Q (sonnet): Is BRCA1 promoter methylation associated with decreased BRCA1 mRNA expression in ovarian cancer?

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

▶ list_studies
{
 "search": "ovarian 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 | `rna_seq_v2_mrna`, `rna_seq_v2_mrna_median_Zscores`, `rna_seq_v2_mrna_median_all_sample_Zscores` (TCGA PanCancer Atlas), `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 |
|  … (4931 more chars)

◀ result
{"result":[{"cancer_study_identifier":"ov_tcga","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Firehose Legacy)","type_of_cancer_id":"hgsoc","sample_count":617,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga"},{"cancer_study_identifier":"hgsoc_tcga_gdc","name":"High-Grade Serous Ovarian Cancer (TCGA GDC, 2025)","type_of_cancer_id":"hgsoc","sample_count":604,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=hgsoc_tcga_gdc"},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"hgsoc","sample_count":585,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"ov_tcga_pub","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Nature 2011)","type_of_cancer_id":"hgsoc","sample_count":489,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga_pub"},{"cancer_study_identifier":"mixed_msk_tcga_2021","name":"RAD51B Associated Mixed Cancers (MSK, NPJ Breast Cancer 2021)","type_of_cancer_id":"mixed","sample_count":17,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=mixed_msk_tcga_2021"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT cancer_study_identifier, profile_type, count() AS n
FROM genetic_alteration_derived
WHERE cancer_study_identifier IN ('ov_tcga_pub','ov_tcga_pan_can_atlas_2018','ov_tcga','hgsoc_tcga_gdc')
  AND hugo_gene_symbol = 'BRCA1'
GROUP BY cancer_study_identifier, profile_type
ORDER BY cancer_study_identifier, profile_type"
}

◀ result
{"rows":[{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"cna","n":571},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"mrna_seq_fpkm","n":427},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"mrna_seq_fpkm_Zscores","n":427},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"mrna_seq_read_counts_Zscores","n":427},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"mrna_seq_tpm","n":427},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"mrna_seq_tpm_Zscores","n":427},{"cancer_study_identifier":"hgsoc_tcga_gdc","profile_type":"rna_seq_mrna","n":427},{"cancer_study_identifier":"ov_tcga","profile_type":"gistic","n":579},{"cancer_study_identifier":"ov_tcga","profile_type":"linear_CNA","n":579},{"cancer_study_identifier":"ov_tcga","profile_type":"methylation_hm27","n":592},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna","n":558},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna_U133","n":535},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna_U133_Zscores","n":535},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna_U133_all_sample_Zscores","n":535},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna_median_Zscores","n":558},{"cancer_study_identifier":"ov_tcga","profile_type":"mrna_median_all_sample_Zscores","n":558},{"cancer_study_identifier":"ov_tcga","profile_type":"protein_quantification","n":21},{"cancer_study_identifier":"ov_tcga","profile_type":"protein_quantification_zscores","n":174},{"cancer_study_identifier":"ov_tcga","profile_type":"rna_seq_v2_mrna","n":307},{"cancer_study_identifier":"ov_tcga","profile_type":"rna_seq_v2_mrna_median_Zscores","n":307},{"cancer_study_identifier":"ov_tcga","profile_type":"rna_seq_v2_mrna_median_all_sample_Zscores","n":307},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","profile_type":"gistic","n":572},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","profile_type":"log2CNA","n":572},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","profile_type":"rna_seq_v2_mrna","n":300},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","profile_type":"rna_seq_v2_mrna_median_Zscores","n":300},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","profile_type":"rna_seq_v2_mrna_median_all_sample_Zscores","n":300},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"gistic","n":489},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"linear_CNA","n":481},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"methylation_hm27","n":489},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"mrna","n":489},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"mrna_median_Zscores","n":489},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"mrna_median_all_sample_Zscores","n":489},{"cancer_study_identifier":"ov_tcga_pub","profile_type":"mrna_merged_median_Zscores","n":489}]}

▶ clickhouse_run_select_query
{
 "query": "WITH meth AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS v
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga'
      AND profile_type = 'methylation_hm27'
      AND hugo_gene_symbol = 'BRCA1'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
),
expr AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS v
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga'
      AND profile_type = 'mrna'
      AND hugo_gene_symbol = 'BRCA1'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
)
SELECT rankCorr(meth.v, expr.v) AS spearman_correlation,
       count() AS num_samples
FROM meth INNER JOIN expr USING (sample_unique_id)"
}

◀ result
{"rows":[{"spearman_correlation":-0.40336141757343147,"num_samples":550}]}

▶ clickhouse_run_select_query
{
 "query": "WITH meth AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS v
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga'
      AND profile_type = 'methylation_hm27'
      AND hugo_gene_symbol = 'BRCA1'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
),
expr AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS v
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga'
      AND profile_type = 'rna_seq_v2_mrna'
      AND hugo_gene_symbol = 'BRCA1'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
)
SELECT rankCorr(meth.v, expr.v) AS spearman_correlation,
       count() AS num_samples
FROM meth INNER JOIN expr USING (sample_unique_id)"
}

◀ result
{"rows":[{"spearman_correlation":-0.4383424829879454,"num_samples":298}]}

▶ resolve_and_route
{
 "studyIds": [
  "ov_tcga"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"ov_tcga","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Firehose Legacy)","sampleCount":617,"studyViewUrl":"https://www.cbioportal.org/study?id=ov_tcga","metadata":{"clinicalAttributeIds":["AGE","AJCC_PATHOLOGIC_TUMOR_STAGE","AJCC_STAGING_EDITION","CANCER_TYPE","CANCER_TYPE_DETAILED","CLINICAL_STAGE","CLIN_M_STAGE","CLIN_N_STAGE","CLIN_T_STAGE","DAYS_TO_COLLECTION","DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS","DAYS_TO_PATIENT_PROGRESSION_FREE","DAYS_TO_SPECIMEN_COLLECTION","DAYS_TO_TUMOR_PROGRESSION","DFS_MONTHS","DFS_STATUS","DISEASE_CODE","ECOG_SCORE","ETHNICITY","EXTRANODAL_INVOLVEMENT","FORM_COMPLETION_DATE","FRACTION_GENOME_ALTERED","GRADE","HISTOLOGICAL_DIAGNOSIS","HISTORY_NEOADJUVANT_TRTYN","HISTORY_OTHER_MALIGNANCY","ICD_10","ICD_O_3_HISTOLOGY","ICD_O_3_SITE","INFORMED_CONSENT_VERIFIED","INITIAL_PATHOLOGIC_DX_YEAR","IS_FFPE","JEWISH_RELIGION_HERITAGE_INDICATOR","KARNOFSKY_PERFORMANCE_SCORE","LONGEST_DIMENSION","LYMPHOVASCULAR_INVASION_INDICATOR","METHOD_OF_INITIAL_SAMPLE_PROCUREMENT","METHOD_OF_INITIAL_SAMPLE_PROCUREMENT_OTHER","METHOD_OF_SAMPLE_PROCUREMENT","MUTATION_COUNT","NEW_TUMOR_EVENT_AFTER_INITIAL_TREATMENT","OCT_EMBEDDED","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER_METHOD_OF_SAMPLE_PROCUREMENT","OTHER_PATIENT_ID","OTHER_SAMPLE_ID","PATHOLOGY_REPORT_FILE_NAME","PATHOLOGY_REPORT_UUID","PATH_M_STAGE","PATH_N_STAGE","PATH_T_STAGE","PERFORMANCE_STATUS_TIMING","PHARMACEUTICAL_TX_ADJUVANT","PRIMARY_SITE","PROJECT_CODE","PROSPECTIVE_COLLECTION","RACE","RADIATION_TREATMENT_ADJUVANT","RESIDUAL_TUMOR","RETROSPECTIVE_COLLECTION","SAMPLE_COUNT","SAMPLE_INITIAL_WEIGHT","SAMPLE_TYPE","SAMPLE_TYPE_ID","SEX","SHORTEST_DIMENSION","SOMATIC_STATUS","SPECIMEN_CURRENT_WEIGHT","SPECIMEN_FREEZING_METHOD","SPECIMEN_SECOND_LONGEST_DIMENSION","STAGE_OTHER","TIME_BETWEEN_CLAMPING_AND_FREEZING","TIME_BETWEEN_EXCISION_AND_FREEZING","TISSUE_SOURCE_SITE","TMB_NONSYNONYMOUS","TREATMENT_OUTCOME_FIRST_COURSE","TUMOR_STATUS","TUMOR_TISSUE_SITE","VASCULAR_INVASION_INDICATOR","VIAL_NUMBER"],"molecularProfileIds":["ov_tcga_gistic","ov_tcga_linear_CNA","ov_tcga_methylation_hm27","ov_tcga_mrna","ov_tcga_mrna_U133","ov_tcga_mrna_U133_Zscores","ov_tcga_mrna_U133_all_sample_Zscores","ov_tcga_mrna_median_Zscores","ov_tcga_mrna_median_all_sample_Zscores","ov_tcga_mutations","ov_tcga_protein_quantification","ov_tcga_protein_quantification_zscores","ov_tcga_rna_seq_v2_mrna","ov_tcga_rna_seq_v2_mrna_median_Zscores","ov_tcga_rna_seq_v2_mrna_median_all_sample_Zscores","ov_tcga_rppa","ov_tcga_rppa_Zscores"],"genericAssayProfiles":["ov_tcga_phosphoprotein_quantification"],"heatmapProfileIds":["ov_tcga_methylation_hm27","ov_tcga_mrna_U133_Zscores","ov_tcga_mrna_U133_all_sample_Zscores","ov_tcga_mrna_median_Zscores","ov_tcga_mrna_median_all_sample_Zscores","ov_tcga_protein_quantification_zscores","ov_tcga_rna_seq_v2_mrna_medi … (256 more chars)

▶ navigate_to_results_view
{
 "studyIds": [
  "ov_tcga"
 ],
 "genes": [
  "BRCA1"
 ],
 "tab": "plots",
 "profileFilter": "mrna,methylation_hm27",
 "plotsHorzSelection": {
  "dataType": "methylation_hm27",
  "selectedGeneOption": "BRCA1"
 },
 "plotsVertSelection": {
  "dataType": "mrna",
  "selectedGeneOption": "BRCA1"
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga&gene_list=BRCA1&case_set_id=ov_tcga_all&profileFilter=mrna%2Cmethylation_hm27&plots_horz_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22methylation_hm27%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22mrna%22%7D","url":"https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga&gene_list=BRCA1&case_set_id=ov_tcga_all&profileFilter=mrna%2Cmethylation_hm27&plots_horz_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22methylation_hm27%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22mrna%22%7D","data":{"studyIds":["ov_tcga"],"studies":[{"studyId":"ov_tcga","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Firehose Legacy)","sampleCount":617}],"genes":["BRCA1"],"caseSetId":"ov_tcga_all","pageDescription":"Scatter/box plots: BRCA1 mrna (y-axis) by BRCA1 methylation_hm27 (x-axis)."}}

═ answer (success)
## Yes — BRCA1 methylation is inversely correlated with BRCA1 mRNA expression in this cohort

Using the **Ovarian Serous Cystadenocarcinoma (TCGA, Firehose Legacy)** study (`ov_tcga`, 617 samples), which has paired Illumina HM27 methylation and mRNA expression data:

| Expression platform | Spearman correlation (methylation vs. mRNA) | Paired samples |
|---|---|---|
| Microarray (`mrna`) | **−0.40** | 550 |
| RNA-seq (RSEM, `rna_seq_v2_mrna`) | **−0.44** | 298 |

Both independent expression platforms show a moderate, consistent **negative** correlation — i.e., samples with higher BRCA1 promoter methylation tend to have lower BRCA1 mRNA levels, and vice versa. This is directionally consistent with the general epigenetic principle that promoter hypermethylation silences transcription, though a Spearman coefficient of ~−0.4 indicates a moderate (not perfect) relationship — other factors (mutation, copy number, regulatory variation) also contribute to BRCA1 expression variance in this cohort.

Note: this is a descriptive correlation from the database, not a hypothesis test — no p-value is reported here. If you want a formal significance test, you can reproduce this in R/Python from the same paired values, or inspect the interactive scatter plot below.

[View BRCA1 methylation vs. mRNA expression scatter plot](https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga&gene_list=BRCA1&case_set_id=ov_tcga_all&profileFilter=mrna%2Cmethylation_hm27&plots_horz_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22methylation_hm27%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%22672%22%2C%22dataType%22%3A%22mrna%22%7D)

This plot shows the full point cloud (BRCA1 methylation on the x-axis vs. BRCA1 mRNA on the y-axis) for all 617 samples in the study, letting you inspect the relationship directly, including outliers and any bimodal methylation pattern typical of BRCA1 promoter hypermethylation in a subset of high-grade serous ovarian tumors.