Q (sonnet): Is there any study with a polygenic risk score?

▶ list_guides
{}

◀ result
{"result":[{"uri":"cbioportal://mutation-frequency-guide","description":"Comprehensive guide for calculating gene mutation frequencies with gene-specific profiling denominators"},{"uri":"cbioportal://clinical-data-guide","description":"Guide for querying clinical data including patient vs sample level considerations"},{"uri":"cbioportal://sample-filtering-guide","description":"Guide for filtering samples and studies in cBioPortal queries"},{"uri":"cbioportal://common-pitfalls","description":"Guide to avoid common mistakes when querying cBioPortal data. If you already know which numbered pitfall applies, fetch just that section via read_guide(\"cbioportal://common-pitfalls#<number>\") (e.g. #16) instead of the full guide"},{"uri":"cbioportal://treatment-guide","description":"Guide for querying treatment/clinical event data including drug agents, timelines, and linking to genomic data"},{"uri":"cbioportal://faq-guide","description":"General cBioPortal FAQ: history, how to cite, data types, reference genome, abbreviations, GISTIC thresholds, API access"},{"uri":"cbioportal://statistical-tests-guide","description":"Statistical test selection guide — decision matrix for choosing Fisher's exact, Wilcoxon, chi-squared, t-test, ANOVA, etc. based on data type and group count"},{"uri":"cbioportal://gene-expression-guide","description":"Gene expression / copy-number / methylation analysis. Covers genetic_alteration_derived, profile_type discovery, and the gene_pair_coexpression view for Spearman correlation between two genes"},{"uri":"cbioportal://external-resources-guide","description":"Guide for finding external linked resources such as imaging, pathology, Minerva, HTAN, or other resource_* table links before declaring data unavailable"},{"uri":"cbioportal://gene-resolution-guide","description":"Guide for resolving ambiguous gene symbols, aliases, gene families, and shorthand such as CD3 before querying expression or alteration data"},{"uri":"cbioportal://study-resolution-guide","description":"Guide for resolving requested studies, avoiding silent substitute cohorts, and redirecting to known external cBioPortal instances when data is not in this deployment"},{"uri":"cbioportal://germline-guide","description":"Guide for querying germline variant data — storage columns, study discovery, query patterns, and somatic vs germline considerations"},{"uri":"cbioportal://study-guide/{study_id}","description":"Dynamic study-specific guide - use get_study_guide(study_id) tool to generate"}]}

▶ read_guide
{
 "uri": "cbioportal://clinical-data-guide"
}

▶ clickhouse_list_table_columns
{
 "table": "clinical_attribute_meta"
}

◀ result
# Clinical Data Query Guide

## Overview
Clinical data in cBioPortal is stored at both patient and sample levels. Understanding the distinction is crucial for accurate analysis.

## Data Organization

### Patient-Level vs Sample-Level Data
- **Patient-level**: Demographics, overall survival, disease stage (stored once per patient)
- **Sample-level**: Sample type, sequencing platform, purity (can have multiple per patient)

### Key Tables
- `clinical_patient`: Patient-level clinical attributes
- `clinical_sample`: Sample-level clinical attributes
- `clinical_data_derived`: Pre-joined view combining both levels
- `clinical_attribute_meta`: Metadata about available clinical attributes

## Recommended Approach: Use clinical_data_derived

The `clinical_data_derived` table is pre-joined and optimized for most queries:

```sql
-- Get clinical data for specific attributes
SELECT
    sample_unique_id,
    patient_unique_id,
    attribute_name,
    attribute_value
FROM clinical_data_derived
WHERE
    cancer_study_identifier = 'your_study_id'
    AND attribute_name IN ('CANCER_TYPE', 'SAMPLE_TYPE', 'TMB_NONSYNONYMOUS');
```

## Clinical Attribute Discovery

### Use clinical_attribute_meta for Discovering Available Attributes
**Always start here** to see what clinical attributes are available for a specific study:

```sql
-- Discover available clinical attributes for a study
SELECT
    attr_id,
    description,
    patient_attribute,
    cancer_study_id
FROM clinical_attribute_meta
WHERE
    cancer_study_id = (
        SELECT cancer_study_id
        FROM cancer_study
        WHERE cancer_study_identifier = 'your_study_id'
    )
ORDER BY patient_attribute, attr_id;
```

**Key Fields:**
- **attr_id**: matches attr_id in clinical_sample/clinical_patient tables
- **description**: human-readable description of the attribute
- **patient_attribute**: true = patient attribute, false = sample attribute
- **cancer_study_id**: links to cancer_study table (filter by study)

## Attribute Semantics and Matching

### Case-Insensitive Matching for Attribute Values

Clinical values are free text across studies and may differ only by case. For example, a controlled-looking value such as germline mutation status may appear as `GERMLINE`, `Germline`, or another case variant.

When filtering `clinical_data_derived.attribute_value`, use case-insensitive matching unless you have already profiled the exact values in the target study:

```sql
-- Correct: case-insensitive clinical value filter
SELECT DISTINCT sample_unique_id, patient_unique_id
FROM clinical_data_derived
WHERE cancer_study_identifier = 'your_study_id'
  AND attribute_name = 'MUTATION_STATUS'
  AND upper(attribute_value) = 'GERMLINE';
```

Do not write `attribute_value = 'GERMLINE'` without first checking all distinct values for that attribute in the study.

### Query the Requested Attribute, Not a Proxy

Do not infer one clinical attribute from a related subtype or marker. Query the actual requested attribute when it … (17073 more chars)

◀ result
{"columns":[{"name":"attr_id","type":"String"},{"name":"display_name","type":"String"},{"name":"description","type":"String"},{"name":"datatype","type":"String"},{"name":"patient_attribute","type":"Int32"},{"name":"priority","type":"String"},{"name":"cancer_study_id","type":"Int64"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT DISTINCT attr_id, display_name, description, cancer_study_id
FROM clinical_attribute_meta
WHERE upper(attr_id) LIKE '%PRS%' OR upper(attr_id) LIKE '%POLYGENIC%'
   OR upper(display_name) LIKE '%POLYGENIC%' OR upper(description) LIKE '%POLYGENIC%'
   OR upper(display_name) LIKE '%RISK SCORE%' OR upper(description) LIKE '%RISK SCORE%'
LIMIT 100"
}

▶ clickhouse_list_tables
{}

◀ result
{"rows":[{"attr_id":"IPSSM_SCORE","display_name":"IPSS-M Score","description":"IPSS-M Risk Score","cancer_study_id":239},{"attr_id":"IPSSR_SCORE","display_name":"IPSS-R Score","description":"IPSS-R Risk Score","cancer_study_id":239},{"attr_id":"MBR_SCORE","display_name":"MBR Score","description":"Microbiome Risk Score calculated by the MBR classifier. The MBR classifier that was built by a relaxed multivariate elastic-net cox regression model including 41 genera","cancer_study_id":105},{"attr_id":"RISK_SCORE","display_name":"Total Risk Score","description":"Risk score calculated using nomogram integrated risk model based on mitotic count, density of Ki-67+ and CD163+ cells, and MTOR mutation. ","cancer_study_id":410},{"attr_id":"TMPRSS2_ERG_FUSION_STATUS","display_name":"TMPRSS2-ERG Fusion Status","description":"TMPRESS2-ERG fusion status.","cancer_study_id":371}]}

◀ 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_run_select_query
{
 "query": "SELECT DISTINCT stable_id, name, description
FROM generic_assay_meta_derived
WHERE upper(name) LIKE '%POLYGENIC%' OR upper(description) LIKE '%POLYGENIC%'
   OR upper(stable_id) LIKE '%PRS%' OR upper(name) LIKE '%PRS%'
LIMIT 50"
}

▶ clickhouse_list_table_columns
{
 "table": "generic_assay_meta_derived"
}

◀ result
{"error_message":"Query execution failed: HTTPDriver for https://dl96orhu96.us-east-1.aws.clickhouse.cloud:8443 received ClickHouse error code 47\n Code: 47. DB::Exception: Unknown expression identifier `stable_id` in scope SELECT DISTINCT stable_id, name, description FROM generic_assay_meta_derived WHERE (upper(name) LIKE '%POLYGENIC%') OR (upper(description) LIKE '%POLYGENIC%') OR (upper(stable_id) LIKE '%PRS%') OR (upper(name) LIKE '%PRS%') LIMIT 50. (UNKNOWN_IDENTIFIER) (version 26.4.1.2359 (official build))\n"}

◀ result
{"columns":[{"name":"entity_stable_id","type":"String"},{"name":"entity_type","type":"LowCardinality(String)"},{"name":"properties","type":"Map(String, String)"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT DISTINCT entity_stable_id, entity_type, properties
FROM generic_assay_meta_derived
WHERE upper(toString(properties)) LIKE '%POLYGENIC%' OR upper(entity_stable_id) LIKE '%PRS%'
LIMIT 50"
}

▶ clickhouse_list_table_columns
{
 "table": "generic_assay_profile_entity_derived"
}

◀ result
{"rows":[{"entity_stable_id":"1_220006106_220007338_EPRS","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"EPRS"}},{"entity_stable_id":"ADPRS_K109k","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"ADPRS","DESCRIPTION":"1_1_109_109","ACETYLSITES":"K109k_1_1_109_109","NAME":"ADPRS_K109k"}},{"entity_stable_id":"TMPRSS11B_K393k","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS11B","DESCRIPTION":"1_1_393_393","ACETYLSITES":"K393k_1_1_393_393","NAME":"TMPRSS11B_K393k"}},{"entity_stable_id":"TMPRSS11B_acetylprotein","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS11B","NAME":"S97s "}},{"entity_stable_id":"TMPRSS13_S135","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13"}},{"entity_stable_id":"TMPRSS13_S70","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13"}},{"entity_stable_id":"TMPRSS13_T29","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13"}},{"entity_stable_id":"TMPRSS13_T49","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13"}},{"entity_stable_id":"TMPRSS13_T64","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13"}},{"entity_stable_id":"TMPRSS13_acetylprotein","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","NAME":"T29t-S70s-S135s "}},{"entity_stable_id":"TMPRSS13_pS134","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS134"}},{"entity_stable_id":"TMPRSS13_pS135","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS135"}},{"entity_stable_id":"TMPRSS13_pS25_T29","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS25_T29"}},{"entity_stable_id":"TMPRSS13_pS45","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS45"}},{"entity_stable_id":"TMPRSS13_pS70","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS70"}},{"entity_stable_id":"TMPRSS13_pS90","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pS90"}},{"entity_stable_id":"TMPRSS13_pT29","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pT29"}},{"entity_stable_id":"TMPRSS13_pT49","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pT49"}},{"entity_stable_id":"TMPRSS13_pT64","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pT64"}},{"entity_stable_id":"TMPRSS13_pT64_S70","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS13","PHOSPHOSITE":"pT64_S70"}},{"entity_stable_id":"TMPRSS9_Y333:NP_892018.1","entity_type":"GENERIC_ASSAY","properties":{"GENE_SYMBOL":"TMPRSS9"}},{"entity_stable_id":"TMPRs_S13_S135s","entity_type":"GENERIC_ASSAY","properties":{"PHOSPHOSITES":"S135s_1_0_134_135","GENE_SYMBOL":"TMPRSS13","DESCRIPTION":"1_0_134_135","NAME":"TMPRs_S13_S135s"}},{"entity_stable_id":"TMPRs_S13_S70s","entity_type":"GENERIC_ASSAY","prope … (4319 more chars)

◀ result
{"columns":[{"name":"profile_stable_id","type":"LowCardinality(String)"},{"name":"entity_stable_id","type":"String"}]}

▶ clickhouse_run_select_query
{
 "query": "SELECT DISTINCT key, count(*) as n
FROM clinical_event_data_derived
WHERE upper(key) LIKE '%POLYGENIC%' OR upper(key) LIKE '%PRS%'
GROUP BY key
LIMIT 50"
}

◀ result
{"rows":[]}

▶ clickhouse_run_select_query
{
 "query": "SELECT DISTINCT attribute_name
FROM clinical_data_derived
WHERE upper(attribute_name) LIKE '%POLYGENIC%'
LIMIT 20"
}

◀ result
{"rows":[]}

═ answer (success)
I searched clinical attributes, clinical event data, and generic assay entities across the entire database for any mention of "polygenic risk score" or "PRS."

**No study in this cBioPortal deployment contains a polygenic risk score.**

The only "risk score" attributes present are unrelated clinical/molecular risk models:
- **IPSS-M / IPSS-R Score** — myelodysplastic syndrome prognostic scores (in an MDS study)
- **Microbiome Risk Score (MBR)** — a microbiome-based Cox model score
- **Total Risk Score** — a nomogram combining mitotic count, Ki-67⁺/CD163⁺ density, and MTOR mutation status (in a separate study)

None of these are germline polygenic risk scores (i.e., aggregated common-variant genetic risk). Polygenic risk scores are generally not a data type cBioPortal is designed to host — the platform focuses on somatic/tumor genomic alterations, clinical annotations, and treatment data rather than germline PRS models used in population genetics or risk-prediction research.

If you're looking for PRS data specifically, that would typically be found in dedicated genetics/genomics resources (e.g., PGS Catalog) rather than cBioPortal. Let me know if you'd like me to pull up any of the risk-score studies I found above, or if there's a related cBioPortal data type I can help you explore instead.