Translate free-text tumor descriptions to OncoTree codes and resolve cancer subtypes/tissue hierarchy. Cross-references UMLS/NCI vocabularies. Use for standardizing cancer-type nomenclature in EHR free-text, building cohorts in OncoKB or GDC, mapping tumor-board notes to ontology codes, and ensuring consistent terminology across cancer-genomics pipelines.
Translate free-text tumor descriptions to OncoTree codes and resolve cancer subtypes/tissue hierarchy. Cross-references UMLS/NCI vocabularies. Use for standardizing cancer-type nomenclature in EHR free-text, building cohorts in OncoKB or GDC, mapping tumor-board notes to ontology codes, and ensuring consistent terminology across cancer-genomics pipelines.
Cancer Classification via OncoTree
Standardize cancer type nomenclature using the OncoTree ontology. Resolves free-text tumor
descriptions to structured codes with UMLS/NCI cross-references, enabling downstream use in
OncoKB variant annotation and GDC cohort selection.
When to Use
Apply when researcher asks about:
"What is the OncoTree code for [tumor description]?"
"Find all subtypes of [cancer type]"
"What cancers originate in [tissue]?"
"I need the tumor type code for OncoKB annotation"
"What is the TCGA/COSMIC code for [cancer]?"
"List all CNS/Brain cancer subtypes"
"What NCI code corresponds to glioblastoma?"
Key Tools
Tool
Purpose
Key Params
OncoTree_search
Free-text search for cancer types
query (tumor name or description)
OncoTree_get_type
Full details for a known OncoTree code
code (e.g., "LUAD", "AML")
OncoTree_list_tissues
List all 32 tissue categories
(no params)
OncoKB_annotate_variant
Variant annotation using OncoTree code
gene, ,
variant
tumor_type
GDC_get_mutation_frequency
Pan-cancer mutation frequency (TCGA)
gene_symbol
Workflow
Phase 1: Cancer Type Discovery
Start with free-text search to find matching OncoTree codes:
Note: Not all codes are valid. "GBM" returns 404 — correct code is "GB" (Glioblastoma, IDH-Wildtype).
Always validate via OncoTree_get_type before using in downstream tools.
Phase 3: Tissue-Level Exploration
When the user wants all cancers in a tissue category:
OncoTree_list_tissues()
-> Returns 32 tissue names: "Breast", "CNS/Brain", "Lung", "Myeloid", ...
OncoTree_search(query="CNS/Brain")
-> All cancer types with tissue="CNS/Brain"
Phase 4: Downstream Use in Variant Annotation
Pass validated OncoTree code to OncoKB for cancer-type-specific therapeutic levels:
OncoKB_annotate_variant(gene="EGFR", variant="L858R", tumor_type="LUAD")
-> highestSensitiveLevel: "1" (FDA-approved therapy for this tumor+variant)
Without tumor_type, OncoKB returns pan-cancer levels which may be less specific.
Tool Parameter Reference
Tool
Required
Optional
Notes
OncoTree_search
query
—
Free text; returns list sorted by relevance
OncoTree_get_type
code
—
Case-sensitive; "BRCA" not "brca". Returns 404 for invalid codes
OncoTree_list_tissues
—
—
No params; returns list of 32 tissue strings
OncoKB_annotate_variant
gene, variant
tumor_type
tumor_type is OncoTree code; omit for pan-cancer
GDC_get_mutation_frequency
gene_symbol
—
Pan-cancer TCGA only; no per-subtype breakdown
Common OncoTree Codes (verified working)
Code
Name
Tissue
BRCA
Invasive Breast Carcinoma
Breast
LUAD
Lung Adenocarcinoma
Lung
LUSC
Lung Squamous Cell Carcinoma
Lung
MEL
Melanoma
Skin
CRC
Colorectal Cancer
Bowel
PAAD
Pancreatic Adenocarcinoma
Pancreas
GBM
(invalid — use GB)
CNS/Brain
GB
Glioblastoma, IDH-Wildtype
CNS/Brain
AML
Acute Myeloid Leukemia
Myeloid
PRAD
Prostate Adenocarcinoma
Prostate
Common Patterns
# Pattern: Resolve free-text to OncoTree code
results = OncoTree_search(query="pancreatic ductal adenocarcinoma")
# Pick result with lowest level number (most specific match)
code = results["data"][0]["code"] # e.g., "PAAD"# Pattern: Get all subtypes within a main type
results = OncoTree_search(query="Glioma")
subtypes = [r for r in results["data"] if r["main_type"] == "Glioma"]
# Pattern: Validate code before OncoKB call
detail = OncoTree_get_type(code="GB")
if detail["status"] == "success":
OncoKB_annotate_variant(gene="IDH1", variant="R132H", tumor_type="GB")
Tumor Classification Reasoning (CRITICAL)
LOOK UP DON'T GUESS -- tumor classification determines treatment. Always verify codes and biomarker interpretation via tools rather than relying on memory.
Histological vs Molecular Classification
Tumors are classified on TWO axes -- both matter for treatment selection:
Histological (what it looks like under microscope): adenocarcinoma, squamous, small cell, etc. This determines the OncoTree hierarchy level 3+.
Molecular (what mutations/alterations drive it): EGFR-mutant, HER2-amplified, MSI-high, etc. This determines OncoKB therapeutic levels.
A tumor can be histologically identical to another but molecularly different, requiring different treatment. Example: two lung adenocarcinomas (both LUAD) but one is EGFR-mutant (targeted therapy) and another is KRAS-mutant (different targeted therapy). Always check both axes.
Biomarker Interpretation Strategy
When interpreting cancer biomarkers, use OncoKB for actionability:
HER2: Positive = IHC 3+ or FISH-amplified. Use OncoKB_annotate_variant(gene="ERBB2", variant="Amplification", tumor_type="BRCA") for therapeutic level
ER/PR: Positive = hormone-receptor positive breast cancer. Changes treatment class (endocrine therapy)
Ki67: Proliferation index. High (>20%) suggests aggressive biology; used in breast cancer grading (Luminal A vs B)
TMB (Tumor Mutational Burden): High TMB (>10 mut/Mb) predicts immunotherapy response across tumor types. Use OncoKB_annotate_variant(gene="Other Biomarkers", variant="TMB-H")
MSI (Microsatellite Instability): MSI-High is FDA-approved biomarker for pembrolizumab pan-cancer. Use OncoKB_annotate_variant(gene="Other Biomarkers", variant="MSI-H")
Staging vs Grading -- Different Concepts
Stage (TNM): How far has it spread? T=tumor size, N=lymph nodes, M=metastasis. Stage I-IV. Determines prognosis and surgery eligibility.
Grade: How abnormal do the cells look? Grade 1 (well-differentiated, slow) to Grade 3 (poorly-differentiated, aggressive). Determines aggressiveness.
A Stage I, Grade 3 tumor (small but aggressive) has different implications than Stage III, Grade 1 (spread but slow-growing).
Actionability Assessment
After classifying the tumor, assess whether findings are clinically actionable:
Level 1 (FDA-approved, specific tumor type): Immediate treatment implication. Example: EGFR L858R in LUAD
Level 2 (Standard care): Strong evidence but context-dependent
Level 4 (Biological evidence): Research-stage only
Always provide the OncoTree code to OncoKB -- without it, you get pan-cancer levels which may understate or overstate actionability for the specific tumor type
OncoTree search returns match, but code not yet validated or missing cross-refs
Search for "cholangiocarcinoma" returns CHOL with partial external refs
Ambiguous
Multiple OncoTree codes match the description at different hierarchy levels
"Breast cancer" matches BRCA (invasive), BREAST (tissue), IBC (inflammatory)
Unresolved
No OncoTree match; tumor type too rare or novel for the ontology
Ultra-rare sarcoma subtype not in OncoTree
Interpretation Guidance
OncoTree code confidence: Always validate candidate codes with OncoTree_get_type before downstream use. Some common acronyms (e.g., "GBM") are NOT valid OncoTree codes (correct code is "GB"). A validated code with UMLS and NCI cross-references is highest confidence.
UMLS/NCI cross-reference priority: For standardized reporting, NCI Thesaurus codes are preferred for cancer-specific contexts (used by caDSR, GDC). UMLS CUIs are broader (cross-disease) and useful for literature mining. When both are available, report both; when only one exists, NCI is preferred for oncology workflows.
Tissue hierarchy interpretation: OncoTree levels represent specificity: Level 1 = tissue of origin (e.g., "Lung"), Level 2 = main cancer type (e.g., "Non-Small Cell Lung Cancer"), Level 3+ = histological subtypes (e.g., "Lung Adenocarcinoma"). For OncoKB variant annotation, use the most specific (deepest) level that accurately describes the tumor. For cohort-level analysis (e.g., TCGA), the Level 2-3 code is typically appropriate.
OncoKB tumor type impact: Providing a tumor type code to OncoKB can change the therapeutic level (e.g., EGFR L858R is Level 1 in LUAD but Level 3B pan-cancer). Always use the validated OncoTree code for the patient's specific tumor type.
Deprecated or renamed codes: OncoTree evolves across versions. The history field in OncoTree_get_type response shows prior names. Always use the current code.
Synthesis Questions
Does the chosen OncoTree code represent the most specific histological subtype, or could a more precise code provide better therapeutic annotation in OncoKB?
When the free-text tumor description maps to multiple OncoTree codes, which hierarchy level best balances specificity and coverage for the analysis goal (variant annotation vs cohort selection)?
Are the UMLS/NCI cross-references consistent with external classifications (WHO, ICD-O), or are there discrepancies that need resolution?
