Related Experiment Video
Updated: Oct 21, 2025

Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018
STK11/LKB1 and KEAP1 mutations in non-small cell lung cancer: Prognostic rather than predictive?
Alessandro Di Federico1, Andrea De Giglio1, Claudia Parisi1
1Division of Medical Oncology, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Italy; Department of Specialized, Experimental and Diagnostic Medicine, University of Bologna, Via Giuseppe Massarenti, 9, 40138 Bologna, Italy.
Abstract:
Immune checkpoint inhibitors (ICIs), either alone or combined with chemotherapy, represent the cornerstone of the treatment of advanced non-small cell lung cancer (NSCLC) without targetable gene alterations. Programmed death ligand-1 expression currently represents the only available biomarker to predict response to ICI, although its reliability is debated. However, most patients still do not derive benefit from immunotherapy, making the identification of further predictive biomarkers extremely needed. Serine/threonine kinase 11 (STK11)/liver kinase B1 (LKB1) and Kelch-like ECH-associated protein 1 (KEAP1) mutations occur in 25-30% and 11-27% of advanced NSCLC, respectively. Several studies associated their presence with poor outcomes in patients treated with ICI. However, more recent evidence showed poor outcomes among NSCLC with STK11/LKB1 and/or KEAP1 mutations regardless of the treatment received. We reviewed the literature to provide a comprehensive, timely and structured overview of the role of STK11/LKB1 and KEAP1 mutations in NSCLC. Although conflicting outcomes have been reported by studies evaluating their impact in KRAS wild-type patients or regardless of KRAS mutation, the correlation between STK11/LKB1 and KEAP1 mutations and poor outcomes with ICI appears to be consistent in presence of concurrent KRAS mutations. The main limitations of most studies are represented by the inclusion of other gene mutations (e.g. TP53) together with STK11 and KEAP1 mutations as a group and by the lack of comparison arms including patients who received other treatments (e.g. chemotherapy). Studies evaluating the impact of STK11 and KEAP1 mutations on the outcomes with ICI and other therapies showed a similar effect regardless of the treatment received, suggesting a prognostic, rather than predictive, value.
Insights
Mutations in STK11/LKB1 and KEAP1 genes are linked to poor outcomes in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). These mutations may have a prognostic rather than predictive role in NSCLC treatment.
Area of Science:
- Oncology
- Genetics
- Immunotherapy
Background:
- Immune checkpoint inhibitors (ICIs) are standard for advanced non-small cell lung cancer (NSCLC) without targetable alterations.
- Programmed death ligand-1 (PD-L1) is an imperfect biomarker for ICI response.
- Novel biomarkers are crucial as most patients do not benefit from immunotherapy.
Purpose of the Study:
- To review the literature on the role of STK11/LKB1 and KEAP1 mutations in NSCLC.
- To clarify the prognostic and predictive value of these mutations in advanced NSCLC.
Main Methods:
- Comprehensive literature review of studies on STK11/LKB1 and KEAP1 mutations in NSCLC.
- Analysis of outcomes in patients treated with ICIs, chemotherapy, and other therapies.
- Evaluation of mutation impact in relation to KRAS status and co-occurring mutations.
Main Results:
- STK11/LKB1 and KEAP1 mutations are common in advanced NSCLC (25-30% and 11-27%, respectively).
- These mutations correlate with poor outcomes with ICI, especially with concurrent KRAS mutations.
- Studies suggest STK11/LKB1 and KEAP1 mutations have a prognostic, not predictive, value, showing similar effects across different treatments.
Conclusions:
- STK11/LKB1 and KEAP1 mutations are associated with poor outcomes in NSCLC, particularly when co-occurring with KRAS mutations.
- The prognostic value of these mutations appears consistent across different treatment modalities.
- Further research is needed to address limitations like combined mutation analysis and lack of diverse treatment comparison arms.
More Related Videos
Related Concept Videos
lncRNA - Long Non-coding RNAs
Targeted Cancer Therapies
There are several types of targeted therapies against...

