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Sökning: WFRF:(Branden G)

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  • Aad, G., et al. (författare)
  • 2012
  • swepub:Mat__t (refereegranskat)
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  • Djureinovic, Dijana, et al. (författare)
  • Profiling cancer testis antigens in non-small-cell lung cancer
  • 2016
  • Ingår i: JCI INSIGHT. - : American Society for Clinical Investigation. - 2379-3708. ; 1:10
  • Tidskriftsartikel (refereegranskat)abstract
    • Cancer testis antigens (CTAs) are of clinical interest as biomarkers and present valuable targets for immunotherapy. To comprehensively characterize the CTA landscape of non-small-cell lung cancer (NSCLC), we compared RNAseq data from 199 NSCLC tissues to the normal transcriptome of 142 samples from 32 different normal organs. Of 232 CTAs currently annotated in the Caner Testis Database (CTdatabase), 96 were confirmed in NSCLC. To obtain an unbiased CTA profile of NSCLC, we applied stringent criteria on our RNAseq data set and defined 90 genes as CTAs, of which 55 genes were not annotated in the CTdatabase, thus representing potential new CTAs. Cluster analysis revealed that CTA expression is histology dependent and concurrent expression is common. IHC confirmed tissue-specific protein expression of selected new CTAs (TKTL1, TGIF2LX, VCX, and CXORF67). Furthermore, methylation was identified as a regulatory mechanism of CTA expression based on independent data from The Cancer Genome Atlas. The proposed prognostic impact of CTAs in lung cancer was not confirmed, neither in our RNAseq cohort nor in an independent meta-analysis of 1,117 NSCLC cases. In summary, we defined a set of 90 reliable CTAs, including information on protein expression, methylation, and survival association. The detailed RNAseq catalog can guide biomarker studies and efforts to identify targets for immunotherapeutic strategies.
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  • Edlund, Karolina, et al. (författare)
  • Prognostic Impact of Tumor Cell Programmed Death Ligand 1 Expression and Immune Cell Infiltration in NSCLC
  • 2019
  • Ingår i: Journal of Thoracic Oncology. - : Elsevier BV. - 1556-0864 .- 1556-1380. ; 14:4, s. 628-640
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: Infiltration of T and B/plasma cells has been linked to NSCLC prognosis, but this has not been thoroughly investigated in relation to the expression of programmed death ligand 1 (PD-L1). Here, we determine the association of lymphocytes and PD-L1 with overall survival (OS) in two retrospective cohorts of operated NSCLC patients who were not treated with checkpoint inhibitors targeting the programmed death 1/PD-L1 axis. Moreover, we evaluate how PD-L1 positivity and clinicopathologic factors affect the prognostic association of lymphocytes.Methods: Cluster of differentiation (CD) 3 (CD3)-, CD8-, CD4-, forkhead box P3 (FOXP3)-, CD20-, CD79A-, and immunoglobulin kappa constant (IGKC)-positive immune cells, and tumor PD-L1 positivity, were determined by immunohistochemistry on tissue microarrays (n = 705). Affymetrix data was analyzed for a patient subset, and supplemented with publicly available transcriptomics data (N = 1724). Associations with OS were assessed by Kaplan-Meier plots and uni- and multivariate Cox regression.Results: Higher levels of T and B plasma cells were associated with longer OS (p = 0.004 and p < 0.001, for CD8 and IGKC, respectively). Highly proliferative tumors with few lymphocytes had the worst outcome. No association of PD-L1 positivity with OS was observed in a nonstratified patient population; however, a significant association with shorter OS was observed in never-smokers (p = 0.009 and p = 0.002, 5% and 50% cutoff). Lymphocyte infiltration was not associated with OS in PD-L1–positive tumors (50% cutoff). The prognostic association of lymphocyte infiltration also depended on the patients’ smoking history and histologic subtype.Conclusions: Proliferation, PD-L1 status, smoking history, and histology should be considered if lymphocyte infiltration is to be used as a prognostic biomarker.
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  • Grinberg, Marianna, et al. (författare)
  • Reaching the limits of prognostication in non-small cell lung cancer : an optimized biomarker panel fails to outperform clinical parameters.
  • 2017
  • Ingår i: Modern Pathology. - : Elsevier BV. - 0893-3952 .- 1530-0285. ; 30:7, s. 964-977
  • 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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