scholarly journals Identification and Prognostic Value Exploration of Radiotherapy Sensitivity-Associated Genes in Non-Small-Cell Lung Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Qing Ma ◽  
Kai Geng ◽  
Ping Xiao ◽  
Lili Zeng
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Small Cell ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Nsclc Patients

Background. Non-small-cell lung cancer (NSCLC) is a prevalent malignancy with high mortality and poor prognosis. The radiotherapy is one of the most common treatments of NSCLC, and the radiotherapy sensitivity of patients could affect the individual prognosis of NSCLC. However, the prognostic signatures related to radiotherapy response still remain limited. Here, we explored the radiosensitivity-associated genes and constructed the prognostically predictive model of NSCLC cases. Methods. The NSCLC samples with radiotherapy records were obtained from The Cancer Genome Atlas database, and the mRNA expression profiles of NSCLC patients from the GSE30219 and GSE31210 datasets were obtained from the Gene Expression Omnibus database. The Weighted Gene Coexpression Network Analysis (WGCNA), univariate, least absolute shrinkage and selection operator (LASSO), multivariate Cox regression analysis, and nomogram were conducted to identify and validate the radiotherapy sensitivity-related signature. Results. WGCNA revealed that 365 genes were significantly correlated with radiotherapy response. LASSO Cox regression analysis identified 8 genes, including FOLR3, SLC6A11, ALPP, IGFN1, KCNJ12, RPS4XP22, HIST1H2BH, and BLACAT1. The overall survival (OS) of the low-risk group was better than that of the high-risk group separated by the Risk Score based on these 8 genes for the NSCLC patients. Furthermore, the immune infiltration analysis showed that monocytes and activated memory CD4 T cells had different relative proportions in the low-risk group compared with the high-risk group. The Risk Score was correlated with immune checkpoints, including CTLA4, PDL1, LAG3, and TIGIT. Conclusion. We identified 365 genes potentially correlated with the radiotherapy response of NSCLC patients. The Risk Score model based on the identified 8 genes can predict the prognosis of NSCLC patients.

scholarly journals Prognostic characterization of immune molecular subtypes in non-small cell lung cancer to immunotherapy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chenlu Li ◽  
Jingjing Pan ◽  
Jing Luo ◽  
Xupeng Chen
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Risk Scores ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Nsclc Patients

Abstract Background Non-small cell lung cancer (NSCLC) was usually associated with poor prognosis and invalid therapeutical response to immunotherapy due to biological heterogeneity. It is urgent to screen reliable biomarkers, especially immunotherapy-associated biomarkers, that can predict outcomes of these patients. Methods Gene expression profiles of 1026 NSCLC patients were collected from The Cancer Genome Atlas (TCGA) datasets with their corresponding clinical and somatic mutation data. Based on immune infiltration scores, molecular clustering classification was performed to identify immune subtypes in NSCLC. After the functional enrichment analysis of subtypes, hub genes were further screened using univariate Cox, Lasso, and multivariate Cox regression analysis, and the risk score was defined to construct the prognostic model. Other microarray data and corresponding clinical information of 603 NSCLC patients from the GEO datasets were applied to conduct random forest models for the prognosis of NSCLC with 100 runs of cross-validation. Finally, external datasets with immunotherapy and chemotherapy were further applied to explore the significance of risk-scores in clinical immunotherapy response for NSCLC patients. Results Compared with Subtype-B, the Subtype-A, associated with better outcomes, was characterized by significantly higher stromal and immune scores, T lymphocytes infiltration scores and up-regulation of immunotherapy markers. In addition, we found and validated an eleven -gene signatures for better application of distinguishing high- and low-risk NSCLC patients and predict patients’ prognosis and therapeutical response to immunotherapy. Furthermore, combined with other clinical characteristics based on multivariate Cox regression analysis, we successfully constructed and validated a nomogram to effectively predict the survival rate of NSCLC patients. External immunotherapy and chemotherapy cohorts validated the patients with higher risk-scores exhibited significant therapeutic response and clinical benefits. Conclusion These results demonstrated the immunological and prognostic heterogeneity within NSCLC and provided a new clinical application in predicting the prognosis and benefits of immunotherapy for the disease.

scholarly journals A Risk Signature of Nine Autophagy-Related Genes Associated With Immune Microenvironment and Clinical Prognosis in Wilms Tumor

2021 ◽  
Author(s):  
Shaopei Ye ◽  
Wenbin Tang ◽  
Ke Huang
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Risk Score ◽  
Cox Regression ◽  
Wilms Tumor ◽  
Risk Group ◽  
High Risk Group ◽  
Differentially Expressed ◽  
Clinical Prognosis ◽  
Cox Regression Analysis

Abstract Background: Autophagy is a biological process to eliminate dysfunctional organelles, aggregates or even long-lived proteins. . Nevertheless, the potential function and prognostic values of autophagy in Wilms Tumor (WT) are complex and remain to be clarifed. Therefore, we proposed to systematically examine the roles of autophagy-associated genes (ARGs) in WT.Methods: Here, we obtained differentially expressed autophagy-related genes (ARGs) between healthy and Wilms tumor from Therapeutically Applicable Research To Generate Effective Treatments(TARGET) and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology. Then univariate COX regression analysis and multivariate COX regression analysis were performed to acquire nine autophagy genes related to WT patients’ survival. According to the risk score, the patients were divided into high-risk and low-risk groups. The Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis.Results: Eighteen DEARGs were identifed, and nine ARGs were fnally utilized to establish the FAGs based signature in the TCGA cohort. we found that patients in the high-risk group were associated with mutations in TP53. We further conducted CIBERSORT analysis, and found that the infiltration of Macrophage M1 was increased in the high-risk group. Finally, the expression levels of crucial ARGs were verifed by the experiment, which were consistent with our bioinformatics analysis.Conclusions: we emphasized the clinical significance of autophagy in WT, established a prediction system based on autophagy, and identified a promising therapeutic target of autophagy for WT.

scholarly journals Prognostic model of head and neck squamous cell carcinoma based on 12 ferroptosis-related genes

2021 ◽  
Author(s):  
Sijia Li ◽  
Hongyang Zhang ◽  
Wei Li
Keyword(s):  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Scores ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Cox Analysis

Abstract Background: The purpose of our study is establishing a model based on ferroptosis-related genes predicting the prognosis of patients with head and neck squamous cell carcinoma (HNSCC).Methods: In our study, transcriptome and clinical data of HNSCC patients were from The Cancer Genome Atlas, ferroptosis-related genes and pathways were from Ferroptosis Signatures Database. Differentially expressed genes (DEGs) were screened by comparing tumor and adjacent normal tissues. Functional enrichment analysis of DEGs, protein-protein interaction network and gene mutation examination were applied. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to identified DEGs. The model was constructed by multivariate Cox regression analysis and verified by Kaplan-Meier analysis. The relationship between risk scores and other clinical features was also analyzed. Univariate and multivariate Cox analysis was used to verified the independence of our model. The model was evaluated by receiver operating characteristic analysis and calculation of the area under the curve (AUC). A nomogram model based on risk score, age, gender and TNM stages was constructed.Results: We analyzed data including 500 tumor tissues and 44 adjacent normal tissues and 259 ferroptosis-related genes, then obtained 73 DEGs. Univariate Cox regression analysis screened out 16 genes related to overall survival, and LASSO analysis fingered out 12 of them with prognostic value. A risk score model based on these 12 genes was constructed by multivariate Cox regression analysis. According to the median risk score, patients were divided into high-risk group and low-risk group. The survival rate of high-risk group was significantly lower than that of low-risk group in Kaplan-Meier curve. Risk scores were related to T and grade. Univariate and multivariate Cox analysis showed our model was an independent prognostic factor. The AUC was 0.669. The nomogram showed high accuracy predicting the prognosis of HNSCC patients.Conclusion: Our model based on 12 ferroptosis-related genes performed excellently in predicting the prognosis of HNSCC patients. Ferroptosis-related genes may be promising biomarkers for HNSCC treatment and prognosis.

scholarly journals Serum miR-1228-3p and miR-181a-5p as Noninvasive Biomarkers for Non-Small Cell Lung Cancer Diagnosis and Prognosis

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Wei-Xiao Xue ◽  
Meng-Yu Zhang ◽  
Rui Li ◽  
Xiao Liu ◽  
Yun-Hong Yin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Roc Analysis ◽  
Cox Regression ◽  
Small Cell ◽  
Healthy Controls ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Diagnosis And Prognosis ◽  
Noninvasive Biomarkers ◽  
Nsclc Patients

Background. Lung cancer is the leading cause of cancer-related mortality worldwide, and non-small cell lung cancer (NSCLC) accounts for over 80% of all lung cancers. Serum microRNAs (miRNAs), due to their high stability, have the potential to become valuable noninvasive biomarkers. This present study was aimed to identify the serum miRNAs expression signatures for the diagnosis and prognosis of NSCLC using bioinformatics analysis. Methods. A total of 12 miRNAs profiling studies have been identified in Pubmed, Gene Expression Omnibus (GEO), and ArreyExpress databases. Differentially expressed miRNAs (DEmiRNAs) were analyzed according to GEO2R online tool and RRA method from R. Then, prediction of DEmiRNAs’ target genes from TargetScan, PicTar, miRDB, Tarbase, and miRanda database. Furthermore, we using reverse transcription– quantitative polymerase chain reaction (RT-qPCR) to evaluate the expression levels of DEmiRNAs in serum samples obtained from NSCLC patients and healthy controls. Subsequently, the clinical significance of the tested miRNAs was determined using receiver operating characteristic (ROC) analysis and Cox regression analysis. Results. A total of 27 DEmiRNAs were identified and 5 of them (miR-1228-3p, miR-1228-5p, miR-133a-3p, miR-1273f, miR-545-3p) were significantly up-regulated and 4 of them (miR-181a-5p, miR-266-5p, miR-361-5p, miR-130a-3p) were significantly down-regulated in NSCLC patients compared with healthy controls. RT-qPCR validated that miR-1228-3p (P =0.006) and miR-181a-5p (P =0.030) were significantly differentially expressed in the serum of NSCLC patients and healthy controls. ROC analysis on miR-1228-3p and miR-181a-5p revealed the area under the curve (AUC) of 0.685 (95% confidence interval [CI], 0.563–0.806; P =0.006) and 0.647 (95% CI, 0.506–0.758; P =0.049). ROC analysis on miR-1228-3p combined miR-181a-5p revealed the AUC of 0.711 (95% CI, 0.593–0.828; P =0.002). Multivariate Cox regression analysis demonstrated that the high serum miR-1228-3p level was an independent factor for the poor prognosis of NSCLC patients. Conclusions. Serum miR-1228-3p and miR-181a-5p are potential noninvasive biomarkers for the diagnosis and prognosis of NSCLC patients.

Correlation between anemia before treatment with survival in patients with advanced non-small cell lung cancer

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 18211-18211
Author(s):  
S. R. Bella ◽  
M. E. Richardet ◽  
P. Gomez Storniolo ◽  
P. Celiz ◽  
A. Lingua ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Cox Regression ◽  
Small Cell ◽  
Hemoglobin Level ◽  
Small Cell Lung ◽  
Cox Regression Analysis

18211 Background: Prognostic factors identified in advanced non small cell lung cancer are: age, gender, PS, h. SWOG univariable analysis in patients with chemotheraphy; confirmed these factors and show a relationship between the hemoglobin level and the overall survival; in addition the metastasic site number and cisplatin- based chemotheraphy (7). To analyse and compare the hemoglobin level before cisplatin- based chemotheraphy with survival in patients with advanced non- small cell lung cancer. Methods: Retrospective study conducted at the IONC of the 179 clinical record were analized, over a 5 year period. The collected data were: age, gender, PS, histologic type, stage, chemotheraphy cycles number, smooke history, number and metastasic site. We analyzed median and overal survival using Kaplan Meier, and the anemia as a prognostic implication factor with univariable and multivariable Cox regression analysis. Istologic type and TNM (1–6). Results: The mean age was 59 (40–79); 146 (81.5%) male and 33 (18.5%) women; histological types found were squamous cell carcinomas in 66 (37%), and adenocarcinoma in 113 (63%); stage IIIB in 61 (34%) and IV in 118 (66%). 147 (82%) were smokers and 32 (18%) were never smokers. All the patients had PS 0–1. Median overall survival time was 11.53 months and 13.88 months in the haemoglobin level < or > 11 gr/ 100 ml, respectively. (p=0.3). In univariable Cox regression analysis, smoking rates and chemotheraphy cycles number were predictors of survival (p=0.05 y p=0.018, respectively). Hemoglobine (p=0.55). In multivariable Cox regression analysis, only the number of cycles was predictor of survival (p=0.026). Hemoglobine (p=0.34). Conclusions: In our experience, a greater survival tendency was observed in patients with advanced non- small cell lung cancer who presented levels of Hemoglobine greater than 11 gr/dl, previous to cisplatin- based chemotherapy without statistical significance. [Table: see text]

scholarly journals Bioinformatic Analysis Revealing Mitotic Spindle Assembly regulated NDC80 and MAD2L1 as Prognostic Biomarkers in Non-Small Cell Lung Cancer Development

2020 ◽  
Author(s):  
Rong Wei ◽  
Ziyue Wang ◽  
Yaping Zhang ◽  
Bin Wang ◽  
Ningning Shen ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Regression Analysis ◽  
Cox Regression ◽  
Bioinformatic Analysis ◽  
Small Cell ◽  
Prognostic Indicators ◽  
Pathological Features ◽  
Small Cell Lung ◽  
Cox Regression Analysis ◽  
Key Genes

Abstract Background Lung cancer has been the leading cause of tumor related death, and 80%~85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease. Methods Firstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data. Results Three GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed. Conclusions Using bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.

scholarly journals A Nomogram with Lymph Node Status Predicts Survival and the Benefit of Postoperative Radiotherapy in IIIA-N2 Non-small Cell Lung Cancer Patients after Surgery

2020 ◽  
Author(s):  
Ye Chen ◽  
Lei Dong ◽  
Minjing Li ◽  
Fei He ◽  
ChenHui Qiu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
High Risk ◽  
Lymph Nodes ◽  
Survival Benefit ◽  
Risk Group ◽  
Postoperative Radiotherapy ◽  
High Risk Group ◽  
Small Cell ◽  
Small Cell Lung ◽  
Nsclc Patients

Abstract Objective: This study aimed at establishing a novel nomogram predicting overall survival and investigating the survival benefit of postoperative radiotherapy in IIIA-N2 Non-small cell lung cancer (NSCLC) patients after surgery.Methods: Data of IIIA-N2 NSCLC patients between 2004 and 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER). Patients were excluded if the information regarding follow-up time and clinicopathological features were incomplete. Through Univariate and multivariate analyses, independent prognostic factors were identified and integrated into the construction of nomogram. The survival benefit of PORT was investigated in model-defined low-risk, intermediate-risk, and high-risk subgroups, respectively.Results: In total, 4389 patients were finally included for analysis. Patients’ age, sex, T stage, differentiation grade, examined lymph nodes number (ELN), metastatic lymph nodes number (MLN), and metastatic lymph nodes ratio (LNR) were identified as independent prognostic factors and were integrated into the construction of nomogram. The C-index and calibration curves indicated that the predictive performance of the nomogram was satisfactory. Patients were then categorized into three prognostic groups with the increasing risk of all-cause of death. Only patients in high-risk group could benefit from PORT.Conclusion: In this large-cohort retrospective study, A survival-predicting nomogram and risk stratification model were established to estimate prognosis in IIIA-N2 NSCLC patients. PORT was recommended for those patients in high-risk group. This study may provide additional integration, introspection, and improvement for therapeutic decision-making.

scholarly journals The Baseline Serum Uric Acid as an Indicator of Chemotherapy-Related Adverse Reaction and Mortality in Aged Males with Stage IIIB or IV Non-Small Cell Lung Cancer

2021 ◽  
Author(s):  
Xiaoyan Chen ◽  
Lisha Hou ◽  
Jianqun Li ◽  
Yanjiao Shen ◽  
Fucha Tan ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bone Marrow ◽  
Uric Acid ◽  
Regression Analysis ◽  
Cox Regression ◽  
Small Cell ◽  
Bone Marrow Suppression ◽  
Stage Iiib ◽  
Small Cell Lung ◽  
Cox Regression Analysis

Abstract Objective: To evaluate the accuracy of baselineserum uric acid(BSUA) in estimating adverse effects (AE) and all-cause mortality (ACM) in older males with stage IIIB or IV non-small cell lung cancer (NSCLC) diagnosis.Study design:This is a single-center retrospective examination, conducted at the West China Hospital, Sichuan University in Chengdu, Sichuan Province, China, between the duration of January 2010 and December 2017.Primary outcome and measures:: All patients data was obtained based on medical reports and mortality information was gathered via telephone interviews. BUSA was assessed prior to chemotherapy. Additionally, the end points of this study included chemotherapy-mediated AE and ACM. Binarylogistic regression analysis was used to explore the correlation between BSUA and AE. Lastly, Cox regression analysis was utilized to examine theimpactof BSUA on ACM.Results: 317 male patients with NSCLC were eligible for this study. Within this population, 18.3% had stage IIIB and 81.7% had stage IV NSCLC. Moreover, 81.39% suffered from adenocarcinoma lung cancer (ACLC), whereas 18.61% suffered from squamous cell carcinoma lung cancer (SCCLC). As of March 1, 2019, 257 (81.07%) patients expired. Following the initial chemotherapeutic course, short-term AE like bone marrow suppression, all infection, liver dysfunction, and digestive reactions, wereobserved in 13.25%, 7.26%, 5.36%, and 4.1% of cases, respectively. Upon normalizing with confounding factors, the adjustedlogistic regression model demonstrated thatthe moderate BSUA was independently linked to a lower risk of bone marrow suppression (OR=0.407,95% CI:0.178-0.931; p=0.033).Moreover, based on the Cox regression analysis, moderate BSUAwas also independently correlated with a low mortality risk (HR=0.705,95% CI:0.518-0.959; p=0.026).Conclusion：In males patients withstage IIIB or IV NSCLC, BSUA is intimately linked to chemotherapy-driven AE and ACM.

scholarly journals The Baseline Serum Uric Acid as an Indicator of Chemotherapy-related Adverse Reaction and Mortality in Aged Males with Stage IIIB or IV Non-small Cell Lung Cancer

2021 ◽  
Author(s):  
Xiaoyan Chen ◽  
Lisha Hou ◽  
Jianqun Li ◽  
Yanjiao Shen ◽  
Birong Dong ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Bone Marrow ◽  
Regression Analysis ◽  
Cox Regression ◽  
Small Cell ◽  
Bone Marrow Suppression ◽  
Stage Iiib ◽  
Small Cell Lung ◽  
Baseline Serum ◽  
Cox Regression Analysis

Abstract Objective: To evaluate the accuracy of baseline serum uric acid (BSUA) in estimating adverse effects (AE) and all-cause mortality (ACM) in older males with stage IIIB or IV non-small cell lung cancer (NSCLC) diagnosis.Methods: All patients data was obtained based on medical reports and mortality information was gathered via telephone interviews. BUSA was assessed prior to chemotherapy. Additionally, the end points of this study included chemotherapy-mediated AE and ACM. Binary logistic regression analysis was used to explore the correlation between BSUA and AE. Lastly, Cox regression analysis was utilized to examine the impact of BSUA on ACM.Results: 317 male patients with NSCLC were eligible for this study. Within this population, 18.3% had stage IIIB and 81.7% had stage IV NSCLC. Moreover, 81.39% suffered from adenocarcinoma lung cancer (ACLC), whereas 18.61% suffered from squamous cell carcinoma lung cancer (SCCLC). As of March 1, 2019, 257 (81.07%) patients expired. Following the initial chemotherapeutic course, short-term AE like bone marrow suppression, all infection, liver dysfunction, and digestive reactions, were observed in 13.25%, 7.26%, 5.36%, and 4.1% of cases, respectively. Upon normalizing with confounding factors, the adjusted logistic regression model demonstrated that the moderate BSUA was independently linked to a lower risk of bone marrow suppression (OR=0.407,95% CI:0.178-0.931; p=0.033). Moreover, based on the Cox regression analysis, moderate BSUA was also independently correlated with a low mortality risk (HR=0.705, 95% CI:0.518-0.959; p=0.026).Conclusion：In males patients with stage IIIB or IV NSCLC, BSUA is intimately linked to chemotherapy-driven AE and ACM.

scholarly journals Systemic characterization of alternative splicing related to prognosis and immune infiltration in malignant mesothelioma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jinzhi Lai ◽  
Hainan Yang ◽  
Tianwen Xu
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Risk Score ◽  
Regulatory Network ◽  
Immune Cell ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Immune Cell Infiltration ◽  
Cox Regression Analysis

Abstract Background Malignant mesothelioma (MM) is a relatively rare and highly lethal tumor with few treatment options. Thus, it is important to identify prognostic markers that can help clinicians diagnose mesothelioma earlier and assess disease activity more accurately. Alternative splicing (AS) events have been recognized as critical signatures for tumor diagnosis and treatment in multiple cancers, including MM. Methods We systematically examined the AS events and clinical information of 83 MM samples from TCGA database. Univariate Cox regression analysis was used to identify AS events associated with overall survival. LASSO analyses followed by multivariate Cox regression analyses were conducted to construct the prognostic signatures and assess the accuracy of these prognostic signatures by receiver operating characteristic (ROC) curve and Kaplan–Meier survival analyses. The ImmuCellAI and ssGSEA algorithms were used to assess the degrees of immune cell infiltration in MM samples. The survival-related splicing regulatory network was established based on the correlation between survival-related AS events and splicing factors (SFs). Results A total of 3976 AS events associated with overall survival were identified by univariate Cox regression analysis, and ES events accounted for the greatest proportion. We constructed prognostic signatures based on survival-related AS events. The prognostic signatures proved to be an efficient predictor with an area under the curve (AUC) greater than 0.9. Additionally, the risk score based on 6 key AS events proved to be an independent prognostic factor, and a nomogram composed of 6 key AS events was established. We found that the risk score was significantly decreased in patients with the epithelioid subtype. In addition, unsupervised clustering clearly showed that the risk score was associated with immune cell infiltration. The abundances of cytotoxic T (Tc) cells, natural killer (NK) cells and T-helper 17 (Th17) cells were higher in the high-risk group, whereas the abundances of induced regulatory T (iTreg) cells were lower in the high-risk group. Finally, we identified 3 SFs (HSPB1, INTS1 and LUC7L2) that were significantly associated with MM patient survival and then constructed a regulatory network between the 3 SFs and survival-related AS to reveal potential regulatory mechanisms in MM. Conclusion Our study provided a prognostic signature based on 6 key events, representing a better effective tumor-specific diagnostic and prognostic marker than the TNM staging system. AS events that are correlated with the immune system may be potential therapeutic targets for MM.

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