Introduction
Pancreatic cancer is the fourth leading cause of all cancer-related deaths, and it has an overall 5-year survival rate of less than 10% due to late diagnosis, frequent metastases, limited treatment options, and poor prognosis (Lee et al.
2021; Jia et al.
2019). Only a minority of patients are eligible for surgery as the disease has often progressed locally or metastasized distantly at the time of diagnosis (Li et al.
2004). In recent years, with the increasing popularity of minimally invasive techniques and adjuvant surgical treatments, the quality and safety of pancreatic cancer surgery have improved. Chemotherapy is now increasingly used as neoadjuvant therapy and is usually accompanied by radiotherapy in PAAD (Kolbeinsson et al.
2023). Extensive testing of the pancreatic cancer genome has also led to a better understanding of the biology of pancreatic cancer, and targeted therapies and immunotherapies have brought new approaches to the treatment of pancreatic cancer (Dalmasso et al.
2022; Qiu et al.
2023). Unfortunately, to date, the efficacy of immune checkpoint inhibitors in patients with pancreatic cancer is not satisfactory (Mukherji et al.
2022). In general, pancreatic cancer is still a disease with a low long-term survival rate, and there is still an urgent need to find new therapeutic targets and treatment methods.
NUDT21 is a key mediator involved in alternative polyadenylation (APA) and pre-mRNA 3′ end processing (Ruegsegger et al.
1998). NUDT21 functions by binding to the UGUA sequence of pre-mRNA (Masamha
2023) and plays a broader role in cell fate changes and chromatin signaling (Brumbaugh et al.
2018). NUDT21 has emerged as an important regulator of cell fate decisions in normal and pathological conditions, but its involvement in cancer is not fully understood (Yang et al.
2020; Abadi et al.
2019). Decreased NUDT21 expression has been reported to promote cell proliferation in glioblastoma, bladder cancer, and hepatocellular carcinoma (Xiong et al.
2019; Masamha et al.
2014; Han and Kim
2014; Tan et al.
2018), and knockdown of NUDT21 also inhibits the proliferation and promotes apoptosis of human K562 leukemia cells through the ERK pathway (Zhang and Zhang
2018); NUDT21 also promotes the proliferation and metastasis in human gastric cancer through modulating SGPP2 (Zhu et al.
2021). The available literature provides evidence supporting the notion that NUDT21 plays a dual role (both oncogenic and tumor suppressor) in the tumorigenesis of different tissues. However, the role and regulation pathway of NUDT21 in PAAD have rarely been reported, and our study will explore the function and possible regulation pathway of NUDT21 in PAAD through bioinformatic data research and in
vitro experiments.
In this study, we will explore the expression of NUDT21 in pancreatic cancer and its effect on patients’ diagnosis and prognosis through preliminary bioinformatic data research, and analyze whether NUDT21 is an oncogene in pancreatic cancer. The effects of NUDT21 on the biological effects of pancreatic cancer cells will be explored by knockdown and overexpression of NUDT21 in pancreatic cancer cell lines. Protein mass spectrometry analysis was performed to identify possible interacted proteins with NUDT21 and possible downstream signaling pathways. As a regulator of RNA processing events, we will explore whether NUDT21 could provide a new feasible therapeutic target for the diagnosis and treatment of pancreatic cancer.
Materials and methods
Data sources and processing
Differential expression data of NUDT21 in PAAD and pan-cancer were obtained from UCSC XENA
https://xenabrowser.net/datapages/ in the TPM format of the TCGA and GTEx processed uniformly by the Toil process (Vivian et al.
2017). Differential RNAseq expression of NUDT21 data were extracted in level 3 HTSeq‐FPKM format from the TCGA (
https://portal.gdc.cancer.gov/ PAAD project. The differential expression of NUDT21 in PAAD at the transcriptome level were downloaded from the TCGA and GTEx online database
http://gepia.cancer-pku.cn/. RNAseq data in FPKM (Fragments per Kilobase per Million) format were converted to TPM (Transcripts per Million Reads) format and log transformed. All final analyses were performed using data in TPM format. All statistical analyses and visualizations were performed using R (version 4.2.1).
Immune infiltration analysis of NUDT21
We selected 24 immune cell markers (Bindea et al.
2013) and analyzed the relative infiltration levels of 24 immune cells in PAAD using the GSVA software package (version 24.1.34) (Hanzelmann et al.
2013). The immune infiltration algorithm was ssGSEA and correlation analysis was performed using Spearman. The samples were divided into low and high expression groups based on the expression of NUDT21, and the enrichment scores of various immune cell infiltrates in the different expression groups were calculated and analyzed using the GSVA software package (version 1.34.0). Correlations between NUDT21 and the expression of immune checkpoint-programmed cell death protein 1 (PD-1)-PDCD1 and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) were assessed using Spearman analysis. We validated the immune infiltration of NUDT21 in PAAD using the online bioinformatics analysis tool TIMER2 (
http://timer.cistrome.org/). Finally, immune cells with statistically significant relative infiltration (
p < 0.001) were analyzed. The visualization uses the circlize package (version 0.4.12).
Functional enrichment analysis of NUDT21 in PAAD
The results of single-gene differential analysis were analyzed by GO, KEGG, and GSEA functional enrichment using the clusterProfiler package (version 3.14.3) (Yu et al.
2012). Gene ID conversion was performed using the org.Hs.eg.db package (version 3.10.0) and the correlation of NUDT21 with the enriched pathways was scored by calculating Z values using the GOplot package (version 1.0.2) (Walter et al.
2015) which scores the relevance of NUDT21 to the enrichment pathway. The reference gene set used for the GSEA was c2.cgp. v7.2.symbols.gmt (Curated) (Subramanian et al.
2005) and the results were significantly enriched if they met the conditions of false discovery rate (FDR) < 0.25 and
p.adjust < 0.05.
Differential expression analysis of NUDT21
The Mann–Whitney U test (Wilcoxon rank sum test) was used to analyze the differences in the expression of NUDT21 in different cancers. Shapiro–Wilk normality test was used to test the normality of the data on the expression of NUDT21 in the unpaired samples. The independent samples t test was used to analyze the differences in the data in unpaired samples. Volcano plots were drawn using the results of the gene difference analyses with a threshold set at |log
2(FC)|> 1. Volcano map was generated by ggplot2 (version 3.3.3). We also investigated the differential expression of NUDT21and NDUFS2 in PAAD using an online bioinformatics analysis tool GEPIA2 (
http://gepia2.cancer-pku.cn/). We also validated the differential expression of NUDT21 in pan-cancer using an online bioinformatics analysis tool TIMER2 (
http://timer.cistrome.org/). All the above analyses were considered statistically significant when
p < 0.05.
Clinical correlation analysis, survival prognosis analysis, and construction of prognostic models
We statistically analyzed the survival data of PAAD patients using the survival software package (version 3.2–10) and plotted the overall survival (OS) and Kaplan–Meier survival curves of PAAD patients using the survminer software package (version 0.4.9). We then analyzed the Kaplan–Meier survival curves of PAAD patients in subgroups according to clinicopathological factors such as age and gender. We then used these clinicopathological factors to calculate their correlation with NUDT21 expression and visualized the results of the calculations using ggplot2 (version 3.3.3). We performed ROC analysis of the data using the pROC software package (version 1.17.0.1) to determine the accuracy of NUDT21 in predicting prognosis.
Cell lines and culture
The human pancreatic cancer PANC05.04 cells were cultured in F12k media (#21,127,022, Gibco) supplemented with 10% FBS and 100 × Penicillin–Streptomycin Solution. Cells were incubated in a humidified incubator at 37 °C with 5% CO2.
Cell transfection
sh-NUDT21, OE-NUDT21, sh-NDUFS2, and their each control plasmids were purchased from Genechem (Shanghai, China) company. Transient transfections were performed with jetPRIME (#150–15, Polyplus, France) transfection reagent following the manufacturer’s instructions.
Cell proliferation assay
Cell viability was quantified using the Cell Counting Kit-8 assay (B34304, Selleckchem). Cells were seeded into 96-well plates at a density of 3 × 103 cells/well and were cultured in a humidified atmosphere with 5% CO2 at 37 °C. Subsequently, 10 μl CCK-8 reagent was added to each well. The absorbance was measured at 450 nm after 2 h. The CCK-8 assay was performed every 24 h for 4 consecutive days.
Cell apoptosis assay
The Annexin V-FITC/PI Apoptosis Detection Kit (Multi Sciences Biotech Co., Ltd.) was used in the present study. Briefly, cells were seeded into 6-well plates and were harvested and resuspended in 500 μl binding buffer after 48 h. Subsequently, cells were incubated with 5 μl Annexin V-FITC and 10 μl PI at room temperature in the dark for 15 min before analysis via flow cytometry.
For colony formation analysis, 1000–1500 cells per well were plated in six-well plates and allowed to grow for 14 days after the indicated treatments, then we fixed the cells with 4% paraformaldehyde (P1110,Solarbio), and stained the cells with 5% crystal violet (G1063,Solarbio).
Cell cycle assay
The Cell Cycle Staining Kit (CCS012, Multi Sciences Biotech Co., Ltd.) was used according to the manufacturer’s protocol. Briefly, cells were harvested and fixed in 70% ethanol at 4 °C overnight. Cells were then treated with 1 ml DNA staining solution and 10 μl permeabilization at 37 °C in the dark for 30 min. Cells were then analyzed via flow cytometry.
Transwell migration assay
2 × 105 cells which were suspended in 1.5 ml serum-free culture media were added to the top chamber of 6-well transwell plates (3428, Corning), and 2.6 ml culture media containing 10% FBS were added to the bottom chamber. After incubating at 37 °C for 48 h, the chambers were washed with PBS twice, and these cells which migrated to the bottom chambers were fixed with 4% paraformaldehyde and stained with crystal violet. Then the number of transitional cells in all chambers was calculated in the 5 visual fields.
Wound healing assay
Cells were seeded on 6-well plate and grew to the pavement overnight. After 24 h of transfection, a channel was drawn on the monolayer cells with 10 μl micropipette tip. Then cells were washed with PBS twice and cultured in serum-free culture media at 5% CO2, 37 °C for an additional 24 h. Photographs were taken by an inverted Leica phase contrast microscope at 0 h and 24 h.
NADP+/NADPH and ATP assay
For measurements of NADP + /NADPH ratio and ATP concentration, cells were harvested and treated with appropriate buffers as indicated by the providers. In particular, NADP + /NADPH ratios were determined using a NADP + /NADPH Assay kit (S0179, Beyotime) and were detected using a colorimetric assay under a microplate reader (Feyond-A400, ALLSHENG, China) with detection wavelengths of 570 nm, respectively. The ATP concentration was calculated using an enhanced ATP assay kit (S0027, Beyotime) by measuring chemiluminescence with a luminometer plate reader.
Western blotting
Cells were lysed using RIPA buffer (P0013B, Beyotime Biotechnology). Subsequently, total protein was separated using SDS-PAGE and transferred to a PVDF membrane. Membranes were blocked and were subsequently incubated at 4 °C overnight with the following primary antibodies against: GAPDH (2118, 1:1000; CST.), beta-Tubulin (16,305, 1:2000; CST), NDUFS2 (sc-390596, 1:1000; MDL Biological, Inc.), AKT (ab8805, 1:1000; Abcam), P-AKT308(ab38449, 1:1000; Abcam), NUDT21 (ab183660, 1/1000; Abcam), PI3K(#4257, 1/1000; CST), and P-PI3K(#4228, 1/1000; CST). All antibodies were used according to the manufacturer’s protocol. Following primary incubation, membranes were incubated with secondary antibodies, HRP-conjugated goat anti-rabbit IgG (PR30011, 1:20,000; Proteintech Co., Ltd.) and HRP-conjugated goat anti-mouse IgG (PR30012, 1:20,000; Proteintech Co., Ltd.) at room temperature for 1 h. Proteins were visualized using ECL Reagent (42,029,053, Millipore Sigma).
Immunofluorescence staining and co-immunoprecipitation
Slides containing human pancreatic tumor tissues or cells were used in our experiment. The slides were incubated with primary antibodies at 4 °C overnight. The following day, after incubation with the corresponding secondary antibody, the nuclei were stained with DAPI (Yeason, 40728ES03) before observing by confocal laser microscopy. Co-immunoprecipitation analysis was carried out using the Pierce Co-Immunoprecipitation Kit (88,804; Thermo Fisher) according to the manufacturer’s instructions.
Drugs and inhibitors
100 μM insulin which is a P-AKT activator and 1 μM wortmannin (CST, #9951) which is an inhibitor of PI3 kinase were used to treat pancreatic cell lines.
Clinical samples
The protocol of this retrospective study was approved by the Ethics Committee of the PLA General Hospital, and all enrolled patients were informed of and agreed to participate in this study by signing a written informed consent form. In this study, paraffin-embedded specimens from 30 patients diagnosed with PAAD between September 1, 2018 and June 1, 2019 were collected from the Department of Hepatobiliary Surgery of the PLA General Hospital, and the baseline characteristics and pathological data of the patients were obtained from the database of the PLA General Hospital.
Statistical analysis
Data are expressed as mean ± standard deviation (mean ± SD). Differences in the expression of NUDT21 in PAAD tumor tissues and adjacent tissues were analyzed by Student’s t test. Comparisons between multiple groups were performed using one-way analysis of variance (ANOVA). The correlation between NUDT21 expression and clinical data of PAAD patients was analyzed using Mann–Whitney U test. Statistical graphs were completed using GraphPad Prism 9, and P < 0.05 was considered a statistically significant difference.
Discussion
Currently, Multi-disciplinary Treatment (MDT), including surgery and chemotherapy, is considered the gold-standard treatment for pancreatic cancer. Neoadjuvant chemotherapy, genetically engineered modified T-cell therapy, CAR-T cells, autophagy, MicroRNAs, tumor vaccines, and targeted therapies have provided new approaches for the treatment of pancreatic cancer (Gugenheim et al.
2022; Leidner et al.
2022; Sadelain
2015; Wang et al.
2021; Chu et al.
2021; Moore et al.
2007), but the outcomes were not always satisfactory. Hence, we urgently need to find more therapeutic targets to provide more treatment options for pancreatic cancer.
NUDT21, a 3′ end processing complex conserved in multicellular organisms but absent from yeast (Darmon and Lutz
2012), is one of the main regulators of 3′ UTR(3′ untranslated regions) length (Li et al.
2015). NUDT21 plays an important physiological function in the occurrence and development of many diseases (Tellier et al.
2018). In this study, the expression profiles of NUDT21 in multiple cancers were analyzed based on TCGA and GEO databases. Then, NUDT21 expression in pancreatic cancer was investigated by gene differential analysis and single-gene correlation analysis. In addition, we performed GO and KEGG pathway analysis, gene enrichment analysis, and Kaplan–Meier survival analysis to predict the potential function of NUDT21 and its role in the prognosis of pancreatic cancer patients. We found that patients with high expression of NUDT21 showed poor OS rates compared with patients with low expression of NUDT21.
The correlation between NUDT21 expression and 24 types of immune cells in PAAD showed that NUDT21 expression was negatively correlated with NK cells, pDC, and Th17 cells. Immune cell infiltration improves poor patient prognosis, whereas low concentrations of infiltrating immune cells can lead to immune escape from cancer cells, resulting in poor prognosis (Buisseret et al.
2018; Chen et al.
2020). In addition, the results of immune infiltration showed that the degree of Th2 cell infiltration was significantly positively correlated with the expression of NUDT21. The transition from Th1/Th2 balance to Th2 dominance is a crucial factor in tumor progression, and Th2 cells are detrimental to the antitumor effects of cellular immunity. Restoring the balance between Th1 and Th2 cells is of great significance in the treatment of tumors (Sharma et al.
2007; Johnson et al.
2014). We also found that most of the immune checkpoints currently used in therapy (e.g., PDCD1, CTLA4) were positively correlated with the expression of NUDT21, implying that it may be possible that PAAD may benefit more from immune-associated therapies against these checkpoints. All these results indicate that upregulation of NUDT21 expression can inhibit the antitumor immune response in PAAD patients.
Apart from the predictions of the bioinformatic data, we further verified the conclusions in vitro. We systematically examined the functional role of NUDT21 in human pancreatic cancer cells. shRNA-mediated depletion of NUDT21 dramatically decreased cell viability, cell colony formation, cell proliferation, cell migration in pancreatic cancer cells as determined by cell apoptosis assay, cell colony formation assay, and cell migration assay, respectively. Overexpression of NUDT21 concordantly promoted both cell proliferation and migration in pancreatic cancer cells. Moreover, we found that NUDT21 regulates pancreatic cancer cell proliferation and migration by modulating and stabilizing NDUFS2 and activating the PI3K-AKT signaling pathway through protein mass spectrometry. Compared with normal pancreatic tissues, NUDT21 was expressed at a higher level in human pancreatic cancer tissues, which was consistent with the prediction of the bioinformatic results.
The phosphoinositide 3-kinase (PI3K)–AKT pathway is the most commonly activated pathway in human cancers (Lawrence et al.
2014). AKT-mediated phosphorylation of these protein targets serves to influence a variety of cell biological functions, including cell growth, proliferation, survival and metabolism (Manning and Toker
2017). Many anticancer therapies including cytotoxic drugs, radiotherapy, or immunotherapy can cause tumor cell death by activating caspase3 (Zhou et al.
2018). AKT/mTOR signaling is also a major determinant of cellular energy metabolism (Manning and Toker
2017; Saxton and Sabatini
2017). After interfering with NUDT21, the PI3K–AKT pathway was inhibited and P-AKT308 expression was downregulated, while after overexpression of NUDT21, the PI3K–AKT pathway was activated and P-AKT308 expression was upregulated. Phosphorylated AKT308 inhibited the expression of caspase3, which promoted the proliferation and migration of pancreatic cancer cells and inhibited apoptosis.
NDUFS2 (NADH: ubiquinone oxidoreductase core subunit S2) is localized in mitochondria and is the core subunit of the mitochondrial respiratory chain complex I, which is encoded by nuclear DNA. It has been shown that after interfering with the intracellular NDUFS2, the activity of Complex I is inhibited, intracellular ATP production is reduced, tumor growth is suppressed, and tumor metastasis is significantly reduced (Liu et al.
2019). In our study, we found that interfering with NUDT21 also inhibited intracellular ATP synthesis and decreased the NADPH/NADP
+ ratio, which means that NDUFS2 could play an important role in the ATP synthesis and redox system.
In conclusion, our results showed that NUDT21 was highly expressed in pancreatic cancer tissues compared with paraneoplastic tissues, and the higher the expression, the worse the prognosis of the patients. NUDT21 promotes the proliferation and migration of pancreatic cancer cells through the regulation and stabilization of NDUFS2 and activation of the PI3K–AKT pathway. NUDT21 can be used as a diagnostic and prognostic marker for pancreatic cancer patients in clinic.
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