NR5A2 gene affects the overall survival of LUAD patients by regulating the activity of CSCs through SNP pathway by OCLR algorithm and immune score

Abstract

Objective: Differentially expressed genes (DEGs) in lung adenocarcinoma (LUAD) tumor stem cells were screened, and the biological characteristics of NR5A2 gene were investigated.

Methods: The expression and prognosis of NR5A2 in human LUAD were predicted and analyzed through bioinformatics analysis from a human cancer database. Gene expression and clinical data of LUAD tumor and normal lung tissues were obtained from The Cancer Genome Atlas (TCGA) database, and DEGs associated with lung cancer tumor stem cells (CSCs) were screened. Univariate and multivariate Cox regression models were used to screen and establish prognostic risk prediction models. The immune function of the patients was scored according to the model, and the relative immune functions of the high- and low-risk groups were compared to determine the difference in survival prognosis between the two groups. In addition, we calculated the index of stemness based on the transcriptome of the samples using one-class linear regression (OCLR).

Results: Bioinformatics analysis of a clinical cancer database showed that NR5A2 was significantly decreased in human LUAD tissues than in normal lung tissues, and the decrease in NR5A2 gene expression shortened the overall survival and progression-free survival of patients with LUAD.

Conclusion: The NR5A2 gene may regulate LUAD tumor stem cells through selective splicing mutations, thereby affecting the survival and prognosis of patients with lung cancer, and the NR5A2 gene may regulate CSCs through single nucleotide polymorphism.

Keywords: Bioinformatics analysis; Cancer stem cell; NR5A2; Prognostic evaluation; Single nucleotide polymorphism.

Fig. 1

A: OCLR score and clinical information distribution map. The top image is the distribution map of OCLR score from low to high, and the bottom image is the distribution of clinical information characteristics after sorting. B: Box plot (G1: tumor metastasis; G2: tumor recurrence; G3: primary tumor). OCLR, one-class linear regression.

Fig. 2

Venn diagram screening analysis in tumor stemness.

Fig. 3

Sankey diagram of NR5A2 gene in lung cancer tumor stem cells.

Fig. 4

A: Volcano Plot of NR5A2 gene expression. B：Differential gene expression heat map. C: Enrichment analysis of biological functions.

Fig. 5

A: Lollipop plot displaying mutation distribution and protein domains for NR5A2 gene in cancer with the labeled recurrent hotspots. Somatic mutation rate and transcript names are indicated by plot title and subtitle. B: Oncoplot displaying the somatic landscape of lung cancer cohort. C: Cohort summary plot displaying distribution of variants according to variant classification, type, and SNP class. Bottom part (from left to right) indicates mutation load for each sample, variant classification type. A stacked barplot shows top ten mutated genes. SNP, single nucleotide polymorphisms.

Fig. 6

A–B: Univariate and multivariate Cox regression in some parameters of the NR5A2 genes. C–D: Nomogram to predict overall survival of lung cancer patients.

Fig. 7

A. Cluster correlation analysis of immune cells. B. Comparative analysis of immune cell subsets; C. Relationship between NR5A2 expression level and clinicopathological features of patients with LUAD (Scale bar: 50 μm)[https://www.proteinatl as.org].

Fig. 8

A–D: Cellular immunofluorescence of NR5A2 gene expression. NR5A2 (Green: NR5A2 in the nucleus; Violet: ab272550, Abcam; Red: Goat Anti-Mouse IgG (H and L), Alexa Fluor® 488, Scale bar: 10 μm) [https://www.proteinatl as.org]. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)