{"id":"pdc-cptac-stad-study","title":"CPTAC STAD Study","short_title":"PDC000622","aliases":["CPTAC STAD Study - Acetylome","CPTAC STAD Study - DIA Ubiquitylome","CPTAC STAD Study - Glycoproteome","CPTAC STAD Study - Metabolome","CPTAC STAD Study - Phosphoproteome","CPTAC STAD Study - Protein-protein Interaction","CPTAC STAD Study - Proteome"],"summary":"The CPTAC gastric cancer study is the most extensively measured cohort indexed here. Four of its seven layers - acetylome, glycoproteome, ubiquitylome and metabolome - exist in fewer than twenty NCI cohorts each, and the combination on a single set of 193 tumors exists nowhere else. Ubiquitylation data on 184 cases is particularly scarce: only five studies in the entire Proteomic Data Commons carry it.\nIt is also a clear illustration of why reuse measurement is hard. All of it is openly downloadable with no account, and yet a literature search for its accession finds almost nothing - because authors cite the marker paper, not the PDC study identifier. The absence of citation evidence here says more about how proteomics data are referenced than about whether anyone has used them.","one_liner":"193 gastric cancers measured seven ways - proteome, phosphoproteome, acetylome, glycoproteome, ubiquitylome, metabolome and protein-protein interaction - the deepest single-cohort molecular characterization in the NCI portfolio, and openly downloadable.","identifiers":[{"scheme":"pdc_study_id","value":"PDC000622","url":"https://pdc.cancer.gov/pdc/study/PDC000622","is_primary":true,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000616","url":"https://pdc.cancer.gov/pdc/study/PDC000616","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000621","url":"https://pdc.cancer.gov/pdc/study/PDC000621","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000615","url":"https://pdc.cancer.gov/pdc/study/PDC000615","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000626","url":"https://pdc.cancer.gov/pdc/study/PDC000626","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000614","url":"https://pdc.cancer.gov/pdc/study/PDC000614","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"scheme":"pdc_study_id","value":"PDC000617","url":"https://pdc.cancer.gov/pdc/study/PDC000617","is_primary":false,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]}],"repository":{"name":"NCI Proteomic Data 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Cancer; primary_sites: Stomach","confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Repository disease labels or primary sites mapped to pinned tissues."}]},"is_pediatric":null,"model_systems":[],"cohort":{"n_cases":193,"n_samples":null,"n_aliquots":1579,"n_files":null,"total_bytes":null,"n_tumor_cases":null,"n_normal_cases":null,"has_matched_normal":null,"demographics":{"sex":{"male":101,"female":70,"not reported":22},"race":{"white":151,"not reported":28,"other":13,"black or african american":1},"ethnicity":{"not reported":192,"not hispanic or latino":1},"age_at_diagnosis_years":{"n":165.0,"min":32.1,"median":68.9,"max":87.6},"vital_status":{"Alive":147,"Not Reported":22,"Dead":18},"country_or_region":{},"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T04:11:17.290636Z","snippet":null,"locator":"PDC000622: clinicalPerStudy demographic 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clinicalPerStudy","retrieved_at":"2026-09-19T04:11:17.290636Z","snippet":null,"locator":"PDC000622: clinicalPerStudy, field days_to_recurrence; a value for 4 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"name":"pdc:treatments.treatment_type","harmonized_name":"diagnoses.treatments.treatment_type","label":"Treatment type","category":"treatment","n_nonmissing":101,"n_not_reported":null,"n_informative":null,"n_total":193,"coverage_pct":null,"populated_pct":52.3,"is_repeated":false,"example_values":["Chemotherapy","Radiation Therapy, NOS","Immunotherapy (Including Vaccines)"],"unit":null,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T03:19:40.475725Z","snippet":null,"locator":"PDC000622: paginatedCaseTreatmentsPerStudy, field treatment_type; informative for 101 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"name":"pdc:treatments.therapeutic_agents","harmonized_name":"diagnoses.treatments.therapeutic_agents","label":"Therapeutic agents","category":"treatment","n_nonmissing":62,"n_not_reported":null,"n_informative":null,"n_total":193,"coverage_pct":null,"populated_pct":32.1,"is_repeated":false,"example_values":["Fluorouracil","Cisplatin","Oxaliplatin","Docetaxel","Capecitabine","Paclitaxel"],"unit":null,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T03:19:40.475725Z","snippet":null,"locator":"PDC000622: paginatedCaseTreatmentsPerStudy, field therapeutic_agents; informative for 62 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"name":"pdc:treatments.treatment_outcome","harmonized_name":"diagnoses.treatments.treatment_outcome","label":"Treatment outcome","category":"treatment","n_nonmissing":96,"n_not_reported":null,"n_informative":null,"n_total":193,"coverage_pct":null,"populated_pct":49.7,"is_repeated":false,"example_values":["Complete Response","Progressive Disease","Partial Response","Stable Disease"],"unit":null,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T03:19:40.475725Z","snippet":null,"locator":"PDC000622: paginatedCaseTreatmentsPerStudy, field treatment_outcome; informative for 96 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"name":"pdc:treatments.regimen_or_line_of_therapy","harmonized_name":"diagnoses.treatments.regimen_or_line_of_therapy","label":"Regimen or line of therapy","category":"treatment","n_nonmissing":0,"n_not_reported":null,"n_informative":null,"n_total":193,"coverage_pct":null,"populated_pct":0.0,"is_repeated":false,"example_values":[],"unit":null,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T03:19:40.475725Z","snippet":null,"locator":"PDC000622: paginatedCaseTreatmentsPerStudy, field regimen_or_line_of_therapy; informative for 0 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},{"name":"pdc:treatments.treatment_or_therapy","harmonized_name":"diagnoses.treatments.treatment_or_therapy","label":"Treatment given","category":"treatment","n_nonmissing":0,"n_not_reported":null,"n_informative":null,"n_total":193,"coverage_pct":null,"populated_pct":0.0,"is_repeated":false,"example_values":[],"unit":null,"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T03:19:40.475725Z","snippet":null,"locator":"PDC000622: paginatedCaseTreatmentsPerStudy, field treatment_or_therapy; informative for 0 of 193 cases","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]}],"longitudinal":{"has_followup":true,"has_survival_endpoint":true,"survival_endpoints":["overall survival"],"median_followup_months":24.5,"max_followup_months":49.9,"n_cases_with_followup":157,"has_serial_samples":null,"timepoints":[],"n_cases_with_serial":null,"has_treatment_response":true,"response_criteria":["Complete Response","Partial Response","Progressive Disease","Stable Disease"],"evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL clinicalPerStudy","retrieved_at":"2026-09-19T04:11:17.290636Z","snippet":null,"locator":"PDC000622: computed from 193 cases: 18 deaths, 157 with a follow-up time, progression informative for 0","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},"access":{"tier":"open","open_components":["7 analytical fraction studies"],"controlled_components":[],"mechanism":"Direct download from the PDC portal or its API; no account required","dua_url":null,"data_access_committee":null,"typical_turnaround":null,"embargo_until":null,"login_required":false,"citation_requirement":"Cite the PDC study identifier and the study's primary publication; PDC asks that the consortium be acknowledged.","license":"Open access under the PDC data use terms","publication_policy_url":"https://pdc.cancer.gov/pdc/data-use-guidelines","evidence":[{"method":"api","source_url":"https://proteomic.datacommons.cancer.gov/graphql","source_label":"PDC GraphQL allPrograms","retrieved_at":"2026-09-18T02:36:15.354973Z","snippet":null,"locator":"7 fraction studies grouped by cohort name","confidence":"high","reviewer":null,"reviewed_at":null,"note":null}]},"useful_for":[{"question":"How do distinct post-translational modification layers diverge from each other and from transcript abundance on the same tumors?","rationale":"Phosphorylation, acetylation, glycosylation and ubiquitylation are measured on largely the same 184 to 193 tumors. Comparing regulation across four modification types on one cohort is an analysis this dataset uniquely enables; almost every other resource offers at most two.","required_fields":[],"required_modalities":["proteome","phosphoproteome","acetylproteome","glycoproteome","ubiquitylome"],"feasibility":"direct","approx_n":184,"statistical_note":"Each layer has its own missingness pattern from mass spectrometry. Do not impute across layers; restrict to features quantified in a pre-specified fraction of samples and report that threshold.","exemplar_pmid":null,"topics":["post-translational-modification","proteogenomics","gastric"],"evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"question":"Does protein degradation signaling, read from the ubiquitylome, identify tumor subgroups invisible to transcriptomics?","rationale":"Ubiquitylome data on 184 cases is among the largest such datasets anywhere. Degradation is a major regulatory axis that expression data cannot see, and a cohort this size makes subgroup discovery feasible rather than anecdotal.","required_fields":[],"required_modalities":["ubiquitylome","proteome"],"feasibility":"direct","approx_n":184,"statistical_note":"Ubiquitylation site quantification is sparser than proteome quantification; expect to lose a substantial fraction of sites to the completeness filter.","exemplar_pmid":null,"topics":["protein-degradation","subtype-discovery"],"evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"question":"How does tumor metabolism, measured directly rather than inferred, relate to signaling state?","rationale":"Metabolomics on 187 cases is available alongside the phosphoproteome, so metabolic state can be related to signaling directly instead of being inferred from enzyme transcript levels - which is what most metabolic analyses in cancer actually do.","required_fields":[],"required_modalities":["metabolome","phosphoproteome"],"feasibility":"direct","approx_n":187,"statistical_note":null,"exemplar_pmid":null,"topics":["metabolism","signaling"],"evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"question":"Can measured protein-protein interaction data improve network inference over correlation-based approaches?","rationale":"Interaction data on 153 cases is exceptionally rare in a tumor cohort, and provides a measured reference against which inferred co-expression networks can be scored.","required_fields":[],"required_modalities":["other","proteome"],"feasibility":"direct","approx_n":153,"statistical_note":null,"exemplar_pmid":null,"topics":["networks","methods-benchmarking"],"evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]}],"limitations":[{"kind":"annotation_quality","statement":"Clinical annotation is served by the PDC API rather than shipped with the study files, and it is uneven. Vital status, stage and race are informative for 86% of the 193 cases and the median follow-up is two years, which supports survival work. A treatment record exists for about half: type for 52%, a RECIST-style outcome for 50%, a named agent for 32%. Progression or recurrence is absent entirely.","severity":"major","affected_analyses":["Progression-free analysis","Complete-case treatment analysis"],"mitigation":"Read the clinical records from the PDC API (clinicalPerStudy and paginatedCaseTreatmentsPerStudy) rather than from the study download, and report the analysable subset. For progression, and for anything the PDC record leaves empty, retrieve the corresponding GDC CPTAC-3 clinical records and join on case identifier.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"kind":"harmonization","statement":"Each analytical fraction is a separate PDC study with its own sample set, so the seven layers do not cover an identical group of tumors - case counts range from 153 to 193.","severity":"major","affected_analyses":["Complete-case multi-layer integration"],"mitigation":"Build the intersection explicitly and report it. A complete-case analysis across all seven layers will be substantially smaller than 193.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"kind":"batch_technical","statement":"Layers were acquired with different enrichment chemistries and instrument methods, so batch structure differs between them and does not cancel out on integration.","severity":"major","affected_analyses":["Cross-layer integration","Unsupervised clustering"],"mitigation":"Model layer-specific batch covariates; do not concatenate raw intensities.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"kind":"population_coverage","statement":"Race is informative for 86% of cases but is overwhelmingly one group, and ethnicity is informative for well under 1%: it is recorded as \"not reported\" for almost every case. Population-stratified work is not supportable here whatever the race field suggests.","severity":"blocking","affected_analyses":["Any population-stratified analysis","Disparities research"],"mitigation":"None within this cohort. Check the race distribution on the dataset page before planning any stratified contrast.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]}],"inappropriate_uses":[{"statement":"Progression-free or recurrence analysis from these data.","reason":"Progression or recurrence is recorded for no case in the PDC clinical records.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"statement":"Treating treatment annotation as complete when reporting a response analysis.","reason":"A treatment outcome is recorded for half the cohort and a named agent for a third, so a complete-case treatment analysis runs on a self-selected subset.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"statement":"Treating the seven layers as a complete-case multi-omic matrix without checking overlap.","reason":"Case counts differ by layer; the naive intersection is smaller than any single layer.","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]}],"primary_publications":[{"pmid":"42013851","pmcid":"PMC13198309","doi":"10.1016/j.xcrm.2026.102756","title":"A 15-layer multi-omics analysis of gastric cancer ecotypes provides therapeutic insights.","journal":"Cell reports. Medicine","year":2026,"authors_short":"Wang et al.","n_authors":null,"url":"https://pubmed.ncbi.nlm.nih.gov/42013851/","is_open_access":true,"citation_count":0,"evidence":[{"method":"derived","source_url":null,"source_label":"Candidate primary publication (machine-inferred)","retrieved_at":"2026-09-20T18:12:46.246949Z","snippet":null,"locator":"earliest highly cited article analyzing PDC000622 (published 2026)","confidence":"low","reviewer":null,"reviewed_at":null,"note":"Inferred, not authoritative. The source repository does not publish a marker-paper link for this dataset, so we nominate the earliest heavily cited article that analyzed it. Flagged for expert review before being relied on."}]}],"reuse":[],"reuse_metrics":{"n_candidates_screened":1,"n_by_tier":{"t3_analyzed":1,"t2_declared":0,"t1_accession":0,"t0_mention":0},"n_by_tier_raw":{"t3_analyzed":1,"t2_declared":0,"t1_accession":0,"t0_mention":0},"accession_precision":{"token":"PDC000622","query":"METHODS:\"PDC000622\"","strategy_id":"epmc-literal-precision-v1","needs_correction":false,"precision":1.0,"precision_low":1.0,"precision_high":1.0,"n_sampled":0,"n_checked":0,"n_literal":0,"note":"This accession is a single indexed term, so Europe PMC matches it exactly and the hit count needs no correction."},"n_citations_to_primary_publication":null,"citation_to_reuse_ratio":null,"has_citable_accession":true,"n_verified_reuse":1,"n_reuse_examined":1,"n_independent_reuse":0,"n_nci_funded_reuse":0,"first_reuse_year":null,"latest_reuse_year":null,"years_since_release":0.72,"expected_reuse":5.73,"reuse_gap_index":-1.751,"reuse_gap_percentile":15.2,"search_strategy_id":"epmc-index-v3","searched_at":"2026-09-20T18:07:48.414817Z","no_reuse_identified":false,"evidence":[{"method":"derived","source_url":"https://www.ebi.ac.uk/europepmc/webservices/rest/search","source_label":"Europe PMC section-scoped hit counts","retrieved_at":"2026-09-20T18:07:48.414817Z","snippet":null,"locator":"tokens: PDC000622, PDC000616, PDC000621; queries: METHODS:\"PDC000622\"; DATA_AVAILABILITY:\"PDC000622\"; ACCESSION_ID:\"PDC000622\"; REF:\"PDC000622\"","confidence":"high","reviewer":null,"reviewed_at":null,"note":"Index strategy epmc-index-v3. Every dataset is measured with the same single section field per tier, so the counts are comparable; the per-tier value is the largest across the dataset's own accessions, excluding any accession shared with other datasets in the corpus. This accession is a single indexed term, so Europe PMC matches it exactly and the hit count needs no correction."},{"method":"derived","source_url":"https://www.ebi.ac.uk/europepmc/webservices/rest/search","source_label":"Europe PMC first-reference dating","retrieved_at":"2026-09-20T18:12:46.246949Z","snippet":null,"locator":"first referenced in 2026 (METHODS section)","confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Availability dated from the literature (epmc-first-reference-v2) rather than from repository file timestamps, which record re-harmonization. This is a lower bound on availability."}]},"underexplored":{"is_underexplored":true,"basis":["1 article(s) reference this dataset's accession in a methods section, against 5.7 predicted for datasets of comparable size, age, modality breadth and access tier (reuse gap index -1.75 on a log2 scale, 15th percentile of the assessed corpus)."],"index_value":-1.751,"percentile":15.2,"comparator_set":"132 datasets in this corpus with a citable accession and sufficient metadata","evidence":[{"method":"derived","source_url":null,"source_label":"Reuse Gap Index (rgi-huber-v2)","retrieved_at":"2026-09-21T02:11:22.976067Z","snippet":null,"locator":"Huber robust regression of log2(analyzing articles + 1) on cohort size, years available, modality breadth and access tier","confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Model, covariates and coefficients are published with the dataset export so the label can be recomputed or contested."}]},"grants":[],"access_steps":[{"order":1,"action":"Browse the study in the PDC portal","detail":"No account is required. All seven fractions are openly downloadable.","url":"https://pdc.cancer.gov/pdc/browse","requires":[],"est_time":"30 minutes","cli_snippet":null,"audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":2,"action":"Pull the study manifest from the PDC GraphQL API","detail":"The API is public and needs no key, which makes this cohort unusually easy to script against.","url":null,"requires":[],"est_time":"1 hour","cli_snippet":"curl -s https://proteomic.datacommons.cancer.gov/graphql \\\n  -H 'Content-Type: application/json' \\\n  -d '{\"query\":\"{ allPrograms { name projects { name studies { pdc_study_id study_name analytical_fraction experiment_type cases_count } } } }\"}' \\\n  | python3 -m json.tool | grep -A4 'CPTAC STAD'\n","audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":3,"action":"Retrieve the matching clinical and genomic data from the GDC","detail":"This is the step people skip. Without it the proteomic layers have no clinical context at all.","url":"https://portal.gdc.cancer.gov/projects/CPTAC-3","requires":[],"est_time":"2-3 hours","cli_snippet":null,"audience":"human","evidence":[{"method":"curated","source_url":null,"source_label":"Expert review","retrieved_at":"2026-09-21T12:30:56.909041Z","snippet":null,"locator":null,"confidence":"high","reviewer":"CD2S project curation","reviewed_at":"2026-09-18","note":"Written by a named reviewer after reading the source documentation and the measured field coverage. Not machine-generated."}]},{"order":4,"action":"Resolve the study UUID, then fetch the file manifest","detail":"filesPerStudy keys on the study UUID, not on PDC000622: called with the pdc_study_id it returns the right number of rows with every column null. Resolve the UUID first and pass the terms acknowledgement.","url":"https://pdc.cancer.gov/data-dictionary/publicapi-documentation/","requires":[],"est_time":null,"cli_snippet":"python - <<'PY'\nimport requests\nAPI = \"https://proteomic.datacommons.cancer.gov/graphql\"\n\ndef gql(query, **variables):\n    r = requests.post(API, json={\"query\": query, \"variables\": variables}, timeout=180)\n    r.raise_for_status()\n    body = r.json()\n    if body.get(\"errors\"):\n        raise RuntimeError(body[\"errors\"][0][\"message\"])\n    return body[\"data\"]\n\nstudy = gql('query($id:String!){ study(pdc_study_id:$id acceptDUA:true){ study_id } }',\n            id=\"PDC000622\")[\"study\"][0]\nfiles = gql('query($sid:String!){ filesPerStudy(study_id:$sid acceptDUA:true)'\n            '{ file_id file_name file_size } }', sid=study[\"study_id\"])[\"filesPerStudy\"]\nprint(len(files), \"files\")\nPY","audience":"agent","evidence":[{"method":"derived","source_url":"https://pdc.cancer.gov/data-dictionary/publicapi-documentation/","source_label":"PDC access documentation","retrieved_at":"2026-09-21T12:30:59.432030Z","snippet":null,"locator":null,"confidence":"medium","reviewer":null,"reviewed_at":null,"note":"Generated by applying the repository's documented access policy to this dataset's identifiers. It is not a reviewer's account of this dataset."}]}],"analysis_examples":[{"level":"intermediate","title":"Find and use the scarcest measurements in the portfolio","question":"Where can I find ubiquitylome, lipidome or metabolome data, and which cohorts carry several scarce layers on the same tumors?","problem":"Rare proteomic layers are scattered across study records and may cover different patients.","lesson":"Find genuinely scarce measurements and bound the complete-case cohort before designing the study.","figure":"Horizontal bars of the case count for each measured layer in the target cohort, with a dashed line at the smallest layer marking the ceiling on any analysis needing every layer at once.","featured":false,"inputs":["Public PDC GraphQL API, no account required","pandas"],"outputs":["Scarcity ranking of every analytical fraction","Cohorts carrying two or more scarce layers","Layer overlap bounding a complete-case analysis","Citation counts demonstrating that PDC accessions are not quoted","A chart of per-layer coverage with the complete-case ceiling marked"],"steps":["Enumerate every PDC study through the public GraphQL endpoint","Rank analytical fractions by number of studies","Group per-fraction studies back into biological cohorts","Report the per-layer case counts that bound a complete-case analysis","Query Europe PMC for each accession to show citation tracing is blind here"],"findings":["Across 255 PDC studies the proteome appears 109 times, the ubiquitylome 5 and the lipidome 3.","CPTAC STAD carries five scarce layers on 193 cases, but a complete-case analysis across all seven is capped at 153.","Each of the six STAD accessions returns one article, so accession tracing is blind to proteomic reuse."],"contributor":null,"contributor_url":null,"language":"python","est_runtime":"about a minute","est_compute":null,"workbook_path":"workbooks/python/04_scarce_modality_cptac.py","workbook_url":null,"notebook_download_url":"/data/notebooks/04_scarce_modality_cptac.ipynb","notebook_preview_url":"/data/notebooks/04_scarce_modality_cptac.png","notebook_preview_width":1045,"notebook_preview_height":616,"colab_url":null,"binder_url":null,"receipt":{"executed":true,"executed_at":"2026-09-21T00:42:56.314549Z","runtime_seconds":107.84,"executor":"nbclient / python 3.12.13 / Darwin 25.5.0 arm64","package_versions":{"python":"3.12.13","pandas":"3.0.6","numpy":"2.5.3","matplotlib":"3.11.2","lifelines":"0.30.0","scipy":"1.18.1","requests":"2.34.2","httpx":"0.28.1"},"n_cells":7,"n_cells_executed":7,"output_hash":"016ed4e8fdca36b1dd852eabc6e6ca96","data_retrieved_at":null,"error":null},"template_source":"04_scarce_modality_cptac","evidence":[{"method":"curated","source_url":null,"source_label":"CD2S workbook","retrieved_at":"2026-09-21T12:30:59.450327Z","snippet":null,"locator":"workbooks/python/04_scarce_modality_cptac.py","confidence":"high","reviewer":null,"reviewed_at":null,"note":"Executed end to end against the live public APIs; the receipt records when, with which package versions and how long it took."}]}],"agent_package":{"json_url":"/data/datasets/pdc-cptac-stad-study.json","jsonld_url":"/data/jsonld/pdc-cptac-stad-study.jsonld","croissant_url":"/data/croissant/pdc-cptac-stad-study.json","instructions_url":"/data/agent/pdc-cptac-stad-study.md","bundle_url":null,"mcp_resource_uri":null},"related_dataset_ids":[],"related_underexplored_ids":[],"review":{"status":"project_curated","reviewer":"CD2S project curation","reviewer_affiliation":null,"reviewed_at":"2026-09-18","sections_reviewed":["useful_for","limitations","inappropriate_uses","access_steps"],"open_questions":["PDC study identifiers are almost never quoted in the literature, so the reuse figure on this page is close to uninformative. A manual review of gastric proteogenomics papers would give a better estimate than any citation-based method."],"notes":null},"verification":{"last_verified_at":null,"link_checks":[],"n_links_ok":0,"n_links_broken":0,"upstream_version_seen":null,"upstream_version_changed":false,"upstream_counts_seen":{},"upstream_drift":{},"notes":[]},"is_showcase":true,"completeness_score":85.7,"tags":["acetylome","gastric","glycoproteome","metabolome","multi-omic","open-access","pdc","protein-protein-interaction","proteogenomics","rare-modality","scarce-modality","ubiquitylome"],"search_text":null}