Abstract

Background

   Lung 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.

Methods

   We 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.

Results

   We 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.

Conclusions

   We built a 13 gene-based SS for prognostic prediction of LUAD, which
   exhibited wide applicability and could contribute to LUAD management.

   Keywords: Lung adenocarcinoma, Transcriptome, Survival, Prediction,
   Risk

Background

   Lung cancer remains intractable but imperative to cope with for the
   highest morbidity and mortality among cancers [[41]1]. A principle
   subtype of lung cancers is lung adenocarcinoma (LUAD), whose
   investigation means a great deal to us [[42]2–[43]4]. Advance in cancer
   biology demonstrated cancer could be regarded as a disorder caused
   mainly by aberrant genes, while some core ones even drive
   carcinogenesis [[44]5, [45]6]. That is to say, genes are undoubtedly
   valuable targets for cancer management.

   In fact, remarkable achievements in clinical practice have proved
   powerful effect of genes on clinical oncology especially for LUAD
   [[46]7, [47]8]. First take chemotherapy for example. Many widely
   applied chemotherapeutic agents are aimed at critical genes in
   biological processes like cell proliferation and metabolism [[48]9,
   [49]10]. Besides, targeted therapy based on driver gene, such as
   epidermal growth factor receptor (EGFR), has significantly improved the
   prognosis of patients with specific genetic background [[50]11,
   [51]12]. Moreover, immunotherapy targeted at immune-checkpoint genes
   has achieved revolutionary progress for LUAD patients, especially for
   who have no targetable driver mutation till now [[52]4, [53]7, [54]13].

   Moreover, clinical predictions based on gene signatures also contribute
   much to handling cancer [[55]14–[56]16]. For example, some canonical
   biomarkers are references for distinguishing specific cancer from