Cancer is a highly heterogeneous disease driven by alterations across the genome, epigenome, transcriptome, proteome, metabolome, and tumor microenvironment. Although high‑throughput technologies have generated extensive molecular data, integrating these layers into a coherent view of tumorigenesis at the cancer cell and tumor ecosystem levels remains a major challenge. Single‑omics studies often provide only partial insight into cancer initiation, progression, immune evasion, and therapy resistance.

Multi‑omics approaches can overcome these limitations. By integrating genomic, epigenomic, transcriptomic, proteomic, metabolomic, and microbiome data, they can dissect tumor complexity and uncover discoveries that single‑omics analyses miss. Integrated multi‑omics can clarify:

Cancer cell–intrinsic processes such as signaling rewiring (e.g., Wnt, JAK–STAT, PI3K/AKT)
RNA modifications and non‑coding RNA regulation
Metabolic reprogramming, including tryptophan metabolism
Lineage plasticity, cell cycle control, apoptosis, and senescence
Cancer cell–extrinsic influences from the tumor microenvironment, including immune cells, stromal cells, and intratumoral microbiota
This Research Topic aims to bridge the translational gap between multi‑omics data generation and clinical application. We will curate studies that combine integrative multi‑omics analysis with experimental or clinical validation to answer key questions in cancer cell biology, with particular interest in digestive system tumors such as hepatocellular carcinoma, but not limited to them. We aim to foster collaboration among bioinformaticians, basic scientists, and clinical oncologists to translate data into mechanistic insight and improved patient outcomes.

Priority will be given to research where cellular and molecular mechanisms form the core of the study and in silico and clinical components support these biological insights. Specifically, we will favour work that:

Integrates two or more omics layers (e.g., genomics, transcriptomics, epigenomics, proteomics, metabolomics, microbiome, single‑cell or spatial omics)
Provides mechanistic insight into cancer cell biology or tumor–microenvironment interactions
Includes experimental or clinical validation (e.g., in cell lines, organoids, patient‑derived xenografts, primary patient samples, or prospective cohorts)
We particularly welcome studies that use in vitro, in vivo, or ex vivo functional assays to establish causal links between molecular alterations and cancer cell behaviour and that reveal actionable biomarkers or therapeutic vulnerabilities.

Submissions that rely solely on secondary analysis of publicly available datasets, without experimental, functional, or clinical validation and without substantial new biological insight into cancer cell biology, will be considered out of scope.

We invite Original Research, Review, Methods, Perspective, and Brief Research Report articles in areas including, but not limited to:

1. Integrative Multi‑Omics Tools for Cancer Cell Biology
Development and application of algorithms, AI/ML models, and software platforms for integrative multi‑omics that primarily serve to elucidate cellular and molecular mechanisms in cancer, addressing questions such as signaling dysregulation, RNA modification networks, metabolic pathways, and intratumoral microbiome interactions, with experimental or clinical validation. Purely methodological studies without application to cancer cell biology and without validation will be considered out of scope.

2. Mechanistic Insights in Digestive System and Other Tumors
Multi‑omics studies that uncover mechanisms of tumour initiation, progression, and therapy resistance in digestive system cancers (e.g., hepatocellular, colorectal, gastric) and other solid tumours, including: key signaling pathways (Wnt, JAK–STAT, PI3K/AKT), RNA methylation and other RNA modifications, non‑coding RNAs, metabolic reprogramming, and cell cycle, apoptosis, and senescence. Functional validation is expected.

3. Tumor Microenvironment, Microbiome, and Metabolic Crosstalk
Multi‑omics and single‑cell/spatial studies of cancer cell interactions with the immune microenvironment, stromal cells, and intratumoral or gut microbiota, linking microbial or metabolic features to tumour genetics/epigenetics, signalling, therapeutic response, and resistance.

4. Single‑Cell and Spatial Multi‑Omics in Tumor Ecosystems
Single‑cell and spatial multi‑omics (e.g., scRNA‑seq, scATAC‑seq, spatial transcriptomics, multiplexed imaging) to map intra‑tumoral heterogeneity, clonal evolution, and cell–cell interactions, ideally integrated with other omics layers and supported by mechanistic or functional validation.

5. Translational Biomarkers and Clinical Integration
Identification and validation of diagnostic, prognostic, or predictive biomarkers from integrated omics data, with clear links to cancer cell biology mechanisms, experimental validation where feasible, and demonstrated potential for patient stratification, risk assessment, or therapy selection, including use in clinical trials.

Impact

Frontiers in Cell and Developmental Biology

Cancer Cell Biology