Q (haiku): What is the correlation coefficient between EGFR copy number and EGFR mRNA expression in ovarian cancer?

▶ read_guide
{
 "uri": "cbioportal://faq-guide"
}

▶ list_guides
{}

◀ result
# cBioPortal FAQ Guide

Curated answers to frequently asked general questions about cBioPortal. Source: [cBioPortal FAQ](https://docs.cbioportal.org/user-guide/faq/).

## What is cBioPortal?

cBioPortal for Cancer Genomics is an open-access, open-source resource for interactive exploration of multidimensional cancer genomics data sets. It was originally developed at Memorial Sloan Kettering Cancer Center (MSK) and is now maintained by a multi-institutional team.

## History

- **2008**: cBioPortal first became available online.
- **2012**: First major publication — Cerami et al., *Cancer Discovery*.
- **2013**: Second major publication — Gao et al., *Science Signaling*.
- **2023**: Third major publication — de Bruijn et al., *Cancer Research*.

## How to Cite cBioPortal

When using cBioPortal in publications, cite these three papers:

1. Cerami et al. "The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data." *Cancer Discovery* 2, 401–404 (2012). doi:10.1158/2159-8290.CD-12-0095
2. Gao et al. "Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal." *Science Signaling* 6, pl1 (2013). doi:10.1126/scisignal.2004088
3. de Bruijn et al. "Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal." *Cancer Research* 83, 3861–3867 (2023). doi:10.1158/0008-5472.CAN-23-0816

Also cite the specific study publication(s) whose data you used.

## What Data Types Does cBioPortal Contain?

- **Mutations** (non-synonymous somatic mutations)
- **DNA copy-number alterations** (CNA) from GISTIC or other methods
- **mRNA expression** data (RNA-seq, microarray)
- **Protein/phosphoprotein** levels (RPPA, mass spectrometry)
- **DNA methylation** data
- **Structural variants** (gene fusions, rearrangements)
- **Clinical data** (demographics, diagnosis, treatment, outcomes)

Note: Synonymous mutations are not included in cBioPortal.

## Data Types Usually Not Stored Directly

cBioPortal generally does not store:

- raw CT, MRI, pathology-slide, or histology image files
- raw sequencing files such as BAM, CRAM, or FASTQ
- polygenic risk scores as a standard data type
- full external clinical-trial databases

However, this deployment may contain links to external viewers or portals through `resource_*` tables. For imaging, pathology, Minerva, HTAN, or viewer questions, read `cbioportal://external-resources-guide` and check those tables before saying the data is absent.

## What the MCP Agent Can and Cannot Produce

The MCP agent can:

- query cBioPortal data and return tables in text/JSON/Markdown
- summarize counts, frequencies, and available attributes
- provide cBioPortal study links and DataHub download links when applicable
- provide SQL snippets or handoff instructions for R/Python/cBioPortal tools

The MCP agent should not promise to:

- render Kaplan-Meier plots or other visual figures directly
- export large … (6558 more chars)

◀ 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://gene-expression-guide"
}

▶ search_oncotree
{
 "search_term": "ovarian cancer"
}

◀ result
# Gene Expression Analysis Guide

This guide covers continuous-value genomic data: gene **expression**, **copy number** values, **methylation**, and related profile types. Mutation/CNA/SV *frequency* analysis lives in `cbioportal://mutation-frequency-guide`.

## Where this data lives

Continuous per-sample-per-gene values are stored in `genetic_alteration_derived`:

| Column | Description |
|---|---|
| `sample_unique_id` | `<study>_<sample_stable_id>` |
| `cancer_study_identifier` | study scope |
| `hugo_gene_symbol` | gene |
| `profile_type` | which assay/normalization (see below) |
| `alteration_value` | the actual value — stored as Nullable(String); cast with `toFloat64OrNull` |

`alteration_value` is a string because the same column hosts many different value scales. The `''` and `'NA'` sentinels mean "missing"; always filter them out and use `toFloat64OrNull(alteration_value) IS NOT NULL` for downstream math.

## Discovering profile types for a study

Different studies expose different profile types depending on what assays were run and how the data was normalized. Always check what a specific study supports before picking one:

```sql
SELECT DISTINCT profile_type
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'brca_metabric'
ORDER BY profile_type;
```

Common values across the public portal:

| Family | Profile types |
|---|---|
| mRNA expression | `mrna`, `mrna_median_Zscores`, `mrna_seq_v2_rsem`, `mrna_seq_v2_rsem_Zscores`, `mrna_seq_cpm`, `mrna_seq_fpkm`, `mrna_U133`, `mrna_outliers` |
| Copy number (continuous) | `cna`, `linear_CNA`, `log2CNA`, `cna_consensus`, `cna_rae`, `gistic` |
| Methylation | `methylation_hm27`, `methylation_hm450`, `methylation_epic`, `methylation_promoters_rrbs` |
| miRNA | `mirna`, `mirna_median_Zscores` |
| Protein | `protein_quantification`, `protein_level`, `RPPA` |

**Z-score vs raw choice.** When the user asks "is X correlated with Y", either works for Spearman (rank-based) — Pearson would care. Default to the non-Z-score variant if both exist, and call out which one in the response.

## Canonical recipe — Spearman correlation between two genes

```sql
SELECT *
FROM gene_pair_coexpression(
    study        = 'brca_metabric',
    gene_a       = 'TP53',
    gene_b       = 'MYC',
    profile_type = 'mrna'
);
```

Returns one row: `(gene_a, gene_b, profile_type, spearman_correlation, num_samples)`.

- `spearman_correlation` in [−1, 1]; `NULL` when fewer than 3 valid paired samples.
- Mirrors cbioportal-backend's `ClickhouseCoExpressionMapper.getCoExpressions`, simplified to a pair lookup (the backend computes one ref gene vs ALL other genes for the coexpression page; here the agent asks about a specific pair).

### Verified examples

| Study | gene_a | gene_b | profile_type | spearman | n |
|---|---|---|---|---|---|
| `brca_metabric` | TP53 | MYC | `mrna` | 0.118 | 1980 |
| `brca_metabric` | ESR1 | PGR | `mrna` | 0.487 | 1980 |

ESR1↔PGR is the textbook breast-cancer estrogen-receptor coregula … (2785 more chars)

◀ result
{"result":[{"code":"BTBEOV","name":"Brenner Tumor, Benign","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > BTOV > BTBEOV"},{"code":"BTBOV","name":"Brenner Tumor, Borderline","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > BTOV > BTBOV"},{"code":"BTMOV","name":"Brenner Tumor, Malignant","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > BTOV > BTMOV"},{"code":"BTOV","name":"Brenner Tumor","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > BTOV"},{"code":"CCBOV","name":"Clear Cell Borderline Ovarian Tumor","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > CCBOV"},{"code":"CCOV","name":"Clear Cell Ovarian Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > CCOV"},{"code":"EBOV","name":"Endometrioid Borderlin Ovarian Tumor","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > EBOV"},{"code":"EOV","name":"Endometrioid Ovarian Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > EOV"},{"code":"HGONEC","name":"High-Grade Neuroendocrine Carcinoma of the Ovary","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OOVC > HGONEC"},{"code":"HGSFT","name":"High-Grade Serous Fallopian Tube Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OOVC > HGSFT"},{"code":"HGSOC","name":"High-Grade Serous Ovarian Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > SOC > HGSOC"},{"code":"LGSOC","name":"Low-Grade Serous Ovarian Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > SOC > LGSOC"},{"code":"MBOV","name":"Mucinous Borderline Ovarian Tumor","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > MBOV"},{"code":"MOV","name":"Mucinous Ovarian Cancer","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > MOV"},{"code":"MXOV","name":"Mixed Ovarian Carcinoma","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > MXOV"},{"code":"OCNOS","name":"Ovarian Choriocarcinoma, NOS","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OOVC > OCNOS"},{"code":"OCS","name":"Ovarian Carcinosarcoma/Malignant Mixed Mesodermal Tumor","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OVT > OCS"},{"code":"OOVC","name":"Ovarian Cancer, Other","score":65,"mainType":"Ovarian Cancer","tissue":"Ovary/Fallopian Tube","hierarchy":"OVARY > OOVC"},{"code":"OSMAD","name":"Ovarian Seromucinous Adenoma","score":65 … (1077 more chars)

▶ list_studies
{
 "search": "ovarian",
 "limit": 20
}

◀ 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":"ov_tcga","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Firehose Legacy)","type_of_cancer_id":"hgsoc","sample_count":617,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga"},{"cancer_study_identifier":"hgsoc_tcga_gdc","name":"High-Grade Serous Ovarian Cancer (TCGA GDC, 2025)","type_of_cancer_id":"hgsoc","sample_count":604,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=hgsoc_tcga_gdc"},{"cancer_study_identifier":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","type_of_cancer_id":"hgsoc","sample_count":585,"has_guide":true,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga_pan_can_atlas_2018"},{"cancer_study_identifier":"ovary_geomx_gray_foundation_2024","name":"Ovarian Cancer (Gray Foundation, Cancer Discov 2024)","type_of_cancer_id":"ovary","sample_count":567,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovary_geomx_gray_foundation_2024"},{"cancer_study_identifier":"ov_tcga_pub","name":"Ovarian Serous Cystadenocarcinoma (TCGA, Nature 2011)","type_of_cancer_id":"hgsoc","sample_count":489,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ov_tcga_pub"},{"cancer_study_identifier":"lgsoc_mapk_msk_2022","name":"Low-Grade Serous Ovarian Cancer (MSK, Clin Cancer Res 2022)","type_of_cancer_id":"lgsoc","sample_count":119,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=lgsoc_mapk_msk_2022"},{"cancer_study_identifier":"ovary_cptac_gdc","name":"Ovarian Cancer (CPTAC GDC, 2025)","type_of_cancer_id":"ovary","sample_count":112,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovary_cptac_gdc"},{"cancer_study_identifier":"msk_spectrum_tme_2022","name":"Ovarian Cancer - MSK SPECTRUM (MSK, Nature 2022)","type_of_cancer_id":"ovary","sample_count":82,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=msk_spectrum_tme_2022"},{"cancer_study_identifier":"hgsoc_msk_2021","name":"High-Grade Serous Ovarian Cancer (MSK, NPJ Genome Med 2021)","type_of_cancer_id":"hgsoc","sample_count":45,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=hgsoc_msk_2021"},{"cancer_study_identifier":"ucec_msk_2024","name":"Endometrial and Ovarian Cancer (MSK, Nature Medicine 2024)","type_of_cancer_id":"mixed","sample_count":33,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ucec_msk_2024"},{"cancer_study_identifier":"ovarian_msk_2025","name":"Serous Ovarian Cancer (MSK, 2025)","type_of_cancer_id":"ovary","sample_count":31,"has_guide":false,"url":"https://www.cbioportal.org/study/summary?id=ovarian_msk_2025"},{"cancer_study_identifier":"mixed_msk_tcga_2021","name":"RAD51B Associated Mixed Cancers (MSK, N … (162 more chars)

▶ clickhouse_run_select_query
{
 "query": "
SELECT DISTINCT profile_type
FROM genetic_alteration_derived
WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
ORDER BY profile_type;
",
 "max_rows": 50
}

◀ 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":"rppa"},{"profile_type":"rppa_Zscores"}]}

▶ clickhouse_run_select_query
{
 "query": "
SELECT *
FROM gene_pair_coexpression(
    study        = 'ov_tcga_pan_can_atlas_2018',
    gene_a       = 'EGFR',
    gene_b       = 'EGFR',
    profile_type_a = 'gistic',
    profile_type_b = 'rna_seq_v2_mrna'
);
",
 "max_rows": 10
}

◀ result
{"error_message":"Query execution failed: HTTPDriver for https://dl96orhu96.us-east-1.aws.clickhouse.cloud:8443 received ClickHouse error code 456\n Code: 456. DB::Exception: Substitution `profile_type` is not set. (UNKNOWN_QUERY_PARAMETER) (version 26.4.1.2359 (official build))\n"}

▶ clickhouse_run_select_query
{
 "query": "
WITH cna AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS cna_value
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND profile_type = 'gistic'
      AND hugo_gene_symbol = 'EGFR'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
),
mrna AS (
    SELECT sample_unique_id, toFloat64OrNull(alteration_value) AS mrna_value
    FROM genetic_alteration_derived
    WHERE cancer_study_identifier = 'ov_tcga_pan_can_atlas_2018'
      AND profile_type = 'rna_seq_v2_mrna'
      AND hugo_gene_symbol = 'EGFR'
      AND alteration_value NOT IN ('', 'NA')
      AND toFloat64OrNull(alteration_value) IS NOT NULL
)
SELECT 
    rankCorr(cna.cna_value, mrna.mrna_value) AS spearman_correlation,
    count() AS num_samples
FROM cna INNER JOIN mrna USING (sample_unique_id);
",
 "max_rows": 10
}

◀ result
{"rows":[{"spearman_correlation":0.41079748894518875,"num_samples":295}]}

▶ resolve_and_route
{
 "studyIds": [
  "ov_tcga_pan_can_atlas_2018"
 ]
}

◀ result
{"success":true,"message":"Found 1 study. Use the metadata to call the appropriate navigation tool(s).","data":{"totalCount":1,"studiesWithMetadata":[{"studyId":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","sampleCount":585,"studyViewUrl":"https://www.cbioportal.org/study?id=ov_tcga_pan_can_atlas_2018","metadata":{"clinicalAttributeIds":["AGE","AJCC_PATHOLOGIC_TUMOR_STAGE","AJCC_STAGING_EDITION","ANEUPLOIDY_SCORE","BUFFA_HYPOXIA_SCORE","CANCER_TYPE","CANCER_TYPE_ACRONYM","CANCER_TYPE_DETAILED","DAYS_LAST_FOLLOWUP","DAYS_TO_BIRTH","DAYS_TO_INITIAL_PATHOLOGIC_DIAGNOSIS","DFS_MONTHS","DFS_STATUS","DSS_MONTHS","DSS_STATUS","ETHNICITY","FORM_COMPLETION_DATE","FRACTION_GENOME_ALTERED","GENETIC_ANCESTRY_LABEL","GRADE","HISTORY_NEOADJUVANT_TRTYN","ICD_10","ICD_O_3_HISTOLOGY","ICD_O_3_SITE","INFORMED_CONSENT_VERIFIED","IN_PANCANPATHWAYS_FREEZE","MSI_SCORE_MANTIS","MSI_SENSOR_SCORE","MUTATION_COUNT","NEW_TUMOR_EVENT_AFTER_INITIAL_TREATMENT","ONCOTREE_CODE","OS_MONTHS","OS_STATUS","OTHER_PATIENT_ID","PATH_M_STAGE","PATH_N_STAGE","PATH_T_STAGE","PERSON_NEOPLASM_CANCER_STATUS","PFS_MONTHS","PFS_STATUS","PRIMARY_LYMPH_NODE_PRESENTATION_ASSESSMENT","PRIOR_DX","RACE","RADIATION_THERAPY","RAGNUM_HYPOXIA_SCORE","SAMPLE_COUNT","SAMPLE_TYPE","SEX","SOMATIC_STATUS","SUBTYPE","TBL_SCORE","TISSUE_PROSPECTIVE_COLLECTION_INDICATOR","TISSUE_RETROSPECTIVE_COLLECTION_INDICATOR","TISSUE_SOURCE_SITE","TISSUE_SOURCE_SITE_CODE","TMB_NONSYNONYMOUS","TUMOR_TISSUE_SITE","TUMOR_TYPE","WEIGHT","WINTER_HYPOXIA_SCORE"],"molecularProfileIds":["ov_tcga_pan_can_atlas_2018_gistic","ov_tcga_pan_can_atlas_2018_log2CNA","ov_tcga_pan_can_atlas_2018_mutations","ov_tcga_pan_can_atlas_2018_protein_quantification","ov_tcga_pan_can_atlas_2018_protein_quantification_zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ov_tcga_pan_can_atlas_2018_rppa","ov_tcga_pan_can_atlas_2018_rppa_Zscores","ov_tcga_pan_can_atlas_2018_structural_variants"],"genericAssayProfiles":["ov_tcga_pan_can_atlas_2018_armlevel_cna","ov_tcga_pan_can_atlas_2018_genetic_ancestry","ov_tcga_pan_can_atlas_2018_methylation_hm27_hm450_merge","ov_tcga_pan_can_atlas_2018_methylation_hm450","ov_tcga_pan_can_atlas_2018_phosphoprotein_quantification"],"heatmapProfileIds":["ov_tcga_pan_can_atlas_2018_protein_quantification_zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_Zscores","ov_tcga_pan_can_atlas_2018_rna_seq_v2_mrna_median_all_sample_Zscores","ov_tcga_pan_can_atlas_2018_rppa_Zscores"],"availableComparisonTabs":["overlap","clinical","survival","alterations","mutations","mrna","protein","generic_assay_armlevel_cna","generic_assay_genetic_ancestry","generic_assay_methylation","generic_assay_phosphosite_quantification"]}}]}}

▶ navigate_to_results_view
{
 "studyIds": [
  "ov_tcga_pan_can_atlas_2018"
 ],
 "genes": [
  "EGFR"
 ],
 "tab": "plots",
 "plotsHorzSelection": {
  "selectedGeneOption": "EGFR",
  "dataType": "log2CNA"
 },
 "plotsVertSelection": {
  "selectedGeneOption": "EGFR",
  "dataType": "mRNA_expression"
 }
}

◀ result
{"success":true,"message":"Navigating to https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=EGFR&case_set_id=ov_tcga_pan_can_atlas_2018_all&plots_horz_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22log2CNA%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22mRNA_expression%22%7D","url":"https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=EGFR&case_set_id=ov_tcga_pan_can_atlas_2018_all&plots_horz_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22log2CNA%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22mRNA_expression%22%7D","data":{"studyIds":["ov_tcga_pan_can_atlas_2018"],"studies":[{"studyId":"ov_tcga_pan_can_atlas_2018","name":"Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)","sampleCount":585}],"genes":["EGFR"],"caseSetId":"ov_tcga_pan_can_atlas_2018_all","pageDescription":"Scatter/box plots: EGFR mrna_expression (y-axis) by EGFR log2cna (x-axis)."}}

═ answer (success)
Perfect! Here are your results:

## EGFR Copy Number vs mRNA Expression in Ovarian Cancer

**Spearman Correlation Coefficient: 0.411** (95 samples with paired data)

This represents a **moderate positive correlation** between EGFR copy number (GISTIC) and EGFR mRNA expression in 295 samples from the TCGA PanCancer Atlas ovarian cancer cohort. The correlation is statistically meaningful, indicating that samples with higher EGFR copy number tend to have higher EGFR mRNA expression.

### Study Details
- **Study:** Ovarian Serous Cystadenocarcinoma (TCGA, PanCancer Atlas)
- **Samples profiled:** 295 (with both EGFR copy number and mRNA data)
- **Total study samples:** 585
- **Copy number data:** GISTIC-normalized
- **Expression data:** RNA-seq v2 (counts)

### Visualization
[View EGFR copy number vs mRNA expression plots](https://www.cbioportal.org/results/plots?cancer_study_list=ov_tcga_pan_can_atlas_2018&gene_list=EGFR&case_set_id=ov_tcga_pan_can_atlas_2018_all&plots_horz_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22log2CNA%22%7D&plots_vert_selection=%7B%22selectedGeneOption%22%3A%221956%22%2C%22dataType%22%3A%22mRNA_expression%22%7D)

The Plots tab shows an interactive scatter plot with EGFR copy number on the x-axis and mRNA expression on the y-axis, allowing you to explore the relationship visually and filter by clinical attributes.