AbstractBackground:Liquid biopsy offers a minimally invasive alternative to tissue biopsy, enabling therapeutic monitoring, precision medicine-based treatment decisions, and detection of tumor heterogeneity. Circulating tumor cell (CTC) analysis is a promising minimally invasive biomarker for monitoring treatment response and stratifying prognosis in EGFR-mutant non-small cell lung cancer (NSCLC). Meanwhile, detection of CTCs in peripheral blood is challenging due to their rarity and the limitations of both marker-dependent and marker-independent isolation techniques, which may compromise sensitivity and specificity. Continuous Centrifugal Microfluidics - Circulating Tumor Cell Disc (CCM-CTCD) enriches heterogeneous CTCs through automated microfluidic extraction and leukocyte depletion without interrupting centrifugation.Method:In this study, 77 EGFR-mutant NSCLC patients treated with EGFR-TKIs were enrolled. CTCs were isolated using CCM-CTCD before and after EGFR-TKI treatment and compared with plasma cfDNA and tissue biopsy for EGFR mutation analysis. CK-positive, CD45-negative CTCs were isolated and visualized using immunofluorescence staining. Patients were categorized as CTC molecular responders or non-responders based on a ≥30% reduction in CTC count from baseline. Progression-free survival (PFS) and tumor burden changes were evaluated.Results:The CCM-CTCD method showed concordance with Cobas® liquid biopsy but demonstrated superior sensitivity in detecting EGFR mutations. Mutational discordance between tissue, plasma cfDNA, and CTCs highlighted tumor heterogeneity. CTC molecular responders had significantly longer median PFS (46.3 vs. 12.2 months) and greater tumor burden reduction (-39.2% vs. -32.2%, p = 0.025) compared to non-responders. Multivariable analysis revealed that CTC molecular response was an independent predictor of improved PFS (HR 0.45, p = 0.023). Additionally, a non-significant trend was observed toward shorter PFS in patients receiving later-line treatments compared to first-line (HR 1.30, p = 0.523), first- or second-generation EGFR-TKIs compared to third-generation EGFR-TKIs (HR 1.59, p = 0.196), and in those with a history of smoking (HR 1.45, p = 0.300). CTC profiling was found to complement traditional methods for identifying genomic alterations and predicting early progression.Conclusion:CTC analysis using CCM-CTCD demonstrates potential as a reliable tool for predicting treatment response and stratifying prognosis in EGFR-mutant NSCLC. Stratifying patients based on CTC molecular response may guide treatment intensification strategies, offering a pathway for risk-adapted precision oncology. Prospective studies are warranted to validate these findings and optimize therapeutic decision-making.Citation Format:Seoyoung Lee, Chaeyeon Kim, Chang Gon Kim, Min Hee Hong, Mina Han, Wonrak Son,Gamin Kim, Minseok Kim, Hye Ryun Kim. Circulating tumor cell-based molecular responses stratify EGFR-TKI efficacy in EGFR-mutant lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 1987.

26 Dec 2024·Bioinformatics

Quantitative analysis of the dexamethasone side effect on human-derived young and aged skeletal muscle by myotube and nuclei segmentation using deep learning

Article

Author: Kim, Minseok S ; Park, Seonghwan ; Kim, Min Young ; Jeong, Jaewon ; Yang, Sohae ; Moon, Inkyu

AbstractMotivationSkeletal muscle cells (skMCs) combine together to create long, multi-nucleated structures called myotubes. By studying the size, length, and number of nuclei in these myotubes, we can gain a deeper understanding of skeletal muscle development. However, human experimenters may often derive unreliable results owing to the unusual shape of the myotube, which causes significant measurement variability.ResultsWe propose a new method for quantitative analysis of the dexamethasone side effect on human-derived young and aged skeletal muscle by simultaneous myotube and nuclei segmentation using deep learning combined with post-processing techniques. The deep learning model outputs myotube semantic segmentation, nuclei semantic segmentation, and nuclei center, and post-processing applies a watershed algorithm to accurately distinguish overlapped nuclei and identify myotube branches through skeletonization. To evaluate the performance of the model, the myotube diameter and the number of nuclei were calculated from the generated segmented images and compared with the results calculated by human experimenters. In particular, the proposed model produced outstanding outcomes when comparing human-derived primary young and aged skMCs treated with dexamethasone. The proposed standardized and consistent automated image segmentation system for myotubes is expected to help streamline the drug-development process for skeletal muscle diseases.Availability and implementationThe code and the data are available at https://github.com/tdn02007/QA-skMCs-Seg

13 Nov 2024·Clinical Cancer Research

Abstract PR002: The clinical relevance of circulating tumor cell size in head and neck squamous cell carcinoma patients

Author: Lee, Sun Min ; Oh, So Yeon ; Woo, Hyeongjung ; Shin, Hyun Young ; Kim, Minseok S.

AbstractCirculating tumor cells (CTCs) play a critical role in the metastatic process of cancer and are widely recognized as important biomarkers that provide valuable information related to tumor characteristics. While most research to date has focused on the biological markers and molecular properties of CTCs, their physical characteristics, particularly size, have been relatively underexplored. However, recent studies suggest that smaller CTCs exhibit enhanced tumor- initiating and metastatic abilities compared to larger CTCs. This indicates that CTC size is not merely a physical trait but may directly influence the invasiveness and metastatic potential of tumors. Such findings suggest that CTC size could be an important indicator for predicting tumor malignancy and provide a new perspective on understanding cancer progression and metastasis. As such, there is a growing emphasis on research that considers the size of CTCs. In this study, it was speculated whether CTC size holds clinical significance in patients with head and neck squamous cell carcinoma (HNSCC). The study was involved with 20 HNSCC patients, analyzing the morphological characteristics of CTCs collected from blood samples before and after treatment, while exploring the potential for monitoring treatment response. Our results found that CTCs were detected 20% more frequently in oropharyngeal cancer (OPC) patients compared to non-OPC patients. This is likely due to the rich vascularity in the oropharyngeal region, which may facilitate greater entry of CTCs into the bloodstream. Additionally, the cell size (23.9 μm in average) and nuclear size (16.4 μm in average) of HPV-positive patients were 32% and 10% larger, respectively, than those of HPV-negative patients (cell size: 18.1 μm; nuclear size: 12.60 μm). This suggests that the sizes of CTC and their nuclei may be associated with HPV status, which is presumed to be due to HPV causing disruptions in the cell cycle. In addition, we could successfully cultivate the CTCs obtained from HPV-positive patients with relatively smaller CTCs for 30 days, predicting that small CTCs have affordable for CTC culture. In conclusion, this study confirms that the physical characteristics of CTCs, particularly size, are linked to HPV infection status in HNSCC patients. CTC- and nucleus- size are closely related to tumor characteristics, demonstrating the potential for developing diagnostic and prognostic tools based on these physical traits. Although more in-depth research is required, poor prognosis in HPV- positive patients may also be related to the physical characteristics of CTCs.Citation Format: Hyeongjung Woo, Hyun Young Shin, So Yeon Oh, Sun Min Lee, Minseok S. Kim. The clinical relevance of circulating tumor cell size in head and neck squamous cell carcinoma patients [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr PR002.

100 Deals associated with CTCELLS, Inc.

100 Translational Medicine associated with CTCELLS, Inc.

Corporation Tree

Boost your research with our corporation tree data.

view full example data

Pipeline

Pipeline Snapshot as of 01 Jul 2025

The statistics for drugs in the Pipeline is the current organization and its subsidiaries are counted as organizations,Early Phase 1 is incorporated into Phase 1, Phase 1/2 is incorporated into phase 2, and phase 2/3 is incorporated into phase 3

Discovery

Preclinical

Current Projects

Drug(Targets)	Indications	Global Highest Phase

CTA-01(Ctcells) ( EGFR )	Colorectal Cancer More	Preclinical
CTA-03(Ctcells) ( CD33 )	Acute Myeloid Leukemia More	Discovery
CTA-02(Ctcells) ( PDL1 )	Triple Negative Breast Cancer More	Discovery

Deal

Boost your decision using our deal data.

view full example data

Translational Medicine

Boost your research with our translational medicine data.

view full example data

Profit

Explore the financial positions of over 360K organizations with Synapse.

view full example data

Grant & Funding(NIH)

Access more than 2 million grant and funding information to elevate your research journey.

view full example data

Investment

Gain insights on the latest company investments from start-ups to established corporations.

view full example data

Financing

Unearth financing trends to validate and advance investment opportunities.

view full example data

AI Agents Built for Biopharma Breakthroughs

Accelerate discovery. Empower decisions. Transform outcomes.

Get started for free today!

Accelerate Strategic R&D decision making with Synapse, PatSnap’s AI-powered Connected Innovation Intelligence Platform Built for Life Sciences Professionals.

Start your data trial now!

Synapse data is also accessible to external entities via APIs or data packages. Empower better decisions with the latest in pharmaceutical intelligence.

Bio

Bio Sequences Search & Analysis

Chemical

Chemical Structures Search & Analysis