{"doi":"10.1101/2023.03.14.532665","title":"Rational design of immune gene therapy combinations via <i>in vivo</i> CRISPR activation screen of tumor microenvironment modulators","abstract":"Abstract The hostile tumor microenvironment (TME) is major challenge for cancer immunotherapies. Here, we design and perform TME-targeted in vivo CRISPR activation (CRISPRa) screens to uncover factors that promote anti-tumor immunity, culminating in rationally designed immune gene therapy combinations. Through adeno-associated virus (AAV) delivery, multiplexed activation of pooled immunoregulatory genes encoding a ntigen p resentation, c ytokine, and co-stimulation m olecules (APCM) leads to enhanced anti-tumor immunity. APCM screen in metastatic tumors identifies Cd80, Tnfsf14, Cxcl10, Tnfsf18, Tnfsf9 , and Ifng as the top immunostimulatory candidates. AAV-mediated delivery of these factors individually or in combination shows anti-tumor efficacy across different cancer models. Further optimization pinpoints Ifng + Tnfsf9 + Il12b(Il12/Il23) as a potent therapeutic combination, leading to increased IFN-γ + CD8 + and tissue-resident memory T cells. APCM therapy synergizes with CAR-T cell therapy against human solid tumors in vivo . APCM-based CRISPRa screen and gene activation systems can thus be leveraged for the rapid generation of off-the-shelf immune gene therapies against solid tumors.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2023,"id":403738,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.952,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":259571,"name":"Feifei Zhang","orcid":"0000-0003-3277-445X","position":1,"is_corresponding":false},{"id":254235,"name":"Ryan D. Chow","orcid":"0000-0002-1872-6307","position":2,"is_corresponding":false},{"id":1181060,"name":"Emily He","orcid":"0000-0002-8231-7735","position":3,"is_corresponding":false},{"id":259568,"name":"Lvyun Zhu","orcid":"0000-0003-2288-5981","position":4,"is_corresponding":false},{"id":1181061,"name":"Qin Han","orcid":"0000-0002-7317-0823","position":5,"is_corresponding":false},{"id":60778,"name":"Sidi Chen","orcid":"0000-0002-3819-5005","position":6,"is_corresponding":false},{"id":259567,"name":"Guangchuan Wang","orcid":"0000-0001-5315-1599","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-19T01:20:36.280647Z","pmid":null,"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":[]}