WGS analyzes the entire genome to identify germline and somatic mutations, CNVs, and structural variations, providing critical data for drug development and biomarker discovery.

Technical Overview

By comprehensively analyzing the entire genome to detect germline/somatic mutations, Copy Number Variations (CNV), and Structural Variations (SV), WGS offers a complete genetic blueprint.

Leveraging CTC-based liquid biopsy, Cytogen delivers high-quality whole-genome data even for patients where traditional tissue acquisition is challenging.

Features

• Comprehensive variant discovery across the entire genomic landscape.
• Optimized for tumor heterogeneity, metastasis mechanisms, and drug resistance research
• Customized bioinformatics pipelines (supports Germline, Somatic, and Joint analysis).

Applications

• Identification of novel targets for anti-cancer drug development.
• Discovery of new biomarkers.
• Development of personalized precision medicine platforms

WES focuses on protein-coding regions to detect clinically significant variants, optimizing companion diagnostics and treatment response prediction.

Technical Overview

WES provides an efficient approach by specifically analyzing exons—the protein-coding regions of the genome—to identify variants with high clinical relevance.

By utilizing CTC-derived DNA instead of tissue, Cytogen enables high-precision analysis while reducing the burden on patients.

Features

• Concentration on genomic regions with high clinical relevance
• Optimized for developing companion diagnostic panels and predicting therapeutic responses
• Capability to discover rare variants

Applications

• Discovery of biomarkers to predict treatment responses
• Companion diagnostic (CDx) development
• Clinical research and patient-tailored treatment design

Based on specific gene panels, high-sensitivity analysis is conducted to validate therapeutic targets and screen patients for clinical trials.

Technical Overview

Targeted Sequencing provides high-sensitivity and high-precision analysis based on specific gene panels.

It enables panel designs customized to research objectives and is optimized for companion diagnostics and therapeutic target validation.

Features

• High-sensitivity variant detection based on specific genes or panels
• Supports analysis of low-quantity samples
• Supports customized panel design

Applications

• Validation of therapeutic target genes
• Patient-tailored treatment design
• Clinical trial patient screening and CDx development

scRNA-seq analyzes gene expression at the single-cell level to identify intratumoral heterogeneity, rare cells, and mechanisms of metastasis and immune evasion.

Technical Overview

scRNA-seq measures gene expression at the single-cell level to identify intratumoral heterogeneity, rare cells, and cell-to-cell interactions.

Further analyses, including pseudotime and immune repertoire (V(D)J), enable the interpretation of metastasis, differentiation processes, and the immune environment.

Features

• Identification of rare cancer cells and immune cell clusters
• Analysis of intratumoral heterogeneity and metastasis mechanisms
• Verification of gene expression and clonal diversity at the single-cell level

Applications

• Research on cancer cell-immune cell interactions
• Identification of metastasis and resistance mechanisms
• Discovery of novel immune biomarkers
• Prediction of response to cancer immunotherapy

qPCR quantifies specific gene expression to monitor patients and validate candidate biomarkers.

Technical Overview

qPCR quantitatively measures the expression levels of specific genes, facilitating comparative analysis and monitoring of patients before and after treatment.

Features

• Rapid and precise quantification of gene expression
• Evaluation of treatment response and validation of candidate biomarkers
• Applicable to various cancer-specific genes

Applications

• Monitoring patient response to treatment
• Tracking expression changes before and after anticancer therapy
• Supplementary diagnostics for clinical research

ddPCR enables ultra-low concentration variant detection, making it effective for Minimal Residual Disease (MRD) monitoring and tracking therapeutic efficacy.

Technical Overview

ddPCR is a next-generation PCR technology capable of precisely detecting even ultra-low concentrations of DNA/RNA mutations.
It is specifically optimized for Minimal Residual Disease (MRD) monitoring and the early detection of recurrence risk.

Features

• Precision detection of ultra-low concentration mutations
• High reproducibility and precision
• Stable detection even in CTC-based samples

Applications

• MRD-based cancer recurrence risk assessment
• Monitoring of anticancer drug efficacy
• Patient-tailored treatment strategy development

By integrating various omics data tailored to research objectives and clinical conditions, we provide customized analytical solutions.

Technical Overview

Multi-omics involves the integrated analysis of diverse data—including genomics, transcriptomics, proteomics, and metabolomics—to comprehensively interpret the complex molecular mechanisms and phenotypes of cancer. By combining NGS data with analysis results from rare cells like CTCs, we derive multidimensional insights through advanced bioinformatics techniques.

Features

• Data fusion and integrated correlation analysis across different molecular layers
• Customized data interpretation and visualization linked to clinical data
• Discovery of biomarkers and therapeutic targets
• Identification of multifaceted causes of disease, including complex disorders, cancer heterogeneity, and evolutionary patterns

Applications

• Tracking cancer heterogeneity and clonal evolution
• Discovery of novel biomarkers and therapeutic targets
• Companion diagnostics and drug development research
• Patient-tailored clinical strategies and treatment response prediction
• Rare cell-based omics research and case reporting