Q (haiku): What percentage of patients in the MSK-CHORD Study have at least one TP53 mutation?

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

▶ resolve_and_route
{
 "studyKeywords": [
  "MSK-CHORD"
 ]
}

◀ 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)

◀ 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"]}}]}}

▶ clickhouse_run_select_query
{
 "query": "
SELECT *
FROM gene_mutation_frequency_in_study(
    study = 'msk_chord_2024',
    gene  = 'TP53'
)
"
}

◀ result
{"rows":[{"cancer_type":"Prostate Cancer","altered_samples":837,"profiled_samples":3211,"frequency_pct":26.1},{"cancer_type":"Breast Cancer","altered_samples":2138,"profiled_samples":5368,"frequency_pct":39.8},{"cancer_type":"Pancreatic Cancer","altered_samples":2076,"profiled_samples":3109,"frequency_pct":66.8},{"cancer_type":"Colorectal Cancer","altered_samples":4068,"profiled_samples":5543,"frequency_pct":73.4},{"cancer_type":"Non-Small Cell Lung Cancer","altered_samples":4005,"profiled_samples":7809,"frequency_pct":51.3}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH tp53_mutant_patients AS (
    SELECT DISTINCT c.patient_unique_id
    FROM genomic_event_derived ged
    JOIN clinical_data_derived c USING (sample_unique_id)
    WHERE ged.cancer_study_identifier = 'msk_chord_2024'
      AND ged.hugo_gene_symbol = 'TP53'
      AND ged.variant_type = 'mutation'
      AND ged.mutation_status != 'UNCALLED'
      AND ged.off_panel = 0
),
tp53_profiled_patients AS (
    SELECT DISTINCT c.patient_unique_id
    FROM sample_to_gene_panel_derived sgp
    JOIN clinical_data_derived c USING (sample_unique_id)
    WHERE sgp.cancer_study_identifier = 'msk_chord_2024'
      AND sgp.alteration_type = 'MUTATION_EXTENDED'
),
totals AS (
    SELECT
        (SELECT COUNT(*) FROM tp53_mutant_patients) AS mutant_patients,
        (SELECT COUNT(*) FROM tp53_profiled_patients) AS profiled_patients
)
SELECT
    mutant_patients,
    profiled_patients,
    ROUND(mutant_patients * 100.0 / NULLIF(profiled_patients, 0), 1) AS frequency_pct
FROM totals
",
 "max_rows": 10
}

◀ result
{"rows":[{"mutant_patients":13105,"profiled_patients":24950,"frequency_pct":52.5}]}

▶ navigate_to_results_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "genes": [
  "TP53"
 ],
 "tab": "oncoprint"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/oncoprint?cancer_study_list=msk_chord_2024&gene_list=TP53&case_set_id=msk_chord_2024_all","url":"https://www.cbioportal.org/results/oncoprint?cancer_study_list=msk_chord_2024&gene_list=TP53&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":["TP53"],"caseSetId":"msk_chord_2024_all","pageDescription":"Visual summary of alterations in queried genes across samples."}}

═ answer (success)
## Results

**52.5%** of patients in the MSK-CHORD Study have at least one TP53 mutation.

**Details:**
- **Mutant patients:** 13,105
- **Profiled patients:** 24,950
- **Patient-level frequency:** 52.5%

### Breakdown by Cancer Type

TP53 mutation frequency varies significantly by cancer type within MSK-CHORD:

| Cancer Type | TP53 Mutation Frequency |
|---|---|
| Colorectal Cancer | 73.4% (4,068/5,543) |
| Pancreatic Cancer | 66.8% (2,076/3,109) |
| Non-Small Cell Lung Cancer | 51.3% (4,005/7,809) |
| Breast Cancer | 39.8% (2,138/5,368) |
| Prostate Cancer | 26.1% (837/3,211) |

[View TP53 alterations in MSK-CHORD (OncoPrint)](https://www.cbioportal.org/results/oncoprint?cancer_study_list=msk_chord_2024&gene_list=TP53&case_set_id=msk_chord_2024_all)