Evidence map›Paper›PMID 32940334›Full record

ArticleBriefings in bioinformatics2021

Scanning window analysis of non-coding regions within normal-tumor whole-genome sequence samples.

J P Torcivia, R Mazumder

Open access · bronzeAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 89% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

J P TorciviaThe Department of Biochemistry and Molecular Medicine, The George Washington University Medical Center, Washington, DC, USA.ORCID 0000-0002-9307-5778
R MazumderThe Department of Biochemistry and Molecular Medicine, The George Washington University Medical Center, Washington, DC, USA.
George Washington University · US

Funding

Integration of comprehensive cancer mutation and expression-associated data for biomarker evaluation and discoveryU01CA215010 · NCI · GEORGE WASHINGTON UNIVERSITY · PI CRICHTON, DANIEL, MAZUMDER, RAJA · 2017 to 2019
$1.3M
CCR NIH HHS HHSN261200800001CNCI NIH HHS HHSN261200800001ENCI NIH HHS U01 CA215010
6 · The paper itself

Abstract

Genomics has benefited from an explosion in affordable high-throughput technology for whole-genome sequencing. The regulatory and functional aspects in non-coding regions may be an important contributor to oncogenesis. Whole-genome tumor-normal paired alignments were used to examine the non-coding regions in five cancer types and two races. Both a sliding window and a binning strategy were introduced to uncover areas of higher than expected variation for additional study. We show that the majority of cancer associated mutations in 154 whole-genome sequences covering breast invasive carcinoma, colon adenocarcinoma, kidney renal papillary cell carcinoma, lung adenocarcinoma and uterine corpus endometrial carcinoma cancers and two races are found outside of the coding region (4 432 885 in non-gene regions versus 1 412 731 in gene regions). A pan-cancer analysis found significantly mutated windows (292 to 3881 in count) demonstrating that there are significant numbers of large mutated regions in the non-coding genome. The 59 significantly mutated windows were found in all studied races and cancers. These offer 16 regions ripe for additional study within 12 different chromosomes-2, 4, 5, 7, 10, 11, 16, 18, 20, 21 and X. Many of these regions were found in centromeric locations. The X chromosome had the largest set of universal windows that cluster almost exclusively in Xq11.1-an area linked to chromosomal instability and oncogenesis. Large consecutive clusters (super windows) were found (19 to 114 in count) providing further evidence that large mutated regions in the genome are influencing cancer development. We show remarkable similarity in highly mutated non-coding regions across both cancer and race.

Indexed as

MutationAlgorithmsBreast NeoplasmsCentromereChromosome MappingColonic NeoplasmsEndometrial NeoplasmsFemaleGenome, HumanGenomicsHumansKidney NeoplasmsLung NeoplasmsNeoplasmsOpen Reading FramesPolymorphism, Single Nucleotidecancercancer hotspotsnon-coding regionpan-cancer analysiswhole-genome sequencing

Identifiers

PMID32940334
PMCPMC8138877
OpenAlexW3087258621

What OpenQuestion holds

Textmetadata
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.