| 1. |
- Grinberg, Marianna, et al.
(författare)
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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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Ingår i: Modern Pathology. - : Elsevier BV. - 0893-3952 .- 1530-0285. ; 30:7, s. 964-977
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Tidskriftsartikel (refereegranskat)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. |
- Mattsson, Jonathan, et al.
(författare)
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Normalization of Wastewater Quality to Estimate Infiltration/Inflow and Mass Flows of Metals
- 2016
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Ingår i: Journal of environmental engineering. - 0733-9372 .- 1943-7870. ; 142:11
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Tidskriftsartikel (refereegranskat)abstract
- The quality of wastewater varies between catchments due to variation in urbanisation, sewer system properties, and pollution levels. This study was conducted to identify wastewater quality parameters that could be normalized to estimate levels of infiltration/inflow (I/I) in selected catchments and to investigate the geographic origins of metals entering sewer systems. Two sampling campaigns were conducted in the five catchments of the Gothenburg area focusing on 14 water quality parameters. Data from a reference study on domestic wastewater quality to normalize the mass flows associated with pure domestic wastewater was applied. The level of dilution due to I/I in wastewater entering Rya Wastewater Treatment Plant, estimated using Tot-N and Tot-P as indicators, provided the closest fit among the water quality parameters with results obtained by established methods for the two campaigns. The results from the study also indicated which catchments generated nondomestic wastewater with higher mass flows of specified metals.
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| 3. |
- Micke, Patrick, et al.
(författare)
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The prognostic impact of the tumour stroma fraction : A machine learning-based analysis in 16 human solid tumour types
- 2021
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 65
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Tidskriftsartikel (refereegranskat)abstract
- Background: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed.Methods: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns.Findings: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR (95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59 (1.49-8.62)) associations of the tumour stroma fraction with survival.Interpretation: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance.
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| 4. |
- Uhlén, Mathias, et al.
(författare)
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A pathology atlas of the human cancer transcriptome
- 2017
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 357:6352, s. 660-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is one of the leading causes of death, and there is great interest in understanding the underlying molecular mechanisms involved in the pathogenesis and progression of individual tumors. We used systems-level approaches to analyze the genome-wide transcriptome of the protein-coding genes of 17 major cancer types with respect to clinical outcome. A general pattern emerged: Shorter patient survival was associated with up-regulation of genes involved in cell growth and with down-regulation of genes involved in cellular differentiation. Using genome-scale metabolic models, we show that cancer patients have widespread metabolic heterogeneity, highlighting the need for precise and personalized medicine for cancer treatment. All data are presented in an interactive open-access database (www.proteinatlas.org/pathology) to allow genome-wide exploration of the impact of individual proteins on clinical outcomes.
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| 5. |
- Andersen, Christina, et al.
(författare)
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Emissions of soot, PAHs, ultrafine particles, NOx, and other health relevant compounds from stressed burning of candles in indoor air
- 2021
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Ingår i: Indoor Air. - : Hindawi Limited. - 0905-6947 .- 1600-0668. ; 31:6, s. 2033-2048
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Tidskriftsartikel (refereegranskat)abstract
- Burning candles release a variety of pollutants to indoor air, some of which are of concern for human health. We studied emissions of particles and gases from the stressed burning of five types of pillar candles with different wax and wick compositions. The stressed burning was introduced by controlled fluctuating air velocities in a 21.6 m3 laboratory chamber. The aerosol physicochemical properties were measured both in well-mixed chamber air and directly above the candle flame with online and offline techniques. All candles showed different emission profiles over time with high repeatability among replicates. The particle mass emissions from stressed burning for all candle types were dominated by soot (black carbon; BC). The wax and wick composition strongly influenced emissions of BC, PM2.5 , and particle-phase polycyclic aromatic hydrocarbons (PAHs), and to lower degree ultrafine particles, inorganic and organic carbon fraction of PM, but did not influence NOx , formaldehyde, and gas-phase PAHs. Measurements directly above the flame showed empirical evidence of short-lived strong emission peaks of soot particles. The results show the importance of including the entire burn time of candles in exposure assessments, as their emissions can vary strongly over time. Preventing stressed burning of candles can reduce exposure to pollutants in indoor air.
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| 6. |
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| 7. |
- Backman, Max, et al.
(författare)
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Extending the immune phenotypes of lung cancer: Oasis in the desert
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Annan publikation (övrigt vetenskapligt/konstnärligt)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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| 8. |
- Backman, Max, et al.
(författare)
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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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Ingår i: Journal of Pathology. - : John Wiley & Sons. - 0022-3417 .- 1096-9896. ; 255:3, s. 243-256
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Tidskriftsartikel (refereegranskat)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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| 9. |
- Backman, Max, 1987-, et al.
(författare)
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Spatial immunophenotyping of the tumor microenvironment in non-small cell lung cancer
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Annan publikation (övrigt vetenskapligt/konstnärligt)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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| 10. |
- Backman, Max, 1987-, et al.
(författare)
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Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer
- 2023
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Ingår i: European Journal of Cancer. - : Elsevier. - 0959-8049 .- 1879-0852. ; 185, s. 40-52
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Tidskriftsartikel (refereegranskat)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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