Q (sonnet): In the TCGA PanCancer Atlas endometrial cancer study, in samples with both KRAS and NRAS mutations, what is the distribution of variant allele frequencies suggesting clonal vs subclonal events?

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

◀ 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)

▶ read_guide
{
 "uri": "cbioportal://sample-filtering-guide"
}

▶ list_studies
{
 "search": "Endometrial TCGA PanCancer Atlas"
}

◀ result
# Sample and Study Filtering Guide

## Overview
Proper filtering is essential for meaningful cBioPortal analysis. This guide covers filtering by studies, sample types, and other criteria.

## Study-Level Filtering

### 1. Always Filter by Study
Every query should specify a study to ensure consistent results:

```sql
-- Always include study filtering
SELECT *
FROM your_table
WHERE
    cancer_study_identifier = 'your_study_id'
    -- Additional filters...
```

### 2. Find Available Studies

```sql
-- Discover available studies
SELECT
    cancer_study_identifier,
    name,
    description,
    type_of_cancer_id
FROM cancer_study
ORDER BY cancer_study_identifier;
```

### 3. Study Information

```sql
-- Get detailed study information
SELECT
    cs.cancer_study_identifier,
    cs.name as study_name,
    cs.description,
    cs.sample_count,
    COUNT(DISTINCT p.internal_id) as patient_count
FROM cancer_study cs
LEFT JOIN patient p ON cs.cancer_study_id = p.cancer_study_id
WHERE
    cs.cancer_study_identifier = 'your_study_id'
GROUP BY cs.cancer_study_identifier, cs.name, cs.description, cs.sample_count;
```

### 4. Find Studies by Available Data Types

Use this when the user asks *"which studies have mutation and copy-number data for X"*, *"studies with expression for Y"*, *"is there any imaging data"*, or any *"studies with Z data"* question. `cancer_study` has one precomputed sample count per data type — filter on them. No join and no schema exploration needed. These are the same counts as the portal's study list and its "Data type" filter.

**Canonical query — studies with ALL requested data types for a cancer type:**

```sql
SELECT
    cancer_study_identifier,
    name,
    sample_count,
    mutation_sample_count,
    cna_sample_count
FROM cancer_study
WHERE type_of_cancer_id = 'luad'          -- ← OncoTree code from search_oncotree
  AND mutation_sample_count > 0           -- ← one condition per required data type
  AND cna_sample_count > 0
ORDER BY sample_count DESC;
```

**Data type → column** (a count of 0 means the study doesn't have that data):

| Data type in the user's question | Column (portal "Data type" filter label) |
|---|---|
| samples in the study | `sample_count` |
| mutation / mutations | `mutation_sample_count` ("Mutations") |
| copy-number / CNA / amplification / deletion | `cna_sample_count` ("CNA") |
| structural variant / fusion | `structural_variant_sample_count` |
| RNA / mRNA / gene expression (any platform) | `mrna_expression_sample_count` — use this for "which studies have expression data" |
| specifically the portal's "RNA-Seq" filter | `rna_seq_sample_count` ("RNA-Seq") — counts only the `<study>_rna_seq_v2_mrna` list; 0 for many GDC and iAtlas studies that do have RNA-Seq |
| specifically the portal's "RNA (microarray)" filter | `mrna_microarray_sample_count` ("RNA (microarray)") — counts only the `<study>_mrna` list |
| microRNA | `mirna_sample_count` ("miRNA") |
| protein / RPPA | `rppa_sample_count` ("RPPA") |
| mas … (7866 more chars)

◀ result
{"result":[{"cancer_study_identifier":"ucec_tcga_pan_can_atlas_2018","name":"Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"ucec","sample_count":529,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=ucec_tcga_pan_can_atlas_2018"}]}

▶ get_study_guide
{
 "study_id": "ucec_tcga_pan_can_atlas_2018"
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
# Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)

**Study ID:** `ucec_tcga_pan_can_atlas_2018`

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

## Study-Specific Attributes

### Molecular Classification (TCGA)
| Attribute | Description | Values (patients) |
|-----------|-------------|--------|
| `SUBTYPE` | TCGA molecular subtype | `UCEC_CN_HIGH` 163, `UCEC_MSI` 148, `UCEC_CN_LOW` 147, `UCEC_POLE` 49, blank 22 |

### Histology
There is no `HISTOLOGICAL_TYPE` attribute; use `CANCER_TYPE_DETAILED`, plus `GRADE` for grade.

| Attribute | Values (samples) |
|-----------|--------|
| `CANCER_TYPE_DETAILED` | Uterine Endometrioid Carcinoma 399, Uterine Serous Carcinoma/Uterine Papillary Serous Carcinoma 109, Uterine Mixed Endometrial Carcinoma 21 |
| `GRADE` | G3 302, G2 119, G1 97, High Grade 11 |

`AJCC_PATHOLOGIC_TUMOR_STAGE` is blank for all samples.

## Molecular Subtypes
| Subtype | Characteristics | Prognosis |
|---------|-----------------|-----------|
| **POLE** | Ultra-hypermutated (>100 mut/Mb), POLE exonuclease mutations | Excellent |
| **MSI** | Hypermutated, microsatellite instability, MLH1 silencing | Intermediate |
| **CN-low** | Microsatellite stable, few copy number alterations | Intermediate |
| **CN-high** | Serous-like, TP53 mutations, extensive CNA | Poor |

## Key Genes
| Gene | Frequency | Subtype Association |
|------|-----------|---------------------|
| PTEN | ~65% | CN-low, MSI |
| PIK3CA | ~50% | All subtypes |
| PIK3R1 | ~30% | CN-low |
| ARID1A | ~35% | MSI |
| TP53 | ~25% | CN-high (>90% in this subtype) |
| KRAS | ~20% | Various |
| CTNNB1 | ~20% | CN-low |
| POLE | ~7% | Defines POLE subtype |

## Notes
- TCGA molecular classification has prognostic value and guides treatment
- POLE and MSI subtypes are hypermutated but have different mechanisms
- TP53 mutations with CN-high pattern indicate serous-like behavior regardless of histology
- POLE mutations should be in exonuclease domain (proofreading) to be driver
- MSI-H tumors respond well to immunotherapy


◀ 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_list_tables
{}

◀ result
{"tables":[{"name":"allele_specific_copy_number"},{"name":"alteration_driver_annotation"},{"name":"cancer_study"},{"name":"cancer_study_query_preferences"},{"name":"cancer_study_tags"},{"name":"cbioportal_sequence_state"},{"name":"clinical_attribute_counts"},{"name":"clinical_attribute_meta"},{"name":"clinical_data_derived"},{"name":"clinical_event"},{"name":"clinical_event_data"},{"name":"clinical_event_data_derived"},{"name":"clinical_event_derived"},{"name":"clinical_patient"},{"name":"clinical_sample"},{"name":"cna_event"},{"name":"cna_panel_gene_coverage"},{"name":"cna_wes_coverage"},{"name":"co_altered_genes_in_study"},{"name":"copy_number_seg"},{"name":"copy_number_seg_file"},{"name":"gene"},{"name":"gene_alias"},{"name":"gene_alteration_frequency_by_cancer_type"},{"name":"gene_cna_distribution_in_study"},{"name":"gene_mutation_frequency_by_cancer_type"},{"name":"gene_mutation_frequency_in_studies"},{"name":"gene_mutation_frequency_in_study"},{"name":"gene_mutation_variants_in_study"},{"name":"gene_pair_coexpression"},{"name":"gene_panel"},{"name":"gene_panel_list"},{"name":"gene_panel_to_gene_derived"},{"name":"generic_assay_data_derived"},{"name":"generic_assay_meta_derived"},{"name":"generic_assay_profile_entity_derived"},{"name":"generic_entity_properties"},{"name":"geneset"},{"name":"geneset_gene"},{"name":"geneset_hierarchy_leaf"},{"name":"geneset_hierarchy_node"},{"name":"genetic_alteration"},{"name":"genetic_alteration_derived"},{"name":"genetic_entity"},{"name":"genetic_profile"},{"name":"genetic_profile_link"},{"name":"genetic_profile_samples"},{"name":"genomic_event_derived"},{"name":"gistic"},{"name":"gistic_to_gene"},{"name":"info"},{"name":"mut_sig"},{"name":"mutation"},{"name":"mutation_count_by_keyword"},{"name":"mutation_derived"},{"name":"mutation_event"},{"name":"mutation_panel_gene_coverage"},{"name":"mutation_wes_coverage"},{"name":"patient"},{"name":"reference_genome"},{"name":"reference_genome_gene"},{"name":"resource_definition"},{"name":"resource_patient"},{"name":"resource_sample"},{"name":"resource_study"},{"name":"sample"},{"name":"sample_cna_event"},{"name":"sample_derived"},{"name":"sample_list"},{"name":"sample_list_list"},{"name":"sample_profile"},{"name":"sample_to_gene_panel_derived"},{"name":"structural_variant"},{"name":"sv_panel_gene_coverage"},{"name":"sv_wes_coverage"},{"name":"top_cna_genes_in_study"},{"name":"top_mutated_genes_in_cohort"},{"name":"top_mutated_genes_in_study"},{"name":"top_sv_genes_in_study"},{"name":"treatment_counts_in_study"},{"name":"treatment_regimens_in_study"},{"name":"type_of_cancer"}]}

▶ clickhouse_list_table_columns
{
 "table": "mutation"
}

▶ clickhouse_list_table_columns
{
 "table": "mutation_derived"
}

◀ result
{"columns":[{"name":"mutation_event_id","type":"Int64","comment":"References mutation_event.mutation_event_id."},{"name":"genetic_profile_id","type":"Int64","comment":"References genetic_profile.genetic_profile_id."},{"name":"sample_id","type":"Int64","comment":"References sample.internal_id."},{"name":"entrez_gene_id","type":"Int64","comment":"References gene.entrez_gene_id."},{"name":"center","type":"Nullable(String)","comment":"Center where sequencing was performed."},{"name":"sequencer","type":"Nullable(String)","comment":"Sequencing platform used."},{"name":"mutation_status","type":"Nullable(String)","comment":"Mutation status: Germline,\n    Somatic,\n    or LOH."},{"name":"validation_status","type":"Nullable(String)","comment":"Validation status."},{"name":"tumor_seq_allele1","type":"Nullable(String)","comment":"Tumor allele 1 sequence."},{"name":"tumor_seq_allele2","type":"Nullable(String)","comment":"Tumor allele 2 sequence."},{"name":"matched_norm_sample_barcode","type":"Nullable(String)","comment":"Matched normal sample barcode."},{"name":"match_norm_seq_allele1","type":"Nullable(String)","comment":"Matched normal allele 1 sequence."},{"name":"match_norm_seq_allele2","type":"Nullable(String)","comment":"Matched normal allele 2 sequence."},{"name":"tumor_validation_allele1","type":"Nullable(String)","comment":"Tumor validation allele 1 sequence."},{"name":"tumor_validation_allele2","type":"Nullable(String)","comment":"Tumor validation allele 2 sequence."},{"name":"match_norm_validation_allele1","type":"Nullable(String)","comment":"Matched normal validation allele 1."},{"name":"match_norm_validation_allele2","type":"Nullable(String)","comment":"Matched normal validation allele 2."},{"name":"verification_status","type":"Nullable(String)","comment":"Verification status."},{"name":"sequencing_phase","type":"Nullable(String)","comment":"Sequencing phase."},{"name":"sequence_source","type":"String","comment":"Source of sequencing data."},{"name":"validation_method","type":"Nullable(String)","comment":"Validation method used."},{"name":"score","type":"Nullable(String)","comment":"Score or quality metric."},{"name":"bam_file","type":"Nullable(String)","comment":"Associated BAM file."},{"name":"tumor_alt_count","type":"Nullable(Int64)","comment":"Tumor alternate allele count."},{"name":"tumor_ref_count","type":"Nullable(Int64)","comment":"Tumor reference allele count."},{"name":"normal_alt_count","type":"Nullable(Int64)","comment":"Normal alternate allele count."},{"name":"normal_ref_count","type":"Nullable(Int64)","comment":"Normal reference allele count."},{"name":"amino_acid_change","type":"Nullable(String)","comment":"Amino acid change from mutation."},{"name":"annotation_json","type":"Nullable(String)","comment":"JSON-formatted annotations."}]}

◀ result
{"columns":[{"name":"molecularProfileId","type":"String","comment":"Stable ID of the genetic profile"},{"name":"sampleId","type":"String","comment":"Stable ID of the sample"},{"name":"sampleInternalId","type":"Int64"},{"name":"patientId","type":"String","comment":"Stable ID of the patient"},{"name":"entrezGeneId","type":"Int64","comment":"Entrez Gene ID from mutation table (NOT NULL)"},{"name":"studyId","type":"String","comment":"Cancer study identifier"},{"name":"center","type":"Nullable(String)","comment":"Sequencing center"},{"name":"mutationStatus","type":"Nullable(String)","comment":"Mutation status (e.g., Somatic, Germline)"},{"name":"validationStatus","type":"Nullable(String)","comment":"Validation status"},{"name":"tumorAltCount","type":"Nullable(Int64)","comment":"Tumor alternate allele count"},{"name":"tumorRefCount","type":"Nullable(Int64)","comment":"Tumor reference allele count"},{"name":"normalAltCount","type":"Nullable(Int64)","comment":"Normal alternate allele count"},{"name":"normalRefCount","type":"Nullable(Int64)","comment":"Normal reference allele count"},{"name":"aminoAcidChange","type":"Nullable(String)","comment":"Amino acid change"},{"name":"chr","type":"Nullable(String)","comment":"Chromosome"},{"name":"startPosition","type":"Nullable(Int64)","comment":"Start position"},{"name":"endPosition","type":"Nullable(Int64)","comment":"End position"},{"name":"referenceAllele","type":"Nullable(String)","comment":"Reference allele"},{"name":"tumorSeqAllele","type":"Nullable(String)","comment":"Tumor sequence allele"},{"name":"proteinChange","type":"Nullable(String)","comment":"Protein change"},{"name":"mutationType","type":"Nullable(String)","comment":"Type of mutation"},{"name":"ncbiBuild","type":"Nullable(String)","comment":"NCBI build version"},{"name":"variantType","type":"Nullable(String)","comment":"Variant type"},{"name":"refseqMrnaId","type":"Nullable(String)","comment":"RefSeq mRNA ID"},{"name":"proteinPosStart","type":"Nullable(Int64)","comment":"Protein position start"},{"name":"proteinPosEnd","type":"Nullable(Int64)","comment":"Protein position end"},{"name":"keyword","type":"Nullable(String)","comment":"Keyword"},{"name":"annotationJSON","type":"Nullable(String)","comment":"Annotation JSON"},{"name":"driverFilter","type":"Nullable(String)","comment":"Driver filter"},{"name":"driverFilterAnnotation","type":"Nullable(String)","comment":"Driver filter annotation"},{"name":"driverTiersFilter","type":"Nullable(String)","comment":"Driver tiers filter"},{"name":"driverTiersFilterAnnotation","type":"Nullable(String)","comment":"Driver tiers filter annotation"},{"name":"GENE.entrezGeneId","type":"Nullable(Int64)","comment":"Gene entrez ID"},{"name":"GENE.hugoGeneSymbol","type":"Nullable(String)","comment":"HUGO gene symbol"},{"name":"GENE.type","type":"Nullable(String)","comment":"Gene type"},{"name":"alleleSpecificCopyNumber.ascnIntegerCopyNumber","type":"Nullable(Int64)","comment":"ASCN integer copy number"},{"name":"alleleSpe … (756 more chars)

▶ clickhouse_run_select_query
{
 "query": "
WITH kras_nras_samples AS (
    SELECT sample_unique_id
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'ucec_tcga_pan_can_atlas_2018'
      AND variant_type = 'mutation'
      AND mutation_status != 'UNCALLED'
      AND hugo_gene_symbol IN ('KRAS', 'NRAS')
    GROUP BY sample_unique_id
    HAVING COUNT(DISTINCT hugo_gene_symbol) = 2
)
SELECT count() FROM kras_nras_samples
"
}

◀ result
{"rows":[{"count()":4}]}

▶ clickhouse_run_select_query
{
 "query": "
WITH kras_nras_samples AS (
    SELECT sample_unique_id
    FROM genomic_event_derived
    WHERE cancer_study_identifier = 'ucec_tcga_pan_can_atlas_2018'
      AND variant_type = 'mutation'
      AND mutation_status != 'UNCALLED'
      AND hugo_gene_symbol IN ('KRAS', 'NRAS')
    GROUP BY sample_unique_id
    HAVING COUNT(DISTINCT hugo_gene_symbol) = 2
)
SELECT
    md.sampleId,
    md.GENE.hugoGeneSymbol AS gene,
    md.proteinChange,
    md.mutationType,
    md.mutationStatus,
    md.tumorRefCount,
    md.tumorAltCount,
    round(md.tumorAltCount * 1.0 / nullif(md.tumorAltCount + md.tumorRefCount, 0), 3) AS vaf,
    md.alleleSpecificCopyNumber.clonal AS clonal_call,
    md.alleleSpecificCopyNumber.ccfExpectedCopies AS ccf
FROM mutation_derived md
WHERE md.studyId = 'ucec_tcga_pan_can_atlas_2018'
  AND concat('ucec_tcga_pan_can_atlas_2018_', md.sampleId) IN (SELECT sample_unique_id FROM kras_nras_samples)
  AND md.GENE.hugoGeneSymbol IN ('KRAS', 'NRAS')
ORDER BY md.sampleId, gene
"
}

◀ result
{"rows":[{"sampleId":"TCGA-A5-A0G2-01","gene":"KRAS","proteinChange":"Q61H","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":47,"tumorAltCount":51,"vaf":0.52},{"sampleId":"TCGA-A5-A0G2-01","gene":"NRAS","proteinChange":"D47N","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":130,"tumorAltCount":53,"vaf":0.29},{"sampleId":"TCGA-A5-A0G2-01","gene":"NRAS","proteinChange":"F78S","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":148,"tumorAltCount":40,"vaf":0.213},{"sampleId":"TCGA-AX-A0J0-01","gene":"KRAS","proteinChange":"K176Q","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":187,"tumorAltCount":137,"vaf":0.423},{"sampleId":"TCGA-AX-A0J0-01","gene":"NRAS","proteinChange":"E162*","mutationType":"Nonsense_Mutation","mutationStatus":".","tumorRefCount":168,"tumorAltCount":19,"vaf":0.102},{"sampleId":"TCGA-B5-A0JV-01","gene":"KRAS","proteinChange":"G12D","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":264,"tumorAltCount":68,"vaf":0.205},{"sampleId":"TCGA-B5-A0JV-01","gene":"NRAS","proteinChange":"Q61K","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":183,"tumorAltCount":43,"vaf":0.19},{"sampleId":"TCGA-DF-A2KZ-01","gene":"KRAS","proteinChange":"A146V","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":51,"tumorAltCount":14,"vaf":0.215},{"sampleId":"TCGA-DF-A2KZ-01","gene":"NRAS","proteinChange":"Q61R","mutationType":"Missense_Mutation","mutationStatus":".","tumorRefCount":42,"tumorAltCount":14,"vaf":0.25}]}

▶ resolve_and_route
{
 "studyIds": [
  "ucec_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":"ucec_tcga_pan_can_atlas_2018","name":"Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)","sampleCount":529,"studyViewUrl":"https://www.cbioportal.org/study?id=ucec_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":["ucec_tcga_pan_can_atlas_2018_gistic","ucec_tcga_pan_can_atlas_2018_log2CNA","ucec_tcga_pan_can_atlas_2018_mutations","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_ref_normal_Zscores","ucec_tcga_pan_can_atlas_2018_rppa","ucec_tcga_pan_can_atlas_2018_rppa_Zscores","ucec_tcga_pan_can_atlas_2018_structural_variants"],"genericAssayProfiles":["ucec_tcga_pan_can_atlas_2018_armlevel_cna","ucec_tcga_pan_can_atlas_2018_genetic_ancestry","ucec_tcga_pan_can_atlas_2018_methylation_hm27_hm450_merge","ucec_tcga_pan_can_atlas_2018_methylation_hm450"],"heatmapProfileIds":["ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ucec_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_ref_normal_Zscores","ucec_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"]}}]}}

▶ navigate_to_results_view
{
 "studyIds": [
  "ucec_tcga_pan_can_atlas_2018"
 ],
 "genes": [
  "KRAS: MUT",
  "NRAS: MUT"
 ],
 "tab": "mutations"
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/mutations?cancer_study_list=ucec_tcga_pan_can_atlas_2018&gene_list=KRAS%3A+MUT%0ANRAS%3A+MUT&case_set_id=ucec_tcga_pan_can_atlas_2018_all","url":"https://www.cbioportal.org/results/mutations?cancer_study_list=ucec_tcga_pan_can_atlas_2018&gene_list=KRAS%3A+MUT%0ANRAS%3A+MUT&case_set_id=ucec_tcga_pan_can_atlas_2018_all","data":{"studyIds":["ucec_tcga_pan_can_atlas_2018"],"studies":[{"studyId":"ucec_tcga_pan_can_atlas_2018","name":"Uterine Corpus Endometrial Carcinoma (TCGA, PanCancer Atlas)","sampleCount":529}],"genes":["KRAS","NRAS"],"caseSetId":"ucec_tcga_pan_can_atlas_2018_all","pageDescription":"Detailed mutation table with lollipop plot showing mutation positions, types, and frequencies for queried genes."}}

═ answer (success)
[View KRAS and NRAS mutations in UCEC PanCancer Atlas](https://www.cbioportal.org/results/mutations?cancer_study_list=ucec_tcga_pan_can_atlas_2018&gene_list=KRAS%3A+MUT%0ANRAS%3A+MUT&case_set_id=ucec_tcga_pan_can_atlas_2018_all) — detailed mutation table with lollipop plots showing mutation positions, types, and frequencies for KRAS and NRAS in this cohort. Individual sample-level allele-count data (as tabulated above) is not directly displayed there, but you can cross-reference variants by sample ID (e.g. TCGA-A5-A0G2, TCGA-AX-A0J0, TCGA-B5-A0JV, TCGA-DF-A2KZ) using the Patient View pages for read-level detail.