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- 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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| 2. |
- 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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| 3. |
- Mezheyeuski, Artur, et al.
(författare)
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The ratio of CD8+ lymphocytes to CD68+CD163+ macrophages is prognostic in immunogenic tumors and predicts immunotherapy response
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Immune cells in the microenvironment shape tumor development and progression. Through in situ analyses we assessed 15 immune cell classes in 352 colorectal cancers and identified a simpleprognostic signature based on the ratio of anti-tumoral CD8+ lymphocytes to tumor-supportiveCD68+CD163+ macrophages in the tumor microenvironment. The prognostic ability of this signature was superior to the state-of-art immune score and was also demonstrated in four other tumor types. Single-cell analyses identified these CD68+CD163+ macrophages as the source of complement C1q, and the ratio of CD8A to C1QA gene expression levels in bulk RNA predicted survival in five tumor types. In single cell analyses, RNA-based versions of the signature also predicted response to checkpoint inhibitor therapy. This supports broad clinical applicability of immune scores considering CD68+CD163+ macrophages as prognostic and predictive biomarkers in common cancers.
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- Agnarsdóttir, Margrét, 1970-, et al.
(författare)
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Protein Biomarkers in Malignant Melanoma: An Image Analysis-Based Study on Melanoma Markers of Potential Clinical Relevance
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The thickness of a primary malignant melanoma tumor is the most important prognostic indicator for a patient with primary cutaneous malignant melanoma. To optimize the management and treatment of melanoma patients there is an unmet need to identify characteristics that can further stratify melanoma patients into high or low risk for progressive disease. Despite numerous studies no single marker has yet been shown to add significant prognostic information. An algorithmic approach, combining data from several markers provides an attractive model to identify patients of increased risk of dying from malignant melanoma. The primary aim of the present study was to analyze the correlation between clinical outcome and protein expression patterns of multiple proteins in malignant melanoma tumors using immunohistochemistry and tissue microarrays. Candidate proteins were identified based on a selective and differential expression pattern in melanoma tumors and tested in a cohort of 143 melanoma patients. Protein expression was analyzed using both manual scoring and automated image analysis-based algorithms. We found no single marker of prognosis that was independent of tumor thickness. When combining potential prognostic markers we could define a prognostic index, based on RBM3, MITF, SOX10 and Ki-67, that was independent of tumor thickness in multivariate analysis. Our findings suggest that a good prognosis signature can be identified in melanoma patients with tumors showing a low fraction of Ki-67 positive tumor cells and a high fraction of RBM3 positive tumor cells combined with low intensity levels of SOX10 and MITF.
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