{"doi":"10.3389/fonc.2022.1014749","title":"The extracellular matrix protein fibulin-3/EFEMP1 promotes pleural mesothelioma growth by activation of PI3K/Akt signaling","abstract":"Malignant pleural mesothelioma (MPM) is an aggressive tumor with poor prognosis and limited therapeutic options. The extracellular matrix protein fibulin-3/EFEMP1 accumulates in the pleural effusions of MPM patients and has been proposed as a prognostic biomarker of these tumors. However, it is entirely unknown whether fibulin-3 plays a functional role on MPM growth and progression. Here, we demonstrate that fibulin-3 is upregulated in MPM tissue, promotes the malignant behavior of MPM cells, and can be targeted to reduce tumor progression. Overexpression of fibulin-3 increased the viability, clonogenic capacity and invasion of mesothelial cells, whereas fibulin-3 knockdown decreased these phenotypic traits as well as chemoresistance in MPM cells. At the molecular level, fibulin-3 activated PI3K/Akt signaling and increased the expression of a PI3K-dependent gene signature associated with cell adhesion, motility, and invasion. These pro-tumoral effects of fibulin-3 on MPM cells were disrupted by PI3K inhibition as well as by a novel, function-blocking, anti-fibulin-3 chimeric antibody. Anti-fibulin-3 antibody therapy tested in two orthotopic models of MPM inhibited fibulin-3 signaling, resulting in decreased tumor cell proliferation, reduced tumor growth, and extended animal survival. Taken together, these results demonstrate for the first time that fibulin-3 is not only a prognostic factor of MPM but also a relevant molecular target in these tumors. Further development of anti-fibulin-3 approaches are proposed to increase early detection and therapeutic impact against MPM.","journal":"Frontiers in Oncology","year":2022,"id":270408,"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":14,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9471,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":69972,"name":"Chandra Goparaju","orcid":"0000-0001-6290-0387","position":1,"is_corresponding":false},{"id":898453,"name":"Somanath Kundu","orcid":"0000-0003-0412-5065","position":2,"is_corresponding":false},{"id":898454,"name":"Mohan S. Nandhu","orcid":"0000-0002-7699-4318","position":3,"is_corresponding":false},{"id":898455,"name":"Sharon L. Longo","orcid":"0009-0002-1967-9730","position":4,"is_corresponding":false},{"id":898456,"name":"John A. Longo","orcid":"0009-0007-4827-0068","position":5,"is_corresponding":false},{"id":935196,"name":"Joan Chou","orcid":null,"position":6,"is_corresponding":false},{"id":88923,"name":"Frank A. Middleton","orcid":"0000-0002-3107-7188","position":7,"is_corresponding":false},{"id":14422,"name":"Harvey I. Pass","orcid":"0000-0003-3222-3471","position":8,"is_corresponding":false},{"id":807932,"name":"Mariano S. Viapiano","orcid":"0000-0002-8756-388X","position":9,"is_corresponding":false},{"id":934639,"name":"Arivazhagan Roshini","orcid":"0009-0001-9842-3508","position":0,"is_corresponding":true}],"reference_count":62,"raw_metadata":null,"created_at":"2026-07-19T00:27:31.019242Z","pmid":"36303838","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":[]}