{"doi":"10.1101/2025.11.05.686836","title":"Ambient mass spectrometry imaging enables spatial metabolomics of optimal cutting temperature compound (OCT)-embedded tumors","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Mass spectrometry imaging (MSI) is emerging as a powerful tool for uncovering the distribution of metabolites in the tumor microenvironment and studying tumor metabolism\n                  <jats:italic>in vivo</jats:italic>\n                  . However, to date, MSI of primary patient biobanked tissues contextualized by patient data has been limited to peptides, proteins, and glycans – with few examples for metabolites. This is because most biobanked fresh-frozen tissue required for spatial metabolomics is embedded in optimal cutting temperature compound (OCT), which introduces high-abundance polymeric interferents. Herein, we use nanospray desorption electrospray ionization (nano-DESI) to demonstrate the MSI of metabolites in OCT-embedded tissue. Metabolite coverage and sensitivity for prepared tissue mimetic homogenates embedded in OCT and an MSI-compatible material, carboxymethylcellulose (CMC), showed excellent agreement. We apply our ambient MSI workflow to detect changes in intratumoral methionine using a preclinical cancer mouse model undergoing adoptive T-cell therapy. Eight days after tumor incubation, lymphoma-bearing mice were maintained on a complete or methionine-restricted diet for 2 days. Nano-DESI MSI revealed a heterogeneous tumor microenvironment, with multiple methionine-cycle intermediates (S-adenosylmethionine, S-adenosylhomocysteine) and related metabolites, including known T-cell modulators (1-methylnicotinamide, polyamines) localizing to tumor subregions. Methionine-restricted tumors exhibited reduced methionine levels and elevated S-adenosylmethionine, relative to the control group. Overall, this work demonstrates spatial metabolomics on fresh-frozen OCT-embedded tissue, unlocking the wealth of information stored in primary tissue biobanks and consequently accelerating our understanding of cancer metabolism and treatment.\n                </jats:p>","journal":null,"year":null,"id":645152,"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":1679723,"name":"Nicholas Woytowich","orcid":null,"position":1,"is_corresponding":false},{"id":1275634,"name":"Tian Zhao","orcid":"0000-0003-0202-5255","position":2,"is_corresponding":false},{"id":1679725,"name":"Kiera Nguyen","orcid":null,"position":3,"is_corresponding":false},{"id":1679726,"name":"Emily Mahony","orcid":null,"position":4,"is_corresponding":false},{"id":883261,"name":"Julian J. Lum","orcid":"0000-0002-5624-3541","position":5,"is_corresponding":false},{"id":495311,"name":"Kyle D. Duncan","orcid":"0000-0003-0575-0858","position":6,"is_corresponding":false},{"id":74605,"name":"J. J. Monaghan","orcid":"0000-0001-6984-6993","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Ambient mass spectrometry imaging enables spatial metabolomics of optimal cutting temperature compound (OCT)-embedded tumors","abstract":"<jats:title>Abstract</jats:title>\n                <jats:p>\n                  Mass spectrometry imaging (MSI) is emerging as a powerful tool for uncovering the distribution of metabolites in the tumor microenvironment and studying tumor metabolism\n                  <jats:italic>in vivo</jats:italic>\n                  . However, to date, MSI of primary patient biobanked tissues contextualized by patient data has been limited to peptides, proteins, and glycans – with few examples for metabolites. This is because most biobanked fresh-frozen tissue required for spatial metabolomics is embedded in optimal cutting temperature compound (OCT), which introduces high-abundance polymeric interferents. Herein, we use nanospray desorption electrospray ionization (nano-DESI) to demonstrate the MSI of metabolites in OCT-embedded tissue. Metabolite coverage and sensitivity for prepared tissue mimetic homogenates embedded in OCT and an MSI-compatible material, carboxymethylcellulose (CMC), showed excellent agreement. We apply our ambient MSI workflow to detect changes in intratumoral methionine using a preclinical cancer mouse model undergoing adoptive T-cell therapy. Eight days after tumor incubation, lymphoma-bearing mice were maintained on a complete or methionine-restricted diet for 2 days. Nano-DESI MSI revealed a heterogeneous tumor microenvironment, with multiple methionine-cycle intermediates (S-adenosylmethionine, S-adenosylhomocysteine) and related metabolites, including known T-cell modulators (1-methylnicotinamide, polyamines) localizing to tumor subregions. Methionine-restricted tumors exhibited reduced methionine levels and elevated S-adenosylmethionine, relative to the control group. Overall, this work demonstrates spatial metabolomics on fresh-frozen OCT-embedded tissue, unlocking the wealth of information stored in primary tissue biobanks and consequently accelerating our understanding of cancer metabolism and treatment.\n                </jats:p>","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":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W4415981338","authors":[],"funders":[{"funder_name":"","grant_id":"RGPIN-2022-03696","title":null},{"funder_name":"Terry Fox Research Institute","grant_id":"Program Project Grant #1125","title":null},{"funder_name":"Mitacs","grant_id":"IT39215","title":null},{"funder_name":"Michael Smith Health Research BC","grant_id":"RT-2024-03771","title":null},{"funder_name":"Michael Smith Health Research BC","grant_id":"SCH-2025-04631","title":null},{"funder_name":"","grant_id":"CFI JELF 43810","title":null}],"total_grants":6,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2026,"count":1}],"oa_status":"green","license":"cc-by-nc","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2025/11/06/2025.11.05.686836.full.pdf","host_type":"repository"},{"url":"https://www.biorxiv.org/content/biorxiv/early/2025/11/06/2025.11.05.686836.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2025.11.05.686836","host_type":"publisher"},{"url":"https://doi.org/10.1101/2025.11.05.686836","host_type":"repository"}],"fields_of_study":["Mass Spectrometry Techniques and Applications","Cancer Cells and Metastasis","Advanced Proteomics Techniques and Applications"],"mesh_terms":[],"keywords":["Metabolomics","Metabolite","Mass spectrometry imaging","Mass spectrometry","Tumor microenvironment","Metabolism","Metabolome"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-09T03:06:47.408910Z","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":[]}