Fully customized panel content and sequencing depth to align precisely with your unique therapeutic targets, from small validation cohorts to large-scale research cohort stratification.
Oncogene Mutation & Copy Number Alteration Analysis Service
Creative Biolabs provides a succinct overview of our commitment to accelerating oncology research. We deliver a high-resolution, integrated analysis of both oncogene mutations and copy number alterations (CNAs) in a single assay. Our clients gain mechanistic clarity through proprietary AI-driven network models that link these genomic changes directly to the functional dysregulation of the Cancer Hallmarks. This actionable data allows researchers to rapidly prioritize targets, stratify experimental cohorts, and gain deeper insight into the complex drivers of cancer progression.
Introduction What We Can Offer Workflow Why Creative Biolabs Customer Reviews FAQs Related Services Contact Us
Decoding Cancer Drivers via Multiplex Genomic Analysis
Identifying key somatic genomic alterations in cancer is vital for research decisions. Traditional sequencing focuses on point mutations, but CNAs - amplifications or deletions - are equally essential drivers. This service integrates high-sensitivity sequencing to quantify both mutations and CNAs simultaneously. Analysis is enhanced by advanced bioinformatics, including 3D protein structure mapping and AI network modeling to link CNAs directly to the functional Hallmarks of Cancer, providing functional context for every genetic change.
Request a formal consultation to assess project suitability.
Fig.1 Various methods to characterize and quantify copy number alterations. 1
What We Can Offer
Bespoke Assay Design
Functional Pathway Insight
Proprietary AI-driven network modeling provides mechanistic clarity by functionally correlating CNAs with the ten Cancer Hallmarks, offering insights into pathway dysregulation that traditional methods miss.
Structural Driver Validation
Implementation of advanced 3D protein structural bioinformatics to map and validate oncogenic "driver" hotspots, significantly reducing false-positive targets and focusing resources efficiently.
Oncogene Mutation & Copy Number Alteration Analysis at Creative Biolabs
Why Choose Us?
| Key Advantages | Unique Features |
|---|---|
| Integrated Multi-Omic Insight | We deliver an integrated view of oncogene activation - from sequence-level variants to chromosome-level CNAs - in a single, comprehensive analysis. |
| Mechanistic Clarity | Our AI-driven network modeling offers a functional context for every alteration, defining how the genomic landscape drives the research phenotype by correlating CNAs with pathway dysregulation. |
| Structural Differentiation | The proprietary 3D protein structural analysis ensures we prioritize drivers with clustered mutations that are most likely to represent functionally active hotspots, reducing false positives in target identification. |
To ascertain the full benefit of the Creative Biolabs platform, prospective clients are encouraged to submit a formal request for a pricing quotation today.
Customer Reviews
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Liquid Biopsy Sensitivity
The utilization of Creative Biolabs' dual next-generation sequencing (NGS) and digital droplet PCR (ddPCR) service established robust reliability for our liquid biopsy surveillance protocol. The inherent high sensitivity of the platform enabled the detection of minimal genomic evolution in our in vivo models. - Dr. K*n H**es. -
Targeting Functional Pathways
Creative Biolabs' service provided a clear gene-hallmark dysregulation map that facilitated our pre-clinical work. We were able to switch our focus from a broadly mutated gene to a different gene whose CNA had a higher correlation with the inducing angiogenesis hallmark, accelerating our target selection. - Dr. A**a S**th.
FAQs
What is the main advantage of combining Mutation and CNA analysis compared to running them separately?
Combining them ensures you capture the complete picture of oncogene activation in a single, verified workflow. Many tumors are driven by CNAs without a corresponding mutation. Our integrated, dual-modality approach eliminates the risk of missing critical drivers and saves valuable sample input.
How does Creative Biolabs' bioinformatic approach compare to public tools like GISTIC or simple frequency-based scoring?
Unlike tools that primarily rank CNAs by frequency, Creative Biolabs' pipeline employs AI-driven network propagation to link the CNA to its functional consequence. Additionally, our 3D structural analysis provides a novel layer of evidence, differentiating true functional hotspots from random changes, significantly increasing the confidence in driver prioritization.
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Single-Cell Transcriptome and Lineage Tracing
Provides unparalleled resolution by quantifying the transcriptome of individual tumor cells while simultaneously tracing cellular lineage using proprietary barcoding methods. This service is essential for dissecting intratumoral heterogeneity, mapping cellular evolution, and understanding the fate decisions of tumor and immune cells within the TME.
Learn More →Tumor Metabolic Profiling
Provides quantitative assessment of metabolic flux, hypoxia, and pH within the tumor microenvironment. This profiling directly assesses the reprogramming energy metabolism hallmark, linking genomic drivers and protein activity to functional changes in glucose/lactate utilization and the acidic TME.
Learn More →How to Contact Us
By fusing high-fidelity dual-modality sequencing with advanced 3D structural and AI-driven functional bioinformatics, Creative Biolabs delivers the comprehensive, actionable genomic intelligence required to accelerate target validation, optimize experimental design, and drive your next breakthrough. Kindly contact our specialized team for comprehensive information and detailed project discussion.
Reference
- Tan, Elaine S et al. "Copy Number Alterations as Novel Biomarkers and Therapeutic Targets in Colorectal Cancer." Cancers vol. 14,9 2223. 29 Apr. 2022. Distributed under an Open Access license CC BY 4.0, without modification. https://doi.org/10.3390/cancers14092223
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