Q (haiku): What are the most commonly co-occurring mutation pairs in breast cancer samples from the MSK-CHORD Study?

▶ 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": "
WITH breast_cancer_samples AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND attribute_name = 'CANCER_TYPE'
      AND attribute_value = 'Breast Cancer'
),
mutated_genes_per_sample AS (
    SELECT DISTINCT sample_unique_id, hugo_gene_symbol
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND variant_type = 'mutation'
      AND mutation_status != 'UNCALLED'
      AND off_panel = 0
      AND sample_unique_id IN (SELECT sample_unique_id FROM breast_cancer_samples)
)
SELECT 
    a.hugo_gene_symbol AS gene_1,
    b.hugo_gene_symbol AS gene_2,
    COUNT() AS co_mutated_samples,
    (SELECT COUNT(DISTINCT sample_unique_id) FROM breast_cancer_samples) AS total_breast_samples
FROM mutated_genes_per_sample a
JOIN mutated_genes_per_sample b 
  ON a.sample_unique_id = b.sample_unique_id 
  AND a.hugo_gene_symbol < b.hugo_gene_symbol
GROUP BY gene_1, gene_2
ORDER BY co_mutated_samples DESC
LIMIT 20
",
 "max_rows": 20
}

◀ result
{"rows":[{"gene_1":"PIK3CA","gene_2":"TP53","co_mutated_samples":597,"total_breast_samples":5368},{"gene_1":"CDH1","gene_2":"PIK3CA","co_mutated_samples":346,"total_breast_samples":5368},{"gene_1":"MAP3K1","gene_2":"PIK3CA","co_mutated_samples":256,"total_breast_samples":5368},{"gene_1":"GATA3","gene_2":"PIK3CA","co_mutated_samples":230,"total_breast_samples":5368},{"gene_1":"KMT2C","gene_2":"PIK3CA","co_mutated_samples":218,"total_breast_samples":5368},{"gene_1":"PTEN","gene_2":"TP53","co_mutated_samples":163,"total_breast_samples":5368},{"gene_1":"KMT2C","gene_2":"TP53","co_mutated_samples":148,"total_breast_samples":5368},{"gene_1":"PIK3CA","gene_2":"TBX3","co_mutated_samples":138,"total_breast_samples":5368},{"gene_1":"NF1","gene_2":"TP53","co_mutated_samples":135,"total_breast_samples":5368},{"gene_1":"CBFB","gene_2":"PIK3CA","co_mutated_samples":129,"total_breast_samples":5368},{"gene_1":"ESR1","gene_2":"PIK3CA","co_mutated_samples":129,"total_breast_samples":5368},{"gene_1":"CDH1","gene_2":"TP53","co_mutated_samples":126,"total_breast_samples":5368},{"gene_1":"ARID1A","gene_2":"PIK3CA","co_mutated_samples":126,"total_breast_samples":5368},{"gene_1":"RB1","gene_2":"TP53","co_mutated_samples":125,"total_breast_samples":5368},{"gene_1":"CDH1","gene_2":"TBX3","co_mutated_samples":124,"total_breast_samples":5368},{"gene_1":"FOXA1","gene_2":"PIK3CA","co_mutated_samples":121,"total_breast_samples":5368},{"gene_1":"GATA3","gene_2":"TP53","co_mutated_samples":111,"total_breast_samples":5368},{"gene_1":"NF1","gene_2":"PIK3CA","co_mutated_samples":110,"total_breast_samples":5368},{"gene_1":"KMT2D","gene_2":"TP53","co_mutated_samples":107,"total_breast_samples":5368},{"gene_1":"MAP3K1","gene_2":"TP53","co_mutated_samples":105,"total_breast_samples":5368}]}

▶ navigate_to_study_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "filterJson": {
  "clinicalDataFilters": [
   {
    "attributeId": "CANCER_TYPE",
    "values": [
     {
      "value": "Breast Cancer"
     }
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Breast%20Cancer%22%7D%5D%7D%5D%7D","url":"https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Breast%20Cancer%22%7D%5D%7D%5D%7D","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"tab":"summary","hasFilters":true,"hasPlotsConfig":false,"pageDescription":"Overview of all study data displayed as interactive charts summarizing available clinical and genomic data. Click within a chart to filter. Additional charts may be available in the Charts menu."}}

▶ navigate_to_results_view
{
 "studyIds": [
  "msk_chord_2024"
 ],
 "genes": [
  "PIK3CA",
  "TP53"
 ],
 "studyViewFilter": {
  "clinicalDataFilters": [
   {
    "attributeId": "CANCER_TYPE",
    "values": [
     {
      "value": "Breast Cancer"
     }
    ]
   }
  ]
 },
 "tab": "oncoprint"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/oncoprint?session_id=6ab42865e497aad53593bdcc","url":"https://www.cbioportal.org/results/oncoprint?session_id=6ab42865e497aad53593bdcc","data":{"studyIds":["msk_chord_2024"],"studies":[{"studyId":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","sampleCount":25040}],"genes":["PIK3CA","TP53"],"filteredSampleCount":5368,"caseSetId":"-1","sessionId":"6ab42865e497aad53593bdcc","studyViewUrl":"https://www.cbioportal.org/study?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Breast%20Cancer%22%7D%5D%7D%5D%7D","pageDescription":"Visual summary of alterations in queried genes across samples."}}

═ answer (success)
## Most Common Co-Occurring Mutation Pairs in MSK-CHORD Breast Cancer

**Sample-level analysis** across 5,368 breast cancer samples from the MSK-CHORD study.

### Top 20 Co-Mutated Gene Pairs

| Rank | Gene Pair | Co-Mutated Samples | Frequency |
|------|-----------|-------------------|-----------|
| 1 | **PIK3CA + TP53** | 597 | 11.1% |
| 2 | CDH1 + PIK3CA | 346 | 6.4% |
| 3 | MAP3K1 + PIK3CA | 256 | 4.8% |
| 4 | GATA3 + PIK3CA | 230 | 4.3% |
| 5 | KMT2C + PIK3CA | 218 | 4.1% |
| 6 | PTEN + TP53 | 163 | 3.0% |
| 7 | KMT2C + TP53 | 148 | 2.8% |
| 8 | PIK3CA + TBX3 | 138 | 2.6% |
| 9 | NF1 + TP53 | 135 | 2.5% |
| 10 | CBFB + PIK3CA | 129 | 2.4% |
| 11 | ESR1 + PIK3CA | 129 | 2.4% |
| 12 | CDH1 + TP53 | 126 | 2.3% |
| 13 | ARID1A + PIK3CA | 126 | 2.3% |
| 14 | RB1 + TP53 | 125 | 2.3% |
| 15 | CDH1 + TBX3 | 124 | 2.3% |
| 16 | FOXA1 + PIK3CA | 121 | 2.3% |
| 17 | GATA3 + TP53 | 111 | 2.1% |
| 18 | NF1 + PIK3CA | 110 | 2.0% |
| 19 | KMT2D + TP53 | 107 | 2.0% |
| 20 | MAP3K1 + TP53 | 105 | 2.0% |

### Key Findings

- **PIK3CA + TP53** is the dominant co-occurring pair (597 samples, 11.1%), consistent with the importance of PI3K and p53 pathways in breast cancer development.
- **PIK3CA dominates the top pairs**, appearing in 8 of the top 20 pairings, reflecting its high baseline mutation frequency in breast cancer.
- **TP53 is the second most common partner**, appearing in 11 of the top 20 pairs, indicating co-selection with multiple driver genes.
- Other common partners with PIK3CA include **CDH1**, **MAP3K1**, **GATA3**, and **KMT2C**, all known breast cancer driver genes.

**Note:** These counts reflect raw co-occurrence; statistical significance (co-occurrence vs. independence) requires additional testing that accounts for individual gene mutation frequencies.

---

### Explore This Data

[**View breast cancer cohort overview**](https://www.cbioportal.org/study/summary?id=msk_chord_2024#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22CANCER_TYPE%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Breast%20Cancer%22%7D%5D%7D%5D%7D) — Summary of clinical and genomic distributions in breast cancer samples.

[**View PIK3CA + TP53 OncoPrint**](https://www.cbioportal.org/results/oncoprint?session_id=6ab42865e497aad53593bdcc) — Visual alteration patterns for the most common co-mutated pair (breast cancer subset).