Single-Cell RNA Sequencing of the Bronchial Epithelium in Smokers with Lung Cancer

Abstract

Cigarette smoking, the major cause of lung cancer, creates a field of injury throughout the respiratory tract. We have previously shown that gene expression from bronchial epithelial cells reflects the physiologic response to cigarette smoke exposure and can serve as a diagnostic biomarker for lung cancer. The purpose of this Idea Development Award is to conduct single cell RNA sequencing on airway epithelial cells obtained from smokers with and without lung cancer to identify cell-type dependent gene expression alterations in the lung cancer field of injury. Cells are being collected by brushing the right mainstem bronchus of smokers undergoing bronchoscopy for the suspicion of lung cancer. We have developed and optimized protocols to isolate single cells from these bronchial brushings using fluorescence-activated cell sorting (FACS) and to prepare libraries using an adapted version of the CEL-Seq RNA library preparation protocol that includes plate-, well-, and transcript-specific barcodes allowing hundreds of cells to be pooled together and sequenced. Additionally, we have developed computational pipelines to process the sequencing data into gene level counts for each cell as well as a new algorithm, Celda, to define and characterize transcriptionally distinct cell populations. We have successfully sequenced 3,456 cells collected by brushing the bronchial epithelium healthy never and current smokers and from high-risk current and former smokers with and without cancer. The data reveals the known and novel types of epithelial and immune cells. The results increase our understanding of our previously published gene expression changes associated with smoking, smoking cessation, and the presence of lung cancer in the bronchial airway epithelium. Over the next year, we plan to sequence between 100 and 200 cells per donor from 6 healthy former smokers and 24 current and former smokers undergoing bronchoscopy for the suspicion of lung cancer.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2017
Accession Number
AD1042891

Entities

People

  • Jennifer Beane-ebel

Organizations

  • Boston University School of Medicine

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Biological Markers
  • Blood
  • Blood Cells
  • Bronchoscopy
  • Cancer
  • Cells
  • Data Analysis
  • Dimensionality Reduction
  • Diseases And Disorders
  • Epithelial Cells
  • Gene Expression
  • Health Services
  • Leukocytes
  • Medical Personnel
  • Neoplasms
  • Rna Sequence Analysis

Fields of Study

  • Biology

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