Evidence map›Paper›PMID 32513296›Full record

ArticleGenome biology2020

Whole-genome sequencing of glioblastoma reveals enrichment of non-coding constraint mutations in known and novel genes.

Sharadha Sakthikumar, Ananya Roy, Lulu Haseeb, Mats E Pettersson, Elisabeth Sundström, Voichita D Marinescu, Kerstin Lindblad-Toh, Karin Forsberg-Nilsson

Open access · goldAbstract readValidation Study
In one paragraph

Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 5% 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

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Article
  19. Article
  20. Using evolutionary constraint to define novel candidate driver genes in medulloblastoma.Proceedings of the National Academy of Sciences of the United States of America · 2023
    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

8 authors at 2 institutions in 2 countries.

Sharadha SakthikumarDepartment of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, SE-751 23, Uppsala, Sweden.
Ananya RoyDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.
Lulu HaseebDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden.
Mats E PetterssonDepartment of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, SE-751 23, Uppsala, Sweden.
Elisabeth SundströmDepartment of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, SE-751 23, Uppsala, Sweden.
Voichita D MarinescuDepartment of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, SE-751 23, Uppsala, Sweden.
Kerstin Lindblad-TohDepartment of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, SE-751 23, Uppsala, Sweden.
Karin Forsberg-NilssonDepartment of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, SE-751 85, Uppsala, Sweden. karin.nilsson@igp.uu.se.ORCID 0000-0003-0692-6245
Uppsala University · SEBroad Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlioblastoma (GBM) has one of the worst 5-year survival rates of all cancers. While genomic studies of the disease have been performed, alterations in the non-coding regulatory regions of GBM have largely remained unexplored. We apply whole-genome sequencing (WGS) to identify non-coding mutations, with regulatory potential in GBM, under the hypothesis that regions of evolutionary constraint are likely to be functional, and somatic mutations are likely more damaging than in unconstrained regions.

resultsWe validate our GBM cohort, finding similar copy number aberrations and mutated genes based on coding mutations as previous studies. Performing analysis on non-coding constraint mutations and their position relative to nearby genes, we find a significant enrichment of non-coding constraint mutations in the neighborhood of 78 genes that have previously been implicated in GBM. Among them, SEMA3C and DYNC1I1 show the highest frequencies of alterations, with multiple mutations overlapping transcription factor binding sites. We find that a non-coding constraint mutation in the SEMA3C promoter reduces the DNA binding capacity of the region. We also identify 1776 other genes enriched for non-coding constraint mutations with likely regulatory potential, providing additional candidate GBM genes. The mutations in the top four genes, DLX5, DLX6, FOXA1, and ISL1, are distributed over promoters, UTRs, and multiple transcription factor binding sites.

conclusionsThese results suggest that non-coding constraint mutations could play an essential role in GBM, underscoring the need to connect non-coding genomic variation to biological function and disease pathology.

Indexed as

AdultAgedAged, 80 and overBrainCohort StudiesCytoplasmic DyneinsFemaleGlioblastomaHumansMaleMiddle AgedMutationPromoter Regions, GeneticRNA, UntranslatedSemaphorinsTelomeraseCytoplasmic DyneinsDYNC1LI1 protein, humanRNA, UntranslatedSema3C protein, humanSemaphorinsTelomeraseTERT protein, humanCancerGene regulationGlioblastomaNon-coding constraint

Identifiers

PMID32513296
PMCPMC7281935
OpenAlexW3027364034

What Socratic 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 Socratic graph.