A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model

Abstract

There have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma. Based on the identified mRNAs, we can build a prognostic model combining mRNAs and clinical features, allowing us to explore new molecules with the potential to predict the prognosis of lung adenocarcinoma. The mRNA data (n = 594) and clinical data (n = 470) for lung adenocarcinoma were obtained from the TCGA database. Gene set enrichment analysis (GSEA), univariate Cox proportional hazards regression, and the Bayesian hierarchical Cox proportional hazards model were used to explore the mRNAs related to the prognosis of lung adenocarcinoma. Multivariate Cox proportional hazard regression was used to identify independent markers. The prediction performance of the prognostic model was evaluated not only by the internal cross-validation but also by the external validation based on the GEO dataset (n = 437). With the Bayesian hierarchical Cox proportional hazards model, a 14-gene signature that included CPS1, CTPS2, DARS2, IGFBP3, MCM5, MCM7, NME4, NT5E, PLK1, POLR3G, PTTG1, SERPINB5, TXNRD1, and TYMS was established to predict overall survival in lung adenocarcinoma. Multivariate analysis demonstrated that the 14-gene signature (HR 3.960, 95% CI 2.710–5.786), T classification (T1, reference; T3, HR 1.925, 95% CI 1.104–3.355) and N classification (N0, reference; N1, HR 2.212, 95% CI 1.520–3.220; N2, HR 2.260, 95% CI 1.499–3.409) were independent predictors. The C-index of the model was 0.733 and 0.735, respectively, after performing cross-validation and external validation, a nomogram was provided for better prediction in clinical application. Bayesian hierarchical Cox proportional hazards models can be used to integrate high-dimensional omics information into a prediction model for lung adenocarcinoma to improve the prognostic prediction and discover potential targets. This approach may be a powerful predictive tool for clinicians treating malignant tumours.

Assessing the Prognostic Capability of Immune-Related Gene Scoring Systems in Lung Adenocarcinoma

“…A risk score was computed for each individual with the prognostic models of immune-related genes. In the training cohort, the KM analysis was used to confirm the difference in survival between the high-risk-score ( N = 113) and low-risk-score ( N = 113) populations classified by a median score [ 17 , 18 ]. In Figure 4(a) , the 5-year survival incidence was 58.07% ( N = 66) in the low -risk-score group vs. 32.74% ( N = 37) in the high-risk-score group.…”

Prognostic roles of a novel basement membranes-related gene signature in lung adenocarcinoma

“…Based on the data from open access public databases, many studies have focused on the link between RNA-seq data of specific genomes and prognosis of individual patients ( Sun et al, 2022 ; Zhao et al, 2022 ), while few studies were focused on the prognosis of LUAD with specific genomes, particularly on clinical application, immune infiltration and other related areas. There was growing evidence that the response of extracellular matrix to TME drives the potential carcinogenic mechanisms of many cancers, including lung cancer ( Li et al, 2021 ).…”

RNA polymerase III transcription and cancer: A tale of two RPC7 subunits

“…Notably, POLR3G upregulation has been linked with poor survival outcomes across a variety of cancers, including in patients with lung adenocarcinoma ( Sun et al, 2022 ), hepatocellular carcinoma ( Dai et al, 2021 ), transitional cell carcinoma ( Liu et al, 2020 ), multiple myeloma ( Yang et al, 2021 ), and other forms of cancer ( Van Bortle et al, 2022 ). In fact, pan-cancer comparison of survival signatures across all cancer subtypes reveals that POLR3G expression is the most significant feature and predictor of poor survival outcomes compared with all other Pol III subunits ( Figure 2A ) ( Smith and Sheltzer, 2022 ).…”