Decoding Tumor Complexity: Broad Perspectives from Integrative Multi-Omics and Single-Cell Technologies in Cancer Genetics

Cancer is a multifaceted disease characterized by profound genetic, epigenetic, transcriptomic, and proteomic alterations. Traditional genomic approaches have shed light on key oncogenic mutations, but recent technological advances reveal that understanding cancer’s true complexity requires moving beyond the genome to integrate multiple layers of molecular information. Multi-omic analyses, spanning genomics, transcriptomics, epigenomics, proteomics, and metabolomics, are providing a more comprehensive molecular portrait of tumors, while single-cell and spatial technologies are exposing the diversity and dynamics of cancer and its microenvironment at an unprecedented resolution. These innovations are revolutionizing our understanding of tumor evolution, heterogeneity, resistance mechanisms, and the intricate cross-talk with stromal and immune cells, presenting exciting avenues for both discovery research and clinical translation.

Despite the promise of comprehensive multi-omic and single-cell approaches in revealing the complexity of cancer, many challenges remain before these insights can be fully translated to precision medicine. Critical questions persist regarding the integration and interpretation of diverse molecular datasets, the identification and clinical validation of actionable biomarkers, and the functional impact of noncoding, structural, and regulatory variation. Moreover, the development of AI-driven computational methods now enables the deciphering of high-dimensional datasets, unlocking hidden patterns relevant for patient stratification, therapy selection, and monitoring disease progression in real time. This Research Topic aims to bring together original and review articles that leverage integrative multi-omic, single-cell, and spatial approaches (with or without advanced analytics) to address pressing questions in cancer genetics and oncogenomics. We particularly seek contributions that provide new biological insights, support clinical translation, or offer methodological frameworks that can be broadly applied across cancer types.

This Research Topic welcomes submissions covering the broad spectrum of integrative, multi-omic, and single-cell approaches in cancer genetics and oncogenomics. We invite innovative work from basic discovery to translational research and clinical studies. Specific themes include, but are not limited to:

• Multi-omic analysis of tumor heterogeneity, clonal evolution, or microenvironmental interactions
• Single-cell or spatial genomics/transcriptomics for deciphering cancer cell states or tumor ecosystems
• Clinical application of liquid biopsy, cell-free nucleic acids, or multi-omic signatures for diagnosis and monitoring
• Discovery and interpretation of novel regulatory, noncoding, or structural variants with functional or clinical impact
• AI, machine learning, and computational integration of high-dimensional cancer omics datasets
• Cross-cancer and pan-cancer studies leveraging integrative molecular profiling frameworks

We encourage submission of original research articles, comprehensive reviews, technical advances, perspectives, and clinical studies that enhance the field of Cancer Genetics and Oncogenomics through integrative, multi-layered molecular analysis.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Registered Report
• Review
• Systematic Review
• Technology and Code

Keywords: multi-omic cancer analysis, integrative omics, single-cell genomics cancer, tumor heterogeneity multi-omics, spatial transcriptomics cancer, cancer microenvironment omics, liquid biopsy multi-omics, noncoding variants cancer

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.