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Xiaoshun Shi



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    P54 - Tumor Biology and Systems Biology - Basic and Translational Science - Carcinogenesis (ID 191)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Tumor Biology and Systems Biology - Basic and Translational Science
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P54.01 - Development and Validation of a Novel Nomogram Integrated with Lung Cancer Susceptibility Genes for Squamous Cell Lung Cancer (ID 1099)

      00:00 - 00:00  |  Presenting Author(s): Xiaoshun Shi

      • Abstract
      • Slides

      Introduction

      Squamous cell lung cancer (LUSC) is a subtype of lung cancer, accounting for approximately 40% of lung cancer. However, how to incorporate lung cancer susceptibility genes with clinical parameters remain less studied.

      Methods

      The clincal and RNA sequencing data of LUSC in the Cancer Genome Atlas (TCGA) were retrieved. We identified genes with differential expression, LUSC survival association, and incorporated the independent prognostic factors to build a nomogram. The predictive accuracy and discriminative ability of the nomogram were also evaluated.

      Results

      A total of 19 out of 196 (9.7%) genes in the LUSC-TCGA cohort were found to be associated with LUSC prognosis. A seven-gene (HYKK, FOXE1, DCBLD1, DAB2IP, ACE, SLC17A8, and HNF1B) signature was identified as an independent prognostic factor (Figure 1A). The AUC value of the risk score was 0.592, 0.633, and 0.662 in predicting 1-, 3-, and 5-year prognosis, respectively (Figure 2A). We successfully incorporated the risk score, age, gender, TNM stage, T stage, N stage, and metastasis status for nomogram development (Figure 2B).

      Figure 1

      lusc figure 1.png

      Figure 2

      figure 1 lusc lcsg.png

      Conclusion

      In this study, we established a novel nomogram for the prediction of OS for the patients with LUSC. This model could provide an example for a novel translational application of lung cancer susceptibility genes for squamous cell lung cancer.

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    P58 - Tumor Biology and Systems Biology - Basic and Translational Science - Epigenomics (ID 196)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Tumor Biology and Systems Biology - Basic and Translational Science
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P58.01 - Systematic Identification of Methylation Sites Associated with Lung Adenocarcinoma Prognosis (ID 1100)

      00:00 - 00:00  |  Presenting Author(s): Xiaoshun Shi

      • Abstract
      • Slides

      Introduction

      Aberrant DNA methylation is found in the processes of carcinogenesis, disease development and recurrence of lung adenocarcinoma, but a systematic analysis of DNA methylation on lung adenocarcinoma prognosis has not been reported.

      Methods

      We accessed clinical and RNA sequencing data from The Cancer Genome Atlas dataset and methylation data from the Infinium HumanMethylation450 dataset at the UCSC Cancer Browser. The univariate Cox regression analysis and the multivariate Cox regression model were used to filtering significant methylation sites for prognostic modeling. The Euclidean distance was used to measure the similarity distance between samples, and K-means was used for clustering. Survival analysis estimated by the Kaplan-Meier method of each cluster was performed.

      Results

      A total of 7336 methylation sites were associated with LUAD survival. Detail composition of each cluster in the T stage, N stage, M stage, and TNM stage were shown in Figure 1. We identified seven methylation subgroups independently affect lung adenocarcinoma survival (Figure 2A). These subtypes have prognostic differences, of which cluster 1 has the best prognosis, and cluster 4 and cluster 5 had the worst prognosis (Figure 2B).

      Figure 1

      figure 2.png

      Figure 2

      figure 1 methylation.png

      Conclusion

      We systematically revealed that methylation sites were associated with LUAD survival and categorized seven methylation subtypes independently affect lung adenocarcinoma survival. The methyl-typing system could provide a new clinical tool for lung adenocarcinoma recurrence assessment.

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    P59 - Tumor Biology and Systems Biology - Basic and Translational Science - Genomics (ID 197)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Tumor Biology and Systems Biology - Basic and Translational Science
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P59.02 - The Impact of CFTR on Lung Adenocarcinoma Prognosis: an in Silica Analysis (ID 1098)

      00:00 - 00:00  |  Presenting Author(s): Xiaoshun Shi

      • Abstract
      • Slides

      Introduction

      Cystic fibrosis transmembrane conductance regulator (CFTR) is an ion channel regulating chloride transduction. Although recent studies have reported that abnormal expression, mutations, and polymorphisms of CFTR are involved in cancer development, progression, and prognosis, a large scale in silica analysis of these aspects on lung cancer is not yet published.

      Methods

      We systematically retrieved pan-cancer data from the Cancer Genome Atlas (TCGA) adenocarcinoma data on the association of CFTR expression and clinical characteristics. Coexpression analysis was used to identify potential CFTR-interacted genes, followed by the Gene Set Enrichment Analysis for revealing potential biological function. Kaplan-Meier curved was applied to visualize the impact of CFTR expression of lung adenocarcinoma survival.

      Results

      In the TCGA lung adenocarcinoma dataset, we found differential CFTR expression between control tissues and LUAD tissues (Figure 1A), even in gender(Figure 1B), age(Figure 1C), smoking history(Figure 1D), TNM stage(Figure 1E), and lymph node metastasis(Figure 1F) subgroup analysis. For Kaplan-Meier analysis, lower expression of CFTR defined by the median is associated with poor prognosis, which supports by two external databases, the Oncolnc(Figure 1G) and the Gepia (Figure 1H) respectively.

      cftr figure 1 abstract.png

      Conclusion

      Our findings suggest that abnormal ion transporters, such as CFTR, could participate in the carcinogenesis and development of lung adenocarcinoma with a time-serial impact, eventually affect prognosis.

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    P66 - Tumor Biology and Systems Biology - Basic and Translational Science - Outcomes (ID 205)

    • Event: WCLC 2020
    • Type: Posters
    • Track: Tumor Biology and Systems Biology - Basic and Translational Science
    • Presentations: 1
    • Moderators:
    • Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
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      P66.02 - A Novel Risk Model of Lung Adenocarcinoma Based on Lung Cancer Susceptibility Genes (ID 1206)

      00:00 - 00:00  |  Presenting Author(s): Xiaoshun Shi

      • Abstract
      • Slides

      Introduction

      Lung cancer susceptibility genes increase the risks of lung cancer. However, how systematically abnormal expression of these genes confer lung adenocarcinoma prognosis is not well studied.

      Methods

      To collect lung adenocarcinoma susceptibility genes, we used three representative resources: lung cancer predisposing SNPs identified by genome-wide association studies and exon sequencing studies, and literature review. Differential expression analysis, univariate Cox regression, multivariate Cox regression, and LASSO regression were used to identified prognostic signatures.

      Results

      In the Cancer Genome Atlas lung adenocarcinoma RNA-seq and clinical information dataset, 31 out of 195 (15.9%) lung adenocarcinoma susceptibility genes were associated with LUAD prognosis. We next developed a 10-gene risk score (HLA.DOB, PRDM2, ABCA1, EPHX1, ABHD16A, VEGFC, DNAJB4, EXO1, KRT8, and REXO4) for TCGA-LUAD cohort (univariate: hazard ratio (HR)=1.076, 95% confidence interval (CI)=1.049−1.103, P<0.001; multivariate: HR=1.066, 95% CI=1.037−1.095, P<0.001). Patients with low-risk scores survived significantly longer than those with high-risk scores (Figure 1A). The ROC curves showed that the risk score was effective in predicting 1-, 3-, and 5-year prognosis for lung adenocarcinoma patients (Figure 1B).

      figure 1 luad lscg.png

      Conclusion

      Our findings suggest that a set of lung adenocarcinoma susceptibility genes can be used as an independent predictor of prognosis, which could potentially expand clinical use of target sequencing kits for a genetic consult.

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