Evidence map›Paper›PMID 35681609›Full record

ArticleCancers2022

Proteomic Analysis of Lung Cancer Types-A Pilot Study.

Simon Sugár, Fanni Bugyi, Gábor Tóth, Judit Pápay, Ilona Kovalszky, Tamás Tornóczky, László Drahos, Lilla Turiák

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 14 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

8 authors at 5 institutions in 1 country.

Simon SugárMS Proteomics Research Group, Research Centre for Natural Sciences, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.ORCID 0000-0001-9728-5732
Fanni BugyiMS Proteomics Research Group, Research Centre for Natural Sciences, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.ORCID 0000-0002-4890-870X
Gábor TóthMS Proteomics Research Group, Research Centre for Natural Sciences, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.ORCID 0000-0003-1428-7906
Judit PápayDepartment of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, H-1085 Budapest, Hungary.
Ilona KovalszkyDepartment of Pathology and Experimental Cancer Research, Semmelweis University, Üllői út 26, H-1085 Budapest, Hungary.ORCID 0000-0002-0179-3378
Tamás TornóczkyDepartment of Pathology, Medical School and Clinical Center, University of Pecs, Szigeti út 12, H-7624 Pecs, Hungary.
László DrahosMS Proteomics Research Group, Research Centre for Natural Sciences, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.ORCID 0000-0001-9589-6652
Lilla TuriákMS Proteomics Research Group, Research Centre for Natural Sciences, Magyar Tudósok Körútja 2, H-1117 Budapest, Hungary.ORCID 0000-0002-2139-8156
Semmelweis University · HUHUN-REN Research Centre for Natural Sciences · HUBudapest University of Technology and Economics · HUEötvös Loránd University · HUUniversity of Pecs · HU

Funding

Hungarian Academy of Sciences János Bolyai Research ScholarshipNational Research, Development, and Innovation Fund of Hungary 2018-1.2.1-NKPNational Research, Development, and Innovation Fund of Hungary NRDI FK_19
6 · The paper itself

Abstract

Lung cancer is the leading cause of tumor-related mortality, therefore significant effort is directed towards understanding molecular alterations occurring at the origin of the disease to improve current treatment options. The aim of our pilot-scale study was to carry out a detailed proteomic analysis of formalin-fixed paraffin-embedded tissue sections from patients with small cell or non-small cell lung cancer (adenocarcinoma, squamous cell carcinoma, and large cell carcinoma). Tissue surface digestion was performed on relatively small cancerous and tumor-adjacent normal regions and differentially expressed proteins were identified using label-free quantitative mass spectrometry and subsequent statistical analysis. Principal component analysis clearly distinguished cancerous and cancer adjacent normal samples, while the four lung cancer types investigated had distinct molecular profiles and gene set enrichment analysis revealed specific dysregulated biological processes as well. Furthermore, proteins with altered expression unique to a specific lung cancer type were identified and could be the targets of future studies.

Indexed as

cancergene set enrichment analysishuman tissuelung cancerlung tissuemass spectrometryNSCLCproteomicsSCLC

Identifiers

PMID35681609
PMCPMC9179298
OpenAlexW4281568881

What Socratic holds

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LicenceCC BY
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 Socratic graph.