Identifying genes associated with resistance to KRAS G12C inhibitors via machine learning methods
Xiandong Lin1, QingLan Ma2, Lei Chen3
1Laboratory of Radiation Oncology and Radiobiology, Clinical Oncology School of Fujian Medical University and Fujian Cancer Hospital, Fuzhou 350014, China.
Background:
Targeted therapy has revolutionized cancer treatment, greatly improving patient outcomes and quality of life. Lung cancer, specifically non-small cell lung cancer, is frequently driven by the G12C mutation at the KRAS locus. The development of KRAS inhibitors has been a breakthrough in the field of cancer research, given the crucial role of KRAS mutations in driving tumor growth and progression. However, over half of patients with cancer bypass inhibition show limited response to treatment. The mechanisms underlying tumor cell resistance to this treatment remain poorly understood.
Methods:
To address above gap in knowledge, we conducted a study aimed to elucidate the differences between tumor cells that respond positively to KRAS (G12C) inhibitor therapy and those that do not. Specifically, we analyzed single-cell gene expression profiles from KRAS G12C-mutant tumor cell models (H358, H2122, and SW1573) treated with KRAS G12C (ARS-1620) inhibitor, which contained 4297 cells that continued to proliferate under treatment and 3315 cells that became quiescent. Each cell was represented by the expression levels on 8687 genes. We then designed an innovative machine learning based framework, incorporating seven feature ranking algorithms and four classification algorithms to identify essential genes and establish quantitative rules.
Results:
Our analysis identified some top-ranked genes, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5, that are known to be associated with the progression of multiple cancers.
Conclusion:
Above genes were relevant to tumor cell resistance to targeted therapy. This study provides important insights into the molecular mechanisms underlying tumor cell resistance to KRAS inhibitor treatment.
Insights
Researchers identified key genes like H2AFZ and CKS1B contributing to resistance against KRAS G12C inhibitor therapy in lung cancer. This discovery offers insights into overcoming treatment limitations for patients with KRAS-mutant cancers.
Area of Science:
- Oncology
- Molecular Biology
- Bioinformatics
Background:
- Targeted therapy, particularly KRAS inhibitors, has advanced cancer treatment.
- Non-small cell lung cancer (NSCLC) often harbors KRAS G12C mutations.
- Limited response and resistance to KRAS inhibitors are significant clinical challenges.
Purpose of the Study:
- To identify molecular differences between tumor cells that respond and resist KRAS (G12C) inhibitor therapy.
- To understand the mechanisms of acquired resistance to KRAS G12C inhibitors.
Main Methods:
- Single-cell gene expression profiling of KRAS G12C-mutant NSCLC cell lines (H358, H2122, SW1573) under ARS-1620 treatment.
- Application of a machine learning framework with feature ranking and classification algorithms.
- Analysis of gene expression data from proliferating and quiescent cells.
Main Results:
- Identified key genes associated with resistance, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5.
- These genes are implicated in the progression of various cancer types.
- Established quantitative rules for identifying resistance markers.
Conclusions:
- The identified genes are crucial for understanding tumor cell resistance to KRAS inhibitor therapy.
- This research provides critical insights into the molecular basis of resistance.
- Findings may inform future therapeutic strategies to overcome resistance.
