Araştırma Makalesi

Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Sayı: 30 31 Ağustos 2026
PDF İndir
EN TR

Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Öz

Aim: To investigate the predictive value of pretreatment breast magnetic resonance imaging (MRI) findings, clinicopathological characteristics, and molecular tumor features for pathological response to neoadjuvant chemotherapy (NACT).

Method: This retrospective study included 194 patients with invasive breast cancer who underwent pretreatment breast MRI, received NACT, and subsequently underwent surgery between 2015 and 2020. Pathological response was assessed using the Miller–Payne grading system and categorized as complete/near-complete response (grades 4–5), partial response (grade 3), or limited response (grades 1–2). Quantitative and morphological MRI parameters, together with clinicopathological and molecular characteristics, were analyzed. Independent predictors of pathological response were identified using multinomial logistic regression analysis.

Results: According to the Miller–Payne classification, 80 patients (41.2%) achieved complete/near-complete response, 98 (50.5%) partial response, and 16 (8.2%) limited response. Histologic subtype, tumor grade, HER2 status, Ki-67 index, molecular subtype, ADC, BPE, tumor margins, enhancement pattern, and MSI were significantly associated with pathological response. In multivariable analysis, non-ductal histology and minimal BPE independently predicted limited versus complete/near-complete response, whereas non-luminal molecular subtype, minimal BPE, and MSI ≥429 independently predicted limited versus partial response. Lower ADC independently distinguished partial from complete/near-complete response. However, substantial overlap in biological and imaging features remained across response groups.

Conclusion: Pretreatment MRI biomarkers may provide complementary information for predicting NACT response when interpreted with clinicopathologic and molecular features. Lower ADC was not an independent predictor of limited response. The occurrence of similar biological and imaging features in both highly responsive and limited-response tumors highlights substantial treatment-response heterogeneity and supports an integrated multiparametric assessment rather than reliance on any single biomarker.

Anahtar Kelimeler

Destekleyen Kurum

The authors received no financial support for the research, authorship, and/or publication of this article.

Etik Beyan

The study was approved by the Clinical Research Ethics Committee of Istanbul Training and Research Hospital (Decision No: 3, Approval Date: January 14, 2022). The study was conducted in accordance with the ethical principles of the Declaration of Helsinki

Kaynakça

  1. 1. Cortazar P, Zhang L, Untch M, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet. 2014;384(9938):164–172. doi: 10.1016/S0140-6736(13)62422-8
  2. 2. Spring LM, Fell G, Arfe A, et al. Pathologic complete response after neoadjuvant chemotherapy and impact on breast cancer recurrence and survival: a comprehensive meta-analysis. Clin Cancer Res. 2020;26(12):2838-2848. doi: 10.1158/1078-0432.CCR-19-3492.
  3. 3. Loibl S, Poortmans P, Morrow M, Denkert C, Curigliano G. Breast cancer. Lancet. 2021;397(10286):1750-1769. doi: 10.1016/S0140-6736(20)32381-3.
  4. 4. Symmans WF, Wei C, Gould R, et al. Long-term prognostic risk after neoadjuvant chemotherapy associated with residual cancer burden and breast cancer subtype. J Clin Oncol. 2017;35(10):1049-1060. doi: 10.1200/JCO.2015.63.1010.
  5. 5. Marinovich ML, Houssami N, Macaskill P, et al. Meta-analysis of magnetic resonance imaging in detecting residual breast cancer after neoadjuvant therapy. J Natl Cancer Inst. 2013;105(5):321-333. doi: 10.1093/jnci/djs528.
  6. 6. Partridge SC, Nissan N, Rahbar H, Kitsch AE, Sigmund EE. Diffusion-weighted breast MRI: clinical applications and emerging techniques. J Magn Reson Imaging. 2017;45(2):337–355. doi: 10.1002/jmri.25479.
  7. 7. Grimm LJ. Radiomics: a primer for breast radiologists. J Breast Imaging. 2021;3(3):276–287.
  8. 8. Lambin P, Leijenaar RTH, Deist TM, et al. Radiomics: the bridge between medical imaging and personalized medicine. Nat Rev Clin Oncol. 2017;14(12):749-762.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Radyoloji ve Organ Görüntüleme

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

31 Ağustos 2026

Yayımlanma Tarihi

31 Ağustos 2026

Gönderilme Tarihi

21 Haziran 2026

Kabul Tarihi

19 Ağustos 2026

Yayımlandığı Sayı

Yıl 2026 Sayı: 30

Kaynak Göster

APA
Nazlı, M. A., Baykara Ulusan, M., Trabulus, F. D., Gürsu, R. U., Esmerer, E., & Kelten Talu, E. C. (2026). Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. Istanbul Gelisim University Journal of Health Sciences, 30, 411-425. https://doi.org/10.38079/igusabder.1975607
AMA
1.Nazlı MA, Baykara Ulusan M, Trabulus FD, Gürsu RU, Esmerer E, Kelten Talu EC. Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. IGUSABDER. 2026;(30):411-425. doi:10.38079/igusabder.1975607
Chicago
Nazlı, Mehmet Ali, Melis Baykara Ulusan, Fadime Didem Trabulus, Rıza Umar Gürsu, Emel Esmerer, ve Esra Canan Kelten Talu. 2026. “Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer”. Istanbul Gelisim University Journal of Health Sciences, sy 30: 411-25. https://doi.org/10.38079/igusabder.1975607.
EndNote
Nazlı MA, Baykara Ulusan M, Trabulus FD, Gürsu RU, Esmerer E, Kelten Talu EC (01 Ağustos 2026) Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. Istanbul Gelisim University Journal of Health Sciences 30 411–425.
IEEE
[1]M. A. Nazlı, M. Baykara Ulusan, F. D. Trabulus, R. U. Gürsu, E. Esmerer, ve E. C. Kelten Talu, “Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer”, IGUSABDER, sy 30, ss. 411–425, Ağu. 2026, doi: 10.38079/igusabder.1975607.
ISNAD
Nazlı, Mehmet Ali - Baykara Ulusan, Melis - Trabulus, Fadime Didem - Gürsu, Rıza Umar - Esmerer, Emel - Kelten Talu, Esra Canan. “Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer”. Istanbul Gelisim University Journal of Health Sciences. 30 (01 Ağustos 2026): 411-425. https://doi.org/10.38079/igusabder.1975607.
JAMA
1.Nazlı MA, Baykara Ulusan M, Trabulus FD, Gürsu RU, Esmerer E, Kelten Talu EC. Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. IGUSABDER. 2026;:411–425.
MLA
Nazlı, Mehmet Ali, vd. “Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer”. Istanbul Gelisim University Journal of Health Sciences, sy 30, Ağustos 2026, ss. 411-25, doi:10.38079/igusabder.1975607.
Vancouver
1.Mehmet Ali Nazlı, Melis Baykara Ulusan, Fadime Didem Trabulus, Rıza Umar Gürsu, Emel Esmerer, Esra Canan Kelten Talu. Integrated MRI-Derived, Pathologic, and Molecular Biomarkers for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer. IGUSABDER. 01 Ağustos 2026;(30):411-25. doi:10.38079/igusabder.1975607

 Alıntı-Gayriticari-Türetilemez 4.0 Uluslararası (CC BY-NC-ND 4.0)