Evidence map›Paper›PMID 36901940›Full record

ArticleInternational journal of molecular sciences2023

Proteotranscriptomic Discrimination of Tumor and Normal Tissues in Renal Cell Carcinoma.

Áron Bartha, Zsuzsanna Darula, Gyöngyi Munkácsy, Éva Klement, Péter Nyirády, Balázs Győrffy

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Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. 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

6 authors.

Áron BarthaCancer Biomarker Research Group, Institute of Enzymology, RCNS, H-1117 Budapest, Hungary.ORCID 0000-0003-0395-243X
Zsuzsanna DarulaSingle Cell Omics Advanced Core Facility, HCEMM, H-6728 Szeged, Hungary.
Gyöngyi MunkácsyCancer Biomarker Research Group, Institute of Enzymology, RCNS, H-1117 Budapest, Hungary.
Éva KlementSingle Cell Omics Advanced Core Facility, HCEMM, H-6728 Szeged, Hungary.ORCID 0000-0002-9841-4142
Péter NyirádyDepartment of Urology, Semmelweis University, H-1082 Budapest, Hungary.
Balázs GyőrffyII. Department of Pediatrics, Semmelweis University, H-1094 Budapest, Hungary.

Funding

EU's Horizon 2020 research and innovation program No. 739593National Research, Development and Innovation Office 2020-1.1.6-JÖVŐ-2021-00013National Research, Development and Innovation Office EFOP-3.6.3-VEKOP-16-2017-00009National Research, Development and Innovation Office RRF-2.3.1-21-2022-00015National Research, Development and Innovation Office ÚNKP-22-4-1-SE-18
6 · The paper itself

Abstract

Clear cell renal carcinoma is the most frequent type of kidney cancer, with an increasing incidence rate worldwide. In this research, we used a proteotranscriptomic approach to differentiate normal and tumor tissues in clear cell renal cell carcinoma (ccRCC). Using transcriptomic data of patients with malignant and paired normal tissue samples from gene array cohorts, we identified the top genes over-expressed in ccRCC. We collected surgically resected ccRCC specimens to further investigate the transcriptomic results on the proteome level. The differential protein abundance was evaluated using targeted mass spectrometry (MS). We assembled a database of 558 renal tissue samples from NCBI GEO and used these to uncover the top genes with higher expression in ccRCC. For protein level analysis 162 malignant and normal kidney tissue samples were acquired. The most consistently upregulated genes were IGFBP3, PLIN2, PLOD2, PFKP, VEGFA, and CCND1 (

Indexed as

Carcinoma, Renal CellKidney NeoplasmsBiomarkers, TumorHumansKidneyProteinsProteomicsBiomarkers, TumorProteinsbiomarkerdiagnosticskidney cancermass spectrometryproteomics

Identifiers

PMID36901940
PMCPMC10003397

What Socratic holds

Textfull text, public
LicenceCC BY
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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.