AI-integrated multi-omics platform to revolutionize anti-metastatic therapy development through circulating tumor cell profiling: SCRUM-MONSTAR-CTC

BACKGROUND: Metastatic disease remains the leading cause of cancer-related death, yet most precision oncology strategies still emphasize profiling primary tumors and tracking cell-free tumor DNA (ctDNA). Although ctDNA has transformed genomic profiling, molecular residual disease monitoring, and early cancer detection, it cannot directly capture viable tumor cell states, phenotypic plasticity, or functional adaptations that drive metastatic spread. We propose that the next phase of precision oncology should integrate the cellular dimension of metastasis through systematic circulating tumor cell (CTC) profiling. METHODS: The SCRUM-MONSTAR platform, one of the largest pan-cancer molecular profiling initiatives in Japan, offers an exceptional foundation for this transition through its nationwide infrastructure for multi-omics analysis, longitudinal biospecimen collection, and artificial intelligence-enabled clinical interpretation. By combining matched tissue profiling, serial ctDNA analysis, single-cell CTC transcriptomics, metabolomics, and organoid- and mouse-based functional modeling, SCRUM-MONSTAR-CTC could evolve into a translational ecosystem for anti-metastatic drug discovery. Within this framework, we highlight adherent-to-suspension transition (AST) as one representative, experimentally tractable plasticity program that enables tumor cells to survive in circulation and subsequently colonize distant organs. DISCUSSION: We envision that identifying and therapeutically targeting AST-related and other metastatic plasticity programs across tumor types will provide a path toward clinically actionable anti-metastatic therapies. More broadly, this framework could enable the identification of metastatic vulnerabilities, the development of biomarker-guided anti-metastatic trials, and the reverse translation of patient-derived discoveries into early-phase clinical testing. Precision oncology must move beyond cataloging tumor genomes and begin targeting metastasis as a dynamic biological process. TRIAL REGISTRATION: UMIN000056873, approved by the Institutional Review Board of the National Cancer Center Hospital East.

Authors

Institutions

Publication Details

Journal
International Journal of Clinical Oncology
Published
2026-07-27
DOI
https://doi.org/10.1007/s10147-026-03149-1
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-integrated multi-omics platform to revolutionize anti-metastatic therapy development through circulating tumor cell profiling: SCRUM-MONSTAR-CTC

Shin Kobayashi, 朋絵 村上, Izumi Miki, Taro Shibuki et al.
International Journal of Clinical Oncology
Cancer Cells and Metastasis
article

AI-integrated multi-omics platform to revolutionize anti-metastatic therapy development through circulating tumor cell profiling: SCRUM-MONSTAR-CTC

Shin Kobayashi, 朋絵 村上, Izumi Miki, Taro Shibuki, Zedao Liu, Tadayoshi Hashimoto, Shugo Yajima, Yasutoshi Sakamoto, Shogen Boku, Naoko Iida, Haruki KURANO, Masataka Amisaki, Mitsuho Imai, Junichiro Yuda, Kensuke Matsuda, Heon Yung Gee, Hideaki Bando, Takayuki Yoshino, Hee Seung Lee, Yoshiaki Nakamura, Hyun Woo Park, Mizuho Kikuchi, Jun Masuda, Hyoju Kim, Atsuko Shimizu, Takao Fujisawa, Riu Yamashita
article en

Abstract

BACKGROUND: Metastatic disease remains the leading cause of cancer-related death, yet most precision oncology strategies still emphasize profiling primary tumors and tracking cell-free tumor DNA (ctDNA). Although ctDNA has transformed genomic profiling, molecular residual disease monitoring, and early cancer detection, it cannot directly capture viable tumor cell states, phenotypic plasticity, or functional adaptations that drive metastatic spread. We propose that the next phase of precision oncology should integrate the cellular dimension of metastasis through systematic circulating tumor cell (CTC) profiling. METHODS: The SCRUM-MONSTAR platform, one of the largest pan-cancer molecular profiling initiatives in Japan, offers an exceptional foundation for this transition through its nationwide infrastructure for multi-omics analysis, longitudinal biospecimen collection, and artificial intelligence-enabled clinical interpretation. By combining matched tissue profiling, serial ctDNA analysis, single-cell CTC transcriptomics, metabolomics, and organoid- and mouse-based functional modeling, SCRUM-MONSTAR-CTC could evolve into a translational ecosystem for anti-metastatic drug discovery. Within this framework, we highlight adherent-to-suspension transition (AST) as one representative, experimentally tractable plasticity program that enables tumor cells to survive in circulation and subsequently colonize distant organs. DISCUSSION: We envision that identifying and therapeutically targeting AST-related and other metastatic plasticity programs across tumor types will provide a path toward clinically actionable anti-metastatic therapies. More broadly, this framework could enable the identification of metastatic vulnerabilities, the development of biomarker-guided anti-metastatic trials, and the reverse translation of patient-derived discoveries into early-phase clinical testing. Precision oncology must move beyond cataloging tumor genomes and begin targeting metastasis as a dynamic biological process. TRIAL REGISTRATION: UMIN000056873, approved by the Institutional Review Board of the National Cancer Center Hospital East.

International Journal of Clinical Oncology
Kansai Medical University (JP), Yonsei University (KR), Keio University (JP), University of Oxford (GB), The Cancer Institute Hospital (JP), National Cancer Center Hospital East (JP), Japanese Foundation For Cancer Research (JP)
Japan Agency for Medical Research and Development, National Cancer Center Japan, Kaken Pharmaceutical, Korea Health Industry Development Institute
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Cancer Cells and Metastasis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.