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

Author:
Preprint
Publisher website
Google Scholar
Abstract
Over the last decades, significant improvement in cancer patient outcomes has occurred due to advances in cancer cell biology, systemic and tumour 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 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 crosstalk between its parts. Targeted cancer and immunotherapies targeting various components 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 the field of molecular diagnostics. This review aims to conceptualize molecular diagnostics in the context of Cancer Hallmarks and TIME using Nonsmall Cell Lung Cancer (NSCLC) as a template. We aim to highlight the potential of a new diagnostic science through the integrative power of AI.

This publication has 83 references indexed in Scilit: