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Changli Wang
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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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P59.05 - Multi-Omic Analysis Between Tumor Tissues from Early and Late Stage Non-Small Cell Lung Cancer Patients (ID 1482)
00:00 - 00:00 | Author(s): Changli Wang
- Abstract
Introduction
Patients with early or late stage non-small cell lung cancer (NSCLC) have significantly different prognosis. The epigenetic differences and gene expression profiles of different stages of NSCLC have not been fully explored. Multi-omic analysis between early and late stage NSCLC will greatly contribute to the understanding of progression mechanism and biomarker discovery.
Methods
We used ATAC-seq and RNA-seq to investigate the epigenetics and gene expression differences of 17 fresh frozen tissue samples, which were collected from 7 early (IA) and 10 late stage (IIIA, 3; IIIB, 2; IV, 5) NSCLC patients.
Results
Hierarchical clustering analysis indicated that the ATAC-seq data generally correlated between the samples within each group of early or late stage NSCLC patients. We then examined the genomic distribution of ATAC-seq open chromatin peaks. While there was 0.81% ATAC-peaks located at the 5’-UTR, promoter-TSS (transcription start site) region for the early stage NSCLC patient samples, samples from the late stage patients had 2.3% ATAC-peaks at the same region, nearly 3-fold increase. These results implicated that the late stage NSCLCs were more active in transcription. KEGG analysis on the distinct ATAC-peaks indicated that the late stage samples had enrichment in pathways including RAS signaling and cell cycle, whereas early stage NSCLCs had more enrichment in RAP1 or phosphatidylinositol signal pathways. The STRING network analysis of pathways enriched in the late stage NSCLCs identified genes playing important roles in the cancer development (including PARP1, IL-6, and MAP2K2) had more direct interaction partners. Furthermore, we found that the ATAC-peaks had distinguished motifs enriched in early and late stage NSCLCs, exemplified by MYB and CDX2 in the early and late stage cancers, respectively. Finally, we performed the Venn diagram analysis of ATAC-seq and RNA-seq data and identified 61 overlapping genes, some involved in ligand-receptor binding or signaling pathways.
Conclusion
This study investigated the epigenetic and expression differences in NSCLC using ATAC-seq and RNA-seq, and identified distinguished patterns between early and late stage NSCLC in open-chromosome status and RNA expression. The study provides potential target information for the diagnosis and clinical intervention for NSCLCs.
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P60 - Tumor Biology and Systems Biology - Basic and Translational Science - Immune Bio (ID 198)
- 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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P60.06 - Single Cell Sequencing Analysis Revealed Altered Lung Cancer Microenvironment by Neoadjuvant Immunotherapy (ID 2105)
00:00 - 00:00 | Presenting Author(s): Changli Wang
- Abstract
Introduction
Single-cell RNA sequencing (scRNA-seq) is a powerful tool to study tumor microenvironment. However, there is limited study utilizing scRNA-seq technology to investigate patient response to immunotherapy. In this study, we use scRNA-seq approach to study tumor microenvironment in lung cancer patients receiving neoadjuvant immunotherapy.
Methods
Lung cancer tissues before and after therapy, paracancerous tissues and distant normal tissues after therapy were harvested from two non-small cell lung cancer patients, one with neoadjuvant platinum chemotherapy, the other with immunotherapy plus platinum chemotherapy. Single cells were isolated followed by scRNA-seq library preparation using Chromium Single Cell 5' Library Construction Kit (10x Genomics) and sequencing using an Illumina HiSeq platform. CellRanger was used to generate expression matrices, and Seurat used to identify cell subpopulations.
Results
After the neoadjuvant therapy, major pathological response (MPR) was achieved in the patient with immunotherapy plus chemotherapy but not in the patient with chemotherapy alone, which demonstrated the effectiveness of neoadjuvant immunotherapy. scRNA-seq revealed clusters of different cell types in the tumor microenvironment, which included epithelial cells, endothelial cells, fibroblasts, T cells, B cells, NK cells, and myeloid cells. We observed that tumor tissue of the patient receiving nivolumab and chemotherapy had increased T cell population after the treatment, whereas the T-cell content in tumor tissue of the patient with chemotherapy alone decreased after the treatment. Interestingly, we observed that the percentage of Treg cells remained stable in the patient treated with nivolumab and chemotherapy, whereas the proportion of Treg cells had two-fold decrease in the chemotherapy alone patient after the treatment. Furthermore, we identified a unique cell subgroup that was mainly derived from tumor tissue of the patient treated with nivolumab and chemotherapy. Cells in this subgroup showed enhanced expression of EPCAM, implicating the epithelial origin. GO analysis showed that the subgroup had elevated expression of genes enriched in functional groups including oxidative phosphorylation, ATP metabolic process, and cellular respiration. These observations support the application of scRNA-seq in monitoring response to immunotherapy.
Conclusion
Single cell sequencing technology can detect the alteration of cell components in tumor microenvironment, provide new tool to evaluate the response to neoadjuvant immunotherapy, and has the potential to reveal novel mechanism of treatment effect.
