Molecular analysis of tumor recurrence using established cancer stem cell-line and drug discovery

Despite advances in adjuvant therapy for colorectal cancer, tumor relapses, often driven by minimal residual disease, remain a formidable clinical challenge. The cancer stem cell hypothesis provides a key framework for understanding this problem, positing that a small, therapy-resistant subpopulation of cells drives recurrence. To elucidate the role of these cells, we developed LGR5-specific monoclonal antibodies and a high-sensitivity immunofluorescence method to visualize the stem cell marker LGR5 in clinical tumors. Furthermore, we established a unique colorectal cancer cell line, PLR123, which maintains robust stem cell properties, and developed an in vitro model to study tumor recurrence. Through analyses including single-cell RNA sequencing and small molecule screening, we identified the RNA Polymerase I inhibitor BMH-21 as a compound that effectively suppresses recurrence both in vitro and in vivo. This article comprehensively reviews our series of studies on understanding the mechanisms of cancer stem cell-driven resistance and offers insights supporting the development of novel therapies aimed at preventing tumor relapses.

Authors

Institutions

Publication Details

Journal
International Journal of Clinical Oncology
Published
2026-01-20
DOI
https://doi.org/10.1007/s10147-025-02948-2
Primary Topic
Cancer Cells and Metastasis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecular analysis of tumor recurrence using established cancer stem cell-line and drug discovery

Kentaro Nonaka, Tetsuro Kawazoe, Shigeto Kawai, EMI OKI et al.
International Journal of Clinical Oncology
Cancer Cells and Metastasis
article

Molecular analysis of tumor recurrence using established cancer stem cell-line and drug discovery

Kentaro Nonaka, Tetsuro Kawazoe, Shigeto Kawai, EMI OKI, Masami Suzuki, Chiyoko Nishime, Norifumi Harimoto, Yoko Zaitsu, Genta Nagae, Koichi Andō, H. Aburatani, Sachie Omori, Tatsumi Yamazaki, Masaki Yamazaki, Keita Natsugoe, Hiroshi Saeki, Kiyotaka Nakano, Yoshihiko Maehara, Mitsuhiko Ota
article en

Abstract

Despite advances in adjuvant therapy for colorectal cancer, tumor relapses, often driven by minimal residual disease, remain a formidable clinical challenge. The cancer stem cell hypothesis provides a key framework for understanding this problem, positing that a small, therapy-resistant subpopulation of cells drives recurrence. To elucidate the role of these cells, we developed LGR5-specific monoclonal antibodies and a high-sensitivity immunofluorescence method to visualize the stem cell marker LGR5 in clinical tumors. Furthermore, we established a unique colorectal cancer cell line, PLR123, which maintains robust stem cell properties, and developed an in vitro model to study tumor recurrence. Through analyses including single-cell RNA sequencing and small molecule screening, we identified the RNA Polymerase I inhibitor BMH-21 as a compound that effectively suppresses recurrence both in vitro and in vivo. This article comprehensively reviews our series of studies on understanding the mechanisms of cancer stem cell-driven resistance and offers insights supporting the development of novel therapies aimed at preventing tumor relapses.

International Journal of Clinical OncologyVol. 31(3)
Kyushu University (JP), Tokyo University of Science (JP), Yokohama University of Pharmacy (JP), Central Institute for Experimental Animals (JP), Fukuoka University Hospital (JP), The University of Tokyo (JP)
Good health and well-being
Openalex Percentile: Top 84%
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.