General

tooluniverse-precision-oncology - Claude MCP Skill

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.

SEO Guide: Enhance your AI agent with the tooluniverse-precision-oncology tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to provide actionable treatment recommendations for cancer patients based on molecular profile. interpr... Download and configure this skill to unlock new capabilities for your AI workflow.

🌟16 stars • 173 forks
📥0 downloads

Documentation

SKILL.md
# 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.

**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

| Tool | WRONG | CORRECT |
|------|-------|---------|
| `civic_get_variant` | `variant_name` | `id` (numeric) |
| `civic_get_evidence_item` | `variant_id` | `id` |
| `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
- `DepMap_get_gene_dependencies` / `DepMap_get_drug_response` - 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
- `DailyMed_search_spls` - FDA label details
- `ChEMBL_get_drug_mechanisms_of_action_by_chemblId` - 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` - Resistance evidence (clinical_significance="Resistance")
- `PubMed_search_articles` - Resistance literature
- `NvidiaNIM_alphafold2` / `NvidiaNIM_diffdock` - Structure-based analysis

### Phase 5: Clinical Trials
- `search_clinical_trials` - Find trials (param: `condition`, NOT `disease`)
- `get_clinical_trial_eligibility_criteria` - Eligibility details

### Phase 5.5: Literature
- `PubMed_search_articles` - Published evidence
- `BioRxiv_search_preprints` / `MedRxiv_search_preprints` - Preprints (flag as NOT peer-reviewed)
- `openalex_search_works` - Citation analysis

---

## References

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

Signals

Avg rating0.0
Reviews0
Favorites0

Information

Repository
mims-harvard/ToolUniverse
Author
mims-harvard
Last Sync
3/12/2026
Repo Updated
3/12/2026
Created
2/8/2026

Reviews (0)

No reviews yet. Be the first to review this skill!