Q (sonnet-5.5): In TCGA lower grade glioma, show me samples that are TP53 mutant or EGFR amplified.

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

▶ resolve_and_route
{
 "studyKeywords": [
  "TCGA",
  "lower grade glioma"
 ]
}

◀ 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
{"success":true,"message":"Found 2 matching studies. Pick the best match (prefer TCGA → prefer PanCancer Atlas), use its metadata to call the appropriate navigation tool(s) and generate URLs immediately. Present other studies as alternatives.","data":{"totalCount":2,"studiesWithMetadata":[{"studyId":"lgg_tcga","name":"Brain Lower Grade Glioma (TCGA, Firehose Legacy)","sampleCount":530,"studyViewUrl":"https://www.cbioportal.org/study?id=lgg_tcga","metadata":{"clinicalAttributeIds":["AGE","ANIMAL_INSECT_ALLERGY_AGE","ANIMAL_INSECT_ALLERGY_HIST","ASTHMA_ECZEMA_ALLERGY_FIRST_DIAGNOSIS","ASTHMA_HISTORY","CANCER_TYPE","CANCER_TYPE_DETAILED","DAYS_TO_COLLECTION","DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS","DAYS_TO_SPECIMEN_COLLECTION","DFS_MONTHS","DFS_STATUS","DISEASE_CODE","ECOG_SCORE","ECZEMA_HISTORY","ETHNICITY","FAMILY_HISTORY_OF_CANCER","FAMILY_HISTORY_OF_PRIMARY_BRAIN_TUMOR","FIRST_SYMPTOM_LONGEST_DURATION","FOOD_ALLERGY_AGE","FOOD_ALLERGY_HISTORY","FOOD_ALLERGY_TYPES","FORM_COMPLETION_DATE","FRACTION_GENOME_ALTERED","GRADE","HAY_FEVER_HISTORY","HEADACHE_HISTORY","HISTOLOGICAL_DIAGNOSIS","HISTORY_IONIZING_RT_TO_HEAD","HISTORY_NEOADJUVANT_MEDICATION","HISTORY_NEOADJUVANT_STEROID_TX","HISTORY_NEOADJUVANT_TRTYN","HISTORY_OTHER_MALIGNANCY","ICD_10","ICD_O_3_HISTOLOGY","ICD_O_3_SITE","IDH1_MUTATION","IDH1_MUTATION_TEST_INDICATOR","IDH1_MUTATION_TEST_METHOD","INFORMED_CONSENT_VERIFIED","INHERITED_GENETIC_SYNDROME_INDICATOR","INHERITED_GENETIC_SYNDROME_SPECIFIED","INITIAL_PATHOLOGIC_DX_YEAR","IS_FFPE","KARNOFSKY_PERFORMANCE_SCORE","LATERALITY","LONGEST_DIMENSION","METHOD_OF_SAMPLE_PROCUREMENT","MOLD_OR_DUST_ALLERGY_HISTORY","MUTATION_COUNT","NEW_TUMOR_EVENT_AFTER_INITIAL_TREATMENT","OCT_EMBEDDED","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER_METHOD_OF_SAMPLE_PROCUREMENT","OTHER_PATIENT_ID","OTHER_SAMPLE_ID","PATHOLOGY_REPORT_FILE_NAME","PATHOLOGY_REPORT_UUID","PERFORMANCE_STATUS_DAYS_TO","PERFORMANCE_STATUS_TIMING","PROJECT_CODE","PROSPECTIVE_COLLECTION","RACE","RADIATION_TREATMENT_ADJUVANT","RELATED_SYMPTOM_FIRST_PRESENT","RETROSPECTIVE_COLLECTION","SAMPLE_COUNT","SAMPLE_INITIAL_WEIGHT","SAMPLE_TYPE","SAMPLE_TYPE_ID","SEIZURE_HISTORY","SEX","SHORTEST_DIMENSION","SITE_OF_TUMOR_TISSUE","SOMATIC_STATUS","SPECIMEN_CURRENT_WEIGHT","SPECIMEN_FREEZING_METHOD","SPECIMEN_SECOND_LONGEST_DIMENSION","SUPRATENTORIAL_LOCALIZATION","SYMP_CHANGES_MENTAL_STATUS","SYMP_CHANGES_MOTOR_MOVEMENT","SYMP_CHANGES_SENSORY","SYMP_CHANGES_VISUAL","TARGETED_MOLECULAR_THERAPY","TIME_BETWEEN_CLAMPING_AND_FREEZING","TIME_BETWEEN_EXCISION_AND_FREEZING","TISSUE_SOURCE_SITE","TMB_NONSYNONYMOUS","TREATMENT_OUTCOME_FIRST_COURSE","TUMOR_SITE","TUMOR_STATUS","VIAL_NUMBER"],"molecularProfileIds":["lgg_tcga_gistic","lgg_tcga_linear_CNA","lgg_tcga_methylation_hm450","lgg_tcga_mrna","lgg_tcga_mrna_median_Zscores","lgg_tcga_mrna_median_all_sample_Zscores","lgg_tcga_mutations","lgg_tcga_rna_seq_v2_mrna","lgg_tcga_rna_seq_v2_mrna_median_Zscores","lgg_tcga_rna_seq_v2_mrna_median_all_sample_Zscores","lg … (2867 more chars)

═ answer (success)
"TCGA lower grade glioma" matches two studies in cBioPortal:

1. **Brain Lower Grade Glioma (TCGA, PanCancer Atlas)** (`lgg_tcga_pan_can_atlas_2018`) has 514 samples.
2. **Brain Lower Grade Glioma (TCGA, Firehose Legacy)** (`lgg_tcga`) has 530 samples.

Which one do you want, or should I use both? Once you choose, I'll list the samples with a TP53 mutation or an EGFR amplification. I'll also give you a link to that filtered cohort in cBioPortal.