Q (sonnet): How many GLASS patients developed hypermutation after TMZ treatment? ▶ list_guides {} ▶ list_studies { "search": "GLASS" } ◀ 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#\") (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"}]} ◀ result {"result":[{"cancer_study_identifier":"difg_glass","name":"Diffuse Glioma (GLASS Consortium)","type_of_cancer_id":"difg","sample_count":693,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=difg_glass"},{"cancer_study_identifier":"difg_glass_2019","name":"Diffuse Glioma (GLASS Consortium, Nature 2019)","type_of_cancer_id":"difg","sample_count":444,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=difg_glass_2019"}]} ▶ read_guide { "uri": "cbioportal://treatment-guide" } ▶ read_guide { "uri": "cbioportal://clinical-data-guide" } ◀ result # Treatment Data Query Guide ## Overview Treatment data in cBioPortal is stored in **clinical event tables**, separate from clinical attributes. This allows for timeline-based treatment records with start/stop dates. ## Start Here: Treatment Views For "most common treatments / agents / regimens in study X", use the parameterized views (documented in `cbioportal://clinical-data-guide`, Study-View Chart Counts): ```sql -- Patients per agent (the portal's Treatment chart), with type/subtype arrays SELECT * FROM treatment_counts_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20; -- Same-day agent combinations (investigational, prior-medication and radiation events excluded) SELECT * FROM treatment_regimens_in_study(study='msk_chord_2024') ORDER BY patients DESC LIMIT 20; ``` Write raw event queries (below) only for subgroups, timelines or keys the views do not expose. ## Key Tables | Table | Description | |-------|-------------| | `clinical_event` | Event records with patient_id, event_type, start_date, stop_date | | `clinical_event_data` | Key-value pairs linked to each clinical_event_id | ## Schema ``` clinical_event ├── clinical_event_id (PK) ├── patient_id (FK → patient.internal_id) ├── event_type (Treatment, TREATMENT, Diagnosis, SURGERY, etc.) ├── start_date (days from diagnosis) └── stop_date (days from diagnosis) clinical_event_data ├── clinical_event_id (FK) ├── key (AGENT, SUBTYPE, etc.) └── value ``` ## Event Types Not all studies have all event types. Common ones include: | Event Type | Description | |------------|-------------| | `Treatment` / `TREATMENT` | Drug/therapy administration | | `SURGERY` | Surgical procedures | | `Diagnosis` | Diagnosis events | | `LAB_TEST` | Laboratory results | | `Sequencing` | Sequencing events | | `Sample acquisition` | Sample collection | | `PATHOLOGY` / `Pathology` | Pathology reports | ## Basic Treatment Queries ### List Available Event Types in a Study ```sql SELECT DISTINCT ce.event_type, COUNT(*) as event_count FROM clinical_event ce JOIN patient p ON ce.patient_id = p.internal_id JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id WHERE cs.cancer_study_identifier = 'your_study_id' GROUP BY ce.event_type ORDER BY event_count DESC; ``` ### List Treatment Data Keys in a Study ```sql SELECT DISTINCT ced.key, COUNT(*) as cnt FROM clinical_event ce JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id JOIN patient p ON ce.patient_id = p.internal_id JOIN cancer_study cs ON p.cancer_study_id = cs.cancer_study_id WHERE cs.cancer_study_identifier = 'your_study_id' AND ce.event_type IN ('Treatment', 'TREATMENT') GROUP BY ced.key ORDER BY cnt DESC; ``` ### Get Most Common Treatment Agents ```sql SELECT ced.value as agent, COUNT(DISTINCT ce.patient_id) as patient_count FROM clinical_event ce JOIN clinical_event_data ced ON ce.clinical_event_id = ced.clinical_event_id JOIN patient p ON ce.patient_id = p.internal_id JOIN cancer_stud … (6220 more chars) ◀ 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) ▶ get_study_guide { "study_id": "difg_glass" } ◀ result # Study Guide: Diffuse Glioma (GLASS Consortium) **Study ID:** `difg_glass` **Cancer Type:** difg **Description:** Whole genome or whole exome sequencing analysis of temporally separated diffuse glioma tumor/normal pairs from 329 adult patients. The data provided is based on the May 31, 2022 version and can be accessed at Synapse. ## Cohort Statistics - **Patients:** 329 - **Samples:** 694 ## Available Data Types - **COPY_NUMBER_ALTERATION**: Copy Number Alterations - **MUTATION_EXTENDED**: Mutations - **MRNA_EXPRESSION**: mRNA expression (RNA Seq TPM) - **MRNA_EXPRESSION**: mRNA expression z-scores relative to all samples (log RNA Seq TPM) ## Gene Panels - **WES** (Whole Exome): 693 samples — all genes profiled ## Available Clinical Attributes | Attribute | Samples with Data | |-----------|------------------| | CANCER_TYPE_DETAILED | 693 | | TREATMENT_CONCURRENT_TMZ | 693 | | ESTIMATE_SCORE | 693 | | MGMT_METHYLATION | 693 | | MUTATION_COUNT | 693 | | ALIQUOT_ANALYSIS_TYPE | 693 | | FRACTION_GENOME_ALTERED | 693 | | SURGERY_TYPE | 693 | | CODEL_STATUS | 693 | | SURGERY_EXTENT_OF_RESECTION | 693 | | TREATMENT_RADIOTHERAPY | 693 | | IDH_STATUS | 693 | | RNA_ALIQUOT_BARCODE | 693 | | TUMOR_GRADE | 693 | | CANCER_TYPE | 693 | | SAMPLE_TYPE | 693 | | IDH_CODEL_STATUS | 693 | | SURGERY_LATERALITY | 693 | | ONCOTREE_CODE | 693 | | ALKYLATING_AGENT_TX | 693 | ## Top Mutated Genes | Gene | Altered Samples | |------|----------------| | TP53 | 273 | | IDH1 | 227 | | TTN | 147 | | PTEN | 143 | | ATRX | 139 | | EGFR | 112 | | MUC16 | 106 | | NF1 | 97 | | RYR2 | 81 | | OBSCN | 70 | ## Sample Types - **First Recurrence**: 318 samples - **Tumor Primary**: 309 samples - **Second Recurrence**: 49 samples - **Third Recurrence**: 14 samples - **Fourth recurrence**: 2 samples - **First Metastasis**: 1 samples ## Query Tips for difg_glass ```sql -- Get all samples in this study SELECT DISTINCT sample_unique_id, patient_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass'; -- Get mutations for a specific gene SELECT sample_unique_id, hugo_gene_symbol, mutation_variant, mutation_type FROM genomic_event_derived WHERE cancer_study_identifier = 'difg_glass' AND hugo_gene_symbol = 'TP53' AND variant_type = 'mutation'; -- Get clinical data for specific attributes SELECT sample_unique_id, attribute_name, attribute_value FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass' AND attribute_name IN ('CANCER_TYPE', 'SAMPLE_TYPE', 'OS_MONTHS'); ``` ▶ clickhouse_run_select_query { "query": "SELECT attr_id, description, patient_attribute FROM clinical_attribute_meta WHERE cancer_study_id = (SELECT cancer_study_id FROM cancer_study WHERE cancer_study_identifier = 'difg_glass') AND (upper(attr_id) LIKE '%HYPERMUT%' OR upper(description) LIKE '%HYPERMUT%')" } ◀ result {"rows":[]} ▶ clickhouse_run_select_query { "query": "SELECT attr_id, description, patient_attribute FROM clinical_attribute_meta WHERE cancer_study_id = (SELECT cancer_study_id FROM cancer_study WHERE cancer_study_identifier = 'difg_glass_2019') AND (upper(attr_id) LIKE '%HYPERMUT%' OR upper(description) LIKE '%HYPERMUT%')" } ◀ result {"rows":[{"attr_id":"HYPERMUTATION_STATUS","description":"Recurrent tumor in the tumor pairs have a mutation burden (Mutations/Mb) > 10?","patient_attribute":1}]} ▶ clickhouse_run_select_query { "query": "SELECT attr_id, description, patient_attribute FROM clinical_attribute_meta WHERE cancer_study_id = (SELECT cancer_study_id FROM cancer_study WHERE cancer_study_identifier = 'difg_glass_2019') ORDER BY patient_attribute, attr_id" } ◀ result {"rows":[{"attr_id":"ALIQUOT_BARCODE","description":"A variable that stitches subject, sample type, portion, sequencing type, and a unique identifier together","patient_attribute":0},{"attr_id":"ALKYLATING_AGENT","description":"Alkylating Agent Treatment","patient_attribute":0},{"attr_id":"ANEUPLOIDY_AMP_SCORE","description":"Aneuploidy Amplification Score","patient_attribute":0},{"attr_id":"ANEUPLOIDY_DEL_SCORE","description":"Aneuploidy Deletion Score","patient_attribute":0},{"attr_id":"ANEUPLOIDY_SCORE","description":"Aneuploidy Score","patient_attribute":0},{"attr_id":"CANCER_TYPE","description":"Cancer Type","patient_attribute":0},{"attr_id":"CANCER_TYPE_DETAILED","description":"Cancer Type Detailed","patient_attribute":0},{"attr_id":"CHEMO_OTHER","description":"A comma separated list indicating combination of specific chemotherapeutic agents as well as unspecified agents","patient_attribute":0},{"attr_id":"CHEMO_OTHER_CYCLES","description":"Treatment cycles for the therapies listed in Chemotherapy Other.","patient_attribute":0},{"attr_id":"COMMENTS","description":"Additional descriptors to aid in the interpretation of treatment fields","patient_attribute":0},{"attr_id":"CONCURRENT_TMZ","description":"Indicates whether temozolomide was administered concurrently with radiotherapy","patient_attribute":0},{"attr_id":"EXTENT_OF_RESECTION","description":"Indicates whether a sample was collected from a Biopsy, Subtotal, or Total resection","patient_attribute":0},{"attr_id":"FRACTION_GENOME_ALTERED","description":"Fraction Genome Altered","patient_attribute":0},{"attr_id":"GENE_PANEL","description":"Sequencing method of the highest quality sample selected when multiple samples are available","patient_attribute":0},{"attr_id":"GRADE","description":"Grade","patient_attribute":0},{"attr_id":"HISTOLOGY","description":"Histology","patient_attribute":0},{"attr_id":"MGMT_METHYLATION","description":"Clinical assessment of MGMT methylation","patient_attribute":0},{"attr_id":"MGMT_METHYLATION_METHOD","description":"MGMT Methylation Method","patient_attribute":0},{"attr_id":"MNP_CLASSIFICATION","description":"DNA methylation-based classification of central nervous system tumors","patient_attribute":0},{"attr_id":"MUTATION_COUNT","description":"Mutation Count","patient_attribute":0},{"attr_id":"ONCOTREE_CODE","description":"Oncotree Code","patient_attribute":0},{"attr_id":"RADIATION_DOSE","description":"The dosage of radiation a subject received, reported in Gray units.","patient_attribute":0},{"attr_id":"RADIATION_OTHER","description":"Additional details about the specific application of radiotherapy","patient_attribute":0},{"attr_id":"RADIOTHERAPY","description":"Indicates whether a subject received radiotherapy","patient_attribute":0},{"attr_id":"RADIOTHERAPY_FRACTIONS","description":"The number of smaller number of radiation doses","patient_attribute":0},{"attr_id":"SAMPLE_CLASS","description":"Sample Class","patient_attribute":0},{"attr_id":"SAMPLE_TYPE", … (3401 more chars) ▶ clickhouse_run_select_query { "query": "SELECT DISTINCT attribute_value FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'HYPERMUTATION_STATUS'" } ◀ result {"rows":[{"attribute_value":"No"},{"attribute_value":"Yes"}]} ▶ clickhouse_run_select_query { "query": "SELECT DISTINCT attribute_value FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name LIKE '%TMZ%'" } ◀ result {"rows":[{"attribute_value":"No"},{"attribute_value":"Yes"},{},{"attribute_value":"12"},{"attribute_value":"5"},{"attribute_value":"6"},{"attribute_value":"7"},{"attribute_value":"4"},{"attribute_value":"2"},{"attribute_value":"3"},{"attribute_value":"9"},{"attribute_value":"11"},{"attribute_value":"20"},{"attribute_value":"1"},{"attribute_value":"13"},{"attribute_value":"35"},{"attribute_value":"24"},{"attribute_value":"15"},{"attribute_value":"8"},{"attribute_value":"14"},{"attribute_value":"26"},{"attribute_value":"33"}]} ▶ clickhouse_run_select_query { "query": "SELECT attribute_name FROM clinical_attribute_meta WHERE cancer_study_id = (SELECT cancer_study_id FROM cancer_study WHERE cancer_study_identifier = 'difg_glass_2019') AND upper(attr_id) LIKE '%TMZ%'" } ◀ 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 `attribute_name` in scope SELECT attribute_name FROM clinical_attribute_meta WHERE (cancer_study_id = (SELECT cancer_study_id FROM cancer_study WHERE cancer_study_identifier = 'difg_glass_2019')) AND (upper(attr_id) LIKE '%TMZ%'). (UNKNOWN_IDENTIFIER) (version 26.4.1.2359 (official build))\n"} ▶ clickhouse_run_select_query { "query": " WITH hyper AS ( SELECT patient_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'HYPERMUTATION_STATUS' AND attribute_value = 'Yes' ), tmz_treated AS ( SELECT DISTINCT patient_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'TMZ_TREATMENT' AND attribute_value = 'Yes' ) SELECT (SELECT count() FROM hyper) AS n_hypermutated_patients, (SELECT count() FROM tmz_treated) AS n_tmz_treated_patients, (SELECT count() FROM hyper WHERE patient_unique_id IN (SELECT patient_unique_id FROM tmz_treated)) AS n_hypermutated_and_tmz_treated, (SELECT count(DISTINCT patient_unique_id) FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'HYPERMUTATION_STATUS') AS n_evaluable_for_hypermutation " } ◀ result {"rows":[{"n_hypermutated_patients":35,"n_tmz_treated_patients":151,"n_hypermutated_and_tmz_treated":30,"n_evaluable_for_hypermutation":222}]} ▶ clickhouse_run_select_query { "query": " WITH hyper AS ( SELECT patient_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'HYPERMUTATION_STATUS' AND attribute_value = 'Yes' ) SELECT patient_unique_id, attribute_name, attribute_value, sample_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name = 'TMZ_TREATMENT' AND patient_unique_id IN (SELECT patient_unique_id FROM hyper) AND patient_unique_id NOT IN ( SELECT patient_unique_id FROM clinical_data_derived WHERE cancer_study_identifier = 'difg_glass_2019' AND attribute_name='TMZ_TREATMENT' AND attribute_value='Yes' ) ORDER BY patient_unique_id " } ◀ result {"rows":[{"patient_unique_id":"difg_glass_2019_GLSS-DK-0008","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-DK-0008-R1"},{"patient_unique_id":"difg_glass_2019_GLSS-DK-0008","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-DK-0008-TP"},{"patient_unique_id":"difg_glass_2019_GLSS-DK-0015","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-DK-0015-R1"},{"patient_unique_id":"difg_glass_2019_GLSS-DK-0015","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-DK-0015-TP"},{"patient_unique_id":"difg_glass_2019_GLSS-MD-0027","attribute_name":"TMZ_TREATMENT","attribute_value":"No","sample_unique_id":"difg_glass_2019_GLSS-MD-0027-R2"},{"patient_unique_id":"difg_glass_2019_GLSS-MD-0027","attribute_name":"TMZ_TREATMENT","attribute_value":"No","sample_unique_id":"difg_glass_2019_GLSS-MD-0027-TP"},{"patient_unique_id":"difg_glass_2019_GLSS-MD-0036","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-MD-0036-R1"},{"patient_unique_id":"difg_glass_2019_GLSS-MD-0036","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-MD-0036-TP"},{"patient_unique_id":"difg_glass_2019_GLSS-SF-0024","attribute_name":"TMZ_TREATMENT","sample_unique_id":"difg_glass_2019_GLSS-SF-0024-R2"},{"patient_unique_id":"difg_glass_2019_GLSS-SF-0024","attribute_name":"TMZ_TREATMENT","attribute_value":"No","sample_unique_id":"difg_glass_2019_GLSS-SF-0024-TP"}]} ▶ resolve_and_route { "studyIds": [ "difg_glass_2019" ] } ◀ result {"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"difg_glass_2019","name":"Diffuse Glioma (GLASS Consortium, Nature 2019)","sampleCount":444,"studyViewUrl":"https://www.cbioportal.org/study?id=difg_glass_2019","metadata":{"clinicalAttributeIds":["1P19Q_STATUS","AGE_AT_DX","ALIQUOT_BARCODE","ALKYLATING_AGENT","ANEUPLOIDY_AMP_SCORE","ANEUPLOIDY_DEL_SCORE","ANEUPLOIDY_SCORE","CANCER_TYPE","CANCER_TYPE_DETAILED","CASE_PROJECT","CHEMO_OTHER","CHEMO_OTHER_CYCLES","COMMENTS","CONCURRENT_TMZ","EXTENT_OF_RESECTION","FRACTION_GENOME_ALTERED","GENE_PANEL","GRADE","HISTOLOGY","HYPERMUTATION_STATUS","IDH_CODEL_SUBTYPE","IDH_STATUS","INITIAL_GRADE","INITIAL_HISTOLOGY","MGMT_METHYLATION","MGMT_METHYLATION_METHOD","MNP_CLASSIFICATION","MUTATION_COUNT","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","POST_RECURRENCE_SURVIVAL_MONTHS","RADIATION_DOSE","RADIATION_OTHER","RADIOTHERAPY","RADIOTHERAPY_FRACTIONS","SAMPLE_CLASS","SAMPLE_COUNT","SAMPLE_TYPE","SEX","SOMATIC_STATUS","SURGERY NUMBER","SURGERY_INDICATION","TIME_TO_FIRST_RECURRENCE","TISSUE_SOURCE","TMB_NONSYNONYMOUS","TMZ_CYCLES","TMZ_TREATMENT","TRANSCRIPTIONAL_SUBTYPES","TUMOR_LATERALITY","TUMOR_LOCATION","TYPE_OF_SURGERY","WHOLE_EXOME_SEQUENCED","WHOLE_GENOME_SEQUENCED","WHO_CLASSIFICATION"],"molecularProfileIds":["difg_glass_2019_mutations","difg_glass_2019_rna_seq_mrna","difg_glass_2019_rna_seq_mrna_median_all_sample_Zscores"],"genericAssayProfiles":["difg_glass_2019_armlevel_cna"],"heatmapProfileIds":["difg_glass_2019_rna_seq_mrna_median_all_sample_Zscores"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations","mrna","generic_assay_armlevel_cna"]}}]}} ▶ navigate_to_study_view { "studyIds": [ "difg_glass_2019" ], "filterJson": { "clinicalDataFilters": [ { "attributeId": "HYPERMUTATION_STATUS", "values": [ { "value": "Yes" } ] }, { "attributeId": "TMZ_TREATMENT", "values": [ { "value": "Yes" } ] } ] } } ◀ result {"success":true,"message":"Navigating to https://www.cbioportal.org/study/summary?id=difg_glass_2019#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HYPERMUTATION_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%2C%7B%22attributeId%22%3A%22TMZ_TREATMENT%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%5D%7D","url":"https://www.cbioportal.org/study/summary?id=difg_glass_2019#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HYPERMUTATION_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%2C%7B%22attributeId%22%3A%22TMZ_TREATMENT%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%5D%7D","data":{"studyIds":["difg_glass_2019"],"studies":[{"studyId":"difg_glass_2019","name":"Diffuse Glioma (GLASS Consortium, Nature 2019)","sampleCount":444}],"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."}} ═ answer (success) [View TMZ-treated + hypermutated patients in GLASS 2019](https://www.cbioportal.org/study/summary?id=difg_glass_2019#filterJson=%7B%22clinicalDataFilters%22%3A%5B%7B%22attributeId%22%3A%22HYPERMUTATION_STATUS%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%2C%7B%22attributeId%22%3A%22TMZ_TREATMENT%22%2C%22values%22%3A%5B%7B%22value%22%3A%22Yes%22%7D%5D%7D%5D%7D) Note this filter applies `TMZ_TREATMENT = Yes` across any sample record for the patient (the same logic used above), matched against the patient-level hypermutation flag — it should reproduce the 30-patient count. Note that TMZ_TREATMENT is recorded per surgical sample (not strictly "before recurrence" timing), so this reflects patients with any recorded TMZ exposure who were later flagged hypermutated at recurrence, consistent with how GLASS defines the phenotype.