Evidence map›Paper›PMID 32209592›Full record

ArticleGenome research2020

Comprehensive analysis of indels in whole-genome microsatellite regions and microsatellite instability across 21 cancer types.

Akihiro Fujimoto, Masashi Fujita, Takanori Hasegawa, Jing Hao Wong, Kazuhiro Maejima, Aya Oku-Sasaki, Kaoru Nakano, Yuichi Shiraishi, Satoru Miyano, Go Yamamoto and 3 more

Abstract read
In one paragraph

Article in Genome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

47 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  11. STR profiling in a cohort of Saudi patients with acute leukemia.Journal of Taibah University Medical Sciences · 2025
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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

13 authors.

Akihiro FujimotoLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.ORCID http://orcid.org/0000-0002-0075-0800
Masashi FujitaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.
Takanori HasegawaHealth Intelligence Center, Institute of Medical Sciences, The University of Tokyo, Tokyo 108-8639, Japan.
Jing Hao WongDepartment of Human Genetics, The University of Tokyo, Graduate School of Medicine, Tokyo 113-0033, Japan.
Kazuhiro MaejimaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.
Aya Oku-SasakiLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.
Kaoru NakanoLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.
Yuichi ShiraishiDivision of Cellular Signaling, National Cancer Center Research Institute, Tokyo 104-0045, Japan.
Satoru MiyanoHealth Intelligence Center, Institute of Medical Sciences, The University of Tokyo, Tokyo 108-8639, Japan.
Go YamamotoDivision of Molecular Diagnosis and Cancer Prevention, Saitama Cancer Center, Saitama 362-0806, Japan.
Kiwamu AkagiDivision of Molecular Diagnosis and Cancer Prevention, Saitama Cancer Center, Saitama 362-0806, Japan.
Seiya ImotoHealth Intelligence Center, Institute of Medical Sciences, The University of Tokyo, Tokyo 108-8639, Japan.
Hidewaki NakagawaLaboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Tokyo 230-0045, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microsatellites are repeats of 1- to 6-bp units, and approximately 10 million microsatellites have been identified across the human genome. Microsatellites are vulnerable to DNA mismatch errors and have thus been used to detect cancers with mismatch repair deficiency. To reveal the mutational landscape of microsatellite repeat regions at the genome level, we analyzed approximately 20.1 billion microsatellites in 2717 whole genomes of pan-cancer samples across 21 tissue types. First, we developed a new insertion and deletion caller (MIMcall) that takes into consideration the error patterns of different types of microsatellites. Among the 2717 pan-cancer samples, our analysis identified 31 samples, including colorectal, uterus, and stomach cancers, with a higher proportion of mutated microsatellite (≥0.03), which we defined as microsatellite instability (MSI) cancers of genome-wide level. Next, we found 20 highly mutated microsatellites that can be used to detect MSI cancers with high sensitivity. Third, we found that replication timing and DNA shape were significantly associated with mutation rates of microsatellites. Last, analysis of mutations in mismatch repair genes showed that somatic SNVs and short indels had larger functional impacts than germline mutations and structural variations. Our analysis provides a comprehensive picture of mutations in the microsatellite regions and reveals possible causes of mutations, as well as provides a useful marker set for MSI detection.

Identifiers

PMID32209592
PMCPMC7111525

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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.