Genomic Diversity and the Microenvironment as Drivers of Progression in DCIS

Abstract

Ductal carcinoma in situ (DCIS) of the breast is an increasingly common diagnosis that is related to aggressive screening patterns (mammography). This pre-invasive lesion may progress to invasive cancer, but does so at a relatively low frequency. Nonetheless, it is commonly treated with extensive surgery, radiation, and hormonal therapy even though most of these lesions would never progress to invasive cancer. Thus, there is a pressing clinical need to stratify the risk of DCIS tumors into those in need of intervention and those that can be safely monitored without intervention. Our project is designed to address this need by characterizing the evolvability of DCIS, detecting those that have a high likelihood of evolving to malignancy versus those that are likely to remain indolent.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2020
Accession Number
AD1190606

Entities

People

  • Carlo Maley

Organizations

  • Arizona State University

Tags

DTIC Thesaurus Topics

  • Breast Cancer
  • Carcinoma
  • Cells
  • Computational Biology
  • Computational Science
  • Computer Vision
  • Convolutional Neural Networks
  • Data Analysis
  • Deep Learning
  • Detection
  • Genetic Variation
  • Genetics
  • Histology
  • Identification
  • Information Science
  • Lymphocytes
  • Machine Learning
  • Medical Personnel
  • Neoplasms
  • Neural Networks

Readers

  • Economics
  • Oncology and Biomarker-Based Cancer Detection.