Abstract
BackgroundLung adenocarcinoma (LUAD) remains a crucial factor endangering human health. Gene-based clinical predictions could be of great help for cancer intervention strategies. Here, we tried to build a gene-based survival score (SS) for LUAD via analyzing multiple transcriptional datasets.MethodsWe first acquired differentially expressed genes between tumors and normal tissues from intersections of four LUAD datasets. Next, survival-related genes were preliminarily unscrambled by univariate Cox regression and further filtrated by LASSO regression. Then, we applied PCA to establish a comprehensive SS based on survival-related genes. Subsequently, we applied four independent LUAD datasets to evaluate prognostic prediction of SS. Moreover, we explored associations between SS and clinicopathological features. Furthermore, we assessed independent predictive value of SS by multivariate Cox analysis and then built prognostic models based on clinical stage and SS. Finally, we performed pathway enrichments analysis and investigated immune checkpoints expression underlying SS in four datasets.ResultsWe established a 13 gene-based SS, which could precisely predict OS and PFS of LUAD. Close relations were elicited between SS and canonical malignant indictors. Furthermore, SS could serve as an independent risk factor for OS and PFS. Besides, the predictive efficacies of prognostic models were also reasonable (C-indexes: OS, 0.7; PFS, 0.7). Finally, we demonstrated enhanced cell proliferation and immune escape might account for high clinical risk of SS.ConclusionsWe built a 13 gene-based SS for prognostic prediction of LUAD, which exhibited wide applicability and could contribute to LUAD management.
Highlights
Lung adenocarcinoma (LUAD) remains a crucial factor endangering human health
Identifying 13 core genes to establish survival score (SS) for LUAD Genes closely related to tumor prognosis are likely to play key roles in tumor progression
We obtained the intersection of differentially expressed genes (DEGs) from four LUAD transcriptomic datasets (GSE10072, GSE32863, GSE43458 and The Cancer Genome Atlas (TCGA)-LUAD), and we acquired 52 upregulated DEGs and 180 downregulated DEGs (Fig. 1a) (Detailed information about acquiring DEGs could be seen in our previous research [31])
Summary
Lung adenocarcinoma (LUAD) remains a crucial factor endangering human health. Gene-based clinical predictions could be of great help for cancer intervention strategies. We tried to build a gene-based survival score (SS) for LUAD via analyzing multiple transcriptional datasets. Lung cancer remains intractable but imperative to cope with for the highest morbidity and mortality among cancers [1]. A principle subtype of lung cancers is lung adenocarcinoma (LUAD), whose investigation means a great deal to us [2,3,4]. Remarkable achievements in clinical practice have proved powerful effect of genes on clinical oncology especially for LUAD [7, 8]. Targeted therapy based on driver gene, such as epidermal
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