Articol susținut de S.N.O.M.R.

Isabela Anda Komporaly^1,2, Adelina Silvana Gheorghe^3,*, Elena Adriana Iovănescu ¹, Bogdan Georgescu ^1,4 and Dana Lucia Stănculeanu^1,3

1. Department of Oncology, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; isabelakomporaly@gmail.com (I.A.K.); dumitrescu.elena.adriana@gmail.com (E.A.I.); dr_bogdan.georgescu@icloud.com (B.G.); dlstanculeanu@gmail.com (D.L.S.)
2. Memorial Băneasa Hospital, 013812 Bucharest, Romania
3. Department of Medical Oncology I, “Prof. Dr. Alexandru Trestioreanu” Institute of Oncology, 022328 Bucharest, Romania
4. Neolife Hospital, 077190 Bucharest, Romania
* Correspondence: adelina.silvana.gheorghe@gmail.com

Int. J. Mol. Sci. 2026, 27, 7799

DOI: https://doi.org/10.3390/ijms27177799

Abstract:
Neoadjuvant chemotherapy (NAC) is the standard of care for locally advanced breast cancer, yet the molecular predictors of pathological response remain incompletely defined, particularly regarding microRNA (miRNA) dynamics. We investigated paired pre- and post-NAC miRNA expression profiles in relation to molecular subtype, residual cancer burden (RCB), and clinical timing parameters. Seven patients with invasive breast cancer (Luminal A n = 3, Luminal B n = 1, TNBC n = 2, HER2+ n = 1) who received NAC (AC-T or TCHP) were included in this pilot study. Small-RNA sequencing (NovaSeq X Plus, CeGaT GmbH, project S17293) was performed on 14 FFPE specimens (7 pre-NAC core needle biopsies, 7 post-NAC surgical specimens). Differential expression analysis used the paired Wilcoxon signed-rank test with Benjamini–Hochberg correction. Spearman correlations assessed associations between miRNA expression, RCB score, and clinical timing intervals. Candidate miRNAs were subsequently annotated using experimentally validated miRNA–target interactions. After filtering (≥ three counts in ≥ three samples), 759 miRNAs were analysed. No miRNA reached strict significance (padj < 0.05, |log2FC| > 1.0) after multiple testing correction, consistent with the limited statistical power (n = 7). Under exploratory criteria (p < 0.10, |log2FC| > 0.5), 156 candidate miRNAs were identified: 70 upregulated and 86 downregulated post-NAC. Leading candidates included hsa-miR139-3p (+2.60), hsa-miR-139-5p (+2.36), and hsa-miR-1323 (+1.55) as upregulated, and hsamiR-429 (−2.53), hsa-miR-141-3p (−1.79), and hsa-miR-1277-5p (−1.25) as downregulated post-NAC. The single patient achieving the lowest residual disease burden (P3, Luminal B, RCB-I, score 1.32) displayed a distinct pre-treatment miRNA profile, separating from all other pre-NAC specimens on principal component analysis and characterised by higher baseline hsa-miR-139-3p/-5p and lower baseline hsa-miR-429 and hsa-miR-141-3p expression, suggesting that baseline miRNA expression paĴerns may contribute to differential chemotherapy response. RCB score showed a non-significant positive trend with post-NAC Ki-67 (ρ = +0.71, p = 0.07). This pilot study identifies NAC-modulated candidate miRNAs in breast cancer and establishes a paired FFPE-based small-RNA-sequencing workflow applicable in routine clinical seĴings. The distinct pre-treatment profile of the single best responder generates the testable hypothesis that baseline expression of tumour suppressor miRNAs of the miR-139 family, together with low miR-200-family expression, may track chemosensitivity. As no candidate reached statistical significance after multiple testing correction and none has been validated in an independent cohort or by an orthogonal method, all findings are exploratory and hypothesis-generating. The results support larger prospective validation studies examining miRNA signatures as predictive biomarkers of NAC response across breast cancer molecular subtypes.
Keywords: breast cancer; microRNA; neoadjuvant chemotherapy; small-RNA sequencing; residual cancer burden; pathological complete response; molecular subtypes; biomarkers; translational oncology