# Emerging hallmarks and the rise of complexities and heterogeneity of tumor

## TL;DR

This paper reviews and expands the concept of tumor hallmarks to better understand cancer complexity and improve precision oncology.

## Contribution

It proposes a unified hierarchical model linking classical and emerging tumor hallmarks using AI-powered multi-omics integration.

## Key findings

- Expands tumor hallmark view across multiple biological frameworks.
- Proposes refined segregation to capture cancer complexity and heterogeneity.
- Highlights AI-powered multi-omics integration for precision oncology.

## Abstract

Cancer is known for its complexities and heterogeneity due to genetic, epigenetic, known, and unknown environmental components. From time to time, incremental viewpoints on the expanding landscape of tumor hallmarks, including sustained proliferation, evasion of cell death, immune evasion, metabolic reprogramming, and the metabolic-epigenomic-immune axis, are presented. Unifying old and new tumor hallmarks may offer progressive platforms for new diagnostic, therapeutic, and monitoring approaches to therapy responses. Here, we strive to present an updated framework at intracellular, cellular, intercellular, and extracellular levels, assisted by emerging technologies such as OMICS and super-resolution imaging technologies. This review emphasizes that understanding emerging tumor hallmarks may help reveal the dynamics and heterogeneity of tumors. This could lead to sustainable diagnosis, prognosis, and therapeutic management, including precision and personalized approaches for cancer patients. This review presents a unified hierarchical model that connects classical and emerging tumor hallmarks through AI-powered multi-omics integration, emphasizing its conceptual innovation and translational potential in advancing precision oncology.

•Expands tumor hallmark view across cellular, intracellular, intercellular and extracellular frameworks.•Critiques current hallmark framework and its limitations.•Proposes refined segregation to capture cancer complexity.•Explores tumor evolution, therapy resistance, and adaptation.•Discuss prevention, diagnosis, prognosis, and therapies in the contexts of expanding tumor hallmarks.

Expands tumor hallmark view across cellular, intracellular, intercellular and extracellular frameworks.

Critiques current hallmark framework and its limitations.

Proposes refined segregation to capture cancer complexity.

Explores tumor evolution, therapy resistance, and adaptation.

Discuss prevention, diagnosis, prognosis, and therapies in the contexts of expanding tumor hallmarks.