Presentation Information
[P01-125]Transcriptomic profiling of circulating tumor cells for the discovery of prognostic biomarkers
○Sakurako SATO1, Takatsugu OKEGAWA2, Yoshiko KANOU1, Takeru KOBAYASHI1, Mayumi DEKI2, Yu NAKAMURA2, Tsuyoshi TANAKA1, Tomoko YOSHINO1 (1. Division of Biotechnology and Life Science, Institute of Engineering, Tokyo University of Agriculture and Technology (Japan), 2. Department of Urology, School of Medicine, Kyorin University (Japan))
Keywords:
Circulating tumor cell,Urothelial carcinoma,Single-cell RNA sequence,Metastasis,prognostic biomarkers
[Purpose]
Cancer remains a leading cause of mortality worldwide. Although tissue biopsy is the gold standard for diagnosis, it is invasive and unsuitable for repeated sampling. Liquid biopsy, which analyzes body fluids such as blood and urine, offers a minimally invasive alternative. Circulating tumor cells (CTCs), shed from primary or metastatic lesions into the bloodstream, are a promising target analyte. However, their rarity in circulation makes isolation technically challenging and limits downstream analyses such as transcriptomic profiling. In this study, we isolated CTCs from urothelial carcinoma patients using our Microcavity Array (MCA)/Gel-based Cell Manipulation (GCM) platform, followed by single-cell RNA sequencing (scRNA-seq) to identify prognostic markers and assess transcriptional heterogeneity.
[Method]
CTCs were isolated from 2 mL blood samples obtained from 22 patients using the MCA/GCM platform, a size-based cell recovery system. Cells captured on an MCA device were encapsulated in hydrogel via light-induced gelation for single-cell isolation, followed by scRNA-seq.
Differential gene expression and survival analysis were conducted to identify candidate prognostic biomarkers. To evaluate the generalizability of identified transcriptional signatures, integrative analyses of scRNA-seq datasets across multiple cancer types were performed using unsupervised clustering.
[Results&Consideration]
A total of 86 single CTCs were successfully isolated and analyzed. Among genes upregulated in metastatic cases, gene X showed the strongest increase, and survival analysis revealed that its high expression prior to radical cystectomy was associated with shorter overall survival, indicating its potential utility as an early prognostic marker. This association was also observed in independent datasets from gastric and breast cancer CTCs, suggesting broader clinical relevance across tumor types.
Integrated clustering analysis identified three transcriptionally distinct CTC phenotypes characterized by (i) platelet-adhesion and cytoskeletal reprogramming, (ii) transcriptional activation, and (iii) translational and protein processing activities. CTCs from patients with poor prognosis were enriched in specific clusters in a cancer type-dependent manner. Notably, gene X-high CTCs were consistently localized within these clusters, despite differences in underlying transcriptional programs. These findings suggest that diverse pathways may drive metastatic progression across cancer types, while gene X serves as a convergent biomarker of aggressive disease.
[Conclusion]
This study identified gene X as a promising prognostic marker in CTCs and demonstrated the transcriptional heterogeneity of CTCs through scRNA-seq. Furthermore, the MCA/GCM platform provides a robust technical framework for transcriptomic profiling of rare cells, highlighting the value of CTC transcriptomics for biomarker discovery and offering mechanistic insights into cancer progression.
Cancer remains a leading cause of mortality worldwide. Although tissue biopsy is the gold standard for diagnosis, it is invasive and unsuitable for repeated sampling. Liquid biopsy, which analyzes body fluids such as blood and urine, offers a minimally invasive alternative. Circulating tumor cells (CTCs), shed from primary or metastatic lesions into the bloodstream, are a promising target analyte. However, their rarity in circulation makes isolation technically challenging and limits downstream analyses such as transcriptomic profiling. In this study, we isolated CTCs from urothelial carcinoma patients using our Microcavity Array (MCA)/Gel-based Cell Manipulation (GCM) platform, followed by single-cell RNA sequencing (scRNA-seq) to identify prognostic markers and assess transcriptional heterogeneity.
[Method]
CTCs were isolated from 2 mL blood samples obtained from 22 patients using the MCA/GCM platform, a size-based cell recovery system. Cells captured on an MCA device were encapsulated in hydrogel via light-induced gelation for single-cell isolation, followed by scRNA-seq.
Differential gene expression and survival analysis were conducted to identify candidate prognostic biomarkers. To evaluate the generalizability of identified transcriptional signatures, integrative analyses of scRNA-seq datasets across multiple cancer types were performed using unsupervised clustering.
[Results&Consideration]
A total of 86 single CTCs were successfully isolated and analyzed. Among genes upregulated in metastatic cases, gene X showed the strongest increase, and survival analysis revealed that its high expression prior to radical cystectomy was associated with shorter overall survival, indicating its potential utility as an early prognostic marker. This association was also observed in independent datasets from gastric and breast cancer CTCs, suggesting broader clinical relevance across tumor types.
Integrated clustering analysis identified three transcriptionally distinct CTC phenotypes characterized by (i) platelet-adhesion and cytoskeletal reprogramming, (ii) transcriptional activation, and (iii) translational and protein processing activities. CTCs from patients with poor prognosis were enriched in specific clusters in a cancer type-dependent manner. Notably, gene X-high CTCs were consistently localized within these clusters, despite differences in underlying transcriptional programs. These findings suggest that diverse pathways may drive metastatic progression across cancer types, while gene X serves as a convergent biomarker of aggressive disease.
[Conclusion]
This study identified gene X as a promising prognostic marker in CTCs and demonstrated the transcriptional heterogeneity of CTCs through scRNA-seq. Furthermore, the MCA/GCM platform provides a robust technical framework for transcriptomic profiling of rare cells, highlighting the value of CTC transcriptomics for biomarker discovery and offering mechanistic insights into cancer progression.
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