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Erin A Marshall



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    MA04 - Models and Biomarkers (ID 122)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Biology
    • Presentations: 1
    • Now Available
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      MA04.11 - Biological and Prognostic Implications of the Long Non-Coding Transcriptome in Tumour-Infiltrating Immune Cells (Now Available) (ID 2838)

      13:30 - 15:00  |  Author(s): Erin A Marshall

      • Abstract
      • Presentation
      • Slides

      Background

      The lung tumour microenvironment is defined by complex infiltration patterns of immune cells which can contribute to both tumour progression and rejection. The advent of targeted immunotherapies has transformed cancer therapy, leading to durable regression even in late-stage lung tumours. Single-cell RNA sequencing and deconvolution of bulk tumour samples have provided insight into the transcriptomes of tumour-infiltrating immune populations and the regulatory networks that promote cytotoxicity and exhaustion transcriptional programs. Long non-coding RNAs (lncRNAs) have emerged as master regulators of gene expression in tumour cells, but their role in immune cells remains undercharacterized. We sought to delineate lncRNA expression profiles in healthy and lung tumour-infiltrating immune cells in order to better understand transcriptional reprogramming in tumour-infiltrating immune cells and to explore their potential as biomarkers of patient outcome and response to immunotherapy.

      Method

      RNAseq profiles of flow-purified adaptive and innate immune subsets were analysed for lncRNA expression, yielding 4919 expressed lncRNAs. Immune lncRNAs were then mapped to tumour and paired non-malignant lung adenocarcinoma samples (TCGA n=108, BCCA n=72) and associated with infiltrating immune populations by deconvolution and methylation-based purity scores. Associations with tumour immunogenicity were assessed by somatic mutational load and expression of tumour-associated antigens. Immune-specific expression of lncRNAs was confirmed in an external single cell RNAseq dataset of lung adenocarcinomas (n=5).

      Result

      We found that lncRNA expression patterns display markedly greater cell-type specificity than protein-coding genes in healthy samples, supporting their role in cell-intrinsic transcriptional regulation. 323 immune lncRNAs were differentially expressed in lung tumours compared to matched non-malignant tissue, with enriched expression of immune lncRNAs in tumours with high antigenic load. Many of these genes were positively correlated with CD45 expression and negatively correlated with tumour purity, suggestive of immune cell-restricted expression patterns. Furthermore, a substantial proportion of these genes showed decreased expression in microdissected tumour samples, suggesting that immune-derived lncRNAs may account for gene expression patterns observed in bulk tumour data. We validated these findings in a scRNAseq dataset and analysed co-expression patterns of immune lncRNAs with immune cell markers in order to identify specific immune cell phenotypes and assess the interaction of immune lncRNAs with cytotoxicity and exhaustion transcriptional networks. We identify immune lncRNAs which may regulate expression of important immune genes related to NK and CD8+ T cell cytotoxicity, as well as immune lncRNAs which predict patient outcome and response.

      Conclusion

      We present an atlas of lncRNAs expressed in innate and adaptive immune cells, emphasizing the multifaceted roles of lncRNAs in homeostasis and anti-tumour immunity. We highlight the potential of immune infiltrate to confound differential expression analysis of bulk tumour RNAseq data, with consideration needed for tumour purity and immune infiltration levels. Our data provide a resource that will facilitate further identification of functionally and clinically useful lncRNAs.

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    MA15 - Usage of Computer and Molecular Analysis in Treatment Selection and Disease Prognostication (ID 141)

    • Event: WCLC 2019
    • Type: Mini Oral Session
    • Track: Pathology
    • Presentations: 1
    • Now Available
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      MA15.11 - Establishing a Cell Sociology Platform for the Assessment of Targetable Interactions to Predict Lung Cancer Outcome (Now Available) (ID 2652)

      15:45 - 17:15  |  Presenting Author(s): Erin A Marshall

      • Abstract
      • Presentation
      • Slides

      Background

      The tumor microenvironment (TME) is a complex mixture of tumor epithelium, stroma and immune cells. The immune component of the TME is highly prognostic for tumor progression and patient outcome. Immune functionality, however, is often dictated by direct cell-to-cell contacts and cannot be resolved by simple metrics of cell density (for example, number of cells per mm2 or flow cytometry). For example, direct contact between CD8+ T cells and target cells is necessary for CD8+ T cell activity, and direct contact between PD1+ and PD-L1+ cells is necessary for the efficacy of immune checkpoint inhibitors. Current immunohistochemistry (IHC) techniques identify immune cell numbers and densities, but lack assessment of spatial relationships (or “cell sociology”). Here, we develop a platform to examine these direct interactions within the TME, and assess their relationship with patient outcome in two independent non-small cell lung cancer (NSCLC) cohorts.

      Method

      Tissue sections of primary tumors from lung adenocarcinoma (LUAD) patients with known clinical outcome were stained using 2 multiplex IHC panels: CD3/CD8/CD79a (Panel 1) and PD1/PDL1/CD8 (Panel 2). Hyperspectral image analysis determined the phenotype of all cells. Using the same IHC panels, these observations were assessed in a secondary NSCLC dataset (n=674). Deconvolution of these images was used to identify cell types, and cellular ‘neighborhoods’ were assessed using a Voronoi approach. This cohort was also profiled by for gene expression to validate immune subset fractions. We further identified other tumor features, including the presence of tertiary lymphoid organs (TLOs; transient immune structures necessary for antibody production from B cells).

      Result

      High density of intra-tumoral CD8+ T cells was associated with non-recurrence of tumors. However, we find that a non-random cell sociology pattern of CD8+ T cells directly surrounded by tumor cells was more significantly associated with non-recurrence compared to density alone. Monte Carlo re‐sampling analysis determined that these cell sociology patterns were non-random.

      Conclusion

      Hyperspectral cell sociology expands our understanding of the complex interplay between tumor cells and immune infiltrate. This technology improves our understanding of the tumour microenvironment and allows us to directly quantify interactions that dictate immune responses to cancers. Consequently, the implementation of this platform could improve predictions of responses to immunotherapy and lead to a deeper understanding of anti-tumor immunity.

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    P1.03 - Biology (ID 161)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Moderators:
    • Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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      P1.03-29 - Cellular Biology Determines Ability of XIST to Act as a miRNA Sponge in Non-Small Cell Lung Cancer (ID 2631)

      09:45 - 18:00  |  Author(s): Erin A Marshall

      • Abstract
      • Slides

      Background

      XIST, the female-specific lncRNA canonically involved in silencing the X chromosome, has been suggested by many studies to function as a miRNA sponge. This sponge mechanism has been suggested to affect many cancer types, including lung adenocarcinoma (LUAD). However, determination of miRNA:lncRNA interaction is largely based on sequence homology, impeding the identification of functional gene pairs. The sex-specificity of XIST provides the opportunity to study the biological relevance of these interactions. Here we take a comprehensive approach by considering factors that affect preferential regulation through XIST-miRNA sponging in LUAD.

      Method

      Sequencing data from 568 LUAD and non-malignant samples (304 female and 264 male) were downloaded from CancerBrowser and processed to provide gene expression for mRNAs, miRNAs, and XIST. 3’UTR sequences of all candidate genes were run through the miRanda binding prediction algorithm. Spearman’s tests were performed to identify positively correlated candidate sponged genes.

      Result

      To identify the best sponge-regulated candidates, we considered genes that (1) were positively correlated with XIST expression and (2) are targeted by shared miRNA with XIST, and (3) expressed in lung adenocarcinoma. This revealed a robust set 128 of genes potentially positively regulated by XIST through the sequestration of 804 shared miRNAs. As XIST is sex-specific, we compared the changes in miRNA-target gene relationships in XIST-high and XIST-low systems to identify a high-confidence set of 13 miRNA-gene pairs. In order to interact with the exclusively nuclear expressed XIST,miRNAs must also be expressed in the nucleus. We validate the nuclear presence of several of these high confidence miRNAs using RT-qPCR, confirming the co-localization required for XIST to interact with these species.

      Conclusion

      We use a biology-driven approach to identify genes defended from miRNA-based inhibition by the lncRNA XIST in LUAD. Importantly, we identify that the miRNAs that mediate the XIST-target gene axis are enriched in the nucleus, co-localizing with XIST in lung cancer cell models. Our results reinforce the necessary consideration of biological features in future studies of lncRNA:miRNA interactions.

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    P2.03 - Biology (ID 162)

    • Event: WCLC 2019
    • Type: Poster Viewing in the Exhibit Hall
    • Track: Biology
    • Presentations: 1
    • Now Available
    • Moderators:
    • Coordinates: 9/09/2019, 10:15 - 18:15, Exhibit Hall
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      P2.03-24 - Concurrent Aberrations in G2/M-Phase Transcriptional Programs and Genomic Gatekeepers Highlight Lung Cancer Predisposition in COPD Patients (Now Available) (ID 2665)

      10:15 - 18:15  |  Presenting Author(s): Erin A Marshall

      • Abstract
      • Slides

      Background

      Chronic obstructive pulmonary disease (COPD) is associated with a 7-fold increased risk of lung cancer occurrence. COPD is defined by clinical symptoms and lung function measurement. It is characterized by chronic inflammation, small airway remodelling and loss as well as destruction of alveoli (emphysema). While an important lung cancer risk factor, the molecular overlap between COPD and lung cancer tumorigenesis is relatively understudied.

      Method

      In order to examine the commonalities between these two diseases, we first analyzed small airway epithelial gene expression profiles from 127 COPD and 140 non-COPD ever-smoker patients obtained by bronchial brushing. We performed weighted gene correlation network analysis (WGCNA) on these gene expression profiles to discover deregulated gene modules (‘metagenes’) associated with reduced lung function (Forced Expiratory Volume at 1 second, FEV1)—a clinical measure of COPD severity most robustly negatively correlated with lung cancer risk. We then assessed the preservation of these modules in two non-small cell lung cancer (NSCLC) tumour/normal data sets (lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), n= 887 tumors total). Airway and tumor patient cohorts were matched for age, gender, tumour stage, and smoking status.

      Result

      We discovered 10 distinct small airway expression modules, two of which were significantly negatively correlated (p < 0.05) with patient FEV1. One of these FEV1 modules was the top overall module preserved in both NSCLC subtypes. This lung cancer-FEV1 module contained 31 genes solely enriched for two related mitotic functions— G2/M phase transition (BH-p = 0.02) and mitotic roles of polo-like kinase (BH-p = 0.001, n=31). Of these, 28 genes were significantly overexpressed in both LUAD and LUSC, and mapped to a highly-clustered sub-network of 23 proteins with 465 known and in silico predicted protein-protein interactions. When tumours enriched for this lung-cancer-FEV1 gene signature were further examined, we observed a significant co-occurrence of DNA-level alterations in DNA damage associated checkpoints, specifically mutated TP53.

      Conclusion

      Coordinated gene expression changes associated with COPD severity measures in small airways and preserved in NSCLC tumors are enriched for G2/M phase transition genes. These genes are further disrupted in tumors, where co-occurring mutations to gate-keeper genes occur. Progression of mitosis during abnormal aneuploidy in lung tissues of COPD patients may confer increased risk of oncogenic transformation in this population, and may underlie the molecular link between COPD and lung cancer.

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