| 1. |
- Olsson, Niclas, et al.
(författare)
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Grading breast cancer tissues using molecular portraits.
- 2013
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Ingår i: Molecular & Cellular Proteomics. - 1535-9484. ; 12:12, s. 3612-3623
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Tidskriftsartikel (refereegranskat)abstract
- Tumor progression and prognosis of breast cancer patients is difficult to assess using current clinical and laboratory parameters, where a pathological grading is indicative of tumor aggressiveness. This grading is based on assessment of nuclear grade, tubule formation, and mitotic rate. We report here the first protein signatures associated with histological grades of breast cancer, using a novel affinity proteomics approach. We profiled 52 breast cancer tissue samples, by combining nine antibodies and label-free LC-MS/MS, which generated detailed quantified proteomic maps representing 1,388 proteins. The results showed that we could define in-depth molecular portraits of histologically graded breast cancer tumors. Consequently, a 49-plex candidate tissue protein signature was defined that discriminated between histological grade 1, 2, and 3 of breast cancer tumors with high accuracy. Highly biologically relevant proteins were identified, and the differentially expressed proteins indicated further support for the current hypothesis regarding remodeling of tumor microenvironment during tumor progression. The protein signature was corroborated using meta-analysis of transcriptional profiling data from an independent patient cohort. In addition, the potential for using the markers to estimate the risk of distant metastasis free survival was also indicated. Taken together, these molecular portraits could pave the way for improved classification and prognostication of breast cancer.
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| 2. |
- Olsson, Petter, et al.
(författare)
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Cognitive Function in Older Suicide Attempters and a Population-Based Comparison Group
- 2016
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Ingår i: Journal of Geriatric Psychiatry and Neurology. - : SAGE Publications. - 0891-9887 .- 1552-5708. ; 29:3, s. 133-41
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Tidskriftsartikel (refereegranskat)abstract
- The aim was to compare cognitive function in older suicide attempters with a population-based comparison group. METHODS: Hospitalized suicide attempters aged 70 years and older were assessed cognitively at baseline (n = 99) and 1-year follow-up (n = 59). Depression symptoms were rated with the Montgomery-Åsberg Depression Rating Scale (MADRS). Results of cognitive assessments in attempters were compared with results in nonattempter comparison subjects (n = 115) selected among participants in our population-based health studies to yield a similar distribution of MADRS scores. RESULTS: Suicide attempters scored lower on Mini-Mental State Examination (MMSE) than comparison persons. Among attempters, the mean MMSE score was lower in those with medically serious attempts. Attempters displayed poorer performance on tests of pentagon drawing and abstract thinking compared to comparison persons, and the results remained also after exclusion of those with medically serious attempts. At 1-year follow-up, significant improvement in MADRS scores was observed in the attempters. No evidence of improvement could be shown regarding cognitive deficits. CONCLUSION: Older suicide attempters may have cognitive deficits, which may in part be related to the attempt itself. This needs to be taken into account when designing intervention strategies.
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| 3. |
- Sandström Gerdtsson, Anna, et al.
(författare)
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A Multicenter Trial Defining a Serum Protein Signature Associated with Pancreatic Ductal Adenocarcinoma.
- 2015
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Ingår i: International Journal of Proteomics. - : Hindawi Limited. - 2090-2174 .- 2090-2166. ; 2015
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Tidskriftsartikel (refereegranskat)abstract
- Background. Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with rapid tumor progression and poor prognosis. This study was motivated by the lack of sensitive and specific PDAC biomarkers and aimed to identify a diagnostic, serum protein signature for PDAC. Methods. To mimic a real life test situation, a multicenter trial comprising a serum sample cohort, including 338 patients with either PDAC or other pancreatic diseases (OPD) and controls with nonpancreatic conditions (NPC), was analyzed on 293-plex recombinant antibody microarrays targeting immunoregulatory and cancer-associated antigens. Results. Serum samples collected from different hospitals were analyzed and showed that (i) sampling from five different hospitals could not be identified as a preanalytical variable and (ii) a multiplexed biomarker signature could be identified, utilizing up to 10 serum markers that could discriminate PDAC from controls, with sensitivities and specificities in the 91-100% range. The first protein profiles associated with the location of the primary tumor in the pancreas could also be identified. Conclusions. The results demonstrate that robust enough serum signatures could be identified in a multicenter trial, potentially contributing to the development of a multiplexed biomarker immunoassay for improved PDAC diagnosis.
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| 4. |
- Skoog, Petter
(författare)
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Molecular Portraits of Cancer : Discovery of Biomarker Signatures using Affinity Proteomics
- 2017. - 1
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The use of antibodies as capture molecules in assays is a common practice. By either printing monoclonal single chain fragment variables (scFvs) on a solid support – recombinant antibody microarray – or attaching them to magnetic beads – Global Proteome Survey (GPS) – we can specifically capture and measure target proteins of interest. Using the recombinant antibody microarray, we target predominantly intact immunoregualtory proteins, and measure their expression patterns in clinical samples, such as cancer samples. With GPS, we target peptides derived from digested (cancer) samples to identify and quantify a variety of proteins. While antibody microarrays use one antibody per targeted protein, GPS targets peptides, where one antibody can bind hundreds of different proteins – i.e. one antibody per several target proteins. The latter is accomplished by designing antibodies against a short 4 to6 amino acid long peptide motif shared among these proteins. In this thesis, both of these methods have been used to decipher cancer biomarker signatures.In paper I, the antibody microarray was used to examine the immunosignature of pancreatic ductal adenocarcinoma (PDAC), and how the profile of the immune response differed between cancer patients compared to both healthy and benign controls. We successfully identified an immunosignature of four to ten scFv antibodies that could classify PDAC from controls with high specificity and sensitivity.In paper II we investigated with the antibody microarray how the immune response evolved with, and shaped, emerging cancer cells in patients later diagnosed with breast cancer using antibody microarray. By determining protein expression profiles for cases and controls, we identified several deregulated immunological proteins that reflected evolving breast cancer, up to two years before diagnosis.In papers III and IV, we used both the antibody microarrays and GPS to decipher biomarker signatures to differentiate between histological grades in breast cancer tumors. With molecular signatures capable of classifying grade, we could also visualize the heterogeneity of intermediate grade 2 tumors. Grade 2 tumors have little clinical prognostic value, and a majority of samples are classified as grade 2. Results from paper IV showed that it might be possible to reclassify many of these samples as either grade 1 or 3, giving clinicians further information for optimal treatment selection.In conclusion, in this thesis I have demonstrated the use of profiling parts of the immune response as a tool for surveying and classifying disease, by using antibodies as specific binders to capture and measure low and high abundant proteins.
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| 5. |
- Skoog, Petter, et al.
(författare)
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Tumor tissue protein signatures reflect histological grade of breast cancer
- 2017
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203.
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Tidskriftsartikel (refereegranskat)abstract
- Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care
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