Evidence map›Paper›PMID 32078798›Full record

ArticleCell systems2020

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations.

Pawel F Przytycki, Mona Singh

Open access · bronzeAbstract read
In one paragraph

Article in Cell systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.2field-weighted citation impact, top 24% 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

13 citing papers in PubMed, 21 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. LncRNA MAFG-AS1 is involved in human cancer progression.European journal of medical research · 2023
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. iScience · 2021
    Article
  13. Review
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.

Pawel F PrzytyckiDepartment of Computer Science, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA.
Mona SinghDepartment of Computer Science, Princeton University, Princeton, NJ 08544, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA. Electronic address: mona@cs.princeton.edu.
Princeton University · US

Funding

Predicting and analyzing variation in cellular interactomesR01GM076275 · NIGMS · PRINCETON UNIVERSITY · PI SINGH, MONA · 2006 to 2022
$4.0M
Interaction-based computational methods for analyzing cancer genomesR01CA208148 · NCI · PRINCETON UNIVERSITY · PI MONA SINGH · 2016 to 2026
$3.2M
NCI NIH HHS R01 CA208148NIGMS NIH HHS R01 GM076275
6 · The paper itself

Abstract

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

Indexed as

AllelesBreast NeoplasmsFemaleGene Expression ProfilingHumansMutationWhole Genome Sequencingallele-specific expressioncancernoncoding mutationswhole-exome sequencingwhole-genome sequencing

Identifiers

PMID32078798
PMCPMC7457951
OpenAlexW3008154341

What OpenQuestion holds

Textmetadata
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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 OpenQuestion graph.