{"doi":"10.1172/jci170953","title":"Breast cancers that disseminate to bone marrow acquire aggressive phenotypes through CX43-related tumor-stroma tunnels","abstract":"Estrogen receptor-positive (ER+) breast cancer commonly disseminates to bone marrow, where interactions with mesenchymal stromal cells (MSCs) shape disease trajectory. We modeled these interactions with tumor-MSC co-cultures and used an integrated transcriptome-proteome-network-analyses workflow to identify a comprehensive catalog of contact-induced changes. Conditioned media from MSCs failed to recapitulate genes and proteins, some borrowed and others tumor-intrinsic, induced in cancer cells by direct contact. Protein-protein interaction networks revealed the rich connectome between \"borrowed\" and \"intrinsic\" components. Bioinformatics prioritized one of the borrowed components, CCDC88A/GIV, a multi-modular metastasis-related protein that has recently been implicated in driving a hallmark of cancer, growth signaling autonomy. MSCs transferred GIV protein to ER+ breast cancer cells (that lack GIV) through tunnelling nanotubes via connexin (Cx)43-facilitated intercellular transport. Reinstating GIV alone in GIV-negative breast cancer cells reproduced approximately 20% of both the borrowed and the intrinsic gene induction patterns from contact co-cultures; conferred resistance to anti-estrogen drugs; and enhanced tumor dissemination. Findings provide a multiomic insight into MSC→tumor cell intercellular transport and validate how transport of one such candidate, GIV, from the haves (MSCs) to have-nots (ER+ breast cancer) orchestrates aggressive disease states.","journal":"Journal of Clinical Investigation","year":2024,"id":428738,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":12,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9464,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1171431,"name":"Brennan W. Callow","orcid":"0009-0001-0576-3934","position":1,"is_corresponding":false},{"id":941118,"name":"Alex P. Farfel","orcid":"0000-0001-9249-9993","position":2,"is_corresponding":false},{"id":382453,"name":"Suchismita Roy","orcid":"0000-0002-6091-2357","position":3,"is_corresponding":false},{"id":1081943,"name":"Siyi Chen","orcid":"0000-0002-0153-6152","position":4,"is_corresponding":false},{"id":1077943,"name":"Maria Masotti","orcid":"0000-0001-6591-3212","position":5,"is_corresponding":false},{"id":478878,"name":"Shrila Rajendran","orcid":"0000-0003-1166-5852","position":6,"is_corresponding":false},{"id":294960,"name":"Johanna M. Buschhaus","orcid":"0000-0002-4181-0953","position":7,"is_corresponding":false},{"id":741477,"name":"Celia R. Espinoza","orcid":null,"position":8,"is_corresponding":false},{"id":773510,"name":"Kathryn E. Luker","orcid":"0000-0001-8314-3370","position":9,"is_corresponding":false},{"id":294967,"name":"Pradipta Ghosh","orcid":"0000-0002-8917-3201","position":10,"is_corresponding":false},{"id":294970,"name":"Gary D. Luker","orcid":"0000-0001-6832-2581","position":11,"is_corresponding":false},{"id":807708,"name":"Saptarshi Sinha","orcid":"0000-0002-4100-5727","position":0,"is_corresponding":true}],"reference_count":100,"raw_metadata":null,"created_at":"2026-07-19T01:59:02.165535Z","pmid":"39480488","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}