Evidence map›Paper›PMID 36562354›Full record

ArticleInternational journal of oncology2023

Landscape of circular RNAs in different types of lung cancer and an emerging role in therapeutic resistance (Review).

Fan Wang, Chuting Yu, Ling Chen, Sheng Xu

Abstract read
In one paragraph

Article in International journal of oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. 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

4 authors.

Fan Wang *National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical University, Shanghai 200433, P.R. China.
Chuting Yu *National Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical University, Shanghai 200433, P.R. China.
Ling ChenDepartment of Thoracic Surgery, Changhai Hospital, Naval Medical University, Shanghai 200433, P.R. China.
Sheng XuNational Key Laboratory of Medical Immunology and Institute of Immunology, Naval Medical University, Shanghai 200433, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most common malignant tumor types and the leading cause of cancer‑associated death worldwide. Different types of lung cancer exhibit differences in terms of pathophysiology and pathogenesis, and also treatment and prognosis. Accumulating evidence has indicated that circular RNAs (circRNAs) are abnormally expressed among different types of lung cancer and confer important biological functions in progression and prognosis. However, studies comparing different circRNAs in lung cancer subtypes are scarce. Furthermore, circRNAs have an important role in drug resistance and are related to clinicopathological features in lung cancer. Summaries of the association of circRNAs with drug resistance are also scarce in the literature. The present study outlined the biological functions of circRNAs and focused on discriminating differential circRNA patterns and mechanisms in three different types of lung cancer. The emerging roles of circRNAs in the resistance to chemotherapy, targeted therapy, radiotherapy and immunotherapy were also highlighted. Understanding these aspects of circRNAs sheds light on novel physiological and pathophysiological processes of lung cancer and suggests the application of circRNAs as biomarkers for diagnosis and prognosis, as well as therapeutic resistance.

Indexed as

Lung NeoplasmsRNA, CircularBiomarkersDrug Resistance, NeoplasmHumansRNABiomarkersRNARNA, CircularcircRNAslung adenocarcinomalung cancerlung squamous cell carcinomanon‑small cell lung cancertherapeutic resistance

Identifiers

PMID36562354
PMCPMC9812256

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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 OpenQuestion graph.