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<p>Triple-negative breast cancer (TNBC) has become one of the most challenging cancers to date due to its great variability in biological features, high growth rate, and rare options for treatment. This review examines several innovative strategies for tailored treatment of TNBC, focusing mainly on the most recent developments and potential directions. The molecular landscape of TNBC is covered in the first section, which keeps the focus on transcriptome and genomic profiling while highlighting key molecular targets like mutations in the <i>BRCA1</i>/2, <i>PIK3CA</i>, androgen receptors (AR), epidermal growth factor receptors (EGFR), and immunological checkpoint molecules. This review also covers novel therapies that aim to block well-defined pathways, including immune checkpoint inhibitors (ICI), EGFR inhibitors, drugs that target AR, poly ADP ribose polymerase (PARP) inhibitors, and drugs that disrupt the PI3K/AKT/mTOR pathway. Additionally, it covers novel strategies focusing on combination therapy, targeting the DNA damage response pathway, and epigenetic modulators. Conclusively, it emphasizes perspectives and directions on topics such as personalized medicine, artificial intelligence (AI), predictive biomarkers, and treatment planning with the inclusion of machine learning (ML).</p>

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Tailored therapies for triple-negative breast cancer: current landscape and future perceptions

  • 期刊论文

  • 发表日期：

    2025年3月3日

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  • Yumna Khan,
  • Sana Rizvi,
  • Ali Raza,
  • Amna Khan,
  • Sadique Hussain,
  • Najeeb Ullah Khan,
  • Saud O. Alshammari,
  • Qamar A. Alshammari,
  • Abdulkarim Alshammari,
  • Doha El-Sayed Ellakwa

摘要

Triple-negative breast cancer (TNBC) has become one of the most challenging cancers to date due to its great variability in biological features, high growth rate, and rare options for treatment. This review examines several innovative strategies for tailored treatment of TNBC, focusing mainly on the most recent developments and potential directions. The molecular landscape of TNBC is covered in the first section, which keeps the focus on transcriptome and genomic profiling while highlighting key molecular targets like mutations in the BRCA1/2, PIK3CA, androgen receptors (AR), epidermal growth factor receptors (EGFR), and immunological checkpoint molecules. This review also covers novel therapies that aim to block well-defined pathways, including immune checkpoint inhibitors (ICI), EGFR inhibitors, drugs that target AR, poly ADP ribose polymerase (PARP) inhibitors, and drugs that disrupt the PI3K/AKT/mTOR pathway. Additionally, it covers novel strategies focusing on combination therapy, targeting the DNA damage response pathway, and epigenetic modulators. Conclusively, it emphasizes perspectives and directions on topics such as personalized medicine, artificial intelligence (AI), predictive biomarkers, and treatment planning with the inclusion of machine learning (ML).