Evidence map›Paper›PMID 34642392›Full record

ArticleScientific reports2021

Protein co-expression network-based profiles revealed from laser-microdissected cancerous cells of lung squamous-cell carcinomas.

Toshihide Nishimura, Kiyonaga Fujii, Haruhiko Nakamura, Saeko Naruki, Hiroki Sakai, Hiroyuki Kimura, Tomoyuki Miyazawa, Masayuki Takagi, Naoki Furuya, Gyorgy Marko-Varga and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

9 citing papers in PubMed, 8 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

12 authors at 4 institutions in 2 countries.

Toshihide Nishimura *Department of Translational Medicine Informatics, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan. t-nisimura@marianna-u.ac.jp.
Kiyonaga Fujii *Department of Translational Medicine Informatics, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Haruhiko Nakamura *Department of Translational Medicine Informatics, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Saeko Naruki *Department of Pathology, St. Marianna University Hospital, Kawasaki, Kanagawa, 216-8511, Japan.
Hiroki SakaiDepartment of Chest Surgery, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Hiroyuki KimuraDepartment of Chest Surgery, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Tomoyuki MiyazawaDepartment of Chest Surgery, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Masayuki TakagiDepartment of Pathology, St. Marianna University Hospital, Kawasaki, Kanagawa, 216-8511, Japan.
Naoki FuruyaDivision of Respiratory Medicine, Department of Internal Medicine, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
Gyorgy Marko-VargaClinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical Engineering, Lund University, BMC D13, 221 84, Lund, Sweden.
Harubumi KatoTokyo Medical University, Tokyo, 160-0023, Japan.
Hisashi SajiDepartment of Chest Surgery, St. Marianna University School of Medicine, Kawasaki, Kanagawa, 216-8511, Japan.
St. Marianna University School of Medicine · JPDaiichi University of Pharmacy · JPInternational University of Health and Welfare · JPLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

No therapeutic targets have been identified for lung squamous cell cancer (SqCC) which is the second most prevalent lung cancer because its molecular profiles remain unclear. This study aimed to unveil disease-related protein networks by proteomic and bioinformatic assessment of laser-microdissected cancerous cells from seven SqCCs compared with eight representative lung adenocarcinomas. We identified three network modules significant to lung SqCC using weighted gene co-expression network analysis. One module was intrinsically annotated to keratinization and cell proliferation of SqCC, accompanied by hypoxia-induced aerobic glycolysis, in which key regulators were activated (HIF1A, ROCK2, EFNA1-5) and highly suppressed (KMT2D). The other two modules were significant for translational initiation, nonsense-mediated mRNA decay, inhibited cell death, and interestingly, eIF2 signaling, in which key regulators, MYC and MLXIPL, were highly activated. Another key regulator LARP1, the master regulator in cap-dependent translation, was highly suppressed although upregulations were observed for hub proteins including EIF3F and LARP1 targeted ribosomal proteins, among which PS25 is the key ribosomal protein in IRES-dependent translation. Our results suggest an underlying progression mechanism largely caused by switching to the cap-independent, IRES-dependent translation of mRNA subsets encoding oncogenic proteins. Our findings may help to develop therapeutic strategies to improve patient outcomes.

Indexed as

Adenocarcinoma of LungAgedCarcinoma, Squamous CellCell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansLaser Capture MicrodissectionLung NeoplasmsMaleMiddle AgedMultivariate AnalysisProtein Interaction MapsProteomics

Identifiers

PMID34642392
PMCPMC8511190
OpenAlexW3195136035

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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.