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Sökning: WFRF:(Botling Johan)

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1.
  • La Fleur, Linnea, et al. (författare)
  • Expression of scavenger receptor MARCO defines a targetable tumor-associated macrophage subset in non-small cell lung cancer
  • 2018
  • Ingår i: International Journal of Cancer. - : WILEY. - 0020-7136 .- 1097-0215. ; 143:7, s. 1741-1752
  • Tidskriftsartikel (refereegranskat)abstract
    • Tumor-associated macrophages (TAMs) are attractive targets for immunotherapy. Recently, studies in animal models showed that treatment with an anti-TAM antibody directed against the scavenger receptor MARCO resulted in suppression of tumor growth and metastatic dissemination. Here we investigated the expression of MARCO in relation to other macrophage markers and immune pathways in a non-small cell lung cancer (NSCLC) cohort (n=352). MARCO, CD68, CD163, MSR1 and programmed death ligand-1 (PD-L1) were analyzed by immunohistochemistry and immunofluorescence, and associations to other immune cells and regulatory pathways were studied in a subset of cases (n=199) with available RNA-seq data. We observed a large variation in macrophage density between cases and a strong correlation between CD68 and CD163, suggesting that the majority of TAMs present in NSCLC exhibit a protumor phenotype. Correlation to clinical data only showed a weak trend toward worse survival for patients with high macrophage infiltration. Interestingly, MARCO was expressed on a distinct subpopulation of TAMs, which tended to aggregate in close proximity to tumor cell nests. On the transcriptomic level, we found a positive association between MARCO gene expression and general immune response pathways including strong links to immunosuppressive TAMs, T-cell infiltration and immune checkpoint molecules. Indeed, a higher macrophage infiltration was seen in tumors expressing PD-L1, and macrophages residing within tumor cell nests co-expressed MARCO and PD-L1. Thus, MARCO is a potential new immune target for anti-TAM treatment in a subset of NSCLC patients, possibly in combination with available immune checkpoint inhibitors.
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2.
  • Backman, Max, et al. (författare)
  • Extending the immune phenotypes of lung cancer: Oasis in the desert
  • 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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3.
  • Backman, Max, et al. (författare)
  • Infiltration of NK and plasma cells is associated with a distinct immune subset in non‐small cell lung cancer
  • 2021
  • Ingår i: Journal of Pathology. - : John Wiley & Sons. - 0022-3417 .- 1096-9896. ; 255:3, s. 243-256
  • 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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4.
  • Backman, Max, 1987-, et al. (författare)
  • Spatial immunophenotyping of the tumor microenvironment in non-small cell lung cancer
  • 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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5.
  • Backman, Max, 1987-, et al. (författare)
  • Spatial immunophenotyping of the tumour microenvironment in non-small cell lung cancer
  • 2023
  • Ingår i: European Journal of Cancer. - : Elsevier. - 0959-8049 .- 1879-0852. ; 185, s. 40-52
  • 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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6.
  • Casar Borota, Olivera, et al. (författare)
  • Serotonin, ATRX, and DAXX Expression in Pituitary Adenomas : Markers in the Differential Diagnosis of Neuroendocrine Tumors of the Sellar Region.
  • 2017
  • Ingår i: American Journal of Surgical Pathology. - 0147-5185 .- 1532-0979. ; 41:9, s. 1238-1246
  • Tidskriftsartikel (refereegranskat)abstract
    • Differential diagnosis based on morphology and immunohistochemistry between a clinically nonfunctioning pituitary neuroendocrine tumor (NET)/pituitary adenoma and a primary or secondary NET of nonpituitary origin in the sellar region may be difficult. Serotonin, a frequently expressed marker in the NETs, has not been systematically evaluated in pituitary NETs. Although mutations in ATRX or DAXX have been reported in a significant proportion of pancreatic NETs, the mutational status of ATRX and DAXX and their possible pathogenetic role in pituitary NETs are unknown. Facing a difficult diagnostic case of an invasive serotonin and adrenocorticotroph hormone immunoreactive NET in the sellar region, we explored the immunohistochemical expression of serotonin, ATRX, and DAXX in a large series of pituitary endocrine tumors of different types from 246 patients and in 2 corticotroph carcinomas. None of the pituitary tumors expressed serotonin, suggesting that serotonin immunoreactive sellar tumors represent primary or secondary NETs of nonpituitary origin. Normal expression of ATRX and DAXX in pituitary tumors suggests that ATRX and DAXX do not play a role in the pathogenesis of pituitary endocrine tumors that remain localized to the sellar and perisellar region. A lack of ATRX or DAXX in a sellar NET suggests a nonpituitary NET, probably of pancreatic origin. One of the 2 examined corticotroph carcinomas, however, demonstrated negative ATRX immunolabeling due to an ATRX gene mutation. Further studies on a larger cohort of pituitary carcinomas are needed to clarify whether ATRX mutations may contribute to the metastatic potential in a subset of pituitary NETs.
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7.
  • Eltahir, Mohamed, et al. (författare)
  • Plasma Proteomic Analysis in Non-Small Cell Lung Cancer Patients Treated with PD-1/PD-L1 Blockade
  • 2021
  • Ingår i: Cancers. - : MDPI. - 2072-6694. ; 13:13
  • Tidskriftsartikel (refereegranskat)abstract
    • Simple Summary Immunotherapy leads to highly variable responses in lung cancer patients. We assessed the value of a blood-based test to predict which patients would benefit from this new treatment modality. We determined that some patients have higher and lower levels of immune markers in their blood samples, and that this is related to better survival without tumor growth. The blood test has the potential to help select the optimal therapy for lung cancer patients. Checkpoint inhibitors have been approved for the treatment of non-small cell lung cancer (NSCLC). However, only a minority of patients demonstrate a durable clinical response. PD-L1 scoring is currently the only biomarker measure routinely used to select patients for immunotherapy, but its predictive accuracy is modest. The aim of our study was to evaluate a proteomic assay for the analysis of patient plasma in the context of immunotherapy. Pretreatment plasma samples from 43 NSCLC patients who received anti-PD-(L)1 therapy were analyzed using a proximity extension assay (PEA) to quantify 92 different immune oncology-related proteins. The plasma protein levels were associated with clinical and histopathological parameters, as well as therapy response and survival. Unsupervised hierarchical cluster analysis revealed two patient groups with distinct protein profiles associated with high and low immune protein levels, designated as "hot" and "cold". Further supervised cluster analysis based on T-cell activation markers showed that higher levels of T-cell activation markers were associated with longer progression-free survival (PFS) (p < 0.01). The analysis of single proteins revealed that high plasma levels of CXCL9 and CXCL10 and low ADA levels were associated with better response and prolonged PFS (p < 0.05). Moreover, in an explorative response prediction model, the combination of protein markers (CXCL9, CXCL10, IL-15, CASP8, and ADA) resulted in higher accuracy in predicting response than tumor PD-L1 expression or each protein assayed individually. Our findings demonstrate a proof of concept for the use of multiplex plasma protein levels as a tool for anti-PD-(L)1 response prediction in NSCLC. Additionally, we identified protein signatures that could predict the response to anti-PD-(L)1 therapy.
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8.
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9.
  • Göransson, Hanna, et al. (författare)
  • Quantification of normal cell fraction and copy number neutral LOH in clinical lung cancer samples using SNP array data
  • 2009
  • Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 4:6, s. e6057-
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Technologies based on DNA microarrays have the potential to provide detailed information on genomic aberrations in tumor cells. In practice a major obstacle for quantitative detection of aberrations is the heterogeneity of clinical tumor tissue. Since tumor tissue invariably contains genetically normal stromal cells, this may lead to a failure to detect aberrations in the tumor cells. PRINCIPAL FINDING: Using SNP array data from 44 non-small cell lung cancer samples we have developed a bioinformatic algorithm that accurately models the fractions of normal and tumor cells in clinical tumor samples. The proportion of normal cells in combination with SNP array data can be used to detect and quantify copy number neutral loss-of-heterozygosity (CNNLOH) in the tumor cells both in crude tumor tissue and in samples enriched for tumor cells by laser capture microdissection. CONCLUSION: Genome-wide quantitative analysis of CNNLOH using the CNNLOH Quantifier method can help to identify recurrent aberrations contributing to tumor development in clinical tumor samples. In addition, SNP-array based analysis of CNNLOH may become important for detection of aberrations that can be used for diagnostic and prognostic purposes.
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10.
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