Scholarlink

<p>Cancer remains a major global health challenge, with substantial morbidity and mortality worldwide. Advances in genomic and proteomic biomarker discovery have transformed cancer diagnosis, prognosis, and treatment selection. The evolution from early serological markers such as carcinoembryonic antigen (CEA) and prostate-specific antigen (PSA) to modern multi-omics approaches enabled by next-generation sequencing (NGS), mass spectrometry (MS), and advanced bioinformatics has revolutionized personalized medicine and targeted therapy, leading to improved outcomes. This review highlights the historical evolution of cancer biomarkers and the current landscape of genomic, proteomic, and proteogenomic biomarkers. We emphasize the role of liquid biopsies, artificial intelligence (AI), and integrative multi-omics analytics in accelerating biomarker identification and validation. We also discuss the differential pace of clinical adoption in high-income versus low- and middle-income countries (LMICs), and outline ongoing challenges including tumor heterogeneity, standardization, cost, and regulatory barriers. Despite these limitations, recent innovations in multi-omics technologies and AI-driven analysis promise to further advance precision oncology and enable more equitable, personalized cancer care worldwide.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

New genomic and proteomic biomarker discovery in cancer: revolutionizing diagnosis and prognostication

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月27日

查看全文
  • Monika Rajput,
  • Manoj Pandey,
  • Ruhi Dixit

摘要

Cancer remains a major global health challenge, with substantial morbidity and mortality worldwide. Advances in genomic and proteomic biomarker discovery have transformed cancer diagnosis, prognosis, and treatment selection. The evolution from early serological markers such as carcinoembryonic antigen (CEA) and prostate-specific antigen (PSA) to modern multi-omics approaches enabled by next-generation sequencing (NGS), mass spectrometry (MS), and advanced bioinformatics has revolutionized personalized medicine and targeted therapy, leading to improved outcomes. This review highlights the historical evolution of cancer biomarkers and the current landscape of genomic, proteomic, and proteogenomic biomarkers. We emphasize the role of liquid biopsies, artificial intelligence (AI), and integrative multi-omics analytics in accelerating biomarker identification and validation. We also discuss the differential pace of clinical adoption in high-income versus low- and middle-income countries (LMICs), and outline ongoing challenges including tumor heterogeneity, standardization, cost, and regulatory barriers. Despite these limitations, recent innovations in multi-omics technologies and AI-driven analysis promise to further advance precision oncology and enable more equitable, personalized cancer care worldwide.