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

Development and validation of a nomogram model based on blood-based genomic mutation signature for predicting the risk of brain metastases in non-small cell lung cancer

PURPOSE

Available research indicates that the mammalian target of rapamycin complex 1 (mTORC1) signaling pathway is significantly correlated with lung cancer brain metastasis (BM). This study established a clinical predictive model for assessing the risk of BM based on the mTORC1-related single nucleotide polymorphisms (SNPs).

METHODS

In this single-center retrospective study, 395 patients with non-small cell lung cancer were included. Clinical, pathological, imaging, and mTORC1-related single nucleotide polymorphism data were collected. Lasso regression was used to identify variables related to the risk of BM in lung cancer, and a nomogram was constructed. Internal validation was performed using 1,000 bootstrap samples. We plotted the receiver operating characteristic (ROC) curve and calculated the area under the curve (AUC). The calibration of the model was assessed using calibration curves and the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA) was plotted to evaluate the net clinical benefit.

RESULTS

The nomogram's predictive factors included lung cancer histology, clinical N stage, CEA, neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), RPTOR: rs1062935, and RPTOR: rs3751934. The AUC of the model in the training set and internal validation were 0.849 and 0.801, respectively. The calibration curves and Hosmer-Lemeshow test both indicated a good fit.

CONCLUSION

The nomogram has practicality and efficacy in predicting the high risk of BM in lung cancer patients, confirming that single nucleotide polymorphisms in the mTORC1 pathway genes may be good predictors in clinical prediction models.

Hyper-methylation and DNMT3A mediated LTC4S downregulation promoted lung adenocarcinoma tumorigenesis via mTORC1 signaling pathway

Background

Lung adenocarcinoma is a malignancy characterized by high mortality rates and unfavorable prognosis. However, the role of Leukotriene C4 Synthase (LTC4S) in lung cancer remains uninvestigated.

Methods

The expression and prognostic value of LTC4S in LUAD were analyzed using the GEPIA online database. Subsequently, the function of LTC4S in lung cancer cells was examined through gain-of function experiments, using assays to evaluate tumor malignant behavior. Subcutaneous xenograft experiments in vivo was used for investigating the functions of LTC4S. Then, tumor hallmark pathways were analyzed by GSEA. Western blot assay was used to validate the impact of LTC4S on mTORC1 pathway. Finally, the correlation of mRNA and methylation of LTC4S were analyzed by cBioPortal. qRT-PCR, ChIP-qPCR and ChIP-Atlas were used to verify the regulation factors of LTC4S low expression in LUAD cells.

Results

LTC4S presented significant decreased expression and favorable prognostic significance in LUAD. LTC4S was correlated with clinical stages in LUAD, which showed decreased expression gradually and significantly along with TNM stages. LTC4S-co-expressed genes were closely related to Ras signaling pathway, and MAPK signaling pathway. Overexpression of LTC4S inhibited cancer malignant phenotype and tumor growth in vitro and vivo. GSEA analysis and Western blot assay suggested low expression of LTC4S activated mTORC1 signaling pathway in LUAD. Moreover, the DNA methylation level of LTC4S in LUAD tissue was markedly elevated compared to normal tissue. The hypermethylation of the LTC4S promoter by DNMT3A leads to the decreased expression of LTC4S in LUAD.

Conclusions

In conclusion, low expression of LTC4S serves as an unfavorable prognostic marker and the critical function of LTC4S in controlling the progression of LUAD. This highlights the promise for exploring the clinical benefits of manipulating LTC4S in LUAD targeted therapies.

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.