GPD1L may inhibit the development of esophageal squamous cell carcinoma through the PI3K/AKT signaling pathway： bioinformatics analysis and experimental exploration

GPD1L may inhibit the development of esophageal squamous cell carcinoma through the PI3K/AKT signaling pathway： bioinformatics analysis and experimental exploration | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article GPD1L may inhibit the development of esophageal squamous cell carcinoma through the PI3K/AKT signaling pathway： bioinformatics analysis and experimental exploration LanLan Gan, Lu Zhou, ALan Chu, Chen Sun, YongTai Wang, MengLin Yang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4843022/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2024 Read the published version in Molecular Biology Reports → Version 1 posted 7 You are reading this latest preprint version Abstract Background Esophageal squamous carcinoma (ESCC) is the most prevalent pathological subtype of esophageal cancer (EC). It has the characteristics of significant local invasion, quick disease progression, high recurrence rates, and a dismal prognosis for survival. Phosphatidylinositol 3-kinase/serine-threonine kinase (PI3K/AKT) is a signaling system whose aberrant activation regulates downstream factors, leading to the promotion of cancer development. This study looks at a protein called Glycerol-3-phosphate dehydrogenase 1-like (GPD1L), which strongly affects the development of several cancers. However, its association with ESCC development and its underlying mechanisms are not clear. Methods In this paper, we analyzed six ESCC transcriptome data obtained from the GEO database. We utilized bioinformatics technology and immunohistochemistry to differentially analyze GPD1L levels of mRNA and protein expression in ESCC and normal adjacent tissues. Furthermore, we conducted survival, co-expression, enrichment, immune infiltration and drug sensitivity analysis. Finally, we further investigated the role and mechanism of GPD1L by Western Blot (WB), Cell Counting Kit-8 (CCK8), wound healing assay, Transwell assay, and flow cytometry. Results The findings manifest that the expression of GPD1L was low in ESCC, and functional experiments showed that GPD1L promoted apoptosis in vitro while blocking cell migration, invasion, and proliferation. Based on mechanism research, GPD1L's impact on ESCC could be explained by its suppression of the PI3K/AKT signaling pathway's activation. Conclusion To sum up, our findings imply that GPD1L may impede the initiation and advancement of ESCC via modulating the PI3K/AKT signaling pathway. GPD1L is considered to be a promising therapeutic target and biomarker to diagnose and treat ESCC. GPD1L ESCC PI3K/AKT bioinformatics biological behavior Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Key points We demonstrate the tumor suppressive role of GPD1L in ESCC. We reveal a novel mechanism by which GPD1L functions, potentially by modulating the PI3K/AKT signaling pathway. Bioinformatics analysis was conducted to investigate the potential correlation between GPD1L and ESCC, including related genes, immune cell and immunoinfiltration analysis, drug sensitivity, etc. 1 INTRODUCTION Esophageal cancer (EC) is one of the major health challenges in the world, and its major pathological subtypes include squamous cell carcinoma, adenocarcinoma, etc. In 2020, EC statistics from 185 countries revealed that there were 604,100 new cases of EC, ranking it eighth in the world in terms of incidence. Additionally, there were 544,100 deaths from EC, placing it sixth in the world for morbidity and mortality 1 . Approximately 14% were esophageal adenocarcinoma (EAC), while 85% of EC cases were esophageal squamous cell carcinoma (ESCC). Easy local invasion, quick disease progression, high recurrence rates, and a dismal prognosis for survival are the hallmarks of ESCC 2 . The 5-year overall survival rate for EC individuals is still low, remaining at 10% − 30% 3 4 , despite the availability of numerous treatments such as surgery, radiation, chemotherapy, immunotherapy, endoscopic resection, ablation, cryotherapy, and argon ion coagulation 5 – 7 . Therefore, we urgently need to further study the pathogenesis of EC and explore new treatment methods and strategies. The protein Glycerol-3-phosphate dehydrogenase 1-like (GPD1L) has the ability to convert glycerol triphosphate into phosphoglycerol 8 . The sequence similarity between it and glycerol-3-phosphate dehydrogenase 1 (GPD1) is 84% 9 . Previous studies have clarified its effect on cardiac Na-ion channels, which reduces the inward sodium current. Defects in this gene can lead to Brugada syndrome type 2 (BRS2) and sudden infant death syndrome (SIDS) 10 – 12 . Additionally, recent research has demonstrated that GPD1L has a function in different tumors, such as lung adenocarcinoma, renal cell carcinoma, colorectal cancer, oropharyngeal carcinoma, squamous carcinoma of the head and neck, etc. 13 – 15 . Therefore, it is assumed that GPD1L may be directly or indirectly involved in energy metabolism, regeneration of blood vessels, cell proliferation and survival. However, GPD1L’s association with ESCC development and the mechanism of its action is still not clear. In human cancers, the PI3K/AKT is frequently activated. Under physiological conditions, this pathway is triggered by cytokines, insulin, growth factors, etc. to regulate critical metabolic processes, including nutrient transporters, glucose metabolism, macromolecule biosynthesis, and redox homeostasis to promote both whole-body metabolic homeostasis and individual cell development and metabolism 16 . The PI3K/AKT pathway was aberrantly activated in tumor cells. The impact of its aberrant activation in tumorigenesis and development as well as its mechanism of action are continuously being discovered to inform new therapeutic strategies. In this study, we investigated the association between GPD1L and ESCC patients using bioinformatics analysis of data from TCGA and GEO databases. Our biofunctional experiments demonstrated that GPD1L inhibits the biological behavior of cells, such as cell migration, invasion, and proliferation while promotes apoptosis in vitro. Additionally, WB results suggest that GPD1L may inhibit the development of ESCC via the PI3K/AKT signaling pathway. Based on our findings, it is suggested that GPD1L holds promise as a potential target for treating ESCC. 2 MATERIALS and METHODS 2.1 Data pre-processing and patient inclusion Six datasets, namely GSE20347, GSE23400, GSE53625, GSE67269 (GPL96), GSE67269 (GPL571), and GSE161533, were selected for analysis. Among these, the dataset GSE67269 contains 34 pairs of datasets based on the GPL96 platform and 73 pairs of datasets based on the GPL571 platform. The mRNA expression raw data of all datasets were preprocessed as follows: firstly, the gene expression data from each dataset were aggregated by calculating the average values; secondly, we used the "limma" package to normalize them. Additionally, the data from GSE161533 was log-transformed. The analysis was conducted using R software (v4.2.1). Furthermore, between 2022 and 2023, paraffin sections of malignant and normal paracancerous tissues were gathered from the Second Affiliated Hospital of Zhengzhou University's Department of Pathology. The study's inclusion criteria consisted of patients meeting the following requirements: possessing residual specimens from the specified department, receiving a diagnosis of ESCC and falling within the age range of 18 to 75 years, having undergone biopsy procedures prior to antitumor treatment, and providing informed consent. Exclusion criteria encompassed the coexistence of additional malignancies, psychological disorders, and contraindications to anti-tumor therapy. Approval for the experiment was obtained from the Ethics Committee of the Second Affiliated Hospital of Zhengzhou University. 2.2 Bioinformatics and the analysis After data preprocessing, utilizing the "limma" package, we initially analyze GPD1L expression in ESCC and normal adjacent tissues across six datasets. We employed paired t-tests to determine if there were significant differences and subsequently investigated the expression of GPD1L in ESCC. Among the six datasets, the GSE53625 dataset contained transcriptomic and clinical data from 179 patients, making it suitable for further bioinformatics analysis. Secondly, based on the median GPD1L expression, ESCC patients were categorized into two groups with high expression (n = 90) and low expression (n = 89). Then we conduct Kaplan-Meier survival analysis by using the "survival" and "surminer" packages. Overall survival curves were constructed to assess whether GPD1L was associated with OS between these two groups. Thirdly, we probed for genes that may be associated with GPD1L in ESCC using a threshold of |cor| > 0.4 and P < 0.05. Genes showing high correlation with GPD1L were visualized using Circos plots. Subsequently, we performed enrichment analysis on the identified GPD1L-related genes to elucidate their functional mechanisms and enriched pathways via the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, we utilized Gene Set Enrichment Analysis (GSEA) to explore the pathways and functional mechanisms associated with differential gene enrichment in the low expression group of GPD1L. This process employ some R packages, such as "ComplexHeatmap", "dplyr", "RColorBrewer", "circle", "clusterProfiler", "enrichplot", "org.hss.e.g.db", "corrlot", "ggExtra", "ggpuber", and "ggplot 2" 17 . Finally, we analyzed the fraction of immune cells in the tumor samples from GSE53625. Then, in the two GPD1L expression groups, we compared the levels of immune cell infiltration, and also examined the correlation of GPD1L with immune cells and with immune checkpoint-related genes. Additionally, we obtained data from GDSC ( https://www.Cancerrxgene.org/ ) to assess the sensitivity of GPD1L to anticancer drugs. During this process, we utilized various packages including "reshape2", "ggpubr", "violot", "ggplot2", "corrplot", "ggExtra", "parallel", and "oncoPredict" 17 18 . 2.3 Cell lines and cell culture The human ESCC cell line Kyse150 was obtained from Shanghai Zhongqiao Xinzhou Biotechnology Co. Ltd, and the normal human esophageal epithelial cell line HEEC was obtained from Nanjing Wanmuchun Biotechnology Co. The other cell lines, such as Het-1A, Kyse450, and ECa109 were provided by the Medical Research Centre of the Second Affiliated Hospital of Zhengzhou University. Three ESCC cell lines were cultured in medium containing 89% RPMI 1640, 1% penicillin-streptomycin solution (Zhongqiao Xinzhou Biotechnology Co., Ltd., China), 10% fetal bovine serum (Procell Biotechnology Co., Ltd., China). The two normal esophageal epithelial cell lines were grown in medium containing 89% DMEM (Procell Biotechnology Co., Ltd., China) with the same supplements as mentioned above. All cells were maintained at 37℃ with a CO 2 concentration of 5% under saturated humidity. 2.4 Cell transfection The GPD1L empty vector plasmid (GPD1L-MOCK) and overexpression plasmid (GPD1L-OE) were purchased from Tsingke Company, while the GPD1L negative control (GPD1L-NC) and small interfering RNA (GPD1L-SI) were ordered from Henan Biolabs Bio-tech Co. Ltd. A six-well plate were inoculated in an appropriate amount of cells and reached 70% density after 16–24 hours. Subsequently, we used Lipofectamine 8000 reagent (Beyotime, China), and the plasmid and siRNA were introduced respectively into ECa109 and Kyse450 cells via transfection. The siRNA sequences can be found in Table 1 . Table 1 Sequences of each assay assay sequence Si-RNA Si-NC:5′-UUCUCCGAACGUCACGUTT-3′ Si1-GPD1L:5′-GCAGCAAAGUAAUGGAGAATT-3′ Si2-GPD1L:5′-CGAAAGCAGACCAGUUCAATT-3′ Si3-GPD1L:5′-GCUGUGGAGACAACACCAATT-3′ RT-qPCR GAPDH-F:5′-ACAACAGCCTCAAGATCATCAGC-3′ GAPDH-R:5′-GCCATCACGCCACAGTTTCC-3′ GPD1L-F:5′-ACGGTGGTTGATGATGCAGACACT-3′ GPD1L-R:5′-CGGATGACGGCCGCTTTGGT-3′ 2.5 Immunohistochemical staining Firstly, 3µm thick sections were obtained from paraffin-embedded human ESCC and their corresponding normal paracancerous tissues. The sections were then baked for 2 hours, deparaffinized, and antigenically repaired with citrate for 2.5 minutes. Subsequently, the sections were blocked by incubating with an appropriate amount of peroxide block for 5 minutes, followed by incubation with GPD1L antibody (CAT. NO. PA5-24216, 1:100, Thermofisher) for 30 minutes at 25℃. Post-primary and polymer were then added to the sections. Fresh DAB was stained for approximately 2 minutes, followed by washing and staining with hematoxylin. The sections were reblued using Roche, dehydrated in gradient ethanol and blocked before being observed under a light microscope at a magnification of 100x. Photographs were taken according to the intensity of staining and the proportion of positive cells. Immunohistochemical staining results were scored semi-quantitatively as follows: Degree of staining - negative staining is marked as 0 points; light yellow is 1 point; brownish yellow is 2 points; reddish brown 3 points. Positive range - <5% scored as 0 points; between 5% ~24% scored as 1 point; between25% ~50% scored as 2 points; between 51%~74% scored as 3 points; and ≥ 75% scored as 4 points. The final score result was determined by multiplying the degree of staining score by the positive range score: negative scored as 0 points; low expression scored as < 5 points, and high expression scored as ≥ 5 points. Scoring was independently performed by two pathologists. 2.6 Cell proliferation The experimental and control groups of ECa109 and Kyse450 cells were seeded into 96-well plates at a density of 3000 cells. After 6 hours, add 10 µl CCK8 reagent per well and incubate away from light for 1.5 hours. This time point was considered as 0h, and then we use a microplate reader (Thermo Fisher Scientific, USA) to measure the optical density (OD) values at 450 nm at 0h, 24h, 48h, and 72h, respectively. 2.7 Cell migration and invasion The wound healing assay was utilized to assess the migratory capacity of cells. In brief, ECa109 and Kyse450 cells were individually inoculated in 6-well plates, and transfection treatment was conducted once the cell density reached 70%-80%. The cells were then observed for 24–48 hours. Upon reaching a cell density of 100%, scratches were made with a 10 µl plastic pipette tip. Subsequently, the cells were cultured in medium containing 1% serum, and images of the scratched areas were captured at 0h, 24h, 48h, and 72h time points. The results were analyzed using the following formula: cell migration area rate = (0h scratch area − 24h scratch area)/0h scratch area x100%. For the transwell experiments, we utilized transwell culture dishes (Corning, USA) and Matrigel (BD, USA) to evaluate the migratory and invasive potential. In brief, cells were suspended in serum-free medium. Then, 500 µl of medium containing 20% serum was added to the lower chamber and 200 µl of cell suspension was added to the upper chamber. After 36 hours, the non-migrating cells above the chamber were removed, and each well was treated with 1ml 4% paraformaldehyde for 1h at room temperature, followed by staining with crystal violet for 15 minutes. Finally, the cells were photographed under a microscope. The invasion assay required the spreading of 200ul of matrix gel dilution before implanting the appealing cells in the upper chamber. Same as above for the rest. 2.8 Flow cytometry Approximately 1x10 5 cells were inoculated into 24-well plates in the presence of 10% fetal bovine serum. After 48 hours of transfection treatment, as per the instructions provided by the Apoptosis Kit (Yakoin, China), each well was added 1ml of freshly prepared apoptosis-inducing solution (apoptosis inducer : complete medium = 1 : 2000), and then they were incubated for 24h. Subsequently, the cells were harvested and stained with Annexin V-FITC and propidium iodide (PI) from the apoptosis kit. The stained cells were analyzed using a flow cytometry system (BeamCyte Flow Cytometer; Bidake Biotechnology Co., Ltd., China), with 10,000–30,000 cells recorded each time to determine the rate of apoptosis. CytoSYS v1.0 software (Bidake Biotechnology Co., Ltd., China) was utilized for data analysis. 2.9 Real-Time qPCR Cells were lysed in six-well plates by adding 1 ml of TRIzol. Total RNA was then extracted using chloroform and isopropanol following the reagent vendor's instructions, and subsequently tested for purity and concentration using a spectrophotometer (Thermo Scientific, USA). Subsequently, we use a reverse transcription kit and a temperature gradient PCR instrument to transcribe 1 µg of RNA into complementary cDNA. Finally, the internal reference gene sequence and the target gene sequence were added, followed by RT-qPCR using an amplification kit and a real-time fluorescence quantitative PCR instrument (Thermo Fisher Scientific, USA). The primer sequences can be found in Supplement 1. 2.10 Western blot Briefly, ECa109 and Kyse450 cells were inoculated in a 6-well plate. When the cell fusion reached 80%-100%, a newly configured mixture of RIPA protein lysate (Servicebio, China) and PMSF (Servicebio, China) at a ratio of 100:1 was added to the cells to lyse them. The proteins were extracted by centrifugation at 4℃ and high speed, and we utilized the BCA kit (Servicebio, China) to determine the protein concentration. Then, an appropriate loading buffer was added, boiled at 100°C for 10 min. The denatured proteins were separated on 10% PAGE gels at constant voltages of 80 V and 120 V respectively before being transferred to methanol-activated polyvinylidene fluoride membranes (PVDF) in transmembrane solution 19 . The excess protein was stored at-80℃. After blocking with a commercial rapid-sealing solution (Servicebio, China), primary antibodies were incubated for 14–18 hours at 4°C on PVDF membranes with a pore size of 0.22 nm. Following three washes in Tris-buffered saline-Tween buffer (TBST), the membranes were incubated with goat anti-rabbit IgG/HRP secondary antibody and visualized using the ECL Protein Detection System (Yakoin, China). Primary antibodies used included Anti-GPD1L (CAT. NO. PA5-24216, 1:1,000, Thermofisher, ), anti-PI3K/AKT signaling pathway panel (CAT. NO. ab283852, 1:1,000, Abcam), anti-β-actin (CAT. NO. GB15003, 1:2,000, Servicebio), and anti-α-tubulin(CAT. NO. 11224-1-AP, 1:2,000, Proteintech). The phosphorylation sites of phosphorylated AKT(P-AKT)were S472, S473, and S474. The HRP-conjugated Affinipure goat anti-rabbit IgG(H + L)(CAT. NO. SA00001-2, 1:2,000, Proteintech) serves as the secondary antibody. 2.11 Statistical analysis Each experiment was conducted three times, and statistical analysis was performed using SPSS 26.0 software (IBM, USA). Continuous measurement data are presented as "mean ± standard deviation (SD)". The significance of the difference between the two groups was determined using appropriate tests such as Student's t-test, Chi-square test, Fisher's exact test, or exact probability test. 3 RESULTS 3.1 GPD1L expression is downregulated in ESCC Six datasets, totaling 384 pairs of ESCC and normal adjacent tissue samples, were screened from the GEO database. When compared to the normal tissue, the tumor exhibited significantly low expression of GPD1L, indicating a statistically significant difference (Fig. 1 .A). This suggests that the expression of GPD1L is down-regulated in ESCC. To further validate the results of the bioinformatics analysis, we conducted immunohistochemistry on 36 pairs of ESCC and normal paracancerous tissues. There are 28 cases of low GPD1L expression in ESCC and 4 cases in normal paracancerous tissues. The results revealed a statistically significant decrease in protein expression of GPD1L in ESCC tissues(Fig. 1 .B and Table 2 ). Table 2 Expression of GPD1L in ESCC and normal paracancerous tissues Group Cancer (n = 36) Normal (n = 36) χ2 P-value GPD1L Low High 28 8 4 32 29.756 < 0.0001 Additionally, we analyzed the protein level expression of GPD1L in normal esophageal epithelial cells (HEEC, Het-1A) and various ESCC cell lines (ECa109, Kyse150, Kyse450, TE-1) using WB. The findings indicated reduced protein expression levels of GPD1L in both ESCC tissues and cell lines when compared to normal paracancerous tissues and normal esophageal epithelial cells (Fig. 1 .C). Furthermore, by detecting differences in the protein level of GPD1L expression in several ESCC cell lines, ECa109 was identified as a GPD1L low-expressing ESCC cell line (Kyse150 was intolerant to various transfection reagents and the transfection efficiency of TE-1 was unsatisfactory) while Kyse450 was identified as a high-expressing one. These selections were based on observed differences at the protein level for the completion of further experiments. 3.2 Identifying and enriching genes relevant to GPD1L Survival analysis (Fig. 2 .A) revealed a significantly lower survival rate in the GPD1L low expression group. The Circos plot (Fig. 2 .B) demonstrated that six genes showed a significant positive association with GPD1L, while five genes showed a substantial negative relationship with it. According to GO enrichment analysis, GPD1L-related genes were predominantly enriched in the Organic acid biosynthetic process lipid modification, Carboxylic acid biosynthetic process (BP), Actin filament bundle, Peroxisome, microbody (CC), Heme binding, Tetrapyrrole binding and Iron ion binding (MF). In the KEGG project, they were enriched in Cytokine − cytokine receptor interaction, Toxoplasmosis, Hematopoietic cell lineage, and Cell adhesion molecules (Fig. 2 .C). GSEA showed enrichment of Arachidonic acid metabolism, Cell adhesion molecules cams, Drug metabolism cytochrome p450, and Intestinal immune network for IgA production in the KEGG project for the low expression group of GPD1L. Additionally, Embryonic skeletal system development, Embryonic skeletal system morphogenesis, and Positive regulation of myotube differentiation were significantly enriched in BP. Furthermore, External side of plasma membrane, Mitochondrial envelope, Mitochondrial matrix, Mitochondrial protein-containing complex, Organelle inner membrane, Receptor complex, and Side of membrane were significantly enriched in CC. Lastly, MHC protein complex binding, Arachidonic acid monooxygenase activity, Immune receptor activity, Aromatase activity, Incorporation of one atom of oxygen, Oxidoreductase activity acting on paired donors with incorporation or reduction of molecular oxygen reduced flavin or flavoprotein as one donor and Oxidoreductase activity acting on CH-OH group of donors were significantly enriched in MF (Fig. 2 .D). 3.3 Immune infiltration and drug sensitivity analysis of GPD1L in ESCC First, an immune correlation analysis was conducted to explore the association between GPD1L and immunity in ESCC. The results from the Boxplot (Fig. 3 .A) revealed that in the low expression group of GPD1L, there was a lower infiltration level of Plasma cells and T cells regulatory (Tregs), while the infiltration level of Macrophages M0 and Mast cells activated was higher. As shown in Fig. 3 .B, Macrophages M2, Mast cells resting, T cells CD8, T cells follicular helper and the degree of infiltration of Tregs have a positive correlation with GPD1L expression, while Macrophages M0, Monocytes, T cells CD4 memory resting, and Mast cells activated exhibited a negative correlation with GPD1L. Figure 3 .C demonstrated that GPD1L was positively correlated with immune checkpoint genes such as CD48, TIGIT, BTLA, CD27, CD200R1, CD28, IDO1, CD40LG, IDO2, CD244, PDCD1, TNFSF18, TMIGD2, and negatively correlated with CD276 and CD44. In addition to this analysis on immune correlation, the GPD1L high and low expression groups were also compared to ascertain whether there were any differences in the 50% maximal inhibitory concentration (IC50) between the commonly used chemotherapeutic agents and the molecularly targeted agents for ESCC. The results indicated that in the GPD1L low-expression group, the IC50 values of PI3K/AKT pathway inhibitors (Taselisib, Afuresertib, Uprosertib) were significantly higher. Additionally, the IC50 values of several EGFR tyrosine kinase inhibitors (Gefitinib, Afatinib, Erlotinib) and mTOR inhibitors (Rapamycin) were also significantly elevated. However, the IC50 value of IGFIR was significantly lower. There were no significant correlations were observed between the drugs 5-Fluorouracil, Paclitaxel, Oxaliplatin, and Cisplatin and GPD1L expression levels (Fig. 3 .D). To sum up, our bioinformatics analysis' results point to a potential involvement for GPD1L in ESCC. 3.4 Up-regulation of GPD1L expression inhibits the development of ESCC To further explore the potential biological roles of GPD1L, we performed in vitro cellular experiments. ECa109 cells with low expression of GPD1L were chosen for transfection with a GPD1L overexpression plasmid. RT-qPCR and WB analysis confirmed the up-regulation of GPD1L expression in ECa109 cells (Fig. 4 .A), and functional experiments were subsequently performed. CCK8 assay showed that ECa109 cell proliferation was markedly inhibited by up-regulation of GPD1L (Fig. 4 .B). As demonstrated by wound healing assay, overexpression of GPD1L significantly reduced ECa109 cells' capacity to migrate (Fig. 4 .C). Transwell assay demonstrated that GPD1L overexpression dramatically reduced ECa109 cells' capacity for invasion and migration (Fig. 4 .D). Moreover, GPD1L overexpression was shown to significantly accelerate apoptosis in flow cytometry assays (Fig. 4 .E). 3.5 Down-regulation of GPD1L expression promotes ESCC development Kyse450 cells with high GPD1L expression were chosen for GPD1L small interfering RNA transfection treatment. RT-qPCR analysis revealed that siRNA1 had the most effective knockdown effect, thus it was selected for subsequent experiments. WB confirmed the reduction of GPD1L expression in Kyse450 cells (Fig. 5 .A). Functional experiments revealed that the silencing GPD1L expression in Kyse450 significantly promoted cell proliferation, migration, and invasive capacity, while also markedly reducing apoptosis (Fig. 5 .B ~ E). 3.6 GPD1L may regulate the PI3K/AKT pathway in vitro to inhibit the development of ESCC To investigate the mechanism underlying the inhibitory effect of GPD1L on ESCC, we conducted a bioinformatics analysis and literature summary to identify a potential association between GPD1L and the PI3K/AKT pathway. Subsequently, WB analysis was utilized to validate this relationship. Our findings revealed that overexpression of GPD1L in ECa109 cells significantly suppressed the phosphorylation of PI3K/AKT (Fig. 6 .A, B). Conversely, the knockdown of GPD1L in Kyse450 cells markedly enhanced the activation of PI3K/AKT (Fig. 6 .C, D). These results indicate that GPD1L may exert its inhibitory effect on ESCC by suppressing the activation of the PI3K/AKT pathway. 4 DISCUSSION EC is one of the most important global health concerns, and in China, the Taihang Mountains region and the southern coastal areas are the high-prevalence areas of this cancer. ESCC, the primary pathological type of EC examined in this study, exhibits typical characteristics of malignant tumors 1 3 4 . There is an urgent need for comprehensive research into the development mechanism of EC and the creation of more targeted therapies suitable for patients. GPD1L, the focus of this paper, was first found to be closely associated with the heart diseases, such as SIDS and BRS 20 , and its pathogenesis is mainly related to cardiac sodium channels 10 – 12 . It was not until 2011 that researchers discovered the gene's relationship with HIF-1α. Several studies in recent years have found that GPD1L exhibits low mRNA and protein expression levels in some malignant tumor cells or tissues 13 – 15 . The mechanism of its cancer inhibitory effect shows a negative feedback loop regulation, in brief, GPD1L can inhibit the expression of HIF-1α, thus playing an inhibitory role in the development of tumor; and under hypoxic conditions, the expression of HIF-1α is elevated, which promotes the downstream targets (e.g. miR-210, etc.), which in turn inhibit GPD1L 21 22 . Recent studies have found that GPD1L is closely associated with mitochondrial autophagy in renal cell carcinoma 13 , further confirming its role in inhibiting cancer development; however, its association with ESCC development and its underlying mechanisms are not clear. In this study, single-gene differential analysis, immunohistochemistry, and multi-cell line WB experiments verified that GPD1L was lowly expressed in ESCC; in addition, the co-expression analysis yielded that GPD1L was positively correlated with a number of genes such as EPB41L4A, RBM47, P4HTM, EYA2, ACADSB, FOXA1, etc. These genes have been proven to inhibit the development of various cancers by many studies 23 – 25 . Especially FOXA1 has been found to have a role in EC 26 ; a negative correlation with FBLIM1, SNAI2, SAMD14, RFLNB, CSPG4, and many papers have demonstrated its cancer-promoting effect in various tumors 27 – 30 . To further explore the effect of GPD1L on ESCC, we conducted in vitro functional assays and confirmed that higher levels of GPD1L in two cell lines, ECa109 and Kyse450, inhibited biological behaviors of ESCC, such as growth speed, invasiveness, metastatic potential and promoted apoptosis. These experiments all verified the above conjectures. In order to further explore the GPD1L’s mechanism in ESCC, enrichment analysis was continued. We found that GPD1L and its related genes are mainly closely related to the metabolism and synthesis of a variety of substances. For example, GO analysis yielded that GPD1L is mainly enriched in peroxisomes, iron ion binding, etc. Peroxisomes play a crucial role in the regulation of immune response and inflammation by affecting lipid metabolism and reactive oxygen species generation and may be a therapeutic target for inflammation-related diseases such as ESCC 31 32 . Intracellular accumulation of iron ions disrupts cell membrane integrity and subsequently produces the well-known “iron death”. Iron death is intricately linked to the progression of tumors, especially the selective killing of tumor cells with abnormal iron metabolism 33 . The mechanism of iron death can be used as a therapeutic target for EC through the induction of EC cell death, and enhancement of the sensitivity of radiotherapy 34 . Whether GPD1L can inhibit ESCC through the above analyzed mechanism of action needs to be verified in further experiments. In KEGG analysis, GPD1L and its related genes were mainly enriched in cytokine-cytokine receptor interactions, and cell adhesion molecules. The former is a key link in cell signaling, and is essential for immune response, cell proliferation, differentiation, apoptosis and so on. The latter mainly includes integrins, calcineurin, selectins, etc. A large amount of research literature shows that these adhesion molecules significantly affect cancer cell proliferation, infiltration, and metastasis 35 . In ESCC, their expression changes are closely associated with signal transduction pathways such as AKT, Wnt/β-linker protein, and Rho GTPases. GSEA showed that the GPD1L low expression group was enriched in the KEGG project for arachidonic acid metabolism, cell adhesion molecules, drug metabolism cytochrome p450, and intestinal immune network for IgA production. These are closely related to the development of various types of cancer, especially arachidonic acid and cell adhesion molecules have a role in promoting the development of ESCC 35 – 37 . Cytochrome P450 affects most drug metabolism, which also implies that GPD1L expression may affect the sensitivity of ESCC patients to anticancer drugs 38 . Previous studies have found that GPD1L is closely related to mitochondria and their metabolic activities 13 39 , and GSEA analysis revealed that in ESCC cell fraction(CC), GPD1L was enriched in several mitochondrial components, such as envelope, matrix, and protein-containing complexes, suggesting that there may be a similar role for GPD1L in ESCC. In the molecular function(MF) analysis, it is not difficult to see that GPD1L plays an important role in biological functions such as redox reaction, immune response, and inflammatory response in the development of ESCC. We continued the immune infiltration analysis of GPD1L. From the differential analysis of immune infiltration, GPD1L not only was positively correlated with T-cell regulation and activation, as well as macrophage M2, but also negatively correlated with macrophage M0 and activated mast cells. "T cells" are an important component of the immune system and their role in tumor development has been widely discussed and applied 40 . For example, immune checkpoint inhibitors (PD1/PDL1) play a cancer-suppressive role by removing the inhibition of T cell activation by tumor cells 41 , and the emerging CAR-T therapy reprograms the patient's own T cells to attack cancer cells 42 . The role of macrophage M0, a new classification intermediate between M1 and M2, in cancer has yet to be investigated. M2 is usually considered a pro-cancer in the progression of malignant tumors, such as ESCC 40 43 . While activated mast cells have both pro-cancer and cancer-suppressive effects, influenced by the mediators they release and the tumor microenvironment 44 . These results suggest that GPD1L may affect the immune microenvironment of ESCC through these immune cells. Immune checkpoint analysis yielded that GPD1L was positively correlated with several CD28 superfamily (CD28, BTLA) 45 46 , tumor necrosis factor superfamily (TNFSF18, CD27, CD40LG) 47 – 49 , TIGIT 50 and other inhibitory immune checkpoints; and negatively correlated with CD276 and CD44, which have pro-cancer effects. In terms of drug sensitivity, although GPD1L does not affect the sensitivity of ESCC patients to drugs such as 5-fluorouracil, low expression increases sensitivity to PI3K/AKT pathway inhibitors(Taselisib, Afuresertib, Uprosertib), EGFR tyrosine kinase inhibitors(Gefitinib, Afatinib, Erlotinib) and mTOR inhibitors (Rapamycin), as well as decreasing sensitivity to IGF1R 51 – 53 . The PI3K/AKT signaling pathway is commonly activated in human cancers. Through a cascade phosphorylation reaction, PI3K and AKT successively produce phosphorylated PI3K (P-PI3K) and phosphorylated AKT (P-AKT) with activation ability. P-AKT can regulate various intracellular downstream factors such as mTOR, HIF-1α, NF-κB, Bad, caspase, etc., which are involved in cellular autophagy regulation, aerobic glycolysis regulation inhibition of apoptosis influence on protein synthesis promotion of tumor cell proliferation, infiltration, metastasis, and migration among other cellular biological functions 54 – 56 . Considering the 84% homology between GPD1 and GPD1L 9 , it has been found that GPD1 can affect the lipid metabolism of cancers through the PI3K/AKT pathway in breast cancer 57 . In summary, this paper continued to explore whether GPD1L affects the biological function of ESCC through the PI3K/AKT signaling pathway. We performed several cell phenotyping experiments and WB experiments for validation and concluded that overexpression of GPD1L affects the activation of the PI3K/AKT signaling pathway, which may consequently inhibit the biological function of ESCC, and conversely, downregulation of GPD1L promotes them by activating PI3K/AKT signaling pathway. Therefore, GDP1L may act as an inhibitor for the development of ESCC. However, this study still has some limitations, and more in-depth functional studies are required to elucidate the underlying mechanisms. Furthermore, there is a need to further explore the role that GPD1L plays in ESCC metabolism and its potential impact on ESCC metabolic reprogramming, which is a fundamental feature of malignant tumors. Additionally, the assessment of the therapeutic significance of GPD1L is crucial. Based on previous studies, it is also necessary to investigate whether the high expression of this gene can disrupt the hypoxic microenvironment on which tumor cell growth depends. Moreover, the impact of GPD1L on tumor cells through aerobic glycolysis under aerobic conditions requires further elucidation. The long-term goal of this research is to address these issues and integrate theory with practical applications for clinical use. CONCLUSION To sum up, we concluded that overexpression of GPD1L affects the activation of the PI3K/AKT signaling pathway, which may consequently inhibit the biological function of ESCC, and conversely, downregulation of GPD1L promotes them by activating PI3K/AKT signaling pathway. Therefore, GDP1L may act as an inhibitor for the development of ESCC. LIST OF ABBREVIATIONS EC -Esophageal cancer ESCC -Esophageal squamous carcinoma EAC -Esophageal adenocarcinoma GPD1L -Glycerol-3-phosphate dehydrogenase 1-like GPD1 -Glycerol-3-phosphate dehydrogenase 1 PI3K/AKT -Phosphatidylinositol 3-kinase/serine-threonine kinase BRS2 -Brugada syndrome type 2 SIDS -Sudden infant death syndrome WB -Western Blot CCK8 -Cell Counting Kit-8 GO -Gene Ontology KEGG -Kyoto Encyclopedia of Genes and Genomes GSEA -Gene Set Enrichment Analysis MOCK -empty vector plasmid OE -overexpression plasmid NC -negative control SI -small interfering RNA OD -optical density PVDF -polyvinylidene fluoride TBST -Tris-buffered saline-Tween buffer SD -standard deviation BP -Biological Pathways CC -Cytological Components MF -Molecular Function IC50 -the 50% maximal inhibitory concentration Declarations CONFLICT OF INTEREST STATEMENT The author disclaims any conflict and interest. ETHICS APPROVAL STATEMENT This study was approved by the Medical Ethics Committee of the Second Affiliated Hospital of Zhengzhou University (approval no.2023201). FUNDING INFORMATION This research was supported by 2022 Henan Province medical science and technology research plan joint construction project (LHGJ20220587, LHGJ20220489) and 2024 Henan Province key research and development and promotion special application (242102310247). Author Contribution LanLan Gan (First Author): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing-Original Drafts; Lu Zhou (Contributed equally): Data Curation, Validation, Writing-Origina Draft; ALan Chu: Resources, Supervision; Chen Sun: Visualization, Investigation, Writing-Review & Editing; YongTai Wang: Software, Validation; MengLin Yang : Software, Visualization; ZongWen Liu (Corresponding author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing-Review & Editing. 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Cite Share Download PDF Status: Published Journal Publication published 13 Nov, 2024 Read the published version in Molecular Biology Reports → Version 1 posted Editorial decision: Revision requested 07 Oct, 2024 Reviews received at journal 07 Oct, 2024 Reviewers agreed at journal 20 Sep, 2024 Reviewers invited by journal 05 Aug, 2024 Editor assigned by journal 05 Aug, 2024 Submission checks completed at journal 05 Aug, 2024 First submitted to journal 01 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4843022","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344587097,"identity":"1cbea86b-f043-49f3-9a79-e41ca40bd606","order_by":0,"name":"LanLan Gan","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"LanLan","middleName":"","lastName":"Gan","suffix":""},{"id":344587098,"identity":"b38ec3a6-c1bb-43c6-9e6c-c18e61f6cd5c","order_by":1,"name":"Lu Zhou","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Zhou","suffix":""},{"id":344587099,"identity":"41ddeb79-73ff-4c6d-89a0-76fc151d9ab5","order_by":2,"name":"ALan Chu","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"ALan","middleName":"","lastName":"Chu","suffix":""},{"id":344587100,"identity":"a30d6c97-c708-4dfb-972c-c8e5a8e1d451","order_by":3,"name":"Chen Sun","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Sun","suffix":""},{"id":344587101,"identity":"e82497a8-8277-447c-962a-2bced3d3d4c1","order_by":4,"name":"YongTai Wang","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"YongTai","middleName":"","lastName":"Wang","suffix":""},{"id":344587102,"identity":"e9a375a9-e113-4f48-9804-5cf4a965e948","order_by":5,"name":"MengLin Yang","email":"","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"MengLin","middleName":"","lastName":"Yang","suffix":""},{"id":344587103,"identity":"7cb00792-3eaa-4b8d-9ccd-99cc2ffffdf7","order_by":6,"name":"ZongWen Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArElEQVRIiWNgGAWjYBACPmYgwdhwQI6BmVgtbFAtxiRoYYBoSWwg2mFs7DzGn3l33Emf38578ANDjU00EQ7jMTDmPfMsd8NhvmQJhmNpuQStA2lJzm07nLsByJBgbDhMnJbDQC3p8s08xj+I1WLYDNSSwHCYx4xYW9iKmf+2HTbcANRikUCMX/j5D2/+OLPtsLx8/xnjGx9qbAhrQQUJpCkfBaNgFIyCUYALAAA8EzfUuwy3RAAAAABJRU5ErkJggg==","orcid":"","institution":"Second Affiliated Hospital of Zhengzhou University","correspondingAuthor":true,"prefix":"","firstName":"ZongWen","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-08-01 14:40:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4843022/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4843022/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11033-024-10070-1","type":"published","date":"2024-11-13T15:57:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63628147,"identity":"7add5d26-0a7f-426a-b0bb-9cd5bb4adc31","added_by":"auto","created_at":"2024-08-30 10:08:16","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":275430,"visible":true,"origin":"","legend":"\u003cp\u003eGPD1L expression is significantly downregulated in ESCC. (A) The expression of GPD1L was analyzed in ESCC using data from GSE20347, GSE23400, GSE53625, GSE67269 (GPL96), GSE67269 (GPL571), and GSE161533. (B) Immunohistochemical images show the differential expression of GPD1L in ESCC tissues compared to normal paracancerous tissues (scale bars, 50µm). (C) WB analysis to detect differences in GPD1L expression across multiple cell lines and quantitative analysis were conducted (n = 5). *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/de59bcafcf09f184db8ba67e.jpg"},{"id":63628150,"identity":"d6d84bff-65cd-48b7-a78b-f1e6ba88372c","added_by":"auto","created_at":"2024-08-30 10:08:16","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":326047,"visible":true,"origin":"","legend":"\u003cp\u003eIdentifying and enriching genes relevant to GPD1L. (A) Survival rate curves of ESCC patients based on GPD1L expression. (B) Circos plot illustrating the connections between GPD1L and 11 genes in ESCC. (C) Findings from GO analysis and KEGG enrichment analysis. (D) Results from GSEA in the low GPD1L expression group.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/dd6afae4edbf56f4f3403d08.jpg"},{"id":63628149,"identity":"a751f28d-3fa0-4f40-b218-d4f0be659566","added_by":"auto","created_at":"2024-08-30 10:08:16","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":812084,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of immune infiltration and drug sensitivity of GPD1L in ESCC. (A) Boxplot illustrating variations in GPD1L expression across 22 different types of immune cells. (B) Lollipop plot demonstrating the correlation between GPD1L expression and infiltration of immune cells. (C) Analysis showing the correlation between GPD1L and genes related to immune checkpoints. (D) Sensitivity analysis of GPD1L with various anticancer drugs including Taselisib, Afuresertib, Uprosertib, IGF1R, Gefitinib, Erlotinib, Afatinib, Rapamycin, 5-Fluorouracil, Paclitaxel, Oxaliplatin, and Cisplatin. *p \u0026lt; 0.05, **p \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/a92f8dfe4cd6ac3fc0326b1d.jpg"},{"id":63628144,"identity":"f16c4072-c5b6-4cd3-be9d-e828bbd033e4","added_by":"auto","created_at":"2024-08-30 10:08:15","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":253959,"visible":true,"origin":"","legend":"\u003cp\u003eUp-regulation of GPD1L expression has been shown to inhibit the of ESCC. (A) The transfection efficiency of the GPD1L overexpression plasmid in ECa109 was assessed. (B) Cell proliferation viability was determined using the CCK8 assay. (C) The migration ability of the cells was examined through the wound healing assay, with quantitative analysis provided (Scale bars, 100μm). (D) The migration and invasion capacity of the cells were assessed using the Transwell assay. (E) Apoptosis of ECa109 cells was analyzed by flow cytometry. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001 versus the mock group, with each group consisting of n=3 samples for statistical analysis purposes.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/750b99d4575e23b80dae6224.jpg"},{"id":63628151,"identity":"776b5ff3-7700-4f2d-9212-9bb11fcdce35","added_by":"auto","created_at":"2024-08-30 10:08:16","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":279825,"visible":true,"origin":"","legend":"\u003cp\u003eDown-regulation of GPD1L expression promotes ESCC development. (A) The transfection efficiency of GPD1L SiRNA in Kyse450 was assessed. (B) Cell proliferation viability was determined using the CCK8 assay. (C) The migration ability of the cells was examined through the wound healing assay, with quantitative analysis provided (Scale bars,100μm). (D) The migration and invasion capacity of the cells were assessed by the Transwell assay. (E) Apoptosis of Kyse450 cells was analyzed using flow cytometry. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001.versus the normal control group, with each group consisting of n=3 samples for statistical analysis purposes.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/6788f2bc3bfc4444644c5977.jpg"},{"id":63628152,"identity":"457167ca-489f-4654-abf9-1a179de45390","added_by":"auto","created_at":"2024-08-30 10:08:17","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":202824,"visible":true,"origin":"","legend":"\u003cp\u003eGPD1L may regulate the PI3K/AKT pathway in vitro to inhibit the development of ESCC. (A,B) The expression levels and quantification of P-PI3K and P-AKT proteins were measured in ECa109 cells transfected with GPD1L-MOCK and GPD1L-OE. (C,D) Similarly, the expression levels and quantification of P-PI3K and P-AKT proteins were assessed in Kyse450 cells transfected with GPD1L-NC and GPD1L-SI. *p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001 compared to the control group, with each group consisting of n=3 samples for statistical analysis purposes.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/c62c66841b31db6a2b1682dd.jpg"},{"id":69286128,"identity":"8e43f887-8bc0-402b-ba75-5a4103cadb79","added_by":"auto","created_at":"2024-11-18 19:30:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2777921,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4843022/v1/665edcf8-489f-4f78-81c2-a32f86cb6549.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"GPD1L may inhibit the development of esophageal squamous cell carcinoma through the PI3K/AKT signaling pathway： bioinformatics analysis and experimental exploration","fulltext":[{"header":"Key points","content":"\u003col\u003e\n \u003cli\u003eWe demonstrate the tumor suppressive role of GPD1L in ESCC.\u003c/li\u003e\n \u003cli\u003eWe reveal a novel mechanism by which GPD1L functions, potentially by modulating the PI3K/AKT signaling pathway.\u003c/li\u003e\n \u003cli\u003eBioinformatics analysis was conducted to investigate the potential correlation between GPD1L and ESCC, including related genes, immune cell and immunoinfiltration analysis, drug sensitivity, etc.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"1 INTRODUCTION","content":"\u003cp\u003eEsophageal cancer (EC) is one of the major health challenges in the world, and its major pathological subtypes include squamous cell carcinoma, adenocarcinoma, etc. In 2020, EC statistics from 185 countries revealed that there were 604,100 new cases of EC, ranking it eighth in the world in terms of incidence. Additionally, there were 544,100 deaths from EC, placing it sixth in the world for morbidity and mortality\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Approximately 14% were esophageal adenocarcinoma (EAC), while 85% of EC cases were esophageal squamous cell carcinoma (ESCC). Easy local invasion, quick disease progression, high recurrence rates, and a dismal prognosis for survival are the hallmarks of ESCC\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The 5-year overall survival rate for EC individuals is still low, remaining at 10% \u0026minus;\u0026thinsp;30%\u003csup\u003e3 4\u003c/sup\u003e, despite the availability of numerous treatments such as surgery, radiation, chemotherapy, immunotherapy, endoscopic resection, ablation, cryotherapy, and argon ion coagulation\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Therefore, we urgently need to further study the pathogenesis of EC and explore new treatment methods and strategies.\u003c/p\u003e \u003cp\u003eThe protein Glycerol-3-phosphate dehydrogenase 1-like (GPD1L) has the ability to convert glycerol triphosphate into phosphoglycerol\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. The sequence similarity between it and glycerol-3-phosphate dehydrogenase 1 (GPD1) is 84%\u003csup\u003e9\u003c/sup\u003e. Previous studies have clarified its effect on cardiac Na-ion channels, which reduces the inward sodium current. Defects in this gene can lead to Brugada syndrome type 2 (BRS2) and sudden infant death syndrome (SIDS)\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Additionally, recent research has demonstrated that GPD1L has a function in different tumors, such as lung adenocarcinoma, renal cell carcinoma, colorectal cancer, oropharyngeal carcinoma, squamous carcinoma of the head and neck, etc.\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Therefore, it is assumed that GPD1L may be directly or indirectly involved in energy metabolism, regeneration of blood vessels, cell proliferation and survival. However, GPD1L\u0026rsquo;s association with ESCC development and the mechanism of its action is still not clear.\u003c/p\u003e \u003cp\u003eIn human cancers, the PI3K/AKT is frequently activated. Under physiological conditions, this pathway is triggered by cytokines, insulin, growth factors, etc. to regulate critical metabolic processes, including nutrient transporters, glucose metabolism, macromolecule biosynthesis, and redox homeostasis to promote both whole-body metabolic homeostasis and individual cell development and metabolism\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The PI3K/AKT pathway was aberrantly activated in tumor cells. The impact of its aberrant activation in tumorigenesis and development as well as its mechanism of action are continuously being discovered to inform new therapeutic strategies.\u003c/p\u003e \u003cp\u003eIn this study, we investigated the association between GPD1L and ESCC patients using bioinformatics analysis of data from TCGA and GEO databases. Our biofunctional experiments demonstrated that GPD1L inhibits the biological behavior of cells, such as cell migration, invasion, and proliferation while promotes apoptosis in vitro. Additionally, WB results suggest that GPD1L may inhibit the development of ESCC via the PI3K/AKT signaling pathway. Based on our findings, it is suggested that GPD1L holds promise as a potential target for treating ESCC.\u003c/p\u003e"},{"header":"2 MATERIALS and METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Data pre-processing and patient inclusion\u003c/h2\u003e \u003cp\u003eSix datasets, namely GSE20347, GSE23400, GSE53625, GSE67269 (GPL96), GSE67269 (GPL571), and GSE161533, were selected for analysis. Among these, the dataset GSE67269 contains 34 pairs of datasets based on the GPL96 platform and 73 pairs of datasets based on the GPL571 platform. The mRNA expression raw data of all datasets were preprocessed as follows: firstly, the gene expression data from each dataset were aggregated by calculating the average values; secondly, we used the \"limma\" package to normalize them. Additionally, the data from GSE161533 was log-transformed. The analysis was conducted using R software (v4.2.1).\u003c/p\u003e \u003cp\u003eFurthermore, between 2022 and 2023, paraffin sections of malignant and normal paracancerous tissues were gathered from the Second Affiliated Hospital of Zhengzhou University's Department of Pathology. The study's inclusion criteria consisted of patients meeting the following requirements: possessing residual specimens from the specified department, receiving a diagnosis of ESCC and falling within the age range of 18 to 75 years, having undergone biopsy procedures prior to antitumor treatment, and providing informed consent. Exclusion criteria encompassed the coexistence of additional malignancies, psychological disorders, and contraindications to anti-tumor therapy. Approval for the experiment was obtained from the Ethics Committee of the Second Affiliated Hospital of Zhengzhou University.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Bioinformatics and the analysis\u003c/h2\u003e \u003cp\u003eAfter data preprocessing, utilizing the \"limma\" package, we initially analyze GPD1L expression in ESCC and normal adjacent tissues across six datasets. We employed paired t-tests to determine if there were significant differences and subsequently investigated the expression of GPD1L in ESCC. Among the six datasets, the GSE53625 dataset contained transcriptomic and clinical data from 179 patients, making it suitable for further bioinformatics analysis.\u003c/p\u003e \u003cp\u003eSecondly, based on the median GPD1L expression, ESCC patients were categorized into two groups with high expression (n\u0026thinsp;=\u0026thinsp;90) and low expression (n\u0026thinsp;=\u0026thinsp;89). Then we conduct Kaplan-Meier survival analysis by using the \"survival\" and \"surminer\" packages. Overall survival curves were constructed to assess whether GPD1L was associated with OS between these two groups.\u003c/p\u003e \u003cp\u003eThirdly, we probed for genes that may be associated with GPD1L in ESCC using a threshold of |cor| \u0026gt; 0.4 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Genes showing high correlation with GPD1L were visualized using Circos plots. Subsequently, we performed enrichment analysis on the identified GPD1L-related genes to elucidate their functional mechanisms and enriched pathways via the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). In addition, we utilized Gene Set Enrichment Analysis (GSEA) to explore the pathways and functional mechanisms associated with differential gene enrichment in the low expression group of GPD1L. This process employ some R packages, such as \"ComplexHeatmap\", \"dplyr\", \"RColorBrewer\", \"circle\", \"clusterProfiler\", \"enrichplot\", \"org.hss.e.g.db\", \"corrlot\", \"ggExtra\", \"ggpuber\", and \"ggplot 2\"\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFinally, we analyzed the fraction of immune cells in the tumor samples from GSE53625. Then, in the two GPD1L expression groups, we compared the levels of immune cell infiltration, and also examined the correlation of GPD1L with immune cells and with immune checkpoint-related genes. Additionally, we obtained data from GDSC (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.Cancerrxgene.org/\u003c/span\u003e\u003cspan address=\"https://www.Cancerrxgene.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to assess the sensitivity of GPD1L to anticancer drugs. During this process, we utilized various packages including \"reshape2\", \"ggpubr\", \"violot\", \"ggplot2\", \"corrplot\", \"ggExtra\", \"parallel\", and \"oncoPredict\"\u003csup\u003e17 18\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Cell lines and cell culture\u003c/h2\u003e \u003cp\u003e The human ESCC cell line Kyse150 was obtained from Shanghai Zhongqiao Xinzhou Biotechnology Co. Ltd, and the normal human esophageal epithelial cell line HEEC was obtained from Nanjing Wanmuchun Biotechnology Co. The other cell lines, such as Het-1A, Kyse450, and ECa109 were provided by the Medical Research Centre of the Second Affiliated Hospital of Zhengzhou University. Three ESCC cell lines were cultured in medium containing 89% RPMI 1640, 1% penicillin-streptomycin solution (Zhongqiao Xinzhou Biotechnology Co., Ltd., China), 10% fetal bovine serum (Procell Biotechnology Co., Ltd., China). The two normal esophageal epithelial cell lines were grown in medium containing 89% DMEM (Procell Biotechnology Co., Ltd., China) with the same supplements as mentioned above. All cells were maintained at 37℃ with a CO\u003csub\u003e2\u003c/sub\u003e concentration of 5% under saturated humidity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Cell transfection\u003c/h2\u003e \u003cp\u003eThe GPD1L empty vector plasmid (GPD1L-MOCK) and overexpression plasmid (GPD1L-OE) were purchased from Tsingke Company, while the GPD1L negative control (GPD1L-NC) and small interfering RNA (GPD1L-SI) were ordered from Henan Biolabs Bio-tech Co. Ltd. A six-well plate were inoculated in an appropriate amount of cells and reached 70% density after 16\u0026ndash;24 hours. Subsequently, we used Lipofectamine 8000 reagent (Beyotime, China), and the plasmid and siRNA were introduced respectively into ECa109 and Kyse450 cells via transfection. The siRNA sequences can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequences of each assay\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eassay\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esequence\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSi-RNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi-NC:5\u0026prime;-UUCUCCGAACGUCACGUTT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi1-GPD1L:5\u0026prime;-GCAGCAAAGUAAUGGAGAATT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi2-GPD1L:5\u0026prime;-CGAAAGCAGACCAGUUCAATT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSi3-GPD1L:5\u0026prime;-GCUGUGGAGACAACACCAATT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRT-qPCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAPDH-F:5\u0026prime;-ACAACAGCCTCAAGATCATCAGC-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAPDH-R:5\u0026prime;-GCCATCACGCCACAGTTTCC-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGPD1L-F:5\u0026prime;-ACGGTGGTTGATGATGCAGACACT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGPD1L-R:5\u0026prime;-CGGATGACGGCCGCTTTGGT-3\u0026prime;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Immunohistochemical staining\u003c/h2\u003e \u003cp\u003eFirstly, 3\u0026micro;m thick sections were obtained from paraffin-embedded human ESCC and their corresponding normal paracancerous tissues. The sections were then baked for 2 hours, deparaffinized, and antigenically repaired with citrate for 2.5 minutes. Subsequently, the sections were blocked by incubating with an appropriate amount of peroxide block for 5 minutes, followed by incubation with GPD1L antibody (CAT. NO. PA5-24216, 1:100, Thermofisher) for 30 minutes at 25℃. Post-primary and polymer were then added to the sections. Fresh DAB was stained for approximately 2 minutes, followed by washing and staining with hematoxylin. The sections were reblued using Roche, dehydrated in gradient ethanol and blocked before being observed under a light microscope at a magnification of 100x. Photographs were taken according to the intensity of staining and the proportion of positive cells. Immunohistochemical staining results were scored semi-quantitatively as follows: Degree of staining - negative staining is marked as 0 points; light yellow is 1 point; brownish yellow is 2 points; reddish brown 3 points. Positive range - \u0026lt;5% scored as 0 points; between 5% ~24% scored as 1 point; between25% ~50% scored as 2 points; between 51%~74% scored as 3 points; and \u0026ge;\u0026thinsp;75% scored as 4 points. The final score result was determined by multiplying the degree of staining score by the positive range score: negative scored as 0 points; low expression scored as \u0026lt;\u0026thinsp;5 points, and high expression scored as \u0026ge;\u0026thinsp;5 points. Scoring was independently performed by two pathologists.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Cell proliferation\u003c/h2\u003e \u003cp\u003eThe experimental and control groups of ECa109 and Kyse450 cells were seeded into 96-well plates at a density of 3000 cells. After 6 hours, add 10 \u0026micro;l CCK8 reagent per well and incubate away from light for 1.5 hours. This time point was considered as 0h, and then we use a microplate reader (Thermo Fisher Scientific, USA) to measure the optical density (OD) values at 450 nm at 0h, 24h, 48h, and 72h, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Cell migration and invasion\u003c/h2\u003e \u003cp\u003eThe wound healing assay was utilized to assess the migratory capacity of cells. In brief, ECa109 and Kyse450 cells were individually inoculated in 6-well plates, and transfection treatment was conducted once the cell density reached 70%-80%. The cells were then observed for 24\u0026ndash;48 hours. Upon reaching a cell density of 100%, scratches were made with a 10 \u0026micro;l plastic pipette tip. Subsequently, the cells were cultured in medium containing 1% serum, and images of the scratched areas were captured at 0h, 24h, 48h, and 72h time points. The results were analyzed using the following formula: cell migration area rate = (0h scratch area \u0026minus;\u0026thinsp;24h scratch area)/0h scratch area x100%.\u003c/p\u003e \u003cp\u003eFor the transwell experiments, we utilized transwell culture dishes (Corning, USA) and Matrigel (BD, USA) to evaluate the migratory and invasive potential. In brief, cells were suspended in serum-free medium. Then, 500 \u0026micro;l of medium containing 20% serum was added to the lower chamber and 200 \u0026micro;l of cell suspension was added to the upper chamber. After 36 hours, the non-migrating cells above the chamber were removed, and each well was treated with 1ml 4% paraformaldehyde for 1h at room temperature, followed by staining with crystal violet for 15 minutes. Finally, the cells were photographed under a microscope. The invasion assay required the spreading of 200ul of matrix gel dilution before implanting the appealing cells in the upper chamber. Same as above for the rest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Flow cytometry\u003c/h2\u003e \u003cp\u003eApproximately 1x10\u003csup\u003e5\u003c/sup\u003e cells were inoculated into 24-well plates in the presence of 10% fetal bovine serum. After 48 hours of transfection treatment, as per the instructions provided by the Apoptosis Kit (Yakoin, China), each well was added 1ml of freshly prepared apoptosis-inducing solution (apoptosis inducer : complete medium\u0026thinsp;=\u0026thinsp;1 : 2000), and then they were incubated for 24h. Subsequently, the cells were harvested and stained with Annexin V-FITC and propidium iodide (PI) from the apoptosis kit. The stained cells were analyzed using a flow cytometry system (BeamCyte Flow Cytometer; Bidake Biotechnology Co., Ltd., China), with 10,000\u0026ndash;30,000 cells recorded each time to determine the rate of apoptosis. CytoSYS v1.0 software (Bidake Biotechnology Co., Ltd., China) was utilized for data analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Real-Time qPCR\u003c/h2\u003e \u003cp\u003eCells were lysed in six-well plates by adding 1 ml of TRIzol. Total RNA was then extracted using chloroform and isopropanol following the reagent vendor's instructions, and subsequently tested for purity and concentration using a spectrophotometer (Thermo Scientific, USA). Subsequently, we use a reverse transcription kit and a temperature gradient PCR instrument to transcribe 1 \u0026micro;g of RNA into complementary cDNA. Finally, the internal reference gene sequence and the target gene sequence were added, followed by RT-qPCR using an amplification kit and a real-time fluorescence quantitative PCR instrument (Thermo Fisher Scientific, USA). The primer sequences can be found in Supplement 1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Western blot\u003c/h2\u003e \u003cp\u003eBriefly, ECa109 and Kyse450 cells were inoculated in a 6-well plate. When the cell fusion reached 80%-100%, a newly configured mixture of RIPA protein lysate (Servicebio, China) and PMSF (Servicebio, China) at a ratio of 100:1 was added to the cells to lyse them. The proteins were extracted by centrifugation at 4℃ and high speed, and we utilized the BCA kit (Servicebio, China) to determine the protein concentration. Then, an appropriate loading buffer was added, boiled at 100\u0026deg;C for 10 min. The denatured proteins were separated on 10% PAGE gels at constant voltages of 80 V and 120 V respectively before being transferred to methanol-activated polyvinylidene fluoride membranes (PVDF) in transmembrane solution\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The excess protein was stored at-80℃. After blocking with a commercial rapid-sealing solution (Servicebio, China), primary antibodies were incubated for 14\u0026ndash;18 hours at 4\u0026deg;C on PVDF membranes with a pore size of 0.22 nm. Following three washes in Tris-buffered saline-Tween buffer (TBST), the membranes were incubated with goat anti-rabbit IgG/HRP secondary antibody and visualized using the ECL Protein Detection System (Yakoin, China). Primary antibodies used included Anti-GPD1L (CAT. NO. PA5-24216, 1:1,000, Thermofisher, ), anti-PI3K/AKT signaling pathway panel (CAT. NO. ab283852, 1:1,000, Abcam), anti-β-actin (CAT. NO. GB15003, 1:2,000, Servicebio), and anti-α-tubulin(CAT. NO. 11224-1-AP, 1:2,000, Proteintech). The phosphorylation sites of phosphorylated AKT(P-AKT)were S472, S473, and S474. The HRP-conjugated Affinipure goat anti-rabbit IgG(H\u0026thinsp;+\u0026thinsp;L)(CAT. NO. SA00001-2, 1:2,000, Proteintech) serves as the secondary antibody.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Statistical analysis\u003c/h2\u003e \u003cp\u003eEach experiment was conducted three times, and statistical analysis was performed using SPSS 26.0 software (IBM, USA). Continuous measurement data are presented as \"mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD)\". The significance of the difference between the two groups was determined using appropriate tests such as Student's t-test, Chi-square test, Fisher's exact test, or exact probability test.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 RESULTS","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1 GPD1L expression is downregulated in ESCC\u003c/h2\u003e \u003cp\u003eSix datasets, totaling 384 pairs of ESCC and normal adjacent tissue samples, were screened from the GEO database. When compared to the normal tissue, the tumor exhibited significantly low expression of GPD1L, indicating a statistically significant difference (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.A). This suggests that the expression of GPD1L is down-regulated in ESCC. To further validate the results of the bioinformatics analysis, we conducted immunohistochemistry on 36 pairs of ESCC and normal paracancerous tissues. There are 28 cases of low GPD1L expression in ESCC and 4 cases in normal paracancerous tissues. The results revealed a statistically significant decrease in protein expression of GPD1L in ESCC tissues(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.B and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExpression of GPD1L in ESCC and normal paracancerous tissues\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCancer\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGPD1L\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditionally, we analyzed the protein level expression of GPD1L in normal esophageal epithelial cells (HEEC, Het-1A) and various ESCC cell lines (ECa109, Kyse150, Kyse450, TE-1) using WB. The findings indicated reduced protein expression levels of GPD1L in both ESCC tissues and cell lines when compared to normal paracancerous tissues and normal esophageal epithelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.C). Furthermore, by detecting differences in the protein level of GPD1L expression in several ESCC cell lines, ECa109 was identified as a GPD1L low-expressing ESCC cell line (Kyse150 was intolerant to various transfection reagents and the transfection efficiency of TE-1 was unsatisfactory) while Kyse450 was identified as a high-expressing one. These selections were based on observed differences at the protein level for the completion of further experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Identifying and enriching genes relevant to GPD1L\u003c/h2\u003e \u003cp\u003eSurvival analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.A) revealed a significantly lower survival rate in the GPD1L low expression group. The Circos plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.B) demonstrated that six genes showed a significant positive association with GPD1L, while five genes showed a substantial negative relationship with it. According to GO enrichment analysis, GPD1L-related genes were predominantly enriched in the Organic acid biosynthetic process lipid modification, Carboxylic acid biosynthetic process (BP), Actin filament bundle, Peroxisome, microbody (CC), Heme binding, Tetrapyrrole binding and Iron ion binding (MF). In the KEGG project, they were enriched in Cytokine\u0026thinsp;\u0026minus;\u0026thinsp;cytokine receptor interaction, Toxoplasmosis, Hematopoietic cell lineage, and Cell adhesion molecules (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.C). GSEA showed enrichment of Arachidonic acid metabolism, Cell adhesion molecules cams, Drug metabolism cytochrome p450, and Intestinal immune network for IgA production in the KEGG project for the low expression group of GPD1L. Additionally, Embryonic skeletal system development, Embryonic skeletal system morphogenesis, and Positive regulation of myotube differentiation were significantly enriched in BP. Furthermore, External side of plasma membrane, Mitochondrial envelope, Mitochondrial matrix, Mitochondrial protein-containing complex, Organelle inner membrane, Receptor complex, and Side of membrane were significantly enriched in CC. Lastly, MHC protein complex binding, Arachidonic acid monooxygenase activity, Immune receptor activity, Aromatase activity, Incorporation of one atom of oxygen, Oxidoreductase activity acting on paired donors with incorporation or reduction of molecular oxygen reduced flavin or flavoprotein as one donor and Oxidoreductase activity acting on CH-OH group of donors were significantly enriched in MF (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.D).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Immune infiltration and drug sensitivity analysis of GPD1L in ESCC\u003c/h2\u003e \u003cp\u003eFirst, an immune correlation analysis was conducted to explore the association between GPD1L and immunity in ESCC. The results from the Boxplot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.A) revealed that in the low expression group of GPD1L, there was a lower infiltration level of Plasma cells and T cells regulatory (Tregs), while the infiltration level of Macrophages M0 and Mast cells activated was higher. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.B, Macrophages M2, Mast cells resting, T cells CD8, T cells follicular helper and the degree of infiltration of Tregs have a positive correlation with GPD1L expression, while Macrophages M0, Monocytes, T cells CD4 memory resting, and Mast cells activated exhibited a negative correlation with GPD1L. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.C demonstrated that GPD1L was positively correlated with immune checkpoint genes such as CD48, TIGIT, BTLA, CD27, CD200R1, CD28, IDO1, CD40LG, IDO2, CD244, PDCD1, TNFSF18, TMIGD2, and negatively correlated with CD276 and CD44. In addition to this analysis on immune correlation, the GPD1L high and low expression groups were also compared to ascertain whether there were any differences in the 50% maximal inhibitory concentration (IC50) between the commonly used chemotherapeutic agents and the molecularly targeted agents for ESCC. The results indicated that in the GPD1L low-expression group, the IC50 values of PI3K/AKT pathway inhibitors (Taselisib, Afuresertib, Uprosertib) were significantly higher. Additionally, the IC50 values of several EGFR tyrosine kinase inhibitors (Gefitinib, Afatinib, Erlotinib) and mTOR inhibitors (Rapamycin) were also significantly elevated. However, the IC50 value of IGFIR was significantly lower. There were no significant correlations were observed between the drugs 5-Fluorouracil, Paclitaxel, Oxaliplatin, and Cisplatin and GPD1L expression levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.D).\u003c/p\u003e \u003cp\u003eTo sum up, our bioinformatics analysis' results point to a potential involvement for GPD1L in ESCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Up-regulation of GPD1L expression inhibits the development of ESCC\u003c/h2\u003e \u003cp\u003eTo further explore the potential biological roles of GPD1L, we performed in vitro cellular experiments. ECa109 cells with low expression of GPD1L were chosen for transfection with a GPD1L overexpression plasmid. RT-qPCR and WB analysis confirmed the up-regulation of GPD1L expression in ECa109 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.A), and functional experiments were subsequently performed.\u003c/p\u003e \u003cp\u003eCCK8 assay showed that ECa109 cell proliferation was markedly inhibited by up-regulation of GPD1L (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.B). As demonstrated by wound healing assay, overexpression of GPD1L significantly reduced ECa109 cells' capacity to migrate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.C). Transwell assay demonstrated that GPD1L overexpression dramatically reduced ECa109 cells' capacity for invasion and migration (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.D). Moreover, GPD1L overexpression was shown to significantly accelerate apoptosis in flow cytometry assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Down-regulation of GPD1L expression promotes ESCC development\u003c/h2\u003e \u003cp\u003eKyse450 cells with high GPD1L expression were chosen for GPD1L small interfering RNA transfection treatment. RT-qPCR analysis revealed that siRNA1 had the most effective knockdown effect, thus it was selected for subsequent experiments. WB confirmed the reduction of GPD1L expression in Kyse450 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.A). Functional experiments revealed that the silencing GPD1L expression in Kyse450 significantly promoted cell proliferation, migration, and invasive capacity, while also markedly reducing apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.B\u0026thinsp;~\u0026thinsp;E).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.6 GPD1L may regulate the PI3K/AKT pathway in vitro to inhibit the development of ESCC\u003c/h2\u003e \u003cp\u003eTo investigate the mechanism underlying the inhibitory effect of GPD1L on ESCC, we conducted a bioinformatics analysis and literature summary to identify a potential association between GPD1L and the PI3K/AKT pathway. Subsequently, WB analysis was utilized to validate this relationship. Our findings revealed that overexpression of GPD1L in ECa109 cells significantly suppressed the phosphorylation of PI3K/AKT (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.A, B). Conversely, the knockdown of GPD1L in Kyse450 cells markedly enhanced the activation of PI3K/AKT (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.C, D). These results indicate that GPD1L may exert its inhibitory effect on ESCC by suppressing the activation of the PI3K/AKT pathway.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 DISCUSSION","content":"\u003cp\u003eEC is one of the most important global health concerns, and in China, the Taihang Mountains region and the southern coastal areas are the high-prevalence areas of this cancer. ESCC, the primary pathological type of EC examined in this study, exhibits typical characteristics of malignant tumors\u003csup\u003e1 3 4\u003c/sup\u003e. There is an urgent need for comprehensive research into the development mechanism of EC and the creation of more targeted therapies suitable for patients. GPD1L, the focus of this paper, was first found to be closely associated with the heart diseases, such as SIDS and BRS\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, and its pathogenesis is mainly related to cardiac sodium channels\u003csup\u003e\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e–\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. It was not until 2011 that researchers discovered the gene's relationship with HIF-1α. Several studies in recent years have found that GPD1L exhibits low mRNA and protein expression levels in some malignant tumor cells or tissues\u003csup\u003e\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The mechanism of its cancer inhibitory effect shows a negative feedback loop regulation, in brief, GPD1L can inhibit the expression of HIF-1α, thus playing an inhibitory role in the development of tumor; and under hypoxic conditions, the expression of HIF-1α is elevated, which promotes the downstream targets (e.g. miR-210, etc.), which in turn inhibit GPD1L\u003csup\u003e21 22\u003c/sup\u003e. Recent studies have found that GPD1L is closely associated with mitochondrial autophagy in renal cell carcinoma\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, further confirming its role in inhibiting cancer development; however, its association with ESCC development and its underlying mechanisms are not clear.\u003c/p\u003e \u003cp\u003eIn this study, single-gene differential analysis, immunohistochemistry, and multi-cell line WB experiments verified that GPD1L was lowly expressed in ESCC; in addition, the co-expression analysis yielded that GPD1L was positively correlated with a number of genes such as EPB41L4A, RBM47, P4HTM, EYA2, ACADSB, FOXA1, etc. These genes have been proven to inhibit the development of various cancers by many studies\u003csup\u003e\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e–\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Especially FOXA1 has been found to have a role in EC\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e; a negative correlation with FBLIM1, SNAI2, SAMD14, RFLNB, CSPG4, and many papers have demonstrated its cancer-promoting effect in various tumors\u003csup\u003e\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e–\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. To further explore the effect of GPD1L on ESCC, we conducted in vitro functional assays and confirmed that higher levels of GPD1L in two cell lines, ECa109 and Kyse450, inhibited biological behaviors of ESCC, such as growth speed, invasiveness, metastatic potential and promoted apoptosis. These experiments all verified the above conjectures.\u003c/p\u003e \u003cp\u003eIn order to further explore the GPD1L’s mechanism in ESCC, enrichment analysis was continued. We found that GPD1L and its related genes are mainly closely related to the metabolism and synthesis of a variety of substances. For example, GO analysis yielded that GPD1L is mainly enriched in peroxisomes, iron ion binding, etc. Peroxisomes play a crucial role in the regulation of immune response and inflammation by affecting lipid metabolism and reactive oxygen species generation and may be a therapeutic target for inflammation-related diseases such as ESCC\u003csup\u003e31 32\u003c/sup\u003e. Intracellular accumulation of iron ions disrupts cell membrane integrity and subsequently produces the well-known “iron death”. Iron death is intricately linked to the progression of tumors, especially the selective killing of tumor cells with abnormal iron metabolism\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. The mechanism of iron death can be used as a therapeutic target for EC through the induction of EC cell death, and enhancement of the sensitivity of radiotherapy\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Whether GPD1L can inhibit ESCC through the above analyzed mechanism of action needs to be verified in further experiments. In KEGG analysis, GPD1L and its related genes were mainly enriched in cytokine-cytokine receptor interactions, and cell adhesion molecules. The former is a key link in cell signaling, and is essential for immune response, cell proliferation, differentiation, apoptosis and so on. The latter mainly includes integrins, calcineurin, selectins, etc. A large amount of research literature shows that these adhesion molecules significantly affect cancer cell proliferation, infiltration, and metastasis\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. In ESCC, their expression changes are closely associated with signal transduction pathways such as AKT, Wnt/β-linker protein, and Rho GTPases. GSEA showed that the GPD1L low expression group was enriched in the KEGG project for arachidonic acid metabolism, cell adhesion molecules, drug metabolism cytochrome p450, and intestinal immune network for IgA production. These are closely related to the development of various types of cancer, especially arachidonic acid and cell adhesion molecules have a role in promoting the development of ESCC\u003csup\u003e\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e–\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Cytochrome P450 affects most drug metabolism, which also implies that GPD1L expression may affect the sensitivity of ESCC patients to anticancer drugs\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Previous studies have found that GPD1L is closely related to mitochondria and their metabolic activities\u003csup\u003e13 39\u003c/sup\u003e, and GSEA analysis revealed that in ESCC cell fraction(CC), GPD1L was enriched in several mitochondrial components, such as envelope, matrix, and protein-containing complexes, suggesting that there may be a similar role for GPD1L in ESCC. In the molecular function(MF) analysis, it is not difficult to see that GPD1L plays an important role in biological functions such as redox reaction, immune response, and inflammatory response in the development of ESCC.\u003c/p\u003e \u003cp\u003eWe continued the immune infiltration analysis of GPD1L. From the differential analysis of immune infiltration, GPD1L not only was positively correlated with T-cell regulation and activation, as well as macrophage M2, but also negatively correlated with macrophage M0 and activated mast cells. \"T cells\" are an important component of the immune system and their role in tumor development has been widely discussed and applied\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. For example, immune checkpoint inhibitors (PD1/PDL1) play a cancer-suppressive role by removing the inhibition of T cell activation by tumor cells\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, and the emerging CAR-T therapy reprograms the patient's own T cells to attack cancer cells\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The role of macrophage M0, a new classification intermediate between M1 and M2, in cancer has yet to be investigated. M2 is usually considered a pro-cancer in the progression of malignant tumors, such as ESCC\u003csup\u003e40 43\u003c/sup\u003e. While activated mast cells have both pro-cancer and cancer-suppressive effects, influenced by the mediators they release and the tumor microenvironment\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. These results suggest that GPD1L may affect the immune microenvironment of ESCC through these immune cells. Immune checkpoint analysis yielded that GPD1L was positively correlated with several CD28 superfamily (CD28, BTLA)\u003csup\u003e45 46\u003c/sup\u003e, tumor necrosis factor superfamily (TNFSF18, CD27, CD40LG)\u003csup\u003e\u003cspan additionalcitationids=\"CR48\" citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e–\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, TIGIT\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and other inhibitory immune checkpoints; and negatively correlated with CD276 and CD44, which have pro-cancer effects.\u003c/p\u003e \u003cp\u003eIn terms of drug sensitivity, although GPD1L does not affect the sensitivity of ESCC patients to drugs such as 5-fluorouracil, low expression increases sensitivity to PI3K/AKT pathway inhibitors(Taselisib, Afuresertib, Uprosertib), EGFR tyrosine kinase inhibitors(Gefitinib, Afatinib, Erlotinib) and mTOR inhibitors (Rapamycin), as well as decreasing sensitivity to IGF1R\u003csup\u003e\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e–\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. The PI3K/AKT signaling pathway is commonly activated in human cancers. Through a cascade phosphorylation reaction, PI3K and AKT successively produce phosphorylated PI3K (P-PI3K) and phosphorylated AKT (P-AKT) with activation ability. P-AKT can regulate various intracellular downstream factors such as mTOR, HIF-1α, NF-κB, Bad, caspase, etc., which are involved in cellular autophagy regulation, aerobic glycolysis regulation inhibition of apoptosis influence on protein synthesis promotion of tumor cell proliferation, infiltration, metastasis, and migration among other cellular biological functions\u003csup\u003e\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e–\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Considering the 84% homology between GPD1 and GPD1L\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, it has been found that GPD1 can affect the lipid metabolism of cancers through the PI3K/AKT pathway in breast cancer\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. In summary, this paper continued to explore whether GPD1L affects the biological function of ESCC through the PI3K/AKT signaling pathway. We performed several cell phenotyping experiments and WB experiments for validation and concluded that overexpression of GPD1L affects the activation of the PI3K/AKT signaling pathway, which may consequently inhibit the biological function of ESCC, and conversely, downregulation of GPD1L promotes them by activating PI3K/AKT signaling pathway. Therefore, GDP1L may act as an inhibitor for the development of ESCC.\u003c/p\u003e \u003cp\u003eHowever, this study still has some limitations, and more in-depth functional studies are required to elucidate the underlying mechanisms. Furthermore, there is a need to further explore the role that GPD1L plays in ESCC metabolism and its potential impact on ESCC metabolic reprogramming, which is a fundamental feature of malignant tumors. Additionally, the assessment of the therapeutic significance of GPD1L is crucial. Based on previous studies, it is also necessary to investigate whether the high expression of this gene can disrupt the hypoxic microenvironment on which tumor cell growth depends. Moreover, the impact of GPD1L on tumor cells through aerobic glycolysis under aerobic conditions requires further elucidation. The long-term goal of this research is to address these issues and integrate theory with practical applications for clinical use.\u003c/p\u003e "},{"header":"CONCLUSION","content":"\u003cp\u003eTo sum up, we concluded that overexpression of GPD1L affects the activation of the PI3K/AKT signaling pathway, which may consequently inhibit the biological function of ESCC, and conversely, downregulation of GPD1L promotes them by activating PI3K/AKT signaling pathway. Therefore, GDP1L may act as an inhibitor for the development of ESCC.\u003c/p\u003e"},{"header":"LIST OF ABBREVIATIONS","content":"\u003cp\u003eEC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Esophageal cancer\u003c/p\u003e\n\u003cp\u003eESCC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Esophageal squamous carcinoma\u003c/p\u003e\n\u003cp\u003eEAC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Esophageal adenocarcinoma\u003c/p\u003e\n\u003cp\u003eGPD1L \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Glycerol-3-phosphate dehydrogenase 1-like\u003c/p\u003e\n\u003cp\u003eGPD1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Glycerol-3-phosphate dehydrogenase 1\u003c/p\u003e\n\u003cp\u003ePI3K/AKT \u0026nbsp; \u0026nbsp; -Phosphatidylinositol 3-kinase/serine-threonine kinase\u003c/p\u003e\n\u003cp\u003eBRS2 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Brugada syndrome type 2\u003c/p\u003e\n\u003cp\u003eSIDS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Sudden infant death syndrome\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWB \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Western Blot\u003c/p\u003e\n\u003cp\u003eCCK8 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Cell Counting Kit-8\u003c/p\u003e\n\u003cp\u003eGO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Gene Ontology\u003c/p\u003e\n\u003cp\u003eKEGG \u0026nbsp; \u0026nbsp; \u0026nbsp; -Kyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n\u003cp\u003eGSEA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Gene Set Enrichment Analysis\u003c/p\u003e\n\u003cp\u003eMOCK \u0026nbsp; \u0026nbsp; \u0026nbsp; -empty vector plasmid\u003c/p\u003e\n\u003cp\u003eOE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-overexpression plasmid\u003c/p\u003e\n\u003cp\u003eNC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-negative control\u003c/p\u003e\n\u003cp\u003eSI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -small interfering RNA\u003c/p\u003e\n\u003cp\u003eOD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-optical density\u003c/p\u003e\n\u003cp\u003ePVDF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-polyvinylidene fluoride\u003c/p\u003e\n\u003cp\u003eTBST \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Tris-buffered saline-Tween buffer\u003c/p\u003e\n\u003cp\u003eSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-standard deviation\u003c/p\u003e\n\u003cp\u003eBP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -Biological Pathways\u003c/p\u003e\n\u003cp\u003eCC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Cytological Components\u003c/p\u003e\n\u003cp\u003eMF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;-Molecular Function\u003c/p\u003e\n\u003cp\u003eIC50 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; -the 50% maximal inhibitory concentration\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCONFLICT OF INTEREST STATEMENT\u003c/h2\u003e \u003cp\u003eThe author disclaims any conflict and interest.\u003c/p\u003e\u003cp\u003eETHICS APPROVAL STATEMENT\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Medical Ethics Committee of the Second Affiliated Hospital of Zhengzhou University (approval no.2023201).\u0026nbsp;\u003c/p\u003e\u003ch2\u003eFUNDING INFORMATION\u003c/h2\u003e \u003cp\u003eThis research was supported by 2022 Henan Province medical science and technology research plan joint construction project (LHGJ20220587, LHGJ20220489) and 2024 Henan Province key research and development and promotion special application (242102310247).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLanLan Gan (First Author): Conceptualization, Methodology, Software, Investigation, Formal Analysis, Writing-Original Drafts; Lu Zhou (Contributed equally): Data Curation, Validation, Writing-Origina Draft; ALan Chu: Resources, Supervision; Chen Sun: Visualization, Investigation, Writing-Review \u0026amp; Editing; YongTai Wang: Software, Validation; MengLin Yang : Software, Visualization; ZongWen Liu (Corresponding author): Conceptualization, Funding Acquisition, Resources, Supervision, Writing-Review \u0026amp; Editing.\u003c/p\u003e\u003ch2\u003eACKNOWLEDGMENTS\u003c/h2\u003e \u003cp\u003e Thanks to the Center for Medical Experiment, The Second Affiliated Hospital of Zhengzhou University provided the experimental site and equipment.\u003c/p\u003e\u003ch2\u003eDATA AVAILABILITY\u003c/h2\u003e \u003cp\u003eWe guarantee that this article has not been published elsewhere and that the raw data is accessible.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMorgan E, Soerjomataram I, Rumgay H et al (1943) New York, N.Y. 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Heliyon 9:e18128\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"GPD1L, ESCC, PI3K/AKT, bioinformatics, biological behavior","lastPublishedDoi":"10.21203/rs.3.rs-4843022/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4843022/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEsophageal squamous carcinoma (ESCC) is the most prevalent pathological subtype of esophageal cancer (EC). It has the characteristics of significant local invasion, quick disease progression, high recurrence rates, and a dismal prognosis for survival. Phosphatidylinositol 3-kinase/serine-threonine kinase (PI3K/AKT) is a signaling system whose aberrant activation regulates downstream factors, leading to the promotion of cancer development. This study looks at a protein called Glycerol-3-phosphate dehydrogenase 1-like (GPD1L), which strongly affects the development of several cancers. However, its association with ESCC development and its underlying mechanisms are not clear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this paper, we analyzed six ESCC transcriptome data obtained from the GEO database. We utilized bioinformatics technology and immunohistochemistry to differentially analyze GPD1L levels of mRNA and protein expression in ESCC and normal adjacent tissues. Furthermore, we conducted survival, co-expression, enrichment, immune infiltration and drug sensitivity analysis. Finally, we further investigated the role and mechanism of GPD1L by Western Blot (WB), Cell Counting Kit-8 (CCK8), wound healing assay, Transwell assay, and flow cytometry.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe findings manifest that the expression of GPD1L was low in ESCC, and functional experiments showed that GPD1L promoted apoptosis in vitro while blocking cell migration, invasion, and proliferation. Based on mechanism research, GPD1L's impact on ESCC could be explained by its suppression of the PI3K/AKT signaling pathway's activation.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTo sum up, our findings imply that GPD1L may impede the initiation and advancement of ESCC via modulating the PI3K/AKT signaling pathway. GPD1L is considered to be a promising therapeutic target and biomarker to diagnose and treat ESCC.\u003c/p\u003e","manuscriptTitle":"GPD1L may inhibit the development of esophageal squamous cell carcinoma through the PI3K/AKT signaling pathway： bioinformatics analysis and experimental exploration","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-30 10:08:07","doi":"10.21203/rs.3.rs-4843022/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-07T10:57:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-07T05:56:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"194157323655406116695514732631613995891","date":"2024-09-21T02:38:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-05T09:32:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-05T07:10:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-05T07:09:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2024-08-01T14:39:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"75e668f4-ef23-4f3e-bcb5-97737acdb71b","owner":[],"postedDate":"August 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-18T19:25:54+00:00","versionOfRecord":{"articleIdentity":"rs-4843022","link":"https://doi.org/10.1007/s11033-024-10070-1","journal":{"identity":"molecular-biology-reports","isVorOnly":false,"title":"Molecular Biology Reports"},"publishedOn":"2024-11-13 15:57:51","publishedOnDateReadable":"November 13th, 2024"},"versionCreatedAt":"2024-08-30 10:08:07","video":"","vorDoi":"10.1007/s11033-024-10070-1","vorDoiUrl":"https://doi.org/10.1007/s11033-024-10070-1","workflowStages":[]},"version":"v1","identity":"rs-4843022","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4843022","identity":"rs-4843022","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}