Single‐Cell Analysis Identified a Recurrent Malignant‐Associated Transcriptional State in Colorectal Cancer

Colorectal cancer (CRC) exhibits substantial molecular heterogeneity, yet detailed single-cell transcriptomic data from Japanese patients remain limited. Here, we performed single-cell RNA sequencing (scRNA-seq) on tumor tissues and adjacent normal tissues from four Japanese CRC patients to characterize malignant cell populations. We identified a common cancer-associated cell cluster observed across all four cases, characterized by high expression of the long noncoding RNA KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1). Further analysis revealed a marked decrease in Ras Association Domain Family Member 6 (RASSF6) expression within this cluster, despite clinical datasets reporting that elevated RASSF6 expression correlates with poor overall survival in Western cohorts. Reanalysis of publicly available bulk RNA-seq data from independent East Asian cohorts confirmed that RASSF6 expression was consistently reduced in tumor tissues compared with adjacent normal colon tissues, while KCNQ1OT1 expression showed no apparent differences across cohorts. Collectively, our single-cell analysis delineates a recurrent cancer-associated transcriptional state observed within this cohort and highlights distinct gene expression features that may be underappreciated by bulk or population-averaged analyses, underscoring the value of single-cell profiling for refining molecular interpretations of CRC.

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Publication Details

Journal
Cancer Science
Published
2026-03-02
DOI
https://doi.org/10.1111/cas.70335
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Single‐Cell Analysis Identified a Recurrent Malignant‐Associated Transcriptional State in Colorectal Cancer

Kiyomi Imamura, Yukie Kashima, Kentaro Sawada, Yoshihiko Hirohashi et al.
Cancer Science
Single-cell and spatial transcriptomics
article

Single‐Cell Analysis Identified a Recurrent Malignant‐Associated Transcriptional State in Colorectal Cancer

Kiyomi Imamura, Yukie Kashima, Kentaro Sawada, Yoshihiko Hirohashi, Toshihiko Torigoe, Yuta Kuze, Motohiro Kojima, Miho Ozawa, Shinichi Hashimoto, H. Taniguchi, Sadahiro Iwabuchi, Yutaka Suzuki, Hideaki Bando, Atsushi Tajima, Takayuki Yoshino, Kazumi Abe
article en

Abstract

Colorectal cancer (CRC) exhibits substantial molecular heterogeneity, yet detailed single-cell transcriptomic data from Japanese patients remain limited. Here, we performed single-cell RNA sequencing (scRNA-seq) on tumor tissues and adjacent normal tissues from four Japanese CRC patients to characterize malignant cell populations. We identified a common cancer-associated cell cluster observed across all four cases, characterized by high expression of the long noncoding RNA KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1). Further analysis revealed a marked decrease in Ras Association Domain Family Member 6 (RASSF6) expression within this cluster, despite clinical datasets reporting that elevated RASSF6 expression correlates with poor overall survival in Western cohorts. Reanalysis of publicly available bulk RNA-seq data from independent East Asian cohorts confirmed that RASSF6 expression was consistently reduced in tumor tissues compared with adjacent normal colon tissues, while KCNQ1OT1 expression showed no apparent differences across cohorts. Collectively, our single-cell analysis delineates a recurrent cancer-associated transcriptional state observed within this cohort and highlights distinct gene expression features that may be underappreciated by bulk or population-averaged analyses, underscoring the value of single-cell profiling for refining molecular interpretations of CRC.

Cancer Science
Kanazawa University (JP), Sapporo Medical University (JP), Wakayama Medical University (JP), Kyoto Prefectural University of Medicine (JP), Kushiro Rosai Hospital (JP), Aichi Cancer Center (JP), National Cancer Center Hospital East (JP), The University of Tokyo (JP)
No poverty
Openalex Percentile: Top 35%
Single-cell and spatial transcriptomics
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