Introduction
Cholangiocarcinoma (CCA) comprises a heterogeneous group of malignant tumours that are divided into intrahepatic, perihilar and distal CAA depending on the anatomical location. It accounts for more than 15% of all primary hepatobiliary malignancies. The incidence of CAA has gradually increased, with an average growth of 4.4% in the past 10 years [
1]. With a 5-year survival rate ranging from 7% to 20%, CCA remains one of the most malignant tumours and accounts for approximately 2% of all cancer-related death worldwide [
2]. Curative resection is the only potential treatment option for patients with CCA who were diagnosed at an early stage, whereas, for those diagnosed at an advanced stage, the treatment options are limited. Several clinical trials have proved the clinical benefit of chemotherapy (cisplatin and gemcitabine) as the first-line treatment for unresectable CCA [
2,
3]. Additional studies have also identified novel targeted therapies, such as pemigatinib, infigratinib and ivosidenib that have been FDA-approved as second-line treatment options [
4,
5]. After decades of research on immune checkpoints inhibitors (ICIs), the use of immunotherapies targeting programmed death-1 (PD-1), its ligand PD-L1 and cytotoxic T lymphocyte antigen 4 (CTLA4) have been reported to be effective in many cancer types. For example, bevacizumab combined with atezolizumab has become the first-line treatment regimen for advanced hepatocellular carcinoma (HCC) [
6]. Similar studies on immunotherapies for biliary tract carcinoma (BTC) have attracted much attention [
7]. Despite enormous advances in the diagnosis and therapies of cancers, long-term outcomes of patients with CCA remain unsatisfactory owing to its aggressive nature, early tumour recurrence and metastasis. Therefore, it is vital to identify effective biomarkers for early diagnoses and explore targets of driver pathways to better understand the molecular mechanisms involved in CCA development and progression.
Initially identified as the sequence with repeating non-receptor tyrosine kinase spore lysis A (SplA) and ryanodine receptor (RyR), the SPRY domain is one of the most abundant protein domains in mammals [
8,
9]. As annotated in SMART [
10], several hundred SPRY domains have been identified and classified and approximately 95 SPRY domains have been coded in the human genome [
11]. Moreover, accumulating evidence has indicated that the SPRY domains act as protein–protein interaction modules in several biological processes [
12]. Specific SPRY domain-containing genes have been reported to play important roles in several human diseases like Opitz syndrome and certain malignancies including melanoma and oral squamous cell carcinoma [
8,
13,
14]. Mutations in SPRY domain-containing genes have also been detected in medullary thyroid cancer and endometrial cancer [
15,
16]. Notably, SPRY-domain containing protein 4 (SPRYD4), a protein encoded by the SPRYD4 gene, has been demonstrated to serve as a tumour suppressor in HCC and inhibit tumour cell growth by inducing apoptosis [
17]. However, its role in CCA remains unexplored.
In this study, the significant downregulation of SPRYD4 was strongly associated with adverse clinical features and outcomes in patients with CCA. Moreover, a strong correlation between SPRYD4 expression and tumour immune infiltration was also demonstrated. Additionally, the overexpression of SPRYD4 inhibited the tumorigenicity and progression of CCA, which was associated with the S/G2 cell phase arrest and enhanced apoptosis. These findings highlighted the role of SPRYD4 as a tumour suppressor, prognostic marker and therapeutic target in CCA.
Methods
Data acquisition
RNA-sequencing data of CCA samples were downloaded from The Cancer Genome Atlas (TCGA) database in October 2022. GSE26566 (104 CCA and six bile duct samples), GSE32225 (149 CCA and six bile duct samples), GSE32958 (16 CCA and seven bile duct samples) and GSE76311 (92 CCA and 93 bile duct samples) datasets were obtained from the Gene Expression Omnibus (GEO) database to validate the expression levels of SPRYD4 in CCA. Additionally, the Gene Expression Profiling Interactive Analysis platform (GEPIA) was used to determine SPRYD4 expression levels [
18].
Tissue samples and patient follow-up
We obtained CCA and adjacent bile duct tissue samples from 82 patients with CAA at the Guangdong Provincial People’s Hospital (GPPH cohort) for validation. All enrolled patients were primarily diagnosed with CCA radiographically and confirmed pathologically. Overall survival (OS) was determined as the time from surgical resection to death or last contact, while disease-free survival (DFS) was defined as the period from surgical resection to tumour recurrence or metastasis. All patients were followed up until October 2022, and the median follow-up time was 23.3 months (range, 11.3–51). Enrolled patients’ clinicopathological characteristics including gender, age, carbohydrate antigen 19–9 (CA19-9) index, lymph node metastasis, lymphovascular invasion, tumour differentiation and TNM stage (AJCC 8th edition) were collated for correlation analysis. Additionally, the independent risk factors were identified using univariate and multivariate cox regression analyses. To evaluate the predictive value, Kaplan–Meier analyses were performed in the high-SPRYD4 and low-SPRYD4 groups in the GPPH cohort. All enrolled patients provided their written informed consent before participation. The study was approved by the Ethics Association of Guangdong Provincial People’s Hospital.
Functional enrichment analyses
The genes that co-expressed with SPRYD4 (|Spearman’s correlation coefficient|> 0.45 and
P < 0.05) were screened using cBioPortal. The Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) analyses were performed as described previously [
19]. The results were visualised using the R package ‘ggplot2’. To analyse the associations between SPRYD4 and its neighbouring genes, GeneMANIA and STRING databases were used to establish a gene network map and protein–protein interaction (PPI) network [
20,
21].
Multiple immune infiltration analyses
Based on an integrated web portal TISIDB for tumour and immune system interaction analysis [
22], we evaluated the relationships between SPRYD4 expression and immunostimulators, immunoinhibitors, tumour infiltrating lymphocytes including CD8
+ T cells, CD4
+ T cells, B cells, macrophages, dendritic cells, natural killer cells and neutrophils in CCA. Additionally, the correlations between SPRYD4 expression and gene markers of immune-infiltrating cells and immune checkpoints were analysed using Spearman’s correlation coefficients.
Cell culture and transfection
We obtained CCA cell strains including HUCCT1, RBE, CCLP-1, huh28, QBC939 and HCCC-9810 from Procell (Wuhan, China). All cells were cultured in Roswell Park Memorial Institute 1640 medium (Gibco, USA) supplemented with 10% foetal bovine serum and incubated at 37℃ with 5% CO
2. An EGFP-Puro-CMV-3 × Flag hSPRYD4 vector was constructed by Generay Biotech Co., Ltd. (Shanghai, China). Mixed with the pPACKH1 packaging plasmid, the SPRYD4-OV vector was transfected into 293 T cells. The virus particles were collected from the concentrated virus precipitation solution following the SBI instructions. The cells were infected with TUNDUX virus transducers. Following this, puromycin screening was used to identify the positive cells. For the generation of cell lines with SPRYD4 knockdown, two siRNAs targeting SPRYD4 were transfected into CCA cells to silence SPRYD4. The siRNAs used in the study were obtained from sequences (5’- 3’) shown below:
Cell proliferation and migration assays
Cell proliferation and migration assays were conducted as previously described [
23].
Flow cytometry
CCA cells were harvested, fixed in 75% ethanol and stored at 4℃ overnight. Then, the cells were pre-treated and stained with Propidium (PI) & RNase Staining Buffer (SIGMA) for cell cycle analysis, while Annexin V-APC (Invitrogen) was used for apoptosis detection. The percentage of CCA cells at different stages and statuses were evaluated using flow cytometry (Novocyte D2060R, Agilent).
Real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC)
RT-qPCR and IHC were performed as described previously [
23]. The primer pairs used for RT-qPCR are listed in Table S
1. TUNEL Detection Kit (Alexa Fluor 640) was obtained from Yeasen Biotechnology (Shanghai, China).
Animal experiments
To establish xenograft mouse models, 1 × 106 HUCCT1 SPRYD4-OV and control group cells were injected subcutaneously into 6-week-old male BALB/c-nude mice (GemPharmatech, China) (n = 6 per group). The tumour volume was measured and recorded using a calliper every 10 days. Fifty days after implantation, the mice were sacrificed by dislocation of cervical vertebra and then the xenografts were removed, weighed, recorded and used in IHC analysis to detect the levels of SPRYD4, Ki67 and Tunel. The Ethics Association of Guangdong Provincial People’s Hospital approved the animal experiments. All 6-week old male BALB/c nude mice were purchased from GemPharmatech (Jiangsu, China).
Statistical analysis
Student’s t-test was performed for the statistical analysis between continuous parameters, while χ2 test or Fisher’s exact test was used to evaluate qualitative variables in vivo and in vitro. All statistical analyses were performed using the SPSS version 24.0 and R software version 4.0.1. P < 0.05 was considered statistically significant.
Discussion
Identification of novel biomarkers of CCA development and progression aids in the development of therapeutic targets and improvement of outcomes in patients with CCA. To the best of our knowledge, this study is the first to identify that SPRYD4 was downregulated in CCA tissues compared to normal bile duct tissues and works as a tumour suppressor in CCA. Moreover, low SPRYD4 expression in CCA was also associated with poor tumour differentiation, positive lymph node metastasis and advanced TNM stage. In the study cohort, patients with CCA having low SPRYD4 expression had the worst survival, highlighting the predictive ability of SPRYD4 in CCA prognosis. Furthermore, in vitro experiments revealed that SPRYD4 over-expression inhibited CCA cell proliferation and migration, while the proliferative and migratory capacity of CCA cells was significantly enhanced after SPRYD4 deletion. Additionally, the tumour-inhibitory effect of SPRYD4 was validated in vivo using xenograft mouse models.
The uncontrolled proliferation of tumour cells is the most vital biological behaviour of malignancies, which is mainly based on the dysfunction of the cell cycle and apoptosis regulation [
25,
26]. Functional enrichment analyses revealed that SPRYD4 and its neighbour genes were mainly enriched in cell growth, cell proliferation and apoptotic processes, which were further validated using flow cytometry. Consistent with previous reports [
17], the over-expression of SPRYD4 triggered the S/G2 phase arrest and promoted apoptosis in CCA cells. Accumulating evidence has suggested that cytokine-dependent kinase 2 (CDK2) plays an essential role in cell cycle transition and DNA repair response (DDR) [
27,
28]. Activated by binding to Cyclin A2 (CCNA2) and cyclin E1/2 (CCNE1/2), CDK2 is a vital cell-cycle regulator that drives G1/S transition, which regulated DNA initiation and replication throughout the S phase [
29,
30]. In the current study, bioinformatic analyses revealed that the expression of SPRYD4 correlated negatively with CDK2 and CCNA2. Thus, after over-expressing SPRYD4, the expression of CDK2 and CCNA2 was proportionally attenuated in CCA cells, which explained the S-phase arrest in SPRYD4-OV cells. Furthermore, SPRYD4 expression also negatively correlates with two notable apoptotic inhibitors, BCL-2 and BIRC5. Herein, SPRYD4 over-expression significantly inhibited BCL-2 and BIRC5/survivin expression. Reed et al. initially identified BCL-2 as an anti-apoptotic gene that was associated with tumorigenesis and cancer progression [
31,
32]. In apoptosis pathways, BCL-2 inhibited cytochrome c that was released from the mitochondria to prevent caspases activation, which was directly responsible for cell apoptosis [
33]. Apart from apoptosis, BCL-2 also played essential roles in angiogenesis and chemotherapy resistance [
34,
35]. This study revealed that SPRYD4 could regulate BCL-2 levels; however, its specific effect on angiogenesis and chemoresistance requires further study.
The tumour immune microenvironment has been vastly studied in recent years, which resulted in immunotherapy advancements that regulate immune responses against tumour cells [
36]. As the most vital determinants of the cancer-related immune response, TILs are responsible for tumour immune surveillance and cancer cell elimination. In our study, GO analysis revealed the involvement of SPRYD4 in immune reactions such as T-cell differentiation and immune response-related cytokine regulation. Notably, SPRYD4 expression was negatively correlated with specific TILs, especially NK T cells, effector memory CD4
+ T cells and memory B cells in CCA. NKT cells are powerful immune regulators that modulate immune responses by secreting either Th1-, Th2-, Th17- or Treg-cell-associated cytokines [
37,
38]. Therefore, NKT cells are also considered essential mediators of cancer immune surveillance. To escape immune surveillance, tumour cells express high levels of immune checkpoints, such as PD-1/PD-L1 and CTLA4, which aid in escaping the tumour-killing effect of TILs [
39]. As one of the most indispensable checkpoints, PD-1 binds to PD-L1, leading to T-cell dysfunction and apoptosis [
39]. Similarly, CTLA4, an inhibitory receptor that is expressed in T cells, inhibits T-cell activation, highlighting its effectiveness in cancer treatment [
40,
41]. To date, ICIs are a hotspot in oncological therapy. Recent clinical trials have demonstrated the significant efficacy of pembrolizumab (PD-1 inhibitor) and ipilimumab (CTLA4 inhibitor) in anti-tumour activity, bringing in a new dawn in CCA treatment [
42]. In the present study, SPRYD4 showed a negative correlation with various important immune checkpoint markers including PD1, PD-L1, CTLA4, TIM3, TIGIT, LMTK3 and VISTA in CCA. However, further studies are required to explore the relationship and underlying regulatory mechanism of SPRYD4 expression with immune infiltration and checkpoints in CCA.
Conclusion
Our study demonstrated that the low expression of SPRYD4 correlated with adverse clinical characteristics and prognosis in patients with CCA. Moreover, in vitro studies suggested that the overexpression of SPRYD4 impaired S/G2 progression in the cell cycle and promoted cell apoptosis, which inhibited CCA initiation and progression. Thus, SPRYD4, a tumour suppressor, can be a potential indicator for CCA prognosis. However, further studies are required to validate its predictive ability.
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