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Introduction

Lung cancer is the most common cancer type and the leading cause of cancer-associated mortality worldwide (1). Non-small cell lung cancer (NSCLC) is the most prevalent and heterogeneous subtype of lung cancer (2,3), including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Despite numerous advances in treatment methods, the 5-year overall survival for advanced lung cancer remains poor (4). Currently, platinum-based postoperative chemotherapy is a standard treatment, and cisplatin is a basic chemotherapy drug for lung carcinoma; however, cisplatin resistance mainly leads to the failure of chemotherapy in these patients (5). Thus, it is urgent to identify specific and effective biomarkers to predict the prognosis of adjuvant chemotherapy for NSCLC.

DNA repair capacity is a major determinant of cisplatin resistance (6). Since the excision repair cross-complementation group 1 (ERCC1) protein is essential for nucleotide excision repair (NER) and influences genomic instability, ERCC1 may serve a critical role in DNA repair (7). It has been reported that the complex of ERCC1 combined with xeroderma pigmentosum complementation group F cleaves on the 5′ side of the DNA lesion. Besides NER, this complex is also involved in the repair of DNA interstrand crosslinks and in the completion of homologous recombination (8). A great part of the complexity of human diseases can be attributed to the regulation of gene expression via alterations in the transcriptional and post-transcriptional levels (9,10). Alternative splicing is a regulated process that occurs in nearly all multi-exon human genes (10). Different transcriptional regulation and splicing mechanisms lead to the production of multiple products by individual genes. The ERCC1 gene generates a variety of isoforms by alternative splicing. Previous studies have demonstrated that the protein products of 297aa encoded by the ERCC1-202 and ERCC1-208 isoforms exhibit different DNA repair capacities (11), although the only difference between the two isoforms is that ERCC1-202 has a longer 3′-untranslated region (3′UTR). It has also been reported that the structural alterations of the 3′UTR were involved in regulating the function and activation of genes (12).

At a genomic level, the transcription termination site of ERCC1 3′UTR is adjacent to a conjunct transcription start site of CD3e molecule associated protein (CD3EAP) and protein phosphatase 1 regulatory subunit 13 like (PPP1R13L), forming a complex sense-antisense gene arrangement (Fig. 1A). ERCC1, CD3EAP and PPP1R13L function as not only adjacent genes, but also participates in the pathway of DNA repair, proliferation and apoptosis, respectively. CD3EAP, also known as antisense to ERCC1, encodes a nucleolar protein localized to the nucleolus fibrillar centers and the nucleolus organizer regions of mitotic chromosomes (13). In addition, CD3EAP is a subunit of the RNA polymerase I complex involved in ribosomal RNA transcription, regulating the biosynthesis of ribosome and participating in cell proliferation (14). The gene PPP1R13L, also known as iASSP, is an inhibitor of the tumor protein p53 (TP53) apoptotic pathway (15) and of the p65 subunit of the transcription factor nuclear factor (NF)-κB. Since TP53 and NF-κB serve a pivotal role in the apoptosis and inflammatory response, their inhibition by PPP1R13L would affect the availability of relative factors and thus modify the regulation of apoptosis (16). Such overlapping sense and antisense gene pairs may act predominantly as regulators of genes transcription (17,18), and have been implicated in numerous different cellular processes (19). Transcription and splicing are tightly coupled (20,21); however, since the transcription process is strand-specific, it is unclear how and whether the overlapping genes interfere mutually (22). Several potential mechanisms may contribute to this effect, such as the overlapping gene cross-talk between their transcription start sites, transcription termination sites, respective splice sites and epigenetic alterations in the overlapping regions of the gene may affect the expression of sence and antisense genes simultaneously (23). Nevertheless, the precise function of overlapping association remains to be elucidated.

Figure 1 (A) Alternative promoter and alternative terminator of ERCC1, CD3EAP and PPP1R13L genes in chromosome 19q13.2-3. Peaks of H3K4Me3 and H3K27Ac, and two CpG islands were identified near the first exon of CD3EAP and PPP1R13L, and adjacent to the terminal exon of ERCC1. Data were derived from the Encyclopedia of DNA Elements project in the UCSC Genome Browser [Human Dec. 2013 (GRCh38/hg38) Assembly]. (B) Protein interaction network analysis. ERCC1, excision repair cross-complementation group 1; CD3EAP, CD3e molecule associated protein; PPP1E13L, protein phosphatase 1 regulatory subunit 13 like.

In the present study, it was hypothesized that the overlap region among ERCC1, CD3EAP and PPP1R13L may be involved in linking the upstream and downstream genes, and have potential implications on cisplatin resistance in NSCLC. The Cancer Genome Atlas (TCGA) project provides a rich sequencing source for the investigation of exon and gene expression in cancer (24). Bioinformatics analysis using the TCGA data portal was conducted, aiming to analyze the correlation between genes in two aspects of transcriptional and alternative splicing. Furthermore, a cell model of cisplatin-induced DNA damage in NSCLC and other in vitro experiments were performed to verify the findings of bioinformatics analysis, providing an insight into the identification of complementary biomarkers associated with lung carcinoma.

Materials and methods

Gene arrangement of 19q13.3 and analysis of protein network

The genome is a one-dimensional linear space, genes are arranged to form a variety of overlapping conformations. The genome structure of 19q13.2-3 was analyzed by bioinformatics analysis. Comprehensive transcript set data were derived from the GENCODE (www.gencodegenes.org). The UCSC Genome Browser on Human Dec. 2013 (GRCh38/hg38) Assembly was used to analyze the distribution of H3K27Ac, H3K4Me3 and CpG islands in 19q13.3 (25). STRING (http://string-db.org/) was used for protein interaction network analysis.

Heatmap of gene exon expression profiles

The exon expression levels of ERCC1, CD3EAP and PPP1R13L in RNA sequencing (RNA-seq) data of LUAD (TCGA Lung Adenocarcinoma) and LUSC (TCGA Lung Squamous Cell Carcinoma) cohorts were downloaded from TCGA data portal (https://cancerge-nome.nih.gov/). Clinical parameters of the LUAD and LUSC cohorts were also downloaded from TCGA database. A total of 60 cases of LUAD and 51 cases of LUSC with matched cancer and adjacent normal tissues were screened. The adjacent normal tissues were defined as specimens collected at a distance that was >2 cm from the tumor margin. A heatmap of the expression levels of exons in the cancer tissue and its adjacent normal control were generated by the heatmap package in R (version 3.3.3; www.r-project.org).

Alternative splicing event analysis

The web-based resource TCGA SpliceSeq (http://bioinformatics.mdanderson.org/TCGASpliceSeq) was used, which provides a quick and highly visual interface for exploring the alternative splicing patterns of TCGA tumors. Percent Spliced In (PSI) is a common intuitive ratio for quantifying splicing events and has a value between 0 and 1 (26). The PSI value was calculated for seven types of alternative splicing events, as follows: Exon skipping, mutually exclusive exons, intron retention, alternative promoter, alternative terminator, alternative donor site and alternative acceptor site. The average PSI values of splice events in ERCC1, CD3EAP and PPP1R13L on the samples included in the LUAD and LUSC cohorts were loaded into TCGA SpliceSeq and filtered by 10% minor splice expression.

Correlation analysis of exon expression

The exon expression RNA-seq data in TCGA LUAD and LUSC cohorts were obtained from the cBioPortal cancer genomic data website (http://www.cbioportal.org/) (27,28). To analyze the correlation patterns of exons in ERCC1, CD3EAP and PPP1R13L expression, the Spearman’s correlation coefficient of each exon pair was calculated using the corrplot package in R (version 3.3.3).

Tumor tissue sample collection

In the present study, tumor tissues were collected from 15 Chinese Han patients with pathologically proven primary NSCLC without other active malignant diseases. The age range of the patients was between 43–76 years of age, and there were 9 male patients and 6 female patients; the clinical staging was based on the latest TNM staging criteria in 2017 (29). These patients were treated between October 2013 and November 2013 at the First Affiliated Hospital of China Medical University (Shenyang, China). Informed consent was obtained from all patients, and the protocol was approved by the Institutional Review Board of China Medical University prior to the study. All activities involving human subjects were conducted under full compliance with the government policies and the Declaration of Helsinki. The tumor tissue specimens were frozen in liquid nitrogen and stored at −80°C.

Cell culture and treatment

A549 cells were purchased from the Cell Bank of the Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences (Shanghai, China), and cultured in Dulbecco’s modified Eagle’s medium/F-12 (HyClone; GE Healthcare Life Sciences, Logan, UT, USA). The normal immortalized 16HBE cell line, kindly provided by Professor Wen Chen (Sun Yat-Sen University, Guangzhou, China), was cultured in minimum essential medium (HyClone; GE Healthcare Life Sciences). The two cell lines were supplemented with 10% fetal bovine serum (HyClone; GE Healthcare Life Sciences) and maintained at 37°C and 5% CO2 in a humidified incubator. Logarithmic growth phase cells were treated with 4 μg/ml cis-diaminedichloroplatinum (CDDP; Tokyo Chemical Industry Co., Ltd., Tokyo, Japan) according to the requirements of each experiment.

RNA preparation

Total RNA was extracted from the treated cells and tissues, using TRIzol reagent (Invitrogen; Thermo Fisher Scientific, Inc., Waltham, MA, USA), and RNA integrity was assessed using an Agilent 2100 bioanalyzer (Agilent Technologies, Inc., Santa Clara, CA, USA). The RNA concentrations were determined by measuring the absorbance at 260 nm using a NanoDrop 2000 device (Thermo Fisher Scientific, Inc.), and the quality control standard was set to an A260/A280 ratio of 1.8–2.1. Extracted total RNA was cryopreserved at under −80°C and prepared for subsequent experiments.

Quantitative polymerase chain reaction (qPCR) assay

A total of 1 μg RNA was reverse transcribed with M-MLV Reverse Transcriptase (Takara 047A; Takara Bio, Inc., Otsu, Japan). The primers used in qPCR were designed at our laboratory, and a BLAST search (https://blast.ncbi.nlm.nih.gov/Blast.cgi) was performed against GenBank to ensure that all primers were unique to the gene of interest. The sequences of the qPCR primers used in the present study are listed in Table I. Quantitative analysis was performed using the LightCycler 480 II instrument (Roche Diagnostics, Indianapolis, IN, USA), and the PCR reactions were performed with SYBR Premix Ex Taq II (Takara Bio, Inc.). The PCR cycling conditions were as follows: Denaturation at 95°C for 30 sec, followed by 40 cycles of 95°C for 5 sec, 60°C for 20 sec. The results were quantified using the 2−ΔΔCq method (30). In all qPCR experiments, the data were normalized to the expression of the human GAPDH housekeeping gene. Three independent RNA preparations were tested for each sample, and each reaction was performed in triplicate.

Table I Primer sequences of quantitative 3′RACE and PCR.

Table I

Primer sequences of quantitative 3′RACE and PCR.

A, 3′RACE
Amplification position	Outer (5′-3′)	Inner (5′-3′)	Distance from the terminating	Transcription name site of the transcript (bp)
Exon 11.2 of ERCC1	AACCACATCCCAGGCTGACCAC	GGTCGTGGATAACACCAATAGC	ERCC1-202	189
Exon 11.1 of ERCC1	GAGCCCTTCTTGAAAGTACCCTG	CCCAGTGTAATAATAAATCGTCCTCC	ERCC1-208	33
Exon 10.2 of ERCC1	GAGAGAGCCCCAAATAAACACAACC	AAGGCGGGAGGACTGCTTGAGG	ERCC1-201	144
Exon 3.3 of CD3EAP	ATCCACCTGCCTTGACCTCCCA	CCAGGAACTATCCATCCACTCT	CD3EAP-201	107
Exon 3.2 of CD3EAP	GGAAGAAGCAGAGTCAGGAAAGCCG	GGAGGACGATTTATTATTACACTGGG	CD3EAP-202	211
Exon 3.1 of CD3EAP	GGCGGCATGTGCCTCTCTCT	CTGCTCACCTCAGGGAAGAAGAAAA	CD3EAP-203/C202	104/1339
Exon 14 of PPP1R13L	TTAGTAATCTGCCTTAGCCTTGGGA	TCTGGGTGGGAAACATTGGTCTCTA	PPP1R13L-201	142

B, qPCR
Primer name	Amplification position	Sense (5′-3′)	Antisense (5′-3′)
E8-10	Exon 8-10 of ERCC1	TGGAGAAGCTAGAGCAGGACTTC	GCATAAGGCCAGATCTTCTCTTG
E11.2	Exon 11.2 of ERCC1	TGTCCAAATGTCCTAAGAATGCAG	CTCACTAAAGGTAGGGGCTATTGGT
C2-3	Exon 2-3 of CD3EAP	TTCTCCTTGGAGGCGCTGA	CCTGCCAATTTGCCCTTGAC
C3.3	Exon 3.3 of CD3EAP	CTGGGATTATAGGTGTGAGCCACT	GAGGCAGGAGAATCGTTGGA
P1	Exon 1 of PPP1R13L	GGACGGTCGATTGGTCTGAAATTCTT	CTGCTTGGTCAGTTCATCCA
P2	Exon 2 of PPP1R13L	GGAGGAAGCCCCCAGGTGCCAGGAT	CTGCTTGGTCAGTTCATCCA
P5-6	Exon 5-6 of PPP1R13L	CGCAGACAGCGAGCTATGAA	CTCTCCCTCCAAGGCAACA
P14	Exon 14 of PPP1R13L	TTAGTAATCTGCCTTAGCCTTGGGA	GGTTTCCTGTCCCCAGTGATTTCCA
GAPDH	Glyceraldehyde 3-phosphate dehydrogenase	TGTTGCCATCAATGACCCCTT	CTCCACGACGTACTCAGCG

Affymetrix GeneChip

Total RNA from A549 and 16HBE cells were hybridized with Affymetrix Human Transcriptome Assay 2.0 (Affymetrix, Santa Clara, CA, USA), accordance with the manufacturer’s protocol. All detection sevice were performed by OE Biotech’s (Shanghai, China). Briefly, the raw data were normalized at the exon level and filtered using Expression Console (version 1.3.1; Affymetrix) by applying the Robust Multi-array Average algorithm. Alternative splice analysis was conducted by Transcriptome Analysis Console (version 1.0; Affymetrix). Differential exon or junction identified through splicing index as well as P-value calculated with One-Way Between-Subject ANOVA (Unpaired). The threshold was splicing index ≥2.0 or ≤−2.0. The splice index was defined as the expression of the exon normalized to the expression of the entire gene. Signal intensity of the Probe Selection Region (PSR) equations use log2 scale data. The score for the isoform was defined as the sum of the PSR scores [see Transcriptome Analysis Console(TAC)3.1 UserGuide].

3′ Rapid amplification of cDNA ends (3′RACE) analysis

Based on the structures of the previously described mRNAs (Fig. 1A), primers were designed to clone the termination region sequence of different isoforms (Table I). For 3′RACE experiments, a first reverse transcription step was performed using 3′-Full RACE Core Set version 2.0 (Takara D314; Takara Bio, Inc.). Amplification was then performed by two rounds of PCR. The first round was performed with a gene-specific primer from outer and the outer adaptor primer used in 3′RACE experiments, while a nested primer and the inner adaptor primer for 3′RACE were used in the second reaction. Gel analysis and sequencing of certain PCR products confirmed the gene specific product amplification.

Statistical analysis

Data analysis to determine the statistical significance and correlation coefficient were performed using R software (version 2.13.2). Differences in the splicing index of the lung cancer and adjacent normal tissues are depicted as the median values, and PCR data are expressed as the mean ± standard deviation. Statistical analysis was performed with IBM SPSS (version 20.0; IBM Corp., Armonk, NY, USA) and GraphPad Prism software (version 5.0; GraphPad Software, Inc., San Diego, CA, USA). Comparative analysis was conducted by independent samples t-test to determine the significance of differences between groups. A statistically significant difference was considered to be indicated by a P-value of <0.05.

Results

Structural characteristics of 19q13.2-3

Overlapping genes appeared to be closely arranged, which may result in the property of signal transitivity. There was direct evidence that CD3EAP and PPP1R13L share the same first exon transcriptional domain, while the transcription termination site of ERCC1 is adjacent to a conjunct transcription start sites of CD3EAP and PPP1R13L. Peaks of H3K27 acetylation, H3K4 trimethylation and CpG islands were identified near the first exon of CD3EAP and PPP1R13L, while these peaks were adjacent to the terminal exon of ERCC1, histone modifications of H3K4me3 and H3K27ac in the CpG island region are often found near active regulatory elements and is conducive to DNA unwinds the double helix (Fig. 1A). Co-expression genes are often functionally associated; in the present study, bioinformatics analysis of protein networks revealed that both CD3EAP and ERCC1 bind to TATA box binding protein (TBP). In addition, PPP1R13L was observed to be indirectly associated with TBP through p53 or SP1 (Fig. 1B).

Differentially expressed exons in normal and tumor tissues

In order to precisely depict the expression correlation between ERCC1, CD3EAP and PPP1R13L, differential expression analysis of exon resolution in tumor and adjacent normal tissues was performed. The expression of the majority of exons varied between lung cancer tissue and the adjacent normal tissue, and marked differences were observed in 11 exons of the ERCC1 gene (E11) and the 2-3 exons of CD3EAP gene (C2-3). In tumor tissues, the differential expression of exons in a single gene were stronger compared with that in adjacent normal tissues, which further suggests that the tumor tissue preferentially expresses a single alternative splicing isoform. According to the order of CD3EAP gene expression levels from low levels to high levels, P1 exhibited a similar trend to C1, E11 and C3 are similar (Fig. 2A).

Figure 2 Gene differential expression analysis and alternative splicing analysis of LUAD and LUSC data obtained from TCGA. (A) Heatmaps depict the exon expression levels in the tumor and adjacent tissues. The mean of each column is defined as 0, while low and high expression is indicated by blue and red bars, respectively. Exons of these target genes (rows) and samples (columns) were sorted by CD3EAP gene expression. (B) Alternative splicing event in LUAD and LUSC are shown. TCGA Splice Seq calculation of alternative splicing event of ERCC1, CD3EAP and PPP1R13L was performed. ERCC1, excision repair cross-complementation group 1; CD3EAP, CD3e molecule associated protein; PPP1E13L, protein phosphatase 1 regulatory subunit 13 like; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; TCGA, The Cancer Genome Atlas.

Analysis of alternative splice events

Compared with the normal tissue, the PSI value of E-AT-11 decreased and that of E-AT-10.2 increased in LUAD and LUSC tissues. The alternative promoter and alternative terminator of ERCC1 converge to the gene center, indicating that ERCC1 can express a shorter transcript in lung cancer tissues (Fig. 2B). It should be noted that we only focused on overlapping genetic regions.

Transcription-associated analysis of gene and exon levels

At the gene level, CD3EAP was significantly positively correlated with PPP1R13L in normal (P<0.01) and tumor tissues (P<0.01) (Fig. 3A). Negative and/or weak correlation was detected between CD3EAP and ERCC1 in normal tissues. Whereas in tumor tissues, CD3EAP was significantly positively correlated with ERCC1 (P<0.01), meanwhile ERCC1 was significantly positively correlated with PPP1R13L (P<0.01). In addition, ERCC1 was negatively correlated with PPP1R13L in normal tissues, whereas these genes exhibited weakly positive correlations in tumor tissues, but the correlation was not significant (P>0.05).

Figure 3 The Spearman correlation coefficient of (A) gene pairs and (B) exon pairs were calculated in lung adenocarcinoma and lung squamous cell carcinoma. The exons examined included E9-E11, C1-C3 and P1-P3. Positive and negative correlation was indicated by blue and red circles, respectively. The Spearman correlation coefficient varied between 0 and 1, and a larger circular area indicated a closer correlation. E9-E11, from the 9 exon of the ERCC1 gene to the 11 exon; C1-C3, from the 1 exon of the CD3EAP gene to the 3 exon; P1-P3, from the 1 exon of the PPP1R13L gene to the 3 exon. ERCC1, excision repair cross-complementation group 1; CD3EAP, CD3e molecule associated protein; PPP1E13L, protein phosphatase 1 regulatory subunit 13 like.

At the exon level, there was a significant positive correlation between the exon pairs with overlapping positions. C1 was significantly associated with P1 (P<0.01), while C3 was significantly associated with E11 in normal and tumor tissues (P<0.01) (Fig. 3B). The pattern was defined as a collection of exons with similar expression behaviors and indicated that there are certain co-expression patterns of those overlapping genes in the 19q13.3 region. We only focused on exons in the overlapping region.

qPCR validation in NSCLC tissue samples

In order to validate the results of bioinformatics analysis, the mRNA expression levels of ERCC1, CD3EAP and PPP1R13L were compared in lung tumor tissues of 15 patients by Spearman rank correlation analysis. Compared with the adjacent normal tissue, the expression levels of characteristic exons in cancer tissues were increased. C2 was significantly associated with P1 and P2, while C3 and E11 expression levels also exhibited a close positive correlation (Fig. 4).

Figure 4 Quantification of characteristic exon expression and correlation analysis in 15 non-small cell lung cancer tissue samples. (A) Compared with the corresponding adjacent tissues, the expression of characteristic exons in the carcinoma tissues increased significantly. Data were normalized for equal loading. Values are expressed as the mean with 95% confidence interval. (B) The correlation between the expression levels of characteristic exons was investigated by Spearman rank correlation analysis in the tissues of 15 patients. ERCC1, excision repair cross-complementation group 1; CD3EAP, CD3e molecule associated protein; PPP1E13L, protein phosphatase 1 regulatory subunit 13 like.

Quantitative change of alternative splicing isoforms

The exon or construct abundances were described using the Human Transcriptome Assay (Fig. 5A). To facilitate the experimental validations, several Affymetrix transcript isoforms with different architectural features were finally selected. Compared with the control, the short transcript containing E2-10 was upregulated by 3.28-fold in A549 cells after cisplatin treatment, whereas it was downregulated by 2.55-fold in 16HBE cells. The full-length transcript containing E 1-11 was mainly expressed in 16HBE cells, where it was upregulated by 5.24-fold. These transcripts containing C1 were downregulated in A549 cells and upregulated in 16HBE cells. The posterior segments of the PPP1R13L gene containing exons 9 to 14 was upregulated in A549 cells (isoform score=3.49). By contrast, the full-length transcript containing P1-14 was upregulated in 16HBE cells. These results indicated that the short transcripts of ERCC1 (exons 2-10), CD3EAP (exons 2-3) and PPP1R13L (exons 9-14) are co-expressed in A549 cells. The full-length transcripts of ERCC1, CD3EAP and PPP1R13L genes are co-expressed in 16HBE cells.

Figure 5 Affymetrix transcriptome microarray analysis and polymerase chain reaction verification. (A) The transcript levels of two cell lines in the CDDP group was compared with the control group, and almost 90% of all exons in ERCC1, CD3EAP and PPP1R13L were detected. The exon or construct intensity signals were concentrated in the range of 3-8 (log2-transformed Probe Selection Region intensity value), while the range of the Splicing Index of the exons compared with the control was between -2 and 2 (from blue to red, respectively). (B) Quantification of specific exon expression changes following treatment with 4 μg/ml CDDP. Data were normalized for equal loading. The x-axis shows the name of the exon specific primer. Values are expressed as the mean ± standard deviation. *P<0.05. (C) Identification of transcription termination sites. The products of the 3′RACE reactions were separated on 2% agarose gels and visualized by ethidium bromide staining. Lane 1 is the 100 bp DNA ladder, and the marker fragment sizes were approximately 100, 200, 300, 400, 500 and 600 bp. Labels under the lanes represent different groups of 3′RACE primers. The expected bands were obtained in the 3′RACE inner reaction, revealing the presence of transcription termination sites of ERCC1, CD3EAP and PPP1R13L. CDDP, cis-diammineplatinum(II) dichloride; ERCC1, excision repair cross-complementation group 1; CD3EAP, CD3e molecule associated protein; PPP1E13L, protein phosphatase 1 regulatory subunit 13 like; 3′RACE, 3′ rapid amplification of cDNA ends.

Relative quantification of the co-expression transcript and 3′RACE identification

The co-expression characteristics of exons or constructs were verified by qPCR, which demonstrated that these clones were indeed differentially expressed. The expression of ERCC1 3′UTR was invariant in A549 cells, and the downregulation of the relative isoform score was mainly attributed to the high expression of the short transcript, while the expression levels of downstream genes CD3EAP and PPP1R13L were slightly increased. The expression of ERCC1 3′UTR was significantly increased in 16HBE cells, and simultaneously, the expression levels of downstream genes CD3EAP and PPP1R13L were enhanced, consistent with the cDNA microarray results (Fig. 4B). 3′RACE-PCR was used for further investigation, to determine the transcription termination sites of human ERCC1, CD3EAP and PPP1R13L. Referring to the transcript informations of the Ensembl database, the expected bands listed in Table I were obtained in the 3′RACE reaction, revealing the transcription termination sites of ERCC1, CD3EAP and PPP1R13L (Fig. 5B).

Discussion

Epigenetic mechanisms that may be involved in the development of cancer have attracted considerable research interest (31). Abnormal DNA histone modifications may be associated with aberrant gene expression patterns. Peaks of H3K27 acetylation and H3K4 trimethylation, and a CpG island were identified near the first exon of CD3EAP and PPP1R13L, which are often identified near the active regulatory elements, suggesting that CD3EAP and PPP1R13L may initiate transcription from the same promoter. In human cell lines, the pattern of histone H3K27 acetylation, H3K4 trimethylation and the CpG island suggests a single promoter, as a universal chromatin modification at the transcription start site of active genes and its levels reflect the amount of transcription and exon splicing (32,33). Furthermore, shared epigenetic modifications were observed to be a potential mechanism for gene co-expression patterns (34), which may additionally be used as cancer biomarkers for diagnostic and prognostic purposes, as well as predictive markers of the response to targeted therapies.

Alternative splicing, as an important process that modifies mRNA isoforms, allows cells to generate a great number of protein and mRNA isoforms with diverse functional and regulatory properties. The plasticity of alternative splicing is often exploited by cancer cells to produce isoform switches that promote cancer cell survival, proliferation, metastasis and drug resistance (35). Differential isoform expression in human tumors correlates with the cancer progression (36,37). Ensembl transcript databases revealed multiple alternative spliceosomes of ERCC1, CD3EAP and PPP1R13L gene. Unlike genomic data, such as copy number variation, systematic analyses of alternative splicing co-expression patterns and associated mechanisms are currently lacking despite their important role in cancer. The present study provided evidence that the different 3′UTR termination sites enable ERCC1 gene not only to produce different mRNAs, but also to release distinct sets of alternative splicing interference signals to downstream genes CD3EAP and PPP1R13L. Furthermore, the overlap region between ERCC1, CD3EAP and PPP1R13L may be involved in linking upstream and downstream genes, and may have potential applications in cisplatin resistance in NSCLC, indicating a novel transcription regulation pattern.

In multicellular organisms, cell death serves an important role in the regulation and maintenance of homeostasis (38,39). Cell death is a major mechanism for the elimination of cells through DNA damage and organelle stress. Apoptosis, the programmed cell death process that is most widely studied and possibly best understood, is the antithesis of proliferation; therefore, it has received attention as an anticancer mechanism (40,41). The evasion of apoptosis is one of the hallmarks of drug resistance. Clearly, in order for tumor cells to ultimately produce an aggressive malignant tissue, they must survive and may be required to evade apoptosis. The results of the current study revealed that ERCC1 3′UTR was able to activate the expression of downstream genes CD3EAP and PPP1R13L. However, whether this co-expression pattern affects the expression of PPP1R13L and further affects apoptosis remains uncertain. The rationale here is that, if cell death processes are activated by anticancer chemotherapies and radiotherapies, it is possible to induce apoptosis through the reversal of other cell death mechanisms (as some cells can escape apoptosis and undergo necrosis, the cell death mechanisms needs to be altered, in order for cells to undergo apoptosis, rather than necrosis) and enhance the sensitivity of the tumor cells to the chemotherapy. More targeted work in this area is required to verify these mechanisms in lung cancer, and more effective cancer therapies that are applicable to a broad range of tumor types will ultimately emerge as a result.

In conclusion, the present study demonstrated that the expression of ERCC1-202 influences the transcription levels of downstream genes, and plays a role in mechanisms connecting the transcription pattern of three genes, the formation of overall expression patterns produced by the special spatial associations, and in the realization of their respective functions of the network cooperative genes. ERCC1-202 activates the expression of the PPP1R13L gene, further affecting the apoptosis function mediated by p53 and affecting the mode of cell death.

Acknowledgments

The authors are particularly grateful to Professor Chen Wen of Sun Yat-sen University, Guangzhou, China for providing the 16HBE cell line.

Funding

This study was supported by the National Natural Science Foundation of China (grant nos. 81773470 and 81273118).

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Authors’ contributions

GZ and PX provided the study concept and design and drafted the manuscript, performed all the analyses and interpreted the data of these results. SC collected the clinical samples and confirmed the pathological diagnosis and critically revised the manuscript. TY, MX and QZ performed the cellular experiments and critically revised the manuscript. YC, CJ, JY and SW coordinated the data collection. XL was involved in drafting the manuscript and revising it critically for important intellectual content, and provided final approval for the submission. The final version of the manuscript has been read and approved by all authors.

Ethics approval and consent to participate

Informed consent was obtained from all patients, and the protocol was approved by the Institutional Review Board of China Medical University prior to the study. All activities involving human subjects were conducted under full compliance with the government policies and the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References