{"entity": "researcher", "timestamp": "2026-06-15T17:56:13.167Z", "family": "Leo", "given": "Isabelle Rose", "initials": "IR", "orcid": "0000-0002-7627-6690", "affiliations": ["Clinical Proteomics Mass Spectrometry, Department of Oncology-Pathology, Karolinska Institutet, Science for Life Laboratory, Tomtebodav\u00e4gen 23A, 171 65, Solna, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/21185d9c6a2343f189397cbbb95c6e71.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/21185d9c6a2343f189397cbbb95c6e71"}}, "publications": [{"entity": "publication", "iuid": "f3a1b1396edb4101b0575fbc43ec7415", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f3a1b1396edb4101b0575fbc43ec7415.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f3a1b1396edb4101b0575fbc43ec7415"}}, "title": "Comparative evaluation of Olink Explore 3072 and mass spectrometry with peptide fractionation for plasma proteomics.", "authors": [{"family": "Sissala", "given": "Noora", "initials": "N", "orcid": "0009-0000-0758-8140", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a96666a6a2e478fbdd3cf33d7db1e74.json"}}, {"family": "Baba\u010di\u0107", "given": "Haris", "initials": "H", "orcid": "0000-0003-0813-0005", "researcher": {"href": "https://publications.scilifelab.se/researcher/45a1c5d3d2d34a9e96d112877632784c.json"}}, {"family": "Leo", "given": "Isabelle R", "initials": "IR", "orcid": "0000-0002-7627-6690", "researcher": {"href": "https://publications.scilifelab.se/researcher/21185d9c6a2343f189397cbbb95c6e71.json"}}, {"family": "Cao", "given": "Xiaofang", "initials": "X"}, {"family": "Forshed", "given": "Jenny", "initials": "J"}, {"family": "Eriksson", "given": "Lars E", "initials": "LE", "orcid": "0000-0001-5121-5325", "researcher": {"href": "https://publications.scilifelab.se/researcher/ebb717a9972245a5b2427a4b8421fe6f.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "\u00c5berg", "given": "Mikael", "initials": "M", "orcid": "0000-0002-7858-8233", "researcher": {"href": "https://publications.scilifelab.se/researcher/90fa86e9aeaa43ea9547e48b4f3f24e3.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "journal article", "published": "2025-11-04", "journal": {"title": "Commun Chem", "issn": "2399-3669", "issn-l": null, "volume": "8", "issue": "1", "pages": "327"}, "abstract": "Plasma proteomics technologies are advancing rapidly, offering new opportunities for biomarker discovery and precision medicine. Direct comparisons of available technologies are needed to understand how platform selection affects downstream findings. We compared the performance of a peptide fractionation-based mass spectrometry method (HiRIEF LC-MS/MS) and the Olink Explore 3072 proximity extension assays on 88 plasma samples, analyzing 1129 proteins with both methods. The platforms exhibited complementary proteome coverage, high precision, and concordance in estimating sex differences in protein levels. Quantitative agreement between platforms was moderate (median correlation 0.59, interquartile range 0.33-0.75), mainly influenced by technical factors. Finally, we present a publicly available tool for peptide-level analysis of platform agreement and demonstrate its utility in clarifying cross-platform discrepancies in protein and proteoform measurements. Our findings provide insights for platform selection and study design, and highlight the value of combining mass spectrometry and affinity-based approaches for more comprehensive and reliable plasma proteome profiling.", "doi": "10.1038/s42004-025-01753-2", "pmid": "41188494", "labels": {"National Genomics Infrastructure": "Service", "NGI Proteomics": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "Affinity Proteomics Stockholm": "Collaborative", "Affinity Proteomics Uppsala": "Collaborative", "Global Proteomics and Proteogenomics": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12586489"}, {"db": "pii", "key": "10.1038/s42004-025-01753-2"}], "notes": [], "created": "2025-11-07T07:35:27.214Z", "modified": "2025-11-27T13:03:30.885Z"}, {"entity": "publication", "iuid": "9ebcad7df6fc4b52a1198f4a36faeb0e", "links": {"self": {"href": "https://publications.scilifelab.se/publication/9ebcad7df6fc4b52a1198f4a36faeb0e.json"}, "display": {"href": "https://publications.scilifelab.se/publication/9ebcad7df6fc4b52a1198f4a36faeb0e"}}, "title": "Integrative multi-omics and drug response profiling of childhood acute lymphoblastic leukemia cell lines.", "authors": [{"family": "Leo", "given": "Isabelle Rose", "initials": "IR", "orcid": "0000-0002-7627-6690", "researcher": {"href": "https://publications.scilifelab.se/researcher/21185d9c6a2343f189397cbbb95c6e71.json"}}, {"family": "Aswad", "given": "Luay", "initials": "L", "orcid": "0000-0002-8730-9208", "researcher": {"href": "https://publications.scilifelab.se/researcher/f01cefe048a541c7bdab2727d9cfc79d.json"}}, {"family": "Stahl", "given": "Matthias", "initials": "M", "orcid": "0000-0002-0176-9386", "researcher": {"href": "https://publications.scilifelab.se/researcher/f113f8aa6e77444d9492b5fed0067b25.json"}}, {"family": "Kunold", "given": "Elena", "initials": "E"}, {"family": "Post", "given": "Frederik", "initials": "F", "orcid": "0000-0003-0376-1326", "researcher": {"href": "https://publications.scilifelab.se/researcher/439eb72d3314446da93915e854774caf.json"}}, {"family": "Erkers", "given": "Tom", "initials": "T"}, {"family": "Struyf", "given": "Nona", "initials": "N", "orcid": "0000-0002-6975-0753", "researcher": {"href": "https://publications.scilifelab.se/researcher/1295c3be31024c4fa2da10cffe42c406.json"}}, {"family": "Mermelekas", "given": "Georgios", "initials": "G"}, {"family": "Joshi", "given": "Rubin Narayan", "initials": "RN"}, {"family": "Gracia-Villacampa", "given": "Eva", "initials": "E", "orcid": "0000-0003-0353-2101", "researcher": {"href": "https://publications.scilifelab.se/researcher/eaf72d81feea4b7899197c67131a85ba.json"}}, {"family": "\u00d6stling", "given": "P\u00e4ivi", "initials": "P"}, {"family": "Kallioniemi", "given": "Olli P", "initials": "OP"}, {"family": "Tamm", "given": "Katja Pokrovskaja", "initials": "KP", "orcid": "0000-0001-6359-1256", "researcher": {"href": "https://publications.scilifelab.se/researcher/09ec3ee706764024bd748c7a77443845.json"}}, {"family": "Siavelis", "given": "Ioannis", "initials": "I"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Vesterlund", "given": "Mattias", "initials": "M", "orcid": "0000-0001-9471-6592", "researcher": {"href": "https://publications.scilifelab.se/researcher/0942e438993b494db2a3db914852c808.json"}}, {"family": "Jafari", "given": "Rozbeh", "initials": "R", "orcid": "0000-0002-3396-4709", "researcher": {"href": "https://publications.scilifelab.se/researcher/481b2a2329634f9086cf52fb808edea5.json"}}], "type": "journal article", "published": "2022-03-30", "journal": {"title": "Nat Commun", "issn": "2041-1723", "issn-l": "2041-1723", "volume": "13", "issue": "1", "pages": "1691"}, "abstract": "Acute lymphoblastic leukemia (ALL) is the most common childhood cancer. Although standard-of-care chemotherapeutics are sufficient for most ALL cases, there are subsets of patients with poor response who relapse in disease. The biology underlying differences between subtypes and their response to therapy has only partially been explained by genetic and transcriptomic profiling. Here, we perform comprehensive multi-omic analyses of 49 readily available childhood ALL cell lines, using proteomics, transcriptomics, and pharmacoproteomic characterization. We connect the molecular phenotypes with drug responses to 528 oncology drugs, identifying drug correlations as well as lineage-dependent correlations. We also identify the diacylglycerol-analog bryostatin-1 as a therapeutic candidate in the MEF2D-HNRNPUL1 fusion high-risk subtype, for which this drug activates pro-apoptotic ERK signaling associated with molecular mediators of pre-B cell negative selection. Our data is the foundation for the interactive online Functional Omics Resource of ALL (FORALL) with navigable proteomics, transcriptomics, and drug sensitivity profiles at https://proteomics.se/forall .", "doi": "10.1038/s41467-022-29224-5", "pmid": "35354797", "labels": {"National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Production)": "Service", "NGI Short read": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC8967900"}, {"db": "pii", "key": "10.1038/s41467-022-29224-5"}], "notes": [], "created": "2022-08-19T08:37:13.488Z", "modified": "2024-01-16T13:48:37.216Z"}]}