Clin Med Insights Oncol. 2025 Oct 21;19:11795549251384582. doi: 10.1177/11795549251384582. eCollection 2025.

ABSTRACT

Recent advancements in cancer multi-omics have transformed our understanding of cancer biology by integrating genomics, transcriptomics, proteomics, and metabolomics. These integrative approaches have led to the identification of novel biomarkers and therapeutic targets, offering deeper insights into the molecular intricacies of various cancers, including breast, lung, gastric, pancreatic, and glioblastoma. Despite these advances, challenges remain, such as the integration of disparate data types and the interpretation of complex biological interactions. However, developments in proteogenomics and mass spectrometry have enhanced the correlation between molecular profiles and clinical features, refining the prediction of therapeutic responses. Future research in cancer drug discovery is poised to benefit from multi-omics approaches, improving the precision and efficacy of personalized therapies. By developing integrative network-based models, researchers aim to address challenges related to heterogeneity, reproducibility, and data interpretation. A standardized framework for multi-omics data integration could revolutionize cancer research, optimizing the identification of novel drug targets and enhancing our understanding of cancer biology. This complete approach holds the promise of advancing personalized therapies by fully characterizing the molecular landscape of cancer, ultimately improving patient outcomes through more effective and targeted treatment strategies. This narrative review underscores the potential of multi-omics approaches to transform cancer research and improve patient outcomes through more precise and effective treatments.

PMID:41147019 | PMC:PMC12553891 | DOI:10.1177/11795549251384582

Clin Med Insights Oncol. 2025 Oct 21;19:11795549251384582. doi: 10.1177/11795549251384582. eCollection 2025.

ABSTRACT

Recent advancements in cancer multi-omics have transformed our understanding of cancer biology by integrating genomics, transcriptomics, proteomics, and metabolomics. These integrative approaches have led to the identification of novel biomarkers and therapeutic targets, offering deeper insights into the molecular intricacies of various cancers, including breast, lung, gastric, pancreatic, and glioblastoma. Despite these advances, challenges remain, such as the integration of disparate data types and the interpretation of complex biological interactions. However, developments in proteogenomics and mass spectrometry have enhanced the correlation between molecular profiles and clinical features, refining the prediction of therapeutic responses. Future research in cancer drug discovery is poised to benefit from multi-omics approaches, improving the precision and efficacy of personalized therapies. By developing integrative network-based models, researchers aim to address challenges related to heterogeneity, reproducibility, and data interpretation. A standardized framework for multi-omics data integration could revolutionize cancer research, optimizing the identification of novel drug targets and enhancing our understanding of cancer biology. This complete approach holds the promise of advancing personalized therapies by fully characterizing the molecular landscape of cancer, ultimately improving patient outcomes through more effective and targeted treatment strategies. This narrative review underscores the potential of multi-omics approaches to transform cancer research and improve patient outcomes through more precise and effective treatments.

PMID:41147019 | PMC:PMC12553891 | DOI:10.1177/11795549251384582

Clin Med Insights Oncol. 2025 Oct 21;19:11795549251384582. doi: 10.1177/11795549251384582. eCollection 2025.

ABSTRACT

Recent advancements in cancer multi-omics have transformed our understanding of cancer biology by integrating genomics, transcriptomics, proteomics, and metabolomics. These integrative approaches have led to the identification of novel biomarkers and therapeutic targets, offering deeper insights into the molecular intricacies of various cancers, including breast, lung, gastric, pancreatic, and glioblastoma. Despite these advances, challenges remain, such as the integration of disparate data types and the interpretation of complex biological interactions. However, developments in proteogenomics and mass spectrometry have enhanced the correlation between molecular profiles and clinical features, refining the prediction of therapeutic responses. Future research in cancer drug discovery is poised to benefit from multi-omics approaches, improving the precision and efficacy of personalized therapies. By developing integrative network-based models, researchers aim to address challenges related to heterogeneity, reproducibility, and data interpretation. A standardized framework for multi-omics data integration could revolutionize cancer research, optimizing the identification of novel drug targets and enhancing our understanding of cancer biology. This complete approach holds the promise of advancing personalized therapies by fully characterizing the molecular landscape of cancer, ultimately improving patient outcomes through more effective and targeted treatment strategies. This narrative review underscores the potential of multi-omics approaches to transform cancer research and improve patient outcomes through more precise and effective treatments.

PMID:41147019 | PMC:PMC12553891 | DOI:10.1177/11795549251384582

Br J Cancer. 2025 Aug 23. doi: 10.1038/s41416-025-03139-6. Online ahead of print.

ABSTRACT

Non-small cell lung cancer (NSCLC) represents a heterogeneous group of malignancies characterised by diverse histological and molecular features. Some NSCLCs, particularly adenocarcinomas, harbour genomic alterations in receptor tyrosine kinases or downstream RAS/RAF signalling pathways, which are targets of effective therapies. NSCLCs lacking actionable genomic alterations often benefit from immune checkpoint inhibitors, though only a minority of patients achieve long-term survival. These tumours often carry alterations in tumour suppressor genes like TP53, KEAP1, STK11, or NF1, for which pharmacological strategies are still under investigation. This review explores emerging therapeutic opportunities unveiled by multi-omics studies in NSCLCs without actionable genomic alterations. Proteogenomic approaches-integrating genomic, transcriptomic and proteomic data-enable a comprehensive understanding of NSCLC molecular landscapes and signalling network dysregulation, helping to identify distinct tumour subtypes and potential therapeutic targets. These tumours exhibit alterations in cell cycle regulation, DNA repair, immune signalling, epigenetic modulation and metabolic and redox pathways. Although therapies targeting tumour suppressor genes like p53 remain highly anticipated, extending our understanding of the broader molecular landscape in these tumours may reveal novel vulnerabilities and inform the development of novel drugs or combination strategies. This could further advance precision oncology for NSCLC.

PMID:40849356 | DOI:10.1038/s41416-025-03139-6