Developments for Personalized Medicine of Lung Cancer Subtypes: Mass Spectrometry-Based Clinical Proteogenomic
Toshihide Nishimura1,2,3, Haruhiko Nakamura4,5
1Translational Medicine Informatics, St. Mariana University School of Medicine, Kanagawa, Japan. t-nisimura-tmu@hotmail.co.jp.
Abstract:
Molecular therapies targeting lung cancers with mutated epidermal growth factor receptor (EGFR) by EGFR-tyrosin kinase inhibitors (EGFR-TKIs), gefitinib and erlotinib, changed the treatment system of lung cancer. It was revealed that drug efficacy differs by race (e.g., Caucasians vs. Asians) due to oncogenic driver mutations specific to each race, exemplified by gefitinib / erlotinib. The molecular target drugs for lung cancer with anaplastic lymphoma kinase (ALK) gene translocation (the fusion gene, EML4-ALK) was approved, and those targeting lung cancers addicted ROS1, RET, and HER2 have been under development. Both identification and quantification of gatekeeper mutations need to be performed using lung cancer tissue specimens obtained from patients to improve the treatment for lung cancer patients: (1) identification and quantitation data of targeted mutated proteins, including investigation of mutation heterogeneity within a tissue; (2) exploratory mass spectrometry (MS)-based clinical proteogenomic analysis of mutated proteins; and also importantly (3) analysis of dynamic protein-protein interaction (PPI) networks of proteins significantly related to a subgroup of patients with lung cancer not only with good efficacy but also with acquired resistance. MS-based proteogenomics is a promising approach to directly capture mutated and fusion proteins expressed in a clinical sample. Technological developments are further expected, which will provide a powerful solution for the stratification of patients and drug discovery (Precision Medicine).
Insights
Molecular therapies like EGFR-TKIs have advanced lung cancer treatment, but efficacy varies by race due to specific mutations. Proteogenomic analysis is key to identifying these mutations and developing targeted therapies for precision medicine.
Area of Science:
- Oncology
- Molecular Biology
- Proteomics
Background:
- Epidermal growth factor receptor (EGFR) mutations drive lung cancer, with targeted therapies like gefitinib and erlotinib showing differential efficacy across racial groups.
- Anaplastic lymphoma kinase (ALK) gene translocations and other targets like ROS1, RET, and HER2 are crucial in lung cancer molecular profiling.
- Understanding racial disparities in drug response necessitates detailed analysis of oncogenic driver mutations.
Purpose of the Study:
- To highlight the importance of identifying and quantifying gatekeeper mutations in lung cancer for improved patient treatment.
- To explore the utility of mass spectrometry (MS)-based proteogenomic analysis for capturing mutated and fusion proteins.
- To investigate dynamic protein-protein interaction (PPI) networks for understanding treatment efficacy and acquired resistance.
Main Methods:
- Proteogenomic analysis using mass spectrometry (MS) to identify and quantify mutated and fusion proteins in clinical samples.
- Analysis of mutation heterogeneity within lung cancer tissue specimens.
- Exploration of protein-protein interaction (PPI) networks associated with treatment response and resistance.
Main Results:
- MS-based proteogenomics enables direct capture of expressed mutated and fusion proteins from clinical samples.
- Identification and quantification of specific mutations are critical for personalized lung cancer treatment strategies.
- Analysis of PPI networks can reveal mechanisms underlying both drug efficacy and acquired resistance.
Conclusions:
- Proteogenomic approaches offer a powerful solution for patient stratification and drug discovery in lung cancer.
- Further technological advancements in MS-based proteogenomics will enhance precision medicine for lung cancer.
- Comprehensive analysis of mutations and their functional interactions is essential for optimizing targeted lung cancer therapies.
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