Evidence map›Paper›PMID 39171503›Full record

ArticleCancer medicine2024

Predictive biomarkers for metachronous gastric cancer development after endoscopic resection of early gastric cancer.

Bokyung Kim, Harim Chun, Jongwon Lee, Miree Park, Yoonjin Kwak, Jung Mogg Kim, Sang Gyun Kim, Ji Kon Ryu, Jungmin Choi, Soo-Jeong Cho

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Bokyung KimDepartment of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Harim ChunDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.
Jongwon LeeDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.ORCID 0000-0002-2203-3634
Miree ParkDepartment of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Yoonjin KwakDepartment of Pathology, Seoul National University Hospital, Seoul, Korea.
Jung Mogg KimDepartment of Microbiology, Hanyang University College of Medicine, Seoul, Korea.
Sang Gyun KimDepartment of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Ji Kon RyuDepartment of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.ORCID 0000-0001-8798-0491
Jungmin ChoiDepartment of Biomedical Sciences, Korea University College of Medicine, Seoul, Korea.
Soo-Jeong ChoDepartment of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.ORCID 0000-0001-7144-0589

Funding

SNUH research fund #03-2020-0370SNUH research fund #03-2022-0140The Basic Science Research Program through the National Research Foundation of Korea (NRF) NRF-2021R1F1A1045550The Korean College of Helicobacter and Upper Gastrointestinal Research Foundation KCHUGR - 202002001The Korean College of Helicobacter and Upper Gastrointestinal Research Foundation KCHUGR-202102001The National Research Foundation of Korea #NRF-2022R1A2B5B01001430The National Research Foundation of Korea #NRF-2022R1A4A2000827The Seoul National University College of Medicine Research foundation 800-20220338
6 · The paper itself

Abstract

objectivesWe aimed to identify predictive markers for metachronous gastric cancer (MGC) in early gastric cancer (EGC) patients curatively treated with endoscopic submucosal dissection (ESD). MATERIALS AND

methodsFrom EGC patients who underwent ESD, bulk RNA sequencing was performed on non-cancerous gastric mucosa samples at the time of initial EGC diagnosis. This included 23 patients who developed MGC, and 23 control patients without additional gastric neoplasms for over 3 years (1:1 matched by age, sex, and Helicobacter pylori infection state). Candidate differentially-expressed genes were identified, from which biomarkers were selected using real-time quantitative polymerase chain reaction and cell viability assays using gastric cell lines. An independent validation cohort of 55 MGC patients and 125 controls was used for marker validation. We also examined the severity of gastric intestinal metaplasia, a known premalignant condition, at initial diagnosis.

resultsFrom the discovery cohort, 86 candidate genes were identified of which KDF1 and CDK1 were selected as markers for MGC, which were confirmed in the validation cohort. CERB5 and AKT2 isoform were identified as markers related to intestinal metaplasia and were also highly expressed in MGC patients compared to controls (p < 0.01). Combining these markers with clinical data (age, sex, H. pylori and severity of intestinal metaplasia) yielded an area under the curve (AUC) of 0.91 (95% CI, 0.85-0.97) for MGC prediction.

conclusionAssessing biomarkers in non-cancerous gastric mucosa may be a useful method for predicting MGC in EGC patients and identifying patients with a higher risk of developing MGC, who can benefit from rigorous surveillance.

Indexed as

Biomarkers, TumorNeoplasms, Second PrimaryStomach NeoplasmsAgedCase-Control StudiesCDC2 Protein KinaseEndoscopic Mucosal ResectionFemaleGastric MucosaGastroscopyGene Expression Regulation, NeoplasticHelicobacter InfectionsHelicobacter pyloriHumansMaleMetaplasiaBiomarkers, TumorCDC2 Protein KinaseCDK1 protein, humanbiomarkersendoscopic resectiongastric cancerRNA sequencingwhole exome sequencing

Identifiers

PMID39171503
PMCPMC11339598

What Socratic 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 Socratic graph.