Evidence map›Paper›PMID 41790338›Full record

ArticleInternational journal of clinical oncology2026

Clinical development of molecular residual disease (MRD) and multi-cancer early detection (MCED) using liquid biopsy multiomics with artificial intelligence (AI).

Taro Shibuki, Riu Yamashita, Tadayoshi Hashimoto, Takao Fujisawa, Mitsuho Imai, Junichiro Yuda, Takeshi Kuwata, Toshihiro Misumi, Yoshiaki Nakamura, Hideaki Bando and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of clinical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. 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

22 authors.

Taro ShibukiDepartment of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital East, Kashiwa, Japan. tshibuki@east.ncc.go.jp.ORCID http://orcid.org/0000-0001-7302-7691
Riu YamashitaDivision of Translational Informatics, Exploratory Oncology Research and Clinical Trial Center, National Cancer Center Hospital East, Kashiwa, Japan.
Tadayoshi HashimotoDepartment for the Promotion of Drug and Diagnostic Development, Division of Drug and Diagnostic Development Promotion, Translational Research Support Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Takao FujisawaDepartment for the Promotion of Drug and Diagnostic Development, Division of Drug and Diagnostic Development Promotion, Translational Research Support Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Mitsuho ImaiDepartment for the Promotion of Drug and Diagnostic Development, Division of Drug and Diagnostic Development Promotion, Translational Research Support Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Junichiro YudaDepartment of Hematology, National Cancer Center Hospital East, Kashiwa, Japan.
Takeshi KuwataDepartment of Genetic Medicine and Services, National Cancer Center Hospital East, Kashiwa, Japan.
Toshihiro MisumiDepartment of Data Science, National Cancer Center Hospital East, Chiba, Japan.
Yoshiaki NakamuraDepartment for the Promotion of Drug and Diagnostic Development, Division of Drug and Diagnostic Development Promotion, Translational Research Support Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Hideaki BandoDepartment for the Promotion of Drug and Diagnostic Development, Division of Drug and Diagnostic Development Promotion, Translational Research Support Office, National Cancer Center Hospital East, 6-5-1, Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Kaname KojimaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Sayuri TokiokaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Ippei ChibaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Naoki NakayaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Atsushi HozawaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Seizo KoshibaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Nobuo FuseTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Sakae SaitoTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Ritsuko ShimizuTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Woong-Yang ParkGxD Inc., Kashiwa, Japan.
Kengo KinoshitaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
Takayuki YoshinoDepartment of Gastroenterology and Gastrointestinal Oncology, National Cancer Center Hospital East, Kashiwa, Japan.

Funding

Japan Agency for Medical Research and Development 23tk0124005h0001Japan Agency for Medical Research and Development 24tk0124005h0002Japan Agency for Medical Research and Development 25tk0124005h0003
6 · The paper itself

Abstract

backgroundEarly detection of cancer and precise recurrence monitoring remain major unmet needs in oncology. Conventional screening is limited to a few cancer types, leaving nearly half of cancers without established programs. Multi-cancer early detection (MCED) tests based on circulating tumor biomarkers have shown promise, but sensitivity for early-stage remains a challenge. In parallel, detection of molecular residual disease (MRD) using circulating tumor DNA (ctDNA) has emerged as a powerful prognostic and predictive tool, though current assays remain limited in sensitivity and specificity. This study aims to integrate multi-omics data to develop more refined and highly sensitive MCED and MRD assays.

methodsThis study leverages clinical information and biospecimens from patients with cancer and cancer-naïve individuals. Samples from patients with cancers will be derived from the MONSTAR-SCREEN-3 study, while those from cancer-naïve individuals will be obtained from the Tohoku Medical Megabank Project. Comprehensive analyses will include whole-genome sequencing (WGS), whole-exome sequencing (WES), whole-transcriptome sequencing (WTS), proteomics, metabolomics, and microbiome profiling using stool and saliva. Artificial intelligence (AI)-based multi-omics integration will be performed to develop novel MCED and MRD assays and to evaluate their clinical performance. The primary endpoints are the sensitivity and specificity of MCED and MRD assays. DISCUSSION: This is the first large-scale study to integrate comprehensive multi-omics profiling with AI for MCED and MRD assay development. The findings are expected to advance precision oncology by improving early diagnosis and recurrence monitoring.

trial registrationUMIN000053815, approved by the Institutional Review Board of the National Cancer Center Hospital East.

Indexed as

Artificial IntelligenceEarly Detection of CancerNeoplasm, ResidualNeoplasmsBiomarkers, TumorCirculating Tumor DNAHumansLiquid BiopsyMultiomicsNeoplasm Recurrence, LocalBiomarkers, TumorCirculating Tumor DNACancer screeningCell-free DNACirculating tumor DNAMCEDMulti-cancer early detectionMultiomics

Identifiers

PMID41790338
PMCPMC13102821

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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.