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 β 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 β 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 β osimertinib (1L); ALK fusion β alectinib/lorlatinib; ROS1 fusion β crizotinib/entrectinib; KRAS G12C β sotorasib/adagrasib; MET exon 14 skip β capmatinib/tepotinib; RET fusion β selpercatinib; BRAF V600E β dabrafenib+trametinib; NTRK fusion β larotrectinib/entrectinib (tumor-agnostic)
- Breast: HER2+ β trastuzumab+pertuzumab (1L), T-DXd (2L); HR+/HER2- β CDK4/6i (palbociclib/ribociclib) + AI; BRCA1/2 mut β olaparib/talazoparib; PIK3CA mut β alpelisib+fulvestrant
- Colorectal: BRAF V600E β encorafenib+cetuximab; MSI-H/dMMR β pembrolizumab (tumor-agnostic); KRAS/NRAS wild-type β cetuximab/panitumumab (anti-EGFR)
- Melanoma: BRAF V600E/K β dabrafenib+trametinib or encorafenib+binimetinib; wild-type β immunotherapy (nivolumab+ipilimumab)
- Tumor-agnostic: MSI-H/dMMR β pembrolizumab; NTRK fusion β larotrectinib; TMB-H (>=10 mut/Mb) β pembrolizumab; RET fusion β selpercatinib
Resistance mechanism reasoning β When a patient progresses on targeted therapy, distinguish primary resistance (never responded β check if the mutation was truly the driver, or if co-mutations like TP53/RB1 abrogate response) from acquired resistance (responded then progressed β on-target mutations or bypass activation). Common patterns:
- EGFR TKIs: 1st/2nd-gen resistance β T790M (50-60%); osimertinib resistance β C797S (10-25%), MET amp (15-20%), HER2 amp, histologic transformation (SCLC ~5%)
- ALK TKIs: crizotinib resistance β ALK secondary mutations (L1196M, G1269A); alectinib resistance β G1202R (solvent front); lorlatinib resistance β 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:
- Report-first - Create report file FIRST, update progressively
- Evidence-graded - Every recommendation has evidence level
- Actionable output - Prioritized treatment options, not data dumps
- Clinical focus - Answer "what should we do?" not "what exists?"
- 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
| Tool |
WRONG |
CORRECT |
civic_get_variant |
variant_name |
variant_id (numeric, e.g., 4170) |
civic_get_evidence_item |
variant_id |
id (numeric) |
OpenTargets_* |
ensemblID |
ensemblId (camelCase) |
search_clinical_trials |
disease |
condition |
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 β 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