Multi-omics approaches integrate various high-dimensional datasets, including genomics, transcriptomics, proteomics, and metabolomics. Recently, these approaches have been increasingly used to unveil the complexity and diversity of cancer cells and their interactions with the tumor microenvironment. The collection covers the following topics: 

1. The concept and rationale of multi-omics approaches in cancer research, including the challenges and opportunities they offer to enhance the understanding, diagnosis, and treatment of cancers. 
2. The development and application of multi-omics algorithms and methods to integrate and analyze datasets from cancer patients, aiming to identify novel biomarkers and therapeutic targets. 
3. The latest findings and implications from large-scale multi-omics studies of various cancers, such as breast, colorectal, lung, and ovarian cancers, and their subtypes. It explores the potential of multi-omics data for precision oncology and drug development. 
4. Integration of multi-omics with other technologies, such as spatial omics and radio-omics (MRI, CT-scan, ECG, PET), for the development of novel anti-cancer therapies. 

The collection aims to provide a comprehensive and up-to-date overview of the state of the art of multi-omics research in cancer, inspiring new directions and collaborations in this emerging and promising field.