Prognostic factors for survival in a Chinese population presenting with advanced non-small cell lung cancer with an emphasis on smoking status: A regional, single-institution, retrospective analysis of 4552 patients

Clinical characteristics and prognostic analysis of SMARCA4-deficient non-small cell lung cancer

PURPOSE

To improve the understanding of special types of tumors, we summarized and analyzed the clinicopathological features and prognostic factors of SMARCA4-deficient non-small cell lung cancer (SMARCA4-dNSCLC).

METHODS

We selected 105 patients with SMARCA4-dNSCLC and 221 patients with SMARCA4-intact non-small cell lung cancer (SMARCA4-iNSCLC) by performing immunohistochemical analysis of 1520 NSCLC samples, and we assessed the patients' clinicopathological features and survival state.

RESULTS

(1) SMARCA4-dNSCLC was significantly associated with older age, male sex, smoking history, larger invasive tumor size, higher tumor proliferation index (Ki-67), more adrenal metastases, more lymph node metastases, and few EGFR mutations (p < 0.05). The tumors were mostly negative for thyroid transcription factor-1 (TTF-1), CD34, and p40 and positive for cytokeratin 7 (CK7) in immunohistochemistry (IHC). Nineteen SMARCA4-dNSCLC patients mostly had TP53, SMARCA4, and LRP1B mutations, and 48% of them had SMARCA4 frameshift mutations. SMARCA4-dNSCLC patients have a worse prognosis than SMARCA4-iNSCLC patients (HR: 0.27; 95% CI: 0.17-0.45). The overall survival (OS) of patients with stage III SMARCA4-dNSCLC was worse than that of patients with SMARCA4-iNSCLC, and the OS of stage IV SMARCA4-dNSCLC patients was also worse than that of SMARCA4-iNSCLC patients (p < 0.01). (2) Multivariate regression analysis showed that sex (HR: 4.12; 95% CI: 1.03-16.39) and smoking history (HR: 2.29; 95% CI: 1.04-5.02) had significant effects on the survival time of SMARCA4-dNSCLC patients. In SMARCA4-dNSCLC patients without distant metastases (stage I-III), patients with stage N2 or N3 lymph node metastases (HR: 6.35; 95% CI: 1.07-37.47) had a poor prognosis. Among patients with SMARCA4-dNSCLC who were treated and had distant metastases (stage IV), male patients and patients treated with immunotherapy combined with chemotherapy showed a longer median overall survival (mOS).

CONCLUSION

SMARCA4-dNSCLC has unique clinicopathological features and a shorter survival prognosis than SMARCA4-iNSCLC. The efficacy of immunotherapy combined with chemotherapy needs to be observed for longer periods.

LncRNA HCG11 Suppresses Cell Proliferation and Promotes Apoptosis via Sponging miR-224-3p in Non-Small-Cell Lung Cancer Cells

INTRODUCTION

Studies have found that Lnc-HCG11 is an important regulator of cancer. However, the function of Lnc-HCG11 in NSCLC is not known. Therefore, this experimental design was based on Lnc-HCG11 to explore the pathogenesis of NSCLC.

METHODS

RT-qPCR was used to detect the expression of Lnc-HCG11 and miR-224-3p in NSCLC. The effects of Lnc-HCG11 and miR-224-3p on proliferation and apoptosis of NSCLC cells were detected by CCK-8 assay, Edu assay and Annexin V-FITC/PI assay. Target gene prediction and screening, luciferase reporter assays were used to verify downstream target genes for lnc-HCG11 and miR-224-3p. Western blotting was used to detect the protein expression of caspase-3. The tumor changes in mice were detected by in vivo.

RESULTS

Lnc-HCG11 was significantly reduced in NSCLC. Lnc-HCG11 significantly inhibited cell proliferation of NSCLC cells and induced apoptosis. miR-224-3p was significantly elevated in the NSCLC cell line. Moreover, miR-224-3p significantly increased cell proliferation and inhibited apoptosis of NSCLC cells. Furthermore, Lnc-HCG11 was negatively correlated with miR-224-3p expression. Lnc-HCG11 over-expression was up-regulated the expression levels of c-caspase-3 and caspase-3. Finally, the results of in vivo animal models confirmed that Lnc-HCG11 inhibited tumor growth by modulating the miR-224-3p/c-caspase-3 axis.

CONCLUSION

Lnc-HCG11 could inhibit the progression of NSCLC by modulating the miR-224-3p/caspase-3 axis, and Lnc-HCG11 may be a potential therapeutic target for NSCLC.

Potentially functional genetic variants in PLIN2, SULT2A1 and UGT1A9 genes of the ketone pathway and survival of nonsmall cell lung cancer

The ketone metabolism pathway is a principle procedure in physiological homeostasis and induces cancer cells to switch between glycolysis and oxidative phosphorylation for energy production. We conducted a two-phase analysis for associations between genetic variants in the ketone metabolism pathway genes and survival of nonsmall cell lung cancer (NSCLC) by analyzing genotyping data from two published genome-wide association studies (GWASs). In the discovery, we used a genotyping dataset from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial in the multivariable Cox proportional hazards regression analysis. We used Bayesian false discovery probability (≤0.80) for multiple testing correction to evaluate associations between 25,819 (2,176 genotyped and 23,643 imputed) single-nucleotide polymorphisms (SNPs) in 162 genes and survival of 1,185 NSCLC patients. Subsequently, we validated the identified significant SNPs with an additional 984 NSCLC patients from the Harvard Lung Cancer Susceptibility GWAS study. Finally, we found that three independent and potentially functional SNPs in three different genes (i.e., PLIN2 rs7867814 G>A, SULT2A1 rs2547235 C>T and UGT1A9 rs2011404 C>T) were independently associated with risk of death from NSCLC, with a combined hazards ratio of 1.22 [95% confidence interval = 1.09-1.36 and p = 0.0003], 0.82 (0.74-0.91 and p = 0.0002) and 1.21 (1.10-1.33 and p = 0.0001), respectively. Additional expression quantitative trait loci analysis found that the survival-associated PLIN2 rs7867814 GA + AA genotypes, but not the genotypes of other two SNPs, were significantly associated with increased mRNA expression levels (p = 0.005). These results indicated that PLIN2 variants may be potential predictors of NSCLC survival through regulating the PLIN2 expression.

γ -H2AX: A Novel Prognostic Marker in a Prognosis Prediction Model of Patients with Early Operable Non-Small Cell Lung Cancer

Cancer is a leading cause of death worldwide and the prognostic evaluation of cancer patients is of great importance in medical care. The use of artificial neural networks in prediction problems is well established in human medical literature. The aim of the current study was to assess the prognostic value of a series of clinical and molecular variables with the addition of γ -H2AX-a new DNA damage response marker-for the prediction of prognosis in patients with early operable non-small cell lung cancer by comparing the γ -H2AX-based artificial network prediction model with the corresponding LR one. Two prognostic models of 96 patients with 27 input variables were constructed by using the parameter-increasing method in order to compare the predictive accuracy of neural network and logistic regression models. The quality of the models was evaluated by an independent validation data set of 11 patients. Neural networks outperformed logistic regression in predicting the patient's outcome according to the experimental results. To assess the importance of the two factors p53 and γ -H2AX, models without these two variables were also constructed. JR and accuracy of these models were lower than those of the models using all input variables, suggesting that these biological markers are very important for optimal performance of the models. This study indicates that neural networks may represent a potentially more useful decision support tool than conventional statistical methods for predicting the outcome of patients with non-small cell lung cancer and that some molecular markers, such as γ -H2AX, enhance their predictive ability.