| 1. |
- Braadland, Peder Rustoen, et al.
(författare)
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Low beta(2)-adrenergic receptor level may promote development of castration resistant prostate cancer and altered steroid metabolism
- 2016
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Ingår i: Oncotarget. - : Impact Journals, LLC. - 1949-2553. ; 7:2, s. 1878-1894
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Tidskriftsartikel (refereegranskat)abstract
- The underlying mechanisms responsible for the development of castration-resistant prostate cancer (CRPC) in patients who have undergone androgen deprivation therapy are not fully understood. This is the first study to address whether beta(2)-adrenergic receptor (ADRB2)- mediated signaling may affect CRPC progression in vivo. By immunohistochemical analyses, we observed that low levels of ADRB2 is associated with a more rapid development of CRPC in a Norwegian patient cohort. To elucidate mechanisms by which ADRB2 may affect CRPC development, we stably transfected LNCaP cells with shRNAs to mimic low and high expression of ADRB2. Two UDP-glucuronosyltransferases, UGT2B15 and UGT2B17, involved in phase II metabolism of androgens, were strongly downregulated in two LNCaP shADRB2 cell lines. The low-ADRB2 LNCaP cell lines displayed lowered glucuronidation activities towards androgens than high-ADRB2 cells. Furthermore, increased levels of testosterone and enhanced androgen responsiveness were observed in LNCaP cells expressing low level of ADRB2. Interestingly, these cells grew faster than high-ADRB2 LNCaP cells, and sustained their low glucuronidation activity in castrated NOD/SCID mice. ADRB2 immunohistochemical staining intensity correlated with UGT2B15 staining intensity in independent TMA studies and with UGT2B17 in one TMA study. Similar to ADRB2, we show that low levels of UGT2B15 are associated with a more rapid CRPC progression. We propose a novel mechanism by which ADRB2 may affect the development of CRPC through downregulation of UGT2B15 and UGT2B17.
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| 2. |
- Johansson, Henrik J., et al.
(författare)
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Breast cancer quantitative proteome and proteogenomic landscape
- 2019
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
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| 3. |
- Paus, Elisabeth, et al.
(författare)
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TD-11 workshop report : characterization of monoclonal antibodies to S100 proteins
- 2011
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Ingår i: Tumor Biology. - : Springer Science and Business Media LLC. - 1010-4283 .- 1423-0380. ; 32:1, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- Fourteen monoclonal antibodies with specificity against native or recombinant antigens within the S100 family were investigated with regard to immunoreactivity. The specificities of the antibodies were studied using ELISA tests, Western blotting epitope mapping using competitive assays, and QCM technology. The mimotopes of antibodies against S100A4 were determined by random peptide phage display libraries. Antibody specificity was also tested by IHC and pair combinations evaluated for construction of immunoradiometric assays for S100B. Out of the 14 antibodies included in this report eight demonstrated specificity to S100B, namely MAbs 4E3, 4D2, S23, S53, 6G1, S21, S36, and 8B10. This reactivity could be classified into four different epitope groups using competing studies. Several of these MAbs did display minor reactivity to other S100 proteins when they were presented in denatured form. Only one of the antibodies, MAb 3B10, displayed preferential reactivity to S100A1; however, it also showed partial cross-reactivity with S100A10 and S100A13. Three antibodies, MAbs 20.1, 22.3, and S195, were specific for recombinant S100A4 in solution. Western blot revealed that MAb 20.1 and 22.3 recognized linear epitopes of S100A4, while MAb S195 reacted with a conformational dependent epitope. Surprisingly, MAb 14B3 did not demonstrate any reactivity to the panel of antigens used in this study.
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| 4. |
- Tekpli, Xavier, et al.
(författare)
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An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture.
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