Metabolic reprograming of antioxidant defense: a precision medicine perspective for radiotherapy of lung cancer?

Radiotherapy plays a key role in the management of lung cancer patients in curative and palliative settings. Traditionally, radiotherapy was either given alone or in combination with surgery, classical cytotoxic chemotherapy, or both. Technical and physical innovations achieved during the last two decades have helped to enhance the accuracy of radiotherapy dose delivery and have facilitated geometric radiotherapy individualization. Furthermore, multimodal combinations with molecularly tailored drugs or immunotherapy yielded promising survival benefits in selected patients. Yet high locoregional failure rates and frequent development of metastases still limit the patient outcome. One major obstacle to successful treatment is the high molecular heterogeneity observed in lung cancer. So far, clinical radiotherapy does not routinely use the knowledge on molecular subtypes with regard to therapy individualization and predictive biomarkers are missing. Herein, altered cancer metabolism has attracted novel attention during recent years as it promotes tumor growth and progression as well as resistance to anticancer therapies. The present perspective will exemplarily highlight how clinically relevant molecular subtypes defined by co-occurring somatic mutations in KRAS-driven lung cancer impact the metabolic phenotype of cancer cells, how the metabolic phenotype supports intrinsic radioresistance by the improved antioxidant defense, and also discuss potential subtype-specific actionable metabolic vulnerabilities. Understanding metabolic phenotypes of radioresistance and metabolic bottlenecks of cancer cells undergoing radiotherapy in a cancer-specific context will offer largely unexploited future avenues for biological individualization and optimization of radiotherapy. Transcriptional profiles will provide additional benefit in defining metabolic phenotypes associated with radioresistance, particularly in cases, where such dependencies cannot be identified by specific somatic mutations.