Evidence map›Paper›PMID 30542712›Full record

ArticleOncology reports2019

A two‑circRNA signature predicts tumour recurrence in clinical non‑functioning pituitary adenoma.

Jing Guo, Zhuang Wang, Yazhou Miao, Yutao Shen, Mingxuan Li, Lei Gong, Hongyun Wang, Yue He, Hua Gao, Qian Liu and 2 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Cell journal · 2022
    Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jing GuoDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Zhuang WangDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Yazhou MiaoDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Yutao ShenDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Mingxuan LiDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Lei GongDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Hongyun WangDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Yue HeDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Hua GaoDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Qian LiuDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Chuzhong LiDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.
Yazhuo ZhangDepartment of Cell Biology, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100050, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AdenomaAdultAgedDisease ProgressionFeasibility StudiesFemaleFollow-Up StudiesHumansMaleMiddle AgedNeoplasm Recurrence, LocalOligonucleotide Array Sequence AnalysisPituitary NeoplasmsPredictive Value of TestsPrognosisProgression-Free SurvivalRNARNA, Circular

Identifiers

PMID30542712
PMCPMC6278571

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.