Pilot Study of Plasma miRNA Signature Panel for Differentiating Single vs Multiglandular Parathyroid Disease.

Publication Title

The Journal of clinical endocrinology and metabolism

Authors

Melanie Goldfarb, Center for Endocrine Tumors and Disorders, Saint John's Cancer Institute (SJCI) at Providence Saint John's Health Center (SJHC), Santa Monica, CA 90404, USAFollow
Matias A Bustos, Department of Translational Molecular Medicine, SJCI at SJHC, Santa Monica, CA 90404, USAFollow
Jamie Moon, Department of Translational Molecular Medicine, SJCI at SJHC, Santa Monica, CA 90404, USAFollow
Katherine Jackson, Center for Endocrine Tumors and Disorders, Saint John's Cancer Institute (SJCI) at Providence Saint John's Health Center (SJHC), Santa Monica, CA 90404, USAFollow
Frederick R Singer, Center for Endocrine Tumors and Disorders, Saint John's Cancer Institute (SJCI) at Providence Saint John's Health Center (SJHC), Santa Monica, CA 90404, USAFollow
Dave S B Hoon, Department of Translational Molecular Medicine, Department of Genomic Sequencing Center, SJCI at Providence SJHC, Santa Monica, CA 90404, USAFollow

Document Type

Article

Publication Date

2-18-2025

Keywords

california; santa monica; sjci

Abstract

CONTEXT: The ability to differentiate sporadic primary hyperparathyroidism (sPHPT) caused by a single parathyroid adenoma (PTA) from multiglandular parathyroid disease (MGD) preoperatively, as well as definitely diagnose sPHPT in difficult patients, would enhance surgical decision-making.

OBJECTIVE: This work aimed to identify miRNA (miR) signatures for MGD, single- and double-PTA, as well as cell-free miRNA (cfmiR) in plasma samples from patients with single-PTAs to use as biomarkers.

METHODS: A total of 47 patients with sPHPT (single-PTA n = 32, double-PTA n = 12, MGD n = 9). Preoperative plasma samples from 16 single-PTA and 29 normal healthy donors (NHDs). All specimens were processed and analyzed for 2083 miRs using HTG EdgeSeq miR whole-transcriptome assay and normalized using DESeq2 to identify differentially expressed (DE) miRs. MiR classifiers were identified using Random Forest. Main outcome measures were receiver operating characteristic curves and areas under the curve.

RESULTS: MiR signatures distinguished normal parathyroid from MGD and PTA as well as MGD from PTA in tissue samples. Common miRs were found in the single-PTA and double-PTAs. Data integration identified a 27-miR signature in single-PTA tissue samples compared to the rest of the tissue samples. In plasma samples analysis, significant cfmiRs were DE in single-PTA patients compared to NHD. Of those, only 9 miRNAs/cfmiRs were found DE both in tissue and plasma samples from patients diagnosed with a single PTA (AUC = 76%).

CONCLUSION: Twenty-seven miRs were consistently found DE in single-PTA tissue and plasma samples. Data integration showed a 9-cfmiR signature with potential clinical utility to preoperatively diagnose sPHPT caused by a single PTA, which could decrease more invasive parathyroid explorations.

Area of Special Interest

Cancer

Specialty/Research Institute

Oncology

Specialty/Research Institute

Endocrinology

DOI

10.1210/clinem/dgae577