Inferring mutational timing and reconstructing tumour evolutionary histories

Area of Science:

• Oncology
• Evolutionary Biology
• Genomics

Background:

• Cancer progression and treatment resistance can be understood using micro- and macro-evolutionary theories.
• Tumor complexity and heterogeneity obscure the precise rules governing cancer evolution, including the role of selection.
• The temporal order of genetic alterations in tumors presents significant opportunities for clinical applications.

Purpose of the Study:

• To review current methods for determining the timing of mutational events in cancer evolution.
• To synthesize evidence from next-generation sequencing data regarding mutational timing across diverse cancer types.
• To explore the clinical and therapeutic implications of understanding mutational timing.

Main Methods:

• Review of existing sampling and computational approaches for inferring mutational timing.
• Analysis of next-generation sequencing data to identify patterns of mutational timing in various cancers.
• Discussion of the integration of mutational timing knowledge into clinical practice.

Main Results:

• Established methods for inferring mutational timing are presented.
• Evidence from next-generation sequencing highlights the importance of mutational timing across tumor types.
• The potential of mutational timing to reveal drivers of cancer initiation and relapse is discussed.

Conclusions:

• Understanding mutational timing is crucial for deciphering cancer evolution.
• Knowledge of mutational timing can guide the development of targeted therapies and improve clinical trial design.
• This review provides a framework for leveraging mutational timing in oncology research and practice.