Background
In NSCLC, TP53 mutations are heterogeneous with varied effects on protein synthesis, function and clinical outcomes. We hypothesize that a refined classification of TP53 mutations, beyond binary categorization, could improve prognostication. Furthermore, specific mutations could be associated with enhanced benefit from immune checkpoint inhibitors (ICI) versus chemotherapy. To investigate this, we analyzed data from randomized trials (OAK and POPLAR) which compared atezolizumab to chemotherapy in previously treated advanced driver-negative NSCLC.
Methods
Participants were classified as TP53 mutant or wild-type using baseline plasma, and by coding mutation, and Olivier’s and Poeta’s classification. We performed multivariable Cox regression analyses to evaluate the prognostic significance of TP53 mutations, and interaction tests to assess their predictive value.
Results
Among 762 participants, 49% harbored a TP53 mutation. TP53 mutations based on binary categorization were associated with poorer but not statistically significant OS compared to wild-type (adjusted-HR 1.15; 95 %CI 0.96–1.38; P = .12). However, nonsense mutations classified by coding mutations (adjusted-HR 1.71; 95% CI 1.22–2.39; P = .002), non-missense mutations classified by Olivier’s classification (adjusted-HR 1.33; 95% CI 1.03–1.74; P = .03) and disruptive mutations classified by Poeta’s classification (adjusted-HR 1.33; 95% CI 1.37–1.77; P = .03) were associated with statistically significant poorer OS. TP53 status did not predict differential benefit from ICI versus chemotherapy (interaction P = .45).
Conclusion
In advanced driver-negative NSCLC following progression on first-line chemotherapy, nonsense, non-missense and disruptive mutations of TP53 were strongly associated with inferior OS. These data support utilizing a nuanced classification of TP53 mutations as a stratification factor in future trials, and laboratory reporting to aid prognostication.
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