Evidence map›Paper›PMID 36797358›Full record

ArticleBritish journal of cancer2023

Utility of molecular subtypes and genetic alterations for evaluating clinical outcomes in 1029 patients with endometrial cancer.

Yuka Asami, Mayumi Kobayashi Kato, Kengo Hiranuma, Maiko Matsuda, Yoko Shimada, Mitsuya Ishikawa, Takafumi Koyama, Masaaki Komatsu, Ryuji Hamamoto, Minoru Nagashima and 8 more

Open access · hybridAbstract read
In one paragraph

Article in British journal of cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
12.1field-weighted citation impact, top 1% 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

29 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 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

18 authors at 5 institutions in 2 countries.

Yuka AsamiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Mayumi Kobayashi KatoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Kengo HiranumaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Maiko MatsudaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Yoko ShimadaDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Mitsuya IshikawaDepartment of Gynecology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
Takafumi KoyamaDepartment of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
Masaaki KomatsuDivision of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Ryuji HamamotoDivision of Medical AI Research and Development, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Minoru NagashimaDepartment of Obstetrics and Gynecology, Showa University School of Medicine, Tokyo, 142-8555, Japan.
Yasuhisa TeraoDepartment of Obstetrics and Gynecology, Juntendo University Faculty of Medicine, Tokyo, 113-8421, Japan.
Atsuo ItakuraDepartment of Obstetrics and Gynecology, Juntendo University Faculty of Medicine, Tokyo, 113-8421, Japan.
Takashi KohnoDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan.
Akihiko SekizawaDepartment of Obstetrics and Gynecology, Showa University School of Medicine, Tokyo, 142-8555, Japan.
Koji MatsumotoDepartment of Obstetrics and Gynecology, Showa University School of Medicine, Tokyo, 142-8555, Japan.
Tomoyasu KatoDepartment of Gynecology, National Cancer Center Hospital, Tokyo, 104-0045, Japan.
Kouya ShiraishiDivision of Genome Biology, National Cancer Center Research Institute, Tokyo, 104-0045, Japan. kshirais@ncc.go.jp.ORCID http://orcid.org/0000-0002-5821-7400
Hiroshi YoshidaDepartment of Diagnostic Pathology, National Cancer Center Hospital, 104-0045, Tokyo, Japan. hiroyosh@ncc.go.jp.
National Cancer Centre Japan · JPShowa University · JPJuntendo University · JPTokyo National Hospital · JPRIKEN Center for Advanced Intelligence Project · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe investigated the utility of a molecular classifier tool and genetic alterations for predicting prognosis in Japanese patients with endometrial cancer.

methodsA total of 1029 patients with endometrial cancer from two independent cohorts were classified into four molecular subtype groups. The primary and secondary endpoints were relapse-free survival (RFS) and overall survival (OS), respectively.

resultsAmong the 265 patients who underwent initial surgery, classified according to immunohistochemistry, patients with DNA polymerase epsilon exonuclease domain mutation had an excellent prognosis (RFS and OS), patients with no specific molecular profile (NSMP) and mismatch repair protein deficiency had an intermediate prognosis, and those with protein 53 abnormal expression (p53abn) had the worst prognosis (P < 0.001). In the NSMP group, mutant KRAS and wild-type ARID1A were associated with significantly poorer 5-year RFS (41.2%) than other genomic characteristics (P < 0.001). The distribution of the subtypes differed significantly between patients with recurrence/progression and classified by sequencing (n = 764) and patients who underwent initial surgery (P < 0.001). Among patients with recurrence/progression, 51.4% had the opportunity to receive molecular targeted therapy.

conclusionsA molecular classifier is a useful tool for determining prognosis and eligibility for molecularly targeted therapy in patients with endometrial cancer.

Indexed as

Biomarkers, TumorEndometrial NeoplasmsFemaleHumansMutationNeoplasm Recurrence, LocalPrognosisBiomarkers, Tumor

Identifiers

PMID36797358
PMCPMC10070437
OpenAlexW4321018485

What OpenQuestion holds

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LicenceCC BY
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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.