Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma

Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma | 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 Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma Liming Zhang, Shaoqiang Wang, Lina Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4728838/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Oct, 2024 Read the published version in BMC Cancer → Version 1 posted 4 You are reading this latest preprint version Abstract Background Lung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established. Methods TCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses. Results In LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC = 0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle. Conclusion Elevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD. lung adenocarcinoma (LUAD) YKT6 prognosis biomarker bioinformatics analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Lung cancer is the leading cause of cancer death in humans worldwide, as well as one of the top causes of cancer-related death in the respiratory system [ 1 ]. According to the different tissue types, lung cancer can be classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the latter accounting for about 85% of total lung cancer. Lung adenocarcinoma (LUAD) is the most common type of NSCLC, with 40% of all lung cancer [ 2 ]. With the popularity of computed tomography (CT) in early screening of lung cancer, the prognosis of patients with LUAD has been significantly improved, alongside the overall understanding of the early diagnosis and effective prevention strategies for early LUAD [ 3 , 4 ]. However, the onset of LUAD is hidden, and the majority of patients are in an advanced stage at the time of diagnosis. Thus, patients failed to undergo surgery, less sensitive to radiotherapy or chemotherapy, resulting in a 5-year survival rate of less than 15% [ 5 , 6 ]. In recent years, targeted therapy has achieved favorable consequences in lung cancer patients; however, its power to combat tumor progress is limited due to the current clinical treatment [ 7 ]. Therefore, it is very important to discover novel potential biomarkers for early diagnosis and prognosis evaluation of LUAD. YKT6 belongs to the soluble N-ethylmaleimide sensitivity factor attachment protein receptor (SNARE) family, with molecular weight 23 kDa [ 8 , 9 ]. YKT6 has no transmembrane domain, but with an N-terminal login domain and a C-terminal SNARE domain, which interacts to form a folded or closed conformation [ 10 ]. Studies have reported that YKT6 is related to vesicle transport, involved in the process of cell membrane fusion, as well as exosome formation and release, which is highly conserved in eukaryotes [ 11 ]. Yang et al . has found that YKT6 is highly expressed in oral squamous cell carcinoma (OSCC), related to the poor prognosis and can promote the invasion and metastasis of OSCC cells [ 12 ]. Previous research has shown that YKT6 is highly expressed in hepatocellular carcinoma (HCC), and its expression is significantly correlated with tumor size, microvascular invasion, and alpha-fetoprotein (AFP) level [ 13 ]. In addition, YKT6 was up-regulated in breast cancer with docetaxel-resistant P53 mutation, and knockdown of YKT6 could enhance DXT-induced apoptosis in breast cancer cells [ 14 ]. Based on the above evidence, it is speculated that YKT6 might play an important role in the occurrence, development, and drug resistance in many tumor types. However, the potential biological role of YKT6 in LUAD has not yet been reported until now. Thus, in our present study, the molecular characteristic analysis was performed to evaluate the potential function of YKT6 in the diagnosis and prognosis of LUAD. Moreover, the fundamental in vitro experiments were conducted to verify its biological function in lung cancer cells. Finally, gene-gene and protein-protein interaction (PPI) network and functional enrichment analyses were carried out to determine the function of YKT6 in LUAD. Therefore, this study indicates that YKT6 can function as a novel prognostic and diagnostic biomarker in LUAD. Materials and methods Expression of YKT6 mRNA in pan-cancer The Cancer Genome Atlas(TCGA)[ 15 ]database ( https://portal.gdc.cancer.gov/ ) is jointly established by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). A total of 36 cancer types are studied, including mutation, copy number variation, mRNA expression, miRNA expression, methylation, and other data. We downloaded and extracted the RNA-seq data of pan-cancer and LUAD from TCGA database, processed the data, excluded missing and repeated samples, statistically analyzed and visualized the results using the ggplot2 package, and analyzed the mRNA expression of YKT6 in pan-cancer and LUAD. Expression of YKT6 protein in LUAD The Human Protein Atlas (HPA) database [ 16 ]( https://www.proteinatlas.org/ ) uses transcriptome and proteomics methods to study protein expression in various human tissues and organs at mRNA and protein levels. HPA database was used to compare YKT6 protein levels in LUAD and para-cancerous tissues. Correlation between YKT6 expression and clinicopathological features UALCAN database[ 17 ]( http://ualcan.path.uab.edu/index.html ) is a website for tumor data analysis and mining, used to analyze the expression of related genes, clinical correlation, and prognosis. First, log into the UALCAN database, select “TCGA” module, enter “YKT6”, select “Lung adenocarcinoma”, click “Explore”, select “Expression” in the “Links for Analysis” module, and then analyze the correlation between YKT6 expression and tumor stage, lymph node metastasis, smoking, and TP53 mutation. Survival analysis of YKT6 in LUAD Download RNA-seq data and clinical information of LUAD project from TCGA database, exclude normal tissue and samples without clinical information, then analyze the data with the survival package, visualize the results with the survminer package and ggplot2 package, and finally explore the correlation between YKT6 expression and overall survival (OS), disease-specific survival (DSS), and progression free interval (PFI). Diagnostic value of YKT6 in LUAD The receiver operating characteristic (ROC) curve was drawn by R package pROC to analyze the RNA-seq data in FPKM format from LUAD project in TCGA database. The ggplot2 package was used for visualization. RNA extraction and qRT-PCR LUAD and para-cancerous tissues were freshly collected. None of the patients had received preoperative treatment. Informed consent was obtained from all participants prior to the study. The Ethics Committee of the Affiliated Hospital of Jining Medical University evaluated and approved this work (Approval number 2021-11-C009). The total RNA was extracted with TRIzol reagent, and RNA concentration was determined. The cDNA was obtained by reverse transcription by DNA synthesis kit HiScript III RT SuperMix for qPCR (+ gDNA wiper) for qRT-PCR. GAPDH was loaded as an internal reference, and the relative expression was calculated by the 2 −ΔΔCt method. The synthetic sequences of relevant primers are listed in Supplementary Table 1. Immunohistochemistry (IHC) and Tissue microarray (TMA) The LUAD and para-cancerous tissues were embedded in paraffin. Continuous 4 µm slices were dewaxing, plugging, incubating with the primary antibody (anti-YKT6, ab236583) overnight at 4°C; then adding the secondary antibody, incubating at room temperature for 2 hours, and analyzing the signal with an optical microscope. The human LUAD tissue microarray (ZL-Lug961) was provided by Shanghai Zhuoli Biotechnology Co., Ltd. (Shanghai, China), and the protein levels of YKT6 was assessed by the automated VisioMorph system (Visiopamm ®, Hoersholm, Denmark). Cell culture and siRNA transfection Human lung cancer cell lines (A549 and Calu-1) were kindly provided by Wuhan Pricella Biotechnology Co.,Ltd, which were cultured in a 37°C CO 2 incubator with RPMI-1640 medium plus 10% fetal bovine serum (FBS). Cells were incubated in a 6-well plate, and siRNA mixed with Lipofectamine 3000 were added into the medium for transfection. The YKT6 siRNA sequences are as follows: Si-1 (YKT6–Homo-684): S: GCUGGGAACACAGUCUAAATT AS: UUUAGACUGUGUUCCCAGCTT Si-2 (YKT6-Homo-257): S: CCAGCGUUCAGGAAUUCAUTT AS: AUGAAUUCCUGAACGCUGGTT Cell proliferation assay by Cell counting kit-8 (CCK-8) 2×10 3 cells were inoculated into a 96-well plate, and 10 µL CCK-8 solution was added to each well at 0 h, 24 h, 48 h, and 72 h, respectively, and incubated at 37°C for 2 hrs. The absorbance at 450 nm was analyzed with standard microplate readers (BioTek, Winsky, Vermont, USA). Scratch wound healing assay 5×10 5 cells per well were seeded in six-well plates. After covering the monolayer, the cells were scratched with the 10 µL tips and washed with PBS. The medium without FBS was added to continue the culture. The pictures were taken under a microscope at 0 hr and 24 hr, and analyzed by ImageJ software. Transwell assay 3×10 5 cells were inoculated and cultured in a six-well plate. 600 µl medium was added to the lower chamber, and 100 µl cells in serum-free RPMI-1640 medium were added to the upper chamber. After being cultured at 37 o C for 24, 36, and 48 hours, the chamber was inverted on absorbent paper to drain the medium, followed by rinsing with PBS. Then the chamber was fixed with 4% paraformaldehyde for 20 minutes, followed by staining with crystal violet (0.1%) for 15 minutes. Non-metastatic cells in the chamber were then removed by cotton swabs. Finally, images were captured under a microscope, and processed by ImageJ software. Detection of apoptosis after YKT6 silencing by flow cytometry 3×10 5 cells were cultured in a six-well plate. The two YKT6 siRNAs were utilized for cell transfection. Annexin V + apoptotic cells were detected 48 hours afterwards with flow cytometry. Construction of gene-gene and PPI Network with hub genes screening Gene-gene interaction network was constructed via GeneMANIA[ 18 ] ( http://genemania.org/ ). The cBioPortal database[ 19 ]( https://www.cbioportal.org/ ) integrates data of somatic mutation, DNA copy number change, mRNA and miRNA expression, protein and phosphoprotein abundance, which can perform mutation correlation analysis and visualization. First, we log into the database to select the top 100 positively correlated genes of YKT6 based on Spearman’s correlation. Then, STRING database ( https://cn.string-db.org ) [ 20 ] and Cytoscape (Version 3.9.0)[ 21 ] were utilized to build the PPI network and screen the top ten hub genes according to the degree scores. GO and KEGG enrichment analysis The DAVID website[ 22 , 23 ] ( https://david.ncifcrf.gov/ ) is a health information database with systematic biological function annotation information for a large number of genes and proteins. The selected top 100 YKT6-related genes were analyzed by GO and KEGG using the DAVID database to explore the possible biological process, cellular component, molecular function, and pathways involved. The Chiplot ( https://www.chiplot.online/#BioPlot ) website was used to visualize the enrichment analyses. GSEA Download the RNA-seq data and clinical information of LUAD project from TCGA database. Extract the expression data of the corresponding molecules, divide them into two groups according to the expression of the molecules, and use the DESeq2 package to analyze the single gene difference of the data. The data set comes from the MSigDB Collections database ( https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp ). Then, we use the org.hs.eg.db package for ID conversion of the differential genes and the clusterprofiler package for GSEA. Statistical method All the statistical data were analyzed by SPSS (Version 22.0) software. The data are expressed as mean ± standard deviation (SD). The differences between subgroups were compared using a 2-tail paired t -test. * P < 0.05 was considered to be statistically significant. Results The expression of YKT6 mRNA in pan-cancer and LUAD Firstly, we explored the expression of YKT6 mRNA in pan-cancer. The results showed that YKT6 was highly expressed in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), but low in thyroid carcinoma (THCA) (Fig. 1 A). In addition, the unpaired samples from TCGA and Genotype-tissue expression (GTEx) showed that YKT6 mRNA expression was significantly elevated in adrenocortical carcinoma (ACC), BLCA, BRCA, cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), CHOL, COAD, lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), ESCA, glioblastoma multiforme (GBM), HNSC, KICH, KIRP, brain lower grade glioma (LGG), LIHC, LUAD, LUSC, ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), PRAD, rectum adenocarcinoma (READ), skin cutaneous melanoma (SKCM), STAD, testicular germ cell tumors (TGCT), thymoma (THYM), UCEC, and uterine carcinosarcoma (UCS) (data not shown). Thus, YKT6 expressed highly in almost all the tumor types except acute myeloid leukemia (LAML) and THCA. Based on the unpaired and paired samples in TCGA and GTEx, YKT6 mRNA showed significantly elevated expression in LUAD (Figs. 1 B-C). HPA revealed that YKT6 protein was weakly stained or not detected in normal lung tissues, but moderately stained in LUAD tissues (Figs. 1 D-E). Therefore, YKT6 mRNA/protein expression in LUAD tissues is higher than that in normal lung tissues. Correlation between YKT6 expression and clinicopathological features UALCAN database showed that the expression of YKT6 was significantly correlated with LUAD clinical stage, lymph node metastasis, smoking, and the TP53 mutation (Figs. 2 A-D). To be precise, YKT6 mRNA expression showed relatively higher levels in Stage III, over 10 axillary lymph nodes metastases, and patients with TP53 mutation. Figure 2 . Relationship between YKT6 expression and clinical features in UALCAN. Prognostic and diagnostic value of YKT6 in LUAD The association between YKT6 expression and LUAD prognosis was examined using the transcriptome and clinical data from TCGA. There was a substantial correlation between high YKT6 expression and poor OS, DSS, and PFI (Figs. 3 A-C). The univariate and multivariate Cox regression revealed that YKT6 expression and TNM stage emerged as independent risk factors for the prognosis of LUAD patients (Figs. 3 D-E). Afterwards, a nomogram was created to predict the survival of LUAD patients (Fig. 3 F). Thus, YKT6 is an independent risk factor, and elevated YKT6 expression indicates adverse outcome in LUAD. In addition, the receiver operating characteristic (ROC) curve was utilized to determine the diagnostic ability of YKT6 in distinguishing tumor and normal samples. Notably, the area under the curve (AUC) value was up to 0.856, demonstrating high diagnostic value in LUAD patients (Fig. 3 G). Validation of the elevated expression of YKT6 in LUAD tissues Tissue samples from patients with LUAD were collected and performed qRT-PCR. Compared to para-cancerous tissues, YKT6 mRNA was expressed highly in LUAD tissue samples (Fig. 4 A). Immunohistochemical (IHC) staining and tissue microarray analysis (TMA) showed that YKT6 protein was significantly elevated in LUAD tissues (Figs. 4 B-F). Moreover, YKT6 mRNA expression was validated by GSE31547, GSE40791, and GSE43458. Consistently, in all these LUAD samples, YKT6 displayed obviously increased expression compared to normal groups (Figs. 4 G-I). Hence, the elevated expression of YKT6 was verified at both mRNA and protein levels by these external LUAD tissue samples. Knockdown of YKT6 inhibits cell proliferation and promotes apoptosis of lung cancer cells YKT6 mRNA expression was significantly reduced in A549 and Calu-1 cells upon silencing by siRNA transfection. Cell proliferation assay by CCK-8 showed that YKT6 knockdown inhibited A549 and Calu-1 cell proliferation (Figs. 5 A-B). In addition, the flow cytometry analysis revealed obviously increased Annexin V + cells after YKT6 silencing in A549 and Calu-1 cells (Fig. 5 C). Thus, YKT6 knockdown could inhibit cell proliferation and promote apoptosis of lung cancer cells. In order to explore the underlying molecular mechanism of YKT6 in LUAD, cell proliferation-related genes were examined after YKT6 knockdown. The results demonstrated that TGF-b, Ki-67, Hes1, Cyclin-B1, Cyclin-E2 and CDK9 expression was considerably suppressed upon silencing of YKT6 in these cells (Figs. 5 E-F). Based on these results, it is speculated that YKT6 might play a role through cell cycle related genes in LUAD. YKT6 silencing inhibits cell migration and invasion The scratch wound healing experiment demonstrated that cell migration ability was decreased upon YKT6 silencing in A549 and Calu-1 cells (Figs. 6 A-B). Similarly, Knockdown of YKT6 reduced cell capacity of invasion in the Transwell assay in A549 and Calu-1 cells (Fig. 6 C). Hence, YKT6 knockdown could inhibit cell migration and invasion of lung cancer cells. Thus, it is speculated that YKT6 might be involved in the regulation of cell migration via EMT-related factors. Consistently, the results demonstrated that EMT-related genes including Slug, Twist1, and Snail were remarkably decreased when YKT6 was knocked down in A549 and Calu-1 cells (Figs. 7 A-B). Moreover, YKT6 might play a role in LUAD through PLK1 pathway as demonstrated by GSEA (Fig. 7 C and Supplementary Fig. 1). TCGA database indicated that PLK1 was highly expressed in LUAD, with a strong positive correlation (R = 0.589) to YKT6 (Figs. 7 D-E). Meanwhile, the in vitro cellular function analysis showed an obvious PLK1 mRNA decrease upon YKT6 silencing in lung cancer cells (Figs. 7 F-G). Construction of gene-gene interaction and PPI Network with hub genes screening The YKT6-related gene-gene interaction network was created via Genemania (Fig. 8 A). The cBioPortal database was used to obtain YKT6 related genes and the top 100 genes were selected based on the Spearman values (Supplementary Table 2). Subsequently, the STRING database was used to construct PPI network and the top ten hub genes were screened as follows: CDC20, PLK1, CDCA8, TPX2, KIF2C, KIF23, KIF4A, FOXM1, MCM7 and CDCA5 (Fig. 8 B). Additionally, TCGA data and clinical information showed that the selected ten hub genes were all highly expressed in LUAD (Supplementary Fig. 2), with relation to poor prognosis of LUAD patients (Supplementary Fig. 3). GO and KEGG enrichment analyses of YKT6 and related genes GO and KEGG enrichment analyses were conducted through the DAVID database to explore the potential biological functions of YKT6 and its co-expressed genes. They were mainly involved in cell division, DNA repair, mitosis, and cell cycle (Fig. 8 C), primarily located in nuclear cytoplasm, cytoplasm, cell membrane, and mitochondria (Fig. 8 D). Their major molecular functions including protein binding, ATP enzyme activity, and ATP binding (Fig. 8 E), with potential mechanisms through cell cycle, cell senescence, and p53 signal pathway (Fig. 8 F). Based on these findings, there is reason to propose that the crucial biological role of YKT6 in LUAD might be mainly involved in cell cycle. Discussion Lung cancer is one of the most common causes of cancer-related death worldwide [ 24 ]. Among them, LUAD is the major histological subtype of lung cancer, with incidence increasing year by year [ 25 ]. However, the outcome for LUAD patients is far from satisfaction due to the delay in early diagnosis [ 26 ]. Although radiotherapy, chemotherapy, surgery, and targeted therapy has significantly improved the survival rate of LUAD patients, it remains a serious global public health issue [ 27 ]. Therefore, it is urgent to find new diagnostic biomarkers and therapeutic targets for LUAD. SNARE proteins are composed of 20–30 kDa proteins with a homologous domain of 60–70 amino acid residues [ 28 ]. SNARE proteins can be divided into Q-SNARE and R-SNARE based on difference in amino acid residues. In mammals, the SNARE family consists of more than 30 members with different subcellular localizations and forms specific SNARE complexes to regulate various cellular biological processes [ 29 ]. YKT6 belongs to R-SNARE protein family, highly conserved from yeast to humans[ 11 ]. YKT6 has been reported to be involved in vesicular transport, secretory, endocytosis, autophagy, and the formation and release of exocrine bodies [ 30 ]. Moreover, YKT6 is related to tumor progression; however, there are few research report on YKT6 in LUAD. In this study, bioinformatics analysis and cell function assays were used to explore the expression, prognosis, and possible biological roles of YKT6 in LUAD. In the present study, YKT6 mRNA/protein was highly expressed in LUAD, correlated with clinical stage, lymph node metastasis, smoking history, and TP53 mutation in LUAD. YKT6 expression showed the highest in clinical stage III and lymph node metastasis stage IV, suggesting an important role in middle and late stages of LUAD. Thus, YKT6 may be used as a potential indicator of LUAD stages. Besides, compared to the expression in TP53-non-mutated LUAD samples, YKT6 showed elevated level in TP53-mutated tissues. Therefore, YKT6 might play an important role in the progression of LUAD through the TP53 pathway. In addition, YKT6 was significantly correlated with OS, DSS and PFI, suggesting a potential prognostic biomarker of LUAD. Among the top ten hub genes (CDC20, PLK1, CDCA8, TPX2, KIF2C, KIF23, KIF4A, FOXM1, MCM7 and CDCA5) selected of YKT6 co-related genes, cell division cycle 20 (CDC20) promotes the resistance of glioblastoma (GBM) cells to chemotherapy and radiotherapy, while knockout of CDC20 can enhance the sensitivity of GBM cells to radiotherapy and chemotherapy by regulating the pro-apoptotic protein Bim [ 31 ].The polo-like kinase 1 (PLK1) is a serine/threonine protein kinase with a key role in eukaryotic cell division, DNA replication, and TP53 regulation [ 32 ]. PLK1 can promote the progress of Kras/TP53-mutated LUAD by regulating the transcriptional activation receptor RET [ 33 ]. In addition, PLK1 is overexpressed in hepatocellular carcinoma (HCC), related to tumor invasiveness and poor prognosis [ 34 ]. Cell division cycle-related genes 8 (CDCA8) and CDCA5 belong to the family of cell division cycle related genes. Studies have shown that miR-133a-3p can target CDCA8 and inhibit the progress of ESCA [ 35 ]. TPX2 can enhance the expression of cyclin-dependent kinase-1 (CDK1) in PRAD, then promote the phosphorylation of the ERK/GSK3b/Snail pathway, and finally EMT[ 36 ]. Kinesin family protein 2C (KIF2C), also known as mitotic centromere-associated driving protein, encodes proteins in microtubule depolymerization, thus promoting chromosome separation during mitosis. KIF2C is highly expressed in HCC, related to tumor histological grade, pathological stage, and poor prognosis. In addition, KIF2C can promote the progression of HCC by activating the renin-angiotensin system (RAS)/mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB) signaling pathways [ 37 ]. Kinesin family member 23 (KIF23) is a member of the Kinesin family, highly expressed in triple-negative breast cancer (TNBC). Silencing of KIF23 expression can inhibit the proliferation and migration of the TNBC cells [ 38 ]. Recent research has demonstrated that KIF4A expression is up-regulated in LUAD and correlates with the prognosis of the patients [ 39 ]. Additionally, it has been reported that miR-877-5p could inhibit cell growth by directly targeting FOXM1, potentially furnishing a promising biomarker for targeted therapy in NSCLC [ 40 ]. MCM7 belongs to the small chromosome maintenance protein family, with a pivotal role in DNA replication and proliferation in eukaryotic cells. Several studies indicated that receptor for activated C kinase1 (RACK1) could modulate the growth and cell cycle progression of human NSCLC cells through MCM7 phosphorylation mediated by the MCM7/RACK1/Akt signal complex [ 41 ]. CDCA5 plays an important role in the occurrence and development of many kinds of cancers by regulating cell cycle. CDCA5 is highly expressed in breast cancer tissues and cell lines. CDCA5 deletion can inhibit cell proliferation, invasion, and migration. Hence, CDCA5 can be used as a prognostic biomarker and therapeutic target for breast cancer [ 42 ]. Thus, the above YKT6-related hub genes are all correlated to tumor progression and prognosis, with functions on tumor cell proliferation, invasion or migration. Enrichment analysis of YKT6 and its related genes showed the main physiological functions were cell division, mitosis, and the cell cycle. Consistently, the hub genes screened were mainly cell cycle-related. YKT6 may play a role in LUAD through PLK1 and TP53 pathways as demonstrated by GSEA. In addition, it is mentioned above that PLK1 can promote the progress of LUAD with K-ras/TP53 mutation by regulating the transcriptional activation receptor RET. Thus, there may exist certain relationship between YKT6 and PLK1 in the occurrence and development of LUAD, which needs further verification. In recent years, tumor immune escape has been the focus of anti-tumor therapy. Numerous immune cells including macrophage, T cell, and NK cell constitute the tumor microenvironment. These cells directly or indirectly affect the microenvironment of tumor cells and regulate their biological behaviors. Therefore, immune cell therapy has a broad application prospect in the treatment of LUAD. YKT6 is related to immune cell infiltration in LUAD (data not shown). The increased infiltration of immune cells is accompanied by elevated YKT6 expression, providing the foundation for effective immunotherapy. Thus, the findings have provided novel insights into immunotherapy for patients with LUAD. To sum up, our present study shows that YKT6 is supported as a potential new biomarker of LUAD. However, it is not clear how YKT6 regulates the occurrence and development of LUAD. Further research and clinical verification are needed to explore the underlying molecular mechanism of YKT6 in the initiation and treatment of LUAD. Conclusion Collectively, this study comprehensively shows the elevated expression of YKT6 in LUAD, and its correlation to the poor prognosis of LUAD patients. It is expected to be a novel prognostic and diagnostic biomarker in LUAD. Declarations Supplementary Information The online version contains supplementary material available at XXXXXXXXXX. Acknowledgements The authors gratefully acknowledge contributions from the TCGA network the authors listed in this manuscript Author contributions Liming Zhang, Shaoqiang Wang and Lina Wang designed and performed bioinformatics analysis. Liming Zhang and Lina Wang analyzed the data and organized pictures. Liming Zhang, Lina Wang and Shaoqiang Wang wrote and revised the paper. All authors read and approved the final version of the manuscript. Funding This work was supported by the National Natural Science Foundation of China (81800182, 81802290). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data availability Publicly available datasets were analyzed in this study. All data generated in the study are included in the present article and supplementary data. Conflict of interest The authors declare that they have no competing interests relating to the publication of this manuscript. Consent for publication The work has not been published previously, and it is not under consideration for publication elsewhere. Ethics approval Not applicable. References H. Sung, J. Ferlay, R.L. Siegel, M. Laversanne, I. Soerjomataram, A. Jemal, F. Bray, Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries, CA Cancer J Clin, 71 (2021) 209-249. J. Rodriguez-Canales, E. 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Henning, A. Bhattacharya, H. Mancilla, P. Sánchez-Martín, C. Kraft, Atg1 kinase regulates autophagosome-vacuole fusion by controlling SNARE bundling, EMBO Rep, 21 (2020) e51869. D.D. Mao, R.T. Cleary, A. Gujar, T. Mahlokozera, A.H. Kim, CDC20 regulates sensitivity to chemotherapy and radiation in glioblastoma stem cells, PLoS One, 17 (2022) e0270251. X.S. Liu, B. Song, X. Liu, The substrates of Plk1, beyond the functions in mitosis, Protein Cell, 1 (2010) 999-1010. Y. Kong, D.B. Allison, Q. Zhang, D. He, Y. Li, F. Mao, C. Li, Z. Li, Y. Zhang, J. Wang, C. Wang, C.F. Brainson, X. Liu, The kinase PLK1 promotes the development of Kras/Tp53-mutant lung adenocarcinoma through transcriptional activation of the receptor RET, Sci Signal, 15 (2022) eabj4009. Z.L. He, H. Zheng, H. Lin, X.Y. Miao, D.W. Zhong, Overexpression of polo-like kinase1 predicts a poor prognosis in hepatocellular carcinoma patients, World J Gastroenterol, 15 (2009) 4177-4182. X. Wang, L. Zhu, X. Lin, Y. Huang, Z. Lin, MiR-133a-3p inhibits the malignant progression of oesophageal cancer by targeting CDCA8, J Biochem, 170 (2022) 689-698. B. Zhang, M. Zhang, Q. Li, Y. Yang, Z. Shang, J. Luo, TPX2 mediates prostate cancer epithelial-mesenchymal transition through CDK1 regulated phosphorylation of ERK/GSK3β/SNAIL pathway, Biochem Biophys Res Commun, 546 (2021) 1-6. S. Mo, D. Fang, S. Zhao, P.T. Thai Hoa, C. Zhou, T. Liang, Y. He, T. Yu, Y. Chen, W. Qin, Q. Han, H. Su, G. Zhu, X. Luo, T. Peng, C. Han, Down regulated oncogene KIF2C inhibits growth, invasion, and metastasis of hepatocellular carcinoma through the Ras/MAPK signaling pathway and epithelial-to-mesenchymal transition, Ann Transl Med, 10 (2022) 151. W. Jian, X.C. Deng, A. Munankarmy, O. Borkhuu, C.L. Ji, X.H. Wang, W.F. Zheng, Y.H. Yu, X.Q. Zhou, L. Fang, KIF23 promotes triple negative breast cancer through activating epithelial-mesenchymal transition, Gland Surg, 10 (2021) 1941-1950. Y. Song, W. Tang, H. Li, Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis, Biosci Rep, 41 (2021). Z. Liu, X. Wang, L. Cao, X. Yin, Q. Zhang, L. Wang, MicroRNA-877-5p Inhibits Cell Progression by Targeting FOXM1 in Lung Cancer, Can Respir J, 2022 (2022) 4256172. L. Fei, Y. Ma, M. Zhang, X. Liu, Y. Luo, C. Wang, H. Zhang, W. Zhang, Y. Han, RACK1 promotes lung cancer cell growth via an MCM7/RACK1/ Akt signaling complex, Oncotarget, 8 (2017) 40501-40513. H. Hu, Y. Xiang, X.Y. Zhang, Y. Deng, F.J. Wan, Y. Huang, X.H. Liao, T.C. Zhang, CDCA5 promotes the progression of breast cancer and serves as a potential prognostic biomarker, Oncol Rep, 48 (2022). Supplementary Information Supplementary Information is not available with this version. Supplementary Figure 1. GSEA of YKT6 DEGs in LUAD. Supplementary Figure 2. The mRNA expression of the ten selected hub genes in LUAD based on TCGA database. (A) CDC20. (B) PLK1. (C) CDCA8. (D) TPX2. (E) KIF2C. (F) KIF23. (G) KIF4A. (H) FOXM1. (I) MCM7. (J) CDCA5. Supplementary Figure 3. The prognosis of the ten selected hub genes in LUAD from Kaplan-Meier plotter. (A) CDC20. (B) PLK1. (C) CDCA8. (D) TPX2. (E) KIF2C. (F) KIF23. (G) KIF4A. (H) FOXM1. (I) MCM7. (J) CDCA5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 Oct, 2024 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 17 Jul, 2024 Editor assigned by journal 15 Jul, 2024 Submission checks completed at journal 15 Jul, 2024 First submitted to journal 12 Jul, 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-4728838","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328042148,"identity":"1fd95239-6e96-4fe1-9b0d-5463a1959a44","order_by":0,"name":"Liming Zhang","email":"","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining Medical University","correspondingAuthor":false,"prefix":"","firstName":"Liming","middleName":"","lastName":"Zhang","suffix":""},{"id":328042149,"identity":"baee7724-26bf-4c54-9f17-39b731b21859","order_by":1,"name":"Shaoqiang Wang","email":"","orcid":"","institution":"Weifang People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shaoqiang","middleName":"","lastName":"Wang","suffix":""},{"id":328042150,"identity":"80da4825-d9b9-4da1-b205-575e59617c21","order_by":2,"name":"Lina Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYLCCBwYgkofhAAODDQ8/fwMRWhIQWtJkJGccIEYLA0QLEBy2MWhIwK/a4PjZwy8SCu7IM7CfPXi4oOY8jwHDAcYPH3PwaDmTl2aRYPDMsIEnL+HwjGO3ecyZG5glZ27DrcXsQI6ZQYLBYcYGCR6Dwzxst3ksGw6wMfPi03L+DViLPUTLv3M8BgcSCGi5kWP8AKglEayFt+0AYS32N96YAQP5cHIDTw5QS18yj+SMg814/SLZn2P84cOfw7YN7GeMP/N8s7Pn528++OEjHi1AwCYBtu4AXICxAa96IGD+QEjFKBgFo2AUjHAAADGOVASXeJUWAAAAAElFTkSuQmCC","orcid":"","institution":"Affiliated Hospital of Jining Medical University, Jining Medical University","correspondingAuthor":true,"prefix":"","firstName":"Lina","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-07-12 08:06:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4728838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4728838/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-024-12975-3","type":"published","date":"2024-10-07T15:57:45+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62631490,"identity":"ad57269b-e0bd-4888-87fd-e1d5f0e3bda1","added_by":"auto","created_at":"2024-08-16 16:04:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":213134,"visible":true,"origin":"","legend":"\u003cp\u003eThe mRNA and protein expression of YKT6 in LUAD based on TCGA.\u003c/p\u003e\n\u003cp\u003e(A) Expression of YKT6 mRNA in paired tissues of pan-cancer in TCGA. (B)-(C) YKT6 mRNA expression in unpaired and paired LUAD tissues. (D)-(E) YKT6 protein levels in LUAD of HPA.\u003c/p\u003e","description":"","filename":"floatimage1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/af446cbf1ab2a4c22cc4c202.jpg"},{"id":62630349,"identity":"0fb8998c-fbb9-4ea9-b3a0-a6d11eb2e3f7","added_by":"auto","created_at":"2024-08-16 15:56:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":208130,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between YKT6 expression and clinical features in UALCAN.\u003c/p\u003e\n\u003cp\u003eCorrelation of YKT6 mRNA expression with clinical stage (A), lymph node metastasis (B), smoking history (C) and TP53 mutation (D).\u003c/p\u003e","description":"","filename":"floatimage2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/fbdb1ba970a3fb57ec04a3ed.jpg"},{"id":62632457,"identity":"8951a54f-9f83-4931-b112-faa12e303435","added_by":"auto","created_at":"2024-08-16 16:12:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":351993,"visible":true,"origin":"","legend":"\u003cp\u003ePrognostic and diagnostic value of YKT6 in LUAD.\u003c/p\u003e\n\u003cp\u003e(A)-(C) The relationship between YKT6 mRNA expression and OS, DSS and PFI in LUAD patients. (D)-(E) The univariate and multivariate Cox analysis of YKT6 in LUAD. (F) Nomogram of YKT6 in LUAD. (G) ROC curve of YKT6 in LUAD.\u003c/p\u003e","description":"","filename":"floatimage3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/1b17e4a719fda0b7f40026ba.jpg"},{"id":62630350,"identity":"e1ca1339-070d-4652-a07f-ab520e67d18c","added_by":"auto","created_at":"2024-08-16 15:56:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":448058,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of YKT6 expression by LUAD tissues and GEO.\u003c/p\u003e\n\u003cp\u003e(A) Detection of YKT6 mRNA expression in LUAD by qRT-PCR. (B)-(C) The representative immunohistochemistry staining of YKT6 in LUAD. (D) Tissue microarray analysis of YKT6 expression in LUAD and normal tissues. (E) The representative IHC staining of YKT6 in LUAD and para-cancerous tissues. (F) YKT6 staining was analyzed by H-score in LUAD and para-cancerous tissues. (G)-(I) YKT6 mRNA expression in GSE31547, GSE40791, and GSE43458.\u003c/p\u003e","description":"","filename":"floatimage4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/2f1111264b463a8f63f13ce2.jpg"},{"id":62633215,"identity":"db0bef66-03f9-41e0-887e-4c8dbe976ecd","added_by":"auto","created_at":"2024-08-16 16:20:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":419979,"visible":true,"origin":"","legend":"\u003cp\u003eKnockdown of YKT6 inhibits proliferation and facilitates apoptosis of LUAD cells.\u003c/p\u003e\n\u003cp\u003eCell proliferation was inhibited in A549 (A) and Calu-1(B) cells detected by CCK-8 assay after YKT6 silencing.\u003c/p\u003e\n\u003cp\u003e(C)-(D) Increased Annexin V+ apoptotic cells in A549 and Calu-1cells analyzed by flow cytometry upon YKT6 knockdown. (E)-(F) The mRNA expression of TGF-b, Ki-67, Hes1, Cyclin-B1, Cylin-E2 and CDK9 was verified after YKT6 was knocked down in A549 and Calu-1 cells by qRT-PCR.\u003c/p\u003e","description":"","filename":"floatimage5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/3baab0c9b4564e4920165223.jpg"},{"id":62633213,"identity":"a5d3f5ed-d715-46fa-a4ab-268d46b0ae52","added_by":"auto","created_at":"2024-08-16 16:20:22","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":387795,"visible":true,"origin":"","legend":"\u003cp\u003eYKT6 silencing attenuates migration and invasion of lung cancer cells.\u003c/p\u003e\n\u003cp\u003eScratch wound healing assay to determine the migration ability of A549 (A-B) and Calu-1(C-D) cells after YKT6 silencing. (E)-(F) The impaired invasive ability of A549 and Calu-1 cells was detected by Transwell assay.\u003c/p\u003e","description":"","filename":"floatimage6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/79ccf5ad817f32bc6a745fef.jpg"},{"id":62630354,"identity":"fefd145e-7ba3-48ab-8c89-299c850a4d46","added_by":"auto","created_at":"2024-08-16 15:56:22","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":331084,"visible":true,"origin":"","legend":"\u003cp\u003eKnockdown of YKT6 inhibits the expression of EMT-related genes and PLK1.\u003c/p\u003e\n\u003cp\u003eThe expression of Slug, Twist1, and Snail was verified upon YKT6 silencing in A549 (A) and Calu-1 (B) cells by qRT-PCR. (C) PLK1 pathway was screened out by GSEA of differentially expressed genes (DEGs) of YKT6 in LUAD. (D) Expression of PLK1 mRNA in paired LUAD tissues based on TCGA database. (E) The scatter plot of the correlation between YKT6 and PLK1 in LUAD of TCGA. (F)-(G) PLK1 mRNA expression was decreased upon YKT6 silencing in A549 and Calu-1 cells detected by qRT-PCR.\u003c/p\u003e","description":"","filename":"floatimage7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/91243bfae3c551028d68c12c.jpg"},{"id":62630355,"identity":"76b3af12-4f86-42c4-812e-85a23f7a4831","added_by":"auto","created_at":"2024-08-16 15:56:23","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":540228,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated analysis of gene-gene network, PPI and functional enrichmentanalysis of YKT6 and its related genes. (A) Creation of gene-gene network via Genemania. (B) PPI Network of YKT6 and related genes. (C) Biological process, (D) Cellular component, (E) Molecular function, and (F) KEGG pathway of YKT6 and its related genes.\u003c/p\u003e","description":"","filename":"floatimage8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/aecff27559cb3bcd51c3a9ce.jpg"},{"id":66597202,"identity":"31a71fa4-5878-4d2c-9d0a-ff22af82ea04","added_by":"auto","created_at":"2024-10-14 16:08:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3594620,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4728838/v1/5917fac3-232e-4238-872e-57a13ac0c171.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLung cancer is the leading cause of cancer death in humans worldwide, as well as one of the top causes of cancer-related death in the respiratory system [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the different tissue types, lung cancer can be classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), the latter accounting for about 85% of total lung cancer. Lung adenocarcinoma (LUAD) is the most common type of NSCLC, with 40% of all lung cancer [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. With the popularity of computed tomography (CT) in early screening of lung cancer, the prognosis of patients with LUAD has been significantly improved, alongside the overall understanding of the early diagnosis and effective prevention strategies for early LUAD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the onset of LUAD is hidden, and the majority of patients are in an advanced stage at the time of diagnosis. Thus, patients failed to undergo surgery, less sensitive to radiotherapy or chemotherapy, resulting in a 5-year survival rate of less than 15% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In recent years, targeted therapy has achieved favorable consequences in lung cancer patients; however, its power to combat tumor progress is limited due to the current clinical treatment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, it is very important to discover novel potential biomarkers for early diagnosis and prognosis evaluation of LUAD.\u003c/p\u003e \u003cp\u003eYKT6 belongs to the soluble N-ethylmaleimide sensitivity factor attachment protein receptor (SNARE) family, with molecular weight 23 kDa [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. YKT6 has no transmembrane domain, but with an N-terminal login domain and a C-terminal SNARE domain, which interacts to form a folded or closed conformation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Studies have reported that YKT6 is related to vesicle transport, involved in the process of cell membrane fusion, as well as exosome formation and release, which is highly conserved in eukaryotes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Yang \u003cem\u003eet al\u003c/em\u003e. has found that YKT6 is highly expressed in oral squamous cell carcinoma (OSCC), related to the poor prognosis and can promote the invasion and metastasis of OSCC cells [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Previous research has shown that YKT6 is highly expressed in hepatocellular carcinoma (HCC), and its expression is significantly correlated with tumor size, microvascular invasion, and alpha-fetoprotein (AFP) level [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition, YKT6 was up-regulated in breast cancer with docetaxel-resistant P53 mutation, and knockdown of YKT6 could enhance DXT-induced apoptosis in breast cancer cells [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Based on the above evidence, it is speculated that YKT6 might play an important role in the occurrence, development, and drug resistance in many tumor types. However, the potential biological role of YKT6 in LUAD has not yet been reported until now.\u003c/p\u003e \u003cp\u003eThus, in our present study, the molecular characteristic analysis was performed to evaluate the potential function of YKT6 in the diagnosis and prognosis of LUAD. Moreover, the fundamental \u003cem\u003ein vitro\u003c/em\u003e experiments were conducted to verify its biological function in lung cancer cells. Finally, gene-gene and protein-protein interaction (PPI) network and functional enrichment analyses were carried out to determine the function of YKT6 in LUAD. Therefore, this study indicates that YKT6 can function as a novel prognostic and diagnostic biomarker in LUAD.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExpression of YKT6 mRNA in pan-cancer\u003c/h2\u003e \u003cp\u003eThe Cancer Genome Atlas(TCGA)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e is jointly established by the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). A total of 36 cancer types are studied, including mutation, copy number variation, mRNA expression, miRNA expression, methylation, and other data. We downloaded and extracted the RNA-seq data of pan-cancer and LUAD from TCGA database, processed the data, excluded missing and repeated samples, statistically analyzed and visualized the results using the ggplot2 package, and analyzed the mRNA expression of YKT6 in pan-cancer and LUAD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExpression of YKT6 protein in LUAD\u003c/h2\u003e \u003cp\u003eThe Human Protein Atlas (HPA) database [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e](\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.proteinatlas.org/\u003c/span\u003e\u003cspan address=\"https://www.proteinatlas.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e uses transcriptome and proteomics methods to study protein expression in various human tissues and organs at mRNA and protein levels. HPA database was used to compare YKT6 protein levels in LUAD and para-cancerous tissues.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCorrelation between YKT6 expression and clinicopathological features\u003c/h2\u003e \u003cp\u003eUALCAN database[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e](\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ualcan.path.uab.edu/index.html\u003c/span\u003e\u003cspan address=\"http://ualcan.path.uab.edu/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e is a website for tumor data analysis and mining, used to analyze the expression of related genes, clinical correlation, and prognosis. First, log into the UALCAN database, select \u0026ldquo;TCGA\u0026rdquo; module, enter \u0026ldquo;YKT6\u0026rdquo;, select \u0026ldquo;Lung adenocarcinoma\u0026rdquo;, click \u0026ldquo;Explore\u0026rdquo;, select \u0026ldquo;Expression\u0026rdquo; in the \u0026ldquo;Links for Analysis\u0026rdquo; module, and then analyze the correlation between YKT6 expression and tumor stage, lymph node metastasis, smoking, and TP53 mutation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSurvival analysis of YKT6 in LUAD\u003c/h2\u003e \u003cp\u003eDownload RNA-seq data and clinical information of LUAD project from TCGA database, exclude normal tissue and samples without clinical information, then analyze the data with the survival package, visualize the results with the survminer package and ggplot2 package, and finally explore the correlation between YKT6 expression and overall survival (OS), disease-specific survival (DSS), and progression free interval (PFI).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic value of YKT6 in LUAD\u003c/h2\u003e \u003cp\u003eThe receiver operating characteristic (ROC) curve was drawn by R package pROC to analyze the RNA-seq data in FPKM format from LUAD project in TCGA database. The ggplot2 package was used for visualization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and qRT-PCR\u003c/h2\u003e \u003cp\u003eLUAD and para-cancerous tissues were freshly collected. None of the patients had received preoperative treatment. Informed consent was obtained from all participants prior to the study. The Ethics Committee of the Affiliated Hospital of Jining Medical University evaluated and approved this work (Approval number 2021-11-C009). The total RNA was extracted with TRIzol reagent, and RNA concentration was determined. The cDNA was obtained by reverse transcription by DNA synthesis kit HiScript III RT SuperMix for qPCR (+\u0026thinsp;gDNA wiper) for qRT-PCR. GAPDH was loaded as an internal reference, and the relative expression was calculated by the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. The synthetic sequences of relevant primers are listed in Supplementary Table\u0026nbsp;1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry (IHC) and Tissue microarray (TMA)\u003c/h2\u003e \u003cp\u003eThe LUAD and para-cancerous tissues were embedded in paraffin. Continuous 4 \u0026micro;m slices were dewaxing, plugging, incubating with the primary antibody (anti-YKT6, ab236583) overnight at 4\u0026deg;C; then adding the secondary antibody, incubating at room temperature for 2 hours, and analyzing the signal with an optical microscope. The human LUAD tissue microarray (ZL-Lug961) was provided by Shanghai Zhuoli Biotechnology Co., Ltd. (Shanghai, China), and the protein levels of YKT6 was assessed by the automated VisioMorph system (Visiopamm \u0026reg;, Hoersholm, Denmark).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCell culture and siRNA transfection\u003c/h2\u003e \u003cp\u003eHuman lung cancer cell lines (A549 and Calu-1) were kindly provided by Wuhan Pricella Biotechnology Co.,Ltd, which were cultured in a 37\u0026deg;C CO\u003csub\u003e2\u003c/sub\u003e incubator with RPMI-1640 medium plus 10% fetal bovine serum (FBS). Cells were incubated in a 6-well plate, and siRNA mixed with Lipofectamine 3000 were added into the medium for transfection. The YKT6 siRNA sequences are as follows:\u003c/p\u003e \u003cp\u003eSi-1 (YKT6\u0026ndash;Homo-684): S: GCUGGGAACACAGUCUAAATT\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAS: UUUAGACUGUGUUCCCAGCTT\u003c/h2\u003e \u003cp\u003eSi-2 (YKT6-Homo-257): S: CCAGCGUUCAGGAAUUCAUTT\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAS: AUGAAUUCCUGAACGCUGGTT\u003c/h2\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eCell proliferation assay by Cell counting kit-8 (CCK-8)\u003c/h2\u003e \u003cp\u003e2\u0026times;10\u003csup\u003e3\u003c/sup\u003e cells were inoculated into a 96-well plate, and 10 \u0026micro;L CCK-8 solution was added to each well at 0 h, 24 h, 48 h, and 72 h, respectively, and incubated at 37\u0026deg;C for 2 hrs. The absorbance at 450 nm was analyzed with standard microplate readers (BioTek, Winsky, Vermont, USA).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eScratch wound healing assay\u003c/h2\u003e \u003cp\u003e5\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells per well were seeded in six-well plates. After covering the monolayer, the cells were scratched with the 10 \u0026micro;L tips and washed with PBS. The medium without FBS was added to continue the culture. The pictures were taken under a microscope at 0 hr and 24 hr, and analyzed by ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eTranswell assay\u003c/h2\u003e \u003cp\u003e3\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were inoculated and cultured in a six-well plate. 600 \u0026micro;l medium was added to the lower chamber, and 100 \u0026micro;l cells in serum-free RPMI-1640 medium were added to the upper chamber. After being cultured at 37\u003csup\u003eo\u003c/sup\u003eC for 24, 36, and 48 hours, the chamber was inverted on absorbent paper to drain the medium, followed by rinsing with PBS. Then the chamber was fixed with 4% paraformaldehyde for 20 minutes, followed by staining with crystal violet (0.1%) for 15 minutes. Non-metastatic cells in the chamber were then removed by cotton swabs. Finally, images were captured under a microscope, and processed by ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDetection of apoptosis after YKT6 silencing by flow cytometry\u003c/h2\u003e \u003cp\u003e3\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells were cultured in a six-well plate. The two YKT6 siRNAs were utilized for cell transfection. Annexin V\u003csup\u003e+\u003c/sup\u003e apoptotic cells were detected 48 hours afterwards with flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of gene-gene and PPI Network with hub genes screening\u003c/h2\u003e \u003cp\u003eGene-gene interaction network was constructed via GeneMANIA[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://genemania.org/\u003c/span\u003e\u003cspan address=\"http://genemania.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The cBioPortal database[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e](\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e integrates data of somatic mutation, DNA copy number change, mRNA and miRNA expression, protein and phosphoprotein abundance, which can perform mutation correlation analysis and visualization. First, we log into the database to select the top 100 positively correlated genes of YKT6 based on Spearman\u0026rsquo;s correlation. Then, STRING database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and Cytoscape (Version 3.9.0)[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] were utilized to build the PPI network and screen the top ten hub genes according to the degree scores.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGO and KEGG enrichment analysis\u003c/h2\u003e \u003cp\u003eThe DAVID website[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e is a health information database with systematic biological function annotation information for a large number of genes and proteins. The selected top 100 YKT6-related genes were analyzed by GO and KEGG using the DAVID database to explore the possible biological process, cellular component, molecular function, and pathways involved. The Chiplot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.chiplot.online/#BioPlot\u003c/span\u003e\u003cspan address=\"https://www.chiplot.online/#BioPlot\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e website was used to visualize the enrichment analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eGSEA\u003c/h2\u003e \u003cp\u003eDownload the RNA-seq data and clinical information of LUAD project from TCGA database. Extract the expression data of the corresponding molecules, divide them into two groups according to the expression of the molecules, and use the DESeq2 package to analyze the single gene difference of the data. The data set comes from the MSigDB Collections database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gsea-msigdb.org/gsea/msigdb/collections.jsp\u003c/span\u003e\u003cspan address=\"https://www.gsea-msigdb.org/gsea/msigdb/collections.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Then, we use the org.hs.eg.db package for ID conversion of the differential genes and the clusterprofiler package for GSEA.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eStatistical method\u003c/h2\u003e \u003cp\u003eAll the statistical data were analyzed by SPSS (Version 22.0) software. The data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). The differences between subgroups were compared using a 2-tail paired \u003cem\u003et\u003c/em\u003e-test. *\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05 was considered to be statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eThe expression of YKT6 mRNA in pan-cancer and LUAD\u003c/h2\u003e \u003cp\u003eFirstly, we explored the expression of YKT6 mRNA in pan-cancer. The results showed that YKT6 was highly expressed in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC), but low in thyroid carcinoma (THCA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In addition, the unpaired samples from TCGA and Genotype-tissue expression (GTEx) showed that YKT6 mRNA expression was significantly elevated in adrenocortical carcinoma (ACC), BLCA, BRCA, cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), CHOL, COAD, lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), ESCA, glioblastoma multiforme (GBM), HNSC, KICH, KIRP, brain lower grade glioma (LGG), LIHC, LUAD, LUSC, ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), PRAD, rectum adenocarcinoma (READ), skin cutaneous melanoma (SKCM), STAD, testicular germ cell tumors (TGCT), thymoma (THYM), UCEC, and uterine carcinosarcoma (UCS) (data not shown). Thus, YKT6 expressed highly in almost all the tumor types except acute myeloid leukemia (LAML) and THCA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBased on the unpaired and paired samples in TCGA and GTEx, YKT6 mRNA showed significantly elevated expression in LUAD (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). HPA revealed that YKT6 protein was weakly stained or not detected in normal lung tissues, but moderately stained in LUAD tissues (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-E). Therefore, YKT6 mRNA/protein expression in LUAD tissues is higher than that in normal lung tissues.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eCorrelation between YKT6 expression and clinicopathological features\u003c/h2\u003e \u003cp\u003eUALCAN database showed that the expression of YKT6 was significantly correlated with LUAD clinical stage, lymph node metastasis, smoking, and the TP53 mutation (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-D). To be precise, YKT6 mRNA expression showed relatively higher levels in Stage III, over 10 axillary lymph nodes metastases, and patients with TP53 mutation. \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Relationship between YKT6 expression and clinical features in UALCAN.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic and diagnostic value of YKT6 in LUAD\u003c/h2\u003e \u003cp\u003eThe association between YKT6 expression and LUAD prognosis was examined using the transcriptome and clinical data from TCGA. There was a substantial correlation between high YKT6 expression and poor OS, DSS, and PFI (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-C). The univariate and multivariate Cox regression revealed that YKT6 expression and TNM stage emerged as independent risk factors for the prognosis of LUAD patients (Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eD-E). Afterwards, a nomogram was created to predict the survival of LUAD patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Thus, YKT6 is an independent risk factor, and elevated YKT6 expression indicates adverse outcome in LUAD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, the receiver operating characteristic (ROC) curve was utilized to determine the diagnostic ability of YKT6 in distinguishing tumor and normal samples. Notably, the area under the curve (AUC) value was up to 0.856, demonstrating high diagnostic value in LUAD patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eValidation of the elevated expression of YKT6 in LUAD tissues\u003c/h2\u003e \u003cp\u003eTissue samples from patients with LUAD were collected and performed qRT-PCR. Compared to para-cancerous tissues, YKT6 mRNA was expressed highly in LUAD tissue samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Immunohistochemical (IHC) staining and tissue microarray analysis (TMA) showed that YKT6 protein was significantly elevated in LUAD tissues (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-F).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMoreover, YKT6 mRNA expression was validated by GSE31547, GSE40791, and GSE43458. Consistently, in all these LUAD samples, YKT6 displayed obviously increased expression compared to normal groups (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eG-I). Hence, the elevated expression of YKT6 was verified at both mRNA and protein levels by these external LUAD tissue samples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eKnockdown of YKT6 inhibits cell proliferation and promotes apoptosis of lung cancer cells\u003c/h2\u003e \u003cp\u003eYKT6 mRNA expression was significantly reduced in A549 and Calu-1 cells upon silencing by siRNA transfection. Cell proliferation assay by CCK-8 showed that YKT6 knockdown inhibited A549 and Calu-1 cell proliferation (Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). In addition, the flow cytometry analysis revealed obviously increased Annexin V\u003csup\u003e+\u003c/sup\u003e cells after YKT6 silencing in A549 and Calu-1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Thus, YKT6 knockdown could inhibit cell proliferation and promote apoptosis of lung cancer cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn order to explore the underlying molecular mechanism of YKT6 in LUAD, cell proliferation-related genes were examined after YKT6 knockdown. The results demonstrated that TGF-b, Ki-67, Hes1, Cyclin-B1, Cyclin-E2 and CDK9 expression was considerably suppressed upon silencing of YKT6 in these cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eE-F). Based on these results, it is speculated that YKT6 might play a role through cell cycle related genes in LUAD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eYKT6 silencing inhibits cell migration and invasion\u003c/h2\u003e \u003cp\u003eThe scratch wound healing experiment demonstrated that cell migration ability was decreased upon YKT6 silencing in A549 and Calu-1 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003eA-B). Similarly, Knockdown of YKT6 reduced cell capacity of invasion in the Transwell assay in A549 and Calu-1 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Hence, YKT6 knockdown could inhibit cell migration and invasion of lung cancer cells. Thus, it is speculated that YKT6 might be involved in the regulation of cell migration via EMT-related factors. Consistently, the results demonstrated that EMT-related genes including Slug, Twist1, and Snail were remarkably decreased when YKT6 was knocked down in A549 and Calu-1 cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eA-B). Moreover, YKT6 might play a role in LUAD through PLK1 pathway as demonstrated by GSEA (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eC and Supplementary Fig.\u0026nbsp;1). TCGA database indicated that PLK1 was highly expressed in LUAD, with a strong positive correlation (R\u0026thinsp;=\u0026thinsp;0.589) to YKT6 (Figs.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eD-E). Meanwhile, the \u003cem\u003ein vitro\u003c/em\u003e cellular function analysis showed an obvious PLK1 mRNA decrease upon YKT6 silencing in lung cancer cells (Figs.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eF-G).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of gene-gene interaction and PPI Network with hub genes screening\u003c/h2\u003e \u003cp\u003eThe YKT6-related gene-gene interaction network was created via Genemania (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). The cBioPortal database was used to obtain YKT6 related genes and the top 100 genes were selected based on the Spearman values (Supplementary Table\u0026nbsp;2). Subsequently, the STRING database was used to construct PPI network and the top ten hub genes were screened as follows: CDC20, PLK1, CDCA8, TPX2, KIF2C, KIF23, KIF4A, FOXM1, MCM7 and CDCA5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Additionally, TCGA data and clinical information showed that the selected ten hub genes were all highly expressed in LUAD (Supplementary Fig.\u0026nbsp;2), with relation to poor prognosis of LUAD patients (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eGO and KEGG enrichment analyses of YKT6 and related genes\u003c/h2\u003e \u003cp\u003eGO and KEGG enrichment analyses were conducted through the DAVID database to explore the potential biological functions of YKT6 and its co-expressed genes. They were mainly involved in cell division, DNA repair, mitosis, and cell cycle (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eC), primarily located in nuclear cytoplasm, cytoplasm, cell membrane, and mitochondria (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eD). Their major molecular functions including protein binding, ATP enzyme activity, and ATP binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eE), with potential mechanisms through cell cycle, cell senescence, and p53 signal pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig15\" class=\"InternalRef\"\u003e8\u003c/span\u003eF). Based on these findings, there is reason to propose that the crucial biological role of YKT6 in LUAD might be mainly involved in cell cycle.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLung cancer is one of the most common causes of cancer-related death worldwide [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Among them, LUAD is the major histological subtype of lung cancer, with incidence increasing year by year [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, the outcome for LUAD patients is far from satisfaction due to the delay in early diagnosis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Although radiotherapy, chemotherapy, surgery, and targeted therapy has significantly improved the survival rate of LUAD patients, it remains a serious global public health issue [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Therefore, it is urgent to find new diagnostic biomarkers and therapeutic targets for LUAD.\u003c/p\u003e \u003cp\u003eSNARE proteins are composed of 20\u0026ndash;30 kDa proteins with a homologous domain of 60\u0026ndash;70 amino acid residues [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. SNARE proteins can be divided into Q-SNARE and R-SNARE based on difference in amino acid residues. In mammals, the SNARE family consists of more than 30 members with different subcellular localizations and forms specific SNARE complexes to regulate various cellular biological processes [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. YKT6 belongs to R-SNARE protein family, highly conserved from yeast to humans[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. YKT6 has been reported to be involved in vesicular transport, secretory, endocytosis, autophagy, and the formation and release of exocrine bodies [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Moreover, YKT6 is related to tumor progression; however, there are few research report on YKT6 in LUAD. In this study, bioinformatics analysis and cell function assays were used to explore the expression, prognosis, and possible biological roles of YKT6 in LUAD.\u003c/p\u003e \u003cp\u003eIn the present study, YKT6 mRNA/protein was highly expressed in LUAD, correlated with clinical stage, lymph node metastasis, smoking history, and TP53 mutation in LUAD. YKT6 expression showed the highest in clinical stage III and lymph node metastasis stage IV, suggesting an important role in middle and late stages of LUAD. Thus, YKT6 may be used as a potential indicator of LUAD stages. Besides, compared to the expression in TP53-non-mutated LUAD samples, YKT6 showed elevated level in TP53-mutated tissues. Therefore, YKT6 might play an important role in the progression of LUAD through the TP53 pathway. In addition, YKT6 was significantly correlated with OS, DSS and PFI, suggesting a potential prognostic biomarker of LUAD.\u003c/p\u003e \u003cp\u003eAmong the top ten hub genes (CDC20, PLK1, CDCA8, TPX2, KIF2C, KIF23, KIF4A, FOXM1, MCM7 and CDCA5) selected of YKT6 co-related genes, cell division cycle 20 (CDC20) promotes the resistance of glioblastoma (GBM) cells to chemotherapy and radiotherapy, while knockout of CDC20 can enhance the sensitivity of GBM cells to radiotherapy and chemotherapy by regulating the pro-apoptotic protein Bim [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].The polo-like kinase 1 (PLK1) is a serine/threonine protein kinase with a key role in eukaryotic cell division, DNA replication, and TP53 regulation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. PLK1 can promote the progress of Kras/TP53-mutated LUAD by regulating the transcriptional activation receptor RET [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In addition, PLK1 is overexpressed in hepatocellular carcinoma (HCC), related to tumor invasiveness and poor prognosis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Cell division cycle-related genes 8 (CDCA8) and CDCA5 belong to the family of cell division cycle related genes. Studies have shown that miR-133a-3p can target CDCA8 and inhibit the progress of ESCA [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. TPX2 can enhance the expression of cyclin-dependent kinase-1 (CDK1) in PRAD, then promote the phosphorylation of the ERK/GSK3b/Snail pathway, and finally EMT[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Kinesin family protein 2C (KIF2C), also known as mitotic centromere-associated driving protein, encodes proteins in microtubule depolymerization, thus promoting chromosome separation during mitosis. KIF2C is highly expressed in HCC, related to tumor histological grade, pathological stage, and poor prognosis. In addition, KIF2C can promote the progression of HCC by activating the renin-angiotensin system (RAS)/mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB) signaling pathways [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Kinesin family member 23 (KIF23) is a member of the Kinesin family, highly expressed in triple-negative breast cancer (TNBC). Silencing of KIF23 expression can inhibit the proliferation and migration of the TNBC cells [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Recent research has demonstrated that KIF4A expression is up-regulated in LUAD and correlates with the prognosis of the patients [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Additionally, it has been reported that miR-877-5p could inhibit cell growth by directly targeting FOXM1, potentially furnishing a promising biomarker for targeted therapy in NSCLC [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. MCM7 belongs to the small chromosome maintenance protein family, with a pivotal role in DNA replication and proliferation in eukaryotic cells. Several studies indicated that receptor for activated C kinase1 (RACK1) could modulate the growth and cell cycle progression of human NSCLC cells through MCM7 phosphorylation mediated by the MCM7/RACK1/Akt signal complex [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. CDCA5 plays an important role in the occurrence and development of many kinds of cancers by regulating cell cycle. CDCA5 is highly expressed in breast cancer tissues and cell lines. CDCA5 deletion can inhibit cell proliferation, invasion, and migration. Hence, CDCA5 can be used as a prognostic biomarker and therapeutic target for breast cancer [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Thus, the above YKT6-related hub genes are all correlated to tumor progression and prognosis, with functions on tumor cell proliferation, invasion or migration.\u003c/p\u003e \u003cp\u003eEnrichment analysis of YKT6 and its related genes showed the main physiological functions were cell division, mitosis, and the cell cycle. Consistently, the hub genes screened were mainly cell cycle-related. YKT6 may play a role in LUAD through PLK1 and TP53 pathways as demonstrated by GSEA. In addition, it is mentioned above that PLK1 can promote the progress of LUAD with K-ras/TP53 mutation by regulating the transcriptional activation receptor RET. Thus, there may exist certain relationship between YKT6 and PLK1 in the occurrence and development of LUAD, which needs further verification.\u003c/p\u003e \u003cp\u003eIn recent years, tumor immune escape has been the focus of anti-tumor therapy. Numerous immune cells including macrophage, T cell, and NK cell constitute the tumor microenvironment. These cells directly or indirectly affect the microenvironment of tumor cells and regulate their biological behaviors. Therefore, immune cell therapy has a broad application prospect in the treatment of LUAD. YKT6 is related to immune cell infiltration in LUAD (data not shown). The increased infiltration of immune cells is accompanied by elevated YKT6 expression, providing the foundation for effective immunotherapy. Thus, the findings have provided novel insights into immunotherapy for patients with LUAD.\u003c/p\u003e \u003cp\u003eTo sum up, our present study shows that YKT6 is supported as a potential new biomarker of LUAD. However, it is not clear how YKT6 regulates the occurrence and development of LUAD. Further research and clinical verification are needed to explore the underlying molecular mechanism of YKT6 in the initiation and treatment of LUAD.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCollectively, this study comprehensively shows the elevated expression of YKT6 in LUAD, and its correlation to the poor prognosis of LUAD patients. It is expected to be a novel prognostic and diagnostic biomarker in LUAD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e The online version contains supplementary material available at XXXXXXXXXX.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e The authors gratefully acknowledge contributions from the TCGA network the authors listed in this manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eLiming Zhang, Shaoqiang Wang and Lina Wang designed and performed bioinformatics analysis. Liming Zhang and Lina Wang analyzed the data and organized pictures. Liming Zhang, Lina Wang and Shaoqiang Wang wrote and revised the paper. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This work was supported by the National Natural Science Foundation of China (81800182, 81802290). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003ePublicly available datasets were analyzed in this study. All data generated in the study are included in the present article and supplementary data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e The authors declare that they have no competing interests relating to the publication of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e The work has not been published previously, and it is not under consideration for publication elsewhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e Not applicable.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eH. Sung, J. Ferlay, R.L. Siegel, M. Laversanne, I. Soerjomataram, A. Jemal, F. Bray, Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries, CA Cancer J Clin, 71 (2021) 209-249.\u003c/li\u003e\n\u003cli\u003eJ. Rodriguez-Canales, E. 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Zhang, Y. Han, RACK1 promotes lung cancer cell growth via an MCM7/RACK1/ Akt signaling complex, Oncotarget, 8 (2017) 40501-40513.\u003c/li\u003e\n\u003cli\u003eH. Hu, Y. Xiang, X.Y. Zhang, Y. Deng, F.J. Wan, Y. Huang, X.H. Liao, T.C. Zhang, CDCA5 promotes the progression of breast cancer and serves as a potential prognostic biomarker, Oncol Rep, 48 (2022).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary Information","content":"\u003cp\u003eSupplementary Information is not available with this version.\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1. GSEA of YKT6 DEGs in LUAD.\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2. The mRNA expression of the ten selected hub genes in LUAD\u0026nbsp;based on TCGA database.\u003c/p\u003e\n\u003cp\u003e(A) CDC20. (B) PLK1. (C) CDCA8. (D) TPX2. (E) KIF2C. (F) KIF23. (G) KIF4A. (H) FOXM1. (I) MCM7. (J) CDCA5.\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 3. The prognosis of the ten selected hub genes in LUAD from Kaplan-Meier plotter.\u003c/p\u003e\n\u003cp\u003e(A) CDC20. (B) PLK1. (C) CDCA8. (D) TPX2. (E) KIF2C. (F) KIF23. (G) KIF4A. (H) FOXM1. (I) MCM7. (J) CDCA5.\u003c/p\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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"lung adenocarcinoma (LUAD), YKT6, prognosis, biomarker, bioinformatics analysis","lastPublishedDoi":"10.21203/rs.3.rs-4728838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4728838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLung cancer is the most common cause of cancer-related death worldwide. The most prevalent histological subtype of lung cancer is lung adenocarcinoma (LUAD), with incidence rising each year. Treating LUAD remains a significant issue due to a lack of early diagnosis and poor therapy outcomes. YKT6 is a member of the SNARE protein family, whose clinical value and biological function in LUAD has yet to be established.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eTCGA, HPA and UALCAN were used to analyze YKT6 mRNA and protein levels, the correlation between YKT6 expression and clinicopathological features and prognosis. YKT6 mRNA and protein expression were verified by qRT-PCR, immunohistochemistry (IHC) and tissue microarrays (TMA). Additionally, lung cancer cell lines were chosen for YKT6 silencing to explore the effects on cell proliferation and migration. The cBioPortal was used to select YKT6-related genes. Protein-protein interaction (PPI) network was created based on STRING database and hub genes were screened, with their expression levels and prognosis values in LUAD analyzed accordingly. YKT6-related genes were enriched by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn LUAD, YKT6 was distinctly highly expressed with relation to clinical features of staging, smoking, lymph node metastasis, and TP53 mutation. Elevated YKT6 expression was linked to adverse prognosis, serving as an independent unfavorable prognostic factor. Moreover, YKT6 presented high diagnostic value in LUAD patients (AUC\u0026thinsp;=\u0026thinsp;0.856). Experimental validation indicated that freshly collected LUAD tissues showed significantly high mRNA expression of YKT6. IHC and TMA verified increased YKT6 protein level in LUAD. Knockdown of YKT6 inhibited cell proliferation and promoted apoptosis, with mitigated capability of migration and invasion. The top ten hub genes screened by PPI network were highly expressed in LUAD, and significantly associated with poor prognosis. GO and KEGG analyses showed that YKT6-related genes were mainly involved in cell cycle.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eElevated YKT6 expression is related to poor prognosis of LUAD patients. YKT6 can serve as a novel biomarker for LUAD diagnosis and prognosis. Cell proliferation, migration and invasion was impaired with increased apoptosis upon YKT6 silencing in lung cancer cells. In summary, this study comprehensively uncovered that YKT6 could be identified as a potential prognostic and diagnostic biomarker in LUAD.\u003c/p\u003e","manuscriptTitle":"Comprehensive analysis identifies YKT6 as a potential prognostic and diagnostic biomarker in lung adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-16 15:56:18","doi":"10.21203/rs.3.rs-4728838/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-17T06:51:33+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-16T02:32:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-16T02:31:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-07-12T08:03:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"33d2ee51-3091-4fa3-bd90-4ad0292e4389","owner":[],"postedDate":"August 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-14T16:02:22+00:00","versionOfRecord":{"articleIdentity":"rs-4728838","link":"https://doi.org/10.1186/s12885-024-12975-3","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2024-10-07 15:57:45","publishedOnDateReadable":"October 7th, 2024"},"versionCreatedAt":"2024-08-16 15:56:18","video":"","vorDoi":"10.1186/s12885-024-12975-3","vorDoiUrl":"https://doi.org/10.1186/s12885-024-12975-3","workflowStages":[]},"version":"v1","identity":"rs-4728838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4728838","identity":"rs-4728838","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}