Q (sonnet): what are the most common events in her2- breast cancer?

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

▶ list_studies
{
 "search": "breast"
}

◀ 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)

◀ 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":"breast_msk_2026","name":"CCNE1 Amplifications in Breast Cancer (MSK, 2026)","type_of_cancer_id":"breast","sample_count":6318,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2026"},{"cancer_study_identifier":"breast_msk_2025","name":"Breast Cancer (MSK, Nat Genet 2025)","type_of_cancer_id":"brca","sample_count":3879,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2025"},{"cancer_study_identifier":"brca_metabric","name":"Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)","type_of_cancer_id":"brca","sample_count":2509,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_metabric"},{"cancer_study_identifier":"breast_msk_2018","name":"Breast Cancer (MSK, Cancer Cell 2018)","type_of_cancer_id":"breast","sample_count":1918,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2018"},{"cancer_study_identifier":"breast_ink4_msk_2021","name":"Metastatic Breast Cancer (MSK, Cancer Discovery 2022)","type_of_cancer_id":"breast","sample_count":1365,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_ink4_msk_2021"},{"cancer_study_identifier":"brca_tcga","name":"Breast Invasive Carcinoma (TCGA, Firehose Legacy)","type_of_cancer_id":"brca","sample_count":1108,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga"},{"cancer_study_identifier":"brca_tcga_gdc","name":"Invasive Breast Carcinoma (TCGA GDC, 2025)","type_of_cancer_id":"brca","sample_count":1102,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_gdc"},{"cancer_study_identifier":"brca_tcga_pan_can_atlas_2018","name":"Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"brca","sample_count":1084,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"brca_tcga_pub","name":"Breast Invasive Carcinoma (TCGA, Nature 2012)","type_of_cancer_id":"brca","sample_count":825,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pub"},{"cancer_study_identifier":"brca_tcga_pub2015","name":"Breast Invasive Carcinoma (TCGA, Cell 2015)","type_of_cancer_id":"brca","sample_count":818,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pub2015"},{"cancer_study_identifier":"brca_msk_2025","name":"Breast Carcinoma (MSK, NPJ Precis Oncol 2025)","type_of_cancer_id":"brca","sample_count":527,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_msk_2025"},{"cancer_study_identifier":"brca_mbcproject_2022","name":"The Metastatic Breast Cancer Project (Provisional, December 2021)","type_of_cancer_id":"brca","sample_count":379,"has_gu … (1846 more chars)

▶ get_study_guide
{
 "study_id": "brca_tcga_pan_can_atlas_2018"
}

▶ clickhouse_list_table_columns
{
 "table": "clinical_data_derived"
}

◀ result
# Breast Invasive Carcinoma (TCGA, PanCancer Atlas)

**Study ID:** `brca_tcga_pan_can_atlas_2018`

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

## Study-Specific Attributes

### Molecular Subtypes
| Attribute | Description | Values (patients) |
|-----------|-------------|--------|
| `SUBTYPE` | PAM50 molecular subtype | `BRCA_LumA` 499, `BRCA_LumB` 197, `BRCA_Basal` 171, `BRCA_Her2` 78, `BRCA_Normal` 36, blank 103 |

### Histology
| Attribute | Description | Values (samples) |
|-----------|-------------|--------|
| `CANCER_TYPE_DETAILED` | Histological type | Breast Invasive Ductal Carcinoma 780, Breast Invasive Lobular Carcinoma 201, Breast Invasive Carcinoma (NOS) 77, Breast Invasive Mixed Mucinous Carcinoma 17, Metaplastic Breast Cancer 8, Invasive Breast Carcinoma 1 |

### Not available in this study
- **ER / PR / HER2 receptor status and triple-negative status**: no clinical attribute; say it is not available here. Do not infer receptor status from `SUBTYPE`: PAM50 is an expression-based classification, not IHC/FISH. If the user accepts an expression-based proxy, `BRCA_Basal` (≈ triple-negative) or `BRCA_Her2` can be offered, labelled as PAM50. ERBB2 amplification is available from CNA data.
- `GRADE` is blank for all samples.

## Key Genes
- **TP53**: Most frequently mutated (~30%)
- **PIK3CA**: Common in ER+ tumors (~35%)
- **CDH1**: Enriched in lobular carcinoma
- **GATA3**: Luminal marker
- **ERBB2**: HER2 amplification target

## Notes
- Molecular subtypes (PAM50) correlate strongly with clinical behavior
- Lobular vs ductal distinction has different mutation profiles


◀ result
{"columns":[{"name":"internal_id","type":"Int32"},{"name":"sample_unique_id","type":"String","comment":"Globally unique sample ID: cancer_study_identifier + \"_\" + sample.stable_id. Empty for patient-level attributes. Use this for sample filtering and joins."},{"name":"patient_unique_id","type":"String","comment":"Globally unique patient ID: cancer_study_identifier + \"_\" + patient.stable_id. Present for both sample and patient-level attributes."},{"name":"attribute_name","type":"LowCardinality(String)","comment":"Clinical attribute name (e.g., SAMPLE_TYPE, CANCER_TYPE, AGE, OS_MONTHS). Use with attribute_value for filtering. AGE may be floored or capped for de-identification (e.g. all children recorded as 18, or everyone 89+ recorded as 89 or 90): before age statistics check for a pile-up at the min/max, and if present compute age from DAYS_TO_BIRTH (-days / 365.25)."},{"name":"attribute_value","type":"String","comment":"Value of the clinical attribute (String). For SAMPLE_TYPE: Primary, Metastasis, Local Recurrence, Unknown. Missing values are empty strings, so use toFloat64OrNull(attribute_value) for numeric comparisons — CAST fails on them."},{"name":"cancer_study_identifier","type":"LowCardinality(String)"},{"name":"type","type":"LowCardinality(String)","comment":"Data level: \"sample\" for sample-level attributes (e.g., SAMPLE_TYPE), \"patient\" for patient-level attributes (e.g., AGE, OS_MONTHS)."}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT attribute_name, count(DISTINCT patient_unique_id) AS n
FROM clinical_data_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND (lower(attribute_name) LIKE '%her2%' OR lower(attribute_name) LIKE '%er_%' OR lower(attribute_name) LIKE '%receptor%' OR lower(attribute_name) LIKE '%hormone%')
GROUP BY attribute_name"
}

◀ result
{"rows":[{"attribute_name":"HER2_STATUS","n":2509},{"attribute_name":"ER_STATUS","n":2509},{"attribute_name":"LATERALITY","n":2509},{"attribute_name":"CANCER_TYPE","n":2509},{"attribute_name":"HER2_SNP6","n":2509},{"attribute_name":"BREAST_SURGERY","n":2509},{"attribute_name":"INFERRED_MENOPAUSAL_STATE","n":2509},{"attribute_name":"CHEMOTHERAPY","n":2509},{"attribute_name":"RADIO_THERAPY","n":2509},{"attribute_name":"HORMONE_THERAPY","n":2509},{"attribute_name":"CANCER_TYPE_DETAILED","n":2509},{"attribute_name":"ER_IHC","n":2509}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT attribute_name, count(DISTINCT patient_unique_id) AS n
FROM clinical_data_derived
WHERE cancer_study_identifier = 'brca_msk_erbb2_2026'
GROUP BY attribute_name
ORDER BY attribute_name"
}

◀ result
{"rows":[{"attribute_name":"CANCER_TYPE","n":272},{"attribute_name":"CANCER_TYPE_DETAILED","n":272},{"attribute_name":"CVR_TMB_SCORE","n":272},{"attribute_name":"ETHNICITY","n":272},{"attribute_name":"FRACTION_GENOME_ALTERED","n":272},{"attribute_name":"GENDER","n":272},{"attribute_name":"GENE_PANEL","n":272},{"attribute_name":"INSTITUTE","n":272},{"attribute_name":"METASTATIC_SITE","n":272},{"attribute_name":"MSI_SCORE","n":272},{"attribute_name":"MSI_TYPE","n":272},{"attribute_name":"MUTATION_COUNT","n":272},{"attribute_name":"ONCOTREE_CODE","n":272},{"attribute_name":"OS_MONTHS","n":272},{"attribute_name":"OS_STATUS","n":272},{"attribute_name":"PRIMARY_SITE","n":272},{"attribute_name":"PRIOR_MED_TO_MSK","n":272},{"attribute_name":"RACE","n":272},{"attribute_name":"SAMPLE_CLASS","n":272},{"attribute_name":"SAMPLE_COUNT","n":272},{"attribute_name":"SAMPLE_TYPE","n":272},{"attribute_name":"SMOKING_PREDICTIONS_3_CLASSES","n":272},{"attribute_name":"SOMATIC_STATUS","n":272},{"attribute_name":"STAGE_HIGHEST_RECORDED","n":272},{"attribute_name":"TUMOR_PURITY","n":272},{"attribute_name":"YOST_INDEX_IMPUTED_MEDIAN","n":272}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT attribute_value, count(DISTINCT patient_unique_id) AS n
FROM clinical_data_derived
WHERE cancer_study_identifier = 'brca_metabric' AND attribute_name = 'HER2_STATUS'
GROUP BY attribute_value ORDER BY n DESC"
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
{"rows":[{"attribute_value":"Negative","n":1733},{"n":529},{"attribute_value":"Positive","n":247}]}

◀ 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 her2neg AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'brca_metabric'
      AND attribute_name = 'HER2_STATUS'
      AND attribute_value = 'Negative'
)
SELECT hugo_gene_symbol,
       variant_type,
       COUNT(DISTINCT sample_unique_id) AS altered_samples,
       COUNT(*) AS events
FROM genomic_event_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND sample_unique_id IN (SELECT sample_unique_id FROM her2neg)
  AND (
      (variant_type = 'mutation' AND mutation_status != 'UNCALLED' AND off_panel = 0)
      OR (variant_type = 'cna' AND cna_alteration IN (2,-2))
  )
GROUP BY hugo_gene_symbol, variant_type
ORDER BY altered_samples DESC
LIMIT 25
"
}

◀ result
{"rows":[{"hugo_gene_symbol":"PIK3CA","variant_type":"mutation","altered_samples":717,"events":839},{"hugo_gene_symbol":"TP53","variant_type":"mutation","altered_samples":498,"events":516},{"hugo_gene_symbol":"TRPS1","variant_type":"cna","altered_samples":436,"events":436},{"hugo_gene_symbol":"MIR205HG","variant_type":"cna","altered_samples":430,"events":430},{"hugo_gene_symbol":"SIPA1L2","variant_type":"cna","altered_samples":427,"events":427},{"hugo_gene_symbol":"PLEKHA6","variant_type":"cna","altered_samples":426,"events":426},{"hugo_gene_symbol":"LRRN2","variant_type":"cna","altered_samples":425,"events":425},{"hugo_gene_symbol":"MDM4","variant_type":"cna","altered_samples":425,"events":425},{"hugo_gene_symbol":"PLXNA2","variant_type":"cna","altered_samples":423,"events":423},{"hugo_gene_symbol":"CAMK1G","variant_type":"cna","altered_samples":423,"events":423},{"hugo_gene_symbol":"PPP1R15B","variant_type":"cna","altered_samples":423,"events":423},{"hugo_gene_symbol":"KLHDC8A","variant_type":"cna","altered_samples":423,"events":423},{"hugo_gene_symbol":"LEMD1-AS1","variant_type":"cna","altered_samples":423,"events":423},{"hugo_gene_symbol":"ESRRG","variant_type":"cna","altered_samples":422,"events":422},{"hugo_gene_symbol":"LEMD1","variant_type":"cna","altered_samples":422,"events":422},{"hugo_gene_symbol":"CDK18","variant_type":"cna","altered_samples":422,"events":422},{"hugo_gene_symbol":"PIK3C2B","variant_type":"cna","altered_samples":422,"events":422},{"hugo_gene_symbol":"LAMB3","variant_type":"cna","altered_samples":421,"events":421},{"hugo_gene_symbol":"SLC60A1","variant_type":"cna","altered_samples":421,"events":421},{"hugo_gene_symbol":"KISS1","variant_type":"cna","altered_samples":421,"events":421},{"hugo_gene_symbol":"NFASC","variant_type":"cna","altered_samples":421,"events":421},{"hugo_gene_symbol":"CD34","variant_type":"cna","altered_samples":421,"events":421},{"hugo_gene_symbol":"CD46","variant_type":"cna","altered_samples":420,"events":420},{"hugo_gene_symbol":"GOLT1A","variant_type":"cna","altered_samples":420,"events":420},{"hugo_gene_symbol":"NUCKS1","variant_type":"cna","altered_samples":420,"events":420}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT count(DISTINCT sample_unique_id) AS her2neg_samples
FROM clinical_data_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND attribute_name = 'HER2_STATUS'
  AND attribute_value = 'Negative'
"
}

◀ result
{"rows":[{"her2neg_samples":1733}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH her2neg AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'brca_metabric'
      AND attribute_name = 'HER2_STATUS'
      AND attribute_value = 'Negative'
)
SELECT hugo_gene_symbol, cna_cytoband, cna_alteration,
       COUNT(DISTINCT sample_unique_id) AS altered_samples
FROM genomic_event_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND sample_unique_id IN (SELECT sample_unique_id FROM her2neg)
  AND variant_type = 'cna' AND cna_alteration IN (2,-2)
GROUP BY hugo_gene_symbol, cna_cytoband, cna_alteration
ORDER BY altered_samples DESC
LIMIT 15
"
}

◀ result
{"rows":[{"hugo_gene_symbol":"TRPS1","cna_cytoband":"8q23.3","cna_alteration":2,"altered_samples":436},{"hugo_gene_symbol":"MIR205HG","cna_cytoband":"1q32.2","cna_alteration":2,"altered_samples":430},{"hugo_gene_symbol":"PLEKHA6","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":426},{"hugo_gene_symbol":"SIPA1L2","cna_cytoband":"1q42.2","cna_alteration":2,"altered_samples":426},{"hugo_gene_symbol":"LRRN2","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":425},{"hugo_gene_symbol":"MDM4","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":425},{"hugo_gene_symbol":"PPP1R15B","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":423},{"hugo_gene_symbol":"PLXNA2","cna_cytoband":"1q32.2","cna_alteration":2,"altered_samples":423},{"hugo_gene_symbol":"LEMD1-AS1","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":423},{"hugo_gene_symbol":"CAMK1G","cna_cytoband":"1q32.2","cna_alteration":2,"altered_samples":423},{"hugo_gene_symbol":"KLHDC8A","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":422},{"hugo_gene_symbol":"ESRRG","cna_cytoband":"1q41","cna_alteration":2,"altered_samples":422},{"hugo_gene_symbol":"CDK18","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":422},{"hugo_gene_symbol":"LEMD1","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":422},{"hugo_gene_symbol":"PIK3C2B","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":422}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT COUNT(DISTINCT stgp.sample_unique_id) AS profiled_mut
FROM sample_to_gene_panel_derived stgp
JOIN gene_panel gp ON stgp.gene_panel_id = gp.stable_id
JOIN gene_panel_list gpl ON gp.internal_id = gpl.internal_id
JOIN gene g ON gpl.gene_id = g.entrez_gene_id
WHERE stgp.alteration_type = 'MUTATION_EXTENDED'
  AND g.hugo_gene_symbol = 'PIK3CA'
  AND stgp.cancer_study_identifier = 'brca_metabric'
  AND stgp.sample_unique_id IN (
      SELECT DISTINCT sample_unique_id FROM clinical_data_derived
      WHERE cancer_study_identifier = 'brca_metabric' AND attribute_name = 'HER2_STATUS' AND attribute_value = 'Negative'
  )
"
}

◀ result
{"rows":[{"profiled_mut":1668}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT COUNT(DISTINCT stgp.sample_unique_id) AS profiled_mut
FROM sample_to_gene_panel_derived stgp
JOIN gene_panel gp ON stgp.gene_panel_id = gp.stable_id
JOIN gene_panel_list gpl ON gp.internal_id = gpl.internal_id
JOIN gene g ON gpl.gene_id = g.entrez_gene_id
WHERE stgp.alteration_type = 'MUTATION_EXTENDED'
  AND g.hugo_gene_symbol = 'TP53'
  AND stgp.cancer_study_identifier = 'brca_metabric'
  AND stgp.sample_unique_id IN (
      SELECT DISTINCT sample_unique_id FROM clinical_data_derived
      WHERE cancer_study_identifier = 'brca_metabric' AND attribute_name = 'HER2_STATUS' AND attribute_value = 'Negative'
  )
"
}

◀ result
{"rows":[{"profiled_mut":1668}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH her2neg AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'brca_metabric'
      AND attribute_name = 'HER2_STATUS'
      AND attribute_value = 'Negative'
)
SELECT hugo_gene_symbol, cna_cytoband, cna_alteration,
       COUNT(DISTINCT sample_unique_id) AS altered_samples
FROM genomic_event_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND sample_unique_id IN (SELECT sample_unique_id FROM her2neg)
  AND variant_type = 'cna' AND cna_alteration IN (2,-2)
  AND hugo_gene_symbol IN ('CCND1','MYC','ZNF703','FGFR1','MDM4','ERBB2','MCL1','RB1','PTEN','CDKN2A','TRPS1')
GROUP BY hugo_gene_symbol, cna_cytoband, cna_alteration
ORDER BY altered_samples DESC
"
}

◀ result
{"rows":[{"hugo_gene_symbol":"TRPS1","cna_cytoband":"8q23.3","cna_alteration":2,"altered_samples":436},{"hugo_gene_symbol":"MDM4","cna_cytoband":"1q32.1","cna_alteration":2,"altered_samples":425},{"hugo_gene_symbol":"MYC","cna_cytoband":"8q24.21","cna_alteration":2,"altered_samples":410},{"hugo_gene_symbol":"MCL1","cna_cytoband":"1q21.2","cna_alteration":2,"altered_samples":332},{"hugo_gene_symbol":"CCND1","cna_cytoband":"11q13.3","cna_alteration":2,"altered_samples":288},{"hugo_gene_symbol":"ZNF703","cna_cytoband":"8p11.23","cna_alteration":2,"altered_samples":253},{"hugo_gene_symbol":"FGFR1","cna_cytoband":"8p11.23","cna_alteration":2,"altered_samples":233},{"hugo_gene_symbol":"ERBB2","cna_cytoband":"17q12","cna_alteration":2,"altered_samples":63},{"hugo_gene_symbol":"CDKN2A","cna_cytoband":"9p21.3","cna_alteration":-2,"altered_samples":41},{"hugo_gene_symbol":"PTEN","cna_cytoband":"10q23.31","cna_alteration":-2,"altered_samples":40},{"hugo_gene_symbol":"CDKN2A","cna_cytoband":"9p21.3","cna_alteration":2,"altered_samples":25},{"hugo_gene_symbol":"RB1","cna_cytoband":"13q14.2","cna_alteration":-2,"altered_samples":12},{"hugo_gene_symbol":"PTEN","cna_cytoband":"10q23.31","cna_alteration":2,"altered_samples":10},{"hugo_gene_symbol":"RB1","cna_cytoband":"13q14.2","cna_alteration":2,"altered_samples":9},{"hugo_gene_symbol":"FGFR1","cna_cytoband":"8p11.23","cna_alteration":-2,"altered_samples":3},{"hugo_gene_symbol":"ZNF703","cna_cytoband":"8p11.23","cna_alteration":-2,"altered_samples":2}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH her2neg AS (
    SELECT DISTINCT sample_unique_id
    FROM clinical_data_derived
    WHERE cancer_study_identifier = 'brca_metabric'
      AND attribute_name = 'HER2_STATUS'
      AND attribute_value = 'Negative'
)
SELECT hugo_gene_symbol,
       COUNT(DISTINCT sample_unique_id) AS altered_samples,
       COUNT(*) AS events
FROM genomic_event_derived
WHERE cancer_study_identifier = 'brca_metabric'
  AND sample_unique_id IN (SELECT sample_unique_id FROM her2neg)
  AND variant_type = 'mutation' AND mutation_status != 'UNCALLED' AND off_panel = 0
GROUP BY hugo_gene_symbol
ORDER BY altered_samples DESC
LIMIT 10
"
}

◀ result
{"rows":[{"hugo_gene_symbol":"PIK3CA","altered_samples":717,"events":839},{"hugo_gene_symbol":"TP53","altered_samples":498,"events":516},{"hugo_gene_symbol":"MUC16","altered_samples":271,"events":339},{"hugo_gene_symbol":"AHNAK2","altered_samples":262,"events":356},{"hugo_gene_symbol":"GATA3","altered_samples":219,"events":227},{"hugo_gene_symbol":"KMT2C","altered_samples":210,"events":240},{"hugo_gene_symbol":"SYNE1","altered_samples":200,"events":233},{"hugo_gene_symbol":"MAP3K1","altered_samples":191,"events":273},{"hugo_gene_symbol":"CDH1","altered_samples":160,"events":166},{"hugo_gene_symbol":"AHNAK","altered_samples":153,"events":173}]}

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

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"brca_metabric","name":"Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)","sampleCount":2509,"studyViewUrl":"https://www.cbioportal.org/study?id=brca_metabric","metadata":{"clinicalAttributeIds":["AGE_AT_DIAGNOSIS","BREAST_SURGERY","CANCER_TYPE","CANCER_TYPE_DETAILED","CELLULARITY","CHEMOTHERAPY","CLAUDIN_SUBTYPE","COHORT","ER_IHC","ER_STATUS","GRADE","HER2_SNP6","HER2_STATUS","HISTOLOGICAL_SUBTYPE","HORMONE_THERAPY","INFERRED_MENOPAUSAL_STATE","INTCLUST","LATERALITY","LYMPH_NODES_EXAMINED_POSITIVE","MUTATION_COUNT","NPI","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","PR_STATUS","RADIO_THERAPY","RFS_MONTHS","RFS_STATUS","SAMPLE_COUNT","SAMPLE_TYPE","SEX","THREEGENE","TMB_NONSYNONYMOUS","TUMOR_SIZE","TUMOR_STAGE","VITAL_STATUS"],"molecularProfileIds":["brca_metabric_cna","brca_metabric_methylation_promoters_rrbs","brca_metabric_mrna","brca_metabric_mrna_median_all_sample_Zscores","brca_metabric_mutations"],"heatmapProfileIds":["brca_metabric_methylation_promoters_rrbs","brca_metabric_mrna_median_all_sample_Zscores"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations","mrna","dna_methylation"]}}]}}

▶ navigate_to_study_view
{
 "studyIds": [
  "brca_metabric"
 ],
 "filterJson": {
  "clinicalDataFilters": [
   {
    "attributeId": "HER2_STATUS",
    "values": [
     {
      "value": "Negative"
     }
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/study/summary?id=brca_metabric#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HER2_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Negative%22%7D%5D%7D%5D%7D","url":"https://www.cbioportal.org/study/summary?id=brca_metabric#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HER2_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Negative%22%7D%5D%7D%5D%7D","data":{"studyIds":["brca_metabric"],"studies":[{"studyId":"brca_metabric","name":"Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)","sampleCount":2509}],"tab":"summary","hasFilters":true,"hasPlotsConfig":false,"pageDescription":"Overview of all study data displayed as interactive charts summarizing available clinical and genomic data. Click within a chart to filter. Additional charts may be available in the Charts menu."}}

▶ navigate_to_results_view
{
 "studyIds": [
  "brca_metabric"
 ],
 "genes": [
  "PIK3CA",
  "TP53",
  "GATA3",
  "KMT2C",
  "MAP3K1",
  "CDH1",
  "MYC",
  "CCND1",
  "ZNF703",
  "FGFR1"
 ],
 "tab": "oncoprint",
 "studyViewFilter": {
  "clinicalDataFilters": [
   {
    "attributeId": "HER2_STATUS",
    "values": [
     {
      "value": "Negative"
     }
    ]
   }
  ]
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/oncoprint?session_id=6ab5d1bcc2115c492d884e27","url":"https://www.cbioportal.org/results/oncoprint?session_id=6ab5d1bcc2115c492d884e27","data":{"studyIds":["brca_metabric"],"studies":[{"studyId":"brca_metabric","name":"Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)","sampleCount":2509}],"genes":["PIK3CA","TP53","GATA3","KMT2C","MAP3K1","CDH1","MYC","CCND1","ZNF703","FGFR1"],"filteredSampleCount":1733,"caseSetId":"-1","sessionId":"6ab5d1bcc2115c492d884e27","studyViewUrl":"https://www.cbioportal.org/study?id=brca_metabric#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HER2_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Negative%22%7D%5D%7D%5D%7D","pageDescription":"Visual summary of alterations in queried genes across samples."}}

═ answer (success)
Both links are ready:

- **[Study View — HER2‑negative cohort (n=1,733)](https://www.cbioportal.org/study/summary?id=brca_metabric#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HER2_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Negative%22%7D%5D%7D%5D%7D)** — clinical/genomic overview with the HER2‑Negative filter applied.
- **[OncoPrint — top mutated & CNA genes in HER2‑negative samples](https://www.cbioportal.org/results/oncoprint?session_id=6ab5d1bcc2115c492d884e27)** — PIK3CA, TP53, GATA3, KMT2C, MAP3K1, CDH1, MYC, CCND1, ZNF703, FGFR1 across the 1,733 HER2‑negative samples.

Both links draw on the METABRIC cohort, chosen specifically because it has curated clinical HER2 status (IHC/FISH) — the TCGA PanCancer Atlas breast study, by contrast, does not carry a receptor-status field, so it couldn't answer this question.