Evidence map›Paper›PMID 33262827›Full record

ReviewOncology letters2021

MicroRNA-126: A new and promising player in lung cancer.

Qijun Chen, Shuanghua Chen, Juanjuan Zhao, Ya Zhou, Lin Xu

Open access · diamondAbstract readReview
In one paragraph

Review in Oncology letters, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

32 citing papers in PubMed, 48 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Qijun ChenDepartment of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Shuanghua ChenDepartment of General Medicine, The Third Hospital Affiliated to Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Juanjuan ZhaoDepartment of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Ya ZhouDepartment of Medical Physics, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Lin XuDepartment of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi, Guizhou 563000, P.R. China.
Zunyi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is one of the most common malignant tumors associated with cancer death; however, the mechanisms involved in lung tumor development have not been completely elucidated, which impedes the advancement of clinical diagnosis and therapy. MicroRNA-126 (miR-126) is an important member of the microRNA family and is encoded by intron 7 of epidermal growth factor-like domain-containing gene 7. Increasing evidence has demonstrated that miR-126, as a distinct endothelial-enriched miRNA and new tumor suppressor gene, serves a promising role in the occurrence, development and metastasis of various types of cancer, including liver cancer, colorectal cancer, melanoma and lung cancer. In the present review, the current knowledge of the role of miR-126 in lung cancer growth, metastasis, diagnosis and prognosis as well as therapy was summarized, which may provide new insights on the biological roles of miRNAsin lung cancer and facilitate the ultimate development of miRNA-based therapies in clinical patients with non-small cell lung cancer.

Indexed as

growthlung cancermetastasismicroRNA-126therapy

Identifiers

PMID33262827
PMCPMC7693477
OpenAlexW3105938835

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.