LKB1 Loss Assessed by Immunohistochemistry as a Prognostic Marker to First-Line Therapy in Advanced Non-Small-Cell Lung Cancer.
Alejandro Avilés-SalasDiego A Díaz-GarcíaLuis Lara-MejíaAndrés F CardonaMario Orozco-MoralesRodrigo CatalánNorma Y Hernández-PedroEduardo Rios-GarciaMaritza Ramos-RamírezArrieta OscarPublished in: Current oncology (Toronto, Ont.) (2022)
(1) Background: Liver kinase B1 (LKB1) is a tumor suppressor gene involved in cell growth and metabolism. However, its alterations are not routinely assessed for guiding therapy in clinical practice. We assessed LKB1 expression by immunohistochemistry as a potential biomarker. (2) Methods: This bicentric retrospective cohort study analyzed data from patients with advanced NSCLC who initiated platinum-based chemotherapy or epidermal growth factor receptor- tyrosine kinase inhibitor (EGFR-TKI) between January 2016 and December 2020. Kaplan-Meier and Cox regression models were used for survival curves and multivariate analysis. (3) Results: 110 patients were evaluated, and the clinical stage IV predominated the lung adenocarcinoma histology. LKB1 loss was observed in 66.3% of cases. LKB1 loss was associated with non-smokers, the absence of wood smoke exposure and an EGFR wild-type status. The median progression-free survival (PFS) and overall survival (OS) in the population were 11.1 and 26.8 months, respectively, in the loss group, compared with cases exhibiting a positive expression. After an adjustment by age, smoking status, Eastern Cooperative Oncology Group Performance Score (ECOG-PS), EGFR status and type of administered therapy, LKB1 loss was significantly associated with worse PFS and OS. (4) Conclusion: Patients with an LKB1 loss had worse clinical outcomes. This study warrants prospective assessments to confirm the prognostic role of the LKB1 expression in advanced NSCLC.
Keyphrases
- epidermal growth factor receptor
- advanced non small cell lung cancer
- tyrosine kinase
- small cell lung cancer
- free survival
- poor prognosis
- clinical practice
- wild type
- end stage renal disease
- newly diagnosed
- ejection fraction
- palliative care
- chronic kidney disease
- squamous cell carcinoma
- smoking cessation
- data analysis
- machine learning
- deep learning
- bone marrow
- long non coding rna
- protein kinase
- dna methylation
- patient reported outcomes
- patient reported