Evidence map›Paper›PMID 33946379›Full record

ArticleCancers2021

Spatial Distribution of Private Gene Mutations in Clear Cell Renal Cell Carcinoma.

Ariane L Moore, Aashil A Batavia, Jack Kuipers, Jochen Singer, Elodie Burcklen, Peter Schraml, Christian Beisel, Holger Moch, Niko Beerenwinkel

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

9 authors at 3 institutions in 1 country.

Ariane L MooreDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.ORCID 0000-0001-7831-5115
Aashil A BataviaDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Jack KuipersDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Jochen SingerDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Elodie BurcklenDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Peter SchramlDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland.
Christian BeiselDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Holger MochDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland.ORCID 0000-0002-7986-2839
Niko BeerenwinkelDepartment of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.ORCID 0000-0002-0573-6119
SIB Swiss Institute of Bioinformatics · CHETH Zurich · CHUniversity of Zurich · CH

Funding

European Research Council 609883Horizon 2020 633974Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung 310030_166391SystemsX.ch SXPHI0_142005
6 · The paper itself

Abstract

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average, 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (

Indexed as

clonal exclusivityintra-tumour heterogeneityprivate mutations

Identifiers

PMID33946379
PMCPMC8124666
OpenAlexW3158026806

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.