Evidence map›Paper›PMID 37999735›Full record

ReviewVirchows Archiv : an international journal of pathology2024

Genomic alterations and diagnosis of renal cancer.

Xingming Zhang, Hella A Bolck, Niels J Rupp, Holger Moch

Open access · hybridAbstract readReview
In one paragraph

Review in Virchows Archiv : an international journal of pathology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 11 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

4 authors at 3 institutions in 2 countries.

Xingming ZhangDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstr. 12, 8091, Zurich, Switzerland.
Hella A BolckDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstr. 12, 8091, Zurich, Switzerland.
Niels J RuppDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstr. 12, 8091, Zurich, Switzerland.
Holger MochDepartment of Pathology and Molecular Pathology, University Hospital Zurich, Schmelzbergstr. 12, 8091, Zurich, Switzerland. holger.moch@usz.ch.ORCID http://orcid.org/0000-0002-7986-2839
University of Zurich · CHSichuan University · CNUniversity Hospital of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The application of molecular profiling has made substantial impact on the classification of urogenital tumors. Therefore, the 2022 World Health Organization incorporated the concept of molecularly defined renal tumor entities into its classification, including succinate dehydrogenase-deficient renal cell carcinoma (RCC), FH-deficient RCC, TFE3-rearranged RCC, TFEB-altered RCC, ALK-rearranged RCC, ELOC-mutated RCC, and renal medullary RCC, which are characterized by SMARCB1-deficiency. This review aims to provide an overview of the most important molecular alterations in renal cancer, with a specific focus on the diagnostic value of characteristic genomic aberrations, their chromosomal localization, and associations with renal tumor subtypes. It may not yet be the time to completely shift to a molecular RCC classification, but undoubtedly, the application of molecular profiling will enhance the accuracy of renal cancer diagnosis, and ultimately guide personalized treatment strategies for patients.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsGenomicsHumansIn Situ Hybridization, FluorescenceKidneyDiagnostic valueGenomic alterationsKidney cancerMolecular defined entitiesRenal cell carcinoma

Identifiers

PMID37999735
PMCPMC10948545
OpenAlexW4388976522

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.