Q (sonnet): What percentage of colorectal cancer samples have KRAS mutations in the MSK-CHORD Study?

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

◀ 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)

▶ list_studies
{
 "search": "MSK CHORD"
}

▶ search_oncotree
{
 "search_term": "colorectal"
}

◀ result
{"result":[{"cancer_study_identifier":"msk_chord_2024","name":"MSK-CHORD (MSK, Nature 2024)","type_of_cancer_id":"mixed","sample_count":25040,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=msk_chord_2024"}]}

◀ result
{"result":[{"code":"COADREAD","name":"Colorectal Adenocarcinoma","score":60,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD"},{"code":"CAIS","name":"Colon Adenocarcinoma In Situ","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > CAIS"},{"code":"CMC","name":"Medullary Carcinoma of the Colon","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > CMC"},{"code":"COAD","name":"Colon Adenocarcinoma","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > COAD"},{"code":"MACR","name":"Mucinous Adenocarcinoma of the Colon and Rectum","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > MACR"},{"code":"READ","name":"Rectal Adenocarcinoma","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > READ"},{"code":"SRCCR","name":"Signet Ring Cell Adenocarcinoma of the Colon and Rectum","score":45,"mainType":"Colorectal Cancer","tissue":"Bowel","hierarchy":"BOWEL > COADREAD > SRCCR"}]}

▶ get_study_guide
{
 "study_id": "msk_chord_2024"
}

◀ result
# MSK-CHORD (MSK, Nature 2024)

**Study ID:** `msk_chord_2024`

## Overview
Targeted sequencing via MSK-IMPACT panels. Clinical annotations include some derived from natural language processing (denoted NLP).

**Exactly five cancer types** (`CANCER_TYPE`, patients): Non-Small Cell Lung Cancer 7,809, Colorectal Cancer 5,543, Breast Cancer 5,368, Prostate Cancer 3,211, Pancreatic Cancer 3,109. There is **no melanoma** or any other cancer type; say so up front if asked, instead of substituting another type.

**No therapy-response variable.** There is no RECIST, objective response, or best-response attribute or event. For treatment-outcome questions (e.g. immunotherapy response), say this first; the only proxies are `OS_MONTHS`/`OS_STATUS`, or NLP radiology progression events (`Diagnosis` events with `SUBTYPE = 'Progression'`, key `PROGRESSION` = Y/N/Indeterminate), in patients with `Treatment` events of the relevant `SUBTYPE` (e.g. `Immuno`: 3,341 patients). Hand off the comparison to cBioPortal group comparison / survival.

**Nearly one sample per patient: 24,950 patients / 25,040 samples.** Only 90 patients have more than one sample, and all 90 have samples from two different cancer types (second primaries); only 26 have both a `Primary` and a `Metastasis` sample. There is no meaningful same-patient (paired) primary-vs-metastasis cohort. For "same patient" / paired questions, say this up front, then offer the **unpaired** comparison of all `Primary` vs `Metastasis` samples (`SAMPLE_TYPE`), labelled as unpaired.
```sql
SELECT countIf(n > 1) AS multi_sample_patients,         -- 90
       countIf(has_p AND has_m) AS primary_and_met      -- 26
FROM (SELECT patient_unique_id, count() AS n,
             has(groupArray(attribute_value), 'Primary') AS has_p,
             has(groupArray(attribute_value), 'Metastasis') AS has_m
      FROM clinical_data_derived
      WHERE cancer_study_identifier = 'msk_chord_2024' AND attribute_name = 'SAMPLE_TYPE'
      GROUP BY patient_unique_id);
```

## Gene Panels
This study uses multiple MSK-IMPACT panel versions:
- **IMPACT341**: Earlier version, 341 genes
- **IMPACT410**: 410 genes
- **IMPACT468**: 468 genes  
- **IMPACT505**: Latest version, 505 genes

**Important:** Different samples may have different gene coverage. Always use gene-specific denominators when calculating mutation frequencies.

## Clinical Attributes - Semantic Guide

### Cancer Classification
| Attribute | Description | Values |
|-----------|-------------|--------|
| `CANCER_TYPE` | Broad cancer category | e.g., "Non-Small Cell Lung Cancer", "Breast Cancer" |
| `CANCER_TYPE_DETAILED` | Specific subtype | e.g., "Lung Adenocarcinoma", "Invasive Ductal Carcinoma" |
| `ONCOTREE_CODE` | OncoTree classification code | Standardized cancer type codes |

### Sample Information
| Attribute | Description | Values |
|-----------|-------------|--------|
| `SAMPLE_TYPE` | Sample origin | Primary, Metastasis, Local Recurrence, Unknown |
| `SAMPLE_CLASS` | Sample … (5439 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT DISTINCT attribute_value FROM clinical_data_derived WHERE cancer_study_identifier = 'msk_chord_2024' AND attribute_name = 'CANCER_TYPE' AND lower(attribute_value) LIKE '%colorectal%'"
}

◀ result
{"rows":[{"attribute_value":"Colorectal Cancer"}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH crc_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 = 'Colorectal Cancer'
),
altered AS (
    SELECT COUNT(DISTINCT sample_unique_id) AS altered_samples
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'msk_chord_2024'
      AND variant_type = 'mutation'
      AND mutation_status != 'UNCALLED'
      AND hugo_gene_symbol = 'KRAS'
      AND off_panel = 0
      AND sample_unique_id IN (SELECT sample_unique_id FROM crc_samples)
),
profiled_for_gene AS (
    SELECT sample_unique_id
    FROM mutation_panel_gene_coverage
    WHERE hugo_gene_symbol = 'KRAS'
      AND cancer_study_identifier = 'msk_chord_2024'
    UNION ALL
    SELECT sample_unique_id
    FROM mutation_wes_coverage
    WHERE cancer_study_identifier = 'msk_chord_2024'
),
profiled AS (
    SELECT COUNT(DISTINCT p.sample_unique_id) AS profiled_samples
    FROM profiled_for_gene p
    WHERE p.sample_unique_id IN (SELECT sample_unique_id FROM crc_samples)
)
SELECT a.altered_samples, p.profiled_samples,
       ROUND(a.altered_samples * 100.0 / p.profiled_samples, 1) AS frequency_pct
FROM altered a, profiled p
"
}

◀ result
{"rows":[{"altered_samples":2355,"profiled_samples":5543,"frequency_pct":42.5}]}

▶ 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": [
  "KRAS: MUT"
 ],
 "tab": "cancerTypesSummary"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/cancerTypesSummary?cancer_study_list=msk_chord_2024&gene_list=KRAS%3A+MUT&case_set_id=msk_chord_2024_all","url":"https://www.cbioportal.org/results/cancerTypesSummary?cancer_study_list=msk_chord_2024&gene_list=KRAS%3A+MUT&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":["KRAS"],"caseSetId":"msk_chord_2024_all","pageDescription":"Alteration frequencies for queried genes by cancer type."}}

═ answer (success)
[View KRAS mutation frequency across cancer types in MSK-CHORD](https://www.cbioportal.org/results/cancerTypesSummary?cancer_study_list=msk_chord_2024&gene_list=KRAS%3A+MUT&case_set_id=msk_chord_2024_all)

This shows the breakdown of KRAS mutation frequency across all five cancer types in the MSK-CHORD cohort (Colorectal, NSCLC, Breast, Prostate, Pancreatic), letting you confirm the colorectal figure and compare it to the other types in the study.