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Byström, Sanna
Publications (5 of 5) Show all publications
Fredolini, C., Byström, S., Sanchez-Rivera, L., Ioannou, M., Tamburro, D., Pontén, F., . . . Schwenk, J. M. (2019). Systematic assessment of antibody selectivity in plasma based on a resource of enrichment profiles. Scientific Reports, 9, Article ID 8324.
Open this publication in new window or tab >>Systematic assessment of antibody selectivity in plasma based on a resource of enrichment profiles
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 8324Article in journal (Refereed) Published
Abstract [en]

There is a strong need for procedures that enable context and application dependent validation of antibodies. Here, we applied a magnetic bead assisted workflow and immunoprecipitation mass spectrometry (IP-MS/MS) to assess antibody selectivity for the detection of proteins in human plasma. A resource was built on 414 IP experiments using 157 antibodies (targeting 120 unique proteins) in assays with heat-treated or untreated EDTA plasma. For each protein we determined their antibody related degrees of enrichment using z-scores and their frequencies of identification across all IP assays. Out of 1,313 unique endogenous proteins, 426 proteins (33%) were detected in >20% of IPs, and these background components were mainly comprised of proteins from the complement system. For 45% (70/157) of the tested antibodies, the expected target proteins were enriched (z-score >= 3). Among these 70 antibodies, 59 (84%) co-enriched other proteins beside the intended target and mainly due to sequence homology or protein abundance. We also detected protein interactions in plasma, and for IGFBP2 confirmed these using several antibodies and sandwich immunoassays. The protein enrichment data with plasma provide a very useful and yet lacking resource for the assessment of antibody selectivity. Our insights will contribute to a more informed use of affinity reagents for plasma proteomics assays.

Place, publisher, year, edition, pages
Nature Publishing Group, 2019
National Category
Bioinformatics and Systems Biology
Identifiers
urn:nbn:se:kth:diva-254077 (URN)10.1038/s41598-019-43552-5 (DOI)000470243800005 ()31171813 (PubMedID)2-s2.0-85067067842 (Scopus ID)
Note

QC 20190624

Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2019-06-24Bibliographically approved
Häussler, R. S., Bendes, A., Iglesias, M. J., Sanchez-Rivera, L., Dodig-Crnkovic, T., Byström, S., . . . Schwenk, J. M. (2019). Systematic Development of Sandwich Immunoassays for the Plasma Secretome. Proteomics, Article ID 1900008.
Open this publication in new window or tab >>Systematic Development of Sandwich Immunoassays for the Plasma Secretome
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2019 (English)In: Proteomics, ISSN 1615-9853, E-ISSN 1615-9861, article id 1900008Article in journal (Refereed) Published
Abstract [en]

The plasma proteome offers a clinically useful window into human health. Recent advances from highly multiplexed assays now call for appropriate pipelines to validate individual candidates. Here, a workflow is developed to build dual binder sandwich immunoassays (SIA) and for proteins predicted to be secreted into plasma. Utilizing suspension bead arrays, ≈1800 unique antibody pairs are first screened against 209 proteins with recombinant proteins as well as EDTA plasma. Employing 624 unique antibodies, dilution-dependent curves in plasma and concentration-dependent curves of full-length proteins for 102 (49%) of the targets are obtained. For 22 protein assays, the longitudinal, interindividual, and technical performance is determined in a set of plasma samples collected from 18 healthy subjects every third month over 1 year. Finally, 14 of these assays are compared with with SIAs composed of other binders, proximity extension assays, and affinity-free targeted mass spectrometry. The workflow provides a multiplexed approach to screen for SIA pairs that suggests using at least three antibodies per target. This design is applicable for a wider range of targets of the plasma proteome, and the assays can be applied for discovery but also to validate emerging candidates derived from other platforms.

Place, publisher, year, edition, pages
Wiley, 2019
Keywords
antibodies, plasma, sandwich assays, screening, secreted proteins
National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:kth:diva-255741 (URN)10.1002/pmic.201900008 (DOI)000477448900001 ()31278833 (PubMedID)
Note

QC 20190812

Available from: 2019-08-12 Created: 2019-08-12 Last updated: 2019-08-12Bibliographically approved
Byström, S., Eklund, M., Hong, M.-G., Fredolini, C., Eriksson, M., Czene, K., . . . Gabrielson, M. (2018). Affinity proteomic profiling of plasma for proteins associated to area-based mammographic breast density. Breast Cancer Research, 20, Article ID 14.
Open this publication in new window or tab >>Affinity proteomic profiling of plasma for proteins associated to area-based mammographic breast density
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2018 (English)In: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 20, article id 14Article in journal (Refereed) Published
Abstract [en]

Background: Mammographic breast density is one of the strongest risk factors for breast cancer, but molecular understanding of how breast density relates to cancer risk is less complete. Studies of proteins in blood plasma, possibly associated with mammographic density, are well-suited as these allow large-scale analyses and might shed light on the association between breast cancer and breast density. Methods: Plasma samples from 1329 women in the Swedish KARMA project, without prior history of breast cancer, were profiled with antibody suspension bead array (SBA) assays. Two sample sets comprising 729 and 600 women were screened by two different SBAs targeting a total number of 357 proteins. Protein targets were selected through searching the literature, for either being related to breast cancer or for being linked to the extracellular matrix. Association between proteins and absolute area-based breast density (AD) was assessed by quantile regression, adjusting for age and body mass index (BMI). Results: Plasma profiling revealed linear association between 20 proteins and AD, concordant in the two sets of samples (p < 0.05). Plasma levels of seven proteins were positively associated and 13 proteins negatively associated with AD. For eleven of these proteins evidence for gene expression in breast tissue existed. Among these, ABCC11, TNFRSF10D, F11R and ERRF were positively associated with AD, and SHC1, CFLAR, ACOX2, ITGB6, RASSF1, FANCD2 and IRX5 were negatively associated with AD. Conclusions: Screening proteins in plasma indicates associations between breast density and processes of tissue homeostasis, DNA repair, cancer development and/or progression in breast cancer. Further validation and follow-up studies of the shortlisted protein candidates in independent cohorts will be needed to infer their role in breast density and its progression in premenopausal and postmenopausal women.

Place, publisher, year, edition, pages
BIOMED CENTRAL LTD, 2018
Keywords
Mammographic breast density, Plasma, Protein profiling, Suspension bead array, Affinity proteomics, KARMA cohort
National Category
Clinical Medicine
Identifiers
urn:nbn:se:kth:diva-223790 (URN)10.1186/s13058-018-0940-z (DOI)000425114200001 ()29444691 (PubMedID)2-s2.0-85042063089 (Scopus ID)
Funder
Swedish Research CouncilThe Kamprad Family FoundationKnut and Alice Wallenberg FoundationSwedish Cancer SocietyScience for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180307

Available from: 2018-03-07 Created: 2018-03-07 Last updated: 2018-03-07Bibliographically approved
Byström, S., Eklund, M., Hong, M.-G., Fredolini, C., Eriksson, M., Czene, K., . . . Gabrielson, M.Affinity proteomic profiling of plasma for proteins associated to mammographic breast density.
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(English)Manuscript (preprint) (Other academic)
National Category
Cancer and Oncology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-202615 (URN)
Note

QC 20170302

Available from: 2017-03-02 Created: 2017-03-02 Last updated: 2017-03-13Bibliographically approved
Byström, S., Fredolini, C., Edqvist, P.-H., Nyaiesh, E.-N., Drobin, K., Uhlén, M., . . . Schwenk, J. M.Affinity proteomics exploration of melanoma identifies proteins in serum with associations to T-stage and recurrence.
Open this publication in new window or tab >>Affinity proteomics exploration of melanoma identifies proteins in serum with associations to T-stage and recurrence
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(English)Manuscript (preprint) (Other academic)
National Category
Cancer and Oncology Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Identifiers
urn:nbn:se:kth:diva-202614 (URN)
Note

QC 20170302

Available from: 2017-03-02 Created: 2017-03-02 Last updated: 2017-03-13Bibliographically approved
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