Q (sonnet): Do ovarian cancer patients with BRCA1 or BRCA2 alterations have significantly different overall survival compared to wild-type patients?

▶ read_guide
{
 "uri": "cbioportal://statistical-tests-guide"
}

▶ list_studies
{
 "search": "ovarian"
}

◀ result
Statistical Test Selection Guide
================================

Purpose
-------
This guide ensures the correct statistical test is selected before performing any group comparison, matching cBioPortal's own Group Comparison defaults.

HARD RULES — NEVER FABRICATE A STATISTIC
----------------------------------------
ClickHouse cannot run statistical tests. The agent therefore must NEVER produce a derived statistic that is not a literal column value from a SQL result. Specifically:

1. **Never invent a p-value.** Not "p < 0.001", not "p ≈ 0.05", not any p-value. If the user asks "what is the p-value?", the answer is *"I can't compute that — here is the 2x2 contingency table (or group statistics). Run it in cBioPortal's Group Comparison tab, in R with `fisher.test(...)` / `wilcox.test(...)`, or in Python with `scipy.stats.fisher_exact(...)` / `mannwhitneyu(...)`."*
2. **Never claim mutual exclusivity (or co-occurrence) from a contingency table alone.** A 2x2 table is not a test. The shape "altered/not altered × group A/group B" needs Fisher's exact + a defined direction (odds ratio < 1 with significant p). Without that test, the agent presents the table and stops. Descriptive phrasing is also a claim: "largely/mostly mutually exclusive", "rarely co-occur", "tend to co-occur" are forbidden without the test — point to cBioPortal's Mutual Exclusivity tab instead.
3. **Never report a "median" that came from `AVG(...)` or any non-median aggregate.** "Median" and "mean" are different statistics; for skewed clinical distributions (especially survival) they differ substantially. Use ClickHouse's `quantile(0.5)(...)` for actual median, and label arithmetic averages as "mean", never "median".
4. **Never report a hazard ratio, odds ratio, risk ratio, or relative risk** that wasn't computed by an external tool. These require regression / model fitting that ClickHouse does not do.
5. **Never report median overall survival from `AVG(OS_MONTHS)` or even `quantile(0.5)(OS_MONTHS)`.** Median OS requires Kaplan-Meier estimation, which handles censoring (`OS_STATUS = 0:LIVING` means the event hasn't happened yet). Naive medians/means over `OS_MONTHS` ignore censoring and are systematically wrong. The correct handoff: return the raw `(OS_MONTHS, OS_STATUS)` pairs (or descriptive counts: N events, N censored, follow-up range) and tell the user to run KM in R (`survival::survfit`) or Python (`lifelines.KaplanMeierFitter`), or use cBioPortal's Survival comparison.

If asked to do any of (1)–(5), respond with the appropriate handoff template from the "Approved Response Templates" section below — do not produce the number.

Ambiguous-Term Clarification (before any analysis)
--------------------------------------------------
If the user's question uses an ambiguous term, ask before computing anything. Examples:

- **"aggressive"** → could mean shorter overall survival, higher metastasis rate, higher grade/stage, higher TMB, or specific molecular features. Ask which definit … (9984 more chars)

◀ result
{"result":[{"cancer_study_identifier":"msk_met_2021","name":"MSK MetTropism (MSK, Cell 2021)","type_of_cancer_id":"mixed","sample_count":25775,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=msk_met_2021"},{"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":"ovary_geomx_gray_foundation_2024","name":"Ovarian Cancer (Gray Foundation, Cancer Discov 2024)","type_of_cancer_id":"ovary","sample_count":567,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovary_geomx_gray_foundation_2024"},{"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":"lgsoc_mapk_msk_2022","name":"Low-Grade Serous Ovarian Cancer (MSK, Clin Cancer Res 2022)","type_of_cancer_id":"lgsoc","sample_count":119,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=lgsoc_mapk_msk_2022"},{"cancer_study_identifier":"ovary_cptac_gdc","name":"Ovarian Cancer (CPTAC GDC, 2025)","type_of_cancer_id":"ovary","sample_count":112,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovary_cptac_gdc"},{"cancer_study_identifier":"msk_spectrum_tme_2022","name":"Ovarian Cancer - MSK SPECTRUM (MSK, Nature 2022)","type_of_cancer_id":"ovary","sample_count":82,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=msk_spectrum_tme_2022"},{"cancer_study_identifier":"hgsoc_msk_2021","name":"High-Grade Serous Ovarian Cancer (MSK, NPJ Genome Med 2021)","type_of_cancer_id":"hgsoc","sample_count":45,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=hgsoc_msk_2021"},{"cancer_study_identifier":"ucec_msk_2024","name":"Endometrial and Ovarian Cancer (MSK, Nature Medicine 2024)","type_of_cancer_id":"mixed","sample_count":33,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ucec_msk_2024"},{"cancer_study_identifier":"ovarian_msk_2025","name":"Serous Ovarian Cancer (MSK, 2025)","type_of_cancer_id":"ovary","sample_count":31,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovarian_msk_2025"},{"cancer_study_identifier":"mixed_msk_tcga_2021","name":"RAD51B Associated Mixed Cancers (MSK, N … (162 more chars)

▶ get_study_guide
{
 "study_id": "ov_tcga_pan_can_atlas_2018"
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
# Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)

**Study ID:** `ov_tcga_pan_can_atlas_2018`

See `_tcga_pancan_template.md` for common TCGA clinical attributes.

## Study-Specific Attributes

### Histology
| Attribute | Description | Values (samples) |
|-----------|-------------|--------|
| `GRADE` | Histologic grade | G3 400, G2 65, GX 7, G1 5, GB 2, G4 1, blank 105 |
| `CANCER_TYPE_DETAILED` | Histology | Serous Ovarian Cancer (all 585) |

### Not available in this study
- **Platinum sensitivity and residual disease**: no treatment-response or surgical-outcome attributes. Survival (`OS_*`, `PFS_*`, `DFS_*`, `DSS_*`) is the only outcome data.
- **BRCA / HRD status**: no clinical status attributes. Derive BRCA1/BRCA2 status from mutation (somatic calls only) and CNA data; there is no HRD score.
- `AJCC_PATHOLOGIC_TUMOR_STAGE` is blank for all samples. `SUBTYPE` is `OV` (177) or blank (408) and carries no molecular subtype.

## Key Genes
| Gene | Frequency | Notes |
|------|-----------|-------|
| TP53 | ~96% | Near-universal in high-grade serous |
| BRCA1 | ~10% germline | PARP inhibitor sensitivity |
| BRCA2 | ~6% germline | PARP inhibitor sensitivity |
| NF1 | ~4% | RAS pathway |
| RB1 | ~2% | Cell cycle |
| CDK12 | ~3% | DNA repair |

## Notes
- High-grade serous ovarian cancer (HGSOC) is genomically distinct from other ovarian subtypes
- TP53 is mutated in virtually all HGSOC
- BRCA1/2 mutations (germline or somatic) predict PARP inhibitor response
- HRD score predicts platinum and PARP sensitivity even without BRCA mutation
- Copy number alterations more prominent than mutations (except TP53)


◀ result
{"columns":[{"name":"sample_unique_id","type":"String"},{"name":"hugo_gene_symbol","type":"String","comment":"HUGO gene symbol (e.g., TP53, KRAS, BRAF). Use for gene-specific queries."},{"name":"entrez_gene_id","type":"Int32"},{"name":"gene_panel_stable_id","type":"LowCardinality(String)"},{"name":"cancer_study_identifier","type":"LowCardinality(String)"},{"name":"genetic_profile_stable_id","type":"LowCardinality(String)"},{"name":"variant_type","type":"LowCardinality(String)","comment":"Type of genomic event: \"mutation\" for SNVs/indels, \"cna\" for copy number alterations, \"structural_variant\" for SVs. Always filter by this."},{"name":"mutation_variant","type":"String","comment":"Protein change notation (e.g., p.V600E, p.R175H). Use for specific variant queries. \"NA\" for non-mutation events."},{"name":"mutation_type","type":"LowCardinality(String)"},{"name":"mutation_status","type":"LowCardinality(String)","comment":"For mutations: Somatic, Germline, UNKNOWN, or UNCALLED. Filter mutation_status != \"UNCALLED\" to exclude uncertain calls. Include all other statuses."},{"name":"driver_filter","type":"LowCardinality(String)"},{"name":"driver_filter_annotation","type":"String"},{"name":"driver_tiers_filter","type":"LowCardinality(String)"},{"name":"driver_tiers_filter_annotation","type":"String"},{"name":"cna_alteration","type":"Nullable(Int8)","comment":"Copy number alteration: only 2 = amplification (AMP) and -2 = deep deletion (HOMDEL) are stored. Shallow deletion (-1), diploid (0) and gain (1) are not in this table; query genetic_alteration_derived WHERE profile_type = 'gistic' (alteration_value is a String, e.g. '-1'). NULL for non-CNA events."},{"name":"cna_cytoband","type":"String"},{"name":"sv_event_info","type":"String"},{"name":"patient_unique_id","type":"String"},{"name":"off_panel","type":"Bool","comment":"Boolean: 1 = mutation outside gene panel coverage (off-panel), 0 = within panel (on-panel). Filter off_panel = 0 for reliable frequency calculations."}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH altered_patients AS (
    SELECT DISTINCT patient_unique_id
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND hugo_gene_symbol IN ('BRCA1','BRCA2')
      AND (
        (variant_type = 'mutation' AND mutation_status != 'UNCALLED' AND off_panel = 0)
        OR (variant_type = 'cna' AND cna_alteration = -2)
      )
),
os_data AS (
    SELECT patient_unique_id,
           maxIf(attribute_value, attribute_name = 'OS_MONTHS') AS os_months,
           maxIf(attribute_value, attribute_name = 'OS_STATUS') AS os_status
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND attribute_name IN ('OS_MONTHS','OS_STATUS')
    GROUP BY patient_unique_id
)
SELECT
    CASE WHEN a.patient_unique_id IS NOT NULL THEN 'BRCA1/2 altered' ELSE 'Wild-type' END AS group_name,
    count(*) AS n_patients,
    countIf(o.os_status = '1:DECEASED') AS n_events,
    countIf(o.os_status = '0:LIVING') AS n_censored,
    min(toFloat64OrNull(o.os_months)) AS min_followup,
    max(toFloat64OrNull(o.os_months)) AS max_followup
FROM os_data o
LEFT JOIN altered_patients a ON o.patient_unique_id = a.patient_unique_id
WHERE o.os_months != '' AND o.os_status != ''
GROUP BY group_name
"
}

◀ result
{"rows":[{"group_name":"BRCA1/2 altered","n_patients":571,"n_events":341,"n_censored":230,"min_followup":0.263010816,"max_followup":180.1952855}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH altered_patients AS (
    SELECT DISTINCT patient_unique_id
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND hugo_gene_symbol IN ('BRCA1','BRCA2')
      AND (
        (variant_type = 'mutation' AND mutation_status != 'UNCALLED' AND off_panel = 0)
        OR (variant_type = 'cna' AND cna_alteration = -2)
      )
),
os_data AS (
    SELECT patient_unique_id,
           maxIf(attribute_value, attribute_name = 'OS_MONTHS') AS os_months,
           maxIf(attribute_value, attribute_name = 'OS_STATUS') AS os_status
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND attribute_name IN ('OS_MONTHS','OS_STATUS')
    GROUP BY patient_unique_id
)
SELECT
    multiIf(a.patient_unique_id != '', 'BRCA1/2 altered', 'Wild-type') AS group_name,
    count(*) AS n_patients,
    countIf(o.os_status = '1:DECEASED') AS n_events,
    countIf(o.os_status = '0:LIVING') AS n_censored,
    min(toFloat64OrNull(o.os_months)) AS min_followup,
    max(toFloat64OrNull(o.os_months)) AS max_followup
FROM os_data o
LEFT JOIN altered_patients a ON o.patient_unique_id = a.patient_unique_id
WHERE o.os_months != '' AND o.os_status != ''
GROUP BY group_name
"
}

◀ result
{"rows":[{"group_name":"Wild-type","n_patients":528,"n_events":325,"n_censored":203,"min_followup":0.295887168,"max_followup":180.1952855},{"group_name":"BRCA1/2 altered","n_patients":43,"n_events":16,"n_censored":27,"min_followup":0.263010816,"max_followup":145.4449814}]}

▶ resolve_and_route
{
 "studyIds": [
  "ov_tcga_pan_can_atlas_2018"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","sampleCount":585,"studyViewUrl":"https://www.cbioportal.org/study?id=ov_tcga_pan_can_atlas_2018","metadata":{"clinicalAttributeIds":["AGE","AJCC_PATHOLOGIC_TUMOR_STAGE","AJCC_STAGING_EDITION","ANEUPLOIDY_SCORE","BUFFA_HYPOXIA_SCORE","CANCER_TYPE","CANCER_TYPE_ACRONYM","CANCER_TYPE_DETAILED","DAYS_LAST_FOLLOWUP","DAYS_TO_BIRTH","DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS","DFS_MONTHS","DFS_STATUS","DSS_MONTHS","DSS_STATUS","ETHNICITY","FORM_COMPLETION_DATE","FRACTION_GENOME_ALTERED","GENETIC_ANCESTRY_LABEL","GRADE","HISTORY_NEOADJUVANT_TRTYN","ICD_10","ICD_O_3_HISTOLOGY","ICD_O_3_SITE","INFORMED_CONSENT_VERIFIED","IN_PANCANPATHWAYS_FREEZE","MSI_SCORE_MANTIS","MSI_SENSOR_SCORE","MUTATION_COUNT","NEW_TUMOR_EVENT_AFTER_INITIAL_TREATMENT","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER_PATIENT_ID","PATH_M_STAGE","PATH_N_STAGE","PATH_T_STAGE","PERSON_NEOPLASM_CANCER_STATUS","PFS_MONTHS","PFS_STATUS","PRIMARY_LYMPH_NODE_PRESENTATION_ASSESSMENT","PRIOR_DX","RACE","RADIATION_THERAPY","RAGNUM_HYPOXIA_SCORE","SAMPLE_COUNT","SAMPLE_TYPE","SEX","SOMATIC_STATUS","SUBTYPE","TBL_SCORE","TISSUE_PROSPECTIVE_COLLECTION_INDICATOR","TISSUE_RETROSPECTIVE_COLLECTION_INDICATOR","TISSUE_SOURCE_SITE","TISSUE_SOURCE_SITE_CODE","TMB_NONSYNONYMOUS","TUMOR_TISSUE_SITE","TUMOR_TYPE","WEIGHT","WINTER_HYPOXIA_SCORE"],"molecularProfileIds":["ov_tcga_pan_can_atlas_2018_gistic","ov_tcga_pan_can_atlas_2018_log2CNA","ov_tcga_pan_can_atlas_2018_mutations","ov_tcga_pan_can_atlas_2018_protein_quantification","ov_tcga_pan_can_atlas_2018_protein_quantification_zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ov_tcga_pan_can_atlas_2018_rppa","ov_tcga_pan_can_atlas_2018_rppa_Zscores","ov_tcga_pan_can_atlas_2018_structural_variants"],"genericAssayProfiles":["ov_tcga_pan_can_atlas_2018_armlevel_cna","ov_tcga_pan_can_atlas_2018_genetic_ancestry","ov_tcga_pan_can_atlas_2018_methylation_hm27_hm450_merge","ov_tcga_pan_can_atlas_2018_methylation_hm450","ov_tcga_pan_can_atlas_2018_phosphoprotein_quantification"],"heatmapProfileIds":["ov_tcga_pan_can_atlas_2018_protein_quantification_zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ov_tcga_pan_can_atlas_2018_rppa_Zscores"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations","mrna","protein","generic_assay_armlevel_cna","generic_assay_genetic_ancestry","generic_assay_methylation","generic_assay_phosphosite_quantification"]}}]}}

▶ navigate_to_results_view
{
 "studyIds": [
  "ov_tcga_pan_can_atlas_2018"
 ],
 "genes": [
  "BRCA1: MUT HOMDEL",
  "BRCA2: MUT HOMDEL"
 ],
 "tab": "comparison/survival"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/comparison/survival?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=BRCA1%3A+MUT+HOMDEL%0ABRCA2%3A+MUT+HOMDEL&case_set_id=ov_tcga_pan_can_atlas_2018_all","url":"https://www.cbioportal.org/results/comparison/survival?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=BRCA1%3A+MUT+HOMDEL%0ABRCA2%3A+MUT+HOMDEL&case_set_id=ov_tcga_pan_can_atlas_2018_all","data":{"studyIds":["ov_tcga_pan_can_atlas_2018"],"studies":[{"studyId":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","sampleCount":585}],"genes":["BRCA1","BRCA2"],"caseSetId":"ov_tcga_pan_can_atlas_2018_all","pageDescription":"Kaplan-Meier survival analysis comparing groups defined by query genes."}}

═ answer (success)
## Summary

**Cohort:** Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas) — `ov_tcga_pan_can_atlas_2018`, 585 samples.

I identified patients with BRCA1/BRCA2 alterations (somatic/germline mutations, on-panel, plus deep deletions) vs. wild-type, using patient-level overall survival data:

| Group | N patients | Events (deceased) | Censored (living) | Follow-up range (months) |
|---|---|---|---|---|
| **BRCA1/2 altered** | 43 | 16 | 27 | 0.26 – 145.4 |
| **Wild-type** | 528 | 325 | 203 | 0.30 – 180.2 |

**On statistical significance:** I cannot compute a p-value or median survival directly in ClickHouse. Overall survival is time-to-event (censored) data, so the correct approach is Kaplan-Meier estimation with a log-rank test — not a raw comparison of `OS_MONTHS`. Note only ~37% of the BRCA-altered group has an event so far, meaning the KM median in that group is likely **not reached**.

To get the actual KM curves and log-rank p-value, use cBioPortal's built-in comparison tool:

[View BRCA1/BRCA2 Altered vs. Unaltered — Survival Comparison](https://www.cbioportal.org/results/comparison/survival?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=BRCA1%3A+MUT+HOMDEL%0ABRCA2%3A+MUT+HOMDEL&case_set_id=ov_tcga_pan_can_atlas_2018_all)

This page will show the Kaplan-Meier plot for Altered vs. Unaltered groups with the log-rank p-value computed automatically. Note: cBioPortal's default "Altered" group includes deep deletions and mutations as configured (I included `HOMDEL` since biallelic BRCA loss is functionally relevant to HR-deficiency, alongside mutations) — you can toggle alteration types on that page if you want mutations only.