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- Kuci Emruli, Venera, et al.
(författare)
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Identification of a serum biomarker signature associated with metastatic prostate cancer
- 2021
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Ingår i: Proteomics - Clinical Applications. - : Wiley. - 1862-8346 .- 1862-8354. ; 15:2-3
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Improved early diagnosis and determination of aggressiveness of prostate cancer (PC) is important to select suitable treatment options and to decrease over-treatment. The conventional marker is total prostate specific antigen (PSA) levels in blood, but lacks specificity and ability to accurately discriminate indolent from aggressive disease. Experimental design: In this study, we sought to identify a serum biomarker signature associated with metastatic PC. We measured 157 analytes in 363 serum samples from healthy subjects, patients with non-metastatic PC and patients with metastatic PC, using a recombinant antibody microarray. Results: A signature consisting of 69 proteins differentiating metastatic PC patients from healthy controls was identified. Conclusions and clinical relevance: The clinical value of this biomarker signature requires validation in larger independent patient cohorts before providing a new prospect for detection of metastatic PC.
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- Liljedahl, Leena, et al.
(författare)
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Effects of insulin and the glucagon-like peptide 1 receptor agonist liraglutide on the kidney proteome in db/db mice.
- 2017
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Ingår i: Physiological Reports. - : Wiley. - 2051-817X. ; 5:6
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Tidskriftsartikel (refereegranskat)abstract
- Diabetes mellitus (DM) is a worldwide disease that affects 9% of the adult world population and type 2 DM accounts for 90% of those. A common consequence of DM is kidney complications, which could lead to kidney failure. We studied the potential effects of treatment with insulin and the glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide on the diabetic kidney proteome through the use of the db/db mouse model system and mass spectrometry (MS). Multivariate analyses revealed distinct effects of insulin and liraglutide on the db/db kidney proteome, which was seen on the protein levels of, for example, pterin-4 α-carbinolamine dehydratase/dimerization cofactor of hepatocyte nuclear factor-1α (PCBD1), neural precursor cell expressed developmentally down-regulated-8 (NEDD8), transcription elongation factor-B polypeptide-1 (ELOC) and hepcidin (HEPC). Furthermore, the separation of the insulin, liraglutide and vehicle db/db mouse groups in multivariate analyses was not mainly related to the albumin excretion rate (AER) or the level of glycated hemoglobin A1c (HbA1c%) in the mice. In summary, we show that insulin and liraglutide give rise to separate protein profiles in the db/db mouse kidney.
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- Liljedahl, Leena
(författare)
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Exploring the diabetic kidney proteome : A junction of tissue and serum
- 2016. - 1
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Diabetic kidney disease is one of the major complications associated with diabetes. Approximately 25-40% of both type 1 and type 2 diabetes patients will acquire a kidney complication and despite global efforts to reduce the prevalence of diabetic kidney disease, it is a leading cause of kidney failure in the western world. There are few treatment options directly targeting the kidney.The overall aim of this thesis was to dig past the current state of knowledge and delve deeper into the proteomic profile of diabetic kidney disease. By the use of discovery based and targeted mass spectrometry, the kidney proteomes of two diabetic mouse models reflecting type 1 and type 2 diabetes with early kidney disease were investigated and the serum proteomes of diabetes patients with various degrees of albuminuria were compared. In summary, the majority of the changes were seen for proteins with expression in the tubules, the reabsorbing organ in the kidneys and not in the glomeruli, which is the filtering unit. The findings in this thesis could imply that we need to re-think the target of kidney medication and the importance of tubuloglomerular feedback.
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- Liljedahl, Leena, et al.
(författare)
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N-glycosylation proteome enrichment analysis in kidney reveals differences between diabetic mouse models
- 2016
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Ingår i: Clinical Proteomics. - : Springer Science and Business Media LLC. - 1542-6416 .- 1559-0275. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Diabetic nephropathy (DN) is a late complication in both type 1 diabetes mellitus (T1DM) and T2DM. Already at an early stage of DN morphological changes occur at the cell surface and in the extracellular matrix where the majority of the proteins carry N-linked glycosylations. These glycosylated proteins are highly important in cell adhesion and cell-matrix processes but not much is known about how they change in DN or whether the distinct etiology of T1DM and T2DM could have an effect on their abundances. Method: We enriched for the N-glycosylated kidney proteome in db/db mice dosed with insulin or vehicle, in streptozotocin-induced (STZ) diabetic mice and healthy control mice dosed with vehicle. Glycopeptides were analyzed with label-free shotgun mass spectrometry and differential protein abundances identified in both mouse models were compared using multivariate analyses. Results: The majority of the N-glycosylated proteins were similarly regulated in both mouse models. However, distinct differences between the two mouse models were for example seen for integrin-β1, a protein expressed mainly in the glomeruli which abundance was increased in the STZ diabetic mice while decreased in the db/db mice and for the sodium/glucose cotransporter-1, mainly expressed in the proximal tubules which abundance was increased in the db/db mice but decreased in the STZ diabetic mice. Insulin had an effect on the level of both glomerular and tubular proteins in the db/db mice. It decreased the abundance of G-protein coupled receptor-116 and of tyrosine-protein phosphatase non-receptor type substrate-1 away from the level in the healthy control mice. Conclusions: Our finding of differences in the N-glycosylation protein profiles in the db/db and STZ mouse models suggest that the etiology of DN could give rise to variations in the cell adhesion and cell-matrix composition in T1DM and T2DM. Thus, N-glycosylated protein differences could be a clue to dissimilarities in T1DM and T2DM at later stages of DN. Furthermore, we observed insulin specific regulation of N-glycosylated proteins both in the direction of and away from the abundances in healthy control mice.
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- Liljedahl, Leena, et al.
(författare)
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Targeted Selected Reaction Monitoring Verifies Histology Specific Peptide Signatures in Epithelial Ovarian Cancer
- 2021
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 13:22
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Tidskriftsartikel (refereegranskat)abstract
- Simple SummaryOvarian cancer is a lethal disease due to its late phase discovery. Any steps towards improving early diagnostics will dramatically increase survival rates. To identify new ovarian cancer biomarker panels, we need to focus on early-stage disease and all histologic subtypes. In this study we have, based on prior discoveries, constructed a multiplexed targeted selected-reaction-monitoring assay to detect peptides from 177 proteins in only 20 mu L of plasma. The assay was evaluated in patients with a focus on early-stages and all ovarian cancer histologies in separate groups. With multivariate analysis, we found the highest predictive value in the benign vs. low-grade serous (Q2 = 0.615) and mucinous (Q2 = 0.611) early stage compared to all malignant (Q2 = 0.226) or late stage (Q2 = 0.43) ovarian cancers. The results show that each ovarian cancer histology subgroup can be identified by a unique panel of proteins.Epithelial ovarian cancer (OC) is a disease with high mortality due to vague early clinical symptoms. Benign ovarian cysts are common and accurate diagnosis remains a challenge because of the molecular heterogeneity of OC. We set out to investigate whether the disease diversity seen in ovarian cyst fluids and tumor tissue could be detected in plasma. Using existing mass spectrometry (MS)-based proteomics data, we constructed a selected reaction monitoring (SRM) assay targeting peptides from 177 cancer-related and classical proteins associated with OC. Plasma from benign, borderline, and malignant ovarian tumors were used to verify expression (n = 74). Unsupervised and supervised multivariate analyses were used for comparisons. The peptide signatures revealed by the supervised multivariate analysis contained 55 to 77 peptides each. The predictive (Q2) values were higher for benign vs. low-grade serous Q2 = 0.615, mucinous Q2 = 0.611, endometrioid Q2 = 0.428 and high-grade serous Q2 = 0.375 (stage I-II Q2 = 0.515; stage III Q2 = 0.43) OC compared to benign vs. all malignant Q2 = 0.226. With targeted SRM MS we constructed a multiplexed assay for simultaneous detection and relative quantification of 185 peptides from 177 proteins in only 20 mu L of plasma. With the approach of histology-specific peptide patterns, derived from pre-selected proteins, we may be able to detect not only high-grade serous OC but also the less common OC subtypes.
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| 9. |
- Liljedahl, Leena, et al.
(författare)
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The impact of the glucagon-like peptide 1 receptor agonist liraglutide on the streptozotocin-induced diabetic mouse kidney proteome
- 2019
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Ingår i: Physiological Reports. - : Wiley. - 2051-817X. ; 7:4
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Tidskriftsartikel (refereegranskat)abstract
- In diabetes mellitus (DM), the kidneys are exposed to increased levels of hyperglycemia-induced oxidative stress. Elevated amounts of reactive oxygen species (ROS) are believed to provoke ultrastructural changes in kidney tissue and can eventually result in DM late complications such as diabetic nephropathy. While it is reported that glucagon-like peptide 1 receptors (GLP-1R) are present in the kidney vasculature, the effects of GLP-1 on the kidney proteome in DM is not well described. Thus, we set out to investigate potential effects on the proteomic level. Here the effects of GLP-1R agonism using the GLP-1 analogue liraglutide are studied in the kidneys of streptozotocin (STZ)-treated mice (n = 6/group) by label-free shotgun mass spectrometry (MS) and targeted MS. Unsupervised and supervised multivariate analyses are followed by one-way ANOVA. Shotgun MS data of vehicle and liraglutide-treated mouse groups are separated in the supervised multivariate analysis and separation is also achieved in the subsequent unsupervised multivariate analysis using targeted MS data. The mouse group receiving the GLP-1R agonist liraglutide has increased protein abundances of glutathione peroxidase-3 (GPX3) and catalase (CATA) while the abundances of neuroplastin (NPTN) and bifunctional glutamate/proline–tRNA ligase (SYEP) are decreased compared to the STZ vehicle mice. The data suggest that GLP-1R agonism mainly influences abundances of structurally involved proteins and proteins involved in oxidative stress responses in the STZ mouse kidney. The changes could be direct effects of GLP-1R agonism in the kidneys or indirectly caused by a systemic response to GLP-1R activation.
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- Lundmark, Per E, et al.
(författare)
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Evaluation of HapMap data in six populations of European descent
- 2008
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Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 16:9, s. 1142-1150
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Tidskriftsartikel (refereegranskat)abstract
- We studied how well the European CEU samples used in the Haplotype Mapping Project (HapMap) represent five European populations by analyzing nuclear family samples from the Swedish, Finnish, Dutch, British and Australian (European ancestry) populations. The number of samples from each population (about 30 parent-offspring trios) was similar to that in the HapMap sample sets. A panel of 186 single nucleotide polymorphisms (SNPs) distributed over the 1.5 Mb region of the GRID2 gene on chromosome 4 was genotyped. The genotype data were compared pair-wise between the HapMap sample and the other population samples. Principal component analysis (PCA) was used to cluster the data from different populations with respect to allele frequencies and to define the markers responsible for observed variance. The only sample with detectable differences in allele frequencies was that from Kuusamo, Finland. This sample also separated from the others, including the other Finnish sample, in the PCA analysis. A set of tagSNPs was defined based on the HapMap data and applied to the samples. The tagSNPs were found to capture the genetic variation in the analyzed region at r(2)>0.8 at levels ranging from 95% in the Kuusamo sample to 87% in the Australian sample. To capture the maximal genetic variation in the region, the Kuusamo, HapMap and Australian samples required 58, 63 and 73 native tagSNPs, respectively. The HapMap CEU sample represents the European samples well for tagSNP selection, with some caution regarding estimation of allele frequencies in the Finnish Kuusamo sample, and a slight reduction in tagging efficiency in the Australian sample.
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