{"doi":"10.1007/978-1-0716-4654-0_18","title":"A Toolkit for Single-Nucleus Characterization of Glioblastoma","abstract":null,"journal":"Methods in Molecular Biology","year":2025,"id":639883,"datarank":0.10397207708399181,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"self_citation_contribution":0.10397207708399181,"citation_network_contribution":0.0,"self_endowment_contribution":0.10397207708399181,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1662846,"name":"Vanshika Khaitan","orcid":null,"position":1,"is_corresponding":false},{"id":1662847,"name":"Connor Clark-Baba","orcid":null,"position":2,"is_corresponding":false},{"id":1662848,"name":"Alberto G. Torrez","orcid":null,"position":3,"is_corresponding":false},{"id":1662849,"name":"Mikhail Y. Salnikov","orcid":null,"position":4,"is_corresponding":false},{"id":1662850,"name":"Kabir Siraj","orcid":null,"position":5,"is_corresponding":false},{"id":1662851,"name":"Solsa Cariba","orcid":null,"position":6,"is_corresponding":false},{"id":892883,"name":"Fuad Chowdhury","orcid":"0000-0002-9657-2681","position":7,"is_corresponding":false},{"id":138120,"name":"Hong Han","orcid":null,"position":8,"is_corresponding":false},{"id":1662845,"name":"Cole C. Nickason","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"A Toolkit for Single-Nucleus Characterization of Glioblastoma","abstract":"Glioblastoma (GBM) is the most common and lethal primary adult brain tumor. It represents a rapidly evolving ecosystem, including heterogeneous tumor cells and an immunosuppressive tumor microenvironment (TME) with diverse non-malignant cells. High-throughput single-cell omics profiling, such as single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq, respectively), is an emerging powerful tool to deconvolute diverse cell types and states as well as intricate cellular and molecular functions and interactions that underlie the complex GBM ecosystem. snRNA-seq is a methodology that profiles the transcriptome using isolated nuclei instead of intact cells. It is an alternative to scRNA-seq and is compatible with frozen samples and difficult-to-dissociate tissues, such as brain or brain tumor tissues. However, efficient, optimized procedures are instrumental in preparing high-quality single nuclei from clinical GBM specimens and patient-derived GBM cell lines across different conditions for snRNA-seq. Here, we provide a toolkit of detailed protocols for nucleus isolation, counting, and quality control, enabling a streamlined single-nucleus preparation for snRNA-seq characterization.","is_dataset_classified":null,"base_score":0.6931471805599453,"endowment":0.6931471805599453,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"40553287","pmcid":null,"openalex_id":"https://openalex.org/W4411550233","authors":[],"funders":[],"total_grants":0,"fwci":8.9101,"citation_percentile":0.95707071,"influential_citations":0,"citation_trend":[{"year":2026,"count":1}],"oa_status":"closed","license":"https://www.springernature.com/gp/researchers/text-and-data-mining","oa_locations":[{"url":"https://link.springer.com/content/pdf/10.1007/978-1-0716-4654-0_18","host_type":"publisher"},{"url":"https://doi.org/10.1007/978-1-0716-4654-0_18","host_type":"book series"},{"url":"https://pubmed.ncbi.nlm.nih.gov/40553287","host_type":"repository"}],"fields_of_study":["Glioma Diagnosis and Treatment","Single-cell and spatial transcriptomics","Cell Image Analysis Techniques"],"mesh_terms":["Brain Neoplasms","Cell Nucleus","Glioblastoma","Humans","RNA, Small Nuclear","Sequence Analysis, RNA","Gene Expression Profiling","Cell Line, Tumor","Single-Cell Analysis","Tumor Microenvironment","Transcriptome"],"keywords":["Glioblastoma","Characterization (materials science)","Nucleus","Computer science","Neuroscience","Biology","Nanotechnology","Cancer research","Materials science","Heterogeneity","Plasticity","Microenvironment","Single-nucleus Rna-seq","In Vitro (Co)-culture","Single-nucleus Isolation"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Zero hunger"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-07T03:37:42.999669Z","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":[]}