Personalized medicine for lung cancer: new challenges for pathology

Area of Science:

• Oncology
• Pathology
• Molecular Diagnostics

Background:

• Current non-small-cell lung cancer (NSCLC) classification is insufficient for personalized treatment selection.
• Tumor heterogeneity and limited tissue from biopsies complicate accurate diagnosis.
• Newer therapies require more specific subtyping for safety and efficacy.

Purpose of the Study:

• To highlight the need for advanced NSCLC subtyping beyond simple discrimination.
• To discuss the role of immunohistochemistry and molecular markers in predicting treatment response.
• To address the challenges posed by limited diagnostic material in minimally invasive biopsies.

Main Methods:

• Utilizing immunohistochemical markers such as P63, cytokeratins 5 and 6, and thyroid transcription factor 1 (TTF1) for histotype prediction.
• Analyzing molecular characteristics, including epidermal growth factor receptor (EGFR) mutations, to predict response to targeted therapies (e.g., erlotinib, gefitinib).
• Evaluating markers like thymidylate synthase (TS) and excision repair cross-complementation group 1 (ERCC1) for predicting response to specific agents (e.g., pemetrexed, cisplatin).

Main Results:

• Immunohistochemistry effectively predicts squamous and adenocarcinoma histology.
• Specific EGFR mutations are reliable predictors of response to EGFR tyrosine kinase inhibitors.
• Molecular markers can indicate sensitivity to targeted agents and predict DNA repair capacity for cytotoxic drugs.

Conclusions:

• Advanced NSCLC subtyping using immunohistochemistry and molecular markers is essential for guiding personalized therapy.
• These diagnostic approaches help overcome limitations of tumor heterogeneity and scarce tissue samples.
• Integrating these methods enhances diagnostic accuracy and optimizes treatment selection for NSCLC patients.