Objective:

To explore the evolution of precision oncology through the integration of molecular mechanisms, multi-omics technologies, functional disease models, and clinically realistic trial design for personalized cancer care.

Approach:

Key Findings:

• Cancer is a dynamic biological system influenced by multiple regulatory layers.
• Epigenetic alterations play a significant role in cancer metastasis and therapeutic resistance.
• Omics technologies aid in the identification of molecular subgroups and therapeutic vulnerabilities.
• Functional modelling using patient-derived organoids shows promise in predicting treatment responses.
• Integrated diagnostic approaches can reduce uncertainty in clinical decision-making.
• Multiple primary lung cancer is underrepresented in clinical trials, affecting evidence generation.

Interpretation:

The articles collectively advocate for a multidimensional approach to precision oncology, emphasizing the integration of various biological and clinical factors in treatment decisions.

Limitations:

• Current biomarkers have limitations and require more refined patient selection.
• Multiple primary lung cancer is underrepresented in clinical trials, affecting evidence generation.

Conclusion:

The future of personalized cancer care relies on the integration of diverse methodologies and a comprehensive understanding of cancer biology.

Attribution Notice

This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.