (BC) stands as one of the most prevalent malignancies affecting women, posing a significant threat to health and life. Timely diagnosis and treatment of BC play a pivotal role in enhancing patient survival rates.

Aim. To explore such a method of visualization of BC as mammography and the correlation of its results with the data of histological and immunohistochemical studies, and their significance in planning organ-conserving operations.

Materials and methods. The study involved 217 patients diagnosed with nodular BC (T1-2N1M0). AH patients underwent digital mammography, histological examination of biopsy and surgical specimens, and immunohistochemical analysis of tumor tissue (determination of the expression of sex hormone receptors (estrogen and progesterone), HER2/neu status and the status of the Ki-67 marker, reflecting the proliferative activity of tumor cells).

Results. Comparison of mammographic and histological/immunohistochemical findings revealed significant differences in tumor visualization among major molecular subtypes of BC. A statistically significant association (p <0.001) was established between carcinoma in situ and radiological features such as spiculated margins and calcifications on mammography.

Conclusion. Mammography emerges as an objective and accessible visualization method for BC, enabling assessment of tumor size and peritumoral region. However, for planning breast-conserving surgery for luminal and HER2-positive BC subtypes, a multimodal diagnostic approach is recommended to assess tumor spread, incorporating ultrasound and contrast-enhanced magnetic resonance imaging.

About the authors

O. S. Khodorovich

Russian Research Center of Radiology, Ministry of Health of Russia

ORCID iD: 0000-0002-6014-4597

86 Profsoyuznaya St., Moscow 117997

Russian Federation

L. B. Kanakhina

Russian Research Center of Radiology, Ministry of Health of Russia; Peoples’ Friendship University of Russia named after Patrice Lumumba

Author for correspondence.
Email: glb.1994@mail.ru
ORCID iD: 0000-0003-0260-1478

Liya Beketaevna Kanakhina

86 Profsoyuznaya St., Moscow 117997; 6 Miklukho-Maklaya St., Moscow 117198

Russian Federation

T. V. Sherstneva

Russian Research Center of Radiology, Ministry of Health of Russia

ORCID iD: 0000-0002-3261-0984

86 Profsoyuznaya St., Moscow 117997

Russian Federation

A. A. Kalinina-Masri

Russian Research Center of Radiology, Ministry of Health of Russia

ORCID iD: 0000-0002-8265-1848

86 Profsoyuznaya St., Moscow 117997

Russian Federation

Sh. M. Dibirova

Russian Research Center of Radiology, Ministry of Health of Russia; Peoples’ Friendship University of Russia named after Patrice Lumumba

ORCID iD: 0000-0001-9657-7776

86 Profsoyuznaya St., Moscow 117997; 6 Miklukho-Maklaya St., Moscow 117198

Russian Federation

References

  1. Cancer Factsheets. Available at: https://gco.iarc.who.int/today/en/fact-sheets-cancers.
  2. Clinical recommendations “Breast cancer”. Ministry of Health of Russia, 2021. (In Russ.).
  3. Mayerhoefer M.E., Materka A., Langs G. et al. Introduction to radiomics. J Nucl Med 2020;61(4):488-95. doi: 10.2967/jnumed.118.222893
  4. Gillies R.J., Kinahan P.E., Hricak H. Radiomics: Images are more than pictures, they are data. Radiology 2016;278(2):563—77. doi: 10.1148/radiol.2015151169
  5. Boisserie-Lacroix M., Hurtevent-Labrot G., Ferron S. et al. Correlation between imaging and molecular classification of breast cancers. Diagn Interv Imaging 2013;94(11):1069-80. doi: 10.1016/j.diii.2013.04.010
  6. Ko E.S., Lee B.H., Kim H.A. et al. Triple-negative breast cancer: Correlation between imaging and pathological findings. Eur Radiol 2010;20(5):1111-7. doi: 10.1007/s00330-009-1656-3
  7. Shin H.J., Kim H.H., Huh M.O. et al. Correlation between mammographic and sonographic findings and prognostic factors in patients with node-negative invasive breast cancer. Br J Radiol 2011;84(997):19-30. doi: 10.1259/bjr/92960562
  8. Chen J.H., Agrawal G., Feig B. et al. Triple-negative breast cancer: MRI features in 29 patients. Ann Oncol 2007;18(12):2042, 2043. doi: 10.1093/annonc/mdm504
  9. Rashmi S., Kamala S., Murthy S.S. et al. Predicting the molecular subtype of breast cancer based on mammography and ultrasound findings. Indian J Radiol Imaging 2018;28(3):354-61. doi: 10.4103/ijri.IJRI_78_18
  10. Sonthineni C., Mohindra N., Agrawal V. et al. Correlation of digital mammography and digital breast tomosynthesis features of self-detected breast cancers with human epidermal growth factor receptor type 2/neu status. South Asian J Cancer 2019;8(3):140-4. doi: 10.4103/sajc.sajc_300_18
  11. Taneja S., Evans A.J., Rakha E.A. et al. The mammographic correlations of a new immunohistochemical classification of invasive breast cancer. Clin Radiol 2008;63(11):1228-35. doi: 10.1016/j.crad.2008.06.006
  12. Yamaguchi J., Ohtani H., Nakamura K. et al. Prognostic impact of marginal adipose tissue invasion in ductal carcinoma of the breast. Am J Clin Pathol 2008;130:382-8. doi: 10.1309/MX6KKA1UNJ1YG8VN
  13. Tchou J., Kossenkov A.V., Chang L. et al. Human breast cancer associated fibroblasts exhibit subtype specific gene expression profiles. BMC Med Genomics 2012;5:39. doi: 10.1186/1755-8794-5-39
  14. Park S.Y., Kim H.M., Koo J.S. Differential expression of cancer- associated fibroblast-related proteins according to molecular subtype and stromal histology in breast cancer. Breast Cancer Res Treat 2015;149:727-41. doi: 10.1007/s10549-015-3291-9
  15. Liu S., Wu X.D., Xu W.J. et al. Is There a correlation between the presence of a spiculated mass on mammogram and luminal a subtype breast cancer? Korean J Radiol 2016;17(6):846-52. doi: 10.3348/kjr.2016.17.6.846
  16. Popova A.Yu., Gazhonova V.E., Demidov S.M., Kazantseva N.V. Radiomic characteristics of different biotypes of stage T1 breast cancer. Luchevaya diagnostika, luchevaya terapiya = Radiodiagnostics, Radiotherapy 2023;6(4):34-41. (In Russ.).
  17. Cen D., Xu L., Li N. et al. BI-RADS 3-5 microcalcifications can preoperatively predict breast cancer HER2 and luminal a molecular subtype. Oncotarget 2017;8:13855-62. doi: 10.18632/oncotarget.14655
  18. Patel T.A., Puppala M., Ogunti R.O. et al. Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods. Cancer 2017;123:114-21. doi: 10.1002/cncr.30245

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