{"doi":"10.3390/cancers14122874","title":"The Machine-Learning-Mediated Interface of Microbiome and Genetic Risk Stratification in Neuroblastoma Reveals Molecular Pathways Related to Patient Survival","abstract":"Currently, most neuroblastoma patients are treated according to the Children’s Oncology Group (COG) risk group assignment; however, neuroblastoma’s heterogeneity renders only a few predictors for treatment response, resulting in excessive treatment. Here, we sought to couple COG risk classification with tumor intracellular microbiome, which is part of the molecular signature of a tumor. We determine that an intra-tumor microbial gene abundance score, namely M-score, separates the high COG-risk patients into two subpopulations (Mhigh and Mlow) with higher accuracy in risk stratification than the current COG risk assessment, thus sparing a subset of high COG-risk patients from being subjected to traditional high-risk therapies. Mechanistically, the classification power of M-scores implies the effect of CREB over-activation, which may influence the critical genes involved in cellular proliferation, anti-apoptosis, and angiogenesis, affecting tumor cell proliferation survival and metastasis. Thus, intracellular microbiota abundance in neuroblastoma regulates intracellular signals to affect patients’ survival.","journal":"Cancers","year":2022,"id":269282,"datarank":0.42498200160843247,"base_score":2.833213344056216,"endowment":2.833213344056216,"self_citation_contribution":0.42498200160843247,"citation_network_contribution":0.0,"self_endowment_contribution":0.42498200160843247,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":16,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9496,"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":524227,"name":"Xiaoqi Wang","orcid":"0000-0001-8251-9102","position":1,"is_corresponding":false},{"id":932451,"name":"Ruihao Huang","orcid":null,"position":2,"is_corresponding":false},{"id":327796,"name":"Andres Stucky","orcid":null,"position":3,"is_corresponding":false},{"id":919351,"name":"Xuelian Chen","orcid":"0000-0003-3697-6243","position":4,"is_corresponding":false},{"id":574778,"name":"Lan Sun","orcid":"0000-0003-3643-6124","position":5,"is_corresponding":false},{"id":932041,"name":"Qin Wen","orcid":"0000-0002-9494-3901","position":6,"is_corresponding":false},{"id":932042,"name":"Yunjing Zeng","orcid":"0009-0002-9875-6967","position":7,"is_corresponding":false},{"id":417596,"name":"Hansel M. Fletcher","orcid":"0000-0002-7165-2159","position":8,"is_corresponding":false},{"id":24562,"name":"Charles Wang","orcid":null,"position":9,"is_corresponding":false},{"id":932043,"name":"Yi Xu","orcid":"0000-0003-4215-1993","position":10,"is_corresponding":false},{"id":932452,"name":"Huynh Cao","orcid":null,"position":11,"is_corresponding":false},{"id":109406,"name":"Fengzhu Sun","orcid":"0000-0002-8552-043X","position":12,"is_corresponding":false},{"id":525545,"name":"Shengwen Calvin Li","orcid":"0000-0002-9699-9204","position":13,"is_corresponding":false},{"id":506457,"name":"Xi Zhang","orcid":"0000-0002-8548-2832","position":14,"is_corresponding":false},{"id":326745,"name":"Jiang F. Zhong","orcid":"0000-0003-0551-5161","position":15,"is_corresponding":false},{"id":240402,"name":"Xin Li","orcid":"0000-0002-7414-5734","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:27:18.142851Z","pmid":"35740540","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":[]}