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

doi:10.21203/rs.3.rs-4843022/v1

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Research Article

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

https://doi.org/10.21203/rs.3.rs-4843022/v1

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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

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.

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 mortality¹. 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 ESCC². 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 phosphoglycerol⁸. 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 metabolism¹⁶. 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.

2.1 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 CO₂ 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 1x10⁵ 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 solution¹⁹. 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.

3.1 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.

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 BRS²⁰, 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 carcinoma¹³, 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 EC²⁶; 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 metabolism³³. 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 radiotherapy³⁴. 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 metastasis³⁵. 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 drugs³⁸. 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 applied⁴⁰. For example, immune checkpoint inhibitors (PD1/PDL1) play a cancer-suppressive role by removing the inhibition of T cell activation by tumor cells⁴¹, and the emerging CAR-T therapy reprograms the patient's own T cells to attack cancer cells⁴². 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 microenvironment⁴⁴. 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, TIGIT⁵⁰ 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 GPD1L⁹, it has been found that GPD1 can affect the lipid metabolism of cancers through the PI3K/AKT pathway in breast cancer⁵⁷. 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.

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.

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

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.

ACKNOWLEDGMENTS

Thanks to the Center for Medical Experiment, The Second Affiliated Hospital of Zhengzhou University provided the experimental site and equipment.

DATA AVAILABILITY

We guarantee that this article has not been published elsewhere and that the raw data is accessible.

Morgan E, Soerjomataram I, Rumgay H et al (1943) New York, N.Y. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology 2022;163: 649–658.e2
Cao L, Ouyang H (2024) Intercellular crosstalk between cancer cells and cancer-associated fibroblasts via exosomes in gastrointestinal tumors. Front Oncol 14:1374742
Reichenbach ZW, Murray MG, Saxena R et al (2019) Clinical and translational advances in esophageal squamous cell carcinoma. Adv Cancer Res 144:95–135
Ahmed O, Ajani JA, Lee JH (2019) Endoscopic management of esophageal cancer. World J Gastrointest Oncol 11:830–841
Huang FL (2018) Yu. Esophageal cancer: Risk factors, genetic association, and treatment. Asian J Surg 41:210–215
Li J, Xu J, Zheng Y et al (2021) Esophageal cancer: Epidemiology, risk factors and screening. Chin J Cancer Res 33:535–547
Yang YM, Hong P, Xu WW, He QY (2020) Li. Advances in targeted therapy for esophageal cancer. Signal Transduct Target Ther 5:229
Zhao Z, Cui X, Guan G et al (2022) Bioinformatics analysis reveals the clinical significance of GIPC2/GPD1L for colorectal cancer using TCGA database. Transl Cancer Res 11:761–771
Ou X, Ji C, Han X et al (2006) Crystal structures of human glycerol 3-phosphate dehydrogenase 1 (GPD1). J Mol Biol 357:858–869
London B, Michalec M, Mehdi H et al (2007) Mutation in glycerol-3-phosphate dehydrogenase 1 like gene (GPD1-L) decreases cardiac Na + current and causes inherited arrhythmias. Circulation 116:2260–2268
Fan J, Ji CC, Cheng YJ et al (2020) A novel mutation in GPD1–L associated with early repolarization syndrome via modulation of cardiomyocyte fast sodium currents. Int J Mol Med 45:947–955
Semino F, Darche FF, Bruehl C et al (2024) GPD1L-A306del modifies sodium current in a family carrying the dysfunctional SCN5A-G1661R mutation associated with Brugada syndrome. Pflugers Arch 476:229–242
Liu T, Zhu H, Ge M et al (2023) GPD1L inhibits renal cell carcinoma progression by regulating PINK1/Parkin-mediated mitophagy. J Cell Mol Med 27:2328–2339
Fan Z, Wu S, Sang H, Li Q, Cheng S, Zhu H (2023) Identification of GPD1L as a Potential Prognosis Biomarker and Associated with Immune Infiltrates in Lung Adenocarcinoma. Mediators Inflamm 2023:9162249
Leung P, Das B, Cheng X, Tarazi M (2023) Prognostic and Predictive Utility of GPD1L in Human Hepatocellular Carcinoma. Int J Mol Sci, ;24
Hoxhaj G, Manning BD (2020) The PI3K-AKT network at the interface of oncogenic signalling and cancer metabolism. Nat Rev Cancer 20:74–88
Zhou L, Gan L, Liu Z (2023) Expression and prognostic value of AIM1L in esophageal squamous cell carcinoma. Med (Baltim) 102:e34677
Zhou L, Gan L, Sun C, Chu A, Yang M, Liu Z (2024) Bioinformatics analysis and experimental verification of NLRX1 as a prognostic factor for esophageal squamous cell carcinoma. Oncol Lett 27:264
Liu D, Wu H, Cui S, Zhao Q (2023) Comprehensive Optimization of Western Blotting. Gels, ;9
Brugada R, Campuzano O, Sarquella-Brugada G, Brugada P, Brugada J, Hong K (1993) Brugada Syndrome
Kelly TJ, Souza AL, Clish CB, Puigserver P (2011) A hypoxia-induced positive feedback loop promotes hypoxia-inducible factor 1alpha stability through miR-210 suppression of glycerol-3-phosphate dehydrogenase 1-like. Mol Cell Biol 31:2696–2706
Du Y, Wei N, Ma R, Jiang S, Song D (2020) A miR-210-3p regulon that controls the Warburg effect by modulating HIF-1α and p53 activity in triple-negative breast cancer. Cell Death Dis 11:731
Hughes CJ, Alderman C, Wolin AR, Fields KM, Zhao R (2024) Ford. All eyes on Eya: A unique transcriptional co-activator and phosphatase in cancer. Biochim Biophys Acta Rev Cancer 1879:189098
Li C, Ding L, Wang X et al (2023) A RBM47 and IGF2BP1 mediated circular FNDC3B-FNDC3B mRNA imbalance is involved in the malignant processes of osteosarcoma. Cancer Cell Int 23:334
Zhang W, Lai R, He X et al (2020) Clinical prognostic implications of EPB41L4A expression in multiple myeloma. J Cancer 11:619–629
Xu Y, Wang W, Li L et al (2018) FOXA1 and CK7 expression in esophageal squamous cell carcinoma and its prognostic significance. Neoplasma 65:469–476
Bai N, Peng E, Qiu X et al (2018) circFBLIM1 act as a ceRNA to promote hepatocellular cancer progression by sponging miR-346. J Exp Clin Cancer Res 37:172
Harrer DC, Dörrie J, Schaft N (2019) CSPG4 as Target for CAR-T-Cell Therapy of Various Tumor Entities-Merits and Challenges. Int J Mol Sci, ;20
Li SH, Qian L, Chen YH et al (2022) Targeting MYO1B impairs tumorigenesis via inhibiting the SNAI2/cyclin D1 signaling in esophageal squamous cell carcinoma. J Cell Physiol 237:3671–3686
Thurner L, Preuss KD, Bewarder M et al (2018) Hyper-N-glycosylated SAMD14 and neurabin-I as driver autoantigens of primary central nervous system lymphoma. Blood 132:2744–2753
Di Cara F, Savary S, Kovacs WJ, Kim P, Rachubinski RA (2023) The peroxisome: an up-and-coming organelle in immunometabolism. Trends Cell Biol 33:70–86
Wu X, Wang Z, Jiang Y et al (2021) Tegaserod Maleate Inhibits Esophageal Squamous Cell Carcinoma Proliferation by Suppressing the Peroxisome Pathway. Front Oncol 11:683241
Dixon SJ, Lemberg KM, Lamprecht MR et al (2012) Ferroptosis: an iron-dependent form of nonapoptotic cell death. Cell 149:1060–1072
Zhao M, Lu T, Bi G et al (2023) PLK1 regulating chemoradiotherapy sensitivity of esophageal squamous cell carcinoma through pentose phosphate pathway/ferroptosis. Biomed Pharmacother 168:115711
Fan C, Xiong F, Zhang S et al (2024) Role of adhesion molecules in cancer and targeted therapy. Sci China Life Sci
Wang B, Wu L, Chen J et al (2021) Metabolism pathways of arachidonic acids: mechanisms and potential therapeutic targets. Signal Transduct Target Ther 6:94
Zhi H, Zhang J, Hu G et al (2003) The deregulation of arachidonic acid metabolism-related genes in human esophageal squamous cell carcinoma. Int J Cancer 106:327–333
Schmelzle M, Dizdar L, Matthaei H et al (2011) Esophageal cancer proliferation is mediated by cytochrome P450 2C9 (CYP2C9). Prostaglandins Other Lipid Mediat 94:25–33
Liu M, Liu H, Dudley SJ (2010) Reactive oxygen species originating from mitochondria regulate the cardiac sodium channel. Circ Res 107:967–974
Zhang J, Dong Y, Di S, Xie S, Fan B, Gong T (2023) Tumor associated macrophages in esophageal squamous carcinoma: Promising therapeutic implications. Biomed Pharmacother 167:115610
Lei Q, Wang D, Sun K, Wang L, Zhang Y (2020) Resistance Mechanisms of Anti-PD1/PDL1 Therapy in Solid Tumors. Front Cell Dev Biol 8:672
June CH, O'Connor RS, Kawalekar OU, Ghassemi S (2018) Milone. CAR T cell immunotherapy for human cancer. Science 359:1361–1365
Yao J, Duan L, Huang X et al (2021) Development and Validation of a Prognostic Gene Signature Correlated With M2 Macrophage Infiltration in Esophageal Squamous Cell Carcinoma. Front Oncol 11:769727
Ribatti D (2024) New insights into the role of mast cells as a therapeutic target in cancer through the blockade of immune checkpoint inhibitors. Front Med (Lausanne) 11:1373230
Khan M, Arooj S, Wang H (2021) Soluble B7-CD28 Family Inhibitory Immune Checkpoint Proteins and Anti-Cancer Immunotherapy. Front Immunol 12:651634
Burke KP, Chaudhri A, Freeman GJ, Sharpe AH (2024) The B7:CD28 family and friends: Unraveling coinhibitory interactions. Immunity 57:223–244
Gui L, Wang Z, Lou W et al (2024) Comparative evaluation of antitumor effects of TNF superfamily costimulatory ligands delivered by mesenchymal stem cells. Int Immunopharmacol 126:111249
Zhou Y, Richmond A, Yan C (2024) Harnessing the potential of CD40 agonism in cancer therapy. Cytokine Growth Factor Rev 75:40–56
Fromm G, de Silva S, Schreiber TH (2023) Reconciling intrinsic properties of activating TNF receptors by native ligands versus synthetic agonists. Front Immunol 14:1236332
Chiang EY, Mellman I (2022) TIGIT-CD226-PVR axis: advancing immune checkpoint blockade for cancer immunotherapy. J Immunother Cancer, ;10
Blagden SP, Hamilton AL, Mileshkin L et al (2019) Phase IB Dose Escalation and Expansion Study of AKT Inhibitor Afuresertib with Carboplatin and Paclitaxel in Recurrent Platinum-resistant Ovarian Cancer. Clin Cancer Res 25:1472–1478
Vanacker H, Cassier PA, Bachelot T (2021) The complex balance of PI3K inhibition. Ann Oncol 32:127–128
Xiong X, Yuan L, Yang K, Wang X (2023) The HIFIA/LINC02913/IGF1R axis promotes the cell function of adipose-derived mesenchymal stem cells under hypoxia via activating the PI3K/AKT pathway. J Transl Med 21:732
Glaviano A, Foo A, Lam HY et al (2023) PI3K/AKT/mTOR signaling transduction pathway and targeted therapies in cancer. Mol Cancer 22:138
Porta C, Paglino C, Mosca A (2014) Targeting PI3K/Akt/mTOR Signaling in Cancer. Front Oncol 4:64
Fresno VJ, Casado E, de Castro J, Cejas P, Belda-Iniesta C (2004) González-Barón. PI3K/Akt signalling pathway and cancer. Cancer Treat Rev 30:193–204
Xia Z, Zhao N, Liu M et al (2023) GPD1 inhibits the carcinogenesis of breast cancer through increasing PI3K/AKT-mediated lipid metabolism signaling pathway. Heliyon 9:e18128

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

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Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

Key points

1 INTRODUCTION

2 MATERIALS and METHODS

2.1 Data pre-processing and patient inclusion

2.2 Bioinformatics and the analysis

2.3 Cell lines and cell culture

2.4 Cell transfection

2.5 Immunohistochemical staining

2.6 Cell proliferation

2.7 Cell migration and invasion

2.8 Flow cytometry

2.9 Real-Time qPCR

2.10 Western blot

2.11 Statistical analysis

3 RESULTS

3.1 GPD1L expression is downregulated in ESCC

3.2 Identifying and enriching genes relevant to GPD1L

3.3 Immune infiltration and drug sensitivity analysis of GPD1L in ESCC

3.4 Up-regulation of GPD1L expression inhibits the development of ESCC

3.5 Down-regulation of GPD1L expression promotes ESCC development

3.6 GPD1L may regulate the PI3K/AKT pathway in vitro to inhibit the development of ESCC

4 DISCUSSION

CONCLUSION

LIST OF ABBREVIATIONS

Declarations

CONFLICT OF INTEREST STATEMENT

FUNDING INFORMATION

Author Contribution

ACKNOWLEDGMENTS

DATA AVAILABILITY

References

Additional Declarations

Status:

Version 1