Effects of single-nucleotide polymorphisms in the mTORC1 pathway on the risk of brain metastasis in patients with non-small cell lung cancer

RPTOR blockade suppresses brain metastases of NSCLC by interfering the ceramide metabolism via hijacking YY1 binding

BACKGROUND

Ceramide metabolism is crucial in the progress of brain metastasis (BM). However, it remains unexplored whether targeting ceramide metabolism may arrest BM.

METHODS

RNA sequencing was applied to screen different genes in primary and metastatic foci and whole-exome sequencing (WES) to seek crucial abnormal pathway in BM + and BM-patients. Cellular arrays were applied to analyze the permeability of blood-brain barrier (BBB) and the activation or inhibition of pathway. Database and Co-Immunoprecipitation (Co-IP) assay were adopted to verify the protein-protein interaction. Xenograft and zebrafish model were further employed to verify the cellular results.

RESULTS

RNA sequencing and WES reported the involvement of RPTOR and ceramide metabolism in BM progress. RPTOR was significantly upregulated in BM foci and increased the permeability of BBB, while RPTOR deficiency attenuated the cell invasiveness and protected extracellular matrix. Exogenous RPTOR boosted the SPHK2/S1P/STAT3 cascades by binding YY1, in which YY1 bound to the regions of SPHK2 promoter (at -353 ~ -365 nt), further promoting the expression of SPHK2. The latter was rescued by YY1 RNAi. Xenograft and zebrafish model showed that RPTOR blockade suppressed BM of non-small cell lung cancer (NSCLC) and impaired the SPHK2/S1P/STAT3 pathway.

CONCLUSION

RPTOR is a key driver gene in the brain metastasis of lung cancer, which signifies that RPTOR blockade may serve as a promising therapeutic candidate for clinical application.

Identification of RHEX as a novel biomarker related to progression and immunity of non-small cell lung carcinoma

Background

The therapeutic response and prognosis of patients with non-small cell lung carcinoma (NSCLC) are widely related to immunity. To improve the prognosis of patients and provide reliable information to guide appropriate personalized treatment strategies, it is necessary to identify reliable prognostic or predictive indicators closely related to tumor phenotype and immune traits in NSCLC.

Methods

Based on The Cancer Genome Atlas (TCGA)-NSCLC mRNA expression profile data, a novel approach combining differential gene expression analysis, single-sample gene set enrichment analysis (ssGSEA), and weighted gene co-expression network analysis (WGCNA) was used to screen hub genes. Subsequently, the regulator of hemoglobinization and erythroid cell expansion (RHEX) was identified as a key gene using the log-rank test and confirmed in the ArrayExpress database. The relationship between RHEX and clinicopathological parameters was analyzed using the Wilcoxon rank-sum test. More importantly, through gene set enrichment analysis (GSEA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithms, and with reference to the Tumor IMmune Estimation Resource (TIMER) database, we explored the relevant pathways of RHEX and its relationship with tumor-infiltrating immune cells (TICs). Finally, we depicted the association between RHEX and immunomodulators in the TCGA and a web portal TISIDB.

Results

The RHEX mRNA expression levels in tumor tissues were lower than those in normal tissues and declined with the progression of NSCLC. Meanwhile, RHEX overexpression was associated with high immune infiltration levels and a favorable clinical prognosis. RHEX may participate in tumor microenvironment (TME) regulation through multiple tumor-immune related pathways, especially the JAK-STAT signaling pathway. Furthermore, RHEX expression affected the infiltrating abundance of multiple TICs and positively correlated with most of the immunomodulators in NSCLC.

Conclusions

Our study is the first to propose that RHEX is an immune-related gene with prognostic value in NSCLC and reveals the underlying mechanism between RHEX and tumor-immune system interactions. These results ultimately provide guidance for prognosis and immunotherapy for NSCLC patients.

A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

Purpose

Lung adenocarcinoma is the most common pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis and precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice.

Methods

The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from the TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate the high and low risk groups and a ROC curve and nomogram to visualize the predictive ability of the current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA.

Results

A total of 1,703 autophagy-related lncRNAs were screened and five autophagy-related lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1, and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate (HR=1.075, 95% CI=1.046–1.104) and multivariate (HR=1.088, 95% CI=1.057−1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-years, and 5-years, was 0.735, 0.672, and 0.662, respectively, indicating a reliable model. Drug sensitivity analysis revealed low risk patients were more sensitive to Gemcitabine and Gefitinib, while high risk patients had a better response to Paclitaxel and Erlotinib. Moreover, the lncRNAs included in our signature were primarily enriched in the autophagy process, metabolism, p53 pathway, and JAK/STAT pathway. Finally, a multi-omics analysis of correlated genes showed CFLAR overexpressed in the tumor sample, while GAPDH and MLST8 had a slightly higher expression in the normal sample.

Conclusion

Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients’ prognosis and the related genes might be potential biomarkers and therapeutic targets.

High Expression of PAMR1 Predicts Favorable Prognosis and Inhibits Proliferation, Invasion, and Migration in Cervical Cancer

Peptidase domain containing associated with muscle regeneration 1 (PAMR1) is frequently lost in breast cancer samples and is considered as a tumor suppressor. The roles and mechanisms of PAMR1 in other types of cancers are still unclear. In our present study, we identified PAMR1 as an invasion-related regulator in cervical cancer. Public database and immunohistochemical (IHC) analysis showed that the expression level of PAMR1 in cervical cancer tissues was lower than that in normal cervix tissues and was negatively related to clinicopathologic features. The high expression of PAMR1 also predicted a better prognosis of cervical cancer patients. CCK8, Transwell, and wound-healing assays demonstrated that knockdown of PAMR1 facilitated the proliferation, migration, and invasion of cervical cancer cells. Additionally, gene set enrichment analysis (GSEA) showed a variety of cancer-related pathways potentially activated or suppressed by PAMR1. Moreover, we verified that PAMR1 inhibited MYC target and mTORC1 signaling pathways. In conclusion, our study revealed the suppressor role of PAMR1 in cervical cancer, providing a new insight into the molecular mechanism of cervical cancer progression.

Advances in Lung Cancer Driver Genes Associated With Brain Metastasis

Brain metastasis, one of the common complications of lung cancer, is an important cause of death in patients with advanced cancer, despite progress in treatment strategies. Lung cancers with positive driver genes have higher incidence and risk of brain metastases, suggesting that driver events associated with these genes might be biomarkers to detect and prevent disease progression. Common lung cancer driver genes mainly encode receptor tyrosine kinases (RTKs), which are important internal signal molecules that interact with external signals. RTKs and their downstream signal pathways are crucial for tumor cell survival, invasion, and colonization in the brain. In addition, new tumor driver genes, which also encode important molecules closely related to the RTK signaling pathway, have been found to be closely related to the brain metastases of lung cancer. In this article, we reviewed the relationship between lung cancer driver genes and brain metastasis, and summarized the mechanism of driver gene-associated pathways in brain metastasis. By understanding the molecular characteristics during brain metastasis, we can better stratify lung cancer patients and alert those at high risk of brain metastasis, which helps to promote individual therapy for lung cancer.