Adding of neurotensin to non-small cell lung cancer cells increases tyrosine phosphorylation of HER3

A novel investigation into the negative impact of opioid use on the efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer patients

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have effectively improved the clinical outcome of advanced non-small cell lung cancer (NSCLC). Opioids are commonly used for pain relief in cancer patients. This study aims to clarify the prognostic impact of opioid use in advanced NSCLC patients receiving ICI therapy.

METHODS

A systematic literature review was carried out using online databases before July 2023. The meta-analysis was used to clarify the correlation of opioid use with the overall survival (OS) or progression-free survival (PFS) of ICI-treated NSCLC patients, both of which were determined using hazard ratios (HRs) coupled with 95 % confidence intervals (CIs). Then, an independent cohort enrolling 181 NSCLC patients was utilized for validation. Finally, a comprehensive bioinformatics analysis based on TCGA cohort was performed to investigate the prognostic significance of opioid target genes (OTGs) and their correlation with immune infiltration in NSCLC patients.

RESULTS

A total of 8 studies enrolling 1174 patients were included in the meta-analysis. Opioid use was negatively associated with worse PFS (HR = 2.16, 95 %CI: 1.26-3.71) and OS (HR = 2.02, 95 %CI: 1.54-2.63) in ICI-treated NSCLC patients. The retrospective validation confirmed the above result and identified opioid use as an independent unfavorable predictor for PFS and OS in both the entire cohort and ICI subgroup. The bioinformatic analysis identified 14 prognostic OTGs (CYP17A1, PDYN, PYCARD, FGA, NTSR1, FABP1, HPCA, PENK, PDGFB, LIN7A, FKBP5, TYMS, CACNA1H and LDHA), most of which were correlated with immune infiltration in NSCLC. A risk model was constructed based on 14 OTGs and found to effectively stratify the clinical outcome in both the training and validation set, independent of age, gender and TNM staging system. The model was also significantly correlated with infiltration of activated dendritic cells, neutrophils and tumor infiltrating lymphocytes. Finally, a nomogram was constructed based on the model, age, gender and TNM stage, which could predict well the 1-, 3- and 5-year survival of NSCLC patients.

CONCLUSION

Opioid use is correlated with the poor clinical outcome in ICI-treated NSCLC patients. Precise pain management is highly advocated and opioids are recommended to be cautiously used in these patients. OTGs have the potential to be prognostic biomarkers for NSCLC patients and their role in tumor immunity needs to be further investigated.

A Six-gene Prognostic Model Based on Neutrophil Extracellular Traps (NETs)-related Gene Signature for Lung Adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most common malignant cancers. Neutrophil extracellular traps (NETs) have been discovered to play a crucial role in the pathogenesis of LUAD. We aimed to establish an innovative prognostic model for LUAD based on the distinct expression patterns of NETs-related genes.

METHODS

The TCGA LUAD dataset was utilized as the training set, while GSE31210, GSE37745, and GSE50081 were undertaken as the verification sets. The patients were grouped into clusters based on the expression signature of NETs-related genes. Differentially expressed genes between clusters were identified through the utilization of the random forest and LASSO algorithms. The NETs score model for LUAD prognosis was developed by multiplying the expression levels of specific genes with their corresponding LASSO coefficients and then summing them. The validity of the model was confirmed by analysis of the survival curves and ROC curves. Additionally, immune infiltration, GSEA, mutation analysis, and drug analysis were conducted. Silencing ABCC2 in A549 cells was achieved to investigate its effect.

RESULTS

We identified six novel NETs-related genes, namely UPK1B, SFTA3, GGTLC1, SCGB3A1, ABCC2, and NTS, and developed a NETs score signature, which exhibited a significant correlation with the clinicopathological and immune traits of the LUAD patients. High-risk patients showed inhibition of immune-related processes. Mutation patterns exhibited variability among the different groups. AZD3759, lapatinib, and dasatinib have been identified as potential candidates for LUAD treatment. Moreover, the downregulation of ABCC2 resulted in the induction of apoptosis and suppression of migration and invasion in A549 cells.

CONCLUSION

Altogether, this study has identified a novel NET-score signature based on six novel NET-related genes to predict the prognosis of LUAD and ABCC2 and has also explored a new method for personalized chemo-/immuno-therapy of LUAD.

Peptide G-Protein-Coupled Receptors and ErbB Receptor Tyrosine Kinases in Cancer

The ErbB RTKs (EGFR, HER2, HER3, and HER4) have been well-studied in cancer. EGFR, HER2, and HER3 stimulate cancer proliferation, principally by activating the phosphatidylinositol-3-kinase and extracellular signal-regulated kinase (ERK) pathways, resulting in increased cancer cell survival and proliferation. Cancer cells have high densities of the EGFR, HER2, and HER3 causing phosphorylation of tyrosine amino acids on protein substrates and tyrosine amino acids near the C-terminal of the RTKs. After transforming growth factor (TGF) α binds to the EGFR, homodimers or EGFR heterodimers form. HER2 forms heterodimers with the EGFR, HER3, and HER4. The EGFR, HER2, and HER3 are overexpressed in lung cancer patient tumors, and monoclonal antibodies (mAbs), such as Herceptin against HER2, are used to treat breast cancer patients. Patients with EGFR mutations are treated with tyrosine kinase inhibitors, such as gefitinib or osimertinib. Peptide GPCRs, such as NTSR1, are present in many cancers, and neurotensin (NTS) stimulates the growth of cancer cells. Lung cancer proliferation is impaired by SR48692, an NTSR1 antagonist. SR48692 is synergistic with gefitinib at inhibiting lung cancer growth. Adding NTS to lung cancer cells increases the shedding of TGFα, which activates the EGFR, or neuregulin-1, which activates HER3. The transactivation process is impaired by SRC, matrix metalloprotease, and reactive oxygen species inhibitors. While the transactivation process is complicated, it is fast and occurs within minutes after adding NTS to cancer cells. This review emphasizes the use of tyrosine kinase inhibitors and SR48692 to impair transactivation and cancer growth.

FHL1 as a novel prognostic biomarker and correlation with immune infiltration levels in lung adenocarcinoma

Aim: We aimed to examine the effect of FHL1 in the diagnosis and prognosis of non-small-cell lung cancer and its relationship with tumor-infiltrating immune cells. Methods: FHL1 expression status and influence on clinical characteristics, diagnosis and prognosis in non-small-cell lung cancer were assessed. Interaction networks of FHL1 were revealed, and a correlation analysis between FHL1 expression and tumor immunity was performed. Results: FHL1 expression was significantly lower in tumors, and downregulated FHL1 predicted a worse prognosis for lung adenocarcinoma. FHL1 expression was correlated with tumor-infiltrating immune cells, immune checkpoints and chemokine levels. Conclusion: FHL1 is a powerful biomarker to evaluate the diagnosis and prognosis and immune infiltration level of lung adenocarcinoma.