Significance of Tumor Mutation Burden related immune gene PAEP in the progression and prognosis of clear cell renal cell carcinoma

Significance of Tumor Mutation Burden related immune gene PAEP in the progression and prognosis of clear cell renal 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 Significance of Tumor Mutation Burden related immune gene PAEP in the progression and prognosis of clear cell renal cell carcinoma Jie Yang, Zhifei Che, Shiying Zhou, Zechun Peng, Fangzhen Cai, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4650268/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 Background Clear cell renal cell carcinoma (ccRCC) is a common renal malignant disease with a poor prognosis. Tumor mutation load (TMB) has received much attention in various tumor studies, however, there were limited studies focus on the relationship between TMB and ccRCC. We aimed to investigate the role of TMB-related immune gene progestagen‑associated endometrial protein (PEAP) in ccRCC and the underlying molecular mechanisms. Methods Somatic mutation data of 336 patients with ccRCC were downloaded from the Cancer Genome Atlas (TCGA) database, and the mutational spectrum was analyzed using the "maftools" software package. Based on TCGA -ccRCC cohort, we summarized the status of gene mutations in ccRCC. The TMB was calculated and the samples were divided into high and low TMB groups. Then, we analyzed the relationship between TMB and clinical characteristic. Meanwhile, we identified some TMB-related immune genes through the intersection of TMB-Related differentially expressed genes (DEGs) and immune related genes. Finally, We selected the immune genes most associated with TMB, investigated its expression in renal tissues of ccRCC patients, and further investigated its role and potential molecular mechanisms In-vivo and in-vitro . Results Using bioinformatics we analyzed the most common mutation of Variant Classification, Variant Type, single nucleotide variants (SNV) Class for missense mutations, single nucleotide polymorphism (SNP) and C > T in ccRCC, respectively. we found that higher TMB related to shorter overall survival (OS), lower age and grade. Finally, we identified progesterone associated endometrial protein (PAEP) gene, a novel TMB-related immune gene in ccRCC, which was significantly overexpression in ccRCC tissues and cells with progression and poor survival in ccRCC patients. Furthermore, by constructing 786-O cell model, our results showed that PAEP promoted the invasion, migration, and proliferation of ccRCC cells; meanwhile, PAEP knockdown suppressed the PI3K/Akt/NF-κB signaling pathway. In- vivo studies, we found that after knocking out the PEAP gene, the subcutaneous transplanted tumors in nude mice were smaller and lighter. Mechanistically, we consider that PAEP may regulate the malignant biological phenotype and poor survival prognosis of ccRCC through the PI3K/Akt/NF-κB signaling pathway. Conclusion Our study suggests that PAEP might represents a potential target of antibody immunotherapy for ccRCC patients and also provides a strong theoretical basis for the clinical application of PAEP. Progesterone associated endometrial protein Tumor mutation burden Immunotherapy Clear cell renal cell carcinoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Renal cell carcinoma (RCC) is the most common genitourinary malignancy. As the most common type of RCC, Clear cell renal cell carcinoma (ccRCC) accounts for 75 ~ 80% of all RCC cases 1 , 2 . Recently, surgery and targeted therapy are the most common and effective clinical treatments for ccRCC patients 3 . However, its overall mortality rates are still slightly increased, partly due to early-stage metastasis of the disease 4 . Therefore, some novel markers for early diagnostic and therapeutic targets involved in ccRCC progression are urgently required with significant clinical value. In recent years, antibody immunotherapy represents a promising therapy for the clinical treatment of ccRCC patents, successfully developed and widely applied 5 . For example, Immune checkpoint inhibitors (ICI) such as PD-1/PD-L1 inhibitors develop as a potential clinical strategy for ccRCC 6 , 7 . However, ccRCC patients sometimes show low objective response rates against ICI 8 . Tumor mutation burden (TMB) is defined as a total number of somatic coding mutations in the exon coding region of the genome of a tumor cell. TMB is a potential biomarker for predicting ICI response in varying tumors 9 , 10 . TMB was first identified as a potential biomarker for treatment with ICI in melanoma in 2014 11 . Since then, TMB has been considered to be related to the therapeutic effect of immune checkpoint inhibitors and has become a key predictor of the efficacy of immunotherapy for some malignant tumors 12 . In addition, studies have shown that high TMB levels are associated with better prognosis in patients with many malignant tumors, such as non-small cell lung cancer and endometrial cancer 13 . A study in advanced cancer patients not treated with ICI reported no correlation between high TMB and better prognosis 14 . However, many studies have shown that high levels of TMB are associated with poor prognosis in patients with thyroid cancer 15 , head and neck squamous cell carcinoma 16 and intrahepatic cholangiocarcinoma 16 . At present, whether the level of TMB is related to the prognosis of patients with malignant tumors is still controversial. The connection between TMB and immune infiltration was deviated from varied tumors 17 , 18 . Nevertheless, limited studies on TMB-related immune genes in ccRCC, so we tried to research the potential relationship between TMB and ccRCC. In this study, based on the TCGA-ccRCC cohort, we summarized the current status of gene mutations in ccRCC. The relationship between TMB and clinical features was then analyzed. Meanwhile, we identified some TMB-related immune genes by cross-validation of TMB-related differentially expressed genes (DEGs) and immune-related genes, and found that gene Progestagen‑associated endometrial protein (PAEP) was closely related to the prognosis of ccRCC. Finally, through clinical data and in vitro experiments, we further confirmed that gene PAEP promoted the malignant progression of ccRCC, which may be related to the PI3K/Akt/NF-κB signaling pathway. Methods Data source and mutation analysis The data of ccRCC patients, including “mask somatic mutation”, transcriptome profiles and clinical data, was obtained from the the Cancer Genome Atlas (TCGA ) database on November 08,2020. At the same time, we used the Mutect algorithm to processed “mask somatic mutation” data and visualized the results using the “maftoools” R package. Then, we categorized the ccRCC patients into high-TMB group and low-TMB group according to the median value of TMB. To analyze the correlation between TMB status and several clinicopathological characteristics, we analyzed the significance. We also analyzed the difference of overall survival (OS) between the high-TMB group and low-TMB group using Kaplan-Meier statistics. To evaluate the diagnostic value of TMB-related immune genes in ccRCC, we performed Receiver Operating Characteristic (ROC) curves and calculated the area under the ROC curve (AUC) to assess the diagnostic efficiency. TMB-Related differentially expressed genes and functional enrichment analysis To understand the TMB-Related function, we used the R package “limma v3.38.3” to perform TMB-Related differentially expressed genes (DEGs) between the above two TMB subgroup with p 1.0. Meanwhile, we visualized the DEGs with volcanic plot and heatmap. Nevertheless, Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) were identified using R package “clusterProfiler, org.Hs.eg.db, enrichplot” to identify the functional enrichment and pathway enrichment of all DEGs 19 . All above results were visualized by R package “ggplot2, heatmap, ggpubr, ggthemes”. Identification and Coexpression analysis of TMB-related immune genes On the other hand, we obtained a list of immune related genes (IRG) from the Immport data ( https://www.immport.org ), then we defined the common genes as TMB-related immune genes between immune related genes and DEGs using R package “ggplot2”. Finally, we performed the expression, correlation, and risk score distribution, survival status of the TMB-related immune genes among patients based on the expression of these genes using R package “corrplot, ggplot2, heapmap”. Finally, we selected the highest correction and novel gene for the future analysis, including expression analysis, Gene Set Enrichment Analysis (GSEA), OS, ROC and clinical correlation with GSEA project (4.0.3) and R package “pROC, ggplot2, CBCgrps” 20 , 21 . Cell culture and and treatment The human ccRCC cell line,769-P, 786-0, A498 and ACHN, was purchased from ASY Biotechnology Ltd., Corp (Wuhan, China). All cells were cultured in 89% RoswellParkMemorialInstitute (RPMI) 1640 medium (Life Technologies, Gibco, USA, 11875119) supplemented with 10% fetal bovine serum(FBS)(Life Technologies, Gibco, USA,) A5670701 and 1% penicillin–streptomycin (Life Technologies, Gibco, USA, 15140122) unless stated otherwise. The cells were incubated at 37°C in a humidified incubator with 5% CO 2 . They were thereafter subjected to growing until 85%– 95% confluency in the culture flask, trypsinized, and harvested for subsequent experiments. Short hairpin RNA construction and cell transfection PAEP short hairpin ribonucleic acid (shRNA) expressing lentivirus was obtained from GeneChem Co., Ltd. (Shanghai, China) ( https://www.genechem.com.cn ). Transfection conditions were reference to our previous paper. Briefly, the short hairpin RNA (shRNA) target sequence was shPAEP1, 5'-AAGATCAACTATACGGTGG-3', shPAEP2, 5'-AAGAGCCGTGCCGTTTCTA-3'. Conforming to the manufacturer's guidance, the 786-0 cells were transfected with shRNA non-sense control (shRNA-Con group) or with PAEP shRNA (shRNA-PAEP group) using lentiviral particles at a MOI (100:1) of 100 pfu/cell in the presence of polybrene (Yeasen, Shanghai, China, 40804ES86). In order to acquire PAEP knockdown cell lines, the transfected cells were treated with 5 mg/mL of puromycin (Yeasen, Shanghai, China, 60209ES10). Then, the resistant colonies were collected and cultivated for further analyses. Patient selection and preparation of tissue 36 patients who were diagnosed as ccRCC at the Second Affiliated Hospital of Hainan Medical University were enrolled in our study. More detailed information of the patents is previous described. The ccRCC and their paired-normal tissues were snap-frozen immediately after removal and stored at − 80 ◦ C. During every stage of our experiments, we adhered to the guidelines outlined in the Code of Ethics of the World Medical Association. The Ethics Committee of Hainan Medical University conducted a review of our research and granted approval(2024-KCSN-13). After receiving sufficient information, all participants enrolled in this study provided their written consent. Western blotting Lysis of the cells was done with RIPA buffer (Beyotime Biotechnology, China, P0013B), protease inhibitor cocktail (Roche, Switzerland, P8215), and phenylmethylsulfonyl fluoride (Beyotime Biotechnology, China, ST507-10mL, China, P0011) in a ratio of volume 100:4:1 for 30 min on ice. A bicinchoninic acid protein assay kit (Beyotime Biotechnology, China, P0011) was utilized to accurately measure the protein concentration. In addition, 30µg protein was isolated on 15% or 10% sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) gel (Biotechwell, China) and transferred onto the polyvinylidene difluoride (PVDF) membrane (# IPFL00010; Millipore, USA). After that, blocking of the PVDF membranes was done using 5% skimmed milk (# 232100; BD Biosciences, USA) for 3 h. The membranes were then incubated throughout the night at 4°C with primary antibodies: anti- PAEP (Abcam, UK, #ab270454, #1:1000), anti-p-PI3K (Abcam, UK, ab278545, #1:1000), anti-PI3K (Abcam, UK, ab302958, #1:1000), anti-AKT (Abcam, UK, ab8805, 1:500), anti-p-AKT (Abcam, UK, ab192623, 1:1000), anti-p-p65 (CST, USA, #3033, 1:1000), anti-p65 (CST, USA, #8242, 1:500), anti-p-IκBα (CST, USA, #2859, 1:1000), anti-IκBα (CST, USA, #9242, 1:1000), and anti-β-Actin (Abcam, UK, ab8226, 1:3000).Afterward, the fluorescent secondary antibodies were utilized for sample incubation in the darkness for 2 h. The Odyssey infrared imaging equipment (LI-COR Biosciences, USA) was utilized to scan and develop the membranes. The grayscale value of the experiment was analyzed with the aid of the ImageJ software. qPCR According to the manufacturer’s instructions, total RNA from the ccRCC and their paired-normal tissues was extracted using the Trizol reagent (Invitrogen, Carlsbad, CA, USA, 15596026CN). The concentration of the RNA was determined using ultraviolet spectrophotometry. The cDNA was synthesized using a PrimeScript RT Reagent Kit (Takara, Shiga, Japan, RR047A). Quantitative real-time PCR analysis for PAEP mRNA levels was performed using a TB Green® Premix Ex Taq ™ II FAST qPCR (Takara, Shiga, Japan, CN830S) through an Applied Biosystems 7500 Real-Time PCR System(Thermo Fisher Scientific, Inc., USA). Relative mRNA expression levels were calculated using the relative Ct method, and the fold change compared with β-actin (Sangon Biotech, Shanghai, China) as the control. The primer sequences were as follows: PAEP: Forward:5-CCTGTTTCTCTGCCTACAGGA-3, Reverse:5-CCTGTTTCTCTGCCTACAGGA-3; β-Actin: Forward:5-GTCCACCGCAAATGCTTCTA-3, Reverse:5-TGCTGTCACCTTCACCGTTC-3. Cell Counting Kit‑8 (CCK‑8) assay The density of 786-O cells was adjusted to 1 × 10 4 cells /mL, 100µL was added to each well in the 96-well culture plate, and cultured in an incubator with 5% CO 2 and 37℃. The cell Optical Density was measured at 450 nm using the Spark™10 M microplate reader (Tecan Group, Ltd.) at 0h, 24h, 48h, and 72h according to the CCK-8 kit (Beyotime Biotechnology, China, C0038) operating manual, and cell growth curves were plotted. Flow cytometry 786-O cells were inoculated on a 6-well plate 48 hours later, cell suspension was collected, 1000g, centrifuged at 4℃ for 5min, cells were collected and counted with precooled PBS, 5–10×10 5 cells were taken, centrifuged at 1000g for 5min, and supernant was discarded. According to the Annexin V-FITC Apoptosis Detection Kit manufacturer's instructions (Beyotime Biotechnology, China, C1062S), Annexin V-FITC binding solution 195µL Annexin V-FITC was added, the cells were lightly suspended, 5µL Annexin V-FITC was added, the cells were lightly mixed, 10µL propyl iodide staining solution was added, the cells were gently mixed, and incubation was performed at room temperature for 10–20 min, the cells were re-suspended for 2–3 times to improve the staining effect, and then placed in an ice bath away from light. Finally on the machine detection. Cell proliferation, migration and invasion assays The colony formation test was conducted to examine the impact of PAEP expression knockdown on the growth potential of 786-O cells. In addition, 700 cells/well (786-O cells transfected with the sh-Con and sh-PAEP) were seeded in 6-well plates, correspondingly, and were treated after 14 days. Then, the cells were fixed in 75% alcohol for 30 min and stained with 0.5% crystal violet (Yeasen, Shanghai, China, 60506ES60) for 30 min. The cell colonies were calculated using Image J software. Three replicates of each experiment were carried out, and the mean ± standard deviation (SD) was calculated. 24-well Transwell plates (cat. no. 3422, Corning, USA) with or without Matrigel matrix (cat. no. 356234, BD Biosciences, USA) were used for migration assay and invasion assay. The upper chambers and the lower chambers were seeded 1 × 10 5 cells in 200 µl without FBS RPMI 1640 medium and added 600 µl of RPMI 1640 containing 20% FBS, respectively. Subsequently, cells that migrated or invaded through the bottom of chambers were fixed with 4% paraformaldehyde, and then stained with 0.5% crystal violet for 30 min. Finally, the image was captured under a microscope. To measure the invasive and migratory capability of cells, we enumerated cells invading the Matrigel using ImageJ. Tumor formation in nude mice BALB/c female nude mice, 5 to 6 weeks old, purchased from Hunan SJA Laboratory Animal Co., Ltd. (production license No. SCXK [Hunan] 2019-0014), kept at 22˚C, Humidity 50%, light/dark cycle 12 h environment, free to eat and drink. All animal experiments were approved by the Ethics Committee of XX University. The nude mice were randomly divided into 3 groups, Ctrl group, shCon group and shPEAP group, with 6 mice in each group. Ctrl group: Logarithmic growth of 786-O cells was implanted in the back of nude mice. shCon group: 786-O cells were transfected with negative control sh-NC, and logarithmic growth cells were implanted in the back of nude mice. shPEAP group: 786-O cells were transfected with lentivirus shPEAP, and logarithmic growth cells were implanted in the back of nude mice. The tumor volume was measured every 2–3 days. 15 days after inoculation, the nude mice were euthanized for cervical dislocation, and the tumors were photographed, measured, weighed, and WB detected. Statistical analysis We selected the TMB-Related DEGs with p 1.0 to further assess. The KM analysis and log-rank test were used to assess OS in the ccRCC cohort. The Chi-square test was used to assess correlation between PAEP expression and clinicopathologic characteristics of ccRCC patients. All experiments were performed with at least three independent biological replicates. The data are expressed as means ± standard deviation (SDs). We employed R (version 4.3.1), SPSS (version 25.0; IBM, USA), and GraphPad Prism (version 7; GraphPad Software, USA) for all statistical analyses. Two-tailed t -tests and one-way analysis of variance (ANOVA) were used to analyze cell culture experiments. The criterion for statistical significance was set at P < 0.05. Results Mutation analysis Somatic mutation profiles of 537 ccRCC patients downloaded from TCGA database were analyzed and visualized using R package “maftools” 22 . A waterfall plot was performed to exhibit the detailed mutation information in each sample. The majority of Variant Classification, Variant Type, single nucleotide variants (SNV) Class were missense mutations, single nucleotide polymorphism (SNP), C > T, respectively (Fig. 1 A i-iii). Counting each sample separately, the median and maximum of mutations in the TCGA-ccRCC cohort were 47 and 1611, respectively (Fig. 1 A iv and Fig. 1 B). In addition, we exhibited the number of each variant classification in the different sample using box plots (Figure.1A v). The top 10 mutated genes in the 336 ccRCC patients were VHL (49%), PBRM1 (42%), TTN (18%), SETD2 (12%), BAP1 (10%), MUC16 (7%), MTOR (7%), KDM5C (6%), HMCN1 (5%), DNAH9 (5%) (Figs. 1 A vi, 1B and 1D), while the PBRM1 and VHL have the highest correlation (Fig. 1 C). Correlation of TMB with prognosis and clinical features After the clinical data of ccRCC patients were collected from TCGA, we selected 336 patients with complete information. Based on the median TMB value (1.29), we divided 336 patients into high-and low-TMB groups (n = 163 VS n = 173). As showed in the Kaplan-Meier curve, the high-TMB group had significantly poor OS outcomes (P = 0.007) (Fig. 2 H). Besides, the correlation of TMB with clinical features showed that only age and grade were significantly associated with TMB (p < 0.05) (Figs. 2 A and 2 C), the other clinical characteristics showed no significantly difference (Figs. 2 B and 2 D- 2 G). TMB-Related differentially expressed genes and Functional enrichment analysis According to the DEGs expression analysis between high-TMB group and low-TMB group, a total of 120 DEGs with |log 2 FC|> 1 and FDR < 0.05 was identified. There are 44 up-regulated genes and 76 down-regulated genes in the high-TMB group, compared to the low-TMB group. The heatmap and volcano plot showed the top 40 DEGs ranked in the order of FDR and all DEGs, respectively (Figs. 3 A and 3 B). According to GO and KEGG analysis, DEGs were enriched in the function enrichment of apical part of cell, apical plasma membrane, axon terminus and the pathway of Calcium signaling pathway, Vibrio cholerae infection and Taurine and hypotaurine metabolism (Figs. 3 C and 3 D). Comparison of gene expression profiles between two tmb groups We further identified the TMB-related immune genes through the intersection of 1793 immune related genes and 120 DEGs for subsequent analysis (Fig. 4 A). Then, we selected 8 TMB-related immune genes including CRP, IGHA2, IGLC3, IL6, LBP, LCN1, PAEP, SLIT2. We extracted the mRNA expression of each TMB-related immune genes to draw the box plot, heatmap and correlation heatmap (Figs. 4 B- 4 D). The results revealed that IGHA2, IGLC3, PAEP were increased, while CRP, LCN1 and SLIT2 decreased, IL-6 and LBP resting in ccRCC tissues, compared to the normal tissues (Figs. 4 B and 4 C). Importantly, PAEP and LCN1 had the highest correlation score (0.96) (Fig. 4 D).in addition, the ccRCC patents with higher risk scores, composing by these genes, had poor outcomes (Fig. 4 E). Finally, we selected the PAEP which is a never reported gene in ccRCC for the further research. PAEP was overexpression and associated with shorter survival in ccRCC patents Considering PAEP overexpression in ccRCC, we further investigated whether it contributed to ccRCC progression. Thus, we chose the 786-0 cells which had the highest levels of PAEP for further investigation (Figs. 5 A- 5 B). 786-0 cells were transfected with short hairpin RNAs (shRNAs) targeting to PAEP, which significantly silenced the PAEP expression (Figs. 5 C- 5 D). PAEP was significantly overexpressed in the TCGA-ccRCC cohort, compared to the normal group (Fig. 5 E), which was further validated in ccRCC tissues and ccRCC cells by RT-qPCR and Western blot analysis (Figs. 5 F- 5 H). Moreover, analysis of clinical characteristics indicated that PAEP overexpression was significantly correlated with Primary tumor size, TNM stage and Fuhrman grade (Table 1 ). Importantly, Kaplan-Meier analysis revealed that ccRCC patients with high PAEP expression had poor OS and disease-free survival (DFS )in the TCGA cohorts and further confirmed in our cohort (without DFS result) (Figs. 5 I- 5 K), indicating that PAEP upregulation was potentially related to the ccRCC progression. To evaluate the diagnostic value of PAEP in ccRCC, we constructed ROC curve and calculated the AUC (Fig. 5 L). The ROC curve of PAEP indicated it was a medium diagnostic tool with an AUC is 0.764. We performed GSEA to reveal potential molecular mechanism of PAEP regulating the progression of ccRCC. The results showed that all the significant pathways were enrichment in the PAEP overexpression group related to various tumorigenesis-related characteristics, containing MAPK signaling pathway, Renal Cell Carcinoma, TGF-β signaling pathway, ubiquitin mediated proteolysis and Wnt signaling pathway, etc (Fig. 5 M). These results provide new clues for exploring the molecular mechanism of ccRCC in the future. In conclusion, PAEP serves as an important oncogene and is associated with a poor clinical outcome of ccRCC. Table 1 Correlation between PAEP expression and clinicopathologic characteristics of ccRCC patients a Characteristics N PAEP expression level p -value Low High Age at surgery 0.289 < 65 years 24 10 14 ≥ 65 years 12 8 4 Sex 0.146 Men 25 10 15 Women 11 8 3 Primary tumor size 0.007 < 7 cm 26 17 9 ≥ 7 cm 10 1 9 pT stage 0.691 pT1-2 28 15 13 pT3-4 8 3 5 TNM stage 0.027 I + II 25 16 9 III + IV 11 2 9 Fuhrman grade 0.041 1 + 2 28 17 11 3 + 4 8 1 7 Abbreviations: N for number of cases, T for tumor stage, TNM for tumor node and distant metastasis. a for Chi-square test, * p < 0.05, ** p < 0.01. PAEP knockdown inhibited ccRCC cells growth First of all, CCK-8 results showed that compared with the Blank group, the cell viability of sh-Con group had no significant change, while the cell viability of sh-PEAP group was significantly reduced (Figs. 6 A). The results of flow cytometry showed that compared with the Blank group, the apoptosis of sh-Con group was not obvious, and the apoptosis of sh-PEAP group was significantly increased ( p < 0.05; Figs. 6 B and 6 C). Then, we performed the transwell assays and colony formation assays to evaluate invasion, migration and proliferation in response to PAEP knockdown in 786-0 cells. Transwell assays showed that PAEP knockdown remarkably reduced cell invasion and migration in 786-0 cells, compared to Blank groups and shCon groups ( p < 0.001; Figs. 6 D − 6F), Meanwhile, colony formation assays revealed that PAEP knockdown significantly reduced cell colonies in 786-0 cells compared with Blank groups and shCon groups ( p < 0.05; Figs. 6 G and 6 H). These results showed that PAEP knockdown inhibited ccRCC cells growth. Taken together, our results suggested that PAEP promoted the progression of ccRCC. PAEP induces activation of the PI3K/Akt/NF-κB pathway Previous studies showed that PAEP contributed to the activation of the PI3K/Akt/NF-κB signaling pathway 23 . It could be inferred that PAEP played an important role in the activation of the PI3K/Akt/NF-κB signaling pathway. Therefore, we performed western blotting assays to assess changed genes involved in the PI3K/Akt/NF-κB signaling pathway in 786-0 cells. The results shown that PAEP knockdown inhibited PI3K/Akt/NF-κB activation ( p < 0.05; Figs. 6 I- 6 K). PAEP knockdown inhibited tumor formation in nude mice. We further studied the effect of PEAP knockdown on subcutaneous tumor formation in nude mice in vivo, and the results showed that we first successfully constructed a subcutaneous tumor transplantation model in nude mice (Fig. 7 C and 7 D). Western blotting study results showed that compared with Ctrl group, there was no significant change in the expression of PEAP protein in shCon group, while the expression of PEAP protein in shPEAP group was significantly reduced (Fig. 7 A and 7 B). At the same time, we also found that compared with the Ctrl group, the weight and volume of transplanted tumors in the shCon group did not change much, while the weight and volume of transplanted tumors in the shPEAP group significantly decreased (Fig. 7 E- 7 F). Discussion In recent years, the incidence of RCC has continued to rise, affecting more than 400,000 people worldwide every year 24 , causing a huge burden on global public health. Of all the renal cell subtypes, ccRCC is the most common, accounting for about 70–80% 1,2 . Current clear cell renal cell carcinoma patients have high metastasis, incremental recurrence, and low response rate to immune checkpoint therapy 1 , 8 . As a new treatment strategy to predict immune responses, TMB had been exhibited their effect in a variety of tumor types 25 . However, the underlying mechanism of how TMB-related immune genes regulate the occurrence and metastasis of ccRCC remains unclear. In our study, we explored the status of TMB in ccRCC. The landscape of mutation profiles in TCGA-ccRCC cohort showed that 88.1% of patients develop varied types of mutation. The majority of Variant Classification, Variant Type, SNV Class were missense mutations, SNP, C > T, respectively. For the correlations between TMB and clinicopathological characteristics, the higher TMB level correlated with higher age, higher AJCC-T, grade and stage. Meanwhile, ccRCC patents with higher TMB have shorter OS. These results were in accordance with previous study 26 . Further, we identified some TMB-related immune genes through the intersection of DEGs and immune related genes, in which PAEP and LCN1 had the highest correlation. Finally, we selected the PAEP gene for the further research, which is a never reported gene in ccRCC. PAEP was overexpressed in approximately 80% of all tumors compared to normal tissue. PAEP was initially described as an immune system modulator in reproduction 27 . Knockdown of PAEP resulted in a deregulation of immune system modulators, such as PD-L1 28,29 . In this study, we confirmed that PAEP was overexpressed in a cohort of 36 ccRCC patients and PAEP overexpression was closely correlated with Primary tumor size, TNM stage and Fuhrman grade. This expression pattern is similarly with the other cancers 30 . Further, PAEP is useful for determining prognosis of ccRCC and also can be severed as a potential diagnostic biomarker. PAEP knockdown significantly inhibited the proliferation, migration and invasion of ccRCC. Our research is consistent with the function of PAEP in other cancer 31 . The abnormality of apoptosis plays a crucial role in the occurrence of tumor. For a long time, apoptosis has been considered as an important mechanism to prevent the occurrence of tumor, and one of the characteristics of tumor cells is to inhibit apoptosis 32 . In this study, we observed that PEAP knockdown promotes apoptosis of ccRCC cells, suggesting that PEAP may be an important target for the treatment of ccRCC. Mechanistically, PAEP knockdown decreased PI3K/Akt/NF-κB signaling pathway in ccRCC. Suraj Peri have found that the NF-κB signaling pathway is constitutively active in a high percentage of ccRCC cases 33 . Nonetheless, we found that knock down PAEP could efficiently depressed the activation of PI3K/Akt/NF-κB pathway, suggesting that PAEP maybe a potential target for this incurable malignancy. In addition, in vivo studies, we found that knocking down PEAP significantly reduced the expression of PEAP protein in transplanted tumor tissue, inhibited the formation of transplanted tumor, and reduced the size and weight of transplanted tumor tissue. These results suggest that low PEAP expression may inhibit the further development of ccRCC. There are some shortcomings in this study. First of all, we only studied the gene mutation status of ccRCC based on the TCGA database and analyzed the relationship between clinical characteristics of TMB, and the results were biased to some extent. Secondly, we identified PAEP gene, which is a new TMB related ccRCC immune gene, and only made preliminary identification through ccRCC tissue. However, the amount of data is still too small and persuasive, and more clinical experiments are needed to further confirm it. Finally, due to the limitation of funds and time, we have not conducted rescue experiments to verify whether the regulatory effect of PEAP is played by the PI3K/Akt signaling pathway, and we plan to conduct in-depth research on this in the follow-up studies. Conclusions In summary, our study showed that overexpression of PAEP promotes ccRCC malignant progression may relate to the PI3K/Akt/NF-κB signaling pathway. Understanding the important role of PAEP in ccRCC would widen our knowledge of the biological basis of ccRCC progression and might represents a potential target of antibody immunotherapy for ccRCC patients. Abbreviations TMB Tumor mutation burden ccRCC Clear cell renal cell carcinoma PAEP Progesterone associated endometrial protein ICI Immune checkpoint inhibitors Declarations Funding This study was supported by Hainan Provincial Natural Science Foundation of China (ZDYF2024SHFZ122, 822NQ472, 820MS142). Author contributions Jie Yang, Zhifei Che, Shiying Zhou, Zechun Peng, Fangzhen Cai and Shuming He performed the bioinformatics analysis, drafted the manuscript and prepared the figures. Jie Yang and Zhifei Che collected the clinical data and experiments. Shuming He and Jie Yang design the study. Jie Yang, Zhifei Che and Shuming He collected the related references and participated in discussion. All authors contributed to this manuscript. All authors read and approved the final manuscript. Availability of data and materials All data generated or analyzed during this study are available from the corresponding author upon reasonable request. The datasets analyzed during the current study are available in the TCGA and Immport databases. [https://portal.gdc.cancer.gov/,https://www.immport.org/home]. Acknowledgments The authors would like to thank the Central Laboratory of Hainan Medical University, where most of this work was performed. Ethics approval and consent to participate All experiments were carried out in accordance with the Code of Ethics of the World Medical Association. The Ethics Committee of Hainan Medical University conducted a review of our research and granted approval(2024-KCSN-13). All the human subjects gave their informed consent for the use of their samples and data. Consent for publication Not applicable. Competing interests The authors declare no conflicts of interest. References Hora M, Albiges L, Bedke J, European Association of Urology Guidelines Panel on Renal Cell Carcinoma Update on the New World Health Organization Classification of Kidney Tumours 2022, et al. The Urologist's Point of View. Eur Urol. 2023;83(2):97–100. Rasti A, Abolhasani M, Zanjani LS, Asgari M, Mehrazma M, Madjd Z. Reduced expression of CXCR4, a novel renal cancer stem cell marker, is associated with high-grade renal cell carcinoma. J Cancer Res Clin Oncol. 2017;143(1):95–104. Li Y, Lih TM, Dhanasekaran SM, et al. Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness. Cancer Cell. 2023;41(1):139–63. e117. Che Z, Fan J, Zhou Z, et al. Activation-Induced Cytidine Deaminase Expression Facilitates the Malignant Phenotype and Epithelial-to-Mesenchymal Transition in Clear Cell Renal Cell Carcinoma. DNA Cell Biol. 2020;39(7):1299–312. Meylan M, Petitprez F, Becht E, et al. Tertiary lymphoid structures generate and propagate anti-tumor antibody-producing plasma cells in renal cell cancer. Immunity. 2022;55(3):527–e541525. Khagi Y, Kurzrock R, Patel SP. Next generation predictive biomarkers for immune checkpoint inhibition. Cancer Metastasis Rev. 2017;36(1):179–90. Nunes-Xavier CE, Angulo JC, Pulido R, Lopez JI. A Critical Insight into the Clinical Translation of PD-1/PD-L1 Blockade Therapy in Clear Cell Renal Cell Carcinoma. Curr Urol Rep. 2019;20(1):1. Sherman E, Lee JL, Debruyne PR, et al. Safety and efficacy of cobimetinib plus atezolizumab in patients with solid tumors: a phase II, open-label, multicenter, multicohort study. ESMO Open. 2023;8(2):100877. Salem ME, Bodor JN, Puccini A, et al. Relationship between MLH1, PMS2, MSH2 and MSH6 gene-specific alterations and tumor mutational burden in 1057 microsatellite instability-high solid tumors. Int J Cancer. 2020;147(10):2948–56. Patel SP, Kurzrock R. PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy. Mol Cancer Ther. 2015;14(4):847–56. Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014;371(23):2189–99. Marabelle A, Fakih M, Lopez J, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21(10):1353–65. Riviere P, Goodman AM, Okamura R, et al. High Tumor Mutational Burden Correlates with Longer Survival in Immunotherapy-Naïve Patients with Diverse Cancers. Mol Cancer Ther. 2020;19(10):2139–45. Samstein RM, Lee CH, Shoushtari AN, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202–6. Xie Z, Li X, Lun Y, et al. Papillary thyroid carcinoma with a high tumor mutation burden has a poor prognosis. Int Immunopharmacol. 2020;89(Pt B):107090. Zhang L, Li B, Peng Y, et al. The prognostic value of TMB and the relationship between TMB and immune infiltration in head and neck squamous cell carcinoma: A gene expression-based study. Oral Oncol. 2020;110:104943. Lee M, Samstein RM, Valero C, Chan TA, Morris LGT. Tumor mutational burden as a predictive biomarker for checkpoint inhibitor immunotherapy. Hum Vaccin Immunother. 2020;16(1):112–5. Klempner SJ, Fabrizio D, Bane S, et al. Tumor Mutational Burden as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors: A Review of Current Evidence. Oncologist. 2020;25(1):e147–59. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7. Robin X, Turck N, Hainard A, et al. pROC: an open-source package for R and S + to analyze and compare ROC curves. BMC Bioinformatics. 2011;12:77. Zhang Z, Gayle AA, Wang J, Zhang H, Cardinal-Fernandez P. Comparing baseline characteristics between groups: an introduction to the CBCgrps package. Ann Transl Med. 2017;5(24):484. Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018;28(11):1747–56. Weber R, Meister M, Muley T, et al. Pathways regulating the expression of the immunomodulatory protein glycodelin in non–small cell lung cancer. Int J Oncol. 2019;54(2):515–26. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394–424. Chan TA, Yarchoan M, Jaffee E, et al. Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic. Ann Oncol. 2019;30(1):44–56. Lang X, Green MD, Wang W, et al. Radiotherapy and Immunotherapy Promote Tumoral Lipid Oxidation and Ferroptosis via Synergistic Repression of SLC7A11. Cancer Discov. 2019;9(12):1673–85. Kamarainen M, Riittinen L, Seppala M, Palotie A, Andersson LC. Progesterone-associated endometrial protein–a constitutive marker of human erythroid precursors. Blood. 1994;84(2):467–73. Ren S, Chai L, Wang C, et al. Human malignant melanoma-derived progestagen-associated endometrial protein immunosuppresses T lymphocytes in vitro. PLoS ONE. 2015;10(3):e0119038. Schneider MA, Granzow M, Warth A, et al. Glycodelin: A New Biomarker with Immunomodulatory Functions in Non-Small Cell Lung Cancer. Clin Cancer Res. 2015;21(15):3529–40. Ho ML, Kuo WK, Chu LJ, et al. N-acetylgalactosamine-6-sulfatase (GALNS), Similar to Glycodelin, Is a Potential General Biomarker for Multiple Malignancies. Anticancer Res. 2019;39(11):6317–24. Cui J, Liu Y, Wang X. The Roles of Glycodelin in Cancer Development and Progression. Front Immunol. 2017;8:1685. Tong X, Tang R, Xiao M, et al. Targeting cell death pathways for cancer therapy: recent developments in necroptosis, pyroptosis, ferroptosis, and cuproptosis research. J Hematol Oncol. 2022;15(1):174. Peri S, Devarajan K, Yang DH, Knudson AG, Balachandran S. Meta-analysis identifies NF-kappaB as a therapeutic target in renal cancer. PLoS ONE. 2013;8(10):e76746. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4650268","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":333445693,"identity":"798de8fc-8e17-464d-b4b1-d101fd8d6eab","order_by":0,"name":"Jie Yang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Yang","suffix":""},{"id":333445694,"identity":"230a9b4a-8b25-4ba5-897b-b4912c04ac4b","order_by":1,"name":"Zhifei Che","email":"","orcid":"","institution":"The First Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhifei","middleName":"","lastName":"Che","suffix":""},{"id":333445695,"identity":"e9c47c76-ddfa-4d18-b856-afd38464bbaf","order_by":2,"name":"Shiying Zhou","email":"","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shiying","middleName":"","lastName":"Zhou","suffix":""},{"id":333445696,"identity":"d7037325-04ae-40f6-8872-1837a4223292","order_by":3,"name":"Zechun Peng","email":"","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zechun","middleName":"","lastName":"Peng","suffix":""},{"id":333445697,"identity":"e2ead4a4-dbc8-4743-b65d-b6ff2e8d3556","order_by":4,"name":"Fangzhen Cai","email":"","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fangzhen","middleName":"","lastName":"Cai","suffix":""},{"id":333445698,"identity":"8b4ad01c-8704-40c2-bcbb-b72028227e47","order_by":5,"name":"Shuming He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACAwYGNiAlwcDAzHz4wQcQg3gt7GxphjNI0AIE/DwK0jzEOMycvf3ZY94cizx5Zx4GY5s/Fnn8DcwPH93Ao8Wy54y5Me82iWLDw7wHHue2SRRLHGAzNs7B57AbOWzSQC2JG5v5EoxzGyQSGw7wsEnj1XL/+TOoFh4DaYs/EonzCWq5wWAG1jKfGaiFgU0icQNBLWdyzCTnArVsYAYGcm8b0LrDhPxy/Pgzibfb6hLn9x8+/ODHn7rEecebHz7GpwWh9wCMxUyMchCQbyBW5SgYBaNgFIw4AABPo0kGZUkiqwAAAABJRU5ErkJggg==","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":true,"prefix":"","firstName":"Shuming","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2024-06-27 16:52:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4650268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4650268/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62131861,"identity":"41190f96-925f-4e5e-b5d3-3b2237a64f61","added_by":"auto","created_at":"2024-08-09 15:44:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":853860,"visible":true,"origin":"","legend":"\u003cp\u003eLandscape of gene mutations in ccRCC. \u003cstrong\u003e(A)\u003c/strong\u003e Landscape of mutation profiles in ccRCC cases. \u003cstrong\u003e(i) \u003c/strong\u003esummary of the number of variant classifications: missense mutation, frame shift del, nonsense mutation, frame shift ins, splice site, nonstop mutation, translation start site, in frame del, in frame ins; \u003cstrong\u003e(ii) \u003c/strong\u003ecounting of variant types: SNP, INS, DEL.\u003cstrong\u003e(iii) \u003c/strong\u003esummary of base mutations: T\u0026gt;G, T\u0026gt;A, T\u0026gt;C, C\u0026gt;T, C\u0026gt;G and C\u0026gt;A. \u003cstrong\u003e(iv-v) \u003c/strong\u003eTMB in ccRCC tissues: variants per sample and variant classification; \u003cstrong\u003e(vi)\u003c/strong\u003etop 10 mutated genes. \u003cstrong\u003e(B) \u003c/strong\u003eThe waterfall showed the top 10 mutated genes in ccRCC. The legend above the waterfall showed the number of altered cases in ccRCC cohort. \u003cstrong\u003e(C) \u003c/strong\u003eA triangular matrix showed mutually co-occurring gene pairs in ccRCC. \u003cstrong\u003e(D) \u003c/strong\u003eFrequency of mutated genes in ccRCC using a word cloud.\u003c/p\u003e","description":"","filename":"Figure1431.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/193ddae1410d1e096dcdc9cd.png"},{"id":62132969,"identity":"66d41327-7008-4742-9969-8f5a94121007","added_by":"auto","created_at":"2024-08-09 15:52:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":126792,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between TMB status and clinical characteristics of ccRCC patients and prognostic value of TMB. \u003cstrong\u003e(A-G)\u003c/strong\u003e Lower of age and grade correlated with lower TMB level, while the gender, stage, M, N, T stage was not significant. \u003cstrong\u003e(H)\u003c/strong\u003e Kaplan–Meier analysis showing that higher TMB levels correlated with a poor prognosis in ccRCC patients (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). Red rectangle represents high TMB group and green rectangle represents low TMB group.\u003c/p\u003e","description":"","filename":"Figure1432.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/974e2068258f3682024e8cdd.png"},{"id":62131863,"identity":"8d5a4636-11e5-4868-bbbc-5450d5189e54","added_by":"auto","created_at":"2024-08-09 15:44:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":566570,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential gene expression analysis and enrichment analyses. \u003cstrong\u003e(A)\u003c/strong\u003e Heatmap of top 20 DEGs between high-and low-TMB groups. \u003cstrong\u003e(B)\u003c/strong\u003e Volcano plot of DEGs between high-and low-TMB groups. \u003cstrong\u003e(C-D)\u003c/strong\u003eGene ontology and KEGG pathway enrichment analysis. DEGs were mainly enriched in immune related and cell adhesion related pathways. DEGs, differentially expressed genes.\u003c/p\u003e","description":"","filename":"Figure1433.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/4990978bd21e105a8eb0cf59.png"},{"id":62131866,"identity":"d29cbee8-64f5-4fb4-a53a-fab39e0c3333","added_by":"auto","created_at":"2024-08-09 15:44:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":262819,"visible":true,"origin":"","legend":"\u003cp\u003eIdentifying TMB-related immune genes and relationship of TMB-related immune genes. \u003cstrong\u003e(A)\u003c/strong\u003e TMB-related immune genes were identified through the intersection of DEGs and immune related genes. \u003cstrong\u003e(B-C)\u003c/strong\u003e Box diagram and heatmap of the expression level of all TMB-related immune genes. Most TMB-related immune genes were overexpression in tumor tissues (T), compared to normal tissues (N). *** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003cstrong\u003e(D) \u003c/strong\u003eCorrelation matrix of TMB-related immune genes. PAEP and LCN1 had the highest correlation score (0.96). \u003cstrong\u003e(E)\u003c/strong\u003e Distribution of risk score, survival status among patients in TCGA.TMB, tumor mutation burden; DEGs, differentially expressed genes.\u003c/p\u003e","description":"","filename":"Figure1434.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/c6a4f6c6c13a827847f22277.png"},{"id":62131862,"identity":"1389f984-1a1d-40fa-bfe3-18c5d78cf599","added_by":"auto","created_at":"2024-08-09 15:44:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":173751,"visible":true,"origin":"","legend":"\u003cp\u003ePAEP expression in ccRCC cells and tissues and PAEP overexpression is associated with poor prognosis of ccRCC patients. \u003cstrong\u003e(A-B)\u003c/strong\u003eWestern blotting results and histogram analysis for the PAEP protein level in four ccRCC cell lines,769-P, 786-0, A498, ACHN. \u003cstrong\u003e(C-D)\u003c/strong\u003e Western blotting results showed that PAEP expression was significant reduction in 786-O cells transfected with shPAEP compared to that in 786-O cells transfected with sh Con. \u003cstrong\u003e(E) \u003c/strong\u003eTCGA data showed that PAEP is upregulated in ccRCC tissues relative (n=539) to non-tumorous tissues (n=72).\u003cstrong\u003e (F) \u003c/strong\u003eRT-PCR analysis showed the expression of PAEP in human ccRCC tissues and normal adjacent tissues . \u003cstrong\u003e(G-H) \u003c/strong\u003eWestern blotting results and histogram analysis for the relative level of PAEP in 786-0 cells was significantly higher than that in HK2 cells. \u003cstrong\u003e(I-J) \u003c/strong\u003eccRCC patients from the TCGA data were divided into low (n=269) and high PAEP expression groups (n=270). \u003cstrong\u003e(K) \u003c/strong\u003eIn our cohort, the Kaplan-Meier curves showed that the ccRCC patients with high PAEP expression had shorter OS, using the median expression of PAEP as cutoff value. \u003cstrong\u003e(L) \u003c/strong\u003eThe diagnostic value of PAEP for the ccRCC patients. \u003cstrong\u003e(M)\u003c/strong\u003e GSEA showed the PAEP-related pathway, including MAPK Signaling Pathway, Renal Cell Carcinoma, TGF β Signaling Pathway, Ubiquitin Mediated Proteolysis, Wnt Signaling Pathway. The experiments were independently repeated with three times (*\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"Figure1435.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/c893524cbc99c8c32d082dfb.png"},{"id":62132970,"identity":"f5e00046-13e4-4176-85f7-a7e331bdb607","added_by":"auto","created_at":"2024-08-09 15:52:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1012820,"visible":true,"origin":"","legend":"\u003cp\u003ePAEP knockdown inhibited the activation of PI3K/Akt/NF-κB signaling pathway and inhibited cell growth. \u003cstrong\u003e(A) \u003c/strong\u003eCCK-8 was used to determine how PAEP knockdown affected the viability of 786-O cells. \u003cstrong\u003e(B-C)\u003c/strong\u003e Flow cytometry was used to determine how PAEP knockdown affected 786-O cells apoptosis. \u003cstrong\u003e(D-F) \u003c/strong\u003eTranswell was able to identify the impact of PAEP knockdown on 786-O cell migration and invasion. \u003cstrong\u003e(G-H) \u003c/strong\u003eThe effect of PAEP knockdown on the proliferation of 786-O cells was detected by cell cloning experiment. (I-K) Western blotting results and histogram analysis showed the changed protein levels involved in the PI3k-Akt-NF-κB pathway after PAEP knockdown in 786-0 cells. All experiments were independently repeated with three times (*\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). shRNA, short hairpin RNA.\u003c/p\u003e","description":"","filename":"Figure1436.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/b3d9cb24298eac08aa418afe.png"},{"id":62131865,"identity":"8eb0ad73-f271-4fcc-abc4-d449ced293ad","added_by":"auto","created_at":"2024-08-09 15:44:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":666189,"visible":true,"origin":"","legend":"\u003cp\u003ePAEP knockdown inhibited tumor formation in nude mice. (A-B) Western blotting was used to detect the changes of PAEP protein in transplanted tumor tissues. (C) The tumor was formed in nude mice in vitro, and the subcutaneous tumor was isolated after 15 days of feeding (n=6). (D-F) Changes in the volume and weight of the transplanted tumor. (**\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"Figure1437.png","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/6ceacaf2fd74d0ae191df600.png"},{"id":67388678,"identity":"0ab49612-43b5-44bf-bd7e-910d8cb27d60","added_by":"auto","created_at":"2024-10-24 10:38:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4477643,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4650268/v1/c172f32b-5478-4729-8929-15cdf7d8a2c1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Significance of Tumor Mutation Burden related immune gene PAEP in the progression and prognosis of clear cell renal cell carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRenal cell carcinoma (RCC) is the most common genitourinary malignancy. As the most common type of RCC, Clear cell renal cell carcinoma (ccRCC) accounts for 75\u0026thinsp;~\u0026thinsp;80% of all RCC cases \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Recently, surgery and targeted therapy are the most common and effective clinical treatments for ccRCC patients \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, its overall mortality rates are still slightly increased, partly due to early-stage metastasis of the disease \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Therefore, some novel markers for early diagnostic and therapeutic targets involved in ccRCC progression are urgently required with significant clinical value.\u003c/p\u003e \u003cp\u003eIn recent years, antibody immunotherapy represents a promising therapy for the clinical treatment of ccRCC patents, successfully developed and widely applied \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. For example, Immune checkpoint inhibitors (ICI) such as PD-1/PD-L1 inhibitors develop as a potential clinical strategy for ccRCC \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. However, ccRCC patients sometimes show low objective response rates against ICI \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Tumor mutation burden (TMB) is defined as a total number of somatic coding mutations in the exon coding region of the genome of a tumor cell. TMB is a potential biomarker for predicting ICI response in varying tumors \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. TMB was first identified as a potential biomarker for treatment with ICI in melanoma in 2014 \u003csup\u003e11\u003c/sup\u003e. Since then, TMB has been considered to be related to the therapeutic effect of immune checkpoint inhibitors and has become a key predictor of the efficacy of immunotherapy for some malignant tumors \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. In addition, studies have shown that high TMB levels are associated with better prognosis in patients with many malignant tumors, such as non-small cell lung cancer and endometrial cancer \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. A study in advanced cancer patients not treated with ICI reported no correlation between high TMB and better prognosis \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, many studies have shown that high levels of TMB are associated with poor prognosis in patients with thyroid cancer \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, head and neck squamous cell carcinoma \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e and intrahepatic cholangiocarcinoma \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. At present, whether the level of TMB is related to the prognosis of patients with malignant tumors is still controversial. The connection between TMB and immune infiltration was deviated from varied tumors \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Nevertheless, limited studies on TMB-related immune genes in ccRCC, so we tried to research the potential relationship between TMB and ccRCC.\u003c/p\u003e \u003cp\u003eIn this study, based on the TCGA-ccRCC cohort, we summarized the current status of gene mutations in ccRCC. The relationship between TMB and clinical features was then analyzed. Meanwhile, we identified some TMB-related immune genes by cross-validation of TMB-related differentially expressed genes (DEGs) and immune-related genes, and found that gene Progestagen‑associated endometrial protein (PAEP) was closely related to the prognosis of ccRCC. Finally, through clinical data and in vitro experiments, we further confirmed that gene PAEP promoted the malignant progression of ccRCC, which may be related to the PI3K/Akt/NF-κB signaling pathway.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and mutation analysis\u003c/h2\u003e \u003cp\u003eThe data of ccRCC patients, including \u0026ldquo;mask somatic mutation\u0026rdquo;, transcriptome profiles and clinical data, was obtained from the the Cancer Genome Atlas (TCGA ) database on November 08,2020. At the same time, we used the Mutect algorithm to processed \u0026ldquo;mask somatic mutation\u0026rdquo; data and visualized the results using the \u0026ldquo;maftoools\u0026rdquo; R package. Then, we categorized the ccRCC patients into high-TMB group and low-TMB group according to the median value of TMB. To analyze the correlation between TMB status and several clinicopathological characteristics, we analyzed the significance. We also analyzed the difference of overall survival (OS) between the high-TMB group and low-TMB group using Kaplan-Meier statistics. To evaluate the diagnostic value of TMB-related immune genes in ccRCC, we performed Receiver Operating Characteristic (ROC) curves and calculated the area under the ROC curve (AUC) to assess the diagnostic efficiency.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTMB-Related differentially expressed genes and functional enrichment analysis\u003c/h2\u003e \u003cp\u003eTo understand the TMB-Related function, we used the R package \u0026ldquo;limma v3.38.3\u0026rdquo; to perform TMB-Related differentially expressed genes (DEGs) between the above two TMB subgroup with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |logFC| \u0026gt; 1.0. Meanwhile, we visualized the DEGs with volcanic plot and heatmap. Nevertheless, Gene Ontology (GO) categories and Kyoto Encyclopedia of Genes and Genomes (KEGG) were identified using R package \u0026ldquo;clusterProfiler, org.Hs.eg.db, enrichplot\u0026rdquo; to identify the functional enrichment and pathway enrichment of all DEGs \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. All above results were visualized by R package \u0026ldquo;ggplot2, heatmap, ggpubr, ggthemes\u0026rdquo;.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eIdentification and Coexpression analysis of TMB-related immune genes\u003c/h2\u003e \u003cp\u003eOn the other hand, we obtained a list of immune related genes (IRG) from the Immport data (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.immport.org\u003c/span\u003e\u003cspan address=\"https://www.immport.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), then we defined the common genes as TMB-related immune genes between immune related genes and DEGs using R package \u0026ldquo;ggplot2\u0026rdquo;. Finally, we performed the expression, correlation, and risk score distribution, survival status of the TMB-related immune genes among patients based on the expression of these genes using R package \u0026ldquo;corrplot, ggplot2, heapmap\u0026rdquo;. Finally, we selected the highest correction and novel gene for the future analysis, including expression analysis, Gene Set Enrichment Analysis (GSEA), OS, ROC and clinical correlation with GSEA project (4.0.3) and R package \u0026ldquo;pROC, ggplot2, CBCgrps\u0026rdquo; \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and and treatment\u003c/h2\u003e \u003cp\u003eThe human ccRCC cell line,769-P, 786-0, A498 and ACHN, was purchased from ASY Biotechnology Ltd., Corp (Wuhan, China). All cells were cultured in 89% RoswellParkMemorialInstitute (RPMI) 1640 medium (Life Technologies, Gibco, USA, 11875119) supplemented with 10% fetal bovine serum(FBS)(Life Technologies, Gibco, USA,) A5670701 and 1% penicillin\u0026ndash;streptomycin (Life Technologies, Gibco, USA, 15140122) unless stated otherwise. The cells were incubated at 37\u0026deg;C in a humidified incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e. They were thereafter subjected to growing until 85%\u0026ndash; 95% confluency in the culture flask, trypsinized, and harvested for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eShort hairpin RNA construction and cell transfection\u003c/h2\u003e \u003cp\u003ePAEP short hairpin ribonucleic acid (shRNA) expressing lentivirus was obtained from GeneChem Co., Ltd. (Shanghai, China) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genechem.com.cn\u003c/span\u003e\u003cspan address=\"https://www.genechem.com.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Transfection conditions were reference to our previous paper. Briefly, the short hairpin RNA (shRNA) target sequence was shPAEP1, 5'-AAGATCAACTATACGGTGG-3', shPAEP2, 5'-AAGAGCCGTGCCGTTTCTA-3'. Conforming to the manufacturer's guidance, the 786-0 cells were transfected with shRNA non-sense control (shRNA-Con group) or with PAEP shRNA (shRNA-PAEP group) using lentiviral particles at a MOI (100:1) of 100 pfu/cell in the presence of polybrene (Yeasen, Shanghai, China, 40804ES86). In order to acquire PAEP knockdown cell lines, the transfected cells were treated with 5 mg/mL of puromycin (Yeasen, Shanghai, China, 60209ES10). Then, the resistant colonies were collected and cultivated for further analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection and preparation of tissue\u003c/h2\u003e \u003cp\u003e36 patients who were diagnosed as ccRCC at the Second Affiliated Hospital of Hainan Medical University were enrolled in our study. More detailed information of the patents is previous described. The ccRCC and their paired-normal tissues were snap-frozen immediately after removal and stored at \u0026minus;\u0026thinsp;80\u003csup\u003e◦\u003c/sup\u003eC. During every stage of our experiments, we adhered to the guidelines outlined in the Code of Ethics of the World Medical Association. The Ethics Committee of Hainan Medical University conducted a review of our research and granted approval(2024-KCSN-13). After receiving sufficient information, all participants enrolled in this study provided their written consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eWestern blotting\u003c/h2\u003e \u003cp\u003eLysis of the cells was done with RIPA buffer (Beyotime Biotechnology, China, P0013B), protease inhibitor cocktail (Roche, Switzerland, P8215), and phenylmethylsulfonyl fluoride (Beyotime Biotechnology, China, ST507-10mL, China, P0011) in a ratio of volume 100:4:1 for 30 min on ice. A bicinchoninic acid protein assay kit (Beyotime Biotechnology, China, P0011) was utilized to accurately measure the protein concentration. In addition, 30\u0026micro;g protein was isolated on 15% or 10% sodium dodecyl sulfate\u0026ndash;polyacrylamide gel electrophoresis (SDS-PAGE) gel (Biotechwell, China) and transferred onto the polyvinylidene difluoride (PVDF) membrane (# IPFL00010; Millipore, USA). After that, blocking of the PVDF membranes was done using 5% skimmed milk (# 232100; BD Biosciences, USA) for 3 h. The membranes were then incubated throughout the night at 4\u0026deg;C with primary antibodies: anti- PAEP (Abcam, UK, #ab270454, #1:1000), anti-p-PI3K (Abcam, UK, ab278545, #1:1000), anti-PI3K (Abcam, UK, ab302958, #1:1000), anti-AKT (Abcam, UK, ab8805, 1:500), anti-p-AKT (Abcam, UK, ab192623, 1:1000), anti-p-p65 (CST, USA, #3033, 1:1000), anti-p65 (CST, USA, #8242, 1:500), anti-p-IκBα (CST, USA, #2859, 1:1000), anti-IκBα (CST, USA, #9242, 1:1000), and anti-β-Actin (Abcam, UK, ab8226, 1:3000).Afterward, the fluorescent secondary antibodies were utilized for sample incubation in the darkness for 2 h. The Odyssey infrared imaging equipment (LI-COR Biosciences, USA) was utilized to scan and develop the membranes. The grayscale value of the experiment was analyzed with the aid of the ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eqPCR\u003c/h2\u003e \u003cp\u003eAccording to the manufacturer\u0026rsquo;s instructions, total RNA from the ccRCC and their paired-normal tissues was extracted using the Trizol reagent (Invitrogen, Carlsbad, CA, USA, 15596026CN). The concentration of the RNA was determined using ultraviolet spectrophotometry. The cDNA was synthesized using a PrimeScript RT Reagent Kit (Takara, Shiga, Japan, RR047A). Quantitative real-time PCR analysis for PAEP mRNA levels was performed using a TB Green\u0026reg; \u003cem\u003ePremix Ex Taq\u003c/em\u003e\u0026trade; II FAST qPCR (Takara, Shiga, Japan, CN830S) through an Applied Biosystems 7500 Real-Time PCR System(Thermo Fisher Scientific, Inc., USA). Relative mRNA expression levels were calculated using the relative Ct method, and the fold change compared with β-actin (Sangon Biotech, Shanghai, China) as the control. The primer sequences were as follows: PAEP: Forward:5-CCTGTTTCTCTGCCTACAGGA-3, Reverse:5-CCTGTTTCTCTGCCTACAGGA-3;\u003c/p\u003e \u003cp\u003eβ-Actin: Forward:5-GTCCACCGCAAATGCTTCTA-3, Reverse:5-TGCTGTCACCTTCACCGTTC-3.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCell Counting Kit‑8 (CCK‑8) assay\u003c/h2\u003e \u003cp\u003eThe density of 786-O cells was adjusted to 1 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e cells /mL, 100\u0026micro;L was added to each well in the 96-well culture plate, and cultured in an incubator with 5% CO\u003csub\u003e2\u003c/sub\u003e and 37℃. The cell Optical Density was measured at 450 nm using the Spark\u0026trade;10 M microplate reader (Tecan Group, Ltd.) at 0h, 24h, 48h, and 72h according to the CCK-8 kit (Beyotime Biotechnology, China, C0038) operating manual, and cell growth curves were plotted.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFlow cytometry\u003c/h2\u003e \u003cp\u003e786-O cells were inoculated on a 6-well plate 48 hours later, cell suspension was collected, 1000g, centrifuged at 4℃ for 5min, cells were collected and counted with precooled PBS, 5\u0026ndash;10\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were taken, centrifuged at 1000g for 5min, and supernant was discarded. According to the Annexin V-FITC Apoptosis Detection Kit manufacturer's instructions (Beyotime Biotechnology, China, C1062S), Annexin V-FITC binding solution 195\u0026micro;L Annexin V-FITC was added, the cells were lightly suspended, 5\u0026micro;L Annexin V-FITC was added, the cells were lightly mixed, 10\u0026micro;L propyl iodide staining solution was added, the cells were gently mixed, and incubation was performed at room temperature for 10\u0026ndash;20 min, the cells were re-suspended for 2\u0026ndash;3 times to improve the staining effect, and then placed in an ice bath away from light. Finally on the machine detection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eCell proliferation, migration and invasion assays\u003c/h2\u003e \u003cp\u003eThe colony formation test was conducted to examine the impact of PAEP expression knockdown on the growth potential of 786-O cells. In addition, 700 cells/well (786-O cells transfected with the sh-Con and sh-PAEP) were seeded in 6-well plates, correspondingly, and were treated after 14 days. Then, the cells were fixed in 75% alcohol for 30 min and stained with 0.5% crystal violet (Yeasen, Shanghai, China, 60506ES60) for 30 min. The cell colonies were calculated using Image J software. Three replicates of each experiment were carried out, and the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) was calculated.\u003c/p\u003e \u003cp\u003e24-well Transwell plates (cat. no. 3422, Corning, USA) with or without Matrigel matrix (cat. no. 356234, BD Biosciences, USA) were used for migration assay and invasion assay. The upper chambers and the lower chambers were seeded 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells in 200 \u0026micro;l without FBS RPMI 1640 medium and added 600 \u0026micro;l of RPMI 1640 containing 20% FBS, respectively. Subsequently, cells that migrated or invaded through the bottom of chambers were fixed with 4% paraformaldehyde, and then stained with 0.5% crystal violet for 30 min. Finally, the image was captured under a microscope. To measure the invasive and migratory capability of cells, we enumerated cells invading the Matrigel using ImageJ.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eTumor formation in nude mice\u003c/h2\u003e \u003cp\u003eBALB/c female nude mice, 5 to 6 weeks old, purchased from Hunan SJA Laboratory Animal Co., Ltd. (production license No. SCXK [Hunan] 2019-0014), kept at 22˚C, Humidity 50%, light/dark cycle 12 h environment, free to eat and drink. All animal experiments were approved by the Ethics Committee of XX University.\u003c/p\u003e \u003cp\u003eThe nude mice were randomly divided into 3 groups, Ctrl group, shCon group and shPEAP group, with 6 mice in each group. Ctrl group: Logarithmic growth of 786-O cells was implanted in the back of nude mice. shCon group: 786-O cells were transfected with negative control sh-NC, and logarithmic growth cells were implanted in the back of nude mice. shPEAP group: 786-O cells were transfected with lentivirus shPEAP, and logarithmic growth cells were implanted in the back of nude mice. The tumor volume was measured every 2\u0026ndash;3 days. 15 days after inoculation, the nude mice were euthanized for cervical dislocation, and the tumors were photographed, measured, weighed, and WB detected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe selected the TMB-Related DEGs with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |logFC| \u0026gt; 1.0 to further assess. The KM analysis and log-rank test were used to assess OS in the ccRCC cohort. The Chi-square test was used to assess correlation between PAEP expression and clinicopathologic characteristics of ccRCC patients. All experiments were performed with at least three independent biological replicates. The data are expressed as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SDs). We employed R (version 4.3.1), SPSS (version 25.0; IBM, USA), and GraphPad Prism (version 7; GraphPad Software, USA) for all statistical analyses. Two-tailed t -tests and one-way analysis of variance (ANOVA) were used to analyze cell culture experiments. The criterion for statistical significance was set 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\u003eMutation analysis\u003c/h2\u003e \u003cp\u003eSomatic mutation profiles of \u003cb\u003e537\u003c/b\u003e ccRCC patients downloaded from TCGA database were analyzed and visualized using R package \u0026ldquo;maftools\u0026rdquo; \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. A waterfall plot was performed to exhibit the detailed mutation information in each sample. The majority of Variant Classification, Variant Type, single nucleotide variants (SNV) Class were missense mutations, single nucleotide polymorphism (SNP), C\u0026thinsp;\u0026gt;\u0026thinsp;T, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA i-iii). Counting each sample separately, the median and maximum of mutations in the TCGA-ccRCC cohort were 47 and 1611, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA iv and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In addition, we exhibited the number of each variant classification in the different sample using box plots (Figure.1A v). The top 10 mutated genes in the 336 ccRCC patients were VHL (49%), PBRM1 (42%), TTN (18%), SETD2 (12%), BAP1 (10%), MUC16 (7%), MTOR (7%), KDM5C (6%), HMCN1 (5%), DNAH9 (5%) (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA vi, 1B and 1D), while the PBRM1 and VHL have the highest correlation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation of TMB with prognosis and clinical features\u003c/h2\u003e \u003cp\u003eAfter the clinical data of ccRCC patients were collected from TCGA, we selected 336 patients with complete information. Based on the median TMB value (1.29), we divided 336 patients into high-and low-TMB groups (n\u0026thinsp;=\u0026thinsp;163 VS n\u0026thinsp;=\u0026thinsp;173). As showed in the Kaplan-Meier curve, the high-TMB group had significantly poor OS outcomes (P\u0026thinsp;=\u0026thinsp;0.007) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eH). Besides, the correlation of TMB with clinical features showed that only age and grade were significantly associated with TMB (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), the other clinical characteristics showed no significantly difference (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTMB-Related differentially expressed genes and Functional enrichment analysis\u003c/h2\u003e \u003cp\u003eAccording to the DEGs expression analysis between high-TMB group and low-TMB group, a total of 120 DEGs with |log\u003csub\u003e2\u003c/sub\u003eFC|\u0026gt; 1 and FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was identified. There are 44 up-regulated genes and 76 down-regulated genes in the high-TMB group, compared to the low-TMB group. The heatmap and volcano plot showed the top 40 DEGs ranked in the order of FDR and all DEGs, respectively (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). According to GO and KEGG analysis, DEGs were enriched in the function enrichment of apical part of cell, apical plasma membrane, axon terminus and the pathway of Calcium signaling pathway, Vibrio cholerae infection and Taurine and hypotaurine metabolism (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eComparison of gene expression profiles between two tmb groups\u003c/h2\u003e \u003cp\u003eWe further identified the TMB-related immune genes through the intersection of 1793 immune related genes and 120 DEGs for subsequent analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Then, we selected 8 TMB-related immune genes including CRP, IGHA2, IGLC3, IL6, LBP, LCN1, PAEP, SLIT2. We extracted the mRNA expression of each TMB-related immune genes to draw the box plot, heatmap and correlation heatmap (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). The results revealed that IGHA2, IGLC3, PAEP were increased, while CRP, LCN1 and SLIT2 decreased, IL-6 and LBP resting in ccRCC tissues, compared to the normal tissues (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Importantly, PAEP and LCN1 had the highest correlation score (0.96) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).in addition, the ccRCC patents with higher risk scores, composing by these genes, had poor outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). Finally, we selected the PAEP which is a never reported gene in ccRCC for the further research.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003ePAEP was overexpression and associated with shorter survival in ccRCC patents\u003c/h2\u003e \u003cp\u003eConsidering PAEP overexpression in ccRCC, we further investigated whether it contributed to ccRCC progression. Thus, we chose the 786-0 cells which had the highest levels of PAEP for further investigation (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). 786-0 cells were transfected with short hairpin RNAs (shRNAs) targeting to PAEP, which significantly silenced the PAEP expression (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). PAEP was significantly overexpressed in the TCGA-ccRCC cohort, compared to the normal group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE), which was further validated in ccRCC tissues and ccRCC cells by RT-qPCR and Western blot analysis (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH). Moreover, analysis of clinical characteristics indicated that PAEP overexpression was significantly correlated with Primary tumor size, TNM stage and Fuhrman grade (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Importantly, Kaplan-Meier analysis revealed that ccRCC patients with high PAEP expression had poor OS and disease-free survival (DFS )in the TCGA cohorts and further confirmed in our cohort (without DFS result) (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eI-\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eK), indicating that PAEP upregulation was potentially related to the ccRCC progression. To evaluate the diagnostic value of PAEP in ccRCC, we constructed ROC curve and calculated the AUC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eL). The ROC curve of PAEP indicated it was a medium diagnostic tool with an AUC is 0.764. We performed GSEA to reveal potential molecular mechanism of PAEP regulating the progression of ccRCC. The results showed that all the significant pathways were enrichment in the PAEP overexpression group related to various tumorigenesis-related characteristics, containing MAPK signaling pathway, Renal Cell Carcinoma, TGF-β signaling pathway, ubiquitin mediated proteolysis and Wnt signaling pathway, etc (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eM). These results provide new clues for exploring the molecular mechanism of ccRCC in the future. In conclusion, PAEP serves as an important oncogene and is associated with a poor clinical outcome of ccRCC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between PAEP expression and clinicopathologic characteristics of ccRCC patients\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePAEP expression level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep -value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;65 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;65 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary tumor size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;7 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;7 cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003epT stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.691\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epT1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epT3-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTNM stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u0026thinsp;+\u0026thinsp;II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u0026thinsp;+\u0026thinsp;IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFuhrman grade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026thinsp;+\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: N for number of cases, T for tumor stage, TNM for tumor node and distant metastasis. \u003csup\u003ea\u003c/sup\u003e for Chi-square test, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePAEP knockdown inhibited ccRCC cells growth\u003c/h2\u003e \u003cp\u003eFirst of all, CCK-8 results showed that compared with the Blank group, the cell viability of sh-Con group had no significant change, while the cell viability of sh-PEAP group was significantly reduced (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). The results of flow cytometry showed that compared with the Blank group, the apoptosis of sh-Con group was not obvious, and the apoptosis of sh-PEAP group was significantly increased (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Then, we performed the transwell assays and colony formation assays to evaluate invasion, migration and proliferation in response to PAEP knockdown in 786-0 cells. Transwell assays showed that PAEP knockdown remarkably reduced cell invasion and migration in 786-0 cells, compared to Blank groups and shCon groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD \u0026minus;\u0026thinsp;6F), Meanwhile, colony formation assays revealed that PAEP knockdown significantly reduced cell colonies in 786-0 cells compared with Blank groups and shCon groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eG and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese results showed that PAEP knockdown inhibited ccRCC cells growth. Taken together, our results suggested that PAEP promoted the progression of ccRCC.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003ePAEP induces activation of the PI3K/Akt/NF-κB pathway\u003c/h2\u003e \u003cp\u003ePrevious studies showed that PAEP contributed to the activation of the PI3K/Akt/NF-κB signaling pathway \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. It could be inferred that PAEP played an important role in the activation of the PI3K/Akt/NF-κB signaling pathway. Therefore, we performed western blotting assays to assess changed genes involved in the PI3K/Akt/NF-κB signaling pathway in 786-0 cells. The results shown that PAEP knockdown inhibited PI3K/Akt/NF-κB activation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eK).\u003c/p\u003e \u003cp\u003e \u003cb\u003ePAEP knockdown inhibited tumor formation in nude mice.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe further studied the effect of PEAP knockdown on subcutaneous tumor formation in nude mice in vivo, and the results showed that we first successfully constructed a subcutaneous tumor transplantation model in nude mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). Western blotting study results showed that compared with Ctrl group, there was no significant change in the expression of PEAP protein in shCon group, while the expression of PEAP protein in shPEAP group was significantly reduced (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). At the same time, we also found that compared with the Ctrl group, the weight and volume of transplanted tumors in the shCon group did not change much, while the weight and volume of transplanted tumors in the shPEAP group significantly decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE-\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn recent years, the incidence of RCC has continued to rise, affecting more than 400,000 people worldwide every year \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, causing a huge burden on global public health. Of all the renal cell subtypes, ccRCC is the most common, accounting for about 70\u0026ndash;80% \u003csup\u003e1,2\u003c/sup\u003e. Current clear cell renal cell carcinoma patients have high metastasis, incremental recurrence, and low response rate to immune checkpoint therapy \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. As a new treatment strategy to predict immune responses, TMB had been exhibited their effect in a variety of tumor types \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, the underlying mechanism of how TMB-related immune genes regulate the occurrence and metastasis of ccRCC remains unclear.\u003c/p\u003e \u003cp\u003eIn our study, we explored the status of TMB in ccRCC. The landscape of mutation profiles in TCGA-ccRCC cohort showed that 88.1% of patients develop varied types of mutation. The majority of Variant Classification, Variant Type, SNV Class were missense mutations, SNP, C\u0026thinsp;\u0026gt;\u0026thinsp;T, respectively. For the correlations between TMB and clinicopathological characteristics, the higher TMB level correlated with higher age, higher AJCC-T, grade and stage. Meanwhile, ccRCC patents with higher TMB have shorter OS. These results were in accordance with previous study \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFurther, we identified some TMB-related immune genes through the intersection of DEGs and immune related genes, in which PAEP and LCN1 had the highest correlation. Finally, we selected the PAEP gene for the further research, which is a never reported gene in ccRCC. PAEP was overexpressed in approximately 80% of all tumors compared to normal tissue. PAEP was initially described as an immune system modulator in reproduction \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Knockdown of PAEP resulted in a deregulation of immune system modulators, such as PD-L1 \u003csup\u003e28,29\u003c/sup\u003e. In this study, we confirmed that PAEP was overexpressed in a cohort of 36 ccRCC patients and PAEP overexpression was closely correlated with Primary tumor size, TNM stage and Fuhrman grade. This expression pattern is similarly with the other cancers \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Further, PAEP is useful for determining prognosis of ccRCC and also can be severed as a potential diagnostic biomarker. PAEP knockdown significantly inhibited the proliferation, migration and invasion of ccRCC. Our research is consistent with the function of PAEP in other cancer \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The abnormality of apoptosis plays a crucial role in the occurrence of tumor. For a long time, apoptosis has been considered as an important mechanism to prevent the occurrence of tumor, and one of the characteristics of tumor cells is to inhibit apoptosis\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. In this study, we observed that PEAP knockdown promotes apoptosis of ccRCC cells, suggesting that PEAP may be an important target for the treatment of ccRCC. Mechanistically, PAEP knockdown decreased PI3K/Akt/NF-κB signaling pathway in ccRCC. Suraj Peri have found that the NF-κB signaling pathway is constitutively active in a high percentage of ccRCC cases \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Nonetheless, we found that knock down PAEP could efficiently depressed the activation of PI3K/Akt/NF-κB pathway, suggesting that PAEP maybe a potential target for this incurable malignancy. In addition, in vivo studies, we found that knocking down PEAP significantly reduced the expression of PEAP protein in transplanted tumor tissue, inhibited the formation of transplanted tumor, and reduced the size and weight of transplanted tumor tissue. These results suggest that low PEAP expression may inhibit the further development of ccRCC.\u003c/p\u003e \u003cp\u003eThere are some shortcomings in this study. First of all, we only studied the gene mutation status of ccRCC based on the TCGA database and analyzed the relationship between clinical characteristics of TMB, and the results were biased to some extent. Secondly, we identified PAEP gene, which is a new TMB related ccRCC immune gene, and only made preliminary identification through ccRCC tissue. However, the amount of data is still too small and persuasive, and more clinical experiments are needed to further confirm it. Finally, due to the limitation of funds and time, we have not conducted rescue experiments to verify whether the regulatory effect of PEAP is played by the PI3K/Akt signaling pathway, and we plan to conduct in-depth research on this in the follow-up studies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, our study showed that overexpression of PAEP promotes ccRCC malignant progression may relate to the PI3K/Akt/NF-κB signaling pathway. Understanding the important role of PAEP in ccRCC would widen our knowledge of the biological basis of ccRCC progression and might represents a potential target of antibody immunotherapy for ccRCC patients.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eTMB Tumor mutation burden\u003c/p\u003e \u003cp\u003eccRCC Clear cell renal cell carcinoma\u003c/p\u003e \u003cp\u003ePAEP Progesterone associated endometrial protein\u003c/p\u003e \u003cp\u003eICI Immune checkpoint inhibitors\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Hainan Provincial Natural Science Foundation of China (ZDYF2024SHFZ122, 822NQ472, 820MS142).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJie Yang, Zhifei Che, Shiying Zhou, Zechun Peng, Fangzhen Cai and Shuming He performed the bioinformatics analysis, drafted the manuscript and prepared the figures. Jie Yang and Zhifei Che collected the clinical data and experiments. Shuming He and Jie Yang design the study. Jie Yang, Zhifei Che and Shuming He collected the related references and participated in discussion. All authors contributed to this manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are available from the corresponding author upon reasonable request. The datasets analyzed during the current study are available in the TCGA and Immport databases. [https://portal.gdc.cancer.gov/,https://www.immport.org/home].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Central Laboratory of Hainan Medical University, where most of this work was performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments were carried out in accordance with the Code of Ethics of the World Medical Association. The Ethics Committee of Hainan Medical University conducted a review of our research and granted approval(2024-KCSN-13).\u0026nbsp;All the human subjects gave their informed consent for the use of their samples and data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHora M, Albiges L, Bedke J, European Association of Urology Guidelines Panel on Renal Cell Carcinoma Update on the New World Health Organization Classification of Kidney Tumours 2022, et al. The Urologist's Point of View. Eur Urol. 2023;83(2):97\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRasti A, Abolhasani M, Zanjani LS, Asgari M, Mehrazma M, Madjd Z. 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PLoS ONE. 2013;8(10):e76746.\u003c/span\u003e\u003c/li\u003e\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":"Progesterone associated endometrial protein, Tumor mutation burden, Immunotherapy, Clear cell renal cell carcinoma","lastPublishedDoi":"10.21203/rs.3.rs-4650268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4650268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eClear cell renal cell carcinoma (ccRCC) is a common renal malignant disease with a poor prognosis. Tumor mutation load (TMB) has received much attention in various tumor studies, however, there were limited studies focus on the relationship between TMB and ccRCC. We aimed to investigate the role of TMB-related immune gene progestagen‑associated endometrial protein (PEAP) in ccRCC and the underlying molecular mechanisms.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSomatic mutation data of 336 patients with ccRCC were downloaded from the Cancer Genome Atlas (TCGA) database, and the mutational spectrum was analyzed using the \"maftools\" software package. Based on TCGA -ccRCC cohort, we summarized the status of gene mutations in ccRCC. The TMB was calculated and the samples were divided into high and low TMB groups. Then, we analyzed the relationship between TMB and clinical characteristic. Meanwhile, we identified some TMB-related immune genes through the intersection of TMB-Related differentially expressed genes (DEGs) and immune related genes. Finally, We selected the immune genes most associated with TMB, investigated its expression in renal tissues of ccRCC patients, and further investigated its role and potential molecular mechanisms \u003cem\u003eIn-vivo and in-vitro\u003c/em\u003e.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eUsing bioinformatics we analyzed the most common mutation of Variant Classification, Variant Type, single nucleotide variants (SNV) Class for missense mutations, single nucleotide polymorphism (SNP) and C\u0026thinsp;\u0026gt;\u0026thinsp;T in ccRCC, respectively. we found that higher TMB related to shorter overall survival (OS), lower age and grade. Finally, we identified progesterone associated endometrial protein (PAEP) gene, a novel TMB-related immune gene in ccRCC, which was significantly overexpression in ccRCC tissues and cells with progression and poor survival in ccRCC patients. Furthermore, by constructing 786-O cell model, our results showed that PAEP promoted the invasion, migration, and proliferation of ccRCC cells; meanwhile, PAEP knockdown suppressed the PI3K/Akt/NF-κB signaling pathway. In-\u003cem\u003evivo\u003c/em\u003e studies, we found that after knocking out the PEAP gene, the subcutaneous transplanted tumors in nude mice were smaller and lighter. Mechanistically, we consider that PAEP may regulate the malignant biological phenotype and poor survival prognosis of ccRCC through the PI3K/Akt/NF-κB signaling pathway.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study suggests that PAEP might represents a potential target of antibody immunotherapy for ccRCC patients and also provides a strong theoretical basis for the clinical application of PAEP.\u003c/p\u003e","manuscriptTitle":"Significance of Tumor Mutation Burden related immune gene PAEP in the progression and prognosis of clear cell renal cell carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-09 15:44:38","doi":"10.21203/rs.3.rs-4650268/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":"72180539-e78c-434f-949b-a54a09ea7f4a","owner":[],"postedDate":"August 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-07T10:23:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-09 15:44:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4650268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4650268","identity":"rs-4650268","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}