Novel Systems Biology Approach to Decoding Actionable Targets to Overcome Resistance in GI Cancer Monotherapies

Abstract

Gastrointestinal (GI) cancer patient responses to treatment are extremely heterogeneous across patient populations, and resistance to current drug therapies often occurs after a short period. Thus, it is urgent to identify new drug combination targets for improving prognosis in a large number of GI cancer patients. GI cancer is more common in military members due to exposure to carcinogens in the field including certain chemicals and ionizing radiation. This type of exposure causes mutations in DNA which increases the rate of cancer development. We have previously shown that heterogeneous cancer mutations potentiate tumor-specific responses through distinct mechanisms and interactome network perturbations. While most of the current methodologies focus on predicting single targets to fight against tumors, few have therapeutic value in designing combination targets. During this reporting period, wehave developed a network-based approach integrating functional variomics and synthetic lethality, and identified novel candidate actionable drug combinations for GI cancer. We hypothesize that combination modulation of GI tumors co-treated with MEK and PARP inhibitors will promote reduction of GI tumors compared to single agents alone. The proposed combination therapy, then, islikely to be most effective in military members with GI cancers as their tumors are likely to carry drug-resistant mutations.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2021
Accession Number
AD1152643

Entities

People

  • Nidhi Sahni

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • Biomedical Research
  • Cancer
  • Cell Line
  • Cell Physiological Processes
  • Cells
  • Combination Therapy
  • Computational Biology
  • Computational Science
  • Data Analysis
  • Drug Combinations
  • Drug Resistance
  • Electronic Mail
  • Gene Expression
  • Inhibitors
  • Medical Personnel
  • Mutations
  • Neoplasms
  • Organoids
  • Programmed Cell Death
  • Side Effects
  • Students
  • Therapy

Fields of Study

  • Biology

Readers

  • Distributed Systems and Data Platform Development
  • Oncology
  • Wetland-Land-Environmental Management.