Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinoma

Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinoma | 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 Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinoma Dayou Shi, Lingzhi Zeng, Yayun Zha, Anwen Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3838907/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract LPCAT1 acts as an oncogene in a variety of cancers, but its effect on lung squamous cell carcinoma (LUSC) has not been reported. This study aimed to determine the prognostic value of LPCAT1 by bioinformatics analyses and to confirm its effect on LUSC cell functions by in vitro experiments. The expression data and clinical information were obtained from the public database. The prognostic value of LPCAT1 was evaluated by Kaplan-Meier curves, nomogram analysis, and Cox regression analyses. The relationships of LPCAT1 and immune features were also estimated. Then, expressions of LPCAT1 and PTEN/Akt pathway in LUSC cell lines (NCI-H226 and NCI-H520) were detected by real-time quantitative polymerase chain reaction and western blot. Cell viability, invasion, and apoptosis were evaluated by CCK-8 assay, Transwell assay, and flow cytometry, respectively. The bioinformatics analyses suggested that LPCAT1 is an independent prognostic risk factor of LUSC and has predictive potential. Meanwhile, LPCAT1 was significantly associated with immune cell infiltration and immune checkpoint gene expressions. Experiment data suggested that LPCAT1 can promote proliferation and invasion but inhibit apoptosis in LUSC cell lines. LPCAT1 can also significantly decrease the PTEN expression but increase the p-Akt expression in vitro . LPCAT1 indicates prognosis and correlates with immune features in LUSC. Experiment data indicated that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway. LPCAT1 lung squamous cell carcinoma prognosis PTEN/Akt pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights 1. LPCAT1 is a prognostic risk factor of LUSC. 2. LPCAT1 is correlated with immune cell infiltration and immune checkpoint in LUSC. 3. LPCAT1 is highly expressed in LUSC cell lines. 4. LPCAT1 affects LUSC cell functions via the PTEN/Akt pathway. Introduction As a major subtype of non-small cell lung cancer, lung squamous cell cancer (LUSC) is one of the leading causes of cancer-related death worldwide, with a non-negligible aggressiveness (Kujtan, Kancha et al. 2022 , Niu, Jin et al. 2022 ). Squamous cell carcinoma of the lung mainly originates from the carcinosis of squamous cell epithelium transformed from glandular epithelium in lung tissues (Maroni, Bassal et al. 2021 ). Compared with lung adenocarcinoma, LUSC usually metastasizes later and are diagnosed at an advanced stage (Chen and Dhahbi 2021 , Li, Kuang et al. 2022 ). Moreover, patients with LUSC suffer from an adverse prognosis, with a 5-year survival rate of less than 15% (Wang, Tang et al. 2021 ). Despite efforts to study the molecular basis of LUSC, the treatment landscape has barely changed in decades, and effective targeted therapies are still lacking. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), also known as AYTL2, is a lipid metabolism-related gene on chromosome 5 with a length of 69555bp (Tao, Luo et al. 2021 ). LPCAT1 is associated with cancer progression, metastasis, and recurrence and has been reported to overexpress as an oncogene in multiple cancers (Shida-Sakazume, Endo-Sakamoto et al. 2015 , Uehara, Kikuchi et al. 2016 , Du, Wang et al. 2017 ). LPCAT1 also correlate with immune cell infiltration and may serve as an independent prognostic marker in endometrial cancer (Zhao, Zhang et al. 2021 ). Wei et al. proposed that LPCAT1 may indicate a poorer clinical prognosis in lung adenocarcinoma and influence tumor progression through the PI3K/Akt signaling pathway (Wei, Dong et al. 2019 ). These findings suggest that LPCAT1 has the potential to be a novel target for cancer therapy. However, the potential role of LPCAT1 in LUSC remains poorly understood. Therefore, using the bioinformatics approach, this study explored the predictive role of LPCAT1 on LUSC prognosis and analyzed its correlations with tumor immune microenvironment characteristics. Based on these results, this study further carried out in vitro experiments to investigate the effects of LPCAT1 on cellular functions and PTEN/Akt pathway through the construction of overexpression and knockdown vectors. These findings may provide a new research idea for further understanding the potential regulatory mechanism of LPCAT1 in LUSC and optimizing treatment strategies to improve clinical outcomes of patients. Materials and methods Cancer Genome Atlas (TCGA)-based data collection and process The expression matrix and clinical information of LUSC samples were downloaded from the TCGA Genomic Data Commons (GDC) database. The clinical survival data including overall survival (OS) and disease-free survival (DFS) were analyzed using GEPIA2 database ( http://gepia2.cancer-pku.cn/#index ). The median expression value of LPCAT1 was used as the threshold to differentiate the groups with high expression and low expression. Using the "time-ROC" package, the receiver operating characteristic (ROC) curves were plotted and the areas under the curve (AUCs) were calculated to estimate the potential of LPCAT1 in predicting prognosis of patients with LUSC. Evaluating the prognostic independence of LPCAT1 Based on the expression of LPCAT1 and clinical traits, a nomogram model was constructed using R language survival package to assess their influences on patient survival. Furthermore, the univariate and multivariate Cox regression analyses were performed by survival kit to appraise whether LPCAT1 and clinical features (including age, gender, and tumor stage) were independent prognostic factors. Enrichment analysis of differentially expressed genes (DEGs) between high- and low-expression groups The limma package of R language was used to analyze the gene expression patterns between the LPCAT1 high- and low-expression groups, with the difference being determined by wilcox.test. The DEGs were selected at |log fold change (FC)| > 1 and false discovery rate (FDR) < 0.05. Then, the Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed by using the R.clusterProfiler package. Based on the download file of "c2. Cp. Kegg. Hs. Symbols. GMT" file, the gene set enrichment analysis (GSEA) function was used for enrichment analysis of GSEA pathway. Comparisons of immune features between LPCAT1 high- and low-expression groups The R language “estimate” package was used to calculate immune scores on the downloaded expression data of LUSC, followed by the comparison between the two groups using the “limma” package. The CIBERSORT was used to analyze the immune cell infiltration level of each sample, and the R language “stat_compare_means” function was used to compare the difference between high- and low-expression groups. The correlations between LPCAT1 expression and immune cell infiltration level were analyzed by the Spearman method, whereas the relationships between expressions of LPCAT1 and immune checkpoint genes were estimated by the Pearson method. All statistical significances were set at p < 0.05. Cell culture LUSC cell line NCI-H226 (BNCC287420) was provided by BNBIO (Beijing, China). LUSC cell line NCI-H520 (CL-0402) and human bronchial epithelial cell line BEAS-2B (CL-0496) were provided by Procell Life Science Technology (Hubei, China). NCI-H226 cells and NCI-H520 cells were cultured in RPMI-1640 media (Gibco, USA) containing 10% fetal bovine serum (FBS) (Gibco, USA) and 1% Pen-Strep (Gibco, USA) at 37°C and 5% CO 2 . BEAS-2B cells were cultured in DMEM media (Gibco, USA) containing 10% FBS and 1% Pen-Strep at 37°C and 5% CO 2 . Construction of expression intervention model of LPCAT1 LPCAT1-pcDNA3.1 plasmid, PTEN-pcDNA3.1 plasmid and pcDNA3.1 plasmid were provided by General Biol (Anhui, China). Among them, LPCAT1-pcDNA3.1 plasmid and PTEN-pcDNA3.1 plasmid were used to construct the overexpression (OE) model of LPCAT1 and PTEN, respectively. Meanwhile, the pcDNA3.1 plasmid was transfected into cells of negative control (NC) groups. To achieve the expression interference of LPCAT1, three LPCAT1 siRNA and the siRNA NC were prepared by General Biol (Anhui, China). The detailed sequences of siRNA are show in Supplementary Table 1. Cell transfection The mixture of plasmid/siRNA and Lipofectamine 3000 (Thermo Fisher, USA) was prepared for gene transfection according to the manufacturer’s instruction. When the confluence reached 70%, the cells were incubated with the mixture for 4 h. Completed medium containing 20% fetal bovine serum was added and the cells were cultured for another 48 h before subsequent examination. Real-time quantitative polymerase chain reaction (RT-qPCR) Cells were collected and resuspended in Trizon reagent (CW0580, CWBIO, China) to extract total RNA which was reversely transcribed to cDNA using HiFiScript cDNA synthesis kit (CW2141, CWBIO, China) according to the manufacturer’s instructions. Then, qPCR was performed using a RT-qPCR system (CFX Connect, Bio-Rad, USA). Detailed sequences of primers are shown in Supplementary Table 2. The relative mRNA level of LPCAT1 was calculated by 2 −ΔΔCt algorithm normalized to GAPDH. Western blot After cell lysis and centrifugation, total protein was extracted and protein concentration was subsequently determined using a BCA kit (CW0014S, CWBIO, China). Then, the protein was denatured, and loaded to conduct sodium dodecyl sulfate polyacrylamide gel electrophoresis for 2 h and transferred to polyvinylidene fluoride membranes at 300 mA. The membranes were incubated with primary antibody at 4°C overnight and then with secondary antibody at room temperature for 2 h. The antibodies used in this study are as follows: mouse anti-GAPDH monoclonal antibody (1:2000, TA-08, ZSGB-BIO, China), horseradish peroxidase (HRP)-labeled goat anti-mouse IgG(H + L) (1:2000, ZB-2305, ZSGB-BIO, China), HRP-labeled goat anti-rabbit IgG(H + L) (1:2000, ZB-2301, ZSGB-BIO, China), rabbit anti-LPCAT1 polyclonal antibody (1:4000, 16112-1-AP, Proteintech, USA), rabbit anti-Akt polyclonal antibody (1:500, ab8805, Abcam, USA), rabbit anti-p-Akt polyclonal antibody (1:500, af0016, Affinity, USA), rabbit anti-PTEN monoclonal antibody (1:1000, ab170941, Abcam, USA). After adding chemiluminescent substrate, the membranes were examined on a gel imaging system (ChemiDoc XRS+, Bio-Rad, USA), and the blots were analyzed by Quantity one software (v4.62, Bio-Rad, USA) with GAPDH being served as an internal control. Cell viability The transfected cells were seeded in 96-well plate at a density of 6×10 3 cells per well. After culturing for 48 h, the medium was replaced by 100 µL fresh one and 10 µL CCK8 reagent was added to each well. After 2h of incubation, the absorbance of each well at 450 nm was detected by a microplate reader to estimate the cell viability. Cell apoptosis The transfected cells were collected, treated with Annexin V-FITC/PI apoptosis kit (AP101-100-kit, MultiSciencesBiotech, China) according to the manufacturer’s instruction, and analyzed on a flow cytometer (NovoCyte, ACEA Biosciences, China). Cell invasion The transfected cells were resuspended in a FBS-free medium and cell suspension containing 5×10 4 cells were added into the upper chamber. The culture medium containing 10% FBS (500 µl) was added into the lower chamber. The cells were cultured for 48 h, washed with PBS for 5 min and stained in 0.1% crystal violet (G1061, Solarbio, China) for 60 min. The cells in the lower chamber were observed under a microscope (CKX41, Olympus, Japan). After removing the crystal violet solution, the cells in each well was mixed with 1 mL 33% acetic acid. The mixture (200µL) was taken from each well to a 96-well plate and the absorbance was measured on a microplate reader at 570 nm. Statistical analysis All data were presented as mean ± standard deviation and statistically analyzed with SPSS 19.0 software (SPSS Inc., IL, USA). Differences were analyzed by one-way analysis of variance with post-hoc test and defined to be significant at p < 0.05. Results LPCAT1 indicates prognosis in LUSC The prognostic value of LPCAT1 in LUSC was analyzed using GEPIA2 database. The Kaplan-Meier curves based on OS and DFS showed that the survival probability of patients with high expression of LPCAT1 was significantly lower than those with low expression of LPCAT1 (Fig. 1 A). The ROC curves were plotted and the AUCs of 1-, 3-, and 5-year survival were 0.553, 0.578, and 0.598, respectively, indicating that the sensitivity and specificity of LPCAT1 in predicting prognosis were ordinary (Fig. 1 B). Further nomogram analysis was performed on LPCAT1 and clinical characteristics, and the results revealed that LPCAT1 was a significant correlation factor affecting the survival time of patients' prognosis (Fig. 1 C). Calibration curves confirmed that the nomogram-predicted OS were close to the actual ones (Fig. 1 D), indicating that the prognostic predictive efficacy of nomogram was good. Furthermore, the univariate and multivariate Cox regression analyses were performed to observe the impact of LPCAT1 expression, age, gender, and tumor stage on the prognosis of LUSC. The results showed that LPCAT1 was a significant high-risk factor in both univariate and multivariate Cox analyses (Figs. 1 E-F). The above results proved that LPCAT1 might be significantly associated with the prognosis survival of patients with LUSC. Functional enrichment analysis based on the expression of LPCAT1 To further understand the potential regulatory mechanism of LPCAT1 in LUSC, the expression of LPCAT1 was grouped, and the samples were divided into high-expression group and low-expression groups. Then, the express profiles were compared between the two groups and 980 DEGs were obtained (Fig. 2 A). GO and KEGG enrichment analyses were performed on these DEGs (Figs. 2 B-C), which were mainly enriched in “cell-cell adhesion via plasma-membrane adhesion molecules”, “collagen trimer”, “metal ion transmembrane transporter activity”, “complement and coagulation cascades” and other functional items and signal pathways. GSEA pathways were also enriched and it was found that “OLFACTORY TRANSDUCTION” pathway was significantly enriched in the high-expression group, while “DNA REPLICATION” channels were significantly enriched in the low-expression group (Fig. 2 D). Therefore, the regulation of LPCAT1 on LUSC might be realized through these functional entries and signaling pathways. Relationships of LPCAT1 expression and immune features in LUSC Tumor microenvironment (TME) is considered to play an important role in the progression of LUSC. Therefore, the TME scores of LUSC samples were calculated and then compared between high-expression group and low-expression groups. The violin plot indicated the significantly higher StromalScore, ImmuneScore and ESTIMATEScore in the group with high LPCAT1 expression than that with low LPCAT1 expression (Fig. 3 A). Furthermore, the infiltration abundances of immune cells were calculated and compared between the two groups. As results, plasma cells, M1 macrophages, neutrophils, CD8 T cells, resting/activated memory CD4 T cells, γδT cells, and resting dentritic cells suggested significant differences in infiltration levels between high and low LPCAT1 expression groups (Fig. 3 B). Meanwhile, the correlation analysis suggested that LPCAT1 had significant positive correlations with neutrophils and resting memory CD4 T cells, but had significant negative relationships with M1 macrophages and plasma cells (Fig. 3 C). We also found that LPCAT1 was positively correlated with almost all immune checkpoint genes at the expression levels (Fig. 3 D). Exploring the expression pattern of LPCAT1 and constructing the expression intervention models To further validate the expression patterns of LPCAT1, as well as biological functions in LUSC, in vitro experiments were conducted accordingly. Results of RT-qPCR and western blot suggested that compared with BEAS-2B cells, the mRNA and protein levels of LPCAT1 increased significantly in both NCI-H226 and NCI-H520 cells (Figs. 4 A-B). Then, pcDNA3.1 plasmid and siRNA of LPCAT1 were transfected into NCI-H226 and NCI-H520 cells to construct the overexpression and interference models, respectively. As shown in Figs. 4 C and 4 E, after transfecting LPCAT1-pcDNA3.1 plasmid, the LPCAT1 levels were significantly elevated in both cells as compared with control and LPCAT1 NC group. Meanwhile, compared with Control group, Si-LPCAT1-1, Si-LPCAT1-2 and Si-LPCAT1-3 can significantly down-regulate the LPCAT1 expression in two cell lines (Figs. 4 D and 4 F). Among them, Si-LPCAT1-2 had the strongest inhibitory effect on the LPCAT1 expression in two cell lines and therefore was selected for subsequent experiments. LPCAT1 affects the proliferation, invasion and apoptosis in LUSC cell lines To observe the effects of LPCAT1 on cell proliferation, the CCK8 assay was performed and the results suggested that compared with NC groups, siRNA transfection significantly reduced the cell viability and LPCAT1-pcDNA3.1 transfection significantly raised the cell viability in both NCI-H226 and NCI-H520 cells (Fig. 5 A). The transwell assay indicated the similar invasive numbers of NCI-H226 and NCI-H520 cells between control and NC groups. Furthermore, the invasive numbers were significantly decreased in siRNA groups but significantly increased in the OE group, compared with their respective NC groups in NCI-H226 cells (Fig. 5 B). Finally, the flow cytometry was applied to detect apoptosis rates in these two cell lines. The results indicated that both NCI-H226 and NCI-H520 cells significantly elevated apoptosis after transfection with siRNA but significantly inhibited apoptosis after transfection with LPCAT1-pcDNA3.1 plasmid (Fig. 5 C). These results revealed that LPCAT1 may promote proliferation and invasion but inhibit apoptosis in LUSC cell lines. LPCAT1 mediates the PTEN/Akt pathway Furthermore, the protein expressions of genes in the PTEN/Akt pathway were also detected using western blot. The results of NCI-H226 and NCI-H520 cells both showed that p-AKT was up-regulated in cells transfected with siRNA but was down-regulated in cells transfected with LPCAT1-pcDNA3.1 plasmid (Fig. 6 A). However, the expression pattern of PTEN is completely opposite to that of p-AKT. Notably, there was no significant difference in the expression level of AKT among all groups. To further study the effect of LPCAT1 on the PTEN/Akt pathway, the PTEN-pcDNA3.1 plasmid was transfected into cells to construct an overexpression model of PTEN. RT-qPCR and western blot verified that after transfecting the PTEN-pcDNA3.1 plasmid, the expression levels were sharply elevated in both NCI-H226 and NCI-H520 cells compared with Control and PTEN NC groups (Figs. 6 B-C). After co-transfected with LPCAT1-pcDNA3.1 and PTEN-pcDNA3.1, the expression level of p-Akt/Akt was detected by the western blot. In NCI-H226 cells, compared with the Control and LPCAT1 NC groups, the expression of p-Akt/Akt in the LPCAT1 and LPCAT1 + PTEN group was up-regulated significantly, and its expression was down-regulated significantly in the LPCAT1 NC + PTEN group (Fig. 6 D). In NCI-H520 cells, the expression of p-Akt/Akt in the LPCAT1 group was significantly higher than that in the Control and LPCAT1 NC groups, and its expression in the LPCAT1 NC + PTEN group was significantly lower than that in the LPCAT1 NC group (Fig. 6 D). Discussion LPCAT1 is a cytoplasmic enzyme that can catalyze the conversion of Lysophosphatidylcholine to phosphatidylcholine (Du, Wang et al. 2017 ). Bioinformatics analysis revealed that survival status of LUSC patients with high expression of LPCAT1 was significantly worse than those with low expression of LPCAT1. The nomogram model and Cox regression analyses also confirmed the prognostic value of LPCAT1 and its predictive potential in LUSC. In addition, the expression of LPCAT1 was found to be related to immune score, immune cell infiltration level, and immune checkpoint expression. To support these findings, the in vitro experiments were conducted and the results illustrated the cancer-promoting role of LPCAT1 via the PTEN/Akt pathway. LPCAT1 has been found to be overexpressed in colorectal cancer (Mansilla, da Costa et al. 2009 ), liver cancer (Morita, Sakaguchi et al. 2013 ), and prostate cancer (Zhou, Lawrence et al. 2012 ) and may be a prognostic risk factor for hepatocellular carcinoma and breast cancer (Lebok, von Hassel et al. 2019 , Li, Wang et al. 2022 , Sun, Liu et al. 2022 ). Consistent with these findings, the present study demonstrates for the first time that LPCAT1 promotes tumor growth and invasion in LUSC and may affect patient survival and prognosis. The results based on the immune score suggested that patients with high LPCAT1 expression had higher StromalScore, ImmuneScore and ESTIMATEScore, indicating that these patients were in an immunologically activated state. Correlation analysis with immune cell infiltration levels further suggested that LPCAT1 was most significantly positively correlated with neutrophils but most significantly negatively correlated with M1 macrophages. Currently, neutrophils have received increasing attention for their pro-cancer effects, and an elevated neutrophil-to-lymphocyte ratio is considered a prognostic indicator for cancer (Xiong, Dong et al. 2021 ). It was reported that the level of neutrophils infiltration was significantly increased in the group with high prognostic risk of LUSC (Ma, Wang et al. 2023 ). In LUSC, neutrophil infiltration levels were also significantly positively correlated with other prognostic risk factors such as GLUT1 and DLD (Zhang, Dong et al. 2022 , Yang, Guo et al. 2023 ). These findings support our conclusions and indicated that the elevated expression of LPCAT1 may promote tumor infiltration of neutrophils, thereby inducing the recurrence and metastasis of LUSC. Furthermore, it is known that pro-inflammatory M1 macrophages phagocytose tumor cells, whereas anti-inflammatory M2 macrophages promote tumor growth and invasion (Xia, Rao et al. 2020 ). Among the macrophage subpopulations, M1 macrophages are thought to have an anti-tumor phenotype (Gao, Liang et al. 2022 ). This study found that the expression of LPCAT1 was significantly negatively correlated with the level of M1 macrophage infiltration, suggesting that LPCAT1 inhibited the phagocytosis of tumor cells by M1 macrophages, thus promoting the progression of LUSC. However, whether M1/M2 polarization was involved in this process still needs to be experimentally explored. To observe the effect of LPCAT1 on LUSC cell functions, in vitro experiments were carried out. The results suggested that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway. PTEN is a tumor suppressor gene with dual specific phosphatase activity discovered in 1997 (Steck, Pershouse et al. 1997 ). PTEN participates in growth inhibition, apoptosis promotion, cell cycle regulation, inhibition of cell adhesion and tumor metastasis by regulating the PIP3 pathway (Nosaka, Yamasaki et al. 2017 , Wise, Hermida et al. 2017 ). The gene deletion and inactivation of PTEN or the over-expression of PIP3 can convert Akt to p-Akt (Zhao, Deng et al. 2017 ). P-Akt acts on downstream mTOR and other substrates through a phosphorylation cascade to promote tumor proliferation and angiogenesis, as well as accelerate tumor invasion and metastasis (Manning and Toker 2017 ). This study found that the interference or over-expression of LPCAT1 altered the expression of p-Akt and PTEN in LUSC cells, and there may be negative feedback regulation between LPCAT1 and PTEN. The relevant research supported our conclusions and proposed that in ERG-negative prostate cancers, LPCAT1 level is significantly increased in the subset of PTEN-deficient cancers (Grupp, Sanader et al. 2013 ). Furthermore, LPCAT1 promotes brain metastasis of lung adenocarcinoma by activating PI3K/Akt pathway (Wei, Dong et al. 2019 ), while PTEN inhibits the occurrence and development of tumors by inhibiting PI3K/Akt pathway (Chen, Chen et al. 2018 ). Therefore, we speculated that LPCAT1 inhibited PTEN expression thereby promoting phosphorylation of downstream Akt, which may further contribute to tumor progression and metastasis in LUSC through the mTOR pathway. However, since the data used in the bioinformatics analysis came from the public database, certain limitations were inevitably brought to this study, and further experimental verification on the relationships of LPCAT1 and immune cells such as neutrophils and M1 macrophages was needed. Besides, the results were only proved at the cellular level, which was another limitation in this study. In the following study, animal experiments in vivo will be conducted to further verify these findings. Conclusions A series of bioinformatics analyses indicated that LPACT1 has independent prognostic value and predictive potential for LUSC, while it is also significantly associated with immune microenvironment characteristics of LUSC. The in vitro experiment data further confirmed that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway. Declarations Author Contribution DS accomplished the design and experiment of this study and wrote the manuscript. LZ and YZ collaborated to perform the statistical analysis of experimental data and convert the data into the form of figures. AL supervised the experimental progress, revised the manuscript, and provided technical support for this study. All authors have read and approved the final manuscript for publication. Funding Not applicable. Acknowledgements Not applicable. Availability of data and materials All datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Conflicts of Interest The authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. References Chen CY, Chen J, He L et al (2018) PTEN: Tumor Suppressor and Metabolic Regulator. Front Endocrinol (Lausanne) 9: 338. https://doi.org/10.3389/fendo.2018.00338 Chen JW and Dhahbi J (2021) Lung adenocarcinoma and lung squamous cell carcinoma cancer classification, biomarker identification, and gene expression analysis using overlapping feature selection methods. 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Anticancer Agents Med Chem 22: 223-238. https://doi.org/10.2174/1871520621666210708115406 Zhao T, Zhang Y, Ma X et al (2021) Elevated expression of LPCAT1 predicts a poor prognosis and is correlated with the tumour microenvironment in endometrial cancer. Cancer Cell Int 21: 269. https://doi.org/10.1186/s12935-021-01965-1 Zhao XD, Deng HB, Lu CL et al (2017) Association of EGFR and KRAS mutations with expression of p-AKT, DR5 and DcR1 in non-small cell lung cancer. Neoplasma 64: 182-191. https://doi.org/10.4149/neo_2017_203 Zhou X, Lawrence TJ, He Z et al (2012) The expression level of lysophosphatidylcholine acyltransferase 1 (LPCAT1) correlates to the progression of prostate cancer. Exp Mol Pathol 92: 105-110. https://doi.org/10.1016/j.yexmp.2011.11.001 Additional Declarations No competing interests reported. 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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-3838907","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265539516,"identity":"528b4980-b7f8-4162-9cc6-4f3bd4344cfa","order_by":0,"name":"Dayou Shi","email":"","orcid":"","institution":"Nanchang University","correspondingAuthor":false,"prefix":"","firstName":"Dayou","middleName":"","lastName":"Shi","suffix":""},{"id":265539517,"identity":"bafd4bc2-d633-4a93-9229-00a5bceceedd","order_by":1,"name":"Lingzhi Zeng","email":"","orcid":"","institution":"the First People’s Hospital of Jiujiang","correspondingAuthor":false,"prefix":"","firstName":"Lingzhi","middleName":"","lastName":"Zeng","suffix":""},{"id":265539518,"identity":"fb2c4a1e-545a-45c6-b67c-7b746f5d7b69","order_by":2,"name":"Yayun Zha","email":"","orcid":"","institution":"the First People’s Hospital of Jiujiang","correspondingAuthor":false,"prefix":"","firstName":"Yayun","middleName":"","lastName":"Zha","suffix":""},{"id":265539519,"identity":"e39e40ad-ad8f-45fa-9393-726071f241b9","order_by":3,"name":"Anwen Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYFAC5oYDDBU2cvzMzIcfEKmFEajlTJqxZDtbmgHRWhgYWw4lGpznUZAgSgP/jMTGw7wNBxKMD/MwGDDU2EQT1CJxI7HhMO+OO3lmh3kPPGA4lpbbQFDPbZCWM8+KzQ7zJRgwNhwmrEUerKXtcOLmZh4DCaK0GMC0bGAmVovh/YcNB+cAA1niMDCQE4jxi9yZw4c/vAFFZf/hww8+1NgQ4X0UkECa8lEwCkbBKBgFuAAA11VHHdLxglkAAAAASUVORK5CYII=","orcid":"","institution":"Nanchang University","correspondingAuthor":true,"prefix":"","firstName":"Anwen","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-01-06 05:44:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3838907/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3838907/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49322256,"identity":"5ca7ef54-258e-40d0-933b-e38fc3db0378","added_by":"auto","created_at":"2024-01-08 16:50:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":764289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluating the prognostic value and predictive potential of LPCAT1 in LUSC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: Kaplan-Meier curves show the differences of OS (left panel) and DFS (right panel) probability between patients with high- and low-expression of LPCAT1. B: ROC curves demonstrate the specificity and sensitivity of the LPCAT1 in predicting 1-, 3- and 5-year survival. C: The nomogram model was constructed to predict OS by integrating LPCAT1 and clinical characteristics. D: Calibration curves were plotted to evaluate the predictive power of the nomogram model. E and F: The univariate (E) and multivariate (F) Cox regression analyses were performed to identify the prognostic independence of LPCAT1 and clinical features.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/c7a5e194d96bcb517062fdf8.jpg"},{"id":49323154,"identity":"c7395e2a-545a-40b5-8da9-11a209dd487b","added_by":"auto","created_at":"2024-01-08 17:06:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1404583,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnrichment analysis on DEGs between samples with high LPCAT1 expression and low LPCAT1 expression groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: The heatmap shows 980 DEGs between high-expression group and low-expression groups. B and C: GO function (B) and KEGG pathway (C) enrichment analyses on DEGs. D: GSEA pathwayenrichment analysis on DEGs.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/0faa08224a6450846dedfaf8.jpg"},{"id":49322671,"identity":"8f7adc5b-1310-4524-ae71-ff76968cb0bc","added_by":"auto","created_at":"2024-01-08 16:58:42","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1175148,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluating the relationships between LPCAT1 expression and immune features in LUSC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: The violin plot shows differences in StromalScore, ImmuneScore and ESTIMATEScore between high- and low-expression groups.(*\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01) B: The box plot depicts differences in immune cell infiltration levels between high- and low-expression groups. (*\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01) C: Correlations between LPCAT1 expression and immune cell infiltration levels. D: Correlations between LPCAT1 and immune checkpoint genes at the expression levels.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/931c14b363d8adc964cfe1f5.jpg"},{"id":49322255,"identity":"9d5999f6-1ba3-4664-b04d-508677653dc5","added_by":"auto","created_at":"2024-01-08 16:50:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1708516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression validation and expression intervention models construction of LPCAT1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA-B: RT-qPCR (A) and western blot (B) compared the expression differences of LPCAT1 between NCI-H226 and NCI-H520 cells with BEAS-2B cells at the mRNA and protein levels, respectively. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. BEAS-2B cells. C: The mRNA expression of LPCAT1 in NCI-H226 and NCI-H520 cells after transfecting pcDNA3.1 plasmid. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. Control, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. LPCAT1 NC. D: The mRNA expression of LPCAT1 in NCI-H226 and NCI-H520 cells after transfecting siRNA. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. Control, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. siRNA NC. E: The protein expression of LPCAT1 in NCI-H226 and NCI-H520 cells after transfecting pcDNA3.1 plasmid. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. Control. F: The pprotein expression of LPCAT1 in NCI-H226 and NCI-H520 cells after transfecting siRNA. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. Control.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/9a644ba70c5b5dfa08044fdf.jpg"},{"id":49322670,"identity":"9f46f0ed-8bbf-499d-b48a-dba4b3a99024","added_by":"auto","created_at":"2024-01-08 16:58:42","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1948277,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of LPCAT1 expression on proliferation, invasion and apoptosis of NCI-H226 and NCI-H520 cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: The viability of NCI-H226 and NCI-H520 cells after transfected with LPCAT1-pcDNA3.1 and siRNA. B: The invasive images and numbers of NCI-H226 and NCI-H520 cells after transfected with LPCAT1-pcDNA3.1 and siRNA. C: The apoptosis images and numbers of NCI-H226 and NCI-H520 cells after transfected with LPCAT1-pcDNA3.1 and siRNA. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. siRNA NC, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. OE NC.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/7f878283a98d02381e410e8b.jpg"},{"id":49322669,"identity":"1ee23cd9-b010-4b32-9a87-73efadd06e59","added_by":"auto","created_at":"2024-01-08 16:58:42","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1584533,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffects of LPCAT1 expression on the PTEN/Akt pathway.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA: The protein expression of Akt, p-Akt and PTEN after transfected with LPCAT1-pcDNA3.1 and siRNA. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. siRNA NC, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. OE NC. B-C: The mRNA (B) and protein (C) expression of PTEN in two cell lines after transfecting PTEN-pcDNA3.1 plasmid. *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. Control, \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. PTEN NC. D: The expression of p-Akt/Akt in NCI-H520 and NCI-H226 cells after transfected with LPCAT1-pcDNA3.1 and PTEN-pcDNA3.1 plasmids. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 vs. Control; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 vs. LPCAT1 NC.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/0cbd37405fc5ed039e8a9602.jpg"},{"id":49427863,"identity":"c0ea57c6-16f6-4a93-9059-53758206ab8a","added_by":"auto","created_at":"2024-01-10 16:07:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1541356,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/b02be0c0-f656-4e58-8fe0-5df2e863d723.pdf"},{"id":49322254,"identity":"faf7b69f-6464-4ee3-9452-c97869e960e3","added_by":"auto","created_at":"2024-01-08 16:50:42","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19366,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-3838907/v1/8886112b409db4489fd93a56.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinoma","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1. LPCAT1 is a prognostic risk factor of LUSC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. LPCAT1 is correlated with immune cell infiltration and immune checkpoint in LUSC.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3. LPCAT1 is highly expressed in LUSC cell lines.\u003c/p\u003e\n\u003cp\u003e4. LPCAT1 affects LUSC cell functions via the PTEN/Akt pathway.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eAs a major subtype of non-small cell lung cancer, lung squamous cell cancer (LUSC) is one of the leading causes of cancer-related death worldwide, with a non-negligible aggressiveness (Kujtan, Kancha et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Niu, Jin et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Squamous cell carcinoma of the lung mainly originates from the carcinosis of squamous cell epithelium transformed from glandular epithelium in lung tissues (Maroni, Bassal et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Compared with lung adenocarcinoma, LUSC usually metastasizes later and are diagnosed at an advanced stage (Chen and Dhahbi \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Li, Kuang et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, patients with LUSC suffer from an adverse prognosis, with a 5-year survival rate of less than 15% (Wang, Tang et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite efforts to study the molecular basis of LUSC, the treatment landscape has barely changed in decades, and effective targeted therapies are still lacking.\u003c/p\u003e \u003cp\u003eLysophosphatidylcholine acyltransferase 1 (LPCAT1), also known as AYTL2, is a lipid metabolism-related gene on chromosome 5 with a length of 69555bp (Tao, Luo et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). LPCAT1 is associated with cancer progression, metastasis, and recurrence and has been reported to overexpress as an oncogene in multiple cancers (Shida-Sakazume, Endo-Sakamoto et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Uehara, Kikuchi et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Du, Wang et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). LPCAT1 also correlate with immune cell infiltration and may serve as an independent prognostic marker in endometrial cancer (Zhao, Zhang et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Wei et al. proposed that LPCAT1 may indicate a poorer clinical prognosis in lung adenocarcinoma and influence tumor progression through the PI3K/Akt signaling pathway (Wei, Dong et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These findings suggest that LPCAT1 has the potential to be a novel target for cancer therapy. However, the potential role of LPCAT1 in LUSC remains poorly understood.\u003c/p\u003e \u003cp\u003eTherefore, using the bioinformatics approach, this study explored the predictive role of LPCAT1 on LUSC prognosis and analyzed its correlations with tumor immune microenvironment characteristics. Based on these results, this study further carried out \u003cem\u003ein vitro\u003c/em\u003e experiments to investigate the effects of LPCAT1 on cellular functions and PTEN/Akt pathway through the construction of overexpression and knockdown vectors. These findings may provide a new research idea for further understanding the potential regulatory mechanism of LPCAT1 in LUSC and optimizing treatment strategies to improve clinical outcomes of patients.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCancer Genome Atlas (TCGA)-based data collection and process\u003c/h2\u003e \u003cp\u003eThe expression matrix and clinical information of LUSC samples were downloaded from the TCGA Genomic Data Commons (GDC) database. The clinical survival data including overall survival (OS) and disease-free survival (DFS) were analyzed using GEPIA2 database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gepia2.cancer-pku.cn/#index\u003c/span\u003e\u003cspan address=\"http://gepia2.cancer-pku.cn/#index\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The median expression value of LPCAT1 was used as the threshold to differentiate the groups with high expression and low expression. Using the \"time-ROC\" package, the receiver operating characteristic (ROC) curves were plotted and the areas under the curve (AUCs) were calculated to estimate the potential of LPCAT1 in predicting prognosis of patients with LUSC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eEvaluating the prognostic independence of LPCAT1\u003c/h2\u003e \u003cp\u003eBased on the expression of LPCAT1 and clinical traits, a nomogram model was constructed using R language survival package to assess their influences on patient survival. Furthermore, the univariate and multivariate Cox regression analyses were performed by survival kit to appraise whether LPCAT1 and clinical features (including age, gender, and tumor stage) were independent prognostic factors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEnrichment analysis of differentially expressed genes (DEGs) between high- and low-expression groups\u003c/h2\u003e \u003cp\u003eThe limma package of R language was used to analyze the gene expression patterns between the LPCAT1 high- and low-expression groups, with the difference being determined by wilcox.test. The DEGs were selected at |log fold change (FC)| \u0026gt; 1 and false discovery rate (FDR)\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Then, the Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed by using the R.clusterProfiler package. Based on the download file of \"c2. Cp. Kegg. Hs. Symbols. GMT\" file, the gene set enrichment analysis (GSEA) function was used for enrichment analysis of GSEA pathway.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eComparisons of immune features between LPCAT1 high- and low-expression groups\u003c/h2\u003e \u003cp\u003eThe R language \u0026ldquo;estimate\u0026rdquo; package was used to calculate immune scores on the downloaded expression data of LUSC, followed by the comparison between the two groups using the \u0026ldquo;limma\u0026rdquo; package. The CIBERSORT was used to analyze the immune cell infiltration level of each sample, and the R language \u0026ldquo;stat_compare_means\u0026rdquo; function was used to compare the difference between high- and low-expression groups. The correlations between LPCAT1 expression and immune cell infiltration level were analyzed by the Spearman method, whereas the relationships between expressions of LPCAT1 and immune checkpoint genes were estimated by the Pearson method. All statistical significances were set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCell culture\u003c/h2\u003e \u003cp\u003eLUSC cell line NCI-H226 (BNCC287420) was provided by BNBIO (Beijing, China). LUSC cell line NCI-H520 (CL-0402) and human bronchial epithelial cell line BEAS-2B (CL-0496) were provided by Procell Life Science Technology (Hubei, China). NCI-H226 cells and NCI-H520 cells were cultured in RPMI-1640 media (Gibco, USA) containing 10% fetal bovine serum (FBS) (Gibco, USA) and 1% Pen-Strep (Gibco, USA) at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. BEAS-2B cells were cultured in DMEM media (Gibco, USA) containing 10% FBS and 1% Pen-Strep at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of expression intervention model of LPCAT1\u003c/h2\u003e \u003cp\u003eLPCAT1-pcDNA3.1 plasmid, PTEN-pcDNA3.1 plasmid and pcDNA3.1 plasmid were provided by General Biol (Anhui, China). Among them, LPCAT1-pcDNA3.1 plasmid and PTEN-pcDNA3.1 plasmid were used to construct the overexpression (OE) model of LPCAT1 and PTEN, respectively. Meanwhile, the pcDNA3.1 plasmid was transfected into cells of negative control (NC) groups. To achieve the expression interference of LPCAT1, three LPCAT1 siRNA and the siRNA NC were prepared by General Biol (Anhui, China). The detailed sequences of siRNA are show in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCell transfection\u003c/h2\u003e \u003cp\u003eThe mixture of plasmid/siRNA and Lipofectamine 3000 (Thermo Fisher, USA) was prepared for gene transfection according to the manufacturer\u0026rsquo;s instruction. When the confluence reached 70%, the cells were incubated with the mixture for 4 h. Completed medium containing 20% fetal bovine serum was added and the cells were cultured for another 48 h before subsequent examination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eReal-time quantitative polymerase chain reaction (RT-qPCR)\u003c/h2\u003e \u003cp\u003eCells were collected and resuspended in Trizon reagent (CW0580, CWBIO, China) to extract total RNA which was reversely transcribed to cDNA using HiFiScript cDNA synthesis kit (CW2141, CWBIO, China) according to the manufacturer\u0026rsquo;s instructions. Then, qPCR was performed using a RT-qPCR system (CFX Connect, Bio-Rad, USA). Detailed sequences of primers are shown in Supplementary Table\u0026nbsp;2. The relative mRNA level of LPCAT1 was calculated by 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e algorithm normalized to GAPDH.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot\u003c/h2\u003e \u003cp\u003eAfter cell lysis and centrifugation, total protein was extracted and protein concentration was subsequently determined using a BCA kit (CW0014S, CWBIO, China). Then, the protein was denatured, and loaded to conduct sodium dodecyl sulfate polyacrylamide gel electrophoresis for 2 h and transferred to polyvinylidene fluoride membranes at 300 mA. The membranes were incubated with primary antibody at 4\u0026deg;C overnight and then with secondary antibody at room temperature for 2 h. The antibodies used in this study are as follows: mouse anti-GAPDH monoclonal antibody (1:2000, TA-08, ZSGB-BIO, China), horseradish peroxidase (HRP)-labeled goat anti-mouse IgG(H\u0026thinsp;+\u0026thinsp;L) (1:2000, ZB-2305, ZSGB-BIO, China), HRP-labeled goat anti-rabbit IgG(H\u0026thinsp;+\u0026thinsp;L) (1:2000, ZB-2301, ZSGB-BIO, China), rabbit anti-LPCAT1 polyclonal antibody (1:4000, 16112-1-AP, Proteintech, USA), rabbit anti-Akt polyclonal antibody (1:500, ab8805, Abcam, USA), rabbit anti-p-Akt polyclonal antibody (1:500, af0016, Affinity, USA), rabbit anti-PTEN monoclonal antibody (1:1000, ab170941, Abcam, USA). After adding chemiluminescent substrate, the membranes were examined on a gel imaging system (ChemiDoc XRS+, Bio-Rad, USA), and the blots were analyzed by Quantity one software (v4.62, Bio-Rad, USA) with GAPDH being served as an internal control.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCell viability\u003c/h2\u003e \u003cp\u003eThe transfected cells were seeded in 96-well plate at a density of 6\u0026times;10\u003csup\u003e3\u003c/sup\u003e cells per well. After culturing for 48 h, the medium was replaced by 100 \u0026micro;L fresh one and 10 \u0026micro;L CCK8 reagent was added to each well. After 2h of incubation, the absorbance of each well at 450 nm was detected by a microplate reader to estimate the cell viability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCell apoptosis\u003c/h2\u003e \u003cp\u003eThe transfected cells were collected, treated with Annexin V-FITC/PI apoptosis kit (AP101-100-kit, MultiSciencesBiotech, China) according to the manufacturer\u0026rsquo;s instruction, and analyzed on a flow cytometer (NovoCyte, ACEA Biosciences, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCell invasion\u003c/h2\u003e \u003cp\u003eThe transfected cells were resuspended in a FBS-free medium and cell suspension containing 5\u0026times;10\u003csup\u003e4\u003c/sup\u003e cells were added into the upper chamber. The culture medium containing 10% FBS (500 \u0026micro;l) was added into the lower chamber. The cells were cultured for 48 h, washed with PBS for 5 min and stained in 0.1% crystal violet (G1061, Solarbio, China) for 60 min. The cells in the lower chamber were observed under a microscope (CKX41, Olympus, Japan). After removing the crystal violet solution, the cells in each well was mixed with 1 mL 33% acetic acid. The mixture (200\u0026micro;L) was taken from each well to a 96-well plate and the absorbance was measured on a microplate reader at 570 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and statistically analyzed with SPSS 19.0 software (SPSS Inc., IL, USA). Differences were analyzed by one-way analysis of variance with post-hoc test and defined to be significant at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eLPCAT1 indicates prognosis in LUSC\u003c/h2\u003e \u003cp\u003eThe prognostic value of LPCAT1 in LUSC was analyzed using GEPIA2 database. The Kaplan-Meier curves based on OS and DFS showed that the survival probability of patients with high expression of LPCAT1 was significantly lower than those with low expression of LPCAT1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The ROC curves were plotted and the AUCs of 1-, 3-, and 5-year survival were 0.553, 0.578, and 0.598, respectively, indicating that the sensitivity and specificity of LPCAT1 in predicting prognosis were ordinary (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Further nomogram analysis was performed on LPCAT1 and clinical characteristics, and the results revealed that LPCAT1 was a significant correlation factor affecting the survival time of patients' prognosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Calibration curves confirmed that the nomogram-predicted OS were close to the actual ones (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), indicating that the prognostic predictive efficacy of nomogram was good. Furthermore, the univariate and multivariate Cox regression analyses were performed to observe the impact of LPCAT1 expression, age, gender, and tumor stage on the prognosis of LUSC. The results showed that LPCAT1 was a significant high-risk factor in both univariate and multivariate Cox analyses (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE-F). The above results proved that LPCAT1 might be significantly associated with the prognosis survival of patients with LUSC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment analysis based on the expression of LPCAT1\u003c/h2\u003e \u003cp\u003eTo further understand the potential regulatory mechanism of LPCAT1 in LUSC, the expression of LPCAT1 was grouped, and the samples were divided into high-expression group and low-expression groups. Then, the express profiles were compared between the two groups and 980 DEGs were obtained (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). GO and KEGG enrichment analyses were performed on these DEGs (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-C), which were mainly enriched in \u0026ldquo;cell-cell adhesion via plasma-membrane adhesion molecules\u0026rdquo;, \u0026ldquo;collagen trimer\u0026rdquo;, \u0026ldquo;metal ion transmembrane transporter activity\u0026rdquo;, \u0026ldquo;complement and coagulation cascades\u0026rdquo; and other functional items and signal pathways. GSEA pathways were also enriched and it was found that \u0026ldquo;OLFACTORY TRANSDUCTION\u0026rdquo; pathway was significantly enriched in the high-expression group, while \u0026ldquo;DNA REPLICATION\u0026rdquo; channels were significantly enriched in the low-expression group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). Therefore, the regulation of LPCAT1 on LUSC might be realized through these functional entries and signaling pathways.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eRelationships of LPCAT1 expression and immune features in LUSC\u003c/h2\u003e \u003cp\u003eTumor microenvironment (TME) is considered to play an important role in the progression of LUSC. Therefore, the TME scores of LUSC samples were calculated and then compared between high-expression group and low-expression groups. The violin plot indicated the significantly higher StromalScore, ImmuneScore and ESTIMATEScore in the group with high LPCAT1 expression than that with low LPCAT1 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Furthermore, the infiltration abundances of immune cells were calculated and compared between the two groups. As results, plasma cells, M1 macrophages, neutrophils, CD8 T cells, resting/activated memory CD4 T cells, γδT cells, and resting dentritic cells suggested significant differences in infiltration levels between high and low LPCAT1 expression groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Meanwhile, the correlation analysis suggested that LPCAT1 had significant positive correlations with neutrophils and resting memory CD4 T cells, but had significant negative relationships with M1 macrophages and plasma cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). We also found that LPCAT1 was positively correlated with almost all immune checkpoint genes at the expression levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eExploring the expression pattern of LPCAT1 and constructing the expression intervention models\u003c/h2\u003e \u003cp\u003eTo further validate the expression patterns of LPCAT1, as well as biological functions in LUSC, \u003cem\u003ein vitro\u003c/em\u003e experiments were conducted accordingly. Results of RT-qPCR and western blot suggested that compared with BEAS-2B cells, the mRNA and protein levels of LPCAT1 increased significantly in both NCI-H226 and NCI-H520 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). Then, pcDNA3.1 plasmid and siRNA of LPCAT1 were transfected into NCI-H226 and NCI-H520 cells to construct the overexpression and interference models, respectively. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, after transfecting LPCAT1-pcDNA3.1 plasmid, the LPCAT1 levels were significantly elevated in both cells as compared with control and LPCAT1 NC group. Meanwhile, compared with Control group, Si-LPCAT1-1, Si-LPCAT1-2 and Si-LPCAT1-3 can significantly down-regulate the LPCAT1 expression in two cell lines (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Among them, Si-LPCAT1-2 had the strongest inhibitory effect on the LPCAT1 expression in two cell lines and therefore was selected for subsequent experiments.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eLPCAT1 affects the proliferation, invasion and apoptosis in LUSC cell lines\u003c/h2\u003e \u003cp\u003eTo observe the effects of LPCAT1 on cell proliferation, the CCK8 assay was performed and the results suggested that compared with NC groups, siRNA transfection significantly reduced the cell viability and LPCAT1-pcDNA3.1 transfection significantly raised the cell viability in both NCI-H226 and NCI-H520 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The transwell assay indicated the similar invasive numbers of NCI-H226 and NCI-H520 cells between control and NC groups. Furthermore, the invasive numbers were significantly decreased in siRNA groups but significantly increased in the OE group, compared with their respective NC groups in NCI-H226 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Finally, the flow cytometry was applied to detect apoptosis rates in these two cell lines. The results indicated that both NCI-H226 and NCI-H520 cells significantly elevated apoptosis after transfection with siRNA but significantly inhibited apoptosis after transfection with LPCAT1-pcDNA3.1 plasmid (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). These results revealed that LPCAT1 may promote proliferation and invasion but inhibit apoptosis in LUSC cell lines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eLPCAT1 mediates the PTEN/Akt pathway\u003c/h2\u003e \u003cp\u003eFurthermore, the protein expressions of genes in the PTEN/Akt pathway were also detected using western blot. The results of NCI-H226 and NCI-H520 cells both showed that p-AKT was up-regulated in cells transfected with siRNA but was down-regulated in cells transfected with LPCAT1-pcDNA3.1 plasmid (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). However, the expression pattern of PTEN is completely opposite to that of p-AKT. Notably, there was no significant difference in the expression level of AKT among all groups. To further study the effect of LPCAT1 on the PTEN/Akt pathway, the PTEN-pcDNA3.1 plasmid was transfected into cells to construct an overexpression model of PTEN. RT-qPCR and western blot verified that after transfecting the PTEN-pcDNA3.1 plasmid, the expression levels were sharply elevated in both NCI-H226 and NCI-H520 cells compared with Control and PTEN NC groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB-C). After co-transfected with LPCAT1-pcDNA3.1 and PTEN-pcDNA3.1, the expression level of p-Akt/Akt was detected by the western blot. In NCI-H226 cells, compared with the Control and LPCAT1 NC groups, the expression of p-Akt/Akt in the LPCAT1 and LPCAT1\u0026thinsp;+\u0026thinsp;PTEN group was up-regulated significantly, and its expression was down-regulated significantly in the LPCAT1 NC\u0026thinsp;+\u0026thinsp;PTEN group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). In NCI-H520 cells, the expression of p-Akt/Akt in the LPCAT1 group was significantly higher than that in the Control and LPCAT1 NC groups, and its expression in the LPCAT1 NC\u0026thinsp;+\u0026thinsp;PTEN group was significantly lower than that in the LPCAT1 NC group (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLPCAT1 is a cytoplasmic enzyme that can catalyze the conversion of Lysophosphatidylcholine to phosphatidylcholine (Du, Wang et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Bioinformatics analysis revealed that survival status of LUSC patients with high expression of LPCAT1 was significantly worse than those with low expression of LPCAT1. The nomogram model and Cox regression analyses also confirmed the prognostic value of LPCAT1 and its predictive potential in LUSC. In addition, the expression of LPCAT1 was found to be related to immune score, immune cell infiltration level, and immune checkpoint expression. To support these findings, the \u003cem\u003ein vitro\u003c/em\u003e experiments were conducted and the results illustrated the cancer-promoting role of LPCAT1 via the PTEN/Akt pathway. LPCAT1 has been found to be overexpressed in colorectal cancer (Mansilla, da Costa et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), liver cancer (Morita, Sakaguchi et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and prostate cancer (Zhou, Lawrence et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and may be a prognostic risk factor for hepatocellular carcinoma and breast cancer (Lebok, von Hassel et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Li, Wang et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Sun, Liu et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consistent with these findings, the present study demonstrates for the first time that LPCAT1 promotes tumor growth and invasion in LUSC and may affect patient survival and prognosis.\u003c/p\u003e \u003cp\u003eThe results based on the immune score suggested that patients with high LPCAT1 expression had higher StromalScore, ImmuneScore and ESTIMATEScore, indicating that these patients were in an immunologically activated state. Correlation analysis with immune cell infiltration levels further suggested that LPCAT1 was most significantly positively correlated with neutrophils but most significantly negatively correlated with M1 macrophages. Currently, neutrophils have received increasing attention for their pro-cancer effects, and an elevated neutrophil-to-lymphocyte ratio is considered a prognostic indicator for cancer (Xiong, Dong et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). It was reported that the level of neutrophils infiltration was significantly increased in the group with high prognostic risk of LUSC (Ma, Wang et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In LUSC, neutrophil infiltration levels were also significantly positively correlated with other prognostic risk factors such as GLUT1 and DLD (Zhang, Dong et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, Yang, Guo et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings support our conclusions and indicated that the elevated expression of LPCAT1 may promote tumor infiltration of neutrophils, thereby inducing the recurrence and metastasis of LUSC. Furthermore, it is known that pro-inflammatory M1 macrophages phagocytose tumor cells, whereas anti-inflammatory M2 macrophages promote tumor growth and invasion (Xia, Rao et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Among the macrophage subpopulations, M1 macrophages are thought to have an anti-tumor phenotype (Gao, Liang et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This study found that the expression of LPCAT1 was significantly negatively correlated with the level of M1 macrophage infiltration, suggesting that LPCAT1 inhibited the phagocytosis of tumor cells by M1 macrophages, thus promoting the progression of LUSC. However, whether M1/M2 polarization was involved in this process still needs to be experimentally explored.\u003c/p\u003e \u003cp\u003eTo observe the effect of LPCAT1 on LUSC cell functions, \u003cem\u003ein vitro\u003c/em\u003e experiments were carried out. The results suggested that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway. PTEN is a tumor suppressor gene with dual specific phosphatase activity discovered in 1997 (Steck, Pershouse et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). PTEN participates in growth inhibition, apoptosis promotion, cell cycle regulation, inhibition of cell adhesion and tumor metastasis by regulating the PIP3 pathway (Nosaka, Yamasaki et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Wise, Hermida et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The gene deletion and inactivation of PTEN or the over-expression of PIP3 can convert Akt to p-Akt (Zhao, Deng et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). P-Akt acts on downstream mTOR and other substrates through a phosphorylation cascade to promote tumor proliferation and angiogenesis, as well as accelerate tumor invasion and metastasis (Manning and Toker \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This study found that the interference or over-expression of LPCAT1 altered the expression of p-Akt and PTEN in LUSC cells, and there may be negative feedback regulation between LPCAT1 and PTEN. The relevant research supported our conclusions and proposed that in ERG-negative prostate cancers, LPCAT1 level is significantly increased in the subset of PTEN-deficient cancers (Grupp, Sanader et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, LPCAT1 promotes brain metastasis of lung adenocarcinoma by activating PI3K/Akt pathway (Wei, Dong et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while PTEN inhibits the occurrence and development of tumors by inhibiting PI3K/Akt pathway (Chen, Chen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Therefore, we speculated that LPCAT1 inhibited PTEN expression thereby promoting phosphorylation of downstream Akt, which may further contribute to tumor progression and metastasis in LUSC through the mTOR pathway.\u003c/p\u003e \u003cp\u003eHowever, since the data used in the bioinformatics analysis came from the public database, certain limitations were inevitably brought to this study, and further experimental verification on the relationships of LPCAT1 and immune cells such as neutrophils and M1 macrophages was needed. Besides, the results were only proved at the cellular level, which was another limitation in this study. In the following study, animal experiments \u003cem\u003ein vivo\u003c/em\u003e will be conducted to further verify these findings.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA series of bioinformatics analyses indicated that LPACT1 has independent prognostic value and predictive potential for LUSC, while it is also significantly associated with immune microenvironment characteristics of LUSC. The in vitro experiment data further confirmed that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e DS accomplished the design and experiment of this study and wrote the manuscript. LZ and YZ collaborated to perform the statistical analysis of experimental data and convert the data into the form of figures. AL supervised the experimental progress, revised the manuscript, and provided technical support for this study. All authors have read and approved the final manuscript for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003eAll datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u0026nbsp;\u003c/strong\u003eThe authors declare that this study was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen CY, Chen J, He L et al (2018) PTEN: Tumor Suppressor and Metabolic Regulator. 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Exp Mol Pathol 92: 105-110. https://doi.org/10.1016/j.yexmp.2011.11.001\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"LPCAT1, lung squamous cell carcinoma, prognosis, PTEN/Akt pathway","lastPublishedDoi":"10.21203/rs.3.rs-3838907/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3838907/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLPCAT1 acts as an oncogene in a variety of cancers, but its effect on lung squamous cell carcinoma (LUSC) has not been reported. This study aimed to determine the prognostic value of LPCAT1 by bioinformatics analyses and to confirm its effect on LUSC cell functions by \u003cem\u003ein vitro\u003c/em\u003eexperiments. The expression data and clinical information were obtained from the public database. The prognostic value of LPCAT1 was evaluated by Kaplan-Meier curves, nomogram analysis, and Cox regression analyses. The relationships of LPCAT1 and immune features were also estimated. Then, expressions of LPCAT1 and PTEN/Akt pathway in LUSC cell lines (NCI-H226 and NCI-H520) were detected by real-time quantitative polymerase chain reaction and western blot. Cell viability, invasion, and apoptosis were evaluated by CCK-8 assay, Transwell assay, and flow cytometry, respectively. The bioinformatics analyses suggested that LPCAT1 is an independent prognostic risk factor of LUSC and has predictive potential. Meanwhile, LPCAT1 was significantly associated with immune cell infiltration and immune checkpoint gene expressions. Experiment data suggested that LPCAT1 can promote proliferation and invasion but inhibit apoptosis in LUSC cell lines. LPCAT1 can also significantly decrease the PTEN expression but increase the p-Akt expression \u003cem\u003ein vitro\u003c/em\u003e. LPCAT1 indicates prognosis and correlates with immune features in LUSC. Experiment data indicated that LPCAT1 may promote proliferation and invasion but inhibit apoptosis of LUSC cell lines via the PTEN/Akt pathway.\u003c/p\u003e","manuscriptTitle":"Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-08 16:50:37","doi":"10.21203/rs.3.rs-3838907/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"16d418e1-a31e-452e-b04d-5a5d2f7319cc","owner":[],"postedDate":"January 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-10T15:59:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-08 16:50:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3838907","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3838907","identity":"rs-3838907","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}