Scalable targeted cancer panel sequencing for efficient somatic variant profiling—ranging from focused hotspot sets to comprehensive gene lists.
CD Genomics provides an end-to-end cancer panel sequencing service for research teams that need somatic variant data with a clear workflow, transparent scope definition, and deliverables designed for downstream analysis and cohort aggregation.
Highlights
Profile somatic SNVs and small indels using targeted NGS panels
Somatic cancer targeted panel sequencing enriches predefined cancer-relevant regions to support efficient tumor profiling in research studies. Panels are commonly selected when you want deeper sequencing on a defined target space, standardized outputs across a cohort, and a streamlined path from sequencing to variant tables and summaries.
This service supports projects from panel tier selection or custom scope definition through sequencing and bioinformatics delivery, with scope and deliverables confirmed during project setup.
Use Cases
When to Use Somatic Cancer Targeted Panels
This service is commonly selected for:
Cohort tumor profiling: build mutation landscapes and frequency summaries across sample sets
Biomarker exploration: evaluate candidate genes/pathways and prioritize follow-up targets
Immuno-oncology research contexts: somatic profiling supporting immuno-oncology research contexts-related hypotheses and cohort stratification
Targeted efficiency: when whole-exome breadth is not required, but robust variant outputs are needed
Sample variability scenarios: projects involving heterogeneous sample quality (e.g., FFPE), where a QC-first intake helps guide feasible study scope
Choose a standard tier or request a custom design. Final targets and deliverables are confirmed during consultation and defined in the quotation.
Tier
Typical Scope
Best For
Core
Focused hotspots / key driver set
Rapid screening, pilot profiling, focused hypotheses
50
Small-to-mid panel for translational profiling
Cohort profiling with targeted scope
100
Mid-size panel with broader pathway coverage
Mechanism-oriented studies and biomarker work
400
Large panel for broad profiling across cancer-relevant genes
Discovery-oriented cohort studies
Comprehensive
Broadest coverage within a panel strategy
Large programs and multi-pathway exploration
How to Choose a Tier (Practical Guidance)
Core: prioritize a compact set of high-impact targets for quick screening or pilot studies
50/100: balance breadth and efficiency for translational cohorts and pathway-level questions
400/Comprehensive: broaden coverage for discovery-oriented profiling where you expect diverse drivers and mechanisms
Custom Add-On / Custom Panel
Bring your gene list, hotspot list, or regions of interest. We support customization to align with tumor type, mechanism hypotheses, and downstream analysis needs.
Common requests
Add specific genes/exons/hotspots to a standard tier
Include study-specific regions relevant to your model or cohort
Configure annotation fields in output tables for easier filtering and prioritization
Gene lists are available upon request. Below are illustrative examples of genes commonly included in somatic cancer panels. This is not a complete list; final content depends on the selected tier or custom scope.
Important: Optional modules are not automatically included. Availability depends on panel design, sequencing characteristics, and project scope, and will be confirmed in the quotation.
Deliverables
What You'll Receive (Deliverables)
Deliverables are designed for both lab teams and bioinformatics teams—clear, file-level handoffs with QC evidence.
Illustrative example. Final metrics are reported in the QC package per project.
Deliverable
Format
Included By Default
Notes
Raw sequencing data
FASTQ
Yes
Per-sample raw reads
QC package
PDF/TSV (or equivalent)
Yes
Key run and coverage/QC indicators (as scoped)
SNV/indel results
Annotated TSV and/or annotated VCF
Yes
Annotation fields and formats confirmed per project
Alignment files
BAM/CRAM
Optional
Available upon request; confirmed in quotation
Optional module outputs
TSV/VCF/PDF
Optional
CNV/SV modules if requested and feasible
Cohort summaries
TSV/Excel-friendly tables
Optional
Cohort-level aggregation if selected
Final deliverables are defined in the quotation to match your study goals and downstream pipeline.
All samples undergo incoming QC review to assess feasibility for the selected tier. If samples do not support the requested scope, we recommend practical options before wet-lab work begins, such as:
Adjusting panel scope (prioritizing key targets)
Revising the study design for the sample matrix
Aligning outputs to realistic data characteristics (RUO)
Bioinfo
Bioinformatics & Reporting
Bioinformatics is delivered as a service component to translate sequencing output into usable research results with standardized formats.
Typically Included (As Scoped)
Read processing and QC summaries
Alignment and coverage metrics
SNV/indel calling and functional annotation outputs
Optional (Project-Scoped)
CNV analysis and rearrangement-oriented analyses (when feasible and requested)
Cohort-level summaries and customized output formats for internal pipelines
Somatic cancer panel projects often face practical constraints such as limited tissue availability and variable nucleic-acid quality. This multicenter study provides an example of implementing a targeted gene panel workflow when cytology specimens are used alongside standard pathology materials.
Researchers conducted a prospective, multicenter evaluation of a targeted lung cancer gene panel workflow using cytology specimens and described a QC-first intake model (including nucleic-acid quantification and quality assessment). The panel scope included commonly profiled lung cancer genes such as EGFR, BRAF, KRAS, ERBB2, ALK, ROS1, MET, and RET.
The authors reported a high overall analytical success rate for panel testing using cytology specimens, supporting the feasibility when conventional tissue is limited. The study illustrates how QC gates and fit-for-purpose panel design can produce robust research-grade variant outputs suitable for cohort characterization.
Nucleic acid yield (A) and quality metrics (B) across cytology specimen collection methods in a prospective multicenter lung cancer study, illustrating a QC-relevant view of sample feasibility for gene panel workflows. Source: Morikawa et al., BMC Cancer (2025).
This published example reinforces a key takeaway for somatic panel projects: a QC-driven onboarding strategy and right-sized panel scope are critical when sample types and quality vary across cohorts.
Method Comparison
Choosing the Right Method
In the table below, we compare Somatic Cancer Targeted Panel Sequencing with three alternative approaches—Targeted Region Sequencing, Whole Exome Sequencing (WES), and Whole Genome Sequencing (WGS)—to help you choose the best fit based on target scope, study goals, and downstream analysis needs (RUO).
Method
Best For
Typical Strengths
Typical Trade-Offs
Somatic Cancer Targeted Panel Sequencing
Focused tumor profiling, cohorts, biomarker work
Efficient targeting; practical for cohorts; streamlined downstream analysis
Limited to targeted regions; optional CNV/SV depends on design & project scope
Genome-wide exploration including non-coding regions
Most comprehensive genomic view
Highest data volume and analysis complexity
Selection tip (RUO): If you already know which genes/pathways matter, start with a targeted panel. If you need broader discovery, consider WES (coding) or WGS (genome-wide).
FAQ
FAQs
1) What is the difference between the Core, 50, 100, 400, and Comprehensive tiers?
They represent increasing target scope—from compact driver-focused sets to broader panels for discovery-oriented profiling. The final gene list and target definition are confirmed during consultation and defined in the quotation.
2) Can you share the full gene list for the 400 or Comprehensive tier?
Yes. A confirmed gene list can be shared during project setup once scope and feasibility are reviewed.
3) Can I provide my own gene list or hotspot list?
Yes. Share your list and study objective; we'll review feasibility and confirm the final target scope during onboarding.
4) What files will I receive?
Typical deliverables include FASTQ, a QC package, and annotated SNV/indel outputs (tables and/or VCF as scoped). Optional deliverables (e.g., BAM/CRAM, cohort summaries) can be included upon request and are confirmed in the quotation.
5) Do you accept FFPE and cfDNA samples?
These sample types can be evaluated depending on QC outcomes and study goals. We recommend sharing sample details for feasibility review before shipment.
6) Can you support CNV or rearrangement-oriented analysis?
Optional modules may be included when panel design and data characteristics support them and are confirmed in the quotation.
7) How do you handle variable sample quality across a cohort?
We use an incoming QC review to assess feasibility per sample set. If needed, we recommend practical adjustments (e.g., scope refinement or prioritizing key targets) before proceeding (RUO).
8) Should I use tumor-only or tumor/normal paired design?
This depends on your study goal and available samples. Share your design preference during consultation; we'll align scope and outputs accordingly.
9) Can you support cohort-level summaries for downstream analysis?
Yes, cohort-level tables and summary outputs can be provided when selected as part of the project scope.
10) How do we start a project quickly?
Send your sample matrix, study objective, and preferred tier (or gene list). We'll respond with a scoped plan and quotation.
Illustrative example. Final metrics are reported in the QC package per project.
Nucleic acid yield (A) and quality metrics (B) across cytology specimen collection methods in a prospective multicenter lung cancer study, illustrating a QC-relevant view of sample feasibility for gene panel workflows. Source: Morikawa et al., BMC Cancer (2025).
