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Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.

Qing Ye1, Jiajia Wang1, Barbara Ducatman2

  • 1West Virginia University Cancer Institute/Mary Babb Randolph Cancer Center, West Virginia University, Morgantown, WV 26506, USA.

International Journal of Molecular Sciences
|July 14, 2023
PubMed
Summary

A new 26-gene expression signature can identify early breast cancer and predict future invasive carcinoma development from premalignant lesions. This discovery aids in selecting high-risk patients and offers potential new therapeutic targets.

Keywords:
CRISPR-Cas9/RNAiatypical ductal hyperplasia (ADH)atypical ductal hyperplasia with cancer (ADHC)diagnosisimmunohistochemistrytriple-negative breast cancer (TNBC)

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Area of Science:

  • Oncology
  • Molecular Biology
  • Genomics

Background:

  • Current methods lack the ability to predict invasive breast cancer development from premalignant lesions.
  • Accurate prediction is crucial for early intervention and improved patient outcomes.

Purpose of the Study:

  • To identify novel gene expression biomarkers for predicting invasive breast cancer development.
  • To develop a gene signature for classifying invasive ductal carcinomas and identifying high-risk premalignant lesions.
  • To explore the therapeutic potential of identified biomarkers and gene signatures.

Main Methods:

  • Utilized a 26-gene mRNA expression profile to distinguish invasive ductal carcinomas from normal and benign breast tissues.
  • Developed a model to identify atypical ductal hyperplasia (ADH) with a high potential for cancer development (ADHC).
  • Validated mRNA expression via RT-PCR in independent tissue and blood samples; assessed protein expression (PBX2, RAD52) using immunohistochemistry.

Main Results:

  • The gene signature accurately classified invasive ductal carcinomas (94.05% accuracy, AUC=0.96) and predicted cancer development in ADH tissues (100% accuracy).
  • Validated mRNA expression in independent samples and confirmed prognostic significance of PBX2 and RAD52 protein expression for breast cancer survival.
  • The signature stratified The Cancer Genome Atlas (TCGA) breast cancer patients, revealed associations with immune infiltration, and predicted drug sensitivity/resistance.

Conclusions:

  • A 26-gene mRNA expression signature effectively identifies invasive breast cancer and predicts future development from premalignant lesions.
  • The identified biomarkers (PBX2, RAD52) have prognostic value for breast cancer survival.
  • The gene signature offers potential for personalized treatment strategies and identified a novel therapeutic target (VEGFR inhibitor ZM-306416).