To analyze the prognostic factors and survival rate of lung cancer patients with obstructive sleep apnea (OSA) by nomogram. The nomogram was established by a development cohort (n = 90), and the validation cohort included 38 patients. Factors in the nomogram were identified by Cox hazard analysis. We tested the accuracy of the nomograms by discrimination and calibration, and plotted decision curves to assess the benefits of nomogram-assisted decisions. There were significant difference in sex, apnea hypopnea index (AHI), Tumor Node Metastasis (TNM), coronary heart disease, lowest arterial oxygen saturation [LSpO2 (%)], oxygen below 90% of the time [T90% (min)], the percentage of the total recorded time spend below 90% oxygen saturation (TS90%) and oxygen desaturation index (ODI4) between lung cancer subgroup and lung cancer with OSA subgroup (P < 0.05). Lung cancer patients with OSA age, AHI, TNM, cancer types, BMI and ODI4 were independent prognostic factor. Based on these six factors, a nomogram model was established. The c-index of internal verification was 0.802 (95% CI 0.767–0.885). The ROC curve analysis for the nomogram show 1-year survival (AUC = 0.827), 3-year survival (AUC = 0.867), 5-year survival (AUC = 0.801) in the development cohort were good accuracy. The calibration curve shows that this prediction model is in good agreement. Decision curve analysis (DCA) suggests that the net benefit of decision-making with this nomogram is higher, especially in the probability interval of <20% threshold. The nomogram can predict the prognosis of patients and guide individualized treatment.

Alternative RNA splicing is an essential mechanism linking genetic variation to human diseases. While the signals from genome-wide association studies(GWAS) have been linked to expression quantitative trait loci(eQTLs) in previous studies,further work is needed to better elucidate the relationship to other genetic regulatory mechanisms,such as splicing QTLs(sQTLs). Here,we performed a genome-wide sQTL analysis to identify variants that might affect RNA splicing in 1,010 non-small cell lung cancer(NSCLC) samples from The Cancer Genome Atlas(TCGA).The identified sQTLs were largely independent of eQTLs and were predominantly enriched in exonic regions,genetic regulatory elements,RNA binding protein(RBP) binding sites, and known NSCLC risk loci. Additionally, target genes affected by sQTLs(sGenes) were involved in multiple processes in cancer,including cell growth,apoptosis,metabolism,immune infiltration,and drug responses,and sGenes were frequently altered genetically in NSCLC. Systematic screening of sQTLs associated with NSCLC risk using GWAS data from 15,474 cases and 12,375 controls identified an sQTL variant rs156697-G allele that was significantly associated with an increased risk of NSCLC. The association between the rs156697-G variant and NSCLC risk was further validated in two additional large population cohorts. The risk variant promoted inclusion of GSTO2 alternative exon 5 and led to higher expression of the GSTO2 full-length isoform(GSTO2-V1) and lower expression of the truncated GSTO2 isoform(GSTO2-V2),which was induced by RBP quaking(QKI). Mechanistically,compared with GSTO2-V1,GSTO2-V2 inhibited NSCLC cells proliferation by increasing S-glutathionylation of AKT1 and thereby functionally blocking AKT1 phosphorylation and activation. Overall,this study provides a comprehensive view of splicing variants linked to NSCLC risk and provides a set of genetic targets with therapeutic potential.

<p>Supplementary Data</p>

<div>Abstract<p>Alternative RNA splicing is an essential mechanism linking genetic variation to human diseases. While the signals from genome-wide association studies (GWAS) have been linked to expression quantitative trait loci (eQTL) in previous studies, further work is needed to better elucidate the relationship to other genetic regulatory mechanisms, such as splicing QTLs (sQTL). Here, we performed a genome-wide sQTL analysis to identify variants that might affect RNA splicing in 1,010 non–small cell lung cancer (NSCLC) samples from The Cancer Genome Atlas. The identified sQTLs were largely independent of eQTLs and were predominantly enriched in exonic regions, genetic regulatory elements, RNA-binding protein (RBP) binding sites, and known NSCLC risk loci. In addition, target genes affected by sQTLs (sGenes) were involved in multiple processes in cancer, including cell growth, apoptosis, metabolism, immune infiltration, and drug responses, and sGenes were frequently altered genetically in NSCLC. Systematic screening of sQTLs associated with NSCLC risk using GWAS data from 15,474 cases and 12,375 controls identified an sQTL variant rs156697-G allele that was significantly associated with an increased risk of NSCLC. The association between the rs156697-G variant and NSCLC risk was further validated in two additional large population cohorts. The risk variant promoted inclusion of <i>GSTO2</i> alternative exon 5 and led to higher expression of the <i>GSTO2</i> full-length isoform (<i>GSTO2</i>-V1) and lower expression of the truncated <i>GSTO2</i> isoform (<i>GSTO2</i>-V2), which was induced by RBP quaking (QKI). Mechanistically, compared with <i>GSTO2</i>-V1, <i>GSTO2</i>-V2 inhibited NSCLC cells proliferation by increasing S-glutathionylation of AKT1 and thereby functionally blocking AKT1 phosphorylation and activation. Overall, this study provides a comprehensive view of splicing variants linked to NSCLC risk and provides a set of genetic targets with therapeutic potential.</p>Significance:<p>Analysis of sQTL reveals the role of genetically driven mRNA splicing alterations in NSCLC risk and elucidates that rs156697 variant impacts risk by altering <i>GSTO2</i> splicing.</p></div>

<div>Abstract<p>Alternative RNA splicing is an essential mechanism linking genetic variation to human diseases. While the signals from genome-wide association studies (GWAS) have been linked to expression quantitative trait loci (eQTL) in previous studies, further work is needed to better elucidate the relationship to other genetic regulatory mechanisms, such as splicing QTLs (sQTL). Here, we performed a genome-wide sQTL analysis to identify variants that might affect RNA splicing in 1,010 non–small cell lung cancer (NSCLC) samples from The Cancer Genome Atlas. The identified sQTLs were largely independent of eQTLs and were predominantly enriched in exonic regions, genetic regulatory elements, RNA-binding protein (RBP) binding sites, and known NSCLC risk loci. In addition, target genes affected by sQTLs (sGenes) were involved in multiple processes in cancer, including cell growth, apoptosis, metabolism, immune infiltration, and drug responses, and sGenes were frequently altered genetically in NSCLC. Systematic screening of sQTLs associated with NSCLC risk using GWAS data from 15,474 cases and 12,375 controls identified an sQTL variant rs156697-G allele that was significantly associated with an increased risk of NSCLC. The association between the rs156697-G variant and NSCLC risk was further validated in two additional large population cohorts. The risk variant promoted inclusion of <i>GSTO2</i> alternative exon 5 and led to higher expression of the <i>GSTO2</i> full-length isoform (<i>GSTO2</i>-V1) and lower expression of the truncated <i>GSTO2</i> isoform (<i>GSTO2</i>-V2), which was induced by RBP quaking (QKI). Mechanistically, compared with <i>GSTO2</i>-V1, <i>GSTO2</i>-V2 inhibited NSCLC cells proliferation by increasing S-glutathionylation of AKT1 and thereby functionally blocking AKT1 phosphorylation and activation. Overall, this study provides a comprehensive view of splicing variants linked to NSCLC risk and provides a set of genetic targets with therapeutic potential.</p>Significance:<p>Analysis of sQTL reveals the role of genetically driven mRNA splicing alterations in NSCLC risk and elucidates that rs156697 variant impacts risk by altering <i>GSTO2</i> splicing.</p></div>