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Johanna Sofia Margareta Mattsson



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    MA 05 - Immuno-Oncology: Novel Biomarker Candidates (ID 658)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Immunology and Immunotherapy
    • Presentations: 1
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      MA 05.13 - Scavenger Receptor MARCO Defines a Targetable Tumor-Associated Macrophage Subset in Lung Cancer (ID 8641)

      15:45 - 17:30  |  Author(s): Johanna Sofia Margareta Mattsson

      • Abstract
      • Presentation
      • Slides

      Background:
      Tumor-associated macrophages (TAMs) with immunosuppressive and tumor promoting features are attractive targets for immunotherapy. MARCO is a scavenger receptor expressed on a subpopulation of macrophages in secondary lymphoid organs. A recent study performed in animal models concluded that treatment with an anti-MARCO antibody results in reprogramming of the TAMs and inhibition of tumor growth and metastatic spread. The expression and function of MARCO in lung cancer TAMs is not known.

      Method:
      The infiltration of TAMs expressing MARCO, CD68, CD163 and MSR1, in the tumor and stromal compartments, was analyzed by immunohistochemistry in a non-small cell lung cancer (NSCLC) cohort (n=352). In addition, PD-L1 expression was assessed on tumor cells. Immunofluorescence was performed on selected cases to evaluate marker co-expression. Associations to immune cells and regulatory inflammatory pathways were studied in a subset of cases (n=174) with available RNA-seq data.

      Result:
      A large variance in TAM density could be observed between cases as well as a strong correlation between CD68 and CD163, indicating a pro-tumor phenotype of infiltrating macrophages. Correlation to clinical data showed a trend towards worse survival for patients with high macrophage infiltration. TAM expression of MARCO was seen on a subpopulation of pro-tumor macrophages. The majority of MARCO expressing TAMs were found to be located within tumor cell nests. Interestingly, stromal macrophages expressing MARCO tended to aggregate in close proximity to the tumor nests. On the transcriptomic level, increased MARCO gene expression correlated to genes linked to immunosuppressive TAMs, T-cell infiltration and immune checkpoint molecules like PD-L1 and CTLA-4. The association between macrophage infiltration and tumor cell PD-L1 expression was confirmed by immunohistochemistry. Also, co-expression of PD-L1 and MARCO could be detected on certain macrophages within the tumor cell nests.

      Conclusion:
      MARCO expression characterizes a specific subpopulation of pro-tumor macrophages that are enriched in PD-L1 positive NSCLC cases. Patients with significant infiltration of MARCO positive TAMs could benefit from treatment with anti-MARCO antibodies, possibly in combination with available immune checkpoint inhibitors.

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    MA 06 - Lung Cancer Biology I (ID 660)

    • Event: WCLC 2017
    • Type: Mini Oral
    • Track: Biology/Pathology
    • Presentations: 1
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      MA 06.01 - Cancer Testis Antigens and Mutational Load in Relation to the Immune Landscape of Non-Small Cell Lung Cancer (ID 9369)

      15:45 - 17:30  |  Author(s): Johanna Sofia Margareta Mattsson

      • Abstract
      • Presentation
      • Slides

      Background:
      The avoidance of immune surveillance by tumor cells is an accepted hallmark of cancer. The aim of this study was to describe the natural immune landscape of NSCLC tissue, to identify important regulatory associations and potential targets of immune response. This includes mutational load and cancer testis antigen (CTA) expression, and the comprehensive analysis of tumor infiltrating immune cells in connection with immune signaling and clinical information.

      Method:
      Tissue microarrays including duplicate cancer samples of 357 NSCLC patients were stained with antibodies against CD3, CD4, CD8, CD45RO, FoxP3, CD20, CD138, and CD44 to analyze the protein expression in the stroma and tumor compartment. For 197 of these cases, corresponding RNA-seq data were available. The immunological data were correlated to the transcriptomic data and to patients’ clinical outcome. The mutation status and the mutational load was based on a targeted next-generation sequencing panel of 82 genes (HaloPlex).

      Result:
      The immune cell infiltration was predominantly in the stroma, although CD8 and FoxP3 cells also showed relevant infiltration of the tumor cell compartment. The amount of T-cells of different subsets and CD20-positive B-cells correlated positively to each other. A higher mutational load was associated with higher CD8 T-cell infiltrates, CD45RO cells, FoxP3 regulatory cells as well as CD20-positive B-cells in the tumor compartment. In contrast, the number of expressed CTAs were associated with an abundance of CD45RO-positive cells in the stromal compartment. Only CD44-positivity (HR = 0.61, p< 0.01) as well as high CD20 positive B-cells (HR = 0.34, p< 0.01) and plasma cell (CD138, HR = 0.71, p< 0.05) counts in the tumor, and for plasma cells also the stromal (HR = 0.61, p< 0.01), compartment were associated with longer overall survival.

      Conclusion:
      Here we describe natural immune profiles in a large clinical NSCLC patient cohort. Interestingly both mutational load and CTA expression is associated with the abundance of distinct immune cell infiltrates. We could not confirm the impact of tumor infiltrating T-cells on survival. However, the consistent prognostic impact of both B-cell markers indicates a major role of the humoral immune response in lung cancer.

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    P2.02 - Biology/Pathology (ID 616)

    • Event: WCLC 2017
    • Type: Poster Session with Presenters Present
    • Track: Biology/Pathology
    • Presentations: 3
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      P2.02-015 - Mutation Patterns in a Swedish Non-Small Cell Lung Cancer Cohort (ID 10048)

      09:30 - 16:00  |  Author(s): Johanna Sofia Margareta Mattsson

      • Abstract
      • Slides

      Background:
      Non-small cell lung cancer (NSCLC) is a heterogeneous disease with unique combinations of somatic molecular alterations in individual patients, as well as significant differences in populations across the world with regard to mutation spectra and mutation frequencies. Here we describe the mutational pattern and linked clinical parameters in a population-based Swedish NSCLC cohort.

      Method:
      The cohort consists of 354 patients treated surgically at the University Hospital in Uppsala between 2006 to 2010. DNA was extracted from either fresh frozen (n=200) or formalin fixed paraffin embedded (FFPE; n=154) tissues prior to library preparation with Haloplex capture probes and Illumina Hiseq sequencing. The gene panel covers all exons of 82 genes, that have been shown to harbor mutations relevant for NSCLC development, and utilizes a reduced target fragment length and two strand capture compatible with degraded FFPE samples.

      Result:
      In order to avoid a systematic technical bias between FFPE and fresh-frozen samples, we adapted the sequencing depth and the bioinformatic pipeline for variant calling to obtain uniform sequence coverage and mutational load across the two sample types. TP53 was the most frequently mutated gene in both adenocarcinoma (AdC; 47%) and squamous cell carcinoma (SqC; 85%). KEAP1 or NFE2L2 was mutated in 19% of AdC and 23% of SqC in a mutually exclusive fashion. In AdC, hotspot alterations in driver genes could be seen in KRAS (43%), EGFR (13%), ERBB2 (3%, exon 20 insertions), BRAF (2%) and MET (1%, exon 14 skipping). Mutations in STK11 were observed in 21% of AdC cases. In SqC, frequently mutated genes were MLL2 (26%), PIK3CA (20%), CDKN2A (15%) and DDR2 (4%). Survival analysis revealed a worse overall survival for AdC patients with a mutation in either TP53, STK11 or SMARCA4. In the KRAS-mutated group poor survival appeared to be linked to concomitant TP53 or STK11 mutations, and not to KRAS mutation as a single aberration. In SqC a worse overall survival could be observed for patients with MLL2 mutations. SqC patients with mutations in CSMD3 had trend for a better prognosis.

      Conclusion:
      Here we have evaluated the mutational status of a Swedish NSCLC cohort. Technical adaption allowed analysis across both FFPE and fresh-frozen samples. Overall, the high frequency of TP53 and KRAS mutations might be related to the large fraction of smokers. Poor prognosis was linked to mutations in TP53, STK11 or SMARCA4 in AdC and MLL2 mutations in SqC.

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      P2.02-023 - Targeted Gene Expression Profiling to Evaluate Minimal Diagnostic FFPE-Biopsies from NSCLC-Patients (ID 9786)

      09:30 - 16:00  |  Presenting Author(s): Johanna Sofia Margareta Mattsson

      • Abstract
      • Slides

      Background:
      The molecular analysis of non-small cell lung cancer (NSCLC) is limited by the availability of only small biopsies or cytological specimens that are procured for diagnostic purpose. The nuclease protection method provides the possibility to analyze minimal amount of formalin fixed paraffin embedded (FFPE) tissue without previous extraction steps. We tested this technique and compared it to the traditional methods RNA sequencing (RNAseq) and immunohistochemistry (IHC).

      Method:
      The nuclease protection method (HTGmolecular) in combination with next-generation sequencing was used to measure gene expression of 549 immune-oncology genes in FFPE samples from NSCLC-patients. Standardized minimal tissue amounts were used for 12 samples (4 tissue circles, 4µm thick, 1 mm in diameter, from a tissue microarray). Of these tissue sections also two corresponding original tumor biopsy were analyzed. RNA sequencing data was available from a corresponding fresh frozen tissue as well as IHC annotation of the immune markers FOXP3, CDH1, CD20, CD44, CD3, CD4, CD8 and PD-L1 on the analyzed tissue cores.

      Result:
      Of the 12 core preparations, 9 samples were successfully analyzed and fulfilled the quality criteria in the first run, the three others in a second re-analysis. The mRNA expression profiles of 12 samples measured with HTG on minute FFPE samples and RNAseq from fresh frozen tissue showed most often good correlations (r=0.41-0.87). HTG based mRNA data correlated with IHC expression for 5 of 8 genes (PD-L1 r=0.76, CD44 r=0.75, CDH1 r=0.61, CD8 r=0.60, CD4 r=0.54). RNAseq data showed good correlations with IHC for only 3 of 8 genes (CD44 r=0.91, PD-L1 r=0.86, CD8 r=0.67). Also, the HTG data of the two biopsies demonstrated very good correlations to the corresponding tissue cores and the RNAseq data (r>0.91). Finally, technical replicates of 10 of the minimal tissue core samples measured in different laboratories revealed relatively good concordance (r=0.71-0.94).

      Conclusion:
      The applied nuclease protection technique opens the possibility to multiplex and analyze the immune profile of 549 genes in minimal diagnostic biopsies with a high success rate. This is of great value for clinical use or in NSCLC clinical studies where the amount of tissue often is a limiting factor in companion diagnostics.

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      P2.02-066 - Identification of Crucial Gene Targets in the in Situ Environment of Cancer by Google Network Ranking (ID 10151)

      09:30 - 16:00  |  Author(s): Johanna Sofia Margareta Mattsson

      • Abstract
      • Slides

      Background:
      The vast majority of cancer driver genes in non-small cell lung cancer (NSCLC) are characterized by activating mutations or high gene copy number amplifications. To identify tumorigenic genes without any genomic aberrations remains difficult. Network analysis of gene expression provides the possibility to describe the relations of genes to each other and by that to estimate their importance.

      Method:
      To analyze gene networks of NSCLC we applied the PageRank algorithm that was established by Google primarily to order the importance of websites. Data from NSCLC cancer tissue (n=1002) and normal lung (n=110) were retrieved from the cancer genome atlas (TCGA) and the highest expressed genes (n=16000) were ranked according to their importance in normal lung tissue as well as in NSCLC tissue. Subsequently, the difference in rank between normal and cancer was analyzed. Four comparative categories were defined and were analyzed with respect to their cellular function (GO annotation) and survival. Additionally, organ specific (n=163), housekeeping (n=68) and lung cancer related genes (n=62) were compared in the networks.

      Result:
      Genes with the highest importance (top 100) in normal lung tissue were connected with cellular metabolic processes or membrane transport. In cancer, most genes (top 100) were related to cell cycle and mitosis, chromosomal localization and DNA processing. There was no overlap between the two lists. Organ specific genes increased in average in their rank (p<0.001) while housekeeping genes decreased (p<0.001). Notably, cancer related genes did not significantly change their relevance in the network. Among the genes (top 100) that increased rank from normal to cancer, many were related to antigen processing and presentation.

      Conclusion:
      The PageRank algorithm provides the possibility to unbiasedly evaluate the importance of genes in the gene expression network of cancer. Surprisingly, not traditional cancer related genes but several hitherto not recognized genes were identified to be of regulatory importance and may be target for therapy. Once again, our results indicate the significance of the immune response in changes related to cancer.

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