# Towards Precision Oncology: How Advances in Cancer Genomics, Immunobiology and Artificial Intelligence Will Change Molecular Diagnostics

## TL;DR

This paper explores how advances in cancer genomics, immunology, and AI can transform molecular diagnostics in precision oncology.

## Contribution

The paper conceptualizes molecular diagnostics through cancer hallmarks and AI integration, using NSCLC as a model.

## Key findings

- Advances in cancer biology, immunity, and AI offer new opportunities for molecular diagnostics.
- Integrating cancer hallmarks with AI can improve personalized cancer treatment strategies.
- Molecular diagnostics is evolving alongside precision oncology through multidimensional data analysis.

## Abstract

Over the last decades, a significant improvement in cancer patient outcomes has occurred due to advances in cancer cell biology, systemic immunity, tumor-immune microenvironment (TIME) and precision cancer therapy. Despite this explosion of knowledge, its usefulness in clinical practice has been limited by the ability to translate multidimensional data into clinical care. Progress in artificial intelligence (AI) opens up a new frontier, with the promise of achieving synergistic and comprehensive integration. The classification of cancer biology and immunobiology into hallmarks of cancer by Hanahan and Weinberg provides a framework for organizing this information. This systematic classification has enabled the understanding of the interplay and cross-talk between its parts. Targeted cancer therapies and immunotherapies have achieved considerable success, yet their combinatorial potential is still being uncovered. Molecular diagnostics has worked hand-in-hand with precision oncology in deploying new therapies in a cancer-informed and patient-specific way. Harnessing the full power of the advances in these three fields with the aid of AI promises a transformation of molecular diagnostics. This review conceptualizes molecular diagnostics in the context of cancer hallmarks using nonsmall cell lung cancer (NSCLC) as a template, highlighting the potential of a new diagnostic science through the integrative power of AI.