Evidence map›Paper›PMID 30440635›Full record

ArticleAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference2018

Micro-Inversions In Human Cancer Genomes.

Li Qu, Huaiqiu Zhu, May Wang

Open access · greenAbstract read
In one paragraph

Article in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2018. 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 85% 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, 1 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

3 authors at 2 institutions in 2 countries.

Li Qu
Huaiqiu Zhu
May Wang
Peking University · CNEmory University · US

Funding

Tissue and Animal UseU54CA119338 · NCI · EMORY UNIVERSITY · PI NIE, SHUMING · 2005 to 2009
$18.4M
NCI NIH HHS U54 CA119338
6 · The paper itself

Abstract

During the past few years, although scientists and researchers have studied variations in the cancer genomes, our current knowledge about the function of Micro-inversions (MIs) in cancer are still limited. MIs are generally defined as small inversions in DNA segments shorter than 100 bp. To expand our knowledge of their roles in cancer, we analyzed the MIs of 209 samples from four types of cancer, including hepatocellular carcinoma, lung cancer, pancreatic cancer, and bladder cancer. Within all the 209 samples, we identified 2,925 MIs, of which 1,519 (51.93%) are in gene regions. Of the 1,519 MIs in the gene regions, 106 (6.98%) are in the exon regions. We also analyzed 209 healthy samples as the control samples. We further analyzed the distribution of MIs in the four types of cancer among 24 chromosomes. Besides the chromosome preference, different cancers also have different preference for various genes. The MIs preference for different genes among four types of cancer may provide a guidance for the treatment and diagnosis on the four types of cancer. Medical doctors should concentrate more on chromosomes and the genes that MIs prefer to locate on. We also calculated the average count of MIs per individual among each cancer. From this result, we found that the bladder cancer has the most average count of MIs per individual, which means MIs may be more likely to exist in bladder cancer. According to our analysis, MIs play an important role in cancer and should be considered for further analysis.

Indexed as

Genome, HumanUrinary Bladder NeoplasmsChromosome InversionDNAHumansDNA

Identifiers

PMID30440635
PMCPMC7339915
OpenAlexW2899028612

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.