ArticleOncology reports2019
A two‑circRNA signature predicts tumour recurrence in clinical non‑functioning pituitary adenoma.
Article in Oncology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Biological functions and molecular mechanisms of circHIPK3 in digestive system tumors.Human cell · 2025Review
- Liquid Biopsy in Pituitary Neuroendocrine Tumors-Potential Biomarkers for Diagnosis, Prognosis, and Therapy.International journal of molecular sciences · 2025Review
- Review
- Article
- Enhancing Gonadotrope Gene Expression Through Regulatory lncRNAs.Endocrinology · 2021Review
- Identifying critical protein-coding genes and long non-coding RNAs in non-functioning pituitary adenoma recurrence.Oncology letters · 2021Article
- Nomogram predictive model of post-operative recurrence in non-functioning pituitary adenoma.Gland surgery · 2021Article
- An Exploration of Non-Coding RNAs in Extracellular Vesicles Delivered by Swine Anterior Pituitary.Frontiers in genetics · 2021Article
- Phosphorylated EGFR (pEGFR T693) as a Novel Predictor of Recurrence in Non-Functioning Pituitary Adenomas.Frontiers in endocrinology · 2021Article
- Novel Insights into Pituitary Tumorigenesis: Genetic and Epigenetic Mechanisms.Endocrine reviews · 2020Review
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Authors and funding
12 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Clinical non‑functioning pituitary adenoma (NFPA) accounts for >30% of all pituitary adenomas, and the recurrence rate is notably high. The ability to predict tumour recurrence during initial surgery will aid in determining if adjunctive therapy is required to reduce recurrence. With the aim of developing a circular RNA (circRNA) signature to improve prognosis prediction in NFPA, the present study examined the circRNA expression profiles in 73 patients with NFPA from Beijing Tiantan Hospital using high‑throughput RNA chip technology. The dataset was randomly separated into a training group and a test group using an R program. In the training group (n=37), a Cox proportional hazards regression model was used to analyse the genes associated with the recurrence and progression‑free survival (PFS) of patients with NFPA. Meanwhile, a random survival forest algorithm, Kaplan‑Meier and receiver operating characteristic curve (ROC) analyses were used to determine the multi‑circRNA signature with the largest area under the ROC curve (AUROC) and verify its efficacy in the test group (n=36). In the training and test groups, the signatures of two circRNAs (hsa_circ_0000066 and hsa_circ_0069707) were specifically associated with the PFS of patients with NFPA (log‑rank P<0.05). Furthermore, the two‑circRNA signature had a high prediction accuracy for tumour recurrence, with an AUROC of 0.87 and 0.67 in the training and test groups, respectively; and the discriminative power of the signature was greater compared with that of age. The present study is the first to suggest a circRNA signature with a clinical application value for predicting recurrence/progression in patients with NFPA.
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