Criticality in tumor evolution and clinical outcome

Area of Science:

• Cancer Biology
• Evolutionary Biology
• Genomics

Background:

• Understanding tumor evolution and its impact on clinical outcomes is critical for cancer treatment.
• The interplay between mutation accumulation and natural selection shapes the tumor fitness landscape.

Purpose of the Study:

• To explore the mutation-selection phase diagram across diverse cancer types.
• To quantify the relationship between mutation load (ML), selection (dN/dS), and patient survival.
• To elucidate the evolutionary trajectories of different cancers.

Main Methods:

• Analyzed somatic point mutation load (ML) and selection (dN/dS) in the proteomes of 6,721 tumors across 23 cancer types.
• Correlated ML and dN/dS with patient survival data.
• Mapped cancer types onto a ML-dN/dS plane to visualize evolutionary strategies.

Main Results:

• Mutation load (ML) strongly correlates with patient survival, exhibiting opposing trends in low-ML and high-ML cancers.
• Low-ML cancers with high mutation counts suggest poor prognosis, while high-ML cancers show improved survival, potentially due to mutational meltdown.
• Cancers evolve near neutrality, with deviations observed at extreme MLs; melanoma shows purifying selection, while low-ML cancers exhibit positive selection.

Conclusions:

• Cancer evolution is characterized by diverse trajectories on the ML-dN/dS plane.
• Tumor evolution exhibits nonlinear effects on survival, influenced by mutation and selection dynamics.
• Findings support and expand theories of tumor evolution and its clinical implications.