Q (sonnet): "In breast cancer, what is the correlation coefficient between EGFR expression levels and PIK3CA mutation status considering only patients who also have a homozygous deletion of PTEN?"

▶ read_guide
{
 "uri": "cbioportal://statistical-tests-guide"
}

◀ result
Statistical Test Selection Guide
================================

Purpose
-------
This guide ensures the correct statistical test is selected before performing any group comparison, matching cBioPortal's own Group Comparison defaults.

HARD RULES — NEVER FABRICATE A STATISTIC
----------------------------------------
ClickHouse cannot run statistical tests. The agent therefore must NEVER produce a derived statistic that is not a literal column value from a SQL result. Specifically:

1. **Never invent a p-value.** Not "p < 0.001", not "p ≈ 0.05", not any p-value. If the user asks "what is the p-value?", the answer is *"I can't compute that — here is the 2x2 contingency table (or group statistics). Run it in cBioPortal's Group Comparison tab, in R with `fisher.test(...)` / `wilcox.test(...)`, or in Python with `scipy.stats.fisher_exact(...)` / `mannwhitneyu(...)`."*
2. **Never claim mutual exclusivity (or co-occurrence) from a contingency table alone.** A 2x2 table is not a test. The shape "altered/not altered × group A/group B" needs Fisher's exact + a defined direction (odds ratio < 1 with significant p). Without that test, the agent presents the table and stops. Descriptive phrasing is also a claim: "largely/mostly mutually exclusive", "rarely co-occur", "tend to co-occur" are forbidden without the test — point to cBioPortal's Mutual Exclusivity tab instead.
3. **Never report a "median" that came from `AVG(...)` or any non-median aggregate.** "Median" and "mean" are different statistics; for skewed clinical distributions (especially survival) they differ substantially. Use ClickHouse's `quantile(0.5)(...)` for actual median, and label arithmetic averages as "mean", never "median".
4. **Never report a hazard ratio, odds ratio, risk ratio, or relative risk** that wasn't computed by an external tool. These require regression / model fitting that ClickHouse does not do.
5. **Never report median overall survival from `AVG(OS_MONTHS)` or even `quantile(0.5)(OS_MONTHS)`.** Median OS requires Kaplan-Meier estimation, which handles censoring (`OS_STATUS = 0:LIVING` means the event hasn't happened yet). Naive medians/means over `OS_MONTHS` ignore censoring and are systematically wrong. The correct handoff: return the raw `(OS_MONTHS, OS_STATUS)` pairs (or descriptive counts: N events, N censored, follow-up range) and tell the user to run KM in R (`survival::survfit`) or Python (`lifelines.KaplanMeierFitter`), or use cBioPortal's Survival comparison.

If asked to do any of (1)–(5), respond with the appropriate handoff template from the "Approved Response Templates" section below — do not produce the number.

Ambiguous-Term Clarification (before any analysis)
--------------------------------------------------
If the user's question uses an ambiguous term, ask before computing anything. Examples:

- **"aggressive"** → could mean shorter overall survival, higher metastasis rate, higher grade/stage, higher TMB, or specific molecular features. Ask which definit … (9984 more chars)

▶ list_studies
{
 "search": "breast"
}

▶ clickhouse_list_table_columns
{
 "table": "genomic_event_derived"
}

◀ result
{"result":[{"cancer_study_identifier":"msk_met_2021","name":"MSK MetTropism (MSK, Cell 2021)","type_of_cancer_id":"mixed","sample_count":25775,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=msk_met_2021"},{"cancer_study_identifier":"breast_msk_2026","name":"CCNE1 Amplifications in Breast Cancer (MSK, 2026)","type_of_cancer_id":"breast","sample_count":6318,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2026"},{"cancer_study_identifier":"breast_msk_2025","name":"Breast Cancer (MSK, Nat Genet 2025)","type_of_cancer_id":"brca","sample_count":3879,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2025"},{"cancer_study_identifier":"brca_metabric","name":"Breast Cancer (METABRIC, Nature 2012 & Nat Commun 2016)","type_of_cancer_id":"brca","sample_count":2509,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_metabric"},{"cancer_study_identifier":"breast_msk_2018","name":"Breast Cancer (MSK, Cancer Cell 2018)","type_of_cancer_id":"breast","sample_count":1918,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_msk_2018"},{"cancer_study_identifier":"breast_ink4_msk_2021","name":"Metastatic Breast Cancer (MSK, Cancer Discovery 2022)","type_of_cancer_id":"breast","sample_count":1365,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=breast_ink4_msk_2021"},{"cancer_study_identifier":"brca_tcga","name":"Breast Invasive Carcinoma (TCGA, Firehose Legacy)","type_of_cancer_id":"brca","sample_count":1108,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga"},{"cancer_study_identifier":"brca_tcga_gdc","name":"Invasive Breast Carcinoma (TCGA GDC, 2025)","type_of_cancer_id":"brca","sample_count":1102,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_gdc"},{"cancer_study_identifier":"brca_tcga_pan_can_atlas_2018","name":"Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"brca","sample_count":1084,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"brca_tcga_pub","name":"Breast Invasive Carcinoma (TCGA, Nature 2012)","type_of_cancer_id":"brca","sample_count":825,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pub"},{"cancer_study_identifier":"brca_tcga_pub2015","name":"Breast Invasive Carcinoma (TCGA, Cell 2015)","type_of_cancer_id":"brca","sample_count":818,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_tcga_pub2015"},{"cancer_study_identifier":"brca_msk_2025","name":"Breast Carcinoma (MSK, NPJ Precis Oncol 2025)","type_of_cancer_id":"brca","sample_count":527,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=brca_msk_2025"},{"cancer_study_identifier":"brca_mbcproject_2022","name":"The Metastatic Breast Cancer Project (Provisional, December 2021)","type_of_cancer_id":"brca","sample_count":379,"has_gu … (1846 more chars)

◀ 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."}]}

▶ get_study_guide
{
 "study_id": "brca_tcga_pan_can_atlas_2018"
}

▶ clickhouse_list_table_columns
{
 "table": "genetic_alteration_derived"
}

◀ result
# Breast Invasive Carcinoma (TCGA, PanCancer Atlas)

**Study ID:** `brca_tcga_pan_can_atlas_2018`

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

## Study-Specific Attributes

### Molecular Subtypes
| Attribute | Description | Values (patients) |
|-----------|-------------|--------|
| `SUBTYPE` | PAM50 molecular subtype | `BRCA_LumA` 499, `BRCA_LumB` 197, `BRCA_Basal` 171, `BRCA_Her2` 78, `BRCA_Normal` 36, blank 103 |

### Histology
| Attribute | Description | Values (samples) |
|-----------|-------------|--------|
| `CANCER_TYPE_DETAILED` | Histological type | Breast Invasive Ductal Carcinoma 780, Breast Invasive Lobular Carcinoma 201, Breast Invasive Carcinoma (NOS) 77, Breast Invasive Mixed Mucinous Carcinoma 17, Metaplastic Breast Cancer 8, Invasive Breast Carcinoma 1 |

### Not available in this study
- **ER / PR / HER2 receptor status and triple-negative status**: no clinical attribute; say it is not available here. Do not infer receptor status from `SUBTYPE`: PAM50 is an expression-based classification, not IHC/FISH. If the user accepts an expression-based proxy, `BRCA_Basal` (≈ triple-negative) or `BRCA_Her2` can be offered, labelled as PAM50. ERBB2 amplification is available from CNA data.
- `GRADE` is blank for all samples.

## Key Genes
- **TP53**: Most frequently mutated (~30%)
- **PIK3CA**: Common in ER+ tumors (~35%)
- **CDH1**: Enriched in lobular carcinoma
- **GATA3**: Luminal marker
- **ERBB2**: HER2 amplification target

## Notes
- Molecular subtypes (PAM50) correlate strongly with clinical behavior
- Lobular vs ductal distinction has different mutation profiles


◀ result
{"columns":[{"name":"sample_unique_id","type":"String"},{"name":"cancer_study_identifier","type":"LowCardinality(String)"},{"name":"hugo_gene_symbol","type":"String"},{"name":"profile_type","type":"LowCardinality(String)"},{"name":"alteration_value","type":"Nullable(String)"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT DISTINCT profile_type
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'brca_tcga_pan_can_atlas_2018'
  AND hugo_gene_symbol = 'EGFR'
"
}

◀ result
{"rows":[{"profile_type":"gistic"},{"profile_type":"log2CNA"},{"profile_type":"protein_quantification"},{"profile_type":"protein_quantification_zscores"},{"profile_type":"rna_seq_v2_mrna"},{"profile_type":"rna_seq_v2_mrna_median_Zscores"},{"profile_type":"rna_seq_v2_mrna_median_all_sample_Zscores"},{"profile_type":"rna_seq_v2_mrna_median_all_sample_ref_normal_Zscores"},{"profile_type":"rppa"},{"profile_type":"rppa_Zscores"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT sample_unique_id
FROM genomic_event_derived
WHERE cancer_study_identifier = 'brca_tcga_pan_can_atlas_2018'
  AND hugo_gene_symbol = 'PTEN'
  AND variant_type = 'cna'
  AND cna_alteration = -2
"
}

◀ result
{"rows":[{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0CL-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0D2-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0T0-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0T2-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0YE-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A3Y0-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A4RW-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A0CJ-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A13H-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A4SA-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A4SD-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A6VV-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A08I-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A09M-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A0A2-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0AR-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0AT-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0XU-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A03N-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0J2-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0J6-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0JD-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AQ-A04J-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A0U0-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A0U1-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A1AR-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A1AY-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A2LO-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-B6-A0RU-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-BH-A0B3-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-BH-A0BW-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-BH-A18T-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-BH-A1EO-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-BH-A8G0-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-C8-A134-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-C8-A1HM-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-D8-A1JC-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-D8-A27I-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-D8-A3Z6-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-E2-A14N-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-E2-A159-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-E2-A1IJ-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-E2-A1LK-01"},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-E2-A573-01"} … (750 more chars)

▶ clickhouse_run_select_query
{
 "query": "
WITH pten_homdel AS (
  SELECT DISTINCT sample_unique_id
  FROM genomic_event_derived
  WHERE cancer_study_identifier = 'brca_tcga_pan_can_atlas_2018'
    AND hugo_gene_symbol = 'PTEN'
    AND variant_type = 'cna'
    AND cna_alteration = -2
),
egfr_expr AS (
  SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS egfr_zscore
  FROM genetic_alteration_derived
  WHERE cancer_study_identifier = 'brca_tcga_pan_can_atlas_2018'
    AND hugo_gene_symbol = 'EGFR'
    AND profile_type = 'rna_seq_v2_mrna_median_Zscores'
),
pik3ca_mut AS (
  SELECT DISTINCT sample_unique_id
  FROM genomic_event_derived
  WHERE cancer_study_identifier = 'brca_tcga_pan_can_atlas_2018'
    AND hugo_gene_symbol = 'PIK3CA'
    AND variant_type = 'mutation'
    AND mutation_status != 'UNCALLED'
)
SELECT
  p.sample_unique_id AS sample_unique_id,
  e.egfr_zscore AS egfr_zscore,
  if(m.sample_unique_id != '', 1, 0) AS pik3ca_mutated
FROM pten_homdel p
LEFT JOIN egfr_expr e ON p.sample_unique_id = e.sample_unique_id
LEFT JOIN pik3ca_mut m ON p.sample_unique_id = m.sample_unique_id
ORDER BY sample_unique_id
"
}

◀ result
{"rows":[{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0CL-01","egfr_zscore":0.0322,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0D2-01","egfr_zscore":-0.2218,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0T0-01","egfr_zscore":0.0914,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0T2-01","egfr_zscore":0.4474,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A0YE-01","egfr_zscore":7.1334,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A3Y0-01","egfr_zscore":0.2332,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A2-A4RW-01","egfr_zscore":-0.0493,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A0CJ-01","egfr_zscore":-0.5467,"pik3ca_mutated":1},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A13H-01","egfr_zscore":-0.1394,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A4SA-01","egfr_zscore":-0.073,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A4SD-01","egfr_zscore":1.1036,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A7-A6VV-01","egfr_zscore":1.0345,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A08I-01","egfr_zscore":-0.354,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A09M-01","egfr_zscore":-0.5852,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-A8-A0A2-01","egfr_zscore":-0.4245,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0AR-01","egfr_zscore":-0.3373,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0AT-01","egfr_zscore":0.2095,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AN-A0XU-01","egfr_zscore":1.8346,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A03N-01","egfr_zscore":-0.427,"pik3ca_mutated":1},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0J2-01","egfr_zscore":0.5432,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0J6-01","egfr_zscore":0.2411,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AO-A0JD-01","egfr_zscore":-0.3757,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AQ-A04J-01","egfr_zscore":1.0851,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A0U0-01","egfr_zscore":1.1473,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A0U1-01","egfr_zscore":0.0917,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A1AR-01","egfr_zscore":1.8488,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A1AY-01","egfr_zscore":1.1521,"pik3ca_mutated":0},{"sample_unique_id":"brca_tcga_pan_can_atlas_2018_TCGA-AR-A2LO-01", … (2980 more chars)

▶ navigate_to_results_view
{
 "studyIds": [
  "brca_tcga_pan_can_atlas_2018"
 ],
 "genes": [
  "EGFR",
  "PIK3CA",
  "PTEN"
 ],
 "tab": "plots",
 "studyViewFilter": {
  "genomicDataFilters": [
   {
    "hugoGeneSymbol": "PTEN",
    "profileType": "gistic",
    "values": [
     {
      "value": "-2"
     }
    ]
   }
  ]
 },
 "plotsHorzSelection": {
  "dataType": "MUTATION_EXTENDED",
  "selectedGeneOption": "PIK3CA",
  "mutationCountBy": "MutationType"
 },
 "plotsVertSelection": {
  "dataType": "mrna",
  "selectedGeneOption": "EGFR",
  "selectedDataSourceOption": "rna_seq_v2_mrna_median_Zscores"
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/plots?session_id=6ab5c0e2e497aad53593c25b","url":"https://www.cbioportal.org/results/plots?session_id=6ab5c0e2e497aad53593c25b","data":{"studyIds":["brca_tcga_pan_can_atlas_2018"],"studies":[{"studyId":"brca_tcga_pan_can_atlas_2018","name":"Breast Invasive Carcinoma (TCGA, PanCancer Atlas)","sampleCount":1084}],"genes":["EGFR","PIK3CA","PTEN"],"filteredSampleCount":55,"caseSetId":"-1","sessionId":"6ab5c0e2e497aad53593c25b","studyViewUrl":"https://www.cbioportal.org/study?id=brca_tcga_pan_can_atlas_2018#filterJson=%7B%22genomicDataFilters%22%3A%5B%7B%22hugoGeneSymbol%22%3A%22PTEN%22%2C%22profileType%22%3A%22gistic%22%2C%22values%22%3A%5B%7B%22value%22%3A%22-2%22%7D%5D%7D%5D%7D","pageDescription":"Scatter/box plots: EGFR mrna (y-axis) by PIK3CA mutation (x-axis)."}}

═ answer (success)
This opens the pre-filtered cohort (PTEN homozygous deletion) directly in cBioPortal's Plots tab, with EGFR mRNA expression on the y-axis and PIK3CA mutation status on the x-axis. cBioPortal's Plots tab does not compute a correlation coefficient for a categorical-vs-continuous axis pairing, but it will render the box/scatter plot distributions per group for visual inspection.

**[View EGFR expression vs. PIK3CA mutation status, PTEN-HOMDEL cohort](https://www.cbioportal.org/results/plots?session_id=6ab5c0e2e497aad53593c25b)**
Scatter/box plots: EGFR mRNA (y-axis) by PIK3CA mutation status (x-axis). 55 samples matched the PTEN deep-deletion filter (near-identical to the 54 in my direct query; likely differ by panel/profiling overlap).

**[View PTEN-HOMDEL cohort in Study View](https://www.cbioportal.org/study?id=brca_tcga_pan_can_atlas_2018#filterJson=%7B%22genomicDataFilters%22%3A%5B%7B%22hugoGeneSymbol%22%3A%22PTEN%22%2C%22profileType%22%3A%22gistic%22%2C%22values%22%3A%5B%7B%22value%22%3A%22-2%22%7D%5D%7D%5D%7D)** — for exploring clinical/genomic characteristics of this subgroup.