Eighteen participants diagnosed with LUAD were recruited from January 2018 to December 2022 at the Division of Thoracic Surgery and Division of Pulmonary and Critical Care Medicine, Kaohsiung Medical University Hospital [approval nos. KMUH-IRB-20180023, KMU-IRB-20200038, KMU-IRB-E(II)-20220175; Kaohsiung, Taiwan R.O.C.]. All patients provided written informed consent to participate. Eight out of eighteen paired adjacent non-tumor lung and tumor tissues (Case nos. 1-8, Table I) obtained underwent deep RNA sequencing (RNA-Seq) at a biotechnology company (Welgene, Inc.) using the Solexa platform (Illumina, Inc.). RNA and small RNA library construction was performed using a sample preparation kit (Illumina, Inc.), following the protocol of the TruSeq RNA or Small RNA Sample Preparation Guide. Data were submitted to the National Center for Biotechnology Information Gene Expression Omnibus (GEO) under accession number GSE236816.

Ten pairs of adjacent non-tumor lung tissues and lung cancer tissues (Case nos. 9-18, Table I) were utilized for IHC. The designated tissue samples were fixed with 10% formalin at room temperature for 1 h and the tissue block was embedded in paraffin. The formalin-fixed paraffin-embedded tissue block was then split into sections (8 µm). Xylene was used to dewax the sections and a descending ethanol gradient was used for rehydration. Antigen retrieval was heat-mediated using a pressure cooker for 90 sec. Endogenous peroxidase activity was inactivated by incubation with 3% hydrogen peroxide for 10 min at room temperature, and non-specific antibody binding was prevented by incubation with 3% bovine serum albumin (MilliporeSigma) for 20 min at room temperature. The sections were incubated with primary antibodies against ERH (1:200; cat. no. NBP1-84976; Novus Biologicals, LLC) and small nuclear ribonucleoprotein polypeptide G (SNRPG; 1:500; cat. no. PA5-64155; Invitrogen; Thermo Fisher Scientific, Inc.) to assess ERH and SNRPG protein expression at 4°C overnight followed by incubation with horseradish peroxidase conjugated anti-rabbit secondary antibodies (1:1,000; cat. no. ab6721, Abcam) for 20 min at room temperature, followed by washing with PBS and 3,3′ diaminobenzidine staining for 2 min at room temperature. The sections were counterstained with hematoxylin for 1 min at room temperature. The results of IHC were imaged using an ICC50 HD light microscope (Leica Microsystems, Inc.) at ×100 magnification.

To validate the findings from the public database, the present study collected 8 human LUAD tumor tissues and adjacent non-tumor tissues. Total RNA was extracted from tissues or cell lines using TRIzol^® reagent (Invitrogen; Thermo Fisher Scientific, Inc.), and 50 ng mRNA was reverse transcribed into cDNA using an oligo (dT) primer and reverse transcriptase (PrimeScript RT Reagent Kit; Takara Bio, Inc.) according to the manufacturer's protocols. RT-qPCR was performed on the human samples to quantify the ERH mRNA expression levels. The primers used in the experiment were as follows: ERH forward (F), ERH_ F1, 5′-CCTACCAAGAGGCCAGAAGG-3′ and reverse (R), ERH_ R1, 5′-TAAACCAGGCAGCTGAGGTC-3′; GAPDH F, 5′-TTCACCACCATGGAGAAGGC-3′ and R, 5′-GGCATGGACTGTGGTCATGA-3′). qPCR was performed at 95°C for 20 sec, followed by 40 cycles at 95°C for 3 sec and 60°C for 30 sec. The expression levels of specific genes were determined using a StepOne-Plus PCR instrument (Applied Biosystems; Thermo Fisher Scientific, Inc.) and SYBR-Green (Thermo Fisher Scientific, Inc.). The relative expression levels of the specific mRNAs were normalized to those of GAPDH. The relative standard method (2^−∆∆Cq) was used to calculate relative RNA expression (21).

The gene expression profile of LUAD was obtained from The Cancer Genome Atlas (TCGA) via the University of Santa Cruz Xena database (https://xenabrowser.net/datapages/?host=https%3A%2F%2Fpancanatlas.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443; accessed on June 15, 2022). For the protein expression pattern in LUAD, data were extracted from The Human Protein Atlas website (https://www.proteinatlas.org/ENSG00000100632-ERH/pathology/lung+cancer#img; accessed on June 22, 2022). In the TCGA cohort, there were 2 tissues from healthy patients, 57 pairs of adjacent non-tumor and tumor tissues, and 454 tumor tissues (total normal tissue, n=59; total tumor tissues, n=511). Further analysis of the gene and protein expression pattern across tissue types, cancer stages and the extent of lymph node metastasis were extracted from the public platform, the University of Alabama at Birmingham CANcer data analysis Portal [the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the International Cancer Proteogenome Consortium datasets, UALCAN; http://ualcan.path.uab.edu]. The gene sets which correlated, either positively or negatively, with ERH were also identified using the UALCAN platform using the cutoff correlation co-efficiency r>0.3 or r <-0.3, respectively. To validate the gene expression results from TCGA, the Asian cohort GSE31210 dataset (control=20, with 15 from adjacent non-tumor tissues and 5 from normal tissues from healthy individuals; tumor=226) from the GEO (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31210) was used with MAS5 normalization (22). STRING is a database of known and predicted protein-protein interactions for numerous genes, including for ERH (https://string-db.org/; version 11.5, accessed on June 15, 2022).

The Human A549 LUAD cell line (American Type Culture Collection; CCL185) was cultured in F-12K Medium (Thermo Fisher Scientific, Inc.) supplemented with 10% fetal bovine serum (FBS; Gibco; Thermo Fisher Scientific, Inc.), 0.1 mg/ml streptomycin and 100 U/ml penicillin (Thermo Fisher Scientific, Inc.). Human CL1-0 LUAD cell line was donated by Professor Pan-Chyr Yang (National Taiwan University, College of Medicine, Taiwan). The CL1-0 cell line was cultured in RPMI 1640 medium supplemented with 10% FBS, 2 mM glutamine and 1% penicillin-streptomycin (Capsugel; Lonza Group, Ltd.). Both cell lines were confirmed negative for mycoplasma contamination using mycoplasma test kits (Mycoalert Mycoplasma Detection Kit; Capsugel; Lonza Group, Ltd.) every 3 months.

The effect on survival of the genes of interest was evaluated using the KM plotter (http://kmplot.com/analysis/; accessed on June 19, 2022) using data sourced from the TCGA and GEO databases. In the survival analysis of LUAD in the KM plotter, data from gene chip microarray or RNA-Seq were used. Subjects were divided into two groups based on their high or low RNA expression levels, with the best cutoff value automatically computed. The hazard ratios for survival, including overall survival, time to first progression and post-progression survival, were calculated using the Cox proportional-hazards model during a pre-defined 60-month period. In addition, cross-analysis was utilized to compare the survival rates between patient cohorts with high and low expression of a specific gene (bisection) (http://kmplot.com/analysis/) (23). P<0.05 was considered to indicate a statistically significant difference.

The biological functions of ERH were evaluated using CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/home.jsp; accessed on June 8, 2023). Gene set enrichment analysis (GSEA) is a computational tool that computes correlations between biological functions or pathological states with a pre-defined gene set. In the present study, the subjects in the TCGA LUAD cohort were divided into ERH high- and low-expression groups that were defined as the 1st and 4th quartiles (highest 25% and lowest 25%) to enhance the significance. GSEA was then used to analyze the enrichment of biological functions in ERH high- and low-expression groups. A false discovery rate of <0.05 and P<0.05 were set as the cutoff criteria. The gene set ‘c2.cp.kegg.v6.2.symbols.gmt’ was used as the reference.

The gene sets either positively or negatively correlated with ERH were extracted using UALCAN. The criteria set for the analysis were Pearson correlation coefficient >0.3/<-0.3 and P<0.05, which were calculated using UALCAN. The GSVA score of the gene sets with regards to gene expression, survival rate and immune infiltration was calculated using Gene Set Cancer Analysis (GSCA) (24) (http://bioinfo.life.hust.edu.cn/GSCA/#/; accessed on July 19, 2022). Metascape (https://metascape.org/gp/index.html#/main/step1; version 3.5, accessed on July 23, 2022) was also used to provide a comprehensive gene list annotation and analysis for the ERH-positively correlated gene set. The correlated pathways enriched with the target gene list were presented as a heatmap and a clustergram (25).

Tumor Immune Estimation Resource 2.0 (TIMER2.0; http://timer.cistrome.org/; accessed on July 15, 2022) was used for the analysis of ERH-associated infiltrating immune cells (26). The ‘gene module’ was used to select and visualize ERH protein expression with its correlated immune cell infiltration level in LUAD. GSCA was also utilized for immune cell abundance analysis of the ERH-positively or negatively correlated gene set (22). Using the ‘Immune cell abundance’ module, the correlation between immune infiltration and the calculated GSVA score was calculated.

A549 and CL1-0 cells were transfected with ERH-siRNA or control-siRNA (10 nM) using ON-TARGET plus SMARTpool siRNA and Dharmafect reagents No1 (GE Healthcare Dharmacon, Inc.) at 37°C for 48 h. The knockdown efficacy of ERH siRNA was determined by RT-qPCR at 48 h post-transfection according to aforementioned methods, respectively. The sequences were as follows: control siRNA: UGGUUUACAUGUCGACUAA, UGGUUUACAUGUUGUGUGA, UGGUUUACAUGUUUUCUGA and UGGUUUACAUGUUUUCCUA and ERH-siRNA: AGACAUACCAGCCUUAUAA, GGGAAAUAAUUGUGUUGGA, AAGAGAAGAUCUACGUGCU and UAGCCAAGAUUGACUGUAU, respectively. The subsequent experiments were performed 48 h post-transfection.

The cell proliferation of control siRNA or ERH siRNA transfected A549 cells and CL1-0 cells were assessed using the WST-1 assay (MilliporeSigma) for a 72 h incubation, according to the manufacturer's protocol.

A total of 2×10⁵ ERH siRNA or control-siRNA transfected A549 and CL1-0 cells were seeded and allowed to grow to ~90% confluence in 24-well plates cultured in media which contained 1% FBS (27). The following day, a uniform scratch was made down the center of the well using a micropipette tip, followed by washing once with phosphate-buffered saline (PBS). Imaging of wound healing at 0 and 24 h was performed using an Olympus inverted light microscope.

A cell migration assay was performed using a Transwell system, as previously described (28). Briefly, 3×10⁴ ERH siRNA and control siRNA transfected A549 and CL1-0 cells were seeded into the top inserts with serum-free medium and incubated for 10 min and complete medium containing 10% FBS was placed in the bottom well and cultured at 37°C in an incubator. After 24 h, the migratory cells on the bottom of inserts then were fixed in 4% paraformaldehyde for 20 min at room temperature and stained with 0.1% crystal violet overnight at room temperature. The migratory cells were counted in 10 random microscope fields for each sample using a light microscope (Nikon Corporation).

The total protein of ERH-knockdown and control A549 and CL1-0 cells was extracted using RIPA buffer (cat. no. 20-188; MilliporeSigma), supplemented with a protease inhibitor mixture (S8830-20TAB, MilliporeSigma). An equal volume of total protein, 25 µg, was denatured by heating and then separated by electrophoresis using 12% sodium dodecyl-sulfate polyacrylamide gels. Proteins in the gel were transferred onto polyvinylidene difluoride membranes (MilliporeSigma) by electroblotting, which was probed with primary antibodies overnight after blocking in 5% non-fat dry milk/0.1% TBST at room temperature (25°C). Primary antibodies against N-cadherin (1:1,000; cat. no. 610921), E-cadherin (1:1,000; cat. no. 610182), and Vimentin (1:1,000; cat. no. 550513) were purchased from Becton, Dickinson and Company. Anti-ERH antibodies (1:1,000; cat. no. NBP1-84976) were purchased from Novus Biologicals, LLC and anti-GAPDH (1:5,000; cat. no. MAB374) antibodies were from MilliporeSigma. After incubation with HRP-conjugated secondary antibodies (1:5,000; anti-mouse, cat. no. 7076; anti-rabbit, cat. no. 7074; Cell Signaling Technology, Inc.). The signal of the specific protein was detected using a chemiluminescence kit (MilliporeSigma). The western blot was semi-quantified using ImageJ (version 1.53; National Institutes of Health) and each experiment was repeated independently at least three times.

The raw data extracted from GSE31210 and the results of the cell functional assays were re-plotted using GraphPad Prism 5 software (GraphPad Software; Dotmatics). One-way ANOVA was used for analysis when comparing more than two groups with Tukey's post hoc test. Unpaired Student's t-test was used to compare mean values between different subjects and cell groups. P<0.05 was considered to indicate a statistically significant difference.

Using the public transcriptomic database TCGA, the mRNA-Seq profile of LUAD was obtained and the levels of ERH mRNA expression were demonstrated to be significantly higher in tumor tissues (n=511) than in the adjacent non-tumor tissues (n=59) (Fig. 1A). Significantly elevated ERH expression was demonstrated across different tumor stages and at different extents of lymph node involvement, although the increase did not demonstrate stage- or lymph node stage-dependence (Fig. 1B and C). To validate these findings in the in-house cohort, RT-qPCR for ERH was performed. Higher ERH expression in tumors was demonstrated in 6 out of 8 samples, ranging from a log₂ fold change of 1.26 to 1.71 compared with the adjacent non-tumor baseline; by contrast, ERH expression was lower in 2 of the 8 samples (Fig. 1D).

The results were also validated in another public transcriptomic dataset, GSE31210, to assess the association between ERH expression and ethnicity. This dataset exclusively includes an Asian population and similarly, the expression of ERH was significantly increased in the tumor tissues (n=226) compared with the mixed healthy and adjacent normal tissues [paired adjacent non-tumor tissues (n=15) and normal tissues from healthy individuals (n=5)] (P<0.05; Fig. 1E). Moreover, the level of ERH expression in LUAD was significantly linked with worse outcomes (Fig. 1F-H). The prognostic profiles regarding overall survival, time to first progression and time of post-progression survival were obtained from the KM plotter and as illustrated, for the higher levels of ERH expressed in tumors, a significantly lower probability of each survival parameter was notably demonstrated in the pre-defined 60-month period. To summarize, higher levels of ERH were expressed in tumor tissues compared with those in normal tissues across different ethnicities and higher expression levels of ERH were significantly associated with reduced survival times. This indicated that ERH may serve a critical role in LUAD.

The ERH protein expression pattern in LUAD was further evaluated. The proteomic data obtained from the CPTAC demonstrated a significantly enhanced expression pattern of ERH protein in tumor tissues compared with adjacent non-tumor tissues (median Z-score, 0.027 vs. −0.613; Fig. 2A). IHC staining images in the Human Protein Atlas demonstrated that there was a higher intensity of ERH expression in tumors compared with in normal tissues (healthy control) (Fig. 2B). These results indicated that ERH might be critical in LUAD at the protein level observed in the public cohorts and the in-house cohort.

The CancerSEA website was utilized to elucidate the corresponding biological function of ERH. It was demonstrated that in LUAD, ERH expression was significantly positively correlated with a broad range of functional behaviors towards cancer progression, such as angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, EMT, hypoxia, invasion, metastasis, proliferation, and stemness. Among these, DNA damage/repair, cell cycle and invasion were the most correlated aggressive functions with ERH expression after setting a cutoff correlation strength of 0.3 (Fig. 3A). Furthermore, when linked to biological processes such as cell cycle, proliferation, invasion, EMT and metastasis using the GSEA method in lung cancer, the ERH-correlated gene set was strongly associated with poor survival and chemo-resistance (Fig. 3B). This bioinformatics evidence demonstrated the roles of ERH in DNA damage/repair, cell cycle and invasion of LUAD progression.

Ten molecules that potentially interact with ERH were identified using the STRING database data on protein-protein interactions. These molecules included DDX39B, CHTOP, HNRNPH1, MATR3, SNRPD1, SNRPD2), SNRPD3, SNRPE, SNRPF, and SNRPG (Fig. 4A). Moreover, all were strongly correlated with ERH expression in the TCGA LUAD dataset with a correlation strength r>0.4 (Fig. 4B). Among the potentially interactive factors, the upregulation of SNRPD1, SNRPD2, SNRPD3, SNRPE, SNRPF and SNRPG were linked to significantly shorter survival times, determined by the best cutoff method, whereas upregulation of MATR3 was associated with a significantly better prognosis (Fig. 4C). Survival-associated molecules were validated using the CPTAC database, from which the available protein expressions of SNRPD3, SNRPE and SNRPG were demonstrated to be significantly different between tumor and non-tumor samples, whereas SNRPD1 and SNRPD2 were expressed in similar amounts between tumor and non-tumor parts. However, only SNRPG protein demonstrated greater expression in primary tumor samples (Fig. 4D), which was in accordance with the presumed expression pattern of mRNA in the TCGA. In addition, 7 out of 10 of the tumor samples (with the exception of patient Nos 1, 8 and 9) in the in-house cohort were strongly stained by ERH or SNRPG antibodies compared with adjacent non-tumor samples. In these 7 patients, higher expression of ERH was accompanied by elevated SNRPG expression (Fig. 4E). SNRPG expression was associated with ERH expression and shorter survival duration.

To assess the potential interacting effect of small nuclear ribonucleoproteins (SNRs) with ERH, the effect of ERH expression on the survival time of patients with LUAD based on high or low levels of various SNRs was evaluated using cross-analysis. Analysis using the KM plotter demonstrated that the overall survival time of patients with high ERH expression was significantly shorter than that of patients with low ERH expression in the high expression subgroups of SNRPD2, SNRPD3, SNRPE and SNRPG (Fig. 5B-D and F). These data indicated a potential SNRPG-dependent interaction that governed the survival impact of ERH.

The top 200 genes either positively or negatively correlated with ERH were extracted from the LUAD cohort of TCGA. The positive and negative gene sets were calculated via the GSCA website to acquire the GSVA scores. The scores provide the significance of the gene set in terms of survival (29). It was demonstrated that the GSVA scores for the ERH positively correlated gene set were significantly higher in LUAD tumor samples than normal tissue samples (Fig. 6A). Inversely, the GSVA scores for the ERH negatively correlated gene set were significantly lower in LUAD tumor samples than normal tissue samples (Fig. 6B). Markedly higher GSVA scores for the ERH positively correlated gene set were linked to advanced cancer stages (Fig. 6C). However, higher GSVA scores for the ERH negatively correlated gene set demonstrated a declining trend as the cancer stage advanced (Fig. 6D). Higher GSVA scores for the ERH positively-correlated gene set were associated with significantly worse patient outcomes in terms of overall survival (OS; HR=1.45), progression-free survival (PFS; HR=1.37) and disease-specific survival (DSS; HR=1.79), but not with disease-free survival (DFI; HR=1.28, Cox P=0.25) (Fig. 6E). In a reverse pattern, higher GSVA scores for the ERH negatively correlated gene set were linked to significantly better patient outcomes in terms of OS (HR=0.66) and DSS (HR=0.57), but not PFS (HR=0.78, Cox P=0.05) and DFI (HR=0.90, Cox P=0.62) (Fig. 6F). Analysis using the Metascape website demonstrated that the ERH positively correlated gene set was associated with certain biological processes, such as the ‘cell cycle, DNA metabolic process, S phase and retinoblastoma gene in cancer’ (Fig. 6G). Associated gene clusters were illustrated as an enriched ontology cluster network (Fig. 6H). Further immune microenvironment analysis was undertaken using the TIMER2.0 website, which demonstrated that ERH gene expression was significantly positively correlated with the infiltration of MDSCs in tumors with a ρ-value of 0.435 but not purity (ρ=0.097) (Fig. 6I). Using the GSCA website, the infiltrating immune cells corresponding to the GSVA scores for the ERH positively correlated gene set were demonstrated to include natural regulatory T cells (nTregs), effector memory T cells, T helper type 1 cells and exhausted T cells. Among those, nTregs demonstrated the highest correlation (Fig. 6J). The ERH negatively correlated gene set correlated with the infiltration of cells such as CD4 T cells, follicular helper T cells, natural killer T (NKT) cells and natural killer (NK) cells (Fig. 6K). Based on the aforementioned findings, ERH and its correlated genes expressed in LUAD were associated with the infiltration of immune-suppressive cells, such as MDSCs and nTregs, which led to a microenvironment against immune surveillance.

GSEA revealed an association between high ERH expression and cancer EMT and invasiveness. To validate the findings in vitro, cellular functional studies were designed using siRNAs to knock down ERH with high knockdown efficiency (Fig. 7A). There was no significant difference in the proliferation of A549 and CL1-0 cells with ERH knockdown compared with that of the control cells (Fig. 7B). To evaluate cell migration, Transwell migration and wound healing assays were performed, with the percentage of migrated cells and the distance of migration both significantly reduced in ERH-knockdown A549 and CL1-0 cells (Fig. 7C and D). These data supported the potential of ERH to enhance cell migration. Concerning EMT, the expression of mesenchymal markers, such as N-cadherin and vimentin, notably declined, whereas the epithelial marker E-cadherin was slightly elevated in ERH-knockdown A549 and CL1-0 cells (Fig. 7E). These results suggested that ERH regulated promotion and progression steps in LUAD, but not proliferation.