RRAS: A key regulator and an important prognostic biomarker in biliary atresia

Abstract

AIM: To characterize the differentially expressed gene profiles in livers from biliary atresia (BA) patients including, ascertain genes, functional categories and pathways that play a central role in the pathogenesis of BA, and identify the novel prognostic markers for BA.

METHODS: Liver tissue samples from control patients, neonatal cholestasis patients, and BA patients at the age of < 60 d, 60-90 d, and > 90 d were pooled for DNA microarray analysis. Bioinformatics analysis was performed using, series test cluster of gene ontology, and Pathway-Finder software. Reverse-transcription polymerase chain reaction was performed to confirm changes in selected genes. Relation between RRAS gene expression and prognosis of 40 BA patients was analyzed in a 2-year follow-up study.

RESULTS: The 4 identified significant gene expression profiles could confidently separate BA liver tissue from normal and other diseased liver tissues. The included genes were mainly involved in inflammation response and reconstruction of cellular matrix. The significant pathways associated with BA were primarily involved in autoimmune response, activation of T lymphocytes and its related cytokines. The RRAS, POMC, SLC26A6 and STX3 genes were important regulatory modules in pathogenesis of BA. The expression of RRAS was negatively correlated with the elimination rate of jaundice and positively correlated with the occurrence rate of cholangitis.

CONCLUSION: Autoimmune response mediated by T lymphocytes may play a vital role in the pathogenesis of BA. The RRAS gene is an important regulatory module in the pathogenesis of BA, which may serve as a novel prognostic marker for BA.

Key Words: Biliary atresia, DNA microarray, Bioinformatics, RRAS, Prognostic biomarker

INTRODUCTION

Biliary atresia (BA) is a devastating disease of infants, invariably leading to cirrhosis, end-stage liver disease, and death if untreated[1]. A recent review reported that BA may involve a primary perinatal hepatobiliary viral infection and a secondary autoimmune-mediated bile duct injury[2]. However, the cause and pathogenesis of BA remain largely unknown.

Microarray technology, emerged as an indispensable research tool for gene expression profiling, has been used to study the mechanism underlying BA, and allows the simultaneous analysis of thousands of transcripts within a single experiment[3]. Some studies have been performed to investigate the gene expression profiling of livers from BA patients[4-6]. However, to our knowledge, none of them was designed to identify genes that play a key role in the pathogenesis and prognosis of BA. In the current study, DNA microarrays for whole genome gene expression and bioinformatics analysis were used to characterize the differentially expressed gene patterns of normal livers and livers from BA patients at different ages, as well as to ascertain the genes and pathways that play a central role in the pathogenesis of BA. Furthermore, reverse-transcription polymerase chain reaction (RT-PCR) was performed to confirm the changes in selected genes. The relation between selected gene expression and prognosis of BA patients was also analyzed.

MATERIALS AND METHODS

Patients and specimens

Biopsy specimens were obtained from livers of 9 patients with BA, 3 patients with neonatal cholestasis and 3 control patients suffering from liver trauma (as normal control) at Children’s Hospital of Fudan University from November 2007 to December 2008. Nine patients with BA were further divided into < 60 d group (n = 3), 60-90 d group (n = 3) and > 90 d group (n = 3). Liver samples from 3 groups of BA patients, neonatal cholestasis and control groups were immediately dissolved in a RNAlater RNA stabilization reagent (Qiagen, Germany) and then stored at -80°C. Liver samples from each group were pooled and total RNA was isolated from them for DNA microarray experiments. Clinical data about these patients are summarized in Table 1. Liver samples were collected from the other 14 patients with neonatal cholestasis and 40 patients with BA for RT-PCR experiments. All subjects gave their informed consent to participate in the study which was approved by the Research Ethics Committee of Fudan University.

Table 1 Microarray analysis showing clinical characteristics of biliary atresia patients.

Case No.	Gender	Age	TB/DB	ALT/AST	AKP/GGT	Albumin	Disease	Group
1	Female	50 d	171/130	132/254	604/609	35.8	BA	1
2	Male	49 d	291/231	148/155	581/408	39.4	BA	1
3	Male	57 d	148/117	189/166	493/535	35.2	BA	1
4	Female	73 d	145/118	111/153	460/1460	36.3	BA	2
5	Male	84 d	160/127	100/149	713/1278	37.3	BA	2
6	Female	66 d	129/108	121/165	632/1235	39.2	BA	2
7	Female	103 d	151/112	85/62	451/360	39.4	BA	3
8	Female	97 d	118/89	74/78	522/501	34.3	BA	3
9	Male	110 d	155/121	105/97	377/912	35.4	BA	3
10	Female	77 d	102/89	201/137	234/317	39.4	Cholestasis	4
11	Male	64 d	137/108	404/267	584/1044	37.2	Cholestasis	4
12	Female	55 d	144/112	389/266	612/1339	41.0	Cholestasis	4
13	Male	4 yr	16/9	33/35	200/50	39.4	Liver trauma	5
14	Male	6 yr	10/4	20/25	192/44	40.1	Liver trauma	5
15	Male	4 yr	12/4.7	29/37	101/38	37.1	Liver trauma	5

TB: Total bilirubin; DB: Direct bilirubin; ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; AKP: Alkaline phosphatase; GGT: γ-glutamyl transferase; BA: Biliary atresia.

RNA extraction, processing and microarray analysis

Total RNA was extracted from liver tissue samples using the Trizol reagent (Invitrogen) according to its manufacturer’s protocol, and then further purified using a NucleoSpin RNA clean-up kit (Macherey-Nagel, Germany). Quantification analysis of RNA was performed on a spectrophotometer and quality of RNA was analyzed by denaturing formaldehyde gel electrophoresis. Five micrograms of total RNA from each group was amplified and labeled with biotin using an Illumina total Prep RNA amp kit (Ambion, Austin,TX, USA) and hybridized to Illumina’s Sentrix Human-6 (Version 3) Expression BeadChips containing 48 000 transcripts (Illumina, San Diego, CA, USA). Three duplicated chips were also used in each group to test the variations in duplications from the same pooling. The hybridized Illumina chips were scanned on a BeadArray reader (Illumina, San Diego, CA, USA) and microarray analysis was performed using the BeadStudio software (Illumina, San Diego, CA, USA). Raw data were normalized using the cubic spline method and the resulting genes were filtered. Finally, only genes with a differential expression score (Diffscore) greater than 20 or less than -20 were included.

Bioinformatics analysis of differentially expressed genes

Differentially expressed genes were analyzed by a series test of cluster (STC) to search a set of model expression profiles that were distinct in 5 groups as previously described[7,8]. These profiles were assigned to significant gene ontology categories using series test cluster of gene ontology (STC-GO)[9], and analyzed with the Pathway-Finder software to obtain the significance of pathway categories[10,11]. Moreover, dynamic gene networks were constructed to find the key genes that may play a central role in the pathogenesis of BA[12,13]. The principle and algorithmic details are available in supplementary data.

Validation of microarray data by RT-PCR

RT-PCR was performed on liver tissue samples from 14 patients with neonatal cholestasis and 40 patients with BA to confirm changes in selected genes, including RRAS, POMC, SLC26A6 and STX3. Total RNA was extracted from liver tissue samples and purified as previously described[14]. Five micrograms of total RNA was reverse transcribed using MMLV reverse transcriptase (Merck, Germany) and random primers in a 20 μL reaction volume at 42°C for 1 h. Oligonucleotide primers for the RRAS, POMC, SLC26A6, STX3 and β-actin are shown in Table 2. The PCR conditions were as follows: an initial denaturation at 94°C for 5 min, followed by 35 cycles of denaturation at 94°C for 30 s, annealing at 58°C for 30 s, extension at 72°C for 30 s, and a final extension at 72°C for 7 min. The PCR products were separated by electrophoresis and UV illuminated on a 2% agarose gel containing ethidium bromide (0.5 μg/mL). The gel image was stored using the UVP gel documentation system 5000 (Ultra-Violet Products Ltd., Cambridge, United Kingdom). Expression levels of the selected genes relative to β-actin were measured with densitometric scanning using the multi-analysis/PC system (Bio-Rad, Hercules, California, USA).

Table 2 Sequences of primers in selected genes used in reverse-transcription polymerase chain reaction.

Gene name	Primer sequences
RRAS	F: TTGGTCGGGAACAAGGCAGAT
	R: CTCGTCCACGTTGAGACGCAGT
POMC	F: GAGAGCAGCCAGTGTCAGG
	R: GAAGTGGCCCATGACGTACT
SLC26A6	F: CGGTATCCTGTGCGTGACT
	R: GGAAGTGCCAAACAGGAAGT
STX3	F: GGCAAAAAGACAACCGATGA
	R: TGTCGTGAAGCTCCTTGATG
β-actin	F: GGGAAATCGTGCGTGCATT
	R: CAGGCAGCTCGTAGCTCTT

Prognostic biomarker and follow-up research

Fibrosis of liver biopsy specimens from 40 patients with BA was histologically classified into different groups. Elimination rate of jaundice (TB < 20 μmol/L) within 6 mo after operation, 2-year survival rates of cholangitis patients and of 40 BA patients were calculated. The diagnostic criteria for cholangitis included fever, increasing jaundice, acholic stools, with other causes of infection excluded. Follow-up data were obtained from our outpatient and inpatient referrals, as well as from interview by telephone or questionnaires. These patients were further classified based on the follow-up data, including presence of jaundice 6 mo after operation, occurrence of cholangitis within 2 years after operation, and 2-year survival rate.

Statistical analysis

Data were expressed as mean ± SD. Variations in duplications were detected by Fisher’s exact test, χ² test, t-test and Cochran-Mantel-Haenszel test using the STATA 8.0 software (Stata Co., College Station, TX, USA). Pair-wise test was used to confirm the limited variations in duplications from the same pooling. P < 0.05 was considered statistically significant.

RESULTS

Differentially expressed gene profiles in liver tissue samples from BA patients

Total RNA was extracted from liver tissues of the normal group, neonatal cholestasis group, and 3 groups of BA patients at different ages (< 60 d, 60-90 d and > 90 d). Denaturing formaldehyde gel electrophoresis showed no degradation (data not shown). Illumina’s Sentrix Human-6 (Version 3) Expression BeadChip was used for each of pooled liver tissue samples from the 5 groups. Pair-wise test confirmed a limited variation in duplications from the same pooling (data not shown). A total of 795 differentially expressed genes were identified from different groups with a Diffscore greater than 20 or less than -20. Further STC analysis yielded 80 expression profiles. Of these expression profiles, 20 were statistically significant (P < 0.05) and 4 had the lowest P value (Figure 1). These 4 expression profiles could confidently separate livers in groups of BA patients from those in normal and neonatal cholestasis groups. Specifically, all the differentially expressed genes in 5 groups were included in profile 76, which showed no significant difference in the 3 groups of BA patients at different ages (< 60 d, 60-90 d and > 90 d). The 611 genes represented in profile 75 were mainly involved in inflammation mediated by activation of T lymphocytes, and reconstruction of extracellular matrix. As shown in Figure 1, the global expression level of the genes in profile 75 was much lower in livers from the group of BA patients at the age of < 60 d than from the groups of BA patients at the age of 60-90 d and > 90 d. The 372 genes represented in profile 74 were associated with an apoptotic pathway and inflammatory response mediated by nuclear factor-κB (NF-κB). The global expression level of profile 74 genes was much lower in the group of BA patients at the age of 60-90 d than in the groups of BA patients at the age of < 60 d and > 90 d. Moreover, the 285 genes represented in profile 49 were mainly involved in inflammatory response mediated by the major histocompatibility complex (MHC) class II antigen. The global expression level of profile 49 genes was much higher in the 3 groups of BA patients at different ages (< 60 d, 60-90 d and > 90 d) than in the normal and neonatal cholestasis groups. Little variance in gene expression was observed neither in the 3 groups of BA patients at different ages (< 60 d, 60-90 d and > 90 d) nor in the normal and neonatal cholestasis groups (See supplementary data for a complete list of these 4 expression profiles).

Figure 1 Four most significant expression profiles in liver samples from biliary atresia patients. 0: Normal control group; 1: Neonatal cholestasis group; 2: Group of biliary atresia (BA) patients > 90 d; 3: Group of BA patients at the age of 60-90 d; 4: Group of BA patients < 60 d. Y axis represents the expression change expressed as log2 [v(i)/v(0)].

Involvement of significant pathways in BA focused on autoimmune response associated with inflammatory response of T lymphocytes

Based on the Kyoto Encyclopedia of Genes and Genomes Database and the most significant 4 gene expression profiles, Fisher’s exact test and χ² test were performed to identify the significant pathways involved in BA as previously described[15]. The significant pathways (P < 0.01) highly associated with BA were mainly focused on (1) autoimmune response associated with asthma, systemic lupus erythematosus, allograft rejection graft-versus-host disease, type I diabetes mellitus, antigen processing and presentation; (2) activation of T lymphocytes and inflammatory response including transendothelial migration of T leukocytes, cell adhesion molecules, NF-κB and MAP kinase (MAPK) signaling pathways, chemokine signaling pathway, cytokine-cytokine receptor interaction, transendothelial migration of leukocytes, Toll-like receptor signaling pathway; and (3) reconstruction of extracellular matrix, including matrix-metalloproteinases. The significant pathways are shown in Table 3.

Table 3 Significant pathways involved in pathogenesis of biliary atresia.

Pathway name	P value	Profile No.
Cell adhesion molecules	0.000118	Profile49
Regulation of actin cytoskeleton	0.000739	Profile49
T Leukocyte transendothelial migration	0.001738	Profile49
Asthma	0.002023	Profile49
Allograft rejection	0.003243	Profile49
Systemic lupus erythematosus	2.44E-05	Profile74
Lysosome	0.0002109	Profile74
NF-kappa B signaling pathway	0.0036605	Profile74
MAPK signaling pathway	0.0052322	Profile74
Allograft rejection	0.0058515	Profile74
Graft-versus-host disease	0.0071277	Profile74
Type I diabetes mellitus	0.00781	Profile74
Chemokine signaling pathway	1.81E-08	Profile75
Matrix_Metalloproteinases	6.52E-07	Profile75
Cytokine-cytokine receptor interaction	3.59E-05	Profile75
T cell receptor signaling pathway	4.34E-05	Profile75
Antigen processing and presentation	0.000337	Profile75
Leukocyte transendothelial migration	0.0010211	Profile75
Lysosome	2.09E-07	Profile76
Toll-like receptor signaling pathway	0.000284	Profile76
T cell receptor signaling pathway	0.000388	Profile76
Chemokine signaling pathway	0.000755	Profile76
Asthma	0.000841	Profile76
Matrix_Metalloproteinases	0.001402	Profile76
Allograft rejection	0.001697	Profile76

Construction of dynamic gene networks

Dynamic gene networks[16] were constructed to find the key regulators that may play a central role in the pathogenesis of BA (Figure 2). Circles indicate genes in the 4 expression profiles, solid lines indicate direct interactions, size of circles indicates their interactions with other molecules, coloring is classified according to the k core and red indicates high k core. The genes with the highest degree and k-core from Figure 2, are listed in Table 4, including the related RAS viral (r-ras) oncogene homolog (RRAS), POMC, SLC26A6 and STX3 genes, indicating that they play a crucial role in the pathogenesis of BA.

Figure 2 Dynamic gene networks constructed showing the key regulators that may play a central role in the pathogenesis of biliary atresia. Circles indicate genes in the 4 expression profiles, solid lines indicate direct interactions, and size of circles indicates their interactions with other molecules. Coloring is classified according to the k core, and red indicates high k core.

Table 4 Genes with the highest degree and k-core in dynamic gene networks.

Gene symbol	Definition	Degree	k-core
RRAS	Homo sapiens related RAS viral (r-ras) oncogene homolog (RRAS), mRNA	12	6
POMC	Homo sapiens POMC, transcript variant 1, mRNA	12	6
SLC26A6	Homo sapiens SLC26A6, transcript variant 3, mRNA	12	6
STX3	Homo sapiens STX3, mRNA	10	6

Expression of RRAS, POMC, SLC26A6 and STX3 genes in liver tissue samples from patients with BA confirmed by RT-PCR

The mRNA expression levels of RRAS, POMC, SLC26A6 and STX3 in liver tissue samples from 40 patients with BA and 14 patients with neonatal cholestasis, measured in order to validate the results derived from microarray data, were significantly higher in liver tissue samples from patients with BA than from those of neonatal patients with cholestasis (P < 0.05, Table 5, Figures 3 and 4). The mRNA expression level of the RRAS gene increased 1.9-fold in BA patients (P < 0.05).

Figure 3 Reverse-transcription polymerase chain reaction showing expression levels of RRAS, POMC, SLC26A6, and STX3 genes. BA: Biliary atresia; Control: Neonatal cholestasis.

Figure 4 Reverse-transcription polymerase chain reaction showing significantly higher relative expression levels of RRAS, POMC, SLC26A6 and STX3 genes in biliary atresia patients (n = 40) than in neonatal cholestasis patients (n = 14). ^aP < 0.05 vs liver tissue samples from neonatal cholestasis patients.

Table 5 Reverse-transcription polymerase chain reaction showing relative expression levels of RRAS, POMC, SLC26A6 and STX3 (mean ± SD).

Group	POMC	SLC26A6	RRAS	STX3
Biliary atresia (n = 40)	0.58 ± 0.090	0.43 ± 0.054	0.89 ± 0.103	0.61 ± 0.074
Neonatal cholestasis (n = 14)	0.41 ± 0.081	0.30 ± 0.029	0.47 ± 0.074	0.51 ± 0.045
P-value	0.031	0.023	0.004	0.017

Correlation between expression of RRAS in liver tissue samples and prognosis of BA patients

To address whether the RRAS expression is associated with the prognosis of BA patients, we performed a 2-year follow-up study in 40 patients with BA. Six months after operation, The RRAS expression level was significantly higher in patients with their jaundice not eliminated than in those with their jaundice eliminated (P = 0.007). Furthermore, the expression level of RRAS was significantly higher in patients with cholangitis reoccurred 3 or more times than in those with no cholangitis recurred (P = 0.028). However, no significant difference in RRAS expression was found between the surviving and dead patients (P = 0.094, Figure 5). In addition, the fibrosis was more serious in group of BA patients at the age of > 60 d than in group of BA patients at the age of < 60 d (Table 6), which was consistent with that observed in profile 75.

Figure 5 Correlation between expression of RRAS in liver tissue samples and prognosis of biliary atresia patients within 2 years.

Table 6 Fibrosis scores for different groups of biliary atresia patients at different ages.

Group	Fibrosis score (n)					Total
	0	1	2	3	4
< 60 d	1	3	8	2	0	14
60-90 d	0	2	3	6	4	15
> 90 d	0	0	1	4	6	11
Total	1	5	12	12	10	40

DISCUSSION

The pathogenesis of BA has not yet been delineated. It has been shown that factors such as genetic susceptibility, congenital heteroplasia, and infectious and abnormal immune response lead to BA[17-23], and its clinical course and surgical outcome are correlated with the age of such patients[24-26]. Although there are some studies involving DNA microarrays in BA[4-6], very few studies are available on gene expression profiling of BA at its different stages of clinical course. That is why the clinicopathologic characteristics of BA vary with the age of such patients.

The differential gene expression patterns of RRAS in liver tissue samples from BA patients at different ages, as well as normal liver tissue samples and liver tissue samples from neonatal cholestasis patients were characterized in this study using the expression DNA microarray technology and bioinformatics. The 4 significant expression profiles identified using STC could confidently separate BA liver tissues from normal and diseased liver tissues. STC-GO analysis revealed that the genes represented in the 4 profiles were mainly involved in inflammatory response and reconstruction of extracellular matrix. Notably, as validated by fibrosis classification, profile 75 showed that the expression level of genes involved in fibrosis and inflammation was much lower in BA patients at the age of < 60 d than in those at the age of > 60 d, which may explain why BA patients at the age of < 60 d often have a good prognosis after a Kasai’s operation[27]. Additionally, this phenomenon may also result from fibrosis due to the continuous hepatic inflammatory response-induced activation of stellate cells[28]. Moreover, a set of genes were involved in apoptosis represented in profile 74, which is in agreement with the reported findings[29]. In this profile, the BA patients at the age of > 90 d and < 60 d showed obvious inflammatory response and apoptosis mediated by NF-κB, which might be associated with the inflammatory response of local bile ducts in BA patients at the age of < 60 d and severe inflammatory response induced by fibrosis in BA patients at the age of > 90 d.

Mack et al[30,31] showed that CD4⁺ Th1-mediated bile duct inflammation is responsible for the development of BA. Profile 74 in the present study contains a set of genes associated with MHC class II antigen-mediated Th1 inflammatory response, which is in agreement with the findings of Mack et al[31] and Osada et al[32]. It is well known that antigens associated with MHC class II can bind to T cell receptors of CD4⁺ Th1 cells, and thereby produce functional T lymphocytes. Furthermore, the significant pathways highly associated with BA were mainly focused on the autoimmune response, activation of T lymphocytes and its related cytokines, suggesting that autoimmune response mediated by T lymphocytes may play a vital role in the pathogenesis of BA, which is consistent with the widely accepted hypothesis of BA[2,22,23,32].

In this study, the RRAS, POMC, SLC26A6 and STX3 genes were found to be important regulatory modules in BA. The RRAS gene is a component of the MAPK signaling pathway with GTP kinase activity[33,34]. The MAPK pathway is associated with BA[35]. Based on the results of this study, it is reasonable to speculate that the RRAS gene plays an important role in the pathogenesis of BA. The human POMC gene is located on chromosome 2p23.3 encoding a preprohormone. The adrenocorticotropin hormone and α melanocyte-stimulating hormone are cleavage products of POMC, which are associated with immune regulation and participate in the pathogenesis of experimental autoimmune encephalomyelitis[36,37]. The SLC26A6 is an anion exchanger involved in the secretion of bile acid. The STX3 has been implicated in the development and differentiation of dendritic cells[38,39]. Nonetheless, the precise role of these genes in the pathogenesis of BA needs to be further elucidated.

Given the key role of RRAS gene in the pathogenesis of BA, we evaluated the relation between the expression of RRAS and prognosis of BA patients through a 2-year follow-up study. The RRAS expression was negatively correlated with the elimination rate of jaundice and positively correlated with the occurrence rate of cholangitis, indicating that up-regulation of RRAS expression may inhibit the recovery of BA from jaundice and cholangitis via activation of the MAPK pathway, continuous inflammatory response, inflammatory cell infiltration, as well as activation of stellate cells[40]. However, no significant difference was found in the 2-year survival rate of patients with different expression levels of RRAS. Validation may require a long-term follow-up and a larger number of subjects.

In summary, autoimmune response mediated by T lymphocytes may play a vital role in the pathogenesis of BA. The RRAS gene and its related MAPK pathway are important regulatory modules in the pathogenesis of BA, which may serve as a novel prognostic marker for BA.

COMMENTS

Background

Biliary atresia (BA) is an inflammatory obliterative cholangiopathy with unknown etiology, leading to progressive fibrosis and cirrhosis. Although there are some studies involving DNA microarrays on BA, very few studies are available on gene expression profiling of BA at different stages of its clinical course, which is why the clinicopathologic characteristics of BA vary with the age.

Research frontiers

Microarray technology and bioinformatics, emerged indispensable research tools for gene expression profiling, have been used to study the pathogenesis of BA and allow the simultaneous analysis of thousands of transcripts within a single experiment. In this study, genes that play a key role in the pathogenesis and prognosis of BA were identified.

Innovations and breakthroughs

In the current study, DNA microarrays for whole genome gene expression and bioinformatics analysis were used to characterize the differentially expressed gene patterns in normal livers and livers from BA patients at different ages, as well as to ascertain genes and pathways playing a central role in the pathogenesis of BA. The results demonstrate that RRAS gene and its related MAP kinase (MAPK) pathway are important regulatory modules in the pathogenesis of BA, which may serve as a novel prognostic marker for BA.

Applications

By identifying genes and pathways playing a central role in the pathogenesis of BA, this study may represent a future strategy for therapeutic intervention in treatment of BA.

Terminology

RRAS gene is a component of the MAPK signaling pathway with GTP kinase activity. The MAPK pathway is associated with BA. Consequently, it is reasonable to speculate that the RRAS gene plays an important role in the pathogenesis of BA.

Peer review

This paper is interesting and valuable for other researchers. BA is a pediatric liver disease, which can lead to liver-related death and is the most common indication for liver transplantation in children. Therefore, the early proper treatment of BA with Kasai procedure is important in this group of patients. Early diagnosis of BA and knowledge of its prognostic factors can improve the treatment outcome of BA. Different prognostic factors have been described in the literature, but no report is available on RRAS as a key regulator and an important prognostic biomarker for BA identified by DNA microarray and bioinformatics.