Integrated Plasma snoRNA–Protein Network Analysis Identifies Circulating Molecular Signatures Associated with High-Risk Benign Breast Lesions and Early Breast Cancer
- 1Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, USA
- 2Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218, USA
Abstract
High-risk benign breast lesions increase subsequent breast cancer risk, yet circulating molecular patterns that distinguish them from early breast cancer remain poorly defined. We profiled plasma small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs (scaRNAs) using UMI-based small RNA sequencing in 32 plasma samples from patients with low-risk benign lesions (Be; 9), high-risk benign lesions (HB; 14), or early breast cancer (CA; 9), and integrated matched data-independent acquisition (DIA) proteomics in a subset of 20 samples (HB; 11, CA; 9). Weighted gene co-expression network analysis (WGCNA) of 475 molecular features identified 11 modules. The Yellow module contained 25 snoRNAs/scaRNAs and 26 proteins and was enriched for extracellular matrix (ECM), blood microparticle, platelet, and serine-type endopeptidase inhibitor functions. An exploratory Yellow-module-focused analysis identified 10 snoRNAs with nominally lower abundance in CA than in HB (p < 0.05), showing concordant directions of differential abundance with the global analysis. The strength of differential RNA evidence correlated with mean intramodular RNA–protein correlation (Spearman ρ = 0.788, p = 2.85 × 10−6). External snoDB target mapping supported 28.6% of the exploratory network edges, including SNORD38A–FN1, SNORA73B–LAMB1, SNORD22–LAMB1, and SNORD22–NCAM1. Integration of differential plasma snoRNA profiling, cross-omic network analysis, and experimentally observed snoRNA interaction data indicated convergence on ECM/collagen and platelet/coagulation biology. These candidate snoRNA–protein axes may characterize differences in the circulating molecular states of CA and HB.
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BibTeX
@article{jijiwa2026integrated,
title = {{Integrated Plasma snoRNA–Protein Network Analysis Identifies Circulating Molecular Signatures Associated with High-Risk Benign Breast Lesions and Early Breast Cancer}},
author = {Mayumi Jijiwa and Vedbar S. Khadka and Matthew Huo and Lauren Higa and Shaina Young and Youping Deng},
journal = {International Journal of Molecular Sciences},
year = {2026},
month = oct,
doi = {10.3390/ijms27219530},
url = {https://www.mdpi.com/1422-0067/27/21/9530},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Integrated Plasma snoRNA–Protein Network Analysis Identifies Circulating Molecular Signatures Associated with High-Risk Benign Breast Lesions and Early Breast Cancer
AU - Mayumi Jijiwa
AU - Vedbar S. Khadka
AU - Matthew Huo
AU - Lauren Higa
AU - Shaina Young
AU - Youping Deng
PY - 2026
DA - 2026/10/25
JO - International Journal of Molecular Sciences
DO - 10.3390/ijms27219530
UR - https://www.mdpi.com/1422-0067/27/21/9530
AB - High-risk benign breast lesions increase subsequent breast cancer risk, yet circulating molecular patterns that distinguish them from early breast cancer remain poorly defined. We profiled plasma small nucleolar RNAs (snoRNAs) and small Cajal body-specific RNAs (scaRNAs) using UMI-based small RNA sequencing in 32 plasma samples from patients with low-risk benign lesions (Be; 9), high-risk benign lesions (HB; 14), or early breast cancer (CA; 9), and integrated matched data-independent acquisition (DIA) proteomics in a subset of 20 samples (HB; 11, CA; 9). Weighted gene co-expression network analysis (WGCNA) of 475 molecular features identified 11 modules. The Yellow module contained 25 snoRNAs/scaRNAs and 26 proteins and was enriched for extracellular matrix (ECM), blood microparticle, platelet, and serine-type endopeptidase inhibitor functions. An exploratory Yellow-module-focused analysis identified 10 snoRNAs with nominally lower abundance in CA than in HB (p < 0.05), showing concordant directions of differential abundance with the global analysis. The strength of differential RNA evidence correlated with mean intramodular RNA–protein correlation (Spearman ρ = 0.788, p = 2.85 × 10−6). External snoDB target mapping supported 28.6% of the exploratory network edges, including SNORD38A–FN1, SNORA73B–LAMB1, SNORD22–LAMB1, and SNORD22–NCAM1. Integration of differential plasma snoRNA profiling, cross-omic network analysis, and experimentally observed snoRNA interaction data indicated convergence on ECM/collagen and platelet/coagulation biology. These candidate snoRNA–protein axes may characterize differences in the circulating molecular states of CA and HB.
SN - 1422-0067
ER -