Q (sonnet): Which genomic alterations are associated with immunotherapy response in melanoma patients from the MSK-CHORD Study?

▶ read_guide
{
 "uri": "cbioportal://treatment-guide"
}

▶ get_study_guide
{
 "study_id": "msk_chord_2024"
}

◀ result
# Treatment Data Query Guide

## Overview

Treatment data in cBioPortal is stored in **clinical event tables**, separate from clinical attributes. This allows for timeline-based treatment records with start/stop dates.

## Start Here: Treatment Views

For "most common treatments / agents / regimens in study X", use the parameterized views (documented in `cbioportal://clinical-data-guide`, Study-View Chart Counts):

```sql
-- Patients per agent (the portal's Treatment chart), with type/subtype arrays
SELECT * FROM treatment_counts_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20;

-- Same-day agent combinations (investigational, prior-medication and radiation events excluded)
SELECT * FROM treatment_regimens_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20;
```

Write raw event queries (below) only for subgroups, timelines or keys the views do not expose.

## Key Tables

| Table | Description |
|-------|-------------|
| `clinical_event` | Event records with patient_id, event_type, start_date, stop_date |
| `clinical_event_data` | Key-value pairs linked to each clinical_event_id |

## Schema

```
clinical_event
├── clinical_event_id (PK)
├── patient_id (FK → patient.internal_id)
├── event_type (Treatment, TREATMENT, Diagnosis, SURGERY, etc.)
├── start_date (days from diagnosis)
└── stop_date (days from diagnosis)

clinical_event_data
├── clinical_event_id (FK)
├── key (AGENT, SUBTYPE, etc.)
└── value
```

## Event Types

Not all studies have all event types. Common ones include:

| Event Type | Description |
|------------|-------------|
| `Treatment` / `TREATMENT` | Drug/therapy administration |
| `SURGERY` | Surgical procedures |
| `Diagnosis` | Diagnosis events |
| `LAB_TEST` | Laboratory results |
| `Sequencing` | Sequencing events |
| `Sample acquisition` | Sample collection |
| `PATHOLOGY` / `Pathology` | Pathology reports |

## Basic Treatment Queries

### List Available Event Types in a Study

```sql
SELECT DISTINCT ce.event_type, COUNT(*) as event_count
FROM clinical_event ce
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id
WHERE cs.cancer_study_identifier = 'your_study_id'
GROUP BY ce.event_type
ORDER BY event_count DESC;
```

### List Treatment Data Keys in a Study

```sql
SELECT DISTINCT ced.key, COUNT(*) as cnt
FROM clinical_event ce
JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id
WHERE cs.cancer_study_identifier = 'your_study_id'
  AND ce.event_type IN ('Treatment', 'TREATMENT')
GROUP BY ced.key
ORDER BY cnt DESC;
```

### Get Most Common Treatment Agents

```sql
SELECT 
    ced.value as agent,
    COUNT(DISTINCT ce.patient_id) as patient_count
FROM clinical_event ce
JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id
JOIN patient p ON ce.patient_id = p.internal_id
JOIN cancer_stud … (6220 more chars)

◀ 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)

═ answer (success)
This surfaces two separate problems with the question, and I want to be upfront about both before doing anything else:

**1. MSK-CHORD does not include melanoma.** The study covers exactly five cancer types: Non-Small Cell Lung Cancer, Colorectal Cancer, Breast Cancer, Prostate Cancer, and Pancreatic Cancer. There is no melanoma cohort in this dataset — I can't substitute a different cancer type and call it melanoma.

**2. Even if melanoma were present, MSK-CHORD has no immunotherapy *response* variable.** There is no RECIST, objective response, or best-response field anywhere in the study. The only available proxies are:
- Overall survival (`OS_MONTHS`/`OS_STATUS`)
- NLP-derived radiology progression flags (`Diagnosis` events with `SUBTYPE = 'Progression'`, `PROGRESSION` = Y/N/Indeterminate) in patients who also have `Treatment` events with `SUBTYPE = 'Immuno'` (3,341 patients study-wide, across the five cancer types above)

Neither of these is a validated "response" endpoint, and linking them to genomic alterations to claim an "association" would require a statistical test (e.g., a group comparison with survival analysis or a contingency table) that I have not run — I won't fabricate that result.

**What I'd suggest instead**, depending on what you're actually after:

- If you're interested in melanoma and immunotherapy, that dataset doesn't exist in MSK-CHORD — I'd need to search for a different melanoma cohort in cBioPortal (e.g., a melanoma immunotherapy study) if that's useful.
- If you're interested in genomic alterations and immunotherapy exposure/outcomes specifically within MSK-CHORD's five actual cancer types (using OS or the NLP progression proxy, clearly labeled as such), I can set that up as a proper group comparison.

Could you clarify which direction you'd like? For example: "find a melanoma immunotherapy study in cBioPortal" or "look at NSCLC/other MSK-CHORD cancers and immunotherapy-treated patients' survival by mutation status."