Q (sonnet):
How often is TP53 mutated in the TCGA PanCancer Atlas cohort?
TP53 is the most frequently mutated gene across the TCGA PanCancer Atlas studies, but its rate varies a lot by cancer type. Would you like me to break it down by cancer type?
Continue this conversation: reply to the user's new message.
yes please
▶ 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)
▶ clickhouse_run_select_query
{
"query": "SELECT * FROM gene_mutation_frequency_by_cancer_type(preference = 'pan_cancer_tcga', gene = 'TP53') ORDER BY frequency_pct DESC",
"max_rows": 40
}
▶ clickhouse_run_select_query
{
"query": "SELECT cancer_study_identifier FROM cancer_study_query_preferences WHERE preference_name = 'pan_cancer_tcga' ORDER BY cancer_study_identifier",
"max_rows": 50
}
◀ result
{"rows":[{"cancer_type":"Ovarian Epithelial Tumor","altered_samples":373,"profiled_samples":523,"frequency_pct":71.3},{"cancer_type":"Head and Neck Cancer","altered_samples":357,"profiled_samples":515,"frequency_pct":69.3},{"cancer_type":"Non-Small Cell Lung Cancer","altered_samples":699,"profiled_samples":1050,"frequency_pct":66.6},{"cancer_type":"Esophagogastric Cancer","altered_samples":371,"profiled_samples":618,"frequency_pct":60},{"cancer_type":"Pancreatic Cancer","altered_samples":107,"profiled_samples":179,"frequency_pct":59.8},{"cancer_type":"Colorectal Cancer","altered_samples":314,"profiled_samples":534,"frequency_pct":58.8},{"cancer_type":"Bladder Cancer","altered_samples":202,"profiled_samples":410,"frequency_pct":49.3},{"cancer_type":"Glioma","altered_samples":249,"profiled_samples":514,"frequency_pct":48.4},{"cancer_type":"Endometrial Cancer","altered_samples":245,"profiled_samples":574,"frequency_pct":42.7},{"cancer_type":"Sarcoma","altered_samples":85,"profiled_samples":255,"frequency_pct":33.3},{"cancer_type":"Breast Cancer","altered_samples":347,"profiled_samples":1066,"frequency_pct":32.6},{"cancer_type":"Glioblastoma","altered_samples":125,"profiled_samples":397,"frequency_pct":31.5},{"cancer_type":"Hepatobiliary Cancer","altered_samples":110,"profiled_samples":366,"frequency_pct":30.1},{"cancer_type":"Adrenocortical Carcinoma","altered_samples":18,"profiled_samples":91,"frequency_pct":19.8},{"cancer_type":"Melanoma","altered_samples":72,"profiled_samples":440,"frequency_pct":16.4},{"cancer_type":"Pleural Mesothelioma","altered_samples":14,"profiled_samples":86,"frequency_pct":16.3},{"cancer_type":"Prostate Cancer","altered_samples":57,"profiled_samples":494,"frequency_pct":11.5},{"cancer_type":"Leukemia","altered_samples":16,"profiled_samples":200,"frequency_pct":8},{"cancer_type":"Renal Non-Clear Cell Carcinoma","altered_samples":27,"profiled_samples":341,"frequency_pct":7.9},{"cancer_type":"Cervical Cancer","altered_samples":23,"profiled_samples":291,"frequency_pct":7.9},{"cancer_type":"Thymic Epithelial Tumor","altered_samples":4,"profiled_samples":123,"frequency_pct":3.3},{"cancer_type":"Renal Clear Cell Carcinoma","altered_samples":11,"profiled_samples":402,"frequency_pct":2.7},{"cancer_type":"Seminoma","altered_samples":1,"profiled_samples":63,"frequency_pct":1.6},{"cancer_type":"Pheochromocytoma","altered_samples":1,"profiled_samples":147,"frequency_pct":0.7},{"cancer_type":"Thyroid Cancer","altered_samples":2,"profiled_samples":490,"frequency_pct":0.4}]}
◀ result
{"rows":[{"cancer_study_identifier":"acc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"blca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"brca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"cesc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"chol_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"coadread_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"dlbc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"esca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"gbm_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"hnsc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"kich_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"kirc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"kirp_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"laml_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"lgg_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"lihc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"luad_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"lusc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"meso_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"paad_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"pcpg_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"prad_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"sarc_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"skcm_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"stad_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"tgct_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"thca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"thym_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"ucec_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"ucs_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"uvm_tcga_pan_can_atlas_2018"}]}
═ answer (success)
Here's the breakdown of TP53 mutation frequency by cancer type across the 32 TCGA PanCancer Atlas studies (sample-level, gene-specific profiled denominator, ≥50 profiled samples per type):
| Cancer Type | Altered / Profiled | Frequency |
|---|---|---|
| Ovarian Epithelial Tumor | 373/523 | **71.3%** |
| Head and Neck Cancer | 357/515 | **69.3%** |
| Non-Small Cell Lung Cancer | 699/1050 | **66.6%** |
| Esophagogastric Cancer | 371/618 | **60.0%** |
| Pancreatic Cancer | 107/179 | **59.8%** |
| Colorectal Cancer | 314/534 | **58.8%** |
| Bladder Cancer | 202/410 | **49.3%** |
| Glioma | 249/514 | **48.4%** |
| Endometrial Cancer | 245/574 | **42.7%** |
| Sarcoma | 85/255 | **33.3%** |
| Breast Cancer | 347/1066 | **32.6%** |
| Glioblastoma | 125/397 | **31.5%** |
| Hepatobiliary Cancer | 110/366 | **30.1%** |
| Adrenocortical Carcinoma | 18/91 | **19.8%** |
| Melanoma | 72/440 | **16.4%** |
| Pleural Mesothelioma | 14/86 | **16.3%** |
| Prostate Cancer | 57/494 | **11.5%** |
| Leukemia | 16/200 | **8.0%** |
| Renal Non-Clear Cell Carcinoma | 27/341 | **7.9%** |
| Cervical Cancer | 23/291 | **7.9%** |
| Thymic Epithelial Tumor | 4/123 | **3.3%** |
| Renal Clear Cell Carcinoma | 11/402 | **2.7%** |
| Seminoma | 1/63 | **1.6%** |
| Pheochromocytoma | 1/147 | **0.7%** |
| Thyroid Cancer | 2/490 | **0.4%** |
A few notes:
- **Non-Small Cell Lung Cancer** pools LUAD and LUSC under one TCGA label — LUSC carries the higher TP53 rate, LUAD the lower, so 66.6% is a blended figure. Let me know if you'd like them split.
- TP53 is essentially universal in high-grade serous ovarian cancer and squamous head & neck cancers, and rare in thyroid, kidney clear-cell, and germ cell tumors.
- These frequencies are descriptive counts, not statistical enrichment claims.
You can explore this interactively in cBioPortal:
[TP53 Cancer Types Summary — TCGA PanCancer Atlas](https://www.cbioportal.org/results/cancerTypesSummary?cancer_study_list=acc_tcga_pan_can_atlas_2018%2Cblca_tcga_pan_can_atlas_2018%2Cbrca_tcga_pan_can_atlas_2018%2Ccesc_tcga_pan_can_atlas_2018%2Cchol_tcga_pan_can_atlas_2018%2Ccoadread_tcga_pan_can_atlas_2018%2Cdlbc_tcga_pan_can_atlas_2018%2Cesca_tcga_pan_can_atlas_2018%2Cgbm_tcga_pan_can_atlas_2018%2Chnsc_tcga_pan_can_atlas_2018%2Ckich_tcga_pan_can_atlas_2018%2Ckirc_tcga_pan_can_atlas_2018%2Ckirp_tcga_pan_can_atlas_2018%2Claml_tcga_pan_can_atlas_2018%2Clgg_tcga_pan_can_atlas_2018%2Clihc_tcga_pan_can_atlas_2018%2Cluad_tcga_pan_can_atlas_2018%2Clusc_tcga_pan_can_atlas_2018%2Cmeso_tcga_pan_can_atlas_2018%2Cov_tcga_pan_can_atlas_2018%2Cpaad_tcga_pan_can_atlas_2018%2Cpcpg_tcga_pan_can_atlas_2018%2Cprad_tcga_pan_can_atlas_2018%2Csarc_tcga_pan_can_atlas_2018%2Cskcm_tcga_pan_can_atlas_2018%2Cstad_tcga_pan_can_atlas_2018%2Ctgct_tcga_pan_can_atlas_2018%2Cthca_tcga_pan_can_atlas_2018%2Cthym_tcga_pan_can_atlas_2018%2Cucec_tcga_pan_can_atlas_2018%2Cucs_tcga_pan_can_atlas_2018%2Cuvm_tcga_pan_can_atlas_2018&Action=Submit&gene_list=TP53&tab_index=tab_visualize)
Let me know if you'd like LUAD vs. LUSC split out, or the OncoPrint view for a specific cancer type.