| 1. |
- Grinberg, Marianna, et al.
(author)
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Reaching the limits of prognostication in non-small cell lung cancer : an optimized biomarker panel fails to outperform clinical parameters.
- 2017
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In: Modern Pathology. - : Elsevier BV. - 0893-3952 .- 1530-0285. ; 30:7, s. 964-977
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Journal article (peer-reviewed)abstract
- Numerous protein biomarkers have been analyzed to improve prognostication in non-small cell lung cancer, but have not yet demonstrated sufficient value to be introduced into clinical practice. Here, we aimed to develop and validate a prognostic model for surgically resected non-small cell lung cancer. A biomarker panel was selected based on (1) prognostic association in published literature, (2) prognostic association in gene expression data sets, (3) availability of reliable antibodies, and (4) representation of diverse biological processes. The five selected proteins (MKI67, EZH2, SLC2A1, CADM1, and NKX2-1 alias TTF1) were analyzed by immunohistochemistry on tissue microarrays including tissue from 326 non-small cell lung cancer patients. One score was obtained for each tumor and each protein. The scores were combined, with or without the inclusion of clinical parameters, and the best prognostic model was defined according to the corresponding concordance index (C-index). The best-performing model was subsequently validated in an independent cohort consisting of tissue from 345 non-small cell lung cancer patients. The model based only on protein expression did not perform better compared to clinicopathological parameters, whereas combining protein expression with clinicopathological data resulted in a slightly better prognostic performance (C-index: all non-small cell lung cancer 0.63 vs 0.64; adenocarcinoma: 0.66 vs 0.70, squamous cell carcinoma: 0.57 vs 0.56). However, this modest effect did not translate into a significantly improved accuracy of survival prediction. The combination of a prognostic biomarker panel with clinicopathological parameters did not improve survival prediction in non-small cell lung cancer, questioning the potential of immunohistochemistry-based assessment of protein biomarkers for prognostication in clinical practice.Modern Pathology advance online publication, 10 March 2017; doi:10.1038/modpathol.2017.14.
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| 2. |
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| 3. |
- Andersen, Toril, et al.
(author)
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Chitosan-Based Nanomedicine to Fight Genital Candida Infections : Chitosomes
- 2017
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In: Marine Drugs. - : MDPI. - 1660-3397. ; 15:3
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Journal article (peer-reviewed)abstract
- Vaginal infections are associated with high recurrence, which is often due to a lack of efficient treatment of complex vaginal infections comprised of several types of pathogens, especially fungi and bacteria. Chitosan, a mucoadhesive polymer with known antifungal effect, could offer a great improvement in vaginal therapy; the chitosan-based nanosystem could both provide antifungal effects and simultaneously deliver antibacterial drugs. We prepared chitosan-containing liposomes, chitosomes, where chitosan is both embedded in liposomes and surface-available as a coating layer. For antimicrobial activity, we entrapped metronidazole as a model drug. To prove that mucoadhesivness alone is not sufficient for successful delivery, we used Carbopol-containing liposomes as a control. All vesicles were characterized for their size, zeta potential, entrapment efficiency, and in vitro drug release. Chitosan-containing liposomes were able to assure the prolonged release of metronidazole. Their antifungal activity was evaluated in a C. albicans model; chitosan-containing liposomes exhibited a potent ability to inhibit the growth of C. albicans. The presence of chitosan was crucial for the system's antifungal activity. The antifungal efficacy of chitosomes combined with antibacterial potential of the entrapped metronidazole could offer improved efficacy in the treatment of mixed/complex vaginal infections.
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| 4. |
- Backman, Max, et al.
(author)
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Extending the immune phenotypes of lung cancer: Oasis in the desert
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Other publication (other academic/artistic)abstract
- Introduction: Tumor infiltrating immune cells are key elements of the tumor microenvironment and mediate the anti-tumor effects of immunotherapy. The aim of the study was to characterize patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to tumor mutations and clinicopathological parameters. Methods: Lymphocytes (CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+) and PD-L1+ were annotated on a tissue microarray including 357 operated NSCLC cases. Somatic mutations and tumor mutational burden were analyzed by targeted sequencing for 82 genes, and transcriptomic immune patterns were established in 197 patients based on RNAseq data. Results: We identified somatic mutations (TP53, NF1, KEAP1, CSMD3, LRP1B) that correlated with specific immune cell infiltrates. Hierarchical clustering revealed four immune classes: with (1) high immune cell infiltration (“inflamed”), (2) low immune cell infiltration (“desert”), (3) a mixed phenotype, and (4) a new phenotype with an overall muted inflammatory cell pattern but with an imprint of NK and plasma cells. This latter class exhibited low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, TGFB1), but was linked to better survival and therefore designated “oasis”. Otherwise, the four immune classes were not related to the presence of specific mutations (EGFR, KRAS, TP53) or histologic subtypes. Conclusion: We present a compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC and identified the novel immune class “oasis”. The immune classification helps to better define the immunogenic potency of NSCLC in the era of immunotherapy.
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| 5. |
- Backman, Max, et al.
(author)
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Infiltration of NK and plasma cells is associated with a distinct immune subset in non‐small cell lung cancer
- 2021
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In: Journal of Pathology. - : John Wiley & Sons. - 0022-3417 .- 1096-9896. ; 255:3, s. 243-256
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Journal article (peer-reviewed)abstract
- Immune cells of the tumor microenvironment are central but erratic targets for immunotherapy. The aim of this study was to characterize novel patterns of immune cell infiltration in non-small cell lung cancer (NSCLC) in relation to its molecular and clinicopathologic characteristics. Lymphocytes (CD3+, CD4+, CD8+, CD20+, FOXP3+, CD45RO+), macrophages (CD163+), plasma cells (CD138+), NK cells (NKp46+), PD1+, and PD-L1+ were annotated on a tissue microarray including 357 NSCLC cases. Somatic mutations were analyzed by targeted sequencing for 82 genes and a tumor mutational load score was estimated. Transcriptomic immune patterns were established in 197 patients based on RNA sequencing data. The immune cell infiltration was variable and showed only poor association with specific mutations. The previously defined immune phenotypic patterns, desert, inflamed, and immune excluded, comprised 30, 13, and 57% of cases, respectively. Notably, mRNA immune activation and high estimated tumor mutational load were unique only for the inflamed pattern. However, in the unsupervised cluster analysis, including all immune cell markers, these conceptual patterns were only weakly reproduced. Instead, four immune classes were identified: (1) high immune cell infiltration, (2) high immune cell infiltration with abundance of CD20+ B cells, (3) low immune cell infiltration, and (4) a phenotype with an imprint of plasma cells and NK cells. This latter class was linked to better survival despite exhibiting low expression of immune response-related genes (e.g. CXCL9, GZMB, INFG, CTLA4). This compartment-specific immune cell analysis in the context of the molecular and clinical background of NSCLC reveals two previously unrecognized immune classes. A refined immune classification, including traits of the humoral and innate immune response, is important to define the immunogenic potency of NSCLC in the era of immunotherapy. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.
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| 6. |
- Backman, Max, 1987-, et al.
(author)
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Spatial immunophenotyping of the tumor microenvironment in non-small cell lung cancer
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Other publication (other academic/artistic)abstract
- Introduction: Immune cells in the tumor microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterize the spatial immune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC).Methods: We established a multiplexed fluorescence multispectral imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4 Eff), CD4 regulatory cells (CD4 Treg), CD8 effector cells (CD8 Eff), CD8 regulatory cells (CD8 Treg), B-cells, NK-cells, NKT-cells, M1 macrophages (M1), CD163+ myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs), and plasmacytoid dendritic cells (pDCs). Results: CD4 Eff cells, CD8 Eff cells, and M1 macrophages were the most abundant immune cells invading the tumor cell compartment and indicated a patient group with a favorable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4 Eff, CD4 Treg, CD8 Treg, and B-cells), as well as pDCs, were independently associated with longer survival. However, when these immune cells were located close to CD8 Treg cells, the favorable impact was attenuated. In the multivariate Cox regression model including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8 Treg–B-cells, CD8 Eff–cancer cells, and B-cells–CD4 Treg) demonstrated positive prognostic impact, while short M2–M1 distances were prognostically unfavorable.Conclusion: We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is also crucial for diagnostic use.
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| 7. |
- Backman, Max, 1987-, et al.
(author)
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Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer
- 2023
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In: European Journal of Cancer. - : Elsevier. - 0959-8049 .- 1879-0852. ; 185, s. 40-52
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Journal article (peer-reviewed)abstract
- Introduction: Immune cells in the tumour microenvironment are associated with prognosis and response to therapy. We aimed to comprehensively characterise the spatial im-mune phenotypes in the mutational and clinicopathological background of non-small cell lung cancer (NSCLC).Methods: We established a multiplexed fluorescence imaging pipeline to spatially quantify 13 immune cell subsets in 359 NSCLC cases: CD4 effector cells (CD4-Eff), CD4 regulatory cells (CD4-Treg), CD8 effector cells (CD8-Eff), CD8 regulatory cells (CD8-Treg), B-cells, natural killer cells, natural killer T-cells, M1 macrophages (M1), CD163 thorn myeloid cells (CD163), M2 macrophages (M2), immature dendritic cells (iDCs), mature dendritic cells (mDCs) and plasmacytoid dendritic cells (pDCs).Results: CD4-Eff cells, CD8-Eff cells and M1 macrophages were the most abundant immune cells invading the tumour cell compartment and indicated a patient group with a favourable prognosis in the cluster analysis. Likewise, single densities of lymphocytic subsets (CD4-Eff, CD4-Treg, CD8-Treg, B-cells and pDCs) were independently associated with longer survival. However, when these immune cells were located close to CD8-Treg cells, the favourable impact was attenuated. In the multivariable Cox regression model, including cell densities and distances, the densities of M1 and CD163 cells and distances between cells (CD8-Treg-B-cells, CD8-Eff-cancer cells and B-cells-CD4-Treg) demonstrated positive prognostic impact, whereas short M2-M1 distances were prognostically unfavourable.Conclusion: We present a unique spatial profile of the in situ immune cell landscape in NSCLC as a publicly available data set. Cell densities and cell distances contribute independently to prognostic information on clinical outcomes, suggesting that spatial information is crucial for diagnostic use.
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| 8. |
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| 9. |
- Bogatyrova, Olga, et al.
(author)
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FGFR1 overexpression in non-small cell lung cancer is mediated by genetic and epigenetic mechanisms and is a determinant of FGFR1 inhibitor response
- 2021
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In: European Journal of Cancer. - : Elsevier. - 0959-8049 .- 1879-0852. ; 151, s. 136-149
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Journal article (peer-reviewed)abstract
- Amplification of fibroblast growth factor receptor 1 (FGFR1) in non-small cell lung cancer (NSCLC) has been considered as an actionable drug target. However, pan-FGFR tyrosine kinase inhibitors did not demonstrate convincing clinical efficacy in FGFR1-amplified NSCLC patients. This study aimed to characterise the molecular context of FGFR1 expression and to define biomarkers predictive of FGFR1 inhibitor response.In this study, 635 NSCLC samples were characterised for FGFR1 protein expression by immunohistochemistry and copy number gain (CNG) by in situ hybridisation (n = 298) or DNA microarray (n = 189). FGFR1 gene expression (n = 369) and immune cell profiles (n = 309) were also examined. Furthermore, gene expression, methylation and microRNA data from The Cancer Genome Atlas (TCGA) were compared. A panel of FGFR1-amplified NSCLC patient-derived xenograft (PDX) models were tested for response to the selective FGFR1 antagonist M6123.A minority of patients demonstrated FGFR1 CNG (10.5%) or increased FGFR1 mRNA (8.7%) and protein expression (4.4%). FGFR1 CNG correlated weakly with FGFR1 gene and protein expression. Tumours overexpressing FGFR1 protein were typically devoid of driver alterations (e.g. EGFR, KRAS) and showed reduced infiltration of T-lymphocytes and lower PD-L1 expression. Promoter methylation and microRNA were identified as regulators of FGFR1 expression in NSCLC and other cancers. Finally, NSCLC PDX models demonstrating FGFR1 amplification and FGFR1 protein overexpression were sensitive to M6123.The unique molecular and immune features of tumours with high FGFR1 expression provide a rationale to stratify patients in future clinical trials of FGFR1 pathway-targeting agents.
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