lncRNA PCBP1-AS1 mediated downregulation of ITGAL as a prognostic biomarker in lung adenocarcinoma

Data collection and processing

We obtained the transcriptome profiles of 504 LUAD samples and 59 samples from healthy lung tissue from the TCGA database (https://cancergenome.nih.gov/).

Gene set cancer analysis (GSCA)

GSCA (http://bioinfo.life.hust.edu.cn/GSCA/#/document) is an integrated platform including the RNA levels, DNA methylation, immune cell infiltration, and drug resistance of TCGA pan-cancer [14].

The cancer therapeutics response portal database

CTRP (http://portals.broadinstitute.org/ctrp/) database is a database, which includes the protein-kinase-targeting drugs and genomic alterations data [15]. In this manuscript, we employed the CTRP to explore the relationships between ITGAL and the sensitivity of different drugs.

Linkedomics database

Linkedomics is a database, which includes biologists and clinicians across tumor types in TCGA [16]. In this study, we determine the potential biological and signaling pathway of ITGAL in NSCLC by Linkedomics.

Human protein Atlas database

HPA is a comprehensive TCGA cancer-related database [17]. In this finding, we were using the HPA database analysis of the protein of ITGAL in lung tissues and lung cancer tissues.

TISIDB database

TISIDB is a tumor immune-related database [18]. In this study, we use TISIDB to examine the correlations between ITGAL and different immune modulators in NSCLC.

Single-cell sequencing analysis

Single-cell sequencing analysis (http://lung.cancer-pku.cn/index.php). In this study, we examined the correlations between ITGAL and different T cells in NSCLC.

Kaplan-Meier plotter

In this manuscript, we analysis of the relationship between ITGAL and overall survival and immune cell in patients with NSCLC by Kaplan-Meier Plotter database.

qRT-PCR assay

The lung cancer cell line was purchased from the ATCC cell bank and cultured using RPMI-1640 medium. Actin as an internal reference gene for qPCR assay. The primer of ITGAL is as follows: qPCR-F: TGCTTATCATCATCACGGATGG, qPCR-R: CTCTCCTTGGTCTGAAAATGCT.

ITGAL is decreased in NSCLC

In the TCGA dataset, we found that ITGAL was down-regulated in NSCLC (Figure 1A–1C). We next explored the correlations between ITGAL level and clinical features of NSCLC patients. Results showed that low expression of ITGAL related to poor clinical features, including pathological, TN stage, age, and diverse survival events (Figure 1D–1I). Using the HPA database, we confirmed that ITGAL was significantly down in lung cancer tissue (Figure 1J). More importantly, compared to normal lung epithelial cells, ITGAL levels in lung cancer tumor cell lines are abnormally decreased (Figure 1K). Kaplan-Meier was employed to determine the prognosis of ITGAL in NSCLC. We found that patients with a lower level of ITGAL have short OS and DSS in NSCLC patients (Figure 2A, 2B). ROC curve data showed that ITGAL may be a potential diagnostic marked in NSCLC (Figure 2C, 2D).

Single-cell sequencing analysis

We examined single-cell transcriptome data of NSCLC and found that ITGAL has different expression modes in diverse immune cells of NSCLC (Figure 3A, 3B). ITGAL major is highly expressed in PTC immune cells and downregulated in NTR immune cells (Figure 3C). Single-cell transcriptome data used conducted function analysis. Results demonstrated that ITGAL level was negatively related to cell apoptosis and EMT (Figure 3D).

KEGG and DNA methylation analysis

Linkedomics was used to get the genes that are positive or negative with ITGAL in NSCLC (Figure 4A, 4B). GO enrichment results confirmed that ITGAL was major involved in the immune response-related signaling pathway (Figure 4C). KEGG results indicated that ITGAL mainly participated in the T cell receptor pathway and Th17 cell differentiation (Figure 4D). DNA methylation plays an indispensable role in regulating cancer malignant progression and recurrence [19]. Hypermethylation of gene promoter regions usually results in gene expression decreased in tumors. We analysis of the correlations between DNA methylation and ITGAL in NSCLC. Results confirmed that DNA methylation of ITGAL was higher in NSCLC tissues than in normal tissues (Figure 5A, 5B). We also found a significant negative correlation between ITGAL levels and DNA methylation status (Figure 5C, 5D). However, the DNA methylation level of the ITGAL gene did not affect the prognosis of lung cancer patients (Figure 5E, 5F).

Correlation of ITGAL expression and immune infiltrates

We further explore the relationship between ITGAL levels and the tumor immune microenvironment of NSCLC. First, we found that ITGAL was highly expressed in the C3 immune subtype (Figure 6A, 6B). Further study indicated that there is a positive correlation between ITGAL CNV and cytotoxic, Treg, NK, Th1, Exhausted, Central-memory, CD8-T, Macrophage, and CD4-T cells in NSCLC (Figure 6C, 6D). Next, we confirmed that ITGAL was positively related to the 23 types of immune cells (Figure 7A–7F), immune scores, stromal scores, and ESTIMATE scores in NSCLC (Figures 8A). Finally, we showed that in the ITGA-high expression group, the infiltration level of most immune cells significantly increased (Figure 8B–8D).

Immune checkpoint-related genes play an indispensable role in tumor progression and immune cell function. To further clarify the function of ITGAL in the immune microenvironment, we uncover that ITGAL level was positively related to the immune modulator, including the tumor-infiltrating lymphocytes (TILs), immune inhibitor, immunostimulator, MHC molecule, chemokines as well as its receptors (Figure 9A–9F).

ITGAL-related ceRNA network in NSCLC

Studies showed that LncRNA is crucial for regulating gene expression at the post-transcriptional level [17]. To explore the upstream lncRNA/ceRNA network of ITGAL. We used starBase for prediction of potential miRNAs that bind with ITGAL. We obtained the 6 miRNAs in total, and according to the negative correlation with ITGAL expression in NSCLC, we identified 2 miRNAs, miR-9-5p and miR-424-5 (Figure 10A). Two miRNAs were downregulated in NSCLC and displayed worse patient prognosis (Figure 10B–10D).

In addition, we determine the lncRNAs that regulate miR-9-5p and miR-424-5 expression. By integrated analysis of two miRNA binding lncRNAs and lncRNAs with low expression in NSCLC and significant correlation with prognosis. We obtained 3 lncRNAs (Figure 10E), but only lncRNA PCBP1-A1 was downregulated in NSCLC and positively correlated with ITGAL expression in NSCLC (Figure 10F, 10G). More importantly, we uncover that lower lncRNA PCBP1-A1 expression correlated with adverse clinical outcomes in NSCLC patients (Figure 10H). More importantly, compared to normal lung epithelial cells, the expression level of PCBP1-A1 in lung cancer tumor cell lines is abnormally decreased (Figure 10I). Unlike ITGAL, PCBP1-A1 level is positively correlated with T helper cell infiltration (Figure 10J). These findings indicated that lncRNA PCBP1-AS1 is an upstream lncRNA for the miR-9-5p and miR-424-5/ ITGAL axis in NSCLC.

Prognostic of ITGAL expressions in NSCLC based on immune cells

Due to the significant correlation between ITGAL and infiltration of different immune cells, we further used Kaplan-Meier plotter analyses and found that low ITGAL levels in NSCLC in decreased Basophils cohort had a worse prognosis (Figure 11A, 11B). We also examined the relationship between ITGAL expression and diverse drug sensitivity in the cancer therapeutics response portal database. We showed that ITGAL expression was negatively correlated with the sensitivity of SNX-2112, GSK-J4, Cytarabine hydrochloride, Narciclasine, LRRK2-IN-1, Teniposide, Sotrastaurin, GSK461364, BRD-K66453893, Piperlongumine AT13387, I-BET151, Ciclopirox, CR-1-31B, Vincristine, Albendazole, PX-12, Belinostat, SR-II-138A, CHM-1, Isoliquiritigenin, Triazolothiadiazine and BI-2536 (r < −4, p < 0.001) (Figure 11C). This evidence suggested that ITGAL may regulate the sensitivity of the above different drugs and promote NSCLC progress. It is necessary to employ these drugs to verify their functions at the cellular level.