Published online Dec 21, 2026. doi: 10.3748/wjg.122668
Revised: June 26, 2026
Accepted: July 28, 2026
Published online: December 21, 2026
Processing time: 185 Days and 21.4 Hours
Zfp36 zinc finger CCCH-type (ZFP36) is a critical RNA-binding protein that plays key roles in cancer progression. However, its specific functions and underlying mechanisms in gastric cancer (GC) remain poorly understood.
To investigate the functional role and molecular mechanisms of ZFP36 in GC pro
A stable ZFP36-overexpressing human gastric adenocarcinoma AGS cell line was established. Cell proliferation, cell cycle distribution, apoptosis, migration, and invasion were assessed. To identify downstream targets of ZFP36, RNA sequen
Overexpression of ZFP36 significantly suppressed proliferation, migration, and invasion of AGS cells, triggered G0/G1 cell cycle arrest, and promoted apoptosis. The anti-tumor effect of ZFP36 was further confirmed in xenograft models. RNA-seq analysis identified 729 differentially expressed genes (510 upregulated and 219 downregulated) and 1729 alternative splicing events regulated by ZFP36. iRIP-seq revealed that ZFP36 binds to target genes via specific sequence motifs. Integrated analysis of RNA-seq and iRIP-seq data identified LIPG as a direct target of ZFP36. ZFP36 was found to bind to the 3’ untranslated region of LIPG mRNA and to promote its expression. Consistent with this, elevated LIPG expression was observed in subcutaneous tumors from ZFP36-overexpressing AGS cells in mice.
Our study demonstrates that ZFP36 inhibits GC progression by enhancing LIPG expression and binding to its 3’ untranslated region. The ZFP36-LIPG axis represents a promising therapeutic target for GC therapy.
Core Tip: Zfp36 zinc finger CCCH-type (ZFP36), an RNA-binding protein, has an unclear role in gastric cancer. Here, ZFP36 overexpression in AGS cells suppressed proliferation, migration, and invasion, as well as G0/G1-phase arrest and apoptosis induction, while also inhibiting xenograft tumor growth. Integrated RNA sequencing and improved RNA immunoprecipitation sequencing identified lipase G (LIPG) as a direct target, with ZFP36 binding to its 3’ untranslated region to enhance LIPG expression. In vivo, LIPG was upregulated in ZFP36-overexpressing tumors. These findings demonstrate that ZFP36 inhibits gastric cancer progression by upregulating LIPG, revealing a potential therapeutic axis.
- Citation: Yu PJ, Zhu SM, Cai BJ, Ma XM, Qiao WJ, Han JJ, Zhang CW. Zfp36 zinc finger CCCH-type inhibits gastric cancer progression by upregulating lipase G and binding its 3’ untranslated region. World J Gastroenterol 2026; 32(47): 122668
- URL: https://www.wjgnet.com/1007-9327/full/v32/i47/122668.htm
- DOI: https://dx.doi.org/10.3748/wjg.122668
Among global gastrointestinal malignancies, gastric cancer (GC) ranks as one of the most common, representing a substantial threat to human health[1]. According to the 2020 Global Cancer Statistics, there were 1.089 million newly diagnosed GC cases and 769000 GC-related deaths worldwide[2]. In China, the disease burden is particularly severe, with GC ranking third in cancer incidence and fourth in mortality[3]. According to the World Health Organization data for 2020, China recorded 479000 new GC cases and 374000 fatalities from the disease, accounting for 44.9% and 48.6% of the global totals, respectively[4]. Due to its insidious onset and lack of specific clinical symptoms, GC is often diagnosed at advanced stages, with an early diagnosis rate of only 20%[5]. Consequently, most patients miss the window for optimal therapeutic intervention, leading to a markedly reduced 5-year survival rate[6]. Thus, identifying molecular biomarkers and therapeutic targets for GC progression is crucial for advancing early detection and personalized treatment, which may extend patient survival and improve quality of life.
Zfp36 zinc finger CCCH-type (ZFP36), also known as tristetraprolin, is a pivotal RNA-binding protein (RBP) that regulates mRNA stability, decay, and translation across various biological processes[7]. ZFP36 attaches to the 3’ untranslated region (3’ UTR) of its mRNA targets, then recruits deadenylation and degradation factors, thereby reducing the stability of mRNAs encoding inflammatory mediators such as tumor necrosis factor, interleukin (IL)-6, IL-17A, and IL-33[8]. This protein plays a central regulatory role in key processes that include lipid peroxidation, oxidative stress, apoptosis, and immune activation[9]. In recent years, the role of ZFP36 in tumorigenesis has emerged as a major research focus. In breast cancer, MCM3AP-AS1 interacts with ZFP36 to modulate tumor cell proliferation, apoptosis, migration, and invasion[10]. Notably, ZFP36 is significantly underexpressed in GC, and its overexpression suppresses programmed death ligand-1 expression, enhances antitumor immune responses, and ultimately inhibits GC progression[11,12]. However, the precise mechanisms and regulatory networks by which ZFP36 acts in GC remain to be fully elucidated.
To systematically characterize the functional mechanisms of ZFP36, this study utilized the human GC cell line AGS to conduct the following investigations: (1) Overexpression of ZFP36 combined with cytological assays (proliferation, cell cycle, apoptosis, migration, and invasion) to determine its phenotypic effects; (2) Integration of RNA sequencing (RNA-seq) and improved RNA immunoprecipitation sequencing (iRIP-seq) to map ZFP36-regulated differentially expressed genes (DEGs), alternative splicing events (ASEs), and identify direct binding targets; and (3) Establishment of a nude mouse subcutaneous xenograft model using ZFP36-overexpressing AGS cells to validate its in vivo functions. This work not only clarifies the regulatory axis of ZFP36 in GC but also provides molecular evidence supporting its potential as a clinical therapeutic target, thereby offering significant translational value for developing novel diagnostic and therapeutic strategies.
Lentiviral particles overexpressing ZFP36 (OE-ZFP36) were sourced from Genepharma (Suzhou, China). The transcript corresponded to NM_003407, and the lentiviral vector was LV5 (EF-1α/GFP/Puro/Amp). The negative control (NC) lentiviral particles were prepared using the same LV5 vector without the ZFP36 insert.
AGS cells (CL-0022, Procell, China) were grown at 37 °C under a humidified, 50 mL/L CO2 environment. The growth medium comprised Ham’s F12 (PM150810, Procell, China) supplemented with 100 mL/L fetal bovine serum (10091148, Gibco, China), along with 100 μg/mL streptomycin and 100 U/mL penicillin (SV30010, Hyclone, United States). For lentiviral delivery, a multiplicity of infection of 500 was used. AGS cells were transduced with either ZFP36-overexpressing lentivirus or the empty vector control lentivirus to generate OE-ZFP36 and NC stable cell lines, respectively. Following selection with 1 μg/mL puromycin, stable clones were harvested and subjected to reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting analysis.
TRIzol reagent (Ambion) was used to extract total RNA, followed by RQ1 deoxyribonuclease treatment (Promega, Madison, WI, United States) to eliminate genomic DNA. RNA concentration and purity were measured using a NanoDrop One spectrophotometer (Thermo Fisher Scientific, Waltham, MA, United States). Glyceraldehyde-3-phosphate dehydrogenase was used as the internal control for normalization. RT-qPCR ran on a Bio-Rad cycler (Bio-Rad Laboratories, Hercules, CA, United States) using the SYBR Green Master Mix (Yeasen, Shanghai, China). Relative expression was quantified via the 2-ΔΔCT method. Primer sequences appear in Supplementary Table 1.
Protein lysates were obtained from AGS cells using radio-immunoprecipitation assay buffer (PR20001, Proteintech Group, Wuhan, China) supplemented with protease inhibitors (4693116001, Sigma-Aldrich, St. Louis, MO, United States). After denaturation in loading buffer (P1040, Solarbio, Beijing, China), samples were resolved by 10% sodium dodecyl sulphate-polyacrylamide gel electrophoresis. Proteins were then electrotransferred onto 0.45-μm polyvinylidene fluoride membranes (ISEQ00010, MilliporeSigma, Burlington, United States). Membranes were blocked with 5% non-fat milk for 1 hour at ambient temperature, then probed overnight at 4 °C with mouse anti-FLAG (1:1000, 66008-3-IG, Proteintech, China) and anti-glyceraldehyde-3-phosphate dehydrogenase (1:1000, 60004-1-IG, Proteintech, China). After washing, the membranes were incubated with an HRP-conjugated anti-mouse secondary antibody (1:5000, AS003, ABclonal Technology, Wuhan, China) for 45 minutes at room temperature. Protein signals were visualized using an enhanced chemiluminescence reagent (P0018FM, Beyotime, Shanghai, China) and imaged with a Tanon 5200 chemiluminescence imaging system (Tanon Science & Technology, Shanghai, China).
A cell counting kit-8 (CCK-8) kit was employed to evaluate cell proliferation (Yeasen, China). A total of 1 × 104 cells per well were plated into 96-well plates and incubated overnight at 37 °C. At designated intervals, the culture medium was exchanged for 100 μL of fresh medium spiked with 10 μL of CCK-8 reagent. After a 2-hour incubation, absorbance at 450 nm was measured using a microplate reader (FC, Thermo, MA, United States).
Following transduction, AGS cells were harvested and stained with propidium iodide (P4170, Sigma-Aldrich, United States) according to the supplier’s protocol. Cell cycle distribution was analyzed on a Beckman Coulter CytoFLEX flow cytometer (Beckman Coulter, CA, United States) using CytExpert software.
Cell apoptosis was evaluated with the Annexin V-APC/7-AAD kit (40304ES60, Yeasen, China) following the product manual. Briefly, AGS cells were transduced for 48 hours, then collected and double-stained with Annexin V-APC and 7-AAD. Apoptosis rates were quantified on a CytoFLEXS system (Beckman Coulter, Brea, CA, United States).
In vitro evaluation of migration and invasion was performed using Transwell chambers (3422, Corning Inc., Corning, NY, United States) featuring 8-μm pore filters. Invasion assays required membranes precoated with Matrigel (356234, BD Biosciences, Franklin Lakes, NJ, United States) diluted 1:8 in serum-free medium, whereas migration assays used uncoated filters. Cells (2.5 × 105) in serum-free medium were seeded into the upper chamber, while the lower chamber contained medium supplemented with 10 mL/L fetal bovine serum (10091148, Gibco, China) as a chemoattractant. Following incubation (24 hours for invasion, 48 hours for migration), non-migrated/invaded cells on the upper surface of the membrane were carefully removed. Cells on the lower surface were fixed, stained with 1 g/L crystal violet (C0121, Beyotime, China). Stained cells were finally observed and counted under an inverted microscope (MF52-N, Mshot, Guangzhou, China) at 200 × magnification[13].
Total RNA was extracted following the procedure described above. Directional RNA-seq libraries were prepared using the VAHTS Universal V8 Library Prep Kit (N605, Vazyme Biotech, Nanjing, China)[14]. Polyadenylated mRNA was enriched with VAHTS mRNA Capture Beads (N401, Vazyme, China), then fragmented and reverse-transcribed into double-stranded complementary DNA. Complementary DNA was end-repaired, adenylated, and ligated to adapters using the VAHTS RNA Multiplex Oligos Set 1 (N323). Libraries were amplified, purified, and quality-checked. Strand-specific sequencing was performed on an Illumina NovaSeq 6000 platform, generating 150-bp paired-end reads.
Raw sequencing reads with more than two ambiguous bases (N) were removed. Adapter sequences and low-quality bases were trimmed using FASTX-Toolkit (v 0.0.13). Reads shorter than 16 nt were discarded. Clean reads were aligned to the GRCh38 genome with HISAT2[15], allowing up to 4 mismatches. Uniquely mapped reads were used for gene-level counting and fragments per kilobase of transcript per million fragments mapped calculations[16].
DEGs were identified using DESeq2 with thresholds of P value < 0.05 and fold change ≥ 1.5 or ≤ 0.6667[17].
ASEs were detected using the ABLas pipeline[18,19]. Ten ASE types were identified: Exon skipping (ES), alternative 5’ and 3’ splice sites (A5SS, A3SS), mutually exclusive exons (MXE), mutually exclusive 5’ and 3’ UTRs (5pMXE, 3pMXE), cassette exon, and the composite types A3SS&ES and A5SS&ES[20]. Student’s t-test was used to evaluate the statistical significance for changes in AS ratios. ASEs with a false discovery rate < 0.05 were considered ZFP36-regulated. Supplementary Table 2 lists the genes undergoing alternative splicing following ZFP36 overexpression in AGS cells.
KOBAS 2.0[21] was utilized for Gene Ontology (GO) enrichment analysis of target genes. The hypergeometric test followed by Benjamini-Hochberg false discovery rate correction to identify significantly enriched terms.
iRIP-seq was performed by Wuhan Ruixing Biotechnology Co., Ltd (Wuhan, China). Cells were UV-crosslinked (400 mJ/cm2) and lysed in buffer containing ribonuclease inhibitors and protease inhibitors. Lysates were treated with deoxyribonuclease, and debris was removed by centrifugation. RNA was fragmented using micrococcal nuclease. The lysate was incubated with anti-FLAG antibody (F7425, Sigma, United States) or control IgG antibody (AC005, ABclonal, China). Antibody-bound complexes were captured with Protein A/G Dynabeads (26162, Thermo Scientific, United States). The beads were washed and bound RNAs were eluted. RNA was digested with Proteinase K and purified by phenol-chloroform extraction (P1011, Solarbio, China). Sequencing was performed on an Illumina NovaSeq 6000 platform (Illumina, Inc., San Diego, CA, United States) using a 150-nt paired-end configuration.
Reads were aligned to the GRCh38 human reference genome using HISAT2. Uniquely mapped reads were kept, and PCR duplicates were removed. Peak calling was performed using piranha and ABLIRC[22]. The ABLIRC algorithm was used to identify binding regions as previously described[19]. Peaks with IP enrichment > 4-fold over input were retained. Target genes were assigned to peaks, and binding motifs were identified using HOMER[23].
BALB/c-nu mice (male, 6-8 weeks) were obtained from Hubei Bainte Biotechnology Co., Ltd. (Hubei, China). For tumor cell implantation, mice were anesthetized via an intraperitoneal injection of 2.5 g/L tribromoethanol at a dosage of 10 μL/g body weight. AGS cells (1 × 107 cells suspended in a 1:1 mixture of serum-free medium and Matrigel) were sub
Results are expressed as the mean ± SD from at least three independent replicates. Statistical comparisons were performed using Student’s t-test. A threshold of P < 0.05 defined statistical significance (aP < 0.05, bP < 0.01, cP < 0.001, dP < 0.0001). Graphs were generated with GraphPad Prism (v8.0, GraphPad Software, San Diego, CA, United States).
To investigate the molecular mechanisms of ZFP36 in GC, lentiviral vectors OE-ZFP36 were constructed and transduced into AGS cells. Successful ZFP36 overexpression was confirmed at both the mRNA and protein levels relative to the NC cells (Figure 1A and B). The functional impact of ZFP36 in AGS cells was assessed using multiple in vitro assays. CCK-8 assays indicated that ZFP36 overexpression led to a marked reduction in cell proliferation relative to the NC group (Figure 1C). Flow cytometry analysis further demonstrated that ZFP36 overexpression induced G0/G1-phase arrest (Figure 1D). Apoptosis assays also confirmed that ZFP36 overexpression enhanced apoptosis (Figure 1E). Furthermore, Transwell assays showed that ZFP36 overexpression markedly impaired both migration and invasion (Figure 1F and G). Collectively, these findings demonstrate that ZFP36 suppresses proliferation, migration, and invasion, and promotes apoptosis in AGS cells.
To uncover how ZFP36 drives GC pathogenesis and identify downstream gene expression alterations, RNA-seq was performed comparing OE-ZFP36 cells with NC controls. Principal component analysis revealed a clear separation between the NC and OE-ZFP36 groups, validating the robustness of the experimental design (Figure 2A). Following ZFP36 upregulation, 510 genes showed significant upregulation while 219 were downregulated in AGS cells (fold change ≥ 1.5) (Figure 2B and C). GO analysis revealed that the identified upregulated genes mainly participated in extracellular matrix organization, the inflammatory response, cell adhesion, and collagen fibril organization (Figure 2D). In addition, the downregulated genes were primarily involved in angiogenesis, integrin-mediated signaling pathways, cell adhesion, apoptotic processes, and extracellular matrix organization (Figure 2E). Among them, RNA-seq data for seven representative upregulated genes, CLIC3, CXXC5, HMOX1, HOXB9, PLA2G2A, SEMA3B, and CEBPA, and six downregulated genes, ALDH3A1, APOBEC3B, F3, LINC00342, PHLDA2, and PLAUR, are shown in Figure 2F. These genes exhibited significant expression changes under OE-ZFP36 conditions, were identified within significantly enriched GO biological processes, and have established links to cancer development through roles in apoptosis, invasion, proliferation, and migration[25]. RT-qPCR validation confirmed a high degree of consistency with the RNA-seq results (Figure 2F). Collectively, these results demonstrate that ZFP36 broadly modulates the expression of numerous oncogenes and tumor suppressors.
To gain insight into the role of ZFP36 in alternative splicing (AS) regulation, the RNA-seq dataset was analyzed with the ABLas tool to assess splicing alterations. By applying a stringent cutoff of P value ≤ 0.05, we identified 1729 high-confidence regulated ASEs. The identified regulated ASEs included A5SS (363 events), A3SS (460 events), ES (224 events), and cassette exons (233 events) (Figure 3A). These data suggest that ZFP36 globally regulates ASEs in AGS cells. The analysis further revealed that the ASE genes regulated by ZFP36 were highly enriched for terms related to translation, cellular response to DNA damage stimulus, regulation of G2/M transition of mitotic cell cycle, and RNA splicing (Figure 3B). To validate the ASEs of cancer-related genes regulated by ZFP36, we selected three cancer-associated genes, WWOX (A3SS), METTL2B (ES), and NEDD9 (A3SS), for experimental confirmation. RT-qPCR analysis demonstrated strong concordance between experimental measurements and RNA-seq predictions across all validated events (Figure 3C-E). Collectively, these findings establish ZFP36 as a critical regulator of AS patterning in AGS cells, potentially mediating its effects through multiple spliceosome-coupled mechanisms.
RBPs are typically evaluated based on their RNA-binding capacity and the efficiency with which they can be recovered. To examine the specificity of ZFP36 pulldown assays, iRIP-seq was performed to capture ZFP36-bound mRNAs. We first validated antibody specificity and immunoprecipitation efficiency using western blotting, employing two independent biological replicates (IP-1 and IP-2) to ensure experimental reproducibility (Figure 4A). The genomic distribution of the reads showed that ZFP36 interacted with diverse RNA elements, including the 5’ UTR, 3’ UTRs, coding sequences, non-coding exons, introns, antisense regions, and intergenic regions (Figure 4B). These findings suggest that ZFP36 may bind to these regions, thereby regulating transcript stability, AS, and translation. Notably, the UCGC binding motifs of ZFP36 identified in the two replicate trials were consistent (Figure 4C). The UCGC motif was predominantly distributed within the 5’ UTR (Figure 4D). Furthermore, we observed that ZFP36 globally binds to RPS25 mRNA, and confirmed their significant interaction via RNA immunoprecipitation-qPCR experiments (Figure 4E). Collectively, these findings indicate that ZFP36 exerts posttranscriptional regulation by recognizing and binding to specific RNA sequences in AGS cells.
Through gene annotation and correlation analysis of binding peak reads, we identified 266 genes associated with ZFP36 binding peaks. These genes were then intersected with transcriptome-derived DEGs, yielding four DEGs that were also ZFP36 binding peak-associated (Figure 5A). Notably, ZFP36 bound to the 3’ UTR of LIPG, which has potential relevance to GC pathogenesis. To verify altered expression and binding capacity, we conducted RT-qPCR and RNA immunoprecipitation-qPCR targeting LIPG. The results aligned with the sequencing data, demonstrating markedly elevated expression levels and enhanced binding signals for LIPG (Figure 5B and C). Collectively, these results suggest that ZFP36 may contribute to GC pathogenesis by promoting LIPG expression.
To further investigate the function of ZFP36 in vivo, parental and ZFP36-overexpressed AGS cells were subcutaneously injected into mice (n = 6). Tumor volumes were measured on days 7, 15, 21, 36, 44, 51, 55, 59, and 63. In the NC group, the maximum tumor diameter reached approximately 1 cm. At the endpoint, xenografts were resected, and tumor weights were recorded. The final tumor volumes and tumor weights were significantly lower in the OE-ZFP36 group than in the NC group (Figure 6A-D). Additionally, the protein expression level of LIPG was notably increased following ZFP36 overexpression (Figure 6E). Taken together, these findings demonstrate that ZFP36 overexpression significantly suppresses the growth of AGS cell-derived tumors by upregulating LIPG expression.
ZFP36, an essential RBP, participates in the pathogenesis and progression of various diseases through transcriptional and post-transcriptional regulatory mechanisms[26-28]. However, the expression patterns, biological functions, and precise molecular mechanisms of ZFP36 in GC remain incompletely understood. This study systematically investigated the cellular functions of ZFP36 in AGS cells. Through integrative analysis of RNA-seq and iRIP-seq, we identified and validated direct RNA targets of ZFP36, followed by in vivo verification in animal models. Mechanistically, ZFP36 specifically bound the 3’ UTR of LIPG mRNA, consequently upregulating its expression and thereby suppressing GC progression. This study not only elucidates the molecular mechanism by which ZFP36 functions as a RBP to regulate GC progression but also provides a valuable theoretical foundation for developing targeted therapeutic strategies against GC.
Functional assays showed that ZFP36 overexpression significantly inhibited the proliferative, migratory, and invasive capacities of AGS cells, induced G0/G1-phase arrest, and promoted apoptosis. In a subcutaneous xenograft model, ZFP36 overexpression also markedly suppressed tumor growth. Consistent with its tumor-suppressive role, downregulation of ZFP36 has been reported in multiple cancer types. For example, in head and neck squamous cell carcinoma, ZFP36 inhibited the expression of Bcl-2 and enhanced the cisplatin sensitivity of head and neck squamous cell carcinoma cells[29]. Ferri et al[30] reported that ZFP36 expression exerts protective effects against oral carcinogenesis by modulating inflammatory infiltration and maintaining the epithelial microenvironment, thereby suggesting a potential barrier function against tumor development. In a clinical analysis of 70 GC patient samples, Deng et al[31] observed significantly reduced ZFP36 mRNA and protein levels in tumor tissues compared with adjacent normal tissues. ZFP36 expression was inversely correlated with tumor invasion depth, lymph node metastasis, and TNM stage, while its downregulation was associated with poor patient prognosis. In the same study, the authors further validated the tumor-suppressive functions of ZFP36 in MGC-803 and SGC-7901 cells[31]. Additionally, Guo et al[12] confirmed these observations in MGC-803 and BGC-823 cells. Collectively, these findings support the role of ZFP36 as a tumor suppressor in GC.
RNA-seq analysis further revealed that ZFP36 overexpression resulted in differential expression of 729 genes (510 upregulated and 219 downregulated). Functional enrichment analysis showed that the downregulated genes were predominantly enriched in biological processes such as angiogenesis, integrin-mediated signaling pathways, cell adhesion, and apoptotic processes. These alterations in gene expression patterns were closely associated with ZFP36-induced inhibition of migration and invasion while promoting apoptosis. qPCR validation confirmed that ZFP36 overexpression led to significant upregulation of CLIC3, CXXC5, HMOX1, HOXB9, PLA2G2A, SEMA3B, and CEBPA, as well as downregulation of ALDH3A1, APOBEC3B, F3, LINC00342, PHLDA2, and PLAUR. Notably, PLAUR knockdown has been shown to induce apoptosis, modulate cell cycle progression, and suppress epithelial-mesenchymal transition processes[32]. PHLDA2 is elevated in colorectal cancer tissues, and its knockdown suppresses tumor cell proliferation, invasion, migration, and epithelial-mesenchymal transition in vitro[33]. LINC00342 is significantly overexpressed in GC tissues and cell lines, and its overexpression enhances proliferation, migration, and invasion but reduces the percentage of G0/G1-phase cells in MGC-803 and MGC-823 cells[34]. These findings suggest that ZFP36 may regulate GC progression partly by modulating the expression of these genes. Collectively, our study provides important experimental evidence for understanding the role of ZFP36 in tumorigenesis and cancer development.
Previous studies have indicated that ZFP36 can regulate the AS patterns of mRNA[35]. Here, we found that overexpression of ZFP36 led to significant alterations in 1729 ASEs. Functional enrichment analysis revealed that these alternatively spliced genes are primarily involved in biological processes including cellular response to DNA damage stimulus, regulation of mitotic cell cycle G2/M-phase transition, and RNA splicing. Notably, WWOX (A3SS) and NEDD9 (A3SS) were upregulated upon ZFP36 overexpression, while METTL2B (ES) showed a downregulated trend. It has been reported that splice variants of WWOX exist in malignant tissues; in ovarian cancer, the most common transcript variant is variant 4 (lacking exons 6-8), which is expressed at significantly lower levels in tumor tissues compared to normal ovarian tissues and is associated with high-grade and advanced-stage disease[36]. In retinoblastoma, retention of intron 1 in METTL2B has been observed[37]. These results suggest that ZFP36 broadly regulates AS of genes in AGS cells, and these genes may represent important potential therapeutic targets in GC progression. Future studies are warranted to systematically validate these AS events using splice-junction spanning primers and gel-based assays, which will provide deeper insights into how ZFP36 modulates AS to exert its tumor-suppressive functions in GC.
Subsequent iRIP-seq results revealed that ZFP36 binds to a large number of protein-coding genes and specifically targets their 3’ UTR, 5’ UTR, coding sequences, and intronic regions, showing unique binding characteristics. Integrative analysis of RNA-seq and iRIP-seq data showed that ZFP36 not only binds to the 3’ UTR of LIPG mRNA but also sig
Several limitations of the present work merit mention. First, functional validation was primarily performed in a single GC cell line (AGS). Confirmation in additional cell lines (e.g., HGC-27, MGC-803, BGC-823, and SGC-7901) would further strengthen the generalizability of our conclusions. Second, although the DEGs and ASEs identified by RNA-seq were validated by RT-qPCR, further experimental approaches are needed to comprehensively decipher the downstream regulatory network of ZFP36. For instance, agarose gel electrophoresis of RT-PCR products is required to confirm specific AS isoform switches, and protein-level changes of key DEGs should be examined by western blotting. Additionally, although ZFP36 bound to the 3’ UTR of LIPG and correlated with increased LIPG expression, future mRNA stability assays (e.g., actinomycin D chase) are required to determine whether this regulation occurs through canonical mRNA stabilization pathways or other mechanisms. Addressing these limitations in future studies will provide a more complete understanding of how ZFP36 exerts its tumor-suppressive functions in GC.
In conclusion, this study demonstrates that ZFP36 may promote LIPG expression and bind to its 3’ UTR region, thereby inhibiting GC progression. These discoveries not only provide novel insights into the molecular regulatory mechanisms of ZFP36 in GC but also offer significant translational value for developing targeted therapeutic strategies, holding promise to revolutionize future GC treatment paradigms.
| 1. | Smyth EC, Nilsson M, Grabsch HI, van Grieken NC, Lordick F. Gastric cancer. Lancet. 2020;396:635-648. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 4042] [Cited by in RCA: 3668] [Article Influence: 611.3] [Reference Citation Analysis (23)] |
| 2. | Yang WJ, Zhao HP, Yu Y, Wang JH, Guo L, Liu JY, Pu J, Lv J. Updates on global epidemiology, risk and prognostic factors of gastric cancer. World J Gastroenterol. 2023;29:2452-2468. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in CrossRef: 469] [Cited by in RCA: 401] [Article Influence: 133.7] [Reference Citation Analysis (6)] |
| 3. | Zhang T, Chen H, Yin X, He Q, Man J, Yang X, Lu M. Changing trends of disease burden of gastric cancer in China from 1990 to 2019 and its predictions: Findings from Global Burden of Disease Study. Chin J Cancer Res. 2021;33:11-26. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 66] [Cited by in RCA: 63] [Article Influence: 12.6] [Reference Citation Analysis (1)] |
| 4. | Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209-249. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 76817] [Cited by in RCA: 71710] [Article Influence: 14342.0] [Reference Citation Analysis (88)] |
| 5. | Guan WL, He Y, Xu RH. Gastric cancer treatment: recent progress and future perspectives. J Hematol Oncol. 2023;16:57. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 763] [Cited by in RCA: 754] [Article Influence: 251.3] [Reference Citation Analysis (13)] |
| 6. | Christodoulidis G, Koumarelas KE, Kouliou MN. Revolutionizing gastric cancer treatment: The potential of immunotherapy. World J Gastroenterol. 2024;30:286-289. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in CrossRef: 40] [Cited by in RCA: 33] [Article Influence: 16.5] [Reference Citation Analysis (0)] |
| 7. | Zhang Z, Guo M, Li Y, Shen M, Kong D, Shao J, Ding H, Tan S, Chen A, Zhang F, Zheng S. RNA-binding protein ZFP36/TTP protects against ferroptosis by regulating autophagy signaling pathway in hepatic stellate cells. Autophagy. 2020;16:1482-1505. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 386] [Cited by in RCA: 401] [Article Influence: 66.8] [Reference Citation Analysis (6)] |
| 8. | Masias C, Vasu S, Cataland SR. None of the above: thrombotic microangiopathy beyond TTP and HUS. Blood. 2017;129:2857-2863. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 81] [Cited by in RCA: 67] [Article Influence: 7.4] [Reference Citation Analysis (0)] |
| 9. | Pillai VG, Bao J, Zander CB, McDaniel JK, Chetty PS, Seeholzer SH, Bdeir K, Cines DB, Zheng XL. Human neutrophil peptides inhibit cleavage of von Willebrand factor by ADAMTS13: a potential link of inflammation to TTP. Blood. 2016;128:110-119. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 66] [Cited by in RCA: 61] [Article Influence: 6.1] [Reference Citation Analysis (0)] |
| 10. | Tang TP, Qin CX, Yu H. MCM3AP-AS1 regulates proliferation, apoptosis, migration, and invasion of breast cancer cells via binding with ZFP36. Transl Cancer Res. 2021;10:4478-4488. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 1] [Cited by in RCA: 7] [Article Influence: 1.4] [Reference Citation Analysis (0)] |
| 11. | Wang H, Chen Y, Guo J, Shan T, Deng K, Chen J, Cai L, Zhou H, Zhao Q, Jin S, Xia J. Dysregulation of tristetraprolin and human antigen R promotes gastric cancer progressions partly by upregulation of the high-mobility group box 1. Sci Rep. 2018;8:7080. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 7] [Cited by in RCA: 12] [Article Influence: 1.5] [Reference Citation Analysis (0)] |
| 12. | Guo J, Qu H, Shan T, Chen Y, Chen Y, Xia J. Tristetraprolin Overexpression in Gastric Cancer Cells Suppresses PD-L1 Expression and Inhibits Tumor Progression by Enhancing Antitumor Immunity. Mol Cells. 2018;41:653-664. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 11] [Reference Citation Analysis (0)] |
| 13. | Guo L, Liu Y, Yan S, Li H, Zhang K, Li J. The RNA-binding protein LARP6 regulates the alternative splicing of related genes in MDA-MB-231 cells. Sci Rep. 2025;15:7883. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 1] [Reference Citation Analysis (0)] |
| 14. | Bu J, Mahan Y, Zhang Y, Zhang S, Wu X, Zhang X, Zhou L. RNA Sequencing Analyses Reveal the Potential Anti-Inflammatory Mechanisms of Acacetin Against ODG/R Injuries in Microglia. J Inflamm Res. 2024;17:3641-3652. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 3] [Reference Citation Analysis (0)] |
| 15. | Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12:357-360. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 21207] [Cited by in RCA: 17323] [Article Influence: 1574.8] [Reference Citation Analysis (7)] |
| 16. | Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28:511-515. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 13804] [Cited by in RCA: 11911] [Article Influence: 744.4] [Reference Citation Analysis (7)] |
| 17. | Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 82919] [Cited by in RCA: 70205] [Article Influence: 5850.4] [Reference Citation Analysis (40)] |
| 18. | Jin L, Li G, Yu D, Huang W, Cheng C, Liao S, Wu Q, Zhang Y. Transcriptome analysis reveals the complexity of alternative splicing regulation in the fungus Verticillium dahliae. BMC Genomics. 2017;18:130. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 39] [Cited by in RCA: 81] [Article Influence: 9.0] [Reference Citation Analysis (0)] |
| 19. | Xia H, Chen D, Wu Q, Wu G, Zhou Y, Zhang Y, Zhang L. CELF1 preferentially binds to exon-intron boundary and regulates alternative splicing in HeLa cells. Biochim Biophys Acta Gene Regul Mech. 2017;1860:911-921. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 55] [Cited by in RCA: 130] [Article Influence: 14.4] [Reference Citation Analysis (0)] |
| 20. | Huang S, Luo K, Jiang L, Zhang XD, Lv YH, Li RF. PCBP1 regulates the transcription and alternative splicing of metastasisrelated genes and pathways in hepatocellular carcinoma. Sci Rep. 2021;11:23356. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 4] [Cited by in RCA: 38] [Article Influence: 7.6] [Reference Citation Analysis (0)] |
| 21. | Xie C, Mao X, Huang J, Ding Y, Wu J, Dong S, Kong L, Gao G, Li CY, Wei L. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 2011;39:W316-W322. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 4298] [Cited by in RCA: 3724] [Article Influence: 248.3] [Reference Citation Analysis (3)] |
| 22. | Uren PJ, Bahrami-Samani E, Burns SC, Qiao M, Karginov FV, Hodges E, Hannon GJ, Sanford JR, Penalva LO, Smith AD. Site identification in high-throughput RNA-protein interaction data. Bioinformatics. 2012;28:3013-3020. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 223] [Cited by in RCA: 263] [Article Influence: 18.8] [Reference Citation Analysis (0)] |
| 23. | Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, Cheng JX, Murre C, Singh H, Glass CK. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576-589. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 11521] [Cited by in RCA: 10755] [Article Influence: 672.2] [Reference Citation Analysis (10)] |
| 24. | Liu S, Li Q, Li G, Zhang Q, Zhuo L, Han X, Zhang M, Chen X, Pan T, Yan L, Jin T, Wang J, Lv Q, Sui X, Xie T. The mechanism of m(6)A methyltransferase METTL3-mediated autophagy in reversing gefitinib resistance in NSCLC cells by β-elemene. Cell Death Dis. 2020;11:969. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 43] [Cited by in RCA: 145] [Article Influence: 24.2] [Reference Citation Analysis (0)] |
| 25. | Kawai S, Fujii T, Shimizu T, Sukegawa K, Hashimoto I, Okumura T, Nagata T, Sakai H, Fujii T. Pathophysiological properties of CLIC3 chloride channel in human gastric cancer cells. J Physiol Sci. 2020;70:15. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 7] [Cited by in RCA: 14] [Article Influence: 2.3] [Reference Citation Analysis (0)] |
| 26. | Cook ME, Bradstreet TR, Webber AM, Kim J, Santeford A, Harris KM, Murphy MK, Tran J, Abdalla NM, Schwarzkopf EA, Greco SC, Halabi CM, Apte RS, Blackshear PJ, Edelson BT. The ZFP36 family of RNA binding proteins regulates homeostatic and autoreactive T cell responses. Sci Immunol. 2022;7:eabo0981. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 22] [Cited by in RCA: 84] [Article Influence: 21.0] [Reference Citation Analysis (0)] |
| 27. | Su H, Liang L, Wang J, Yuan X, Zhao B. ZFP36, an RNA-binding protein promotes hBMSCs osteogenic differentiation via binding with JUN. J Orthop Surg Res. 2024;19:758. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in RCA: 6] [Reference Citation Analysis (0)] |
| 28. | Jiang X, Xiao Y, Hou W, Yu J, He TS, Xu LG. The RNA-binding protein ZFP36 strengthens innate antiviral signaling by targeting RIG-I for K63-linked ubiquitination. J Cell Physiol. 2023;238:2348-2360. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 9] [Cited by in RCA: 8] [Article Influence: 2.7] [Reference Citation Analysis (0)] |
| 29. | Park SB, Lee JH, Jeong WW, Kim YH, Cha HJ, Joe Y, Chung HT, Cho WJ, Do JW, Lee BJ, Park JW, Ko BK. TTP mediates cisplatin-induced apoptosis of head and neck cancer cells by down-regulating the expression of Bcl-2. J Chemother. 2015;27:174-180. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 13] [Cited by in RCA: 16] [Article Influence: 1.5] [Reference Citation Analysis (0)] |
| 30. | Ferri DM, Ayre M, Ariza Bareño L, Stedile M, DiGaudio AV, Fernandez Ugazio G, Kordon EC, Blackshear PJ, Urtreger A, Raimondi AR. TTP as Tumor Suppressor and Inflammatory Regulator in Oral Carcinogenesis. J Dent Res. 2025;104:795-805. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 1] [Cited by in RCA: 3] [Article Influence: 3.0] [Reference Citation Analysis (0)] |
| 31. | Deng K, Wang H, Shan T, Chen Y, Zhou H, Zhao Q, Xia J. Tristetraprolin inhibits gastric cancer progression through suppression of IL-33. Sci Rep. 2016;6:24505. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 23] [Cited by in RCA: 35] [Article Influence: 3.5] [Reference Citation Analysis (0)] |
| 32. | Qin T, Huang M, Wei W, Zhou W, Tang Q, Huang Q, Tang N, Gai S. PLAUR facilitates the progression of clear cell renal cell carcinoma by activating the PI3K/AKT/mTOR signaling pathway. PeerJ. 2024;12:e17555. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 9] [Cited by in RCA: 9] [Article Influence: 4.5] [Reference Citation Analysis (0)] |
| 33. | Ma Z, Lou S, Jiang Z. PHLDA2 regulates EMT and autophagy in colorectal cancer via the PI3K/AKT signaling pathway. Aging (Albany NY). 2020;12:7985-8000. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 129] [Cited by in RCA: 118] [Article Influence: 19.7] [Reference Citation Analysis (0)] |
| 34. | Xin B, Liu G, Zhang C, Wang B, Shi L. [LncRNA LINC00342 regulates gastric cancer cell proliferation, migration and invasion by targeting miR-596]. Nan Fang Yi Ke Da Xue Xue Bao. 2023;43:1761-1770. [RCA] [PubMed] [DOI] [Full Text] [Reference Citation Analysis (0)] |
| 35. | Tu Y, Wu X, Yu F, Dang J, Wang J, Wei Y, Cai Z, Zhou Z, Liao W, Li L, Zhang Y. Tristetraprolin specifically regulates the expression and alternative splicing of immune response genes in HeLa cells. BMC Immunol. 2019;20:13. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 16] [Cited by in RCA: 32] [Article Influence: 4.6] [Reference Citation Analysis (0)] |
| 36. | Gourley C, Paige AJW, Taylor KJ, Scott D, Francis NJ, Rush R, Aldaz CM, Smyth JF, Gabra H. WWOX mRNA expression profile in epithelial ovarian cancer supports the role of WWOX variant 1 as a tumour suppressor, although the role of variant 4 remains unclear. Int J Oncol. 2005;26:1681-1689. [RCA] [PubMed] [DOI] [Full Text] [Cited by in Crossref: 3] [Cited by in RCA: 23] [Article Influence: 1.1] [Reference Citation Analysis (0)] |
| 37. | Tu J, Huo Z, Yu Y, Zhu D, Xu A, Huang MF, Hu R, Wang R, Gingold JA, Chen YH, Tsai KL, Forcioli-Conti NR, Huang SXL, Webb TR, Su J, Bazer DA, Jia P, Yustein JT, Wang LL, Hung MC, Zhao Z, Huff CD, Shen J, Zhao R, Lee DF. Hereditary retinoblastoma iPSC model reveals aberrant spliceosome function driving bone malignancies. Proc Natl Acad Sci U S A. 2022;119:e2117857119. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 26] [Cited by in RCA: 28] [Article Influence: 7.0] [Reference Citation Analysis (1)] |
| 38. | Yi J, Wu M, Zheng Z, Zhou Q, Li X, Lu Y, Liu P. Integrated analysis of DNA methylome and transcriptome reveals SFRP1 and LIPG as potential drivers of ovarian cancer metastasis. J Gynecol Oncol. 2023;34:e71. [RCA] [PubMed] [DOI] [Full Text] [Cited by in RCA: 4] [Reference Citation Analysis (0)] |
| 39. | Dong X, Wang G, Zhang G, Ni Z, Suo J, Cui J, Cui A, Yang Q, Xu Y, Li F. The endothelial lipase protein is promising urinary biomarker for diagnosis of gastric cancer. Diagn Pathol. 2013;8:45. [RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)] [Cited by in Crossref: 12] [Cited by in RCA: 20] [Article Influence: 1.5] [Reference Citation Analysis (0)] |