Evidence map›Paper›PMID 35278272›Full record

ArticleCancer science2022

Clinical impact of genetic alterations of CTNNB1 in patients with grade 3 endometrial endometrioid carcinoma.

Mayumi Kobayashi Kato, Yuka Asami, Daisuke Takayanagi, Maiko Matsuda, Yoko Shimada, Kengo Hiranuma, Ikumi Kuno, Masaaki Komatsu, Ryuji Hamamoto, Koji Matsumoto and 5 more

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

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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

15 authors at 3 institutions in 1 country.

Mayumi Kobayashi KatoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.ORCID https://orcid.org/0000-0003-4065-0289
Yuka AsamiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Daisuke TakayanagiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Maiko MatsudaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Yoko ShimadaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Kengo HiranumaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.
Ikumi KunoDepartment of Gynecology, National Cancer Center Hospital, Tokyo, Japan.
Masaaki KomatsuDivision of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan.
Ryuji HamamotoDivision of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, Japan.
Koji MatsumotoDepartment of Obstetrics and Gynecology, Showa University School of Medicine, Tokyo, Japan.ORCID https://orcid.org/0000-0001-6184-618X
Mitsuya IshikawaDepartment of Gynecology, National Cancer Center Hospital, Tokyo, Japan.
Takashi KohnoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5371-706X
Tomoyasu KatoDepartment of Gynecology, National Cancer Center Hospital, Tokyo, Japan.
Kouya ShiraishiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan.ORCID https://orcid.org/0000-0002-5821-7400
Hiroshi YoshidaDivision of Diagnostic Pathology, National Cancer Center Hospital, Tokyo, Japan.ORCID https://orcid.org/0000-0002-7569-7813
Tokyo National Hospital · JPRIKEN Center for Advanced Intelligence Project · JPShowa University · JP

Funding

Japan Agency for Medical Research and Development (AMED) 20ck0106554h0001Japan Society for the Promotion of Science 19K16572Japan Society for the Promotion of Science 20H03695Japan Society for the Promotion of Science 20K09636Japan Society for the Promotion of Science 20K18207National Cancer Center Research and Development Fund 2020-J-2
6 · The paper itself

Abstract

To identify prognostic factors in patients with grade 3 (high-grade) endometrial endometrioid carcinoma, we evaluated the spectrum of genomic alterations and examined whether previously reported molecular subtypes of endometrial carcinoma were adapted to clinical outcome prediction. Seventy-five Japanese patients with grade 3 endometrial endometrioid carcinoma, who underwent a potentially curative resection procedure between 1997 and 2018 at the National Cancer Center Hospital, were included. We classified the patients into four risk groups of the disease based on the Proactive Molecular Risk Classifier for Endometrial Cancer. Genomic alterations in PTEN, ARID1A, TP53, and PIK3CA were detected in more than 30% of the patients. Overall survival and recurrence-free survival of patients with genomic alterations in CTNNB1 were poorer than those of patients with wild-type CTNNB1 (p = 0.006 and p = 0.004, respectively). Compared with that of alterations prevalent in Caucasians, the frequency of genomic alterations in POLE and TP53 was higher in our study than in The Cancer Genome Atlas dataset (p = 0.01 and p = 0.01, respectively). The tendency for recurrence-free survival in the POLE exonuclease domain mutation group was better than that in the TP53 mutation and mismatch repair-deficient groups (p = 0.08 and p = 0.07, respectively), consistent with the Proactive Molecular Risk Classifier for Endometrial Cancer risk classifier definition. The CTNNB1 mutation is a potential novel biomarker for the prognosis of patients with grade 3 endometrial endometrioid carcinoma, and prognosis classification using Proactive Molecular Risk Classifier for Endometrial Cancer may help screen Japanese patients with the disease.

Indexed as

Carcinoma, EndometrioidEndometrial Neoplasmsbeta CateninDisease-Free SurvivalFemaleHumansMutationPrognosisbeta CateninCTNNB1 protein, humanCTNNB1genetic alterationsgrade 3 endometrial endometrioid carcinomaprognosisProMisE

Identifiers

PMID35278272
PMCPMC9128156
OpenAlexW4220690134

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.