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<p>Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinicalheterogeneity. Traditional single-analyte biomarkers often lack the sensitivity and specificity required for early detectionand personalized therapy, highlighting the need for robust next-generation biomarkers (NGBs). This review provides a concise overview of NGBs in cancer and autoimmune diseases, emphasizing multi-omicsintegration and artificial intelligence (AI)-driven approaches shaping precision diagnostics and therapeutics. A literature search of PubMed, Scopus, and Web of Science over the last 15 years focused on genomics, transcriptomics,spatial transcriptomics, proteomics, metabolomics, and Microbiomics, particularly studies combining multi-omicsdatasets with AI/machine learning. Multi-omics and AI reveal dynamic molecular signatures—circulating tumor DNA, microRNAs, long non-codingRNAs, proteins, metabolites, and immune profiles. Single-cell and spatial analyses uncover cellular heterogeneity and tissuecontext, while proteomics, metabolomics, and microbiomics provide functional insights, enhancing disease detection,patient stratification, and therapy monitoring. Challenges include assay standardization, inter-patient variability, and regulatoryhurdles. Multi-omics and AI-powered NGBs promise to transform precision diagnostics and personalized therapy, requiringcontinued research, standardization, and global collaboration.</p> Graphical Abstract <p></p>

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Biological multi-omics approaches to next-generation biomarkers in immune-related disorders and malignancies: An overview

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • Pawan Kumar Goswami,
  • Sandip Chatterjee

摘要

Cancer and autoimmune diseases are major global health challenges characterized by molecular and clinicalheterogeneity. Traditional single-analyte biomarkers often lack the sensitivity and specificity required for early detectionand personalized therapy, highlighting the need for robust next-generation biomarkers (NGBs). This review provides a concise overview of NGBs in cancer and autoimmune diseases, emphasizing multi-omicsintegration and artificial intelligence (AI)-driven approaches shaping precision diagnostics and therapeutics. A literature search of PubMed, Scopus, and Web of Science over the last 15 years focused on genomics, transcriptomics,spatial transcriptomics, proteomics, metabolomics, and Microbiomics, particularly studies combining multi-omicsdatasets with AI/machine learning. Multi-omics and AI reveal dynamic molecular signatures—circulating tumor DNA, microRNAs, long non-codingRNAs, proteins, metabolites, and immune profiles. Single-cell and spatial analyses uncover cellular heterogeneity and tissuecontext, while proteomics, metabolomics, and microbiomics provide functional insights, enhancing disease detection,patient stratification, and therapy monitoring. Challenges include assay standardization, inter-patient variability, and regulatoryhurdles. Multi-omics and AI-powered NGBs promise to transform precision diagnostics and personalized therapy, requiringcontinued research, standardization, and global collaboration.

Graphical Abstract