Q (sonnet): I receive a report with the PIK3CA p.*1069Wext*3 mutation. Can you provide details of it

▶ read_guide
{
 "uri": "cbioportal://common-pitfalls"
}

▶ read_guide
{
 "uri": "cbioportal://mutation-frequency-guide"
}

◀ result
# Common Query Pitfalls Guide

## Overview
This guide highlights frequent mistakes when analyzing cBioPortal data and provides solutions to avoid them.

## Critical Pitfalls

### 1. 🚨 CRITICAL MUTATION FREQUENCY ERRORS

#### ❌ WRONG: Using study-wide totals for gene frequencies
```sql
-- INCORRECT - This gives wrong frequencies!
SELECT
    hugo_gene_symbol,
    COUNT(DISTINCT sample_unique_id) as altered_samples,
    (SELECT COUNT(DISTINCT sample_unique_id)
     FROM genomic_event_derived
     WHERE cancer_study_identifier = 'your_study_id') as total_samples
FROM genomic_event_derived
WHERE variant_type = 'mutation' AND cancer_study_identifier = 'your_study_id'
GROUP BY hugo_gene_symbol;
```
**Problem**: Different genes have different profiling coverage - you can't use study-wide totals!

#### ❌ WRONG: Not using gene-specific profiling denominators
```sql
-- INCORRECT - Missing gene-specific denominators
SELECT
    hugo_gene_symbol,
    COUNT(DISTINCT sample_unique_id) as altered_samples
FROM genomic_event_derived
WHERE variant_type = 'mutation'
GROUP BY hugo_gene_symbol;
-- Missing: WHERE ARE THE DENOMINATORS FOR EACH GENE?
```

#### ❌ WRONG: Skipping individual gene profiling queries
**Problem**: Failing to run separate profiling queries for EACH gene in results.
**Each gene has different coverage**: TP53 might be profiled in 25,040 samples, MUC16 in 23,000, etc.

#### ✅ CORRECT: Complete gene-specific workflow
```sql
-- STEP 1: Get altered counts per gene
SELECT
    hugo_gene_symbol,
    entrez_gene_id,
    COUNT(DISTINCT CASE WHEN off_panel = 0 THEN sample_unique_id END) AS numberOfAlteredSamplesOnPanel,
    COUNT(*) AS totalMutationEvents
FROM genomic_event_derived
WHERE variant_type = 'mutation' AND mutation_status != 'UNCALLED'
GROUP BY entrez_gene_id, hugo_gene_symbol
ORDER BY numberOfAlteredSamplesOnPanel DESC;

-- STEP 2: FOR EACH GENE, run this profiling query:
SELECT COUNT(DISTINCT stgp.sample_unique_id) AS numberOfProfiledSamples
FROM sample_to_gene_panel_derived stgp
JOIN gene_panel gp ON stgp.gene_panel_id = gp.stable_id
JOIN gene_panel_list gpl ON gp.internal_id = gpl.internal_id
JOIN gene g ON gpl.gene_id = g.entrez_gene_id
WHERE stgp.alteration_type = 'MUTATION_EXTENDED'
  AND g.hugo_gene_symbol = 'TP53'  -- Replace with each gene from Step 1
  AND stgp.cancer_study_identifier = 'your_study_id';

-- STEP 3: Calculate frequency = numberOfAlteredSamplesOnPanel / numberOfProfiledSamples * 100
```

#### 🚨 WORKFLOW REQUIREMENTS VIOLATIONS:
- **Missing denominator columns**: Must show gene-specific profiled samples per row
- **Wrong table format**: Should be | Gene | # Mutations | # Samples | Profiled Samples | Sample % |
- **Not replacing gene symbols**: Must replace 'TP53' with actual gene for each query
- **Using study totals**: Never use genomic_event_derived for total sample counts

### 2. 🚨 OFF-PANEL MUTATION INCLUSION

#### ❌ Wrong: Including off-panel mutations
```sql
-- INCORRECT - Includes mutations outside gene panels
SELEC … (37891 more chars)

◀ result
# Mutation Frequency Analysis Guide

## IMPORTANT: Reporting Mutation Frequencies
- **ALWAYS report frequencies as percentages**, not raw counts: `frequency = (altered_samples / total_profiled_samples) × 100`
- For quick frequency lookups, **prefer the TCGA Pan-Cancer Atlas study first**, then offer to expand to other studies
- When reporting across multiple studies, show **ranges** (e.g., "TP53 is mutated in 30–60% of samples") rather than a single average
- **NEVER** sum mutation events across studies to compute an aggregate frequency — this can exceed 100% due to double-counting
- Warn users that samples may overlap across cohorts (e.g., MSK studies may share patients)
- **Choose and state the counting unit**: use patient-level frequencies for prevalence/rate questions unless the user explicitly asks for samples; use sample-level frequencies when the user asks about samples.
- **For "across cancer types" questions**, jump to the [Cross-Cancer-Type Mutation Frequency](#cross-cancer-type-mutation-frequency) section below — there is one correct recipe and several common wrong ones.

## Counting Unit: Samples vs Patients

Before answering any mutation count or frequency question, decide whether the unit is samples or patients and state that choice in the answer.

| User wording | Counting unit |
|--------------|---------------|
| "prevalence", "rate", "fraction of patients", "patients with", "how common is" | Patient-level: `COUNT(DISTINCT patient_unique_id)` |
| "samples", "specimens", "biopsies", sample-level cohort composition | Sample-level: `COUNT(DISTINCT sample_unique_id)` |
| Ambiguous | Ask, or default to patient-level for prevalence/rate language and say so |

### Cross-study sample-count caveat

When an answer touches more than one study and reports a sample count, prepend a one-line caveat:

> Sample IDs are unique within cBioPortal study prefixes, not guaranteed biological-sample identifiers across studies; overlapping cohorts can count the same patient/sample more than once.

Prefer one of these safer approaches:

- Use a shipped `cancer_study_query_preferences` cohort such as `pan_cancer_tcga` or `all_studies_non_redundant`.
- Restrict to one named study.
- Aggregate by `patient_unique_id` when the biological question is patient prevalence.

## STOP rule: a frequency above 100% means your query is wrong

If your query returns a frequency over 100%, **do not try to debug or explain the data inconsistency to the user**. The cause is always one of these query bugs:

- Summing mutation events instead of `COUNT(DISTINCT sample_unique_id)` for the numerator
- Using a study-wide sample count as the denominator instead of the gene-specific profiled count
- Cross-study aggregation where the same biological sample appears under multiple `sample_unique_id` values (e.g., MSK-IMPACT and MSK-CHORD share patients)
- **Joining the profiled CTE through `gene_panel` / `gene_panel_list` without a WES branch.** `gene_panel_id = 'WES'` is *not* a row in … (35166 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT cancer_study_identifier, hugo_gene_symbol, mutation_variant, mutation_type, mutation_status, COUNT(DISTINCT sample_unique_id) AS n_samples
FROM genomic_event_derived
WHERE hugo_gene_symbol = 'PIK3CA'
  AND variant_type = 'mutation'
  AND (mutation_variant ILIKE '%1069%' OR mutation_variant ILIKE '%ext%')
GROUP BY cancer_study_identifier, hugo_gene_symbol, mutation_variant, mutation_type, mutation_status
ORDER BY n_samples DESC
LIMIT 50",
 "max_rows": 50
}

◀ result
{"rows":[{"cancer_study_identifier":"msk_impact_50k_2026","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Ffs*5","mutation_type":"Frame_Shift_Ins","mutation_status":"SOMATIC","n_samples":3},{"cancer_study_identifier":"msk_impact_50k_2026","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":3},{"cancer_study_identifier":"msk_impact_2017","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Ffs*5","mutation_type":"Frame_Shift_Ins","mutation_status":"NA","n_samples":3},{"cancer_study_identifier":"msk_met_2021","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"ccle_broad_2025","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","n_samples":2},{"cancer_study_identifier":"crc_msk_2026","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"msk_impact_50k_2026","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069*","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"breast_msk_2026","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069*","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"msk_met_2021","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Ffs*5","mutation_type":"Frame_Shift_Ins","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"cellline_ccle_broad","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","n_samples":2},{"cancer_study_identifier":"msk_chord_2024","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"ccle_genentech_2014","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","n_samples":2},{"cancer_study_identifier":"msk_chord_2024","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Ffs*5","mutation_type":"Frame_Shift_Ins","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"pancan_mimsi_msk_2024","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","n_samples":2},{"cancer_study_identifier":"ccle_broad_2019","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","n_samples":2},{"cancer_study_identifier":"msk_chord_2024","hugo_gene_symbol":"PIK3CA","mutation_variant":"*1069fs*","mutation_type":"Frame_Shift_Del","mutation_status":"SOMATIC","n_samples":1},{"cancer_study_identifier":"gbm_tcga_pub2013","hugo_gene_symbol":"PIK3CA","mutat … (4783 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT cancer_study_identifier, mutation_variant, mutation_type, mutation_status, off_panel, COUNT(DISTINCT sample_unique_id) AS n_samples
FROM genomic_event_derived
WHERE hugo_gene_symbol = 'PIK3CA'
  AND variant_type = 'mutation'
  AND mutation_variant = '*1069Wext*4'
GROUP BY cancer_study_identifier, mutation_variant, mutation_type, mutation_status, off_panel
ORDER BY n_samples DESC",
 "max_rows": 50
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
{"rows":[{"cancer_study_identifier":"msk_impact_50k_2026","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","off_panel":false,"n_samples":3},{"cancer_study_identifier":"msk_chord_2024","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","off_panel":false,"n_samples":2},{"cancer_study_identifier":"msk_met_2021","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","off_panel":false,"n_samples":2},{"cancer_study_identifier":"ccle_genentech_2014","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":2},{"cancer_study_identifier":"cellline_ccle_broad","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":2},{"cancer_study_identifier":"ccle_broad_2019","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":2},{"cancer_study_identifier":"pancan_mimsi_msk_2024","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","off_panel":false,"n_samples":2},{"cancer_study_identifier":"ccle_broad_2025","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":2},{"cancer_study_identifier":"crc_msk_2026","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"SOMATIC","off_panel":false,"n_samples":2},{"cancer_study_identifier":"cellline_nci60","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":1},{"cancer_study_identifier":"coadread_dfci_2016","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":1},{"cancer_study_identifier":"gbm_tcga_pub2013","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"Unknown","off_panel":false,"n_samples":1},{"cancer_study_identifier":"gbm_tcga_pan_can_atlas_2018","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":".","off_panel":false,"n_samples":1},{"cancer_study_identifier":"gbm_tcga","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"Somatic","off_panel":false,"n_samples":1},{"cancer_study_identifier":"gbm_tcga_gdc","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"Somatic","off_panel":false,"n_samples":1},{"cancer_study_identifier":"brca_metabric","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":1},{"cancer_study_identifier":"lgggbm_tcga_pub","mutation_variant":"*1069Wext*4","mutation_type":"Nonstop_Mutation","mutation_status":"NA","off_panel":false,"n_samples":1}]}

◀ result
{"columns":[{"name":"sample_unique_id","type":"String"},{"name":"hugo_gene_symbol","type":"String","comment":"HUGO gene symbol (e.g., TP53, KRAS, BRAF). Use for gene-specific queries."},{"name":"entrez_gene_id","type":"Int32"},{"name":"gene_panel_stable_id","type":"LowCardinality(String)"},{"name":"cancer_study_identifier","type":"LowCardinality(String)"},{"name":"genetic_profile_stable_id","type":"LowCardinality(String)"},{"name":"variant_type","type":"LowCardinality(String)","comment":"Type of genomic event: \"mutation\" for SNVs/indels, \"cna\" for copy number alterations, \"structural_variant\" for SVs. Always filter by this."},{"name":"mutation_variant","type":"String","comment":"Protein change notation (e.g., p.V600E, p.R175H). Use for specific variant queries. \"NA\" for non-mutation events."},{"name":"mutation_type","type":"LowCardinality(String)"},{"name":"mutation_status","type":"LowCardinality(String)","comment":"For mutations: Somatic, Germline, UNKNOWN, or UNCALLED. Filter mutation_status != \"UNCALLED\" to exclude uncertain calls. Include all other statuses."},{"name":"driver_filter","type":"LowCardinality(String)"},{"name":"driver_filter_annotation","type":"String"},{"name":"driver_tiers_filter","type":"LowCardinality(String)"},{"name":"driver_tiers_filter_annotation","type":"String"},{"name":"cna_alteration","type":"Nullable(Int8)","comment":"Copy number alteration: only 2 = amplification (AMP) and -2 = deep deletion (HOMDEL) are stored. Shallow deletion (-1), diploid (0) and gain (1) are not in this table; query genetic_alteration_derived WHERE profile_type = 'gistic' (alteration_value is a String, e.g. '-1'). NULL for non-CNA events."},{"name":"cna_cytoband","type":"String"},{"name":"sv_event_info","type":"String"},{"name":"patient_unique_id","type":"String"},{"name":"off_panel","type":"Bool","comment":"Boolean: 1 = mutation outside gene panel coverage (off-panel), 0 = within panel (on-panel). Filter off_panel = 0 for reliable frequency calculations."}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT cancer_study_identifier, mutation_variant, driver_filter, driver_filter_annotation, driver_tiers_filter, driver_tiers_filter_annotation
FROM genomic_event_derived
WHERE hugo_gene_symbol = 'PIK3CA'
  AND variant_type = 'mutation'
  AND mutation_variant = '*1069Wext*4'
LIMIT 20",
 "max_rows": 20
}

◀ result
{"rows":[{"cancer_study_identifier":"brca_metabric","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"ccle_broad_2019","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"ccle_broad_2019","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"ccle_broad_2025","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"ccle_broad_2025","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"gbm_tcga_gdc","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"gbm_tcga","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"gbm_tcga_pan_can_atlas_2018","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_chord_2024","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_chord_2024","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"pancan_mimsi_msk_2024","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"pancan_mimsi_msk_2024","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"coadread_dfci_2016","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"lgggbm_tcga_pub","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_impact_50k_2026","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_impact_50k_2026","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_impact_50k_2026","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"gbm_tcga_pub2013","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_met_2021","mutation_variant":"*1069Wext*4"},{"cancer_study_identifier":"msk_met_2021","mutation_variant":"*1069Wext*4"}]}

▶ resolve_and_route
{
 "studyIds": [
  "msk_chord_2024"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040,"studyViewUrl":"https://www.cbioportal.org/study?id=msk_chord_2024","metadata":{"clinicalAttributeIds":["ADRENAL_GLANDS","BONE","CANCER_TYPE","CANCER_TYPE_DETAILED","CLINICAL_GROUP","CLINICAL_SUMMARY","CNS_BRAIN","CURRENT_AGE_DEID","DIAGNOSIS_DESCRIPTION","ETHNICITY","FRACTION_GENOME_ALTERED","GENDER","GENE_PANEL","GLEASON_FIRST_REPORTED","GLEASON_HIGHEST_REPORTED","GLEASON_SAMPLE_LEVEL","HER2","HISTORY_OF_PDL1","HR","ICD_O_HISTOLOGY_DESCRIPTION","INTRA_ABDOMINAL","LIVER","LUNG","LYMPH_NODES","METASTATIC_SITE","MSI_COMMENT","MSI_SCORE","MSI_TYPE","MUTATION_COUNT","NUM_ICDO_DX","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER","PATHOLOGICAL_GROUP","PDL1_POSITIVE","PLEURA","PRIMARY_SITE","PRIOR_MED_TO_MSK","RACE","REPRODUCTIVE_ORGANS","SAMPLE_CLASS","SAMPLE_COUNT","SAMPLE_COVERAGE","SAMPLE_TYPE","SMOKING_PREDICTIONS_3_CLASSES","SOMATIC_STATUS","STAGE_HIGHEST_RECORDED","TMB_NONSYNONYMOUS","TUMOR_PURITY"],"molecularProfileIds":["msk_chord_2024_cna","msk_chord_2024_mutations","msk_chord_2024_structural_variants"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations"]}}]}}

▶ navigate_to_results_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "genes": [
  "PIK3CA: X1069Wext*4"
 ],
 "tab": "mutations"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/mutations?cancer_study_list=msk_chord_2024&gene_list=PIK3CA%3A+X1069Wext*4&case_set_id=msk_chord_2024_all","url":"https://www.cbioportal.org/results/mutations?cancer_study_list=msk_chord_2024&gene_list=PIK3CA%3A+X1069Wext*4&case_set_id=msk_chord_2024_all","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"genes":["PIK3CA"],"caseSetId":"msk_chord_2024_all","pageDescription":"Detailed mutation table with lollipop plot showing mutation positions, types, and frequencies for queried genes."}}

═ answer (success)
[View PIK3CA *1069Wext*4 mutations in MSK-CHORD (Mutations Tab)](https://www.cbioportal.org/results/mutations?cancer_study_list=msk_chord_2024&gene_list=PIK3CA%3A+X1069Wext*4&case_set_id=msk_chord_2024_all)

This opens the MSK-CHORD cohort (25,040 samples) Mutations tab with a lollipop plot showing this variant's position and the 2 samples carrying it, alongside the full PIK3CA mutation spectrum for context. You can switch the study dropdown in the portal to view other cohorts (e.g., msk_impact_50k_2026, gbm_tcga_pan_can_atlas_2018) where it also recurs.

**Bottom line:** This is a real, recurrent (though rare) PIK3CA stop-loss variant seen across ~15 cBioPortal cohorts, but I have no driver/oncogenicity annotation for it in this database, and I flagged a nomenclature discrepancy (`ext*3` in your report vs. `ext*4` here) that's worth verifying against your report's exact transcript. For functional/clinical interpretation, please consult OncoKB, ClinVar, or your lab's variant-interpretation pipeline — this is research data, not clinical guidance.