Collection

Integrative Analysis of Multiple-omics Data for Precision Cancer Diagnosis and Treatment

Cancer is a complex disease characterized by genetic and molecular heterogeneity. Traditional cancer research has focused on studying individual omics layers, such as genomics, transcriptomics, proteomics, and metabolomics. However, recent advancements in high-throughput technologies have enabled the generation of large-scale multi-omics datasets, providing a comprehensive view of the molecular landscape of cancer. Integrating and analyzing these multi-omics layers can offer valuable insights into the underlying mechanisms of cancer development, progression, and response to therapy. This research topic explores the potential of integrating multi-omics data, including genomics, transcriptomics, proteomics, and metabolomics, to improve cancer diagnosis and treatment strategies. By leveraging the complementary information provided by each omics layer, we aim to identify novel biomarkers, molecular subtypes, and therapeutic targets that can enhance precision medicine approaches in cancer. This special issue welcomes reviews, research articles, computational tools, and databases. Topics include but are not limited to:

1. Identification of novel biomarkers for early cancer detection and prognosis prediction.

2. Discovery of molecular subtypes that can guide personalized treatment strategies.

3. Uncovering potential therapeutic targets and pathways for drug development.

4. Development of computational tools and algorithms for multi-omics data integration and analysis.

Editors

Articles (3 in this collection)