Cancer Testing Table

Testing Resources

Comprehensive Breast Cancer Testing Options

TIER 1: STANDARD OF CARE - AUTOMATIC TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
ER/PR/HER2 Testing	Immunohistochemistry	Tumor tissue (FFPE)	N/A	Protein expression (ER, PR, HER2)	At diagnosis - determines targeted therapy eligibility	Level 1A Evidence	Covered	3-5 days	$800-1,600 total	Automatic	Usually available
Pathology Assessment	Histopathologic evaluation	Tumor tissue (FFPE)	N/A	N/A	Grade (1-3), histologic type (IDC/ILC), tumor size, lymph node status, TNM staging	Standard pathology	Covered	3-7 days	Included in biopsy/surgery	Automatic	Pathology report provided

TIER 2: GUIDELINE-RECOMMENDED TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
Oncotype DX	RNA-seq	Tumor tissue (FFPE)	N/A	21-gene expression signature	Early-stage ER+/HER2- - chemotherapy benefit	Level 1A (TAILORx)	Usually covered for qualifying patients	10-14 days	$3,500	Conditional	Contact company
MammaPrint	RNA-seq	Tumor tissue (FFPE)	N/A	70-gene expression signature	Early-stage - recurrence risk	Level 1A (MINDACT)	Usually covered for qualifying patients	≤6 days	$4,000-5,000	Conditional	Contact company
Prosigna	RNA-seq	Tumor tissue (FFPE)	N/A	PAM50 + clinical factors	Postmenopausal ER+ - subtyping/risk	Level 1A Evidence	Coverage varies	3-5 days	$3,500-4,500	Conditional	Contact company
EndoPredict	RNA-seq	Tumor tissue (FFPE)	N/A	12-gene molecular score	ER+ - extended recurrence risk 0-15 years	Level 1A Evidence	Coverage varies	~14 days	$3,000-4,000	Conditional	Contact company
BRCA1/BRCA2 Testing	Germline DNA sequencing	Blood/saliva	BRCA1 and BRCA2 genes	None	Hereditary breast cancer risk assessment	Level 1A Evidence	Usually covered for qualifying patients	1-2 weeks	$300-500	Conditional	Usually available
Hereditary Cancer Panels	Germline DNA sequencing	Blood/saliva	20-80+ genes (PALB2, ATM, CHEK2, TP53, CDH1, PTEN, etc.)	None	Comprehensive hereditary cancer risk	Level 1A Evidence	Coverage varies for qualifying patients	2-3 weeks	$1,000-3,000	Conditional	Usually available

TIER 3: FDA-APPROVED COMPANION DIAGNOSTICS ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
Foundation One CDx	DNA-seq, genomic signatures	Tumor tissue (FFPE)	324 genes (mutations, CNVs, genomic signatures)	None	Treatment selection - comprehensive profiling	FDA Companion Diagnostic	Usually covered for advanced/metastatic cancer	~14 days	$3,500	Optional	Available via physician
Foundation One Liquid CDx	ctDNA from blood	Blood (ctDNA)	324 genes (mutations, CNVs)	None	Treatment selection - liquid biopsy	FDA Companion Diagnostic	Usually covered for advanced/metastatic cancer	~14 days	$3,500	Optional	Available via physician
Guardant360 CDx	ctDNA from blood	Blood (ctDNA)	74 genes (mutations, CNVs, fusions)	None	Treatment selection, ESR1 mutations	FDA Companion Diagnostic	Usually covered for advanced/metastatic cancer	~7 days	$5,000	Optional	Available via physician
Tempus xT CDx	DNA-seq, MSI, CNVs, fusions	Tumor tissue (FFPE) + matched normal	648 genes (mutations, CNVs, MSI, fusions)	None	Treatment selection - comprehensive profiling	FDA Companion Diagnostic	Usually covered for advanced/metastatic cancer	~14 days	$4,500	Optional	Available via physician
Myriad MyChoice CDx	HRD analysis	Tumor tissue (FFPE)	BRCA1/2 + genomic instability score	None	PARP inhibitor selection	FDA Companion Diagnostic	Usually covered for PARP inhibitor selection	Up to 14 days	$4,000-5,000	Optional	Contact company
PD-L1 Testing	Immunohistochemistry	Tumor tissue (FFPE)	N/A	PD-L1 protein expression	Immunotherapy selection (TNBC)	FDA Companion Diagnostic	Usually covered for immunotherapy selection in advanced solid tumors	3-5 days	$500-800	Conditional	Usually available
PIK3CA Mutation Testing	DNA sequencing	Tumor tissue (FFPE)	PIK3CA gene mutations	None	Alpelisib (Piqray) selection for HR+/HER2- breast cancer	FDA Companion Diagnostic	Usually covered when prescribing alpelisib	5-7 days	$500-1,000	Conditional	Usually available

TIER 4: RESEARCH-VALIDATED BIOMARKER TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
MSI Testing	DNA microsatellite analysis	Tumor tissue (FFPE)	Microsatellite regions	None	Immunotherapy selection	Research-Validated	Usually covered for immunotherapy selection	5-7 days	$800-1,200	Optional	Usually available
TMB Testing	Mutational burden analysis	Tumor tissue (FFPE)	Whole exome or large panels	None	Immunotherapy response prediction	Research-Validated	Coverage varies	7-14 days	$1,000-2,000	Optional	Usually available
Ki-67 Testing	Immunohistochemistry	Tumor tissue (FFPE)	N/A	Ki-67 protein (proliferation marker)	Proliferation assessment	Research-Validated	Usually covered	2-3 days	$200-400	Optional	Usually available
Tempus xRSecondary Analysis	RNA-seq	Tumor tissue (FFPE)	N/A	Whole transcriptome (23,000+ genes)	Fusion detection, altered splicing, immune profiling	Research-Validated	Coverage varies	~14 days	$2,500-3,500	Optional	Available via physician
Tempus xF+	ctDNA from blood	Blood (ctDNA)	523 genes (mutations, CNVs, fusions)	None	Treatment selection, monitoring, resistance detection	Research-Validated	Coverage varies	~7-10 days	$4,500-5,500	Optional	Available via physician
CellSearch CTC Enumeration	Circulating tumor cell capture	Blood	N/A	CTC count per 7.5mL blood	Prognostic monitoring in metastatic breast cancer	FDA-approved (Prognostic)	Coverage varies	3-5 days	$1,000-2,000	Optional	Contact company
Comprehensive Germline Exome Sequencing	Germline whole exome sequencing	Blood/saliva	23,000+ genes (whole exome)	None	Comprehensive hereditary cancer and disease risk assessment	Research-Validated Methods	Sometimes covered for high-risk patients	3-4 weeks	$3,000-5,000	Optional	Usually available via physician
Galleri (GRAIL)	Methylation-based ctDNA	Blood (ctDNA)	50+ cancer types (methylation patterns)	None	Multi-cancer early detection	Research-Validated	Not covered	~2 weeks	$949	Optional	Limited proprietary access
CancerSEEK (Thrive/Exact Sciences)	ctDNA + proteins	Blood (ctDNA)	16 genes + 8 proteins	None	Multi-cancer early detection	Research-Validated	Not available commercially	~2-3 weeks	Target $300-500	Not yet available	Limited proprietary access
NeXT Personal Dx (Personalis/Tempus)Secondary Analysis	Ultra-sensitive tumor-informed ctDNA	Blood (ctDNA)	Up to 1,800 tumor-specific variants	None	MRD detection, recurrence monitoring	Research-Validated	Working toward Medicare coverage	~2-3 weeks	Available via Tempus	Limited access	Available via physician
Guardant360 Response	ctDNA monitoring	Blood (ctDNA)	Circulating tumor DNA tracking	None	Treatment response monitoring, ctDNA changes	Research-Validated	Coverage varies	~2 weeks	$5,000	Optional	Available via physician

TIER 5: COMPREHENSIVE GENOMIC/EXPRESSION TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
Comprehensive WES+WTS PlatformsSecondary Analysis	WES, WTS, ±IHC, ±AI	Tumor tissue (FFPE)	20,000-23,000+ genes (whole exome)	Whole transcriptome	Comprehensive molecular profiling	Research-Validated Methods	Coverage varies; typically advanced/metastatic cancer only	~14 days	$6,000-8,000	Optional	Available via physician
Signatera*Secondary Analysis	Personalized ctDNA tracking	Tumor tissue initial, then blood monitoring	16 personalized variants reported, BUT full exome sequencing performed on tumor + normal	None	Minimal residual disease monitoring	Research-Validated	Medicare covered: colorectal, stage IIb+ breast, ovarian, bladder, IO monitoring	~2 weeks initial	$5,000-8,000	Optional	Full exome data accessible
NanoString PanCancer IO360	RNA-seq immune profiling	Tumor tissue (FFPE)	N/A	770 immune-related genes	Immune profiling for research	Research-Validated Methods (Proprietary Platform)	Not covered	~7-10 days	$2,000-3,000	Research participation	Available for research
EXACTA/ETASecondary Analysis	Multi-omics (DNA, RNA, proteins)	Tumor tissue (FFPE)	20,000+ genes (comprehensive genomic)	Comprehensive transcriptome	Comprehensive tumor profiling	Research-Validated Methods	Not covered	~14-21 days	$6,000-8,000	Limited availability	Contact company

TIER 6: FUNCTIONAL TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
Champions TumorGraft3D	3D organoid drug screening	Fresh tumor tissue	N/A	Functional drug sensitivity profiles	Drug response prediction	Research-Validated Methods (Limited Secondary Analysis Potential)	Not covered	~3-4 weeks	$8,000-12,000	Research collaboration	Available for research
PARIS Test	Functional drug screening	Fresh tumor tissue	N/A	Drug sensitivity/resistance profiles	Drug sensitivity screening	Research-Validated Methods (Limited Secondary Analysis Potential)	Not covered	~2-3 weeks	$6,000-8,000	Limited access	Not typically available
EXACTA/ETA Functional Testing	Functional drug screening + multi-omics	Tumor tissue (FFPE)	N/A	Drug sensitivity/resistance profiles	Functional drug response prediction	Research-Validated Methods (Limited Secondary Analysis Potential)	Not covered	~14-21 days	$6,000-8,000	Limited availability	Available for research

TIER 7: COMMERCIAL/QUESTIONABLE VALIDITY ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
RGCC	Proprietary CTC analysis	Blood	N/A	Limited CTC analysis	CTC monitoring	Limited/Questionable Validation	Not covered	~2-3 weeks	$3,000-5,000	Not Recommended	Contact company
ChemoFx	Functional testing (historical)	Fresh tumor tissue	N/A	Drug sensitivity	Drug selection	Limited/Questionable Validation	Not covered	N/A (discontinued)	N/A	Not Available	N/A

GENERAL HEALTH TESTING ▶

Test	Data Types	Sample Type	Genomic Scope (DNA)	Expression Scope	Clinical Context	Evidence Level	Insurance Coverage	Turnaround	Cost	Patient Decision	Raw Data Access
23andMe Health	SNP genotyping	Saliva	~700,000 SNPs	None	Health predispositions, BRCA variants	FDA-authorized reports	Not covered	~6-8 weeks	$99-199	Optional	Available via account
Nutrigenome Testing	SNP genotyping	Saliva/buccal swab	40-100+ nutrition variants	None	Personalized nutrition	Limited Evidence	Not covered	~2-3 weeks	$200-800	Optional	Varies by company
MTHFR Testing	Single gene testing	Blood/saliva	MTHFR gene variants	None	Methylation pathway	Limited Clinical Utility	Sometimes covered	~1-2 weeks	$100-300	Optional	Usually available
DUTCH Test	Hormone metabolite analysis	Dried urine	N/A	None (metabolomics)	Hormone assessment	Limited Evidence	Not covered	~2-3 weeks	$400-500	Optional	Available

Important Notes

SIGNATERA SPECIAL NOTE: Signatera performs full whole exome sequencing on BOTH tumor tissue AND germline (normal) DNA to design their personalized 16-variant panel. While they only report on 16 variants for monitoring, patients can request access to their complete exome sequencing data from BOTH tumor AND germline samples.

TEMPUS SPECIAL NOTES:

Tempus xF+ Clonal Evolution Analysis: The 523-gene liquid biopsy panel enables tracking of tumor genetic changes over time, providing insights into clonal evolution and resistance mechanisms.

Tempus xR Transcriptome Analysis: Provides whole transcriptome sequencing (23,000+ genes) enabling extensive secondary analysis including custom gene signatures and pathway analysis.

CEtHI DATA OWNERSHIP PRINCIPLE: Full exome + transcriptome data can subsume many targeted tests through secondary analysis. Tests marked with "Secondary Analysis" badges collect more comprehensive data than they report and/or are amenable to more comprehensive analyses.

Understanding Cancer Testing Data Types

A Guide to Genomic, Expression, and Functional Analyses

Genomic Data: The Foundation of Molecular Testing
Expression Data: From Proteins to Transcriptomes
Circulating Tumor DNA (ctDNA): The Liquid Biopsy Revolution
Functional Testing: Beyond Genetics to Actual Behavior
SNP Data: Population Genetics and Common Variants
Emerging and Advanced Data Types
Cutting-Edge Multimodal AI Analysis
Secondary Analysis: Making Comprehensive Data Work Harder
Current Limitations and the Research-to-Clinical Gap

Genomic Data: The Foundation of Molecular Testing

Normal (Germline) vs. Tumor Tissue Genomic Data

Genomic data examines DNA sequences, but the source matters enormously. Germline genomic data comes from normal tissue (blood, saliva) and represents your inherited genetic blueprint - the DNA you were born with. When we test for BRCA1/BRCA2 mutations in blood, we're looking for inherited predispositions passed down through families.

Tumor genomic data, by contrast, examines DNA from cancer cells themselves. These contain both your original inherited DNA plus additional somatic mutations - genetic changes that occurred during cancer development. A person might have normal germline BRCA1/BRCA2 genes but develop somatic BRCA mutations specifically in their tumor tissue.

Example: Foundation One CDx sequences 324 genes from tumor tissue to find somatic mutations that can guide targeted therapies, while hereditary cancer panels sequence the same genes from blood to find inherited risk variants.

Expression Data: From Proteins to Transcriptomes

Expression data measures what genes are actually doing rather than just what the DNA sequence says. This represents the dynamic, functional output of the genome.

Standard Expression Markers (ER/PR/HER2)

These classic biomarkers use immunohistochemistry (IHC) to measure specific proteins directly in tissue. When we say a tumor is "ER+" we mean estrogen receptor proteins are detectable on cancer cell surfaces. This is targeted, focused expression analysis of known important proteins.

Whole Transcriptome Expression

RNA sequencing measures the expression levels of all ~23,000 human genes simultaneously by quantifying messenger RNA (mRNA) molecules. This provides a comprehensive snapshot of cellular activity - which genes are turned "on" or "off" and by how much.

Example: Oncotype DX measures RNA expression of 21 specific genes to calculate a recurrence score. Tempus xR performs whole transcriptome sequencing of all genes. This comprehensive dataset can then yield the same 21-gene signature plus thousands of other potential biomarkers.

Immune Profiling Through Expression Data

Immune profiling typically uses RNA sequencing to measure expression of immune-related genes. Tests like NanoString IO360 examine 770 immune genes to characterize the tumor microenvironment - are T-cells infiltrating? Are immune checkpoint pathways active? This helps predict immunotherapy response by understanding the immune landscape around the tumor.

Circulating Tumor DNA (ctDNA): The Liquid Biopsy Revolution

ctDNA represents fragments of tumor DNA that circulate freely in blood. When cancer cells die, they release their DNA into the bloodstream. Advanced sequencing can detect these tumor-derived DNA fragments among the much larger background of normal cell-free DNA.

 Key Advantages Non-invasive: Simple blood draw vs. tissue biopsy
Real-time monitoring: Can track changes during treatment
Comprehensive sampling: Captures DNA from all tumor sites, not just one biopsy location
 

Example: Guardant360 CDx analyzes 74 genes from blood ctDNA to guide treatment decisions, while Signatera creates a personalized panel of 16 tumor-specific mutations to monitor for minimal residual disease after treatment.

Functional Testing: Beyond Genetics to Actual Behavior

Functional testing moves beyond "what mutations does the tumor have?" to "how does the tumor actually behave?" This involves growing tumor cells in laboratory conditions and directly testing their response to various treatments.

Methods

Organoids: 3D tissue cultures that mimic tumor structure
Drug screening: Testing multiple chemotherapy agents directly on patient cells
Sensitivity profiling: Measuring which drugs kill tumor cells most effectively

Example: Champions TumorGraft3D grows patient tumor cells in 3D culture and tests their response to dozens of drugs, providing direct functional evidence of drug sensitivity rather than inferring it from genetic mutations.

SNP Data: Population Genetics and Common Variants

Single Nucleotide Polymorphisms (SNPs) represent common genetic variants found throughout human populations. Unlike rare disease-causing mutations, SNPs are normal genetic differences that occur in >1% of people.

SNP Arrays

Test ~700,000 predetermined positions

Assess common variants linked to traits/diseases

Broad but shallow coverage

Clinical Sequencing

Read entire gene sequences

Find rare pathogenic mutations

Deep and comprehensive

Example: 23andMe tests SNPs associated with BRCA1/BRCA2 regions but only captures ~0.1% of possible pathogenic variants, while clinical BRCA sequencing reads every DNA letter in these genes to find rare disease-causing mutations.

Emerging and Advanced Data Types

Epigenetic Data: The Genome's Control Layer

Epigenetic modifications control gene expression without changing DNA sequence itself. DNA methylation patterns can silence tumor suppressor genes even when the underlying DNA is normal. Methylation-based tests like Galleri detect cancer by identifying abnormal methylation patterns across thousands of genes.

Proteomic Data: The Functional Output

While genomics tells us what could happen and transcriptomics what should happen, proteomics measures what actually is happening. Mass spectrometry can quantify thousands of proteins simultaneously, revealing post-translational modifications and protein interactions that don't show up in DNA or RNA data.

Metabolomic Data: Cellular Chemistry in Action

Metabolomics measures small molecules (metabolites) that represent the end products of cellular processes. Cancer cells often have altered metabolism, producing unique metabolic signatures detectable in blood or urine.

Cutting-Edge Multimodal AI Analysis

Genomics + Imaging Integration

Emerging AI approaches combine multiple data types for more powerful analysis. Radiogenomics uses machine learning to predict genetic mutations directly from medical images (CT, MRI, pathology slides). For example, AI can predict EGFR mutations in lung cancer from CT scans, or identify microsatellite instability from H&E pathology slides without additional molecular testing.

Multimodal Pathology AI

Advanced systems analyze digitized pathology slides alongside genomic data to predict treatment responses, identify missed diagnoses, or discover new biomarkers. The AI learns patterns invisible to human pathologists by processing millions of image features simultaneously.

CEtHI Secondary Analysis Opportunity

Since medical images (pathology slides, radiology) are typically provided to patients as part of their medical records, organizations like CEtHI with appropriate AI/imaging expertise could potentially perform secondary analyses combining imaging data with genomic results - extracting additional insights from data patients already own without requiring new tests.

Secondary Analysis: Making Comprehensive Data Work Harder

The Power of Comprehensive Data Collection

When a test performs whole exome sequencing (20,000+ genes) but only reports results for a specific gene panel, the unreported data doesn't disappear - it remains available for future analysis. This enables "secondary analysis" where comprehensive datasets can answer new questions without additional testing.

Examples

Signatera: Performs whole exome sequencing on tumor and normal tissue but initially reports only 16 personalized variants for monitoring. Patients can later request analysis of cancer predisposition genes, pharmacogenomic variants, or other findings from the same dataset.
Tempus xR: Sequences the entire transcriptome but initially focuses on clinically actionable findings. The same data can later be reanalyzed for research signatures, pathway analysis, or newly discovered biomarkers.

Why This Matters

Secondary analysis democratizes access to comprehensive testing by allowing targeted test results to be extracted from broad datasets, often at lower cost than running separate tests.

Current Limitations and the Research-to-Clinical Gap

Insurance and Standard of Care Barriers

Advanced multimodal analyses and many secondary analyses are not covered by insurance because they are not yet considered "standard of care." Insurance systems typically lag years behind scientific developments, requiring extensive clinical trial validation before coverage approval.

The Clinical Translation Lag

A significant gap exists between research developments and clinical application. Promising biomarkers and AI-based analyses may show strong research evidence but require 5-15 years to become clinically adopted. During this period, patients may benefit from research-grade information that their healthcare systems cannot yet provide.

Access Limitations

Most cutting-edge analyses remain confined to academic medical centers or research institutions. Standard community oncology practices may lack access to the latest developments, creating disparities in available information. Organizations like CEtHI aim to bridge this gap by providing research-grade analyses directly to patients, empowering informed decision-making without waiting for traditional clinical adoption timelines.

One key CEtHI objective is to bridge the gap between
what we know in research and
what we do in the clinic.

As a genetic epidemiologist, I am in position to help patients navigate the full spectrum
of testing options and leverage comprehensive molecular data for informed decision-making.

Learn about our services

Patient Empowerment. Patient Dignity. Patient Flourishing.

Cancer Testing Options Table