{"entity": "researcher", "timestamp": "2026-06-09T03:27:33.409Z", "family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "affiliations": ["Affinity Proteomics, Science for Life Laboratory, Department of Protein Science, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Tomtebodav\u00e4gen 23, 171 65 Stockholm, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b"}}, "publications": [{"entity": "publication", "iuid": "a13b9b2a120741f2af40dbd525b2c748", "links": {"self": {"href": "https://publications.scilifelab.se/publication/a13b9b2a120741f2af40dbd525b2c748.json"}, "display": {"href": "https://publications.scilifelab.se/publication/a13b9b2a120741f2af40dbd525b2c748"}}, "title": "Exploration of immune phenotypes in self-sampling citizens", "authors": [{"family": "Dahl", "given": "Leo", "initials": "L", "orcid": "0000-0003-1492-3052", "researcher": {"href": "https://publications.scilifelab.se/researcher/d4df506f315c4289935b935a503efd56.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "\u00c1lvez", "given": "Mar\u00eda Bueno", "initials": "MB", "orcid": "0000-0002-2669-7796", "researcher": {"href": "https://publications.scilifelab.se/researcher/b6a18cc0ce34429a91758206cedb5d60.json"}}, {"family": "Albrecht", "given": "Vincent", "initials": "V", "orcid": "0009-0003-1985-7733", "researcher": {"href": "https://publications.scilifelab.se/researcher/4d422e623e9e449f98853e6830cdd401.json"}}, {"family": "Aghelpasand", "given": "Hooman", "initials": "H"}, {"family": "Bj\u00f6rkander", "given": "Sophia", "initials": "S", "orcid": "0000-0002-4600-2883", "researcher": {"href": "https://publications.scilifelab.se/researcher/310af30b841741a790046af03a3cee6d.json"}}, {"family": "Merid", "given": "Simon Kebede", "initials": "SK", "orcid": "0000-0001-5974-7676", "researcher": {"href": "https://publications.scilifelab.se/researcher/c7a04c6538814b089994c7a822ecf07f.json"}}, {"family": "Mezger", "given": "Anja", "initials": "A", "orcid": "0000-0002-7337-9547", "researcher": {"href": "https://publications.scilifelab.se/researcher/ebf61fe41e6f43e4aec2be101de688d4.json"}}, {"family": "K\u00e4ller", "given": "Max", "initials": "M", "orcid": "0000-0001-6813-3051", "researcher": {"href": "https://publications.scilifelab.se/researcher/536ad902a272482aba853c078557e240.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Naluai", "given": "\u00c5sa Torinsson", "initials": "\u00c5T"}, {"family": "Beck", "given": "Olof", "initials": "O"}, {"family": "Mel\u00e9n", "given": "Erik", "initials": "E", "orcid": "0000-0002-8248-0663", "researcher": {"href": "https://publications.scilifelab.se/researcher/3af5a23ba0a847778eea300f745cb143.json"}}, {"family": "Bauer", "given": "Stefan", "initials": "S"}, {"family": "Gissl\u00e9n", "given": "Magnus", "initials": "M", "orcid": "0000-0002-2357-1020", "researcher": {"href": "https://publications.scilifelab.se/researcher/8b50df8c8ecc45b89574dc76e244b07e.json"}}, {"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal-article", "published": "2026-02-00", "journal": {"title": "iScience", "issn": "2589-0042", "volume": "29", "issue": "2", "pages": "114611", "issn-l": "2589-0042"}, "abstract": "Blood proteins have provided essential insights into how humans responded to the recent pandemic. To expand our understanding beyond patients seeking medical care, we conducted a citizen-centric survey with 2,000 random residents (age: 18-69 years) from Sweden's two largest cities in 2021. With self-sampled dried blood spots (DBS) and health information from 437 (22%) volunteers, we performed multi-analyte COVID-19 serology, measured autoantibodies (AAbs) against 22 interferons, and quantified 502 circulating low-abundant immune-related blood proteins. Antibody assays confirmed self-reported infections (26%) and vaccinations (40%), showed timing-dependent discrepancies in the immune response, and revealed anti-type I interferon AAbs co-occurring frequently alongside natural infections. Proteomics data added plausible mechanistic insights into cell-mediated processes: data-driven analyses revealed 24% of participants presented deviating immune phenotypes linked to infections, immunity, respiratory effects, and age. Multi-molecular DBS analysis of random layperson samples captured the broader spectrum of immune system states, adding relevant insights for clinical and public health investigations.", "doi": "10.1016/j.isci.2025.114611", "pmid": "41630906", "labels": {"National Genomics Infrastructure": "Collaborative", "NGI Stockholm (Genomics Production)": "Service", "NGI Stockholm (Genomics Applications)": "Collaborative", "NGI Short read": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC12860695"}, {"db": "pii", "key": "S2589-0042(25)02872-X"}], "notes": [], "created": "2026-02-26T13:37:49.302Z", "modified": "2026-03-24T09:13:34.204Z"}, {"entity": "publication", "iuid": "80e99fbd84564cf4ac30476f23324ecb", "links": {"self": {"href": "https://publications.scilifelab.se/publication/80e99fbd84564cf4ac30476f23324ecb.json"}, "display": {"href": "https://publications.scilifelab.se/publication/80e99fbd84564cf4ac30476f23324ecb"}}, "title": "Frequent longitudinal blood microsampling and proteome monitoring identify disease markers and enable timely intervention in a mouse model of type 1 diabetes.", "authors": [{"family": "Parajuli", "given": "Anirudra", "initials": "A", "orcid": "0000-0001-6886-0566", "researcher": {"href": "https://publications.scilifelab.se/researcher/8fe93f2ebd614b8aad9655bbde6b4561.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Byvald", "given": "Fabian", "initials": "F", "orcid": "0000-0003-0516-5448", "researcher": {"href": "https://publications.scilifelab.se/researcher/c9f5e5ac109d4efaa0878ff7b21e07e2.json"}}, {"family": "Stone", "given": "Virginia M", "initials": "VM", "orcid": "0000-0003-3091-2142", "researcher": {"href": "https://publications.scilifelab.se/researcher/e7c201c6440e42419ca79d35c2b7dbcc.json"}}, {"family": "Ringqvist", "given": "Emma E", "initials": "EE", "orcid": "0000-0001-6303-6076", "researcher": {"href": "https://publications.scilifelab.se/researcher/cfad17442063471cb570d5be1c4dbc48.json"}}, {"family": "Butrym", "given": "Marta", "initials": "M", "orcid": "0000-0002-9285-7276", "researcher": {"href": "https://publications.scilifelab.se/researcher/81afcc509ade4f959e996f2ce8775fbc.json"}}, {"family": "Angelis", "given": "Emmanouil", "initials": "E"}, {"family": "Kipper", "given": "Sophie", "initials": "S", "orcid": "0009-0004-8075-1660", "researcher": {"href": "https://publications.scilifelab.se/researcher/d1d4e2b9a8984cad89430969277a9f73.json"}}, {"family": "Bauer", "given": "Stefan", "initials": "S", "orcid": "0000-0003-1712-060X", "researcher": {"href": "https://publications.scilifelab.se/researcher/4cc1926b89e545f4973968445a4fead0.json"}}, {"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "Flodstr\u00f6m-Tullberg", "given": "Malin", "initials": "M", "orcid": "0000-0003-2685-2052", "researcher": {"href": "https://publications.scilifelab.se/researcher/bb6d04afbe8141c2b9297854de64dab8.json"}}], "type": "journal article", "published": "2025-10-00", "journal": {"title": "Diabetologia", "issn": "1432-0428", "volume": "68", "issue": "10", "pages": "2277-2289", "issn-l": "0012-186X"}, "abstract": "Type 1 diabetes manifests after irreversible beta cell damage, highlighting the crucial need for markers of the presymptomatic phase to enable early and effective interventions. Current efforts to identify molecular markers of disease-triggering events lack resolution and convenience. Analysing frequently self-collected dried blood spots (DBS) could enable the detection of early disease-predictive markers and facilitate tailored interventions. Here, we present a novel strategy for monitoring transient molecular changes induced by environmental triggers that enable timely disease interception.\n\nWhole blood (10 \u03bcl) was sampled regularly (every 1-5 days) from adult NOD mice infected with Coxsackievirus B3 (CVB3) or treated with vehicle alone. Blood samples (5 \u03bcl) were dried on filter discs. DBS samples were analysed by proximity extension assay. Generalised additive models were used to assess linear and non-linear relationships between protein levels and the number of days post infection (p.i.). A multi-layer perceptron (MLP) classifier was developed to predict infection status. CVB3-infected SOCS-1-transgenic (tg) mice were treated with immune- or non-immune sera on days 2 and 3 p.i., followed by monitoring of diabetes development.\n\nFrequent blood sampling and longitudinal measurement of the blood proteome revealed transient molecular changes in virus-infected animals that would have been missed with less frequent sampling. The MLP classifier predicted infection status after day 2 p.i. with over 90% accuracy. Treatment with immune sera on day 2 p.i. prevented diabetes development in all (100%) of CVB3-infected SOCS-1-tg NOD mice while five out of eight (62.5%) of the CVB3-infected controls treated with non-immune sera developed diabetes.\n\nOur study demonstrates the utility of frequently collected DBS samples to monitor dynamic proteome changes induced by an environmental trigger during the presymptomatic phase of type 1 diabetes. This approach enables disease interception and can be translated into human initiatives, offering a new method for early detection and intervention in type 1 diabetes.\n\nAdditional data available at https://doi.org/10.17044/scilifelab.27368322 . Additional visualisations are presented in the Shiny app interface https://mouse-dbs-profiling.serve.scilifelab.se/ .", "doi": "10.1007/s00125-025-06502-7", "pmid": "40760251", "labels": {"Affinity Proteomics Stockholm": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12423192"}, {"db": "pii", "key": "10.1007/s00125-025-06502-7"}], "notes": [], "created": "2025-09-19T16:31:14.024Z", "modified": "2025-09-19T16:31:15.201Z"}, {"entity": "publication", "iuid": "111154cd228d47fabf63f871f677a0d7", "links": {"self": {"href": "https://publications.scilifelab.se/publication/111154cd228d47fabf63f871f677a0d7.json"}, "display": {"href": "https://publications.scilifelab.se/publication/111154cd228d47fabf63f871f677a0d7"}}, "title": "Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections.", "authors": [{"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Dodig-Crnkovi\u0107", "given": "Tea", "initials": "T"}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Dahl", "given": "Leo", "initials": "L", "orcid": "0000-0003-1492-3052", "researcher": {"href": "https://publications.scilifelab.se/researcher/d4df506f315c4289935b935a503efd56.json"}}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Albrecht", "given": "Vincent", "initials": "V", "orcid": "0009-0003-1985-7733", "researcher": {"href": "https://publications.scilifelab.se/researcher/4d422e623e9e449f98853e6830cdd401.json"}}, {"family": "Mattsson", "given": "Cecilia", "initials": "C"}, {"family": "Thomas", "given": "Cecilia E", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "Torinsson Naluai", "given": "\u00c5sa", "initials": "\u00c5", "orcid": "0000-0002-0504-6492", "researcher": {"href": "https://publications.scilifelab.se/researcher/bcf3474dc7054c598cbe3a195deb8a1b.json"}}, {"family": "Gisslen", "given": "Magnus", "initials": "M"}, {"family": "Beck", "given": "Olof", "initials": "O"}, {"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal article", "published": "2024-04-02", "journal": {"title": "Commun Med (Lond)", "issn": "2730-664X", "issn-l": null, "volume": "4", "issue": "1", "pages": "55"}, "abstract": "Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.\r\n\r\nOur study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.\r\n\r\nOur three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors.\r\n\r\nProteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.", "doi": "10.1038/s43856-024-00480-4", "pmid": "38565620", "labels": {"Affinity Proteomics Stockholm": "Technology development", "Autoimmunity and Serology Profiling": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC10987641"}, {"db": "pii", "key": "10.1038/s43856-024-00480-4"}], "notes": [], "created": "2024-04-18T09:27:59.211Z", "modified": "2024-08-28T11:04:43.993Z"}, {"entity": "publication", "iuid": "48993691f2c64543b650f3b600450b73", "links": {"self": {"href": "https://publications.scilifelab.se/publication/48993691f2c64543b650f3b600450b73.json"}, "display": {"href": "https://publications.scilifelab.se/publication/48993691f2c64543b650f3b600450b73"}}, "title": "Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2.", "authors": [{"family": "Roxhed", "given": "Niclas", "initials": "N", "orcid": "0000-0002-7147-6730", "researcher": {"href": "https://publications.scilifelab.se/researcher/3739210caaf14a28898849f20bf6ece5.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Dale", "given": "Matilda", "initials": "M", "orcid": "0000-0002-5788-7744", "researcher": {"href": "https://publications.scilifelab.se/researcher/59306e7e902048829efb30599ee3d2b1.json"}}, {"family": "Mattsson", "given": "Cecilia", "initials": "C"}, {"family": "Hanke", "given": "Leo", "initials": "L", "orcid": "0000-0001-5514-2418", "researcher": {"href": "https://publications.scilifelab.se/researcher/ece050a286f946f6807170cffc9320e7.json"}}, {"family": "Dodig-Crnkovi\u0107", "given": "Tea", "initials": "T", "orcid": "0000-0002-2875-896X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cf18af5b676b449693945249fc1767e4.json"}}, {"family": "Christian", "given": "Murray", "initials": "M"}, {"family": "Meineke", "given": "Birthe", "initials": "B"}, {"family": "Els\u00e4sser", "given": "Simon", "initials": "S", "orcid": "0000-0001-8724-4849", "researcher": {"href": "https://publications.scilifelab.se/researcher/fcf26e35e037499aa1441a7738ba61af.json"}}, {"family": "Andr\u00e9ll", "given": "Juni", "initials": "J"}, {"family": "Havervall", "given": "Sebastian", "initials": "S"}, {"family": "Th\u00e5lin", "given": "Charlotte", "initials": "C", "orcid": "0000-0002-1345-6491", "researcher": {"href": "https://publications.scilifelab.se/researcher/130fb6ef6b774613a767e98f9f9b2eb4.json"}}, {"family": "Eklund", "given": "Carina", "initials": "C"}, {"family": "Dillner", "given": "Joakim", "initials": "J", "orcid": "0000-0001-8588-6506", "researcher": {"href": "https://publications.scilifelab.se/researcher/2b5c258635ad412f9e79994dcee4e323.json"}}, {"family": "Beck", "given": "Olof", "initials": "O"}, {"family": "Thomas", "given": "Cecilia E", "initials": "CE", "orcid": "0000-0001-6201-6380", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1156f987764218af202efbd76c31fd.json"}}, {"family": "McInerney", "given": "Gerald", "initials": "G", "orcid": "0000-0003-2257-7241", "researcher": {"href": "https://publications.scilifelab.se/researcher/5ac2f68095fe4426b97ec070865e5091.json"}}, {"family": "Hong", "given": "Mun-Gwan", "initials": "M"}, {"family": "Murrell", "given": "Ben", "initials": "B", "orcid": "0000-0002-0393-4445", "researcher": {"href": "https://publications.scilifelab.se/researcher/8a899203048943489bf7b6310a32b19f.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}], "type": "journal article", "published": "2021-06-17", "journal": {"title": "Nat Commun", "issn": "2041-1723", "issn-l": "2041-1723", "volume": "12", "issue": "1", "pages": "3695"}, "abstract": "Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgG+IgM+ against several SARS-CoV-2 proteins, as well as 2.1% being IgG-IgM+ and 5.0% being IgG+IgM- for the virus' S protein. Subjects classified as IgG+ for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG+ for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.", "doi": "10.1038/s41467-021-23893-4", "pmid": "34140485", "labels": {"Affinity Proteomics Stockholm": "Technology development"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-021-23893-4"}, {"db": "pmc", "key": "PMC8211676"}], "notes": [], "created": "2021-10-05T16:26:34.397Z", "modified": "2021-12-06T07:43:55.459Z"}, {"entity": "publication", "iuid": "a074964a79c24ad1b92ce498859976e4", "links": {"self": {"href": "https://publications.scilifelab.se/publication/a074964a79c24ad1b92ce498859976e4.json"}, "display": {"href": "https://publications.scilifelab.se/publication/a074964a79c24ad1b92ce498859976e4"}}, "title": "Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer.", "authors": [{"family": "Drobin", "given": "Kimi", "initials": "K"}, {"family": "Marczyk", "given": "Michal", "initials": "M", "orcid": "0000-0003-2508-5736", "researcher": {"href": "https://publications.scilifelab.se/researcher/f41817907c56448991e2c9e94f15da42.json"}}, {"family": "Halle", "given": "Martin", "initials": "M"}, {"family": "Danielsson", "given": "Daniel", "initials": "D", "orcid": "0000-0001-9407-2774", "researcher": {"href": "https://publications.scilifelab.se/researcher/45064e20ddfc4eadb626612584d8f95a.json"}}, {"family": "Papiez", "given": "Anna", "initials": "A", "orcid": "0000-0003-0179-1302", "researcher": {"href": "https://publications.scilifelab.se/researcher/f12e4932eb264f0096db641d0915e3b6.json"}}, {"family": "Sangsuwan", "given": "Traimate", "initials": "T", "orcid": "0000-0003-4051-8376", "researcher": {"href": "https://publications.scilifelab.se/researcher/7521353e59bd45f68393e2f85b2a978f.json"}}, {"family": "Bendes", "given": "Annika", "initials": "A", "orcid": "0000-0001-9329-2353", "researcher": {"href": "https://publications.scilifelab.se/researcher/50dffce4f4444dd8b5ff8f9294146a0b.json"}}, {"family": "Hong", "given": "Mun-Gwan", "initials": "MG", "orcid": "0000-0001-8603-8293", "researcher": {"href": "https://publications.scilifelab.se/researcher/5d66c199ece143a6ab15222d8b55e3ea.json"}}, {"family": "Qundos", "given": "Ulrika", "initials": "U"}, {"family": "Harms-Ringdahl", "given": "Mats", "initials": "M"}, {"family": "Wers\u00e4ll", "given": "Peter", "initials": "P"}, {"family": "Polanska", "given": "Joanna", "initials": "J", "orcid": "0000-0001-8004-9864", "researcher": {"href": "https://publications.scilifelab.se/researcher/329d4bcbf1e64ecca6bc2b3505cc8901.json"}}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "Haghdoost", "given": "Siamak", "initials": "S", "orcid": "0000-0002-2867-4774", "researcher": {"href": "https://publications.scilifelab.se/researcher/e53acb351cb34d49924b840e1b2d2dc1.json"}}], "type": "journal article", "published": "2020-03-22", "journal": {"title": "Cancers (Basel)", "issn": "2072-6694", "issn-l": "2072-6694", "volume": "12", "issue": "3", "pages": "753"}, "abstract": "Nearly half of all cancers are treated with radiotherapy alone or in combination with other treatments, where damage to normal tissues is a limiting factor for the treatment. Radiotherapy-induced adverse health effects, mostly of importance for cancer patients with long-term survival, may appear during or long time after finishing radiotherapy and depend on the patient's radiosensitivity. Currently, there is no assay available that can reliably predict the individual's response to radiotherapy. We profiled two study sets from breast (n = 29) and head-and-neck cancer patients (n = 74) that included radiosensitive patients and matched radioresistant controls.. We studied 55 single nucleotide polymorphisms (SNPs) in 33 genes by DNA genotyping and 130 circulating proteins by affinity-based plasma proteomics. In both study sets, we discovered several plasma proteins with the predictive power to find radiosensitive patients (adjusted p < 0.05) and validated the two most predictive proteins (THPO and STIM1) by sandwich immunoassays. By integrating genotypic and proteomic data into an analysis model, it was found that the proteins CHIT1, PDGFB, PNKD, RP2, SERPINC1, SLC4A, STIM1, and THPO, as well as the VEGFA gene variant rs69947, predicted radiosensitivity of our breast cancer (AUC = 0.76) and head-and-neck cancer (AUC = 0.89) patients. In conclusion, circulating proteins and a SNP variant of VEGFA suggest that processes such as vascular growth capacity, immune response, DNA repair and oxidative stress/hypoxia may be involved in an individual's risk of experiencing radiation-induced toxicity.", "doi": "10.3390/cancers12030753", "pmid": "32235817", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "cancers12030753"}, {"db": "pmc", "key": "PMC7140105"}], "notes": [], "created": "2020-12-10T19:03:40.959Z", "modified": "2021-11-10T12:52:54.485Z"}]}