DNA Methylation and Prospects for Predicting the Therapeutic Effect of Neoadjuvant Chemotherapy for Triple-Negative and Luminal B Breast Cancer

Author:

Sigin Vladimir O.1,Kalinkin Alexey I.1,Nikolaeva Alexandra F.1,Ignatova Ekaterina O.12,Kuznetsova Ekaterina B.13,Chesnokova Galina G.1,Litviakov Nikolai V.4,Tsyganov Matvey M.4ORCID,Ibragimova Marina K.4,Vinogradov Ilya I.56,Vinogradov Maxim I.5,Vinogradov Igor Y.6,Zaletaev Dmitry V.1,Nemtsova Marina V.13,Kutsev Sergey I.1,Tanas Alexander S.1,Strelnikov Vladimir V.1

Affiliation:

1. Research Centre for Medical Genetics, 115522 Moscow, Russia

2. N. N. Blokhin National Medical Research Center of Oncology, 115478 Moscow, Russia

3. Laboratory of Medical Genetics, I. M. Sechenov First Moscow State Medical University (Sechenov University), 119992 Moscow, Russia

4. Cancer Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, 634009 Tomsk, Russia

5. Regional Clinical Oncology Dispensary, 390011 Ryazan, Russia

6. Department of Pathological Anatomy, Ryazan State Medical University, 390026 Ryazan, Russia

Abstract

Despite advances in the diagnosis and treatment of breast cancer (BC), the main cause of deaths is resistance to existing therapies. An approach to improve the effectiveness of therapy in patients with aggressive BC subtypes is neoadjuvant chemotherapy (NACT). Yet, the response to NACT for aggressive subtypes is less than 65% according to large clinical trials. An obvious fact is the lack of biomarkers predicting the therapeutic effect of NACT. In a search for epigenetic markers, we performed genome-wide differential methylation screening by XmaI-RRBS in cohorts of NACT responders and nonresponders, for triple-negative (TN) and luminal B tumors. The predictive potential of the most discriminative loci was further assessed in independent cohorts by methylation-sensitive restriction enzyme quantitative PCR (MSRE-qPCR), a promising method for the implementation of DNA methylation markers in diagnostic laboratories. The selected most informative individual markers were combined into panels demonstrating cvAUC = 0.83 (TMEM132D and MYO15B markers panel) for TN tumors and cvAUC = 0.76 (TTC34, LTBR and CLEC14A) for luminal B tumors. The combination of methylation markers with clinical features that correlate with NACT effect (clinical stage for TN and lymph node status for luminal B tumors) produces better classifiers, with cvAUC = 0.87 for TN tumors and cvAUC = 0.83 for luminal B tumors. Thus, clinical characteristics predictive of NACT response are independently additive to the epigenetic classifier and in combination improve prediction.

Funder

Russian Science Foundation

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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