Sputum Biomarkers to Improve CT Screening for the Early Detection of Lung Cancer in Veterans

Abstract

We propose to develop a model for identifying lung cancer in indeterminate pulmonary nodules (PNs). Specific aims: (1) identify new sputum small noncoding RNA (ncRNA) biomarkers for lung cancer, (2) validate the previously and newly identified biomarkers and develop a prediction model, and (3) blindly validate the prediction model for distinguishing benign from malignant growths in a different cohort. Until 08/2020, we produced 13 peer-reviewed research articles published. We have the important findings as shown below: Demonstrating that aberrant ncRNAs detected in the bronchial epitheliums of sputum could reflects those in malignant PNs (lung tumors). Developing and validating panels of sputum miRNA, snoRNA, and lncRNA biomarkers for lung cancer. Defining a landscape of various types of ncRNAs of bronchial epitheliums of lung cancer patients. Combined analysis of ncRNAs and DNA methylation has a synergistic effect for lung cancer diagnosis. We have developed a prediction model that has more than 90% sensitivity and 95% specificity for lung cancer detection. The diagnostic value of the prediction model is validated in a different cohort.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2020
Accession Number
AD1116903

Entities

People

  • Feng Jiang

Organizations

  • University of Maryland, Baltimore

Tags

DTIC Thesaurus Topics

  • Cell Physiological Processes
  • Cells
  • Chemistry
  • Computational Science
  • Data Mining
  • Health Services
  • Information Processing
  • Information Science
  • Lung Diseases
  • Medical Personnel
  • Neural Networks
  • X-Ray Computed Tomography

Fields of Study

  • Biology

Readers

  • Medical Imaging.
  • Molecular and genetic basis of cancer.
  • Oncology