Q (sonnet): in salivary cancer (adenoid cystic carcinoma), what are the expected drivers ? Classify them by actionability. What about BCOR mutations, either somatic or germline ?

▶ list_studies
{
 "search": "adenoid cystic"
}

▶ search_oncotree
{
 "search_term": "adenoid cystic carcinoma"
}

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

◀ result
{"result":[{"cancer_study_identifier":"acc_2019","name":"Adenoid Cystic Carcinoma Project (J Clin Invest 2019)","type_of_cancer_id":"acyc","sample_count":1049,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acc_2019"},{"cancer_study_identifier":"acyc_mda_2015","name":"Adenoid Cystic Carcinoma (MDA, Clin Cancer Res 2015)","type_of_cancer_id":"acyc","sample_count":102,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_mda_2015"},{"cancer_study_identifier":"acyc_mskcc_2013","name":"Adenoid Cystic Carcinoma (MSK, Nat Genet 2013)","type_of_cancer_id":"acyc","sample_count":60,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_mskcc_2013"},{"cancer_study_identifier":"acyc_fmi_2014","name":"Adenoid Cystic Carcinoma (FMI, Am J Surg Pathl. 2014)","type_of_cancer_id":"acyc","sample_count":28,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_fmi_2014"},{"cancer_study_identifier":"acyc_jhu_2016","name":"Adenoid Cystic Carcinoma (JHU, Cancer Prev Res 2016)","type_of_cancer_id":"acyc","sample_count":25,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_jhu_2016"},{"cancer_study_identifier":"acyc_sanger_2013","name":"Adenoid Cystic Carcinoma (Sanger/MDA, JCI 2013)","type_of_cancer_id":"acyc","sample_count":24,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_sanger_2013"},{"cancer_study_identifier":"acbc_mskcc_2015","name":"Adenoid Cystic Carcinoma of the Breast (MSK, J Pathol. 2015)","type_of_cancer_id":"acbc","sample_count":12,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acbc_mskcc_2015"},{"cancer_study_identifier":"acyc_mgh_2016","name":"Adenoid Cystic Carcinoma (MGH, Nat Gen 2016)","type_of_cancer_id":"acyc","sample_count":10,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=acyc_mgh_2016"}]}

◀ result
{"result":[{"code":"ACYC","name":"Adenoid Cystic Carcinoma","score":80,"mainType":"Salivary Gland Cancer","tissue":"Head and Neck","hierarchy":"HEAD_NECK > SACA > ACYC"},{"code":"ACLG","name":"Adenoid Cystic Carcinoma of the Lacrimal Gland","score":60,"mainType":"Lacrimal Gland Tumor","tissue":"Eye","hierarchy":"EYE > LGT > ACLG"},{"code":"LUACC","name":"Adenoid Cystic Carcinoma of the Lung","score":60,"mainType":"Non-Small Cell Lung Cancer","tissue":"Lung","hierarchy":"LUNG > NSCLC > SGTTL > LUACC"},{"code":"CACC","name":"Cervical Adenoid Cystic Carcinoma","score":50,"mainType":"Cervical Cancer","tissue":"Cervix","hierarchy":"CERVIX > CACC"}]}

◀ 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 … (36467 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT * FROM top_mutated_genes_in_study(study = 'acc_2019', top_n = 30)"
}

▶ clickhouse_run_select_query
{
 "query": "SELECT * FROM top_sv_genes_in_study(study = 'acc_2019', top_n = 20)"
}

▶ clickhouse_run_select_query
{
 "query": "SELECT * FROM top_cna_genes_in_study(study = 'acc_2019', top_n = 20)"
}

◀ result
{"rows":[{"hugo_gene_symbol":"NOTCH1","altered_samples":232,"profiled_samples":1049,"frequency_pct":22.1,"total_mutation_events":345},{"hugo_gene_symbol":"KDM6A","altered_samples":138,"profiled_samples":1049,"frequency_pct":13.2,"total_mutation_events":151},{"hugo_gene_symbol":"ARID1A","altered_samples":120,"profiled_samples":1049,"frequency_pct":11.4,"total_mutation_events":139},{"hugo_gene_symbol":"KMT2D","altered_samples":111,"profiled_samples":1049,"frequency_pct":10.6,"total_mutation_events":135},{"hugo_gene_symbol":"BCOR","altered_samples":109,"profiled_samples":1049,"frequency_pct":10.4,"total_mutation_events":119},{"hugo_gene_symbol":"KMT2C","altered_samples":99,"profiled_samples":1049,"frequency_pct":9.4,"total_mutation_events":128},{"hugo_gene_symbol":"CREBBP","altered_samples":98,"profiled_samples":1049,"frequency_pct":9.3,"total_mutation_events":113},{"hugo_gene_symbol":"ARID1B","altered_samples":82,"profiled_samples":1049,"frequency_pct":7.8,"total_mutation_events":86},{"hugo_gene_symbol":"TERT","altered_samples":82,"profiled_samples":1049,"frequency_pct":7.8,"total_mutation_events":83},{"hugo_gene_symbol":"TP53","altered_samples":76,"profiled_samples":1049,"frequency_pct":7.2,"total_mutation_events":98},{"hugo_gene_symbol":"EP300","altered_samples":74,"profiled_samples":1049,"frequency_pct":7.1,"total_mutation_events":81},{"hugo_gene_symbol":"RUNX1","altered_samples":71,"profiled_samples":1049,"frequency_pct":6.8,"total_mutation_events":79},{"hugo_gene_symbol":"SPEN","altered_samples":67,"profiled_samples":1049,"frequency_pct":6.4,"total_mutation_events":79},{"hugo_gene_symbol":"BRCA2","altered_samples":64,"profiled_samples":1049,"frequency_pct":6.1,"total_mutation_events":65},{"hugo_gene_symbol":"ATM","altered_samples":59,"profiled_samples":1049,"frequency_pct":5.6,"total_mutation_events":66},{"hugo_gene_symbol":"FAT1","altered_samples":57,"profiled_samples":1049,"frequency_pct":5.4,"total_mutation_events":60},{"hugo_gene_symbol":"PIK3CA","altered_samples":54,"profiled_samples":1049,"frequency_pct":5.1,"total_mutation_events":56},{"hugo_gene_symbol":"LRP1B","altered_samples":52,"profiled_samples":1049,"frequency_pct":5,"total_mutation_events":58},{"hugo_gene_symbol":"PIK3R1","altered_samples":49,"profiled_samples":1049,"frequency_pct":4.7,"total_mutation_events":55},{"hugo_gene_symbol":"MED12","altered_samples":44,"profiled_samples":1049,"frequency_pct":4.2,"total_mutation_events":44},{"hugo_gene_symbol":"NOTCH3","altered_samples":44,"profiled_samples":1049,"frequency_pct":4.2,"total_mutation_events":48},{"hugo_gene_symbol":"IRS2","altered_samples":43,"profiled_samples":1049,"frequency_pct":4.1,"total_mutation_events":44},{"hugo_gene_symbol":"TSC2","altered_samples":43,"profiled_samples":1049,"frequency_pct":4.1,"total_mutation_events":43},{"hugo_gene_symbol":"FAT3","altered_samples":41,"profiled_samples":1049,"frequency_pct":3.9,"total_mutation_events":43},{"hugo_gene_symbol":"NTRK1","altered_samples":40,"profiled_samples":1049,"f … (650 more chars)

▶ clickhouse_run_select_query
{
 "query": "SELECT driver_filter, count() AS mutations
FROM genomic_event_derived
WHERE cancer_study_identifier = 'acc_2019' AND variant_type = 'mutation'
GROUP BY driver_filter"
}

◀ result
{"rows":[{"hugo_gene_symbol":"MYB","altered_samples":187,"profiled_samples":1049,"frequency_pct":17.8,"total_sv_events":192},{"hugo_gene_symbol":"NFIB","altered_samples":173,"profiled_samples":1049,"frequency_pct":16.5,"total_sv_events":187},{"hugo_gene_symbol":"MYBL1","altered_samples":7,"profiled_samples":1049,"frequency_pct":0.7,"total_sv_events":7},{"hugo_gene_symbol":"NOTCH1","altered_samples":7,"profiled_samples":1049,"frequency_pct":0.7,"total_sv_events":7},{"hugo_gene_symbol":"NOTCH2","altered_samples":5,"profiled_samples":1049,"frequency_pct":0.5,"total_sv_events":5},{"hugo_gene_symbol":"TTC28","altered_samples":5,"profiled_samples":1049,"frequency_pct":0.5,"total_sv_events":5},{"hugo_gene_symbol":"HBS1L","altered_samples":4,"profiled_samples":1049,"frequency_pct":0.4,"total_sv_events":4},{"hugo_gene_symbol":"MAP3K5","altered_samples":4,"profiled_samples":1049,"frequency_pct":0.4,"total_sv_events":9},{"hugo_gene_symbol":"NKAIN2","altered_samples":3,"profiled_samples":1049,"frequency_pct":0.3,"total_sv_events":3},{"hugo_gene_symbol":"AHI1","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"AIG1","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":4},{"hugo_gene_symbol":"ARID1A","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"BNC2","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"CCDC171","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"CDKN2A","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"DICER1","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":3},{"hugo_gene_symbol":"EGFR","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"EYA4","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":3},{"hugo_gene_symbol":"GNA11","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2},{"hugo_gene_symbol":"PEX7","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_sv_events":2}]}

◀ result
{"rows":[{"hugo_gene_symbol":"PDGFRA","cytoband":"4q12","cna_type":"AMP","altered_samples":36,"profiled_samples":928,"frequency_pct":3.9},{"hugo_gene_symbol":"KIT","cytoband":"4q12","cna_type":"AMP","altered_samples":31,"profiled_samples":928,"frequency_pct":3.3},{"hugo_gene_symbol":"CDKN2A","cytoband":"9p21.3","cna_type":"HOMDEL","altered_samples":29,"profiled_samples":928,"frequency_pct":3.1},{"hugo_gene_symbol":"KDR","cytoband":"4q12","cna_type":"AMP","altered_samples":29,"profiled_samples":928,"frequency_pct":3.1},{"hugo_gene_symbol":"CDKN2B","cytoband":"9p21.3","cna_type":"HOMDEL","altered_samples":27,"profiled_samples":928,"frequency_pct":2.9},{"hugo_gene_symbol":"MDM2","cytoband":"12q15","cna_type":"AMP","altered_samples":25,"profiled_samples":928,"frequency_pct":2.7},{"hugo_gene_symbol":"FRS2","cytoband":"12q15","cna_type":"AMP","altered_samples":17,"profiled_samples":928,"frequency_pct":1.8},{"hugo_gene_symbol":"ARID2","cytoband":"12q12","cna_type":"HOMDEL","altered_samples":16,"profiled_samples":928,"frequency_pct":1.7},{"hugo_gene_symbol":"SLC38A1","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":16,"profiled_samples":928,"frequency_pct":1.7},{"hugo_gene_symbol":"SLC38A2","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":16,"profiled_samples":928,"frequency_pct":1.7},{"hugo_gene_symbol":"SLC38A4","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":16,"profiled_samples":928,"frequency_pct":1.7},{"hugo_gene_symbol":"ADCY6","cytoband":"12q13.12","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"AMIGO2","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"ANP32D","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"ARF3","cytoband":"12q13.12","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"ASB8","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"C12ORF54","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"C1QL4","cytoband":"12q13.12","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"CACNB3","cytoband":"12q13.12","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6},{"hugo_gene_symbol":"CCDC184","cytoband":"12q13.11","cna_type":"HOMDEL","altered_samples":15,"profiled_samples":928,"frequency_pct":1.6}]}

◀ result
{"rows":[{"mutations":9532}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT mutation_type, count() AS n, uniqExact(sample_unique_id) AS samples
FROM genomic_event_derived
WHERE cancer_study_identifier = 'acc_2019' AND variant_type = 'mutation' AND hugo_gene_symbol = 'BCOR'
GROUP BY mutation_type ORDER BY n DESC"
}

▶ clickhouse_run_select_query
{
 "query": "SELECT upper(mutation_status) AS status, count() AS n
FROM genomic_event_derived
WHERE cancer_study_identifier = 'acc_2019' AND variant_type = 'mutation' AND hugo_gene_symbol = 'BCOR'
GROUP BY status"
}

◀ result
{"rows":[{"mutation_type":"Frame_Shift_Del","n":41,"samples":41},{"mutation_type":"Frame_Shift_Ins","n":38,"samples":36},{"mutation_type":"Nonsense_Mutation","n":19,"samples":19},{"mutation_type":"Missense_Mutation","n":16,"samples":16},{"mutation_type":"Splice_Site","n":2,"samples":2},{"mutation_type":"Targeted_Region","n":2,"samples":2},{"mutation_type":"In_Frame_Ins","n":1,"samples":1}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT * FROM gene_mutation_variants_in_study(study = 'acc_2019', gene = 'BCOR') ORDER BY altered_samples DESC LIMIT 20"
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
{"rows":[{"status":"SOMATIC","n":119}]}

◀ result
{"rows":[{"mutation_variant":"Q600Hfs*11","mutation_type":"Frame_Shift_Ins","altered_samples":3,"profiled_samples":1049,"frequency_pct":0.3,"total_mutation_events":3},{"mutation_variant":"E983*","mutation_type":"Nonsense_Mutation","altered_samples":3,"profiled_samples":1049,"frequency_pct":0.3,"total_mutation_events":3},{"mutation_variant":"L333Ffs*48","mutation_type":"Frame_Shift_Ins","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"S209L","mutation_type":"Missense_Mutation","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"MUTATED","mutation_type":"Targeted_Region","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"S1297*","mutation_type":"Nonsense_Mutation","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"E1042Rfs*37","mutation_type":"Frame_Shift_Ins","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"L279Rfs*21","mutation_type":"Frame_Shift_Del","altered_samples":2,"profiled_samples":1049,"frequency_pct":0.2,"total_mutation_events":2},{"mutation_variant":"L93V","mutation_type":"Missense_Mutation","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"Q1468Tfs*9","mutation_type":"Frame_Shift_Ins","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"I148Tfs*33","mutation_type":"Frame_Shift_Del","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"Q918Lfs*29","mutation_type":"Frame_Shift_Ins","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"A385Sfs*60","mutation_type":"Frame_Shift_Ins","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"T347Lfs*29","mutation_type":"Frame_Shift_Del","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"Q600Hfs*9","mutation_type":"Frame_Shift_Del","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"N891Pfs*25","mutation_type":"Frame_Shift_Del","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"E518*","mutation_type":"Nonsense_Mutation","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"K615Pfs*2","mutation_type":"Frame_Shift_Ins","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutation_variant":"N1686Tfs*39","mutation_type":"Frame_Shift_Del","altered_samples":1,"profiled_samples":1049,"frequency_pct":0.1,"total_mutation_events":1},{"mutat … (153 more chars)

◀ 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": "SELECT cancer_study_identifier, upper(mutation_status) AS status, count() AS n
FROM genomic_event_derived
WHERE cancer_study_identifier IN ('acyc_mda_2015','acyc_mskcc_2013','acyc_fmi_2014','acyc_jhu_2016','acyc_sanger_2013','acyc_mgh_2016','acbc_mskcc_2015')
  AND variant_type = 'mutation' AND hugo_gene_symbol = 'BCOR'
GROUP BY cancer_study_identifier, status"
}

▶ get_study_guide
{
 "study_id": "acc_2019"
}

◀ result
{"rows":[{"cancer_study_identifier":"acyc_mskcc_2013","status":"SOMATIC","n":1},{"cancer_study_identifier":"acyc_mda_2015","status":"SOMATIC","n":1}]}

◀ result
Error generating study guide for 'acc_2019': Query execution failed: HTTPDriver for https://dl96orhu96.us-east-1.aws.clickhouse.cloud:8443 received ClickHouse error code 241
 Code: 241. DB::Exception: (total) memory limit exceeded: would use 31.58 GiB (attempt to allocate chunk of 0.00 B), current RSS: 31.58 GiB, maximum: 28.80 GiB. (MEMORY_LIMIT_EXCEEDED)


▶ resolve_and_route
{
 "studyIds": [
  "acc_2019"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"acc_2019","name":"Adenoid Cystic Carcinoma Project (J Clin Invest 2019)","sampleCount":1049,"studyViewUrl":"https://www.cbioportal.org/study?id=acc_2019","metadata":{"clinicalAttributeIds":["AGE","CANCER_TYPE","CANCER_TYPE_DETAILED","DATA_SOURCE","FRACTION_GENOME_ALTERED","MUTATION_COUNT","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","SAMPLE_COUNT","SAMPLE_TYPE","SEX","SOMATIC_STATUS","STUDY","TMB_NONSYNONYMOUS"],"molecularProfileIds":["acc_2019_cna","acc_2019_mutations","acc_2019_structural_variants"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations"]}}]}}

▶ navigate_to_results_view
{
 "studyIds": [
  "acc_2019"
 ],
 "genes": [
  "MYB",
  "MYBL1",
  "NFIB",
  "NOTCH1",
  "BCOR",
  "KDM6A",
  "ARID1A",
  "KMT2D",
  "KMT2C",
  "CREBBP",
  "TP53",
  "PIK3CA",
  "PDGFRA",
  "KIT",
  "MDM2",
  "CDKN2A"
 ],
 "tab": "oncoprint"
}

◀ result
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▶ navigate_to_study_view
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 ],
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   {
    "molecularProfileIds": [
     "acc_2019_mutations"
    ],
    "geneQueries": [
     [
      {
       "hugoGeneSymbol": "BCOR"
      }
     ]
    ]
   }
  ]
 }
}

◀ result
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═ answer (success)
## Adenoid Cystic Carcinoma (ACC) — Driver Landscape

Data from the **[Adenoid Cystic Carcinoma Project](https://www.cbioportal.org/study/summary?id=acc_2019)** (J Clin Invest 2019), the largest ACC cohort in cBioPortal (1,049 samples, MSK/Dana-Farber/multi-institution). Frequencies below are sample-level (altered/profiled × 100).

**Important caveat:** this dataset carries no OncoKB/hotspot driver annotation in the database (the `driver_filter` field is empty for all 9,532 mutation records), so I cannot certify any gene below as an "OncoKB-annotated driver." Classification below reflects recurrence/established biology of ACC, not a database-verified driver call — for driver/hotspot filtering, use the OQL `DRIVER` modifier in the portal itself.

### Structural drivers (initiating, near-pathognomonic)
| Alteration | Frequency | Notes |
|---|---|---|
| **MYB** rearrangement (t(6;9), MYB-NFIB fusion) | 187/1049 (17.8%) | Classic ACC-defining fusion |
| **NFIB** rearrangement (fusion partner) | 173/1049 (16.5%) | |
| **MYBL1** rearrangement | 7/1049 (0.7%) | Alternative to MYB in MYB-fusion-negative tumors |

MYB/MYBL1 dysregulation (via fusion or enhancer hijacking) is the near-universal oncogenic driver mechanism in ACC — collectively affecting the majority of tumors when fusion-negative cases with MYB/MYBL1 overexpression by other mechanisms are included (not directly measurable from DNA-seq data here).

### Recurrently mutated genes (chromatin/epigenetic and signaling)
| Gene | Frequency | Pathway |
|---|---|---|
| **NOTCH1** | 232/1049 (22.1%) | Notch signaling — most frequently mutated gene by SNV/indel |
| **KDM6A** | 138/1049 (13.2%) | Chromatin (H3K27 demethylase) |
| **ARID1A** | 120/1049 (11.4%) | SWI/SNF chromatin remodeling |
| **KMT2D** | 111/1049 (10.6%) | Histone methyltransferase |
| **BCOR** | 109/1049 (10.4%) | Polycomb-associated corepressor |
| **KMT2C** | 99/1049 (9.4%) | Histone methyltransferase |
| **CREBBP** | 98/1049 (9.3%) | Histone acetyltransferase |
| **ARID1B** | 82/1049 (7.8%) | SWI/SNF |
| **TERT** | 82/1049 (7.8%) | Includes promoter events |
| **TP53** | 76/1049 (7.2%) | Tumor suppressor |
| **RUNX1** | 71/1049 (6.8%) | Transcription factor |

### Copy-number events
| Gene | Type | Frequency |
|---|---|---|
| PDGFRA | AMP | 36/928 (3.9%) |
| KIT | AMP | 31/928 (3.3%) |
| CDKN2A/CDKN2B | HOMDEL | ~29/928 (3.1%) |
| MDM2 | AMP | 25/928 (2.7%) |

---

### Classification by actionability

**1. Clinically actionable today (approved or guideline-supported targeted options)**
- None of these alterations have an FDA-approved ACC-specific targeted therapy. Actionability in ACC is investigational/trial-based rather than standard-of-care.

**2. Potentially actionable (biomarker-driven trial eligibility / off-label rationale)**
- **NOTCH1 mutations (22%)** — rationale for gamma-secretase inhibitors (e.g., AL101/crenigacestat) in clinical trials for NOTCH-activated ACC.
- **KIT / PDGFRA amplification** — rationale for multi-kinase inhibitors (imatinib, sunitinib); historically disappointing single-agent activity in ACC despite KIT expression.
- **TERT alterations** — no direct targeted agent, but relevant to telomerase-targeting trials.
- **NTRK1** mutations (3.8%, rare fusions may occur separately) — TRK inhibitors (larotrectinib/entrectinib) are tumor-agnostic approved therapies *if* an actionable NTRK fusion (not just a point mutation) is present; would need confirmation of fusion vs. SNV.
- **MDM2 amplification (2.7%)** — rationale for MDM2 inhibitors in trials (TP53 wild-type required).
- **CDKN2A/B loss (~3%)** — rationale for CDK4/6 inhibitor trials.

**3. Prognostic/biological, not currently actionable**
- **MYB/MYBL1/NFIB fusions** — diagnostic and biologically central, but no direct MYB-targeted drug is clinically available; considered "undruggable" transcription factor drivers.
- **Chromatin-remodeling genes** (KDM6A, ARID1A, ARID1B, KMT2C/D, CREBBP, BCOR) — epigenetic vulnerability hypotheses (e.g., EZH2 inhibitors in SWI/SNF-deficient tumors) exist in other cancers but are not established/validated in ACC specifically.
- **TP53 mutations** — prognostic (associated with high-grade transformation/solid variant), not directly druggable.

*(This actionability framing draws on general oncology knowledge of these gene classes, not on data retrieved from cBioPortal — cBioPortal itself does not store therapeutic actionability tiers.)*

---

### BCOR mutations specifically

- **Frequency:** 109/1049 samples (10.4%), 119 total mutation events — the 5th most frequently mutated gene in this cohort.
- **Mutation types:** predominantly **truncating** — frameshift deletions (41), frameshift insertions (38/39), nonsense (19) — versus only 16 missense and 2 splice-site events. This pattern (>80% truncating) is consistent with **BCOR acting as a tumor suppressor** in ACC, causing loss of its polycomb-repressive-complex corepressor function.
- **Somatic vs. germline:** **All 119 BCOR mutation records in this study, and in every other ACC cohort in cBioPortal (MSKCC 2013, MDA 2015), are annotated as somatic.** I found **no germline BCOR mutations** recorded in any ACC dataset here. If you're asking because of a specific patient with a suspected germline BCOR variant (BCOR is linked to a rare X-linked developmental syndrome, unrelated to sporadic ACC pathogenesis), that would need to be confirmed via clinical germline testing — it is not represented in these tumor-sequencing cohorts.
- **Actionability:** loss-of-function/truncating — not directly druggable; classified as **prognostic/biological**, in the same bucket as other chromatin-modifier mutations above. It has been associated in the literature with higher-grade/more aggressive ACC in some cohorts, but I have not run a statistical comparison to confirm that association here.

---

### Explore further
- [OncoPrint — MYB/NFIB fusions + top mutated + CNA drivers across all 1,049 samples](https://www.cbioportal.org/results/oncoprint?cancer_study_list=acc_2019&gene_list=MYB%0AMYBL1%0ANFIB%0ANOTCH1%0ABCOR%0AKDM6A%0AARID1A%0AKMT2D%0AKMT2C%0ACREBBP%0ATP53%0APIK3CA%0APDGFRA%0AKIT%0AMDM2%0ACDKN2A&case_set_id=acc_2019_all)
- [Study View filtered to BCOR-mutant samples](https://www.cbioportal.org/study/summary?id=acc_2019#filterJson=%7B%22geneFilters%22%3A%5B%7B%22geneQueries%22%3A%5B%5B%7B%22hugoGeneSymbol%22%3A%22BCOR%22%7D%5D%5D%2C%22molecularProfileIds%22%3A%5B%22acc_2019_mutations%22%5D%7D%5D%7D) — explore clinical correlations (grade, site, outcome) interactively.

This is for research exploration only — not a substitute for genomic tumor board review or clinical decision-making.