Differential Expression of MALAT1 and HOTAIR lncRNAs in Early and Advanced Stage Breast Cancer Patients: Potential Prognostic Biomarkers
Received: 11 September 2025; Revised: 17 November 2025; Accepted: 25 November 2025; Published: 3 February 2026
Abstract
Long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression involved in tumor initiation, progression, and metastasis. Among them, HOTAIR (HOX Transcript Antisense Intergenic RNA) and MALAT1 (Metastasis-Associated Lung Adenocarcinoma Transcript 1) have been implicated in several cancers, including breast cancer. However, their stage-specific expression patterns and prognostic relevance in breast cancer remain underexplored. This study aimed to evaluate the differential expression of HOTAIR and MALAT1 in early-stage (I–II) and late-stage (III–IV) breast cancers and to assess their association with clinicopathological and demographic parameters to determine their potential as prognostic biomarkers. Eighty breast cancer samples were analyzed for HOTAIR and MALAT1 expression using qRT-PCR. Clinicopathological data, including age, menopausal status, lymph node involvement, and hormone receptor status (ER, PR, HER2/neu), were collected. Logistic regression, ROC curve, and univariate analyses assessed their diagnostic and predictive significance. HOTAIR expression was significantly upregulated in late-stage (III–IV) breast cancer compared with early-stage (I–II) cases (p < 0.05), showing strong association with lymph node metastasis, postmenopausal status, and receptor negativity. ROC analysis demonstrated HOTAIR’s predictive potential with an AUC of 0.73 (sensitivity: 64%; specificity: 86%). MALAT1 expression was non-significantly elevated in late-stage tumors. Logistic regression analysis we observed that overexpression of HOTAIR, lymph node involvement, and hormone receptor negativity as increases disease risk. The findings indicate that HOTAIR over expression serves as a potential prognostic biomarker for breast cancer at late stage and associated with clinicopathological features and disease progression.