Q (haiku): are there cdkn2a het losses in gbm tcga study?

▶ read_guide
{
 "uri": "cbioportal://gene-expression-guide"
}

▶ list_studies
{
 "search": "GBM TCGA"
}

◀ result
# Gene Expression Analysis Guide

This guide covers continuous-value genomic data: gene **expression**, **copy number** values, **methylation**, and related profile types. Mutation/CNA/SV *frequency* analysis lives in `cbioportal://mutation-frequency-guide`.

## Where this data lives

Continuous per-sample-per-gene values are stored in `genetic_alteration_derived`:

| Column | Description |
|---|---|
| `sample_unique_id` | `<study>_<sample_stable_id>` |
| `cancer_study_identifier` | study scope |
| `hugo_gene_symbol` | gene |
| `profile_type` | which assay/normalization (see below) |
| `alteration_value` | the actual value — stored as Nullable(String); cast with `toFloat64OrNull` |

`alteration_value` is a string because the same column hosts many different value scales. The `''` and `'NA'` sentinels mean "missing"; always filter them out and use `toFloat64OrNull(alteration_value) IS NOT NULL` for downstream math.

## Discovering profile types for a study

Different studies expose different profile types depending on what assays were run and how the data was normalized. Always check what a specific study supports before picking one:

```sql
SELECT DISTINCT profile_type
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'brca_metabric'
ORDER BY profile_type;
```

Common values across the public portal:

| Family | Profile types |
|---|---|
| mRNA expression | `mrna`, `mrna_median_Zscores`, `mrna_seq_v2_rsem`, `mrna_seq_v2_rsem_Zscores`, `mrna_seq_cpm`, `mrna_seq_fpkm`, `mrna_U133`, `mrna_outliers` |
| Copy number (continuous) | `cna`, `linear_CNA`, `log2CNA`, `cna_consensus`, `cna_rae`, `gistic` |
| Methylation | `methylation_hm27`, `methylation_hm450`, `methylation_epic`, `methylation_promoters_rrbs` |
| miRNA | `mirna`, `mirna_median_Zscores` |
| Protein | `protein_quantification`, `protein_level`, `RPPA` |

**Z-score vs raw choice.** When the user asks "is X correlated with Y", either works for Spearman (rank-based) — Pearson would care. Default to the non-Z-score variant if both exist, and call out which one in the response.

## Canonical recipe — Spearman correlation between two genes

```sql
SELECT *
FROM gene_pair_coexpression(
    study        = 'brca_metabric',
    gene_a       = 'TP53',
    gene_b       = 'MYC',
    profile_type = 'mrna'
);
```

Returns one row: `(gene_a, gene_b, profile_type, spearman_correlation, num_samples)`.

- `spearman_correlation` in [−1, 1]; `NULL` when fewer than 3 valid paired samples.
- Mirrors cbioportal-backend's `ClickhouseCoExpressionMapper.getCoExpressions`, simplified to a pair lookup (the backend computes one ref gene vs ALL other genes for the coexpression page; here the agent asks about a specific pair).

### Verified examples

| Study | gene_a | gene_b | profile_type | spearman | n |
|---|---|---|---|---|---|
| `brca_metabric` | TP53 | MYC | `mrna` | 0.118 | 1980 |
| `brca_metabric` | ESR1 | PGR | `mrna` | 0.487 | 1980 |

ESR1↔PGR is the textbook breast-cancer estrogen-receptor coregula … (2785 more chars)

✗ error
<tool_use_error>Error: No such tool available: mcp__navigator__list_studies</tool_use_error>

▶ list_studies
{
 "search": "GBM TCGA"
}

◀ result
{"result":[{"cancer_study_identifier":"lgggbm_tcga_pub","name":"Merged Cohort of LGG and GBM (TCGA, Cell 2016)","type_of_cancer_id":"difg","sample_count":1122,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=lgggbm_tcga_pub"},{"cancer_study_identifier":"gbm_tcga","name":"Glioblastoma Multiforme (TCGA, Firehose Legacy)","type_of_cancer_id":"difg","sample_count":619,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=gbm_tcga"},{"cancer_study_identifier":"gbm_tcga_gdc","name":"Glioblastoma Multiforme (TCGA GDC, 2025)","type_of_cancer_id":"difg","sample_count":611,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=gbm_tcga_gdc"},{"cancer_study_identifier":"gbm_tcga_pan_can_atlas_2018","name":"Glioblastoma Multiforme (TCGA, PanCancer Atlas)","type_of_cancer_id":"difg","sample_count":592,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=gbm_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"gbm_tcga_pub2013","name":"Glioblastoma (TCGA, Cell 2013)","type_of_cancer_id":"difg","sample_count":577,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=gbm_tcga_pub2013"},{"cancer_study_identifier":"gbm_tcga_pub","name":"Glioblastoma (TCGA, Nature 2008)","type_of_cancer_id":"difg","sample_count":206,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=gbm_tcga_pub"}]}

▶ clickhouse_run_select_query
{
 "query": "
-- Check available CNA profile types for GBM TCGA PanCancer Atlas
SELECT DISTINCT profile_type
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'gbm_tcga_pan_can_atlas_2018'
  AND hugo_gene_symbol = 'CDKN2A'
ORDER BY profile_type
"
}

◀ result
{"rows":[{"profile_type":"gistic"},{"profile_type":"log2CNA"},{"profile_type":"rna_seq_v2_mrna"},{"profile_type":"rna_seq_v2_mrna_median_Zscores"},{"profile_type":"rna_seq_v2_mrna_median_all_sample_Zscores"}]}

▶ clickhouse_run_select_query
{
 "query": "
-- CDKN2A heterozygous losses (HETLOSS = -1) in GBM TCGA PanCancer Atlas
SELECT
  COUNT(DISTINCT sample_unique_id) AS hetloss_samples,
  toFloat64OrNull(alteration_value) AS cna_level,
  COUNT(*) AS sample_count
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'gbm_tcga_pan_can_atlas_2018'
  AND hugo_gene_symbol = 'CDKN2A'
  AND profile_type = 'gistic'
  AND alteration_value NOT IN ('', 'NA')
GROUP BY cna_level
ORDER BY cna_level DESC
",
 "max_rows": 50
}

◀ result
{"rows":[{"hetloss_samples":20,"cna_level":1,"sample_count":20},{"hetloss_samples":119,"cna_level":0,"sample_count":119},{"hetloss_samples":114,"cna_level":-1,"sample_count":114},{"hetloss_samples":322,"cna_level":-2,"sample_count":322}]}

▶ clickhouse_run_select_query
{
 "query": "
-- Total GBM TCGA samples profiled for CDKN2A CNA
SELECT COUNT(DISTINCT sample_unique_id) AS total_profiled
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'gbm_tcga_pan_can_atlas_2018'
  AND hugo_gene_symbol = 'CDKN2A'
  AND profile_type = 'gistic'
"
}

◀ result
{"rows":[{"total_profiled":575}]}

▶ navigate_to_results_view
{
 "studyIds": [
  "gbm_tcga_pan_can_atlas_2018"
 ],
 "genes": [
  "CDKN2A"
 ],
 "tab": "oncoprint"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/oncoprint?cancer_study_list=gbm_tcga_pan_can_atlas_2018&gene_list=CDKN2A&case_set_id=gbm_tcga_pan_can_atlas_2018_all","url":"https://www.cbioportal.org/results/oncoprint?cancer_study_list=gbm_tcga_pan_can_atlas_2018&gene_list=CDKN2A&case_set_id=gbm_tcga_pan_can_atlas_2018_all","data":{"studyIds":["gbm_tcga_pan_can_atlas_2018"],"studies":[{"studyId":"gbm_tcga_pan_can_atlas_2018","name":"Glioblastoma Multiforme (TCGA, PanCancer Atlas)","sampleCount":592}],"genes":["CDKN2A"],"caseSetId":"gbm_tcga_pan_can_atlas_2018_all","pageDescription":"Visual summary of alterations in queried genes across samples."}}

═ answer (success)
## Yes, CDKN2A heterozygous losses are present in GBM TCGA.

**Summary:**

| CNA Level | Samples | % of Profiled |
|-----------|---------|---------------|
| **Heterozygous loss (−1)** | **114** | **19.8%** |
| Homozygous deletion (−2) | 322 | 56.0% |
| Neutral (0) | 119 | 20.7% |
| Gain (+1) | 20 | 3.5% |

In the **Glioblastoma Multiforme (TCGA, PanCancer Atlas)** study with 575 samples profiled for CDKN2A copy number, **114 samples (19.8%) show heterozygous loss**, and notably, **322 samples (56.0%) show homozygous deletion**—making CDKN2A one of the most frequently deleted genes in GBM.

[View CDKN2A alterations in GBM TCGA](https://www.cbioportal.org/results/oncoprint?cancer_study_list=gbm_tcga_pan_can_atlas_2018&gene_list=CDKN2A&case_set_id=gbm_tcga_pan_can_atlas_2018_all) — OncoPrint shows the full spectrum of alterations (heterozygous loss, homozygous deletion, and expression changes).