The roles of risk model based on the 3-XRCC genes in lung adenocarcinoma progression

Role of rs873601 Polymorphisms in Prognosis of Lung Cancer Patients Treated with Platinum-Based Chemotherapy

BACKGROUND

Lung cancer is still the most lethal malignancy in the world, according to the report of Cancer Statistics in 2021. Platinum-based chemotherapy combined with immunotherapy is the first-line treatment in lung cancer patients. However, the 5-year survival rate is always affected by the adverse reactions and drug resistance caused by platinum-based chemotherapy. DNA damage and repair system is one of the important mechanisms that can affect the response to chemotherapy and clinical outcomes in lung cancer patients.

OBJECTIVE

The objective of this study is to find the relationship between the polymorphisms of DNA repair genes with the prognosis of platinum-based chemotherapy in lung cancer patients.

PATIENTS AND METHODS

We performed genotyping in 17 single nucleotide polymorphisms (SNPs) of Excision Repair Cross-Complementation group (ERCC) genes and X-ray Repair Cross-Complementing (XRCC) genes of 345 lung cancer patients via Sequenom MassARRAY. We used Cox proportional hazard models, state, and plink to analyze the associations between SNPs and the prognosis of lung cancer patients.

RESULTS

We found that the ERCC5 rs873601 was associated with the overall survival time in lung cancer patients treated with platinum-based chemotherapy (p = 0.031). There were some polymorphisms that were related to the prognosis in specific subgroups of lung cancer. Rs873601 showed a great influence on the prognosis of patients more than 55 years, Small Cell Lung Cancer (SCLC), and smoking patients. Rs2444933 was associated with prognosis in age less than 55 years, SCLC, metastasis, and stage III/IV/ED patients. Rs3740051 played an important role in the prognosis of SCLC and metastasis patients. Rs1869641 was involved in the prognosis of SCLC patients. Rs1051685 was related to the prognosis in non-metastasis patients.

CONCLUSION

The ERCC5 rs873601 (G>A) was a valuable biomarker for predicting the prognosis in lung cancer patients treated with platinum-based chemotherapy.

Construction and validation of an efferocytosis-related prognostic signature in lung adenocarcinoma

BACKGROUND

Accumulating evidence highlights the potential significance of efferocytosis in tumor progression. This study is directed towards the construction of a prognostic risk model for lung adenocarcinoma (LUAD), grounded on efferocytosis-related genes (ERGs).

METHODS

Employing LASSO-COX regression analysis, a risk-prognostic model was formulated, centered on seven ERGs. Concurrently, a nomogram was established that incorporated patient clinical features and risk scores. The predictive accuracy of the risk model and the nomogram was substantiated via external validation sets. The landscapes of immune infiltration and genetic mutation were evaluated for high- and low-risk groups, with the expression of seven key genes validated through RT-PCR.

RESULTS

Our findings reveal that the high-risk group displayed considerably inferior survival outcomes in comparison to the low-risk group. A diminished abundance of immune cell infiltrates and a higher prevalence of gene mutations characterized the high-risk group. Genes with high expression were markedly enriched in pathways related to cell proliferation. The superior predictive performance of the risk model and nomogram was adequately substantiated by the external validation sets (GSE31210, GSE30219, and GSE50081). In addition, we discerned several potential therapeutic drugs demonstrating different sensitivities across patient risk groups. The differential expression of seven central genes was confirmed in A549, H1299, and BEAS-2B cell lines.

CONCLUSION

The constructed risk model and nomogram display high accuracy in predicting the survival and immune landscape of LUAD patients, thus providing invaluable prognostic tools in clinical scenarios.

A novel risk model of three gefitinib-related genes FBP1, SBK1 and AURKA is related to the immune microenvironment and is predicting prognosis of lung adenocarcinoma patients

PURPOSE

Gefitinib, an anticancer drug, has been reported to potentially improve the prognosis of patients with lung adenocarcinoma (LUAD). This study aims to investigate the roles and mechanisms of Gefitinib.

METHODS

The effects of Gefitinib on the growth and migration of LUAD cells were assessed using various methods, including CCK-8, flow cytometry, wound healing, and Transwell assays. To analyze the function and mechanisms of the differentially expressed Gefitinib target genes (GTGs), data from the TCGA database were utilized. Kaplan-Meier survival and ROC analysis identified prognostic-related GTGs and constructed a prognostic nomogram in LUAD. Consensus clustering, COX analysis and survival analysis evaluated the relationship between GTGs and the prognosis of LUAD patients. The mechanisms of the risk model involved LUAD progression, and the relationship between the risk model and immune microenvironment were investigated.

RESULTS

Gefitinib could inhibit proliferation, migration and invasion and promote cell apoptosis. 84 DEGTGs were involved in RAS, MAPK, ERBB pathways. The DEGTGs (FBP1, SBK1, and AURKA) were the independent risk factors for dismal prognosis of LUAD patients and were used to establish risk model and nomogram. Gefitinib could promote the expression of FBP1 and inhibit the expression of SBK1 and AURKA. High-risk LUAD patients had the dismal prognosis, and the high-risk score group was significantly associated with the immune microenvironment.

CONCLUSION

FBP1, SBK1, and AURKA are prognostic risk factors, and the risk model and nomogram of FBP1, SBK1 and AURKA are associated with dismal prognosis and immune cell infiltration, and have huge prospects for application in evaluating the prognosis in LUAD.

A Risk Model Based on Sorafenib-Response Target Genes Predicts the Prognosis of Patients with HCC

Sorafenib is used to treat digestive system tumors in patients who do not respond to or cannot tolerate surgery. However, the roles and inhibitory mechanisms of sorafenib against hepatocellular carcinoma (HCC) are unclear. Differentially expressed genes in tissues from responders and nonresponders to sorafenib were investigated using the HCC GSE109211 data set. Biological functions and mechanisms were studied using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The expression levels of differential expressed target genes were identified in HCC tissues, using The Cancer Genome Atlas database, and their prognostic and diagnostic values were explored using survival and receiver operating characteristic curve analysis. A nomogram and risk model of sorafenib-response target genes enabled the evaluation of the prognosis of patients with HCC. The relationship between risk scores and levels of infiltrating immune cells was visualized via correlation analysis. We identified 1620 sorafenib-response target genes involved in the PPAR signaling pathway, antigen processing and presentation, and ferroptosis. SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 were independent risk factors for a poor prognosis for patients with HCC and had diagnostic value. A risk model based on SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 expression showed that patients with HCC in the high-risk group had a worse prognosis. Consensus-clustering analysis (performed with K set to 2) distinguished two clusters (the cluster 1 and cluster 2 groups). Patients in cluster 1 survived significantly longer than those in cluster 2. The risk score correlated with the levels of T cells, cytotoxic lymphocytes, CD8+ T cells, macrophages, memory B cells, follicular helper T cells, and other immune cells. The high risk based on the sorafenib-response targets SLC41A3, SEC61A1, LRP4, PPM1G, and HSP90AA1 represented the poor prognosis for patients with HCC and significantly correlated with the levels of immune infiltrating cells in HCC.

The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients

Background

Oxidative stress plays a role in carcinogenesis. This study explores the roles of oxidative stress-related genes (OSRGs) in lung adenocarcinoma (LAC). Besides, we construct a risk score model of OSRGs that evaluates the prognosis of LAC patients.

Methods

OSRGs were downloaded from the Gene Set Enrichment Analysis (GSEA) website. The expression levels of OSRGs were confirmed in LAC tissues of the TCGA database. GO and KEGG analyses were used to evaluate the roles and mechanisms of oxidative stress-related differentially expressed genes (DEGs). Survival, ROC, Cox analysis, and AIC method were used to screen the prognostic DEGs in LAC patients. Subsequently, we constructed a risk score model of OSRGs and a nomogram. Further, this work investigated the values of the risk score model in LAC progression and the relationship between the risk score model and immune infiltration.

Results

We discovered 163 oxidative stress-related DEGs in LAC, involving cellular response to oxidative stress and reactive oxygen species. Besides, the areas under the curve of CCNA2, CDC25C, ERO1A, CDK1, PLK1, ITGB4, and GJB2 were 0.970, 0.984, 0.984, 0.945, 0.984, 0.771, and 0.959, respectively. This indicates that these OSRGs have diagnosis values of LAC and are significantly related to the overall survival of LAC patients. ERO1A, CDC25C, and ITGB4 overexpressions were independent risk factors for the poor prognosis of LAC patients and were associated with risk scores in the risk model. High-risk score levels affected the poor prognosis of LAC patients. Notably, a high-risk score may be implicated in LAC progression via cell cycle, DNA replication, mismatch repair, and other mechanisms. Further, ERO1A, CDC25C, and ITGB4 expression levels were related to the immune infiltrating cells of LAC, including mast cells, NK cells, and CD8 T cells.

Conclusion

In summary, ERO1A, CDC25C, and ITGB4 of OSRGs are associated with poor prognosis of LAC patients. We confirmed that the risk model based on the ERO1A, CDC25C, and ITGB4 is expected to assess the prognosis of LAC patients.