Human pan-cancer analysis of the predictive biomarker for the CDKN3

Human pan-cancer analysis of the predictive biomarker for the CDKN3 | 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 Human pan-cancer analysis of the predictive biomarker for the CDKN3 Yingjun Chen, Dai Li, Kaihui Sha, Xuezhong Zhang, Tonggang Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4071308/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 May, 2024 Read the published version in European Journal of Medical Research → Version 1 posted 8 You are reading this latest preprint version Abstract BACKGROUND Cell cycle protein-dependent kinase inhibitor protein 3 (CDKN3) is a member of the protein kinase family and has been shown to be oncogenic in several tumors. However, there are no pan-carcinogenic analyses for CDKN3. METHODS Using bioinformatics tools such as The Cancer Genome Atlas (TCGA) and the UCSC Xena database, we performed a pan-cancer analysis of CDKN3. We investigated the function of CDKN3 in 33 different kinds of tumor. And we explored the gene expression, survival prognosis status, clinical significance,DNA methylation, immune infiltration, and associated signal pathways of CDKN3. RESULTS CDKN3 was significantly upregulated in most of tumors and correlated with overall survival (OS) of patients. Methylation levels of CDKN3 differed significantly between tumors and normal tissues. In addition, infiltration of CD4 + T cells, cancer-associated fibroblasts, macrophages, and endothelial cells were associated with CDKN3 expression in various tumors. Mechanistically, CDKN3 was associated with P53, PI3K-AKT, cell cycle checkpoints, mitotic spindle checkpoint, and chromosome maintenance. CONCLUSION Our pan-cancer analysis provides a comprehensive understanding of the role of CDKN3 gene in tumorigenesis. Targeting CDKN3 may provide a new direction for future tumor therapy. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Cancer is one of the most formidable challenges to human health in world 1 . Although numerous studies have been invested in the field of cancer, the mechanism of tumor evolution is still not fully understood 2 . In order to better understand the pathogenesis of tumors, conducting a wide range of pan cancer analysis compared to targeting individual tumors can not only effectively promote treatment methods for tumors, but also reduce the possibility of related drug resistance 3 . CDKN3 is a member of the protein kinase family and is thought to play an important role in the cell cycle regulatory pathway 4 , 5 . CDKN3 was found to have roles in cell cycle progression regulation 6 – 9 , human vascular endothelial cells 10 , severe COVID-19 11 , female genotoxicity 12 , vascular endothelial cell injury 13 , control of mitosis 14 , and promotion of preadipocyte proliferation 15 . Interestingly, CDKN3 has also been shown to be involved in tumor progression. Previous studies surface that CDKN3 is associated with tumors such as cervical cancer 16 , ovarian cancer 17 , bladder cancer 18 , colorectal cancer 19 , hepatocellular carcinoma 20 , lung cancer 21 , gastric carcinoma 22 and breast cancer 23 . This shows that CDKN3 may have an extremely strong correlation with tumors. However, most of the previously listed studies are limited to the mechanism of action of CDKN3 in a particular cancer. Few pan-cancer analyses of CDKN3 have been conducted to explore in depth whether there is a common mechanism of action between CDKN3 and tumor cells. Therefore, this study analysed the prognosis, methylation, and immune infiltration of CDKN3 and pan-cancer. It is hoped that it will provide new targets of action for tumor therapy. In addition, we investigated the role played by CDKN3 in the development and clinical prognosis of different cancers by means of TCGA, the Clinical Proteomics tumor Analysis Consortium (CPTAC), and Kaplan Meier survival analysis in order to explore the potential link between CDKN3 and tumors. Materials and Methods Differential expression analysis The clinical data of this study is from the TCGA( http://portal.gdc.cancer.gov/ ) and the UCSC Xena database( https://xenabrowser.net/datapages/ ). We obtained relevant RNA seq data through the UCSC XENA database. We use log2 conversion to analyze RNA seq data in TPM format. And use R software to analyze the data. We also use the R software package "ggplot2" for visualization. We also used UALCAN software to detect the differences in gene expression levels of CDKN3 at different stages in tumor and normal tissues. The P-value threshold is 0.05. Survival prognosis analysis We obtained clinical information on CDKN3 patients through the TCGA database. We conducted relevant prognostic analysis based on indicators such as OS, disease -specific survival (DSS), and progression-free interval (PFI). We also evaluated the survival probability of different tumor patients through univariate Cox regression analysis and Kaplan Meier survival analysis. The relevant data is analyzed using R packets. We also used timeROC to assess the predictive ability of CDKN3 as a clinical indicator. Association analysis between CDKN3 expression and clinical features Exploring the association between the expression of CDKN3 and relevant clinical indicators (gender, pathological stage, and TNM staging) using R packets. The relevant data was analyzed using the ggplot2 software package. Establishment and evaluation of the nomogram models Analyze which tumors may have an impact on the prognosis of CDKN3. The univariate Cox regression analysis was performed on the relevant tumors. To create a column chart model, select tumors with statistical significance and a sampling size above 500. And use calibration curves to determine the accuracy of the 1-, 3-, and 5-year column charts. Immune infiltration analysis The relationship between CDKN3 expression and immune infiltration was analyzed through TIMER2 online. And immune cells such as T cells, macrophages, and fibroblasts were selected as reference objects. Evaluate the degree of immune infiltration using quantitative methods such as TIDE, XCELL, and EPIC. Use the purity-adjusted Spearman test to calculate P-values and correlation (cor) results. The data obtained above is presented through a heat map. Methylation analysis Use the UALCAN website to detect methylation differences between tumors and normal tissues. And generate relevant data using the TCGA dataset. Gene enrichment analysis and protein-protein interaction network analysis We used the GEPIA2 database to obtain the 100 genes most closely associated with CDKN3 (Supplementary Table S10). Analyze the function of CDKN3 through GO analysis and KEGG pathway analysis. In addition, we generated a PPI network using 100 CDKN3-related genes on the STRING website(Supplementary Figure S2). Gene set enrichment analysis We conducted GSEA analysis using differential expression of CDKN3. And attempt to elucidate the biological function of CDKN3 in tumor progression. Results CDKN3 expression in pan-cancer In this study, we conducted an analysis of TCGA_GTEx data obtained from UCSC to explore the expression of CDKN3 in pan-cancer. Our investigation unveiled diverse expression patterns of the CDKN3 gene within distinct tumor cells. tumor cells. The expression of CDKN3 was significantly up-regulated in majority of tumors. However, CDKN3 expression was significantly down-regulated in LAML and TGCT (Fig. 1 A)., We also found that the expression of CDKN3 was significantly overexpressed in most of tumors. This result harmoniously resonated with the observations gleaned from the TCGA dataset. (Fig. 1 B). We also scrutinized CDKN3 expression in both tumors and corresponding normal tissues. Intriguingly, barring THCA, a consistent trend emerged wherein the majority of tumor tissues demonstrated heightened CDKN3 expression relative to their corresponding normal tissue counterparts. However, there was no conspicuous change in CDKN3 expression was observed between the normal tissues and the tumor tissues of CESC, PAAD, and PCPG (Fig. 1 C). Furthermore, we also obtained alterations in CDKN3 expression levels at distinct tumor stages by the utilization of the UALCAN online tool. In the advanced stages of 16 diverse cancer types, including BLCA, BRCA, CESC, COAD, ESCA, CHOL, KICH, KIRC, KIRP, HNSC, LIHC, LUAD, LUSC, READ, STAD, and UCEC, we observed a significant augmentation in CDKN3 expression (Fig. 2 ). The association between CDKN3 expression and prognosis in pan-cancer Kaplan-Meier survival analysis was used to investigate the correlation between CDKN3 expression and clinical outcomes. As shown in Fig. 3 A, we delved further into the association between CDKN3 expression and overall survival (OS) in 33 distinct cancers. The results demonstrated a compelling correlation between abnormal CDKN3 expression and OS in a subset of cancers, including ACC, BLCA, KIRC, KIRP, LGG, LIHC, LUSC, MESO, PAAD, UCEC, and UCEC (Figs. 3 B- 3 L). importantly, it was discerened that high level of CDKN3 was associated with shorter OS in these particular cancer types. Subsequently, we explored the association between CDKN3 expression and disease specific survival (DSS) (Fig. 4 A). Our exploration yielded compelling insights, revealing distinct associations between CDKN3 expression and DSS in a range of cancer types. Notably, the findings showed significant associations between CDKN3 expression and DSS in ACC (Fig. 4 B), BLCA (Fig. 4 C), DLBC (Fig. 4 D), LGG (Fig. 4 E), HNSC (Fig. 4 F), KIRC (Fig. 4 G), KIRP (Fig. 4 H), LIHC (Fig. 4 I), LUSC (Fig. 4 J), MESO (Fig. 4 K), PAAD (Fig. 4 L) and UVM (Fig. 4 M). In these specific cancers, elevated CDKN3 expression was conspicuously correlated with poorer DSS. Finally, an in-depth exploration into the relationship between CDKN3 expression and Progression-Free Interval (PFI) was undertaken (Fig. 5 A). This endeavor yielded noteworthy findings, enabling us to discern a clear pattern where elevated CDKN3 expression aligns with adverse PFI outcomes across several tissue types. Specifically, our analysis revealed that high CDKN3 expression is indicative of poorer PFI in the following tissues: ACC, BLCA, LGG, KIRC, KIRP, LIHC, LUAD, MESO, PAAD, PRAD, STAD, TGCT, and UVM. Supplementary Figure S1 A-E showcases Receiver Operating Characteristic (ROC) curves for five tumors where the prognosis is notably linked to CDKN3 expression, effectively illustrating the diagnostic potential of CDKN3 in these cases. The relationships between CDKN3 expression and clinical parameters The expression of CDKN3 was related to the prognosis of 17 different types of tumors, including ACC, BLCA, DLBC, HNSC, LGG, KIRC, KIRP, LIHC, LUAD, LUSC, MESO, PAAD, UCEC, PRAD, STAD, TGCT, and UVM. Here, we investigated the relationships between CDKN3 expression and the clinicopathological characteristics of these 17 tumors. These findings revealed that in the cases of HNSC, KIRP, LUAD, and LUSC, CDKN3 expression was associated with gender (Figs. 6 A-D). In the meantime, tumor size exhibited a connection with CDKN3 expression in ACC, KIRC, KIRP, and LIHC (Figs. 6 E-H). Additionally, CDKN3 expression was associated with lymph node metastases in HNSC, KIRC, KIRP, LUAD, LUSC, and PRAD (Figs. 6 I-N). There was also a correlation between CDKN3 expression and the pathological stage in ACC, KIRC, KIRP, LIHC, LUAD, and LUSC (Figs. 6 O-T). Building and assessing nomogram models for kidney renal clear cell carcinoma and lung squamous cell carcinoma In order to investigate the effect of CDKN3 expression on the prognosis of certain tumors, we performed univariate Cox regression analysis for OS in six tumors (Supplementary Tables S1–S9). To evaluate the prognostic value, we employed calibration curves to assess the prediction accuracy of nomogram model across 1,3 and 5-year periods. KIRC and LIHC with sample sizes more than 400 were selected. These models were constructed using the findings of a single-variate Cox regression. Results indicated that CDKN3 had a signoficant capacity to predict OS for KIRC and LIHC (Figs. 7 A, C), and calibrated survival prediction curves at 1, 3 and 5-year demonstrated that the nomogram model had a high level of precision and accuracy (Figs. 7 B, D). The correlation of CDKN3 expression and tumor immune microenvironment The progression of tumors are significantly influenced by the immune microenvironment. To investigate the relationship between CDKN3 and the immune microenvironment in pan-cancer, we conducted an analysis using the GEPIA2 database to assess the correlation between CDKN3 expression and immune cells. Heatmaps were used to illustrate the associations between CDKN3 expression and CD4 + T cells, cancer-associated fibroblasts, macrophages, and endothelial cells (Fig. 8 A-D). Over-expression of CDKN3 was significantly associated with Th2 (Fig. 6 A). In the TCGA tumors of BRCA, HNSC-HPV+, LUSC, and THYM tumors, we found a statistically significant negative connection between CDKN3 expression and infiltrating cancer-associated fibroblasts. However, CDKN3 expression in THCA was positively connected with fibroblast infiltration related to malignancy (Fig. 8 B). Furthermore, we found a statistically significant inverse relationship between CDKN3 expression and endothelial cells in the BRCA, KIRC, LUAD, LUSC, STAD, and THYM tumors. The expression of CDKN3 was positively linked with endothelial cells in LGG (Fig. 8 C). Figure 8 D demonstrated significant correlations between macrophages and CDKN3 expression in BLCA, KIRC HNSC-HPV-, MESO, PRAD, and THCA. DNA methylation analysis Tumor development, growth, and cellular carcinogenesis are all tightly connected with abnormal DNA methylation. The degree of DNA methylation of certain genes as well as variations in DNA methylation levels may also be used to detect tumors 24 . Using the UALCAN and TCGA databases, the DNA methylation levels of CDKN3 between normal and primary tumor tissues were explored. The CDKN3 methylation expression levels in HNSC and TGCT tumor tissues were significantly down-regulated (Fig. 9 ). Additionally, ESCA, KIRC, LUSC, and PAAD tumor tissues had considerably higher levels of CDKN3 methylation expression (Fig. 9 ). Functional enrichment and protein-protein interactions of CDKN3-related genes From the GEPIA2 database, 100 genes with the closest relationships to CDKN3 were analyzed to better understand the biological role of CDKN3 in tumors (Supplementary Table S10). According to GO analysis (Fig. 10 A), CDKN3-related genes may be involved in a variety of biological processes, including "mitotic sister chromatid segregation," "organelle fission," "nuclear division," and "mitotic nuclear division." Involved in “spindle”,“chromosomal region”, “chromosome, centromeric region”and other cell components. Along with other molecular activities, it takes part in "microtubule binding," "tubulin binding," and "microtubule motor activity." CDKN3-related genes may be related to "Cell cycle," "Oocyte meiosis," "Progesterone-mediated oocyte maturation," "DNA replication," and "p53 signalling pathway," according to KEGG pathway analysis (Fig. 10 B). The PPI network on the STRING website was constructed using 100 CDKN3-related genes (Supplementary Figure S2). Collectively, these analyses provided a comprehensive framework for understanding the biological significance of CDKN3 in the context of tumors, unraveling its involvement in vital cellular processes, molecular interactions, and pathways that influence tumor development and progression. Gene set enrichment analysis The GSEA analysis was used to clarify the biological function of CDKN3 in the 17 tumors with CDKN3 related to prognosis. These 17 tumors included ACC, BLCA, HNSC, DLBC, LGG, KIRC, KIRP, LIHC, LUAD, LUSC, MESO, PAAD, UCEC, PRAD, STAD, TGCT, and UVM(Fig. 10 -S). The findings imply that CDKN3 was primarily involved in mitotic spindle checkpoints, cell cycle checkpoints, and chromosome maintenance. Discussion The presence of tumor heterogeneity leads to reduced therapeutic efficacy and poor prognostic outcomes. Despite the gradual improvement in the understanding of tumor cell subpopulations with the advent of novel technologies such as single-cell sequencing, the field of clinical oncology remains slow. Therefore, it is of great importance to effectively accelerate the pace of clinical translation through the search for new tumor marker. Some research progress has been made on CDKN3 at the present time, and CDKN3 has been found to have a role in the regulation of cell cycle progression, severe COVID-19, female reproductive toxicity, vascular endothelial cell injury, control of mitosis, and promotion of adipocyte proliferation. There have been studies on how CDKN3 regulates the progression of a single tumor, which indirectly demonstrates the possibility of CDKN3 acting as a target for tumor markers. However, there is a lack of research in this area to analyse whether CDKN3 is suitable as a tumor marker or not from a macroscopic overall perspective. Here, we performed a pan-cancer analysis using bioinformatics data. In TCGA-GTEx samples, TCGA samples, and TCGA paired samples, we examined the differential expression of CDKN3 in normal and tumor tissues of several organs.We found significant variations in the expression of CDKN3 between tumor and normal tissues. With the exception of THCA, we confirmed that most tumor tissues had higher CDKN3 expression than paired normal tissues. However, inconsistent results were obtained. For example, the conclusions obtained for TCGA_GTEx and THCA were diametrically opposed to those for TCGA, and we speculate that this may be due to differences in we speculate that this may be due to differences in the sample size of the control group. Therefore, in order to obtain more accurate conclusions, we suggest increasing the sample size of the control group. To date, there is no overall assessment of the prognostic value of CDKN3 in various cancers. In this study, we demonstrated the multifaceted prognostic impact of CDKN3 overexpression on tumor OS based on TCGA and GEO databases. Our study showed that cancer patients with elevated CDKN3 expression had poorer OS, DSS, DFI, and PFI, especially in ACC, BLCA, KIRC, KIRP, LGG, LIHC, MESO, PAAD, and UVM. It has been confirmed that high expression of CDKN3 promotes proliferation and metastasis in renal cell carcinoma 25 . while a bioinformatics-based key gene screen revealed that increased levels of CDKN3 lead to poor prognosis in hepatocellular carcinoma 26 . while no relevant studies have been conducted on CDKN3 in bladder tumors, multiple myeloma, neuroendocrine tumors and melanoma. According to our findings, CDKN3 also plays a very important role in the above mentioned tumors, therefore, future studies engaging in these kinds of tumors can continue to explore the role played by CDKN3 in them. Interestingly, we found that CDKN3 and immune cells also have some connections. In the tumor microenvironment, immune cells, which are the soil, have an extremely important role for tumors. Our analysis reflects that CDKN3 has some correlation with CD4 + T cells, fibroblasts, macrophages and endothelial cells. Interestingly, the level of CDKN3 and macrophage infiltration varies in different cancer types. Therefore, we grouped them according to the level of expressed CDKN3 content. By grouping, we tried to explore the crosstalk between CDKN3, immune cells, and tumor prognosis. Based on the findings, we found a strong association between CDKN3 and the degree of immune cell infiltration. In turn, a high level of immune cell infiltration implied a poor tumor prognosis. Therefore, we speculate that high levels of CDKN3 may interfere with the prognosis of tumor patients by affecting immune cells and thereby. This is consistent with the results of a number of studies that have been previously obtained 27 , 28 . And the link between CDKN3 and clinical prognosis is not limited to immune cells in the tumor microenvironment. In addition to correlating the prognosis of 17 tumors with CDKN3 expression as analysed by TCGA, we also found a correlation between CDKN3 expression in ACC, KIRC, KIRP and LIHC and tumor size. It is worth thinking whether CDKN3 is linked in some aspects of tumor cell renewal and proliferation? It was shown that miR-127-3p promotes the proliferation and metastasis of renal cell carcinoma through CDKN 25 . And ZNF677 was also shown to inhibit the progression of renal cell carcinoma through the transcription of N6-methyladenosine and CDKN 29 . CDKN3 was moreover demonstrated to be an independent prognostic factor contributing to the progression of nasopharyngeal carcinoma to advanced stages 30 . which is in line with our concluded. In addition to tumor progression, we also found that CDKN3 was associated with lymph node metastasis in six tumors. This result was similarly confirmed in oral cancer 31 . In summary, we can confirm that the presence of CDKN3 predicts a poor tumor prognosis. Therefore, the use of CDKN3 as a tumor therapeutic target would be of great importance. There have already been studies identifying CDKN3 as a core gene for colorectal cancer prognosis by transcriptomics 32 , and in the future we believe that CDKN3 will have a broader research prospect. In the current various researches targeting tumors, besides the immune microenvironment we mentioned above, and various common cell death modes (e.g. apoptosis, autophagy, etc.), there is nothing hotter than epigenetic modifications. And methylation modification has been a hot field for many scholars in it. Our study also found that the methylation expression level of CDKN3 in HNSC and TGCT tumor tissues was significantly lower than that in normal tissues.In addition, the methylation expression level of CDKN3 was significantly elevated in ESCA, KIRC, LUSC and PAAD tumor tissues. This proves that CDKN3 may have a positive association with methylation. So, is there an association between CDKN3 and methylation or not? It has been demonstrated that ZNF677 inhibits renal cell carcinoma progression through the transcription of N6-methyladenosine and CDKN3 29 . It has also been shown that modulation of neuroblastoma cell proliferation can alter the methylation of the promoter region of the CDKN3 gene 33 . Interestingly, CDKN3, as the RNA methylation-associated isoform of pancreatic cancer, has been demonstrated to be associated with immune infiltration 28 . This could enable us to determine whether CDKN3 is associated with methylation or not 28 , which can be linked to the correlation we elaborated in the previous paragraph. This is more reflective of the fact that in the tumor microenvironment, the exchange of information between cells is presented as a kind of meshwork in which CDKN3 plays a very crucial role. Through the analysis in this paper, we found that CDKN3 has a strong connection with P53 and PI3K-AKT pathway, which is also confirmed 34 , 35 in related studies. However, we found that the NOTCH signalling pathway is also linked to CDKN3 through our study, but this has not been confirmed in relevant studies yet. It is worth thinking why no current studies focus on this signalling pathway? After all, the NOTCH signalling pathway has been shown to be a critical hub for both maintaining tumor cell stemness and causing DNA mutations. Is it because the link between NOTCH and CDKN3 is not as strong as we have analysed, or is it because of the number of samples, the type of tumor, or statistical errors that have led to a bottleneck in the relevant studies? This is all a focus we can explore in the future. In summary, this paper highlights the role played by CDKN3 in pan-cancer analyses. Through different analyses, we exemplify the feasibility of CDKN3 as a tumor marker. However, it is very unfortunate that, firstly, this paper did not verify the importance of CDKN3 by relevant experimental means, and secondly, in the future, we hope to have the opportunity to combine the information of single-cell sequencing libraries to classify tumor cells in a more detailed way. We believe that a more in-depth analysis of the connection between CDKN3 and the tumor microenvironment is of great significance for the targeted treatment of tumors. Conclusions In summary, we conducted a comprehensive pan cancer study on CDKN3. We observed the significant relationship between CDKN3 expression and clinical prognosis, gene mutation, DNA methylation, immune cell infiltration and tumor mutation in a variety of human malignant tumors, trying to help understand the function of CDKN3 in tumors from multiple perspectives. Declarations Conflicts of Interest The authors declare no conflicts of interest related to this study. Author Contributions Y-jC and D-L proposed the study idea. Y-jC collected and analysed the data and drafted the manuscript. X-zZ, D-L critically revised the manuscript. All authors contributed to the article and approved the submitted version. Funding Statement This study is supported by grants from the Natural Science Foundation of Shandong Province. (Grant No. ZR2020MH322) Data Availability The datasets used in this investigation are available through public repositories. Conflict of interest All the authors declare no conficts of interest. Ethical approval Our study was approved by the China Medical University Consent for publication Our manuscripts do not contain personal data in any case. References Seferbekova, Z., Lomakin, A., Yates, L. R. & Gerstung, M. Spatial biology of cancer evolution. Nature reviews. Genetics 24, 295–313, doi: 10.1038/s41576-022-00553-x (2023). Feinberg, A. P. & Levchenko, A. Epigenetics as a mediator of plasticity in cancer. 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D., Yamamuro, Y. & Zeisel, S. H. Choline availability modulates human neuroblastoma cell proliferation and alters the methylation of the promoter region of the cyclin-dependent kinase inhibitor 3 gene. Journal of neurochemistry 89, 1252–1259, doi: 10.1111/j.1471-4159.2004.02414.x (2004). Liu, D. et al. YY1 suppresses proliferation and migration of pancreatic ductal adenocarcinoma by regulating the CDKN3/MdM2/P53/P21 signaling pathway. International journal of cancer 142, 1392–1404, doi: 10.1002/ijc.31173 (2018). Gao, L. M. et al. Tumor-suppressive effects of microRNA-181d-5p on non-small-cell lung cancer through the CDKN3-mediated Akt signaling pathway in vivo and in vitro. American journal of physiology. Lung cellular and molecular physiology 316, L918-l933, doi: 10.1152/ajplung.00334.2018 (2019). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.zip Cite Share Download PDF Status: Published Journal Publication published 08 May, 2024 Read the published version in European Journal of Medical Research → Version 1 posted Editorial decision: Revision requested 12 Apr, 2024 Reviews received at journal 04 Apr, 2024 Reviewers agreed at journal 23 Mar, 2024 Reviewers agreed at journal 19 Mar, 2024 Reviewers invited by journal 19 Mar, 2024 Editor assigned by journal 14 Mar, 2024 Submission checks completed at journal 12 Mar, 2024 First submitted to journal 11 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-4071308","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":278626104,"identity":"5aaa49e0-2f4d-4bf8-994e-49fcd0e538b3","order_by":0,"name":"Yingjun Chen","email":"","orcid":"","institution":"Binzhou Medical University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yingjun","middleName":"","lastName":"Chen","suffix":""},{"id":278626105,"identity":"f523b1c7-642e-4fb1-93d6-65cb03f082c5","order_by":1,"name":"Dai Li","email":"","orcid":"","institution":"The Fourth Affiliated Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dai","middleName":"","lastName":"Li","suffix":""},{"id":278626106,"identity":"d24db756-8ad4-4c54-9189-fac96551212f","order_by":2,"name":"Kaihui Sha","email":"","orcid":"","institution":"Binzhou Medical University School of Nursing","correspondingAuthor":false,"prefix":"","firstName":"Kaihui","middleName":"","lastName":"Sha","suffix":""},{"id":278626107,"identity":"0fdeb4dd-0d45-475a-861c-55a8757e49a7","order_by":3,"name":"Xuezhong Zhang","email":"","orcid":"","institution":"Zibo Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuezhong","middleName":"","lastName":"Zhang","suffix":""},{"id":278626108,"identity":"1127eab6-a6f4-4eb4-bdb1-93f426bb2402","order_by":4,"name":"Tonggang Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYBACPmYkzoEPP2x4+Nkb8GthY2ZghClhPDizJ01GsucAAS0MCC3Mh3nYDtsY3HAgoIWdx/zBxx21dv2z2y8c4OE5z8Nwg4Hxw8ccfA7jMWyceeZ48ow7ZwoOSFjc5mGc3cAsOXMbfi3NvG3Hkhlu5CQcMOC5zcMsc4CNmZcYLfIgLQls53jYJBKI0lJjZ3Aj/cCBA2xA7xDWwlY4c2bbgQTDGzkMBxt7knkkeA424/ULP//hDR8+ttXZy91If/z5zw87e/vjzQc/fMSjBQoOJzYw8BhAOfCIwgvq7BkY2B8Qo3IUjIJRMApGIAAAwMBVUfdF8YUAAAAASUVORK5CYII=","orcid":"","institution":"Binzhou Medical University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Tonggang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-03-11 08:17:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4071308/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4071308/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40001-024-01869-6","type":"published","date":"2024-05-08T04:01:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":52711374,"identity":"87f104f0-60cb-40f3-abe0-a5788e581a58","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":376809,"visible":true,"origin":"","legend":"\u003cp\u003eCDKN3 mRNA expression in pan-cancers.(A) CDKN3 mRNA expression in 33 tumors from TCGA-GTEx samples.(B) CDKN3 mRNA expression in 33 tumors from the TCGA database. (C) CDKN3 expression was observed in 23 paired tumor specimens from the TCGA database. (ns, p ≥ 0.05; *p \u0026lt; 0.05; **p \u0026lt; 0.01;***p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/731bb4d836b41e8e44e7cbf2.png"},{"id":52711375,"identity":"44d85bfe-9aad-42b3-868b-e043816662d2","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":483981,"visible":true,"origin":"","legend":"\u003cp\u003eAn analysis of the association between CDKN3 expression and tumor stage. (ns, p ≥ 0.05; *p \u0026lt; 0.05; **p \u0026lt; 0.01;***p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/b53721f32f6cc0d5fe70cee8.png"},{"id":52712753,"identity":"c706c40b-56de-4aef-a849-b88249a6a8f8","added_by":"auto","created_at":"2024-03-14 20:13:31","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":496853,"visible":true,"origin":"","legend":"\u003cp\u003eCDKN3 expression correlates with OS in pan-cancer survival analysis. (A) Forest plots of the survival results. (B-L) A survival curve showed that CDKN3 expression associated with OS.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/44e3a908711d1bd412ed52fe.png"},{"id":52711380,"identity":"e4e0ba1e-815a-425d-bb5b-20c7c7a15592","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":521643,"visible":true,"origin":"","legend":"\u003cp\u003eCDKN3 expression correlates with DSS in pan-cancer survival analysis. (A) Forest plots of the survival results. (B-M) A survival curve showed that CDKN3 expression associated with DSS.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/ed949a9e5eafed4ea5ed883e.png"},{"id":52711385,"identity":"b1c6557b-1e6e-41c1-93a4-138342a0768f","added_by":"auto","created_at":"2024-03-14 19:57:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":614202,"visible":true,"origin":"","legend":"\u003cp\u003eCDKN3 expression correlates with PFI in pan-cancer survival analysis. (A) Forest plots of the outcomes of the surviving. (B-N) A survival curve based on Kaplan-Meier analysis showed that CDKN3 expression correlated with PFI.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/c5bf9035f5bad746aad45b11.png"},{"id":52711383,"identity":"5d1237bb-c892-4acf-a3ec-a5f185fd7973","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":567777,"visible":true,"origin":"","legend":"\u003cp\u003eClinical metrics and CDKN3 expression's relationship (A-D) CDKN3 expression was related to gender. (E-H) Expression of CDKN3 was related to the T stage. (I-N) CDKN3 expression was related to the N stage. (O-T) CDKN3 expression was related to pathologic stage. (*p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/5f0345015a74a5bfa4412220.png"},{"id":52712015,"identity":"0ba6aecb-5b49-4fab-8eb2-dfaa2ee38563","added_by":"auto","created_at":"2024-03-14 20:05:31","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":262627,"visible":true,"origin":"","legend":"\u003cp\u003eThe CDKN3 prognostic signature was combined with independent TCGA components to create our hybrid nomogram. (A) Creation of a nomogram model that takes CDKN3 expression in KIRC into account. (B) Using calibration curves for 1, 3, and 5 years, we assessed the KIRC nomogram model's prediction accuracy. The expression of (C)CDKN3 in LIHC is modelled using a nomogram. (D) Using calibration curves for 1, 3, and 5 years, we assessed the LIHC nomogram model's prediction accuracy.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/3e003e99f81f458658d7a55d.png"},{"id":52711379,"identity":"ceb24c1e-6b4c-4ed5-9912-f9f5370a6b52","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":675098,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the relationship between CDKN3 expression and immune infiltration of CD4+ T cells (A), Cancer associated fibroblasts (B), Macrophages(C), and endothelial cells (D).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/bddb21336ecebb0f0192f6a9.png"},{"id":52711384,"identity":"5beca89a-3e7a-4700-b68c-531bd5cd52dc","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":126522,"visible":true,"origin":"","legend":"\u003cp\u003eThe methylationlevel of CDKN3 in ESCA, KIRC, HNSC, LUSC, TGCT, and PAAD.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/7c6ed93f52a92f7d4e2e4496.png"},{"id":52711378,"identity":"9e3bf437-f4c8-4447-8ff4-814185df5790","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":556016,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of CDKN3-related genes' functional enrichment. (A) Analyses of GO functional enrichment (BP, CC, and MF). (B) Analysis of KEGG pathways for 100 CDKN3-related genes. (C-S) GSEA based on differential expression analyses for ACC, BLCA , HNSC, DLBC, LGG, KIRC, KIRP, LIHC, LUAD, LUSC, MESO, PAAD, UCEC, PRAD, STAD, TGCT and UVM, respectively.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/d55a69befba31b3077eaa9f3.png"},{"id":56140470,"identity":"2bde0ae4-baa8-4fe5-ada7-b230cb1ae3d1","added_by":"auto","created_at":"2024-05-09 04:27:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4983514,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/6e76c34f-7a28-4e2f-8e41-b8c6de8ffff5.pdf"},{"id":52711377,"identity":"dcec2c9f-4876-44c5-9f7f-59bc455be646","added_by":"auto","created_at":"2024-03-14 19:57:31","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1522851,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.zip","url":"https://assets-eu.researchsquare.com/files/rs-4071308/v1/ee9ffe9b83359c777cd811d9.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Human pan-cancer analysis of the predictive biomarker for the CDKN3","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer is one of the most formidable challenges to human health in world\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Although numerous studies have been invested in the field of cancer, the mechanism of tumor evolution is still not fully understood\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In order to better understand the pathogenesis of tumors, conducting a wide range of pan cancer analysis compared to targeting individual tumors can not only effectively promote treatment methods for tumors, but also reduce the possibility of related drug resistance\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCDKN3 is a member of the protein kinase family and is thought to play an important role in the cell cycle regulatory pathway\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. CDKN3 was found to have roles in cell cycle progression regulation\u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, human vascular endothelial cells\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, severe COVID-19\u003csup\u003e11\u003c/sup\u003e, female genotoxicity\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, vascular endothelial cell injury\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, control of mitosis\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, and promotion of preadipocyte proliferation\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Interestingly, CDKN3 has also been shown to be involved in tumor progression. Previous studies surface that CDKN3 is associated with tumors such as cervical cancer\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, ovarian cancer\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, bladder cancer\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, colorectal cancer\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, hepatocellular carcinoma\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, lung cancer\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, gastric carcinoma\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and breast cancer\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. This shows that CDKN3 may have an extremely strong correlation with tumors.\u003c/p\u003e \u003cp\u003eHowever, most of the previously listed studies are limited to the mechanism of action of CDKN3 in a particular cancer. Few pan-cancer analyses of CDKN3 have been conducted to explore in depth whether there is a common mechanism of action between CDKN3 and tumor cells. Therefore, this study analysed the prognosis, methylation, and immune infiltration of CDKN3 and pan-cancer. It is hoped that it will provide new targets of action for tumor therapy.\u003c/p\u003e \u003cp\u003eIn addition, we investigated the role played by CDKN3 in the development and clinical prognosis of different cancers by means of TCGA, the Clinical Proteomics tumor Analysis Consortium (CPTAC), and Kaplan Meier survival analysis in order to explore the potential link between CDKN3 and tumors.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDifferential expression analysis\u003c/h2\u003e \u003cp\u003eThe clinical data of this study is from the TCGA(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://portal.gdc.cancer.gov/\u003c/span\u003e\u003cspan address=\"http://portal.gdc.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the UCSC Xena database(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://xenabrowser.net/datapages/\u003c/span\u003e\u003cspan address=\"https://xenabrowser.net/datapages/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We obtained relevant RNA seq data through the UCSC XENA database. We use log2 conversion to analyze RNA seq data in TPM format. And use R software to analyze the data. We also use the R software package \"ggplot2\" for visualization. We also used UALCAN software to detect the differences in gene expression levels of CDKN3 at different stages in tumor and normal tissues. The P-value threshold is 0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSurvival prognosis analysis\u003c/h2\u003e \u003cp\u003eWe obtained clinical information on CDKN3 patients through the TCGA database. We conducted relevant prognostic analysis based on indicators such as OS, disease -specific survival (DSS), and progression-free interval (PFI). We also evaluated the survival probability of different tumor patients through univariate Cox regression analysis and Kaplan Meier survival analysis. The relevant data is analyzed using R packets. We also used timeROC to assess the predictive ability of CDKN3 as a clinical indicator.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssociation analysis between CDKN3 expression and clinical features\u003c/h2\u003e \u003cp\u003eExploring the association between the expression of CDKN3 and relevant clinical indicators (gender, pathological stage, and TNM staging) using R packets. The relevant data was analyzed using the ggplot2 software package.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEstablishment and evaluation of the nomogram models\u003c/h2\u003e \u003cp\u003eAnalyze which tumors may have an impact on the prognosis of CDKN3. The univariate Cox regression analysis was performed on the relevant tumors. To create a column chart model, select tumors with statistical significance and a sampling size above 500. And use calibration curves to determine the accuracy of the 1-, 3-, and 5-year column charts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eImmune infiltration analysis\u003c/h2\u003e \u003cp\u003eThe relationship between CDKN3 expression and immune infiltration was analyzed through TIMER2 online. And immune cells such as T cells, macrophages, and fibroblasts were selected as reference objects. Evaluate the degree of immune infiltration using quantitative methods such as TIDE, XCELL, and EPIC. Use the purity-adjusted Spearman test to calculate P-values and correlation (cor) results. The data obtained above is presented through a heat map.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMethylation analysis\u003c/h2\u003e \u003cp\u003eUse the UALCAN website to detect methylation differences between tumors and normal tissues. And generate relevant data using the TCGA dataset.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eGene enrichment analysis and protein-protein interaction network analysis\u003c/h2\u003e \u003cp\u003eWe used the GEPIA2 database to obtain the 100 genes most closely associated with CDKN3 (Supplementary Table S10). Analyze the function of CDKN3 through GO analysis and KEGG pathway analysis. In addition, we generated a PPI network using 100 CDKN3-related genes on the STRING website(Supplementary Figure S2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eGene set enrichment analysis\u003c/h2\u003e \u003cp\u003eWe conducted GSEA analysis using differential expression of CDKN3. And attempt to elucidate the biological function of CDKN3 in tumor progression.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCDKN3 expression in pan-cancer\u003c/h2\u003e \u003cp\u003eIn this study, we conducted an analysis of TCGA_GTEx data obtained from UCSC to explore the expression of CDKN3 in pan-cancer. Our investigation unveiled diverse expression patterns of the CDKN3 gene within distinct tumor cells. tumor cells. The expression of CDKN3 was significantly up-regulated in majority of tumors. However, CDKN3 expression was significantly down-regulated in LAML and TGCT (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA)., We also found that the expression of CDKN3 was significantly overexpressed in most of tumors. This result harmoniously resonated with the observations gleaned from the TCGA dataset. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). We also scrutinized CDKN3 expression in both tumors and corresponding normal tissues. Intriguingly, barring THCA, a consistent trend emerged wherein the majority of tumor tissues demonstrated heightened CDKN3 expression relative to their corresponding normal tissue counterparts. However, there was no conspicuous change in CDKN3 expression was observed between the normal tissues and the tumor tissues of CESC, PAAD, and PCPG (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eFurthermore, we also obtained alterations in CDKN3 expression levels at distinct tumor stages by the utilization of the UALCAN online tool. In the advanced stages of 16 diverse cancer types, including BLCA, BRCA, CESC, COAD, ESCA, CHOL, KICH, KIRC, KIRP, HNSC, LIHC, LUAD, LUSC, READ, STAD, and UCEC, we observed a significant augmentation in CDKN3 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe association between CDKN3 expression and prognosis in pan-cancer\u003c/h2\u003e \u003cp\u003eKaplan-Meier survival analysis was used to investigate the correlation between CDKN3 expression and clinical outcomes. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, we delved further into the association between CDKN3 expression and overall survival (OS) in 33 distinct cancers. The results demonstrated a compelling correlation between abnormal CDKN3 expression and OS in a subset of cancers, including ACC, BLCA, KIRC, KIRP, LGG, LIHC, LUSC, MESO, PAAD, UCEC, and UCEC (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). importantly, it was discerened that high level of CDKN3 was associated with shorter OS in these particular cancer types.\u003c/p\u003e \u003cp\u003eSubsequently, we explored the association between CDKN3 expression and disease specific survival (DSS) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Our exploration yielded compelling insights, revealing distinct associations between CDKN3 expression and DSS in a range of cancer types. Notably, the findings showed significant associations between CDKN3 expression and DSS in ACC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), BLCA (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), DLBC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), LGG (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE), HNSC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), KIRC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG), KIRP (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH), LIHC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eI), LUSC (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eJ), MESO (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eK), PAAD (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eL) and UVM (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eM). In these specific cancers, elevated CDKN3 expression was conspicuously correlated with poorer DSS.\u003c/p\u003e \u003cp\u003eFinally, an in-depth exploration into the relationship between CDKN3 expression and Progression-Free Interval (PFI) was undertaken (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This endeavor yielded noteworthy findings, enabling us to discern a clear pattern where elevated CDKN3 expression aligns with adverse PFI outcomes across several tissue types. Specifically, our analysis revealed that high CDKN3 expression is indicative of poorer PFI in the following tissues: ACC, BLCA, LGG, KIRC, KIRP, LIHC, LUAD, MESO, PAAD, PRAD, STAD, TGCT, and UVM. Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA-E showcases Receiver Operating Characteristic (ROC) curves for five tumors where the prognosis is notably linked to CDKN3 expression, effectively illustrating the diagnostic potential of CDKN3 in these cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eThe relationships between CDKN3 expression and clinical parameters\u003c/h2\u003e \u003cp\u003eThe expression of CDKN3 was related to the prognosis of 17 different types of tumors, including ACC, BLCA, DLBC, HNSC, LGG, KIRC, KIRP, LIHC, LUAD, LUSC, MESO, PAAD, UCEC, PRAD, STAD, TGCT, and UVM. Here, we investigated the relationships between CDKN3 expression and the clinicopathological characteristics of these 17 tumors. These findings revealed that in the cases of HNSC, KIRP, LUAD, and LUSC, CDKN3 expression was associated with gender (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-D). In the meantime, tumor size exhibited a connection with CDKN3 expression in ACC, KIRC, KIRP, and LIHC (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-H). Additionally, CDKN3 expression was associated with lymph node metastases in HNSC, KIRC, KIRP, LUAD, LUSC, and PRAD (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eI-N). There was also a correlation between CDKN3 expression and the pathological stage in ACC, KIRC, KIRP, LIHC, LUAD, and LUSC (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eO-T).\u003c/p\u003e\u003cp\u003e \u003cb\u003eBuilding and assessing nomogram models for kidney renal clear cell carcinoma and lung squamous cell carcinoma\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn order to investigate the effect of CDKN3 expression on the prognosis of certain tumors, we performed univariate Cox regression analysis for OS in six tumors (Supplementary Tables S1\u0026ndash;S9). To evaluate the prognostic value, we employed calibration curves to assess the prediction accuracy of nomogram model across 1,3 and 5-year periods. KIRC and LIHC with sample sizes more than 400 were selected. These models were constructed using the findings of a single-variate Cox regression. Results indicated that CDKN3 had a signoficant capacity to predict OS for KIRC and LIHC (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA, C), and calibrated survival prediction curves at 1, 3 and 5-year demonstrated that the nomogram model had a high level of precision and accuracy (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, D).\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eThe correlation of CDKN3 expression and tumor immune microenvironment\u003c/h2\u003e \u003cp\u003eThe progression of tumors are significantly influenced by the immune microenvironment. To investigate the relationship between CDKN3 and the immune microenvironment in pan-cancer, we conducted an analysis using the GEPIA2 database to assess the correlation between CDKN3 expression and immune cells. Heatmaps were used to illustrate the associations between CDKN3 expression and CD4\u0026thinsp;+\u0026thinsp;T cells, cancer-associated fibroblasts, macrophages, and endothelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-D). Over-expression of CDKN3 was significantly associated with Th2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). In the TCGA tumors of BRCA, HNSC-HPV+, LUSC, and THYM tumors, we found a statistically significant negative connection between CDKN3 expression and infiltrating cancer-associated fibroblasts. However, CDKN3 expression in THCA was positively connected with fibroblast infiltration related to malignancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Furthermore, we found a statistically significant inverse relationship between CDKN3 expression and endothelial cells in the BRCA, KIRC, LUAD, LUSC, STAD, and THYM tumors. The expression of CDKN3 was positively linked with endothelial cells in LGG (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD demonstrated significant correlations between macrophages and CDKN3 expression in BLCA, KIRC HNSC-HPV-, MESO, PRAD, and THCA.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDNA methylation analysis\u003c/h2\u003e \u003cp\u003eTumor development, growth, and cellular carcinogenesis are all tightly connected with abnormal DNA methylation. The degree of DNA methylation of certain genes as well as variations in DNA methylation levels may also be used to detect tumors\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Using the UALCAN and TCGA databases, the DNA methylation levels of CDKN3 between normal and primary tumor tissues were explored. The CDKN3 methylation expression levels in HNSC and TGCT tumor tissues were significantly down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Additionally, ESCA, KIRC, LUSC, and PAAD tumor tissues had considerably higher levels of CDKN3 methylation expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eFunctional enrichment and protein-protein interactions of CDKN3-related genes\u003c/h2\u003e \u003cp\u003eFrom the GEPIA2 database, 100 genes with the closest relationships to CDKN3 were analyzed to better understand the biological role of CDKN3 in tumors (Supplementary Table S10). According to GO analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eA), CDKN3-related genes may be involved in a variety of biological processes, including \"mitotic sister chromatid segregation,\" \"organelle fission,\" \"nuclear division,\" and \"mitotic nuclear division.\" Involved in \u0026ldquo;spindle\u0026rdquo;,\u0026ldquo;chromosomal region\u0026rdquo;, \u0026ldquo;chromosome, centromeric region\u0026rdquo;and other cell components. Along with other molecular activities, it takes part in \"microtubule binding,\" \"tubulin binding,\" and \"microtubule motor activity.\" CDKN3-related genes may be related to \"Cell cycle,\" \"Oocyte meiosis,\" \"Progesterone-mediated oocyte maturation,\" \"DNA replication,\" and \"p53 signalling pathway,\" according to KEGG pathway analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003eB). The PPI network on the STRING website was constructed using 100 CDKN3-related genes (Supplementary Figure S2). Collectively, these analyses provided a comprehensive framework for understanding the biological significance of CDKN3 in the context of tumors, unraveling its involvement in vital cellular processes, molecular interactions, and pathways that influence tumor development and progression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGene set enrichment analysis\u003c/h2\u003e \u003cp\u003eThe GSEA analysis was used to clarify the biological function of CDKN3 in the 17 tumors with CDKN3 related to prognosis. These 17 tumors included ACC, BLCA, HNSC, DLBC, LGG, KIRC, KIRP, LIHC, LUAD, LUSC, MESO, PAAD, UCEC, PRAD, STAD, TGCT, and UVM(Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-S). The findings imply that CDKN3 was primarily involved in mitotic spindle checkpoints, cell cycle checkpoints, and chromosome maintenance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe presence of tumor heterogeneity leads to reduced therapeutic efficacy and poor prognostic outcomes. Despite the gradual improvement in the understanding of tumor cell subpopulations with the advent of novel technologies such as single-cell sequencing, the field of clinical oncology remains slow. Therefore, it is of great importance to effectively accelerate the pace of clinical translation through the search for new tumor marker.\u003c/p\u003e \u003cp\u003eSome research progress has been made on CDKN3 at the present time, and CDKN3 has been found to have a role in the regulation of cell cycle progression, severe COVID-19, female reproductive toxicity, vascular endothelial cell injury, control of mitosis, and promotion of adipocyte proliferation. There have been studies on how CDKN3 regulates the progression of a single tumor, which indirectly demonstrates the possibility of CDKN3 acting as a target for tumor markers. However, there is a lack of research in this area to analyse whether CDKN3 is suitable as a tumor marker or not from a macroscopic overall perspective.\u003c/p\u003e \u003cp\u003eHere, we performed a pan-cancer analysis using bioinformatics data. In TCGA-GTEx samples, TCGA samples, and TCGA paired samples, we examined the differential expression of CDKN3 in normal and tumor tissues of several organs.We found significant variations in the expression of CDKN3 between tumor and normal tissues. With the exception of THCA, we confirmed that most tumor tissues had higher CDKN3 expression than paired normal tissues. However, inconsistent results were obtained. For example, the conclusions obtained for TCGA_GTEx and THCA were diametrically opposed to those for TCGA, and we speculate that this may be due to differences in we speculate that this may be due to differences in the sample size of the control group. Therefore, in order to obtain more accurate conclusions, we suggest increasing the sample size of the control group.\u003c/p\u003e \u003cp\u003eTo date, there is no overall assessment of the prognostic value of CDKN3 in various cancers. In this study, we demonstrated the multifaceted prognostic impact of CDKN3 overexpression on tumor OS based on TCGA and GEO databases. Our study showed that cancer patients with elevated CDKN3 expression had poorer OS, DSS, DFI, and PFI, especially in ACC, BLCA, KIRC, KIRP, LGG, LIHC, MESO, PAAD, and UVM. It has been confirmed that high expression of CDKN3 promotes proliferation and metastasis in renal cell carcinoma\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. while a bioinformatics-based key gene screen revealed that increased levels of CDKN3 lead to poor prognosis in hepatocellular carcinoma\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. while no relevant studies have been conducted on CDKN3 in bladder tumors, multiple myeloma, neuroendocrine tumors and melanoma. According to our findings, CDKN3 also plays a very important role in the above mentioned tumors, therefore, future studies engaging in these kinds of tumors can continue to explore the role played by CDKN3 in them.\u003c/p\u003e \u003cp\u003eInterestingly, we found that CDKN3 and immune cells also have some connections. In the tumor microenvironment, immune cells, which are the soil, have an extremely important role for tumors. Our analysis reflects that CDKN3 has some correlation with CD4\u0026thinsp;+\u0026thinsp;T cells, fibroblasts, macrophages and endothelial cells. Interestingly, the level of CDKN3 and macrophage infiltration varies in different cancer types. Therefore, we grouped them according to the level of expressed CDKN3 content. By grouping, we tried to explore the crosstalk between CDKN3, immune cells, and tumor prognosis. Based on the findings, we found a strong association between CDKN3 and the degree of immune cell infiltration. In turn, a high level of immune cell infiltration implied a poor tumor prognosis. Therefore, we speculate that high levels of CDKN3 may interfere with the prognosis of tumor patients by affecting immune cells and thereby. This is consistent with the results of a number of studies that have been previously obtained \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAnd the link between CDKN3 and clinical prognosis is not limited to immune cells in the tumor microenvironment. In addition to correlating the prognosis of 17 tumors with CDKN3 expression as analysed by TCGA, we also found a correlation between CDKN3 expression in ACC, KIRC, KIRP and LIHC and tumor size. It is worth thinking whether CDKN3 is linked in some aspects of tumor cell renewal and proliferation? It was shown that miR-127-3p promotes the proliferation and metastasis of renal cell carcinoma through CDKN\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. And ZNF677 was also shown to inhibit the progression of renal cell carcinoma through the transcription of N6-methyladenosine and CDKN\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. CDKN3 was moreover demonstrated to be an independent prognostic factor contributing to the progression of nasopharyngeal carcinoma to advanced stages\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. which is in line with our concluded. In addition to tumor progression, we also found that CDKN3 was associated with lymph node metastasis in six tumors. This result was similarly confirmed in oral cancer\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. In summary, we can confirm that the presence of CDKN3 predicts a poor tumor prognosis. Therefore, the use of CDKN3 as a tumor therapeutic target would be of great importance. There have already been studies identifying CDKN3 as a core gene for colorectal cancer prognosis by transcriptomics \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, and in the future we believe that CDKN3 will have a broader research prospect.\u003c/p\u003e \u003cp\u003eIn the current various researches targeting tumors, besides the immune microenvironment we mentioned above, and various common cell death modes (e.g. apoptosis, autophagy, etc.), there is nothing hotter than epigenetic modifications. And methylation modification has been a hot field for many scholars in it. Our study also found that the methylation expression level of CDKN3 in HNSC and TGCT tumor tissues was significantly lower than that in normal tissues.In addition, the methylation expression level of CDKN3 was significantly elevated in ESCA, KIRC, LUSC and PAAD tumor tissues. This proves that CDKN3 may have a positive association with methylation. So, is there an association between CDKN3 and methylation or not? It has been demonstrated that ZNF677 inhibits renal cell carcinoma progression through the transcription of N6-methyladenosine and CDKN3\u003csup\u003e29\u003c/sup\u003e. It has also been shown that modulation of neuroblastoma cell proliferation can alter the methylation of the promoter region of the CDKN3 gene\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Interestingly, CDKN3, as the RNA methylation-associated isoform of pancreatic cancer, has been demonstrated to be associated with immune infiltration\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. This could enable us to determine whether CDKN3 is associated with methylation or not\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, which can be linked to the correlation we elaborated in the previous paragraph. This is more reflective of the fact that in the tumor microenvironment, the exchange of information between cells is presented as a kind of meshwork in which CDKN3 plays a very crucial role.\u003c/p\u003e \u003cp\u003eThrough the analysis in this paper, we found that CDKN3 has a strong connection with P53 and PI3K-AKT pathway, which is also confirmed \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e in related studies. However, we found that the NOTCH signalling pathway is also linked to CDKN3 through our study, but this has not been confirmed in relevant studies yet. It is worth thinking why no current studies focus on this signalling pathway? After all, the NOTCH signalling pathway has been shown to be a critical hub for both maintaining tumor cell stemness and causing DNA mutations. Is it because the link between NOTCH and CDKN3 is not as strong as we have analysed, or is it because of the number of samples, the type of tumor, or statistical errors that have led to a bottleneck in the relevant studies? This is all a focus we can explore in the future.\u003c/p\u003e \u003cp\u003eIn summary, this paper highlights the role played by CDKN3 in pan-cancer analyses. Through different analyses, we exemplify the feasibility of CDKN3 as a tumor marker. However, it is very unfortunate that, firstly, this paper did not verify the importance of CDKN3 by relevant experimental means, and secondly, in the future, we hope to have the opportunity to combine the information of single-cell sequencing libraries to classify tumor cells in a more detailed way. We believe that a more in-depth analysis of the connection between CDKN3 and the tumor microenvironment is of great significance for the targeted treatment of tumors.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, we conducted a comprehensive pan cancer study on CDKN3. We observed the significant relationship between CDKN3 expression and clinical prognosis, gene mutation, DNA methylation, immune cell infiltration and tumor mutation in a variety of human malignant tumors, trying to help understand the function of CDKN3 in tumors from multiple perspectives.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest related to this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY-jC and D-L proposed the study idea. Y-jC collected and analysed the data and drafted the manuscript. X-zZ, D-L critically revised the manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is supported by grants from the Natural Science Foundation of Shandong Province.\u0026nbsp;(Grant No. ZR2020MH322)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used in this investigation are available through public repositories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors declare no conficts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study was approved by the China Medical University\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur manuscripts do not contain personal data in any case.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSeferbekova, Z., Lomakin, A., Yates, L. 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Lung cellular and molecular physiology 316, L918-l933, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/ajplung.00334.2018\u003c/span\u003e\u003cspan address=\"10.1152/ajplung.00334.2018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4071308/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4071308/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eCell cycle protein-dependent kinase inhibitor protein 3 (CDKN3) is a member of the protein kinase family and has been shown to be oncogenic in several tumors. However, there are no pan-carcinogenic analyses for CDKN3.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eUsing bioinformatics tools such as The Cancer Genome Atlas (TCGA) and the UCSC Xena database, we performed a pan-cancer analysis of CDKN3. We investigated the function of CDKN3 in 33 different kinds of tumor. And we explored the gene expression, survival prognosis status, clinical significance,DNA methylation, immune infiltration, and associated signal pathways of CDKN3.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eCDKN3 was significantly upregulated in most of tumors and correlated with overall survival (OS) of patients. Methylation levels of CDKN3 differed significantly between tumors and normal tissues. In addition, infiltration of CD4\u0026thinsp;+\u0026thinsp;T cells, cancer-associated fibroblasts, macrophages, and endothelial cells were associated with CDKN3 expression in various tumors. Mechanistically, CDKN3 was associated with P53, PI3K-AKT, cell cycle checkpoints, mitotic spindle checkpoint, and chromosome maintenance.\u003c/p\u003e\u003ch2\u003eCONCLUSION\u003c/h2\u003e \u003cp\u003eOur pan-cancer analysis provides a comprehensive understanding of the role of CDKN3 gene in tumorigenesis. Targeting CDKN3 may provide a new direction for future tumor therapy.\u003c/p\u003e","manuscriptTitle":"Human pan-cancer analysis of the predictive biomarker for the CDKN3","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-14 19:57:26","doi":"10.21203/rs.3.rs-4071308/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-12T17:23:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-04T06:02:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"14b3e606-c42f-4565-8a16-d51f669ed67f","date":"2024-03-23T08:32:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"dc478376-2032-41e5-9f8d-65c90fba8924","date":"2024-03-19T12:56:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-19T10:41:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-14T11:03:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-12T07:36:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Medical Research","date":"2024-03-11T07:23:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-medical-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejmr","sideBox":"Learn more about [European Journal of Medical Research](http://eurjmedres.biomedcentral.com)","snPcode":"40001","submissionUrl":"https://submission.nature.com/new-submission/40001/3","title":"European Journal of Medical Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f941e4d0-ffb5-48c0-9e4b-c12dd4c23c90","owner":[],"postedDate":"March 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-09T04:01:34+00:00","versionOfRecord":{"articleIdentity":"rs-4071308","link":"https://doi.org/10.1186/s40001-024-01869-6","journal":{"identity":"european-journal-of-medical-research","isVorOnly":false,"title":"European Journal of Medical Research"},"publishedOn":"2024-05-08 04:01:33","publishedOnDateReadable":"May 8th, 2024"},"versionCreatedAt":"2024-03-14 19:57:26","video":"","vorDoi":"10.1186/s40001-024-01869-6","vorDoiUrl":"https://doi.org/10.1186/s40001-024-01869-6","workflowStages":[]},"version":"v1","identity":"rs-4071308","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4071308","identity":"rs-4071308","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}