Evidence map›Paper›PMID 40224997›Full record

ReviewTranslational cancer research2025

A narrative review of papillary thyroid carcinoma-related long non-coding RNAs and their relevance to malignant tumors.

Yuanhao Su, Yi Jin

Abstract readReview
In one paragraph

Review in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

2 authors.

Yuanhao SuDepartment of General Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Yi JinCell and Gene Research Therapy Institute, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: In recent years, research on the relationship between papillary thyroid carcinoma (PTC) and long non-coding RNAs (lncRNAs) has been burgeoning. However, there has not been an analysis of the regulatory mechanisms of these lncRNAs in all tumors, nor a comprehensive categorization and comparison of these mechanisms. This review aims to uncover whether PTC-related lncRNAs also play an important role in other tumors and to identify a common pattern of action. Methods: We conducted a statistical analysis of lncRNAs related to PTC that have been reported during the period from Jan 2022 to May 2024 through searching in the Embase, Web of Science, and PubMed databases, focusing on those with greater research value. Using them as the focal points of our study, we compiled data on their different regulatory mechanisms across various malignant tumors, emphasizing key findings. Key Content and Findings: This comprehensive analysis not only provides valuable insights into potential regulatory mechanisms of these lncRNAs in PTC but also serves as a reference for exploring their broader regulatory networks within cancer. The principal discovery is that lncRNAs associated with PTC can competitively interact with microRNAs (miRNAs). This interaction influences miRNA-targeted messenger RNA (mRNA) and the expression of cancer-related proteins, ultimately facilitating the progression of PTC as well as other malignant tumors. Conclusions: The lncRNAs associated with PTC exert regulatory functions in other malignancies as well and possess similar regulatory mechanisms. This provides a molecular basis for the future development of relevant targeted therapies.

Indexed as

long non-coding RNAs (lncRNAs)Papillary thyroid carcinoma (PTC)targeted therapy

Identifiers

PMID40224997
PMCPMC11985200

What Socratic holds

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Registered trials

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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 Socratic graph.