The histone deacetylase SIRT6 promotes glycolysis through the HIF-1α/HK2 signaling axis and induces erlotinib resistance in non-small cell lung cancer.

Erlotinib is a first-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI). Overcoming erlotinib resistance is crucial to improve the survival of advanced non-small cell lung cancer (NSCLC) patients with sensitive EGFR mutations. It is also an important clinical problem that urgently needs a solution. In this study, we explored strategies to overcome erlotinib resistance from the perspective of energy metabolism. SIRT6 is a histone deacetylase. Here, we found that high expression of SIRT6 is associated with poor prognosis of lung adenocarcinoma, especially in EGFR-mutated NSCLC patients. The next cell experiment found that SIRT6 expression increased in erlotinib-resistant cells, and SIRT6 expression was negatively correlated with the sensitivity of NSCLC to erlotinib. Inhibition of SIRT6 promoted erlotinib-induced apoptosis in erlotinib-resistant cells, and glycolysis in drug-resistant cells was also inhibited. Functional studies have shown that SIRT6 increases glycolysis through the HIF-1α/HK2 signaling axis in drug-resistant cells and inhibits the sensitivity of NSCLC cells to erlotinib. In addition, the HIF-1α blocker PX478-2HCL attenuated the glycolysis and erlotinib resistance induced by SIRT6. More importantly, we confirmed the antitumor effect of SIRT6 inhibition combined with erlotinib in NSCLC-bearing mice. Our findings indicate that the cancer metabolic pathway regulated by SIRT6 may be a new target for attenuating NSCLC erlotinib resistance and has potential as a biomarker or therapeutic target to improve outcomes in NSCLC patients.

Predicting potential therapeutic targets and small molecule drugs for early-stage lung adenocarcinoma.

Lung cancer is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) constituting the majority, and its main subtype being lung adenocarcinoma (LUAD). Despite substantial advances in LUAD diagnosis and treatment, early diagnostic biomarkers inadequately fulfill clinical requirements. Thus, we conducted bioinformatics analysis to identify potential biomarkers and corresponding therapeutic drugs for early-stage LUAD patients. Here we identified a total of 10 differentially expressed genes (DEGs) with survival significance through the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Subsequently, we identified a promising small molecule drug, Aminopurvalanol A, based on the 10 key genes using the L1000FWD application, which was validated by molecular docking followed by in vivo and in vitro experiments. The results highlighted TOP2A, CDH3, ASPM, CENPF, SLC2A1, and PRC1 as potential detection biomarkers for early LUAD. We confirmed the efficacy and safety of Aminopurvalanol A, providing valuable insights for the clinical management of LUAD.

Clinical associations and prognostic value of site-specific metastases in non-small cell lung cancer: A population-based study.

The prognosis of non-small cell lung cancer (NSCLC) is poor, particularly for patients with metastatic disease. Numerous efforts have been made to improve the prognosis of these patients; however, only a small number of studies have explored the occurrence rate and prognostic value of different patterns of distant metastasis (DM) in NSCLC systematically. To investigate these, information from patients diagnosed with NSCLC between 2010 and 2014 was collected from the Surveillance, Epidemiology and End Results database. Survival rate comparisons were performed using Kaplan-Meier analysis and log-rank tests. A Cox proportional hazard model was established to determine factors associated with improved overall survival (OS) and cancer-specific survival (CSS). The present study revealed that the most common site of single metastasis occurrence was bone, and the least common was the liver for NSCLC. As for multi-site metastases, the most common two-site metastasis involved bone and lung, and the most common three-site metastasis involved bone, liver and lung. As for NSCLC subtypes, large cell carcinoma (LCC) exhibited more specific metastatic features. The most common single metastatic site was the brain for patients with LCC, and the most common two-site metastatic combination was bone and liver. Patients with isolated liver metastasis exhibited the worst OS and CSS among patients with single metastasis. Furthermore, for patients with multi-site metastases, metastases involving the liver were associated with the worst OS and CSS among various combinations. To the best of our knowledge, the present study is the first to investigate the occurrence rate and prognostic value of different metastatic patterns of site-specific DM for NSCLC using a large population-based dataset. The findings of the present study may have vital implications for classifying patients with advanced NSCLC, thus laying a foundation for individualized precise treatment.

Rab25 promotes erlotinib resistance by activating the ß1 integrin/AKT/ß-catenin pathway in NSCLC.

OBJECTIVES: Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) has significant therapeutic efficacy in non-small-cell lung cancer (NSCLC) patients. However, acquired resistance is inevitable and limits the long-term efficacy of EGFR-TKI. Our study aimed to investigate the role of ras-associated binding protein 25 (Rab25) in mediating EGFR-TKI resistance in NSCLC. MATERIALS AND METHODS: Rab25 expression in NSCLC patients was measured by immunohistochemical staining. Western blotting was used to analyse the expression of molecules in the Rab25, EGFR and Wnt signalling pathways. Lentiviral vectors were constructed to knock in and knock out Rab25. The biological function of Rab25 was demonstrated by cell-counting kit-8 and flow cytometry. The interaction between Rab25 and ß1 integrin was confirmed by co-immunoprecipitation. RESULTS: Rab25 overexpression induced erlotinib resistance, whereas Rab25 knockdown reversed this refractoriness in vitro and in vivo. Moreover, Rab25 interacts with ß1 integrin and promotes its trafficking to the cytoplasmic membrane. The membrane-ß1 integrin induced protein kinase B (AKT) phosphorylation and subsequently activated the Wnt/ß-catenin signalling pathway, promoting cell proliferation. Furthermore, high Rab25 expression was associated with poor response to EGFR-TKI treatment in NSCLC patients. CONCLUSIONS: Rab25 mediates erlotinib resistance by activating the ß1 integrin/AKT/ß-catenin signalling pathway. Rab25 may be a predictive biomarker and has potential therapeutic value in NSCLC patients with acquired resistance to EGFR-TKI.

Multimodal detection of PD-L1: reasonable biomarkers for immune checkpoint inhibitor.

Immune checkpoint inhibitor (ICI) therapy had achieved significant clinical benefit in multiple malignant solid tumors, such as non-small cell lung cancer, melanoma and urothelial cancer. ICI therapy not only revolutionarily altered the treatment strategy of malignant solid tumors, but also dramatically prolonged overall survival. However, the objective response rate (ORR) of ICI therapy in second line treatment remains 20% or less. How to find patients eligible for ICI therapy by effective biomarkers became hot nowadays. High expression of PD-L1 protein in tumor cells or tumor microenvironment (TME) had been identified to be a logical biomarker for predicting efficacy of ICI therapy and approved by the U.S. Food and Drug Administration to be an indicator of initiating treatment for some solid tumors. Controversially, patients with low PD-L1 protein expression might also show clinical benefit. In this sense, tissue PD-L1 protein expression might not be a precise biomarker. Multimodal detection of PD-L1, such as PD-L1 protein, PD-L1 mRNA, and circulating PD-L1, might provide a comprehensive tumor profile and could find the patients who are more suitable for ICI therapy. Besides, dynamic monitoring of PD-L1 expression could shed light on efficacy assessment and drug resistance. ICI-based combination strategy had demonstrated better outcome than ICI alone. Single biomarker might not be efficient to precisely find advantage patients. Combined biomarkers could better instruct the consideration of therapeutic regimen. In addition, nomogram and artificial intelligence platform could integrate multiparameter information of biomarkers which might shed light on tumor profile and give a hint to treatment decision.