version: "1.0.0" name: tooluniverse-precision-oncology description: Provide actionable treatment recommendations for cancer patients based on molecular profile. Interprets tumor mutations, identifies FDA-approved therapies, finds resistance mechanisms, matches clinical trials. Use when oncologist asks about treatment options for specific mutations (EGFR, KRAS, BRAF, etc.), therapy resistance, or clinical trial eligibility.

Precision Oncology Treatment Advisor

Provide actionable treatment recommendations for cancer patients based on their molecular profile using CIViC, ClinVar, OpenTargets, ClinicalTrials.gov, and structure-based analysis.

Domain Reasoning

Treatment selection follows a strict evidence hierarchy: FDA-approved for this specific mutation in this cancer type ranks highest, followed by approval for this mutation in any cancer (tumor-agnostic), then active clinical trials, and finally off-label use. Skipping this hierarchy to recommend off-label therapies when an approved option exists is a clinical error. Always check current NCCN guidelines and recent literature, as approvals change rapidly — a drug that was investigational last year may now be first-line.

When looking up treatment for a specific mutation, search CIViC and OncoKB FIRST, not PubMed. These databases have curated evidence levels. PubMed is for when curated databases don't have the answer.

Treatment Selection Reasoning

Biomarker-to-drug logic — When a biomarker is identified, the first-line targeted therapy follows established mappings. Always verify current approval status via OncoKB/CIViC, but use this as a starting framework:

• NSCLC: EGFR exon 19 del / L858R → osimertinib (1L); ALK fusion → alectinib/lorlatinib; ROS1 fusion → crizotinib/entrectinib; KRAS G12C → sotorasib/adagrasib; MET exon 14 skip → capmatinib/tepotinib; RET fusion → selpercatinib; BRAF V600E → dabrafenib+trametinib; NTRK fusion → larotrectinib/entrectinib (tumor-agnostic)
• Breast: HER2+ → trastuzumab+pertuzumab (1L), T-DXd (2L); HR+/HER2- → CDK4/6i (palbociclib/ribociclib) + AI; BRCA1/2 mut → olaparib/talazoparib; PIK3CA mut → alpelisib+fulvestrant
• Colorectal: BRAF V600E → encorafenib+cetuximab; MSI-H/dMMR → pembrolizumab (tumor-agnostic); KRAS/NRAS wild-type → cetuximab/panitumumab (anti-EGFR)
• Melanoma: BRAF V600E/K → dabrafenib+trametinib or encorafenib+binimetinib; wild-type → immunotherapy (nivolumab+ipilimumab)
• Tumor-agnostic: MSI-H/dMMR → pembrolizumab; NTRK fusion → larotrectinib; TMB-H (>=10 mut/Mb) → pembrolizumab; RET fusion → selpercatinib

Resistance mechanism reasoning — When a patient progresses on targeted therapy, distinguish primary resistance (never responded — check if the mutation was truly the driver, or if co-mutations like TP53/RB1 abrogate response) from acquired resistance (responded then progressed — on-target mutations or bypass activation). Common patterns:

• EGFR TKIs: 1st/2nd-gen resistance → T790M (50-60%); osimertinib resistance → C797S (10-25%), MET amp (15-20%), HER2 amp, histologic transformation (SCLC ~5%)
• ALK TKIs: crizotinib resistance → ALK secondary mutations (L1196M, G1269A); alectinib resistance → G1202R (solvent front); lorlatinib resistance → compound mutations
• BRAF inhibitors: MAPK reactivation (MEK mutations, BRAF amplification, NRAS mutations), PI3K/AKT bypass
• Anti-HER2: HER2 truncation (p95HER2), PIK3CA activation, HER3 upregulation
• Immunotherapy (anti-PD1): B2M loss (MHC-I loss), JAK1/2 loss-of-function (IFN-gamma signaling escape), WNT/beta-catenin activation (T-cell exclusion)

For resistance workup: query civic_search_evidence_items with the drug name + "resistance", then PubMed_search_articles for recent mechanisms.

LOOK UP DON'T GUESS

• FDA approval status for a mutation-drug pair: query OncoKB_annotate_variant and civic_search_variants; never assume approval status from memory.
• Active clinical trials: search search_clinical_trials with the specific condition and mutation; do not cite trials from memory.
• Resistance mechanisms for specific drugs: query civic_search_evidence_items and PubMed_search_articles; do not assume resistance pathways.
• Variant frequency in TCGA: retrieve from GDC_get_mutation_frequency or cBioPortal_get_mutations; do not estimate prevalence.

KEY PRINCIPLES:

1. Report-first - Create report file FIRST, update progressively
2. Evidence-graded - Every recommendation has evidence level
3. Actionable output - Prioritized treatment options, not data dumps
4. Clinical focus - Answer "what should we do?" not "what exists?"
5. English-first queries - Always use English terms in tool calls (mutations, drug names, cancer types), even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language

When to Use

• "Patient has [cancer] with [mutation] - what treatments?"
• "What are options for EGFR-mutant lung cancer?"
• "Patient failed [drug], what's next?"
• "Clinical trials for KRAS G12C?"
• "Why isn't [drug] working anymore?"

Phase 0: Tool Verification

Workflow Overview

Input: Cancer type + Molecular profile (mutations, fusions, amplifications)
 
Phase 1: Profile Validation -> Resolve gene IDs (Ensembl, UniProt, ChEMBL)
Phase 2: Variant Interpretation -> CIViC, ClinVar, COSMIC, GDC/TCGA, DepMap, OncoKB, cBioPortal, HPA
Phase 2.5: Tumor Expression -> CELLxGENE cell-type expression, ChIPAtlas regulatory context
Phase 3: Treatment Options -> OpenTargets + DailyMed (approved), ChEMBL (off-label)
Phase 3.5: Pathway & Network -> KEGG/Reactome pathways, IntAct interactions
Phase 4: Resistance Analysis -> CIViC + PubMed + NvidiaNIM structure analysis
Phase 5: Clinical Trials -> ClinicalTrials.gov search + eligibility
Phase 5.5: Literature -> PubMed, BioRxiv/MedRxiv preprints, OpenAlex citations
Phase 6: Report Synthesis -> Executive summary + prioritized recommendations

Key Tools by Phase

Phase 1: Profile Validation

• MyGene_query_genes - Resolve gene to Ensembl ID
• UniProt_search - Get UniProt accession
• ChEMBL_search_targets - Get ChEMBL target ID

Phase 2: Variant Interpretation

• civic_search_variants / civic_get_variant - CIViC evidence
• COSMIC_get_mutations_by_gene / COSMIC_search_mutations - Somatic mutations
• GDC_get_mutation_frequency / GDC_get_ssm_by_gene - TCGA patient data
• GDC_get_gene_expression / GDC_get_cnv_data - Expression and CNV
• GDC_get_survival - Kaplan-Meier survival data by project and optional gene mutation filter
• GDC_get_clinical_data - TCGA clinical metadata (stage, vital status, treatment, demographics)
• Progenetix_cnv_search - Copy number variation biosamples by genomic region and cancer type (NCIt code)
• DepMap_get_gene_dependencies / PharmacoDB_get_experiments - Target essentiality
• OncoKB_annotate_variant / OncoKB_get_gene_info - Actionability
• cBioPortal_get_mutations / cBioPortal_get_cancer_studies - Cross-study data
• HPA_search_genes_by_query / HPA_get_comparative_expression_by_gene_and_cellline - Expression

Phase 2.5: Tumor Expression

• CELLxGENE_get_expression_data / CELLxGENE_get_cell_metadata - Cell-type expression

Phase 3: Treatment Options

• OpenTargets_get_associated_drugs_by_target_ensemblID - Approved drugs (param: ensemblId, camelCase)
• DGIdb_get_drug_gene_interactions - Drug-gene interactions (param: genes as array, e.g., ["EGFR"]). Comprehensive; covers inhibitors, antibodies, and investigational agents.
• DailyMed_search_spls - FDA label details
• ChEMBL_get_drug_mechanisms - Drug mechanism

Phase 3.5: Pathway & Network

• kegg_find_genes / kegg_get_gene_info - KEGG pathways
• reactome_disease_target_score - Reactome disease relevance
• intact_get_interaction_network - Protein interactions

Phase 4: Resistance Analysis

• civic_search_evidence_items - Search by known resistance mutations individually (e.g., molecular_profile="EGFR C797S", molecular_profile="MET Amplification"). The significance field in results indicates Resistance/Sensitivity — filter on it after retrieval.
• PubMed_search_articles - Resistance literature (e.g., "osimertinib resistance C797S combination therapy")
• alphafold_get_prediction / get_diffdock_info - Structure-based analysis (AlphaFold for structure, DiffDock for docking)

Phase 5: Clinical Trials

• search_clinical_trials - Find trials (param: condition, NOT disease)
• get_clinical_trial_eligibility_criteria - Eligibility details

Phase 5.5: Safety & Pharmacogenomics

• FAERS_search_adverse_event_reports - Real-world adverse events (param: medicinalproduct). Check for serious AEs, death rates, common toxicities.
• FAERS_count_death_related_by_drug - Mortality signal for a drug
• FDA_get_warnings_and_cautions_by_drug_name - FDA label safety info
• CPIC_list_guidelines - Check for relevant PGx guidelines (e.g., DPYD for fluoropyrimidines in chemo regimens, UGT1A1 for irinotecan). No CPIC guidelines exist for EGFR TKIs.
• fda_pharmacogenomic_biomarkers - FDA-labeled PGx biomarkers for the drug

OncoKB demo mode: Without ONCOKB_API_TOKEN env var, OncoKB only covers BRAF, TP53, ROS1. For other genes (EGFR, KRAS, ALK, etc.), set the API key or use CIViC as the primary evidence source.

Phase 6: Literature

• PubMed_search_articles - Published evidence (use limit, mindate, maxdate for date filtering)
• BioRxiv_list_recent_preprints / MedRxiv_get_preprint - Preprints (flag as NOT peer-reviewed)
• openalex_search_works - Citation analysis

Cross-Skill References

For CYP interaction with cancer drugs, run: python3 skills/tooluniverse-drug-drug-interaction/scripts/pharmacology_ref.py --type cyp_substrate --drug drugname

References

• TOOLS_REFERENCE.md - Complete tool documentation with parameters and examples
• API_USAGE_PATTERNS.md - Detailed code examples for each phase
• TREATMENT_ALGORITHMS.md - Evidence grading, treatment prioritization, cancer type mappings, DepMap interpretation
• REPORT_TEMPLATE.md - Report template with output tables
• EXAMPLES.md - Worked examples (EGFR NSCLC, T790M resistance, KRAS G12C, no actionable mutations)
• CHECKLIST.md - Quality and completeness checklist