Evidence map›Paper›PMID 37335337›Full record

ArticleJournal of cancer research and clinical oncology2023

Comprehensive landscape of the miRNA-regulated prognostic marker LAYN with immune infiltration and stemness in pan-cancer.

Wang Jiawen, Wang Jinfu, Liu Jianyong, Zhang Yaoguang, Wang Jianye

Open access · greenAbstract read
In one paragraph

Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Liquid-liquid phase separation-related genes associated with prognosis, tumor microenvironment characteristics, and tumor cell features in bladder cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Article
  4. 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

5 authors at 1 institution in 1 country.

Wang Jiawen *Department of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Wang Jinfu *Department of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Liu JianyongDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Zhang YaoguangDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Wang JianyeDepartment of Urology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. wangjybjh@126.com.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

National Key Research and Development Program of China 2018YFC2002202
6 · The paper itself

Abstract

backgroundCOVID-19 has created a significant risk to worldwide public health. According to recent research, C-type lectins may be SARS-CoV-2 receptors. Layilin (LAYN), a broadly expressed integral membrane hyaluronan receptor with a C-type lectin structural domain, is a gene related to cell senescence. There are a few studies on C-type lectins in pan-cancer, and no pan-cancer analysis has been conducted for LAYN.

methodsThe genotype tissue expression (GTEx) portal and the cancer genome map (TCGA) database were used to collect samples from healthy and cancer patients. Bioinformatics methods are used to construct immune landscape, mutation landscape, and stemness landscape of LAYN. The single-cell sequencing data were used from the CancerSEA website to analyze the functions of LAYN. The prognosis potential of LAYN was discussed based on machine learning.

resultsLAYN is differentially expressed among cancers. Survival analysis indicated that LAYN was related to a poor overall survival (OS) rate in cancers, like HNSC, MESO, and OV. Mutational landscapes of LAYN in SKCM and STAD were constructed. LAYN was negatively related to Tumor Mutation Burden (TMB) in THCA, PRAD, and UCEC, and with the Microsatellite Instability (MSI) in STAD, LUAD, and UCEC. The immune landscape in pan-cancer suggested that LAYN may be involved in tumor immune escape. LAYN plays a crucial role in the infiltration of immune cells in malignant tumors. LAYN participates in methylation modifications and affects tumor proliferation and metastasis by regulating stemness. Analysis of single-cell sequencing data suggests that LAYN may participate in several biological processes, like stemness, apoptosis, and DNA repair. LAYN transcript was predicted as a liquid-liquid phase separation (LLPS)-related RNA. The results of KIRC were verified in the GEO and ArrayExpress databases. Furthermore, prognostic models based on machine learning of LAYN-related genes were established. Hsa-miR-153-5p and hsa-miR-505-3p may be the upstream miRNAs of LAYN and have a high value for tumor prognosis.

conclusionThis study elucidated the functional mechanisms of LAYN from a pan-cancer perspective and provided novel insights into cancer prognosis, metastasis, and immunotherapy. LAYN has the potential to become a new target of mRNA vaccines and molecular therapies in tumors.

Indexed as

COVID-19MicroRNAsNeoplasmsHumansLectins, C-TypePrognosisSARS-CoV-2LAYN protein, humanLectins, C-TypeMicroRNAsMIRN153 microRNA, humanMIRN505 microRNA, humanImmune infiltrationLAYNPan-cancerPrognostic markerStemness

Identifiers

PMID37335337
PMCPMC11796549
OpenAlexW4381185836

What OpenQuestion 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 OpenQuestion graph.