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Updated: Jun 7, 2025

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

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Using bioinformatics and artificial intelligence to map the cyclin-dependent kinase 4/6 inhibitor biomarker landscape

Kim Wager1, Yao Wang2, Andrew Liew1

  • 1AI & Data Science, Oxford PharmaGenesis Ltd, Oxford, UK.

Future Oncology (London, England)
|November 12, 2024
PubMed

Insights

Identifying biomarkers for cyclin-dependent kinase 4/6 (CDK4/6) inhibitors is crucial for advanced breast cancer treatment. This study compiles key biomarkers to predict response and resistance, guiding future research.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors plus endocrine therapy are standard for hormone receptor-positive/human epidermal growth factor receptor 2-negative advanced breast cancer.
  • Treatment response is variable, and resistance frequently develops, necessitating predictive biomarkers.

Purpose of the Study:

  • To comprehensively identify and describe biomarkers associated with response or resistance to CDK4/6 inhibitors in breast cancer.
  • To guide future clinical research and therapeutic strategies.

Main Methods:

  • Combined bioinformatic-database analyses, artificial intelligence-assisted literature review, and manual literature review (Embase, OVID Medline; Jan 2012-Oct 2022).
  • Expert validation of identified biomarkers.

Main Results:

  • Identified 15 clinically important biomarkers related to CDK4/6 inhibitor efficacy.
  • Key biomarkers include AR, AURKA, ERBB2, ESR1, CCNE1, CDKN1A/B, CDK2, CDK6, CDK7, CDK9, FGFR1/2, MYC, PIK3CA/AKT, RB1, and STAT3.

Conclusions:

  • The identified biomarker landscape provides critical insights into CDK4/6 inhibitor response and resistance mechanisms.
  • These biomarkers can inform patient selection and guide the development of novel therapeutic approaches in breast cancer.
Keywords:
CDK4/6 inhibitorsHR+/HER2-artificial intelligencebioinformaticsbiomarkersbreast cancerdrug resistanceresponse

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