{"doi":"10.1186/s13045-023-01517-2","title":"Multiscale protein networks systematically identify aberrant protein interactions and oncogenic regulators in seven cancer types","abstract":"Global proteomic data generated by advanced mass spectrometry (MS) technologies can help bridge the gap between genome/transcriptome and functions and hold great potential in elucidating unbiased functional models of pro-tumorigenic pathways. To this end, we collected the high-throughput, whole-genome MS data and conducted integrative proteomic network analyses of 687 cases across 7 cancer types including breast carcinoma (115 tumor samples; 10,438 genes), clear cell renal carcinoma (100 tumor samples; 9,910 genes), colorectal cancer (91 tumor samples; 7,362 genes), hepatocellular carcinoma (101 tumor samples; 6,478 genes), lung adenocarcinoma (104 tumor samples; 10,967 genes), stomach adenocarcinoma (80 tumor samples; 9,268 genes), and uterine corpus endometrial carcinoma UCEC (96 tumor samples; 10,768 genes). Through the protein co-expression network analysis, we identified co-expressed protein modules enriched for differentially expressed proteins in tumor as disease-associated pathways. Comparison with the respective transcriptome network models revealed proteome-specific cancer subnetworks associated with heme metabolism, DNA repair, spliceosome, oxidative phosphorylation and several oncogenic signaling pathways. Cross-cancer comparison identified highly preserved protein modules showing robust pan-cancer interactions and identified endoplasmic reticulum-associated degradation (ERAD) and N-acetyltransferase activity as the central functional axes. We further utilized these network models to predict pan-cancer protein regulators of disease-associated pathways. The top predicted pan-cancer regulators including RSL1D1, DDX21 and SMC2, were experimentally validated in lung, colon, breast cancer and fetal kidney cells. In summary, this study has developed interpretable network models of cancer proteomes, showcasing their potential in unveiling novel oncogenic regulators, elucidating underlying mechanisms, and identifying new therapeutic targets.","journal":"Journal of Hematology & Oncology","year":2023,"id":10321,"datarank":0.41594541914189775,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.0562611282221421,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.0562611282221421,"corpus_percentile":49.959316517493896,"corpus_rank":616,"citation_count":14,"citer_count":10,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8616,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-12-15","fair_score":43.5417,"fair_percentile":42.56816182937555,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":4388,"name":"Richard Farias","orcid":null,"position":2,"is_corresponding":false},{"id":4389,"name":"Peng Xu","orcid":"0000-0001-8007-9879","position":3,"is_corresponding":false},{"id":4390,"name":"Xianxiao Zhou","orcid":"0000-0001-9350-4467","position":4,"is_corresponding":false},{"id":4391,"name":"Benjamin Hopkins","orcid":null,"position":5,"is_corresponding":false},{"id":1998,"name":"Kuan-lin Huang","orcid":"0000-0002-3237-4248","position":6,"is_corresponding":false},{"id":4392,"name":"Bin Zhang","orcid":"0000-0002-4579-1075","position":7,"is_corresponding":false},{"id":39840,"name":"Won‐Min Song","orcid":"0000-0003-0948-119X","position":8,"is_corresponding":false},{"id":2334,"name":"Abdülkadir Elmas","orcid":"0000-0002-7999-5770","position":9,"is_corresponding":false},{"id":4393,"name":"Benjamin D. Hopkins","orcid":"0000-0002-7970-6430","position":10,"is_corresponding":false}],"reference_count":11,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":"38102665","pmcid":"PMC10724946","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":"gold","license":"cc-by","views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":52.5,"fair_a":67.5,"fair_i":12.5,"fair_r":41.6667,"fair_zscore":-0.151,"fair_rationale":{"fair_score":43.54,"has_llm":true,"dimensions":{"F":{"name":"Findable","score":52.5,"criteria":[{"key":"f_has_doi","label":"Has a persistent DOI","kind":"deterministic","weight":1.0,"fraction":1.0,"signal":"DOI present","rationale":null},{"key":"f_repository_presence","label":"Indexed in repositories / literature DBs","kind":"deterministic","weight":1.0,"fraction":1.0,"signal":"datacite=0, pmcid=True, pmid=True","rationale":null},{"key":"f_persistent_ids","label":"Resolvable scholarly identifiers (OpenAlex)","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"no OpenAlex id","rationale":null},{"key":"f_metadata_richness","label":"Rich, machine-readable metadata","kind":"llm","weight":1.0,"fraction":0.25,"signal":null,"rationale":"The paper provides no machine-readable metadata (e.g., schema.org, structured data), relying solely on human-readable text and files."}]},"A":{"name":"Accessible","score":67.5,"criteria":[{"key":"a_open_access","label":"Open Access / files deposited","kind":"deterministic","weight":1.5,"fraction":1.0,"signal":"Open Access","rationale":null},{"key":"a_retrievable","label":"Free full text retrievable","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"0 OA location(s)","rationale":null},{"key":"a_access_protocol","label":"Clear data/code access protocol","kind":"llm","weight":1.0,"fraction":0.75,"signal":null,"rationale":"The paper clearly specifies public repositories (CPTAC, GDC, Zenodo) and DOIs for data and code, but does not describe an authentication/authorization protocol or automated access method (e.g., API)."}]},"I":{"name":"Interoperable","score":12.5,"criteria":[{"key":"i_linked_data","label":"Linked datasets / DataCite relations","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"linked_datasets=0, datacite=0","rationale":null},{"key":"i_standard_ids","label":"References data via standard accessions","kind":"deterministic","weight":1.0,"fraction":0.0,"signal":"accessions=0, trials=0","rationale":null},{"key":"i_standards","label":"Standard formats, vocabularies & identifiers","kind":"llm","weight":1.0,"fraction":0.25,"signal":null,"rationale":"No standard formats, controlled vocabularies, or persistent identifiers (beyond regular DOIs for datasets) are mentioned for the data or metadata."}]},"R":{"name":"Reusable","score":41.67,"criteria":[{"key":"r_license","label":"Clear, open reuse license","kind":"deterministic","weight":1.5,"fraction":0.0,"signal":"no license","rationale":null},{"key":"r_downloads","label":"Demonstrated reuse (downloads)","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"downloads=0","rationale":null},{"key":"r_version","label":"Versioned / maintained","kind":"deterministic","weight":0.5,"fraction":0.0,"signal":"no version chain","rationale":null},{"key":"r_dataset","label":"Classified as a data resource","kind":"deterministic","weight":0.5,"fraction":1.0,"signal":"is_dataset","rationale":null},{"key":"r_reusability","label":"Data-availability statement, license & reproducibility","kind":"llm","weight":2.0,"fraction":0.667,"signal":null,"rationale":"The paper includes a data-availability statement with links to raw and processed data/code under a CC BY 4.0 license, but lacks a formal software license and does not describe reproducibility steps beyond code availability."}]}},"suggestions":["Add structured metadata (e.g., JSON-LD with schema.org) to the paper or repository landing page for machine readability.","Provide an API or documented script to programmatically access the data (e.g., via Zenodo's API) rather than just download links.","Adopt community-standard formats (e.g., Proteomics Standards Initiative (PSI) formats for MS data) and use persistent identifiers for all biological entities (e.g., Uniprot IDs for proteins).","Include a clear software license (e.g., MIT, Apache 2.0) for the code repository and a detailed reproducibility guide (e.g., computational environment, container)."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v2","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v2","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-06-18T00:48:56.750698Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}