SMC2 as a potential prognostic biomarker in lung adenocarcinoma and its correlation with immune microenvironment

SMC2 as a potential prognostic biomarker in lung adenocarcinoma and its correlation with immune microenvironment | 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 SMC2 as a potential prognostic biomarker in lung adenocarcinoma and its correlation with immune microenvironment Fu-Qiang Zheng, Yu Li, Hui-Guo Chen, You Peng, Xiao-Cai Tian This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4659994/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Structural maintenance of chromosome 2 (SMC2) has been recognized to play an important role in a variety of cancers, but its function in lung adenocarcinoma (LUAD) remains poorly understood.First, we explored the expression level of SMC2 and its relationship with clinical pathological features using the LUAD dataset from the TCGA database. The expression of SMC2 in LUAD cell lines and tissues was verified using quantitative polymerase chain reaction (qPCR). Secondly, Kaplan-Meier analysis, COX regression analysis and Nomogram construction were employed to assess the prognostic potential of SMC2 in LUAD. In addition, the biological behavior and possible signaling pathways of SMC2 were forecasted by protein-protein interaction (PPI) networks, single-gene correlation analysis, genetic ontology (GO) and genome enrichment analysis (GSEA), together with Kyoto Encyclopedia of Genes and Genomes (KEGG). At last, a systematic analysis of crosstalk and mutations between SMC2 and immune features in the tumor microenvironment (TME) was conducted using a single-sample GSEA algorithm, the Tumor Immune Dysfunction and Rejection (TIDE) algorithm, the TIMER 2.0 and TISIDB databases, as well as the cBioportal database.SMC2 was markedly up-regulated in LUAD cell lines and tissues and was strongly correlated with adverse clinicopathological features and prognosis. ROC curves showed a good diagnostic effect (AUC value: 0.787). The enrichment analysis suggested that SMC2 might be involved in the regulation of LUAD cell cycle. The TIMER algorithm and ssGSEA algorithm showed that SMC2 was associated with suppressive immune cells (e.g., B cells) in LUAD. In addition, SMC2 may interact with the expression of molecules such as NDC80, KIFC1, SKA1, NCAPH, ESPL1, MELK, KIF11, SGO1, TOP2A, KNL1, KIF4A, TPX2, TICRR, TTK, KIF14, NCAPG and others to promote LUAD progression. Evidence from the TISIDB database shows that SMC2 is positively associated with immunosuppressive genes such as CD274, PDCD1LG2, TGFBR1 and LAG3. However, it is inversely associated with chemokines and receptors such as CCL14, CCL17, CXCL16, CX3CL1, CX3CR1, CCR6, CCR7 and CXCR5. Also, as predicted by the TIDE algorithm, patients with high SMC2 expression responded poorly to immunotherapy.Our analysis shows that the high expression status of SMC2 in LUAD is associated with poor patient outcomes and describes some potential reasons for this poor prognosis. These findings suggest that SMC2 is associated with the malignant progression of LUAD and therefore may be a potential target for improving outcomes in LUAD in the foreseeable future. SMC2 Lung adenocarcinoma Poor prognosis Immune infiltration Biomarker. Figures Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Introduction Lung cancer is one of the most prevalent malignant tumors with the worst prognosis worldwide. Lung cancer is divided into two types: non-small cell lung cancer (NSCLC, about 85%) and small cell lung cancer (SCLC, about 15%)(Siegel, Miller and Jemal 2020), while lung adenocarcinoma (LUAD) is the most frequent histologic subtype of NSCLC, accounting for about 60% of cases(Denisenko, Budkevich and Zhivotovsky 2018), and its 5-year survival rate is only 22.1%(Kim et al. 2019). In recent years, new therapies for NSCLC have emerged, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy(Herbst, Morgensztern and Boshoff 2018). Nevertheless, the recurrence and mortality rates of LUAD are still high, and the prognosis of patients is poor. Therefore, it is imperative to find more effective biomarkers to facilitate new therapeutic treatments. Structural maintenance of chromosomes (SMC) proteins, a family of DNA-binding ATPases, are vital for maintaining chromosome integration during cell division(Hirano 2006). Whereas SMC2 is one of the six members of the SMC family, it forms a dimer with SMC4, which binds to three non-SMC proteins to form a pentameric complex called condensin(Dávalos et al. 2012). Condensin has DNA supercoiling activity, which is necessary for chromatin packaging prior to cell division. It has also been shown to be required for the disassembly of sister chromatids at later stages(Hudson, Marshall and Earnshaw 2009; Paliulis and Nicklas 2004). Thus, SMC2 proteins play an important role in the organization of chromatin packaging prior to cell division and the DNA damage response, which is needed for the maintenance of chromosome stability(Murakami-Tonami et al. 2014). It has been revealed that it may have pro-carcinogenic functions, and SMC2 knockdown inhibits tumor growth in colorectal cancer and is involved in cell mitosis(Dávalos et al. 2012). In addition, experimental studies have shown that SMC2 knockdown increased apoptosis in neuroblastoma cells(Murakami-Tonami et al. 2014). Badea et al. demonstrated that the expression level of SMC2 mRNA was significantly higher in human pancreatic cancer tissues than in adjacent normal tissues (Badea et al. 2008). Meanwhile, several other genes of the SMC family have been found to be closely associated with tumorigenesis, such as SMC1A(Yadav et al. 2019), SMC3(Kraft et al. 2019), and SMC4(Jiang et al. 2017). Obviously, to some extent this supports the connection between SMC2 and cancer aggressiveness. Interestingly, firstly, with the help of RNA sequencing data from TCGA database and a series of bioinformatics analysis tools such as HPA and UALCAN, we found that SMC2 mRNA expression was significantly up-regulated in LUAD tissues, and verified the trend in cell lines and tissues. Secondly, with the help of gene set enrichment analysis (GSEA), we explored its potential pathways of action in LUAD. In addition, the cBioPortal database was utilized to analyze SMC2 mutations in LUAD. TIMER and ssGSEA algorithm were further utilized to analyze the relationship between SMC2 expression and immune cell infiltration in LUAD. Finally, the relationship of SMC2 with immune checkpoints and chemokines and receptors was analyzed using the TISIDB database. Taken together, our findings provide new perspectives on the prognosis and mutation and immunity of SMC2 in LUAD. 2. Methods Ethical statement The study was performed in compliance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Hunan Provincial People's Hospital. We also selected 8 pairs of fresh LUAD and adjacent non-tumor tissues from our study center. Use of these samples was authorized by the Ethics Committee, and all the patients enrolled in the study gave their informed consent. Access to RNA sequencing data and clinical information The sequencing data and corresponding clinicopathologic information for 539 LUAD samples and 59 adjacent normal samples were downloaded from the TCGA database (https://portal.gdc.cancer.gov/)(Tomczak, Czerwińska and Wiznerowicz 2015). In order to compensate for the relative lack of normal samples when performing differential gene expression analysis, we obtained SMC2 expression data in 347 normal lung tissue samples from the GTEx database (https://www.gtexportal.org/)(2015). Quantitative polymerase chain reaction (qPCR) analysis Total RNA was extracted from cell lines (BEAS-2B, A549, H1975 and PC9) and 8 pairs of lung adenocarcinoma tissues, and then reverse transcription and qPCR were performed using cDNA synthesis kit (Qiagen, USA) and SYBR real-time PCR kit (Qiagen, USA) according to the instructions of the kits; quantitative analysis was performed using the 2-ΔΔCt method. The primer sequences were as follows: SMC2_F: TCTCAGGTTCGGGCTTCTAAT; SMC2_R: CCTGTACTCTGGTGTTGTTGG; the internal reference gene was β-actin. UALCAN and HPA database UALCAN (http://ualcan.path.uab.edu/) is an interactive web resource that is comprehensive and user-friendly, allowing users to recognize biomarkers or validate potential genes of interest in silico (Chandrashekar et al. 2022). It was used here to assess the protein expression levels of SMC2 at different levels. In addition, the immunohistochemistry of SMC2 was obtained from the Human Protein Atlas(HPA)(Asplund et al. 2012). Nomogram construction and evaluation Indexes with independent prognostic value screened in multivariate COX analyses were included in Nomogram constructs predicting 1-, 3-, and 5-year disease-specific survival (DSS) in patients with LUAD; predictive effects were assessed by calibration curves drawn by the "rms "R software package. Protein–protein interaction (PPI) We first performed gene correlation analysis on SMC2, then, we screened differentially expressed genes (DEGs) with |log2FoldChange| > 1.2 in LUAD to draw volcano plots. Subsequently, the top 800 genes and DEGs most closely related to SMC2 in the TCGA database were cross-tabulated by Venn diagrams, and the target molecules were used for the next step of PPI and Genetic Ontology (GO) analyses. The PPI network was constructed in the STRING(Szklarczyk et al. 2021) database (https://cn.string-db.org/) and then imported into Cytoscape (version 3.10.0) for adjustments to find molecules more related to SMC2 in LUAD. GO and gene set enrichment analysis (GSEA) Differential genes associated with SMC2 were used for GO and KEGG pathway analysis to explore the biological processes in which SMC2 may be involved in LUAD.GO analysis was used to estimate the biological processes, molecular functions, and cellular compositions of the mRNAs. GSEA is a pathway enrichment analysis algorithm that well controls type I and type II errors and is therefore extensively used in the processing of multi-omics data (Canzler and Hackermüller 2020). The analysis was performed using the 'clusterprofiler' in the R package; 1000 operations were performed per analysis, with normalized enrichment scores (NES) >1, false discovery rates (FDR) <0.25 and adjusted p-values <0.05 were considered statistically significant. Genetic alterations in the SMC2 gene in LUAD On one hand, we analyzed the distribution of different types of SMC2 mutations in cancer using the COSMIC(Bamford et al. 2004) website (https://cancer.sanger.ac.uk/cosmic/); on the other hand, we analyzed the distribution of SMC2 mutations in cancer using three datasets of LUAD from the cBioPortal(Cerami et al. 2012; Gao et al. 2013) ( http://www.cbioportal.org/ ) platform (TCGA, Firehose Legacy; TCGA, Nature 2014; TCGA, PanCancer Atlas) analyzed SMC2 gene alterations in LUAD. Single-sample GSEA (ssGSEA) and TIMER 2.0 ssGSEA is an extension of the GSEA method that calculates enrichment scores for each sample and gene set pair. In this way, ssGSEA converts gene expression profiles of individual samples into gene set enrichment profiles. Thus, ssGESA was used to analyze the relationship between SMC2 and several tumor-infiltrating immune cells. TIMER 2.0 (Li et al. 2020) (http://timer.comp-genomics.org/) is a well-rounded resource that systematically analyzes the relationship between genes and the abundance of immune-infiltrating cells in different types of cancers, enabling users to explore the full range of immunological, clinical, and genomic features of tumors. This study used these data to analyze the correlation between SMC2 and the abundance of immune-infiltrating lymphocytes in the tumor microenvironment. TISIDB databases TISIDB (Ru et al. 2019) (http://cis.hku.hk/TISIDB/) is a portal for exploring tumor-immune system interactions. We used this platform to systematically analyze the correlation between SMC2 and immune checkpoint inhibitors, stimulators and chemokines, and receptors in LUAD. Statistical Analyses All RNA sequencing data were performed using R software (version 3.6.3); pROC software package was used to plot ROC curves, Kaplan-Meier analysis and COX analysis were used to assess the effect of SMC2 on LUAD patients' survival outcomes, and spearman correlation analysis was used to describe the correlation between SMC2 expression and tumor-infiltrating lymphocytes (TILs), immune correlations between checkpoint inhibitors, chemokines and related genes, etc., and P<0.05 was considered statistically significantly different. 3. Results Pan-cancer analysis of SMC2 mRNA and up-regulation of expression in LUAD Given the role of SMC2 in a variety of human cancers, we performed a pan-cancer analysis of SMC2 mRNA levels by using the TCGA database. The results revealed that SMC2 was highly expressed in a number of cancers, including lung adenocarcinoma and uterine corpus endometrial carcinoma, as well as colon adenocarcinoma (see Fig. 1A for details). Then, we comprehensively analyzed the effects of SMC2 on overall survival (OS), DSS, and progression-free interval (PFI) in cancer patients, and the results revealed that the upregulation of SMC2 might be adverse to the prognosis of LUAD patients ( Fig. 1, B to D ). As a result, we chose LUAD as the targeted carcinoma in this study. Subsequently, the expression levels of SMC2 in LUAD are shown in Fig. 1, E and F . This indicates that the expression levels of SMC2 are up-regulated in LUAD tissues, regardless of the inclusion of data from the GTEx database. This trend was as well observed in paired samples ( Fig. 1G ). Finally, high expression of SMC2 was verified in LUAD cell lines (A549, H1975 and PC9) and human bronchial epithelial cells BEAS-2B, as well as in 8 pairs of LUAD tissues and adjacent normal tissues from our medical center ( Fig. 1, H and I ). Taken together, these results suggest that SMC2 is highly expressed in LUAD. The expression of SMC at the protein level in LUAD To begin with, in the CPTAC database of the UALCAN platform, we found that the protein expression level of SMC2 in LUAD was increased relative to normal tissues ( Fig. 2A ). Next, SMC2 protein expression levels in LUAD were derived from immunohistochemical staining data in the HPA database (antibody HPA071309). Consistent with the upregulation of mRNA levels, SMC2 protein expression was also significantly upregulated in LUAD tissues (Patient ID: 1907, 2003, and 4923) relative to normal tissues (Patient ID: 1470, 1678, and 2643) ( Fig. 2B ). Likewise, protein expression levels of SMC2 were progressively higher in pathological grades 2 and 3 compared with the normal group, although there was no significant change in grade 1 ( Fig. 2C ). As shown in Fig. 2, D to F , alterations in the mTOR and HIPPO pathways combined with the WNT pathway also contributed to elevated SMC2 protein expression levels. Relationship between SMC2 and clinicopathologic features From Fig. 3, A to I , we can observe that SMC2 was remarkably overexpressed in LUAD patients with T2-T4 stage, N1-N3 stage, M1 stage, higher pathologic stage and OS fatal event, along with in patients with DSS/PFI events. In view of these evidences, we can speculate that SMC2 may adversely influence the survival of patients. Diagnostic and prognostic value of SMC2 in LUAD To start with, the diagnostic effect of SMC2 in LUAD was assessed using ROC curves. As shown in Fig. 4A , the AUC value of SMC2 in distinguishing LUAD tissues from normal tissues was 0.787. The Kaplan-Meier curve revealed the effect of SMC2 expression on the tumor prognosis of patients with LUAD, the SMC2 high-expression group was correlated with poorer OS, DSS, and PFI in LUAD patients, with the risk ratios (HR) of 1.49, 1.72, and 1.51, respectively ( Fig. 4, B to D ) (p<0.05). In the meantime, we performed univariate ( Fig, 4E ) and multivariate ( Fig, 4F ) COX regression analyses, which further confirmed that SMC2 might be an independent prognostic factor for LUAD. In addition, according to the results of COX analysis, we further constructed Nomogram to predict the DSS of LUAD patients at 1-, 3-, and 5 years ( Fig, 4G ). It was reassuring that the C-index for evaluating its predictive effect was 0.701, and the calibration curve objectively demonstrated the comparatively good agreement between the predicted and actual values ( Fig. 4, H to J ). Filtering mRNA potentially relevant to SMC2 We first selected the top 800 mRNAs that were closely associated with SMC2 in LUAD, and the heatmap in Fig. 5A shows the top 20 molecules. Then, differentially expressed mRNAs in LUAD were screened by volcano plots according to the filtering standard, in which 750 mRNAs were either up- or down-regulated ( Fig. 5B ). Besides, Venn diagrams further identified overlapping genes in the two groups ( Fig. 5C ). These 46 target molecules were then constructed into a PPI network through the STRING database, and the hub genes were selected based on the centrality of the nodes ( Fig. 5D ). In the end, Kaplan-Meier survival analysis of mRNAs (NDC80, KIFC1, SKA1, NCAPH, ESPL1, MELK, KIF11, SGO1, TOP2A, KNL1, KIF4A, TPX2, TICRR, TTK, KIF14, NCAPG) was performed to explore more about their effects on OS in LUAD patients. Interestingly, upregulation of all these molecules in LUAD exacerbated the poor prognosis of OS in patients ( Fig. 6, A to P ). Apparently, the detrimental effect of these mRNAs on the survival prognosis of LUAD patients is consistent with the tendency of SMC2. Exploring the potential mechanisms of SMC2 in LUAD Based on the 46 targets mRNA obtained from the pre-screening, we performed GO analysis and found that SMC2 may be involved in the following biological processes, including: nuclear division, mitotic sister chromatid segregation, cellular process involved in reproduction in multicellular organism, DNA replication, et al. Meanwhile, it is involved in cellular components such as condensed chromosome, centromeric region, kinetochore and mitotic spindle, and its potential molecular function is mainly to influence tubulin binding ( Fig.7, A and B ). In addition, we explored the potential pathway of SMC2 in LUAD using GSEA. As shown in Fig. 7, C and D , the significantly enriched KEGG pathways included cell cycle, oocyte meiosis, homologous recombination, human T-cell leukemia virus 1 infection. The REACTOME pathways included DNA damage telomere stress induced senescence, DNA replication, cell cycle checkpoints, epigenetic regulation of gene expression as well as cellular senescence. These findings may provide a reference for further studies in the future! SMC2 genetic alteration in LUAD The COSMIC website shows the distribution of different types of SMC2 mutations in cancer ( Fig. 8, A and B ). Missense substitutions were the most common type of mutation, following by synonymous substitutions, and G>A, C>T and A>G were the most common substitution mutations. Next, the SMC2 gene mutations in LUAD were analyzed by three datasets in the cBioPortal database. The results indicated that SMC2 was genetic alteration in 2.4% of LUAD patients ( Fig. 8C ). As shown in Fig. 8D , we can visualize the specific types and frequency of gene mutations. SMC2 mRNA expression was elevated in the shallow deletion group compared with the diploid group, and interestingly, the expression of gain groups was also increased ( Fig. 8E ). In the LUAD samples, 23 SMC2 missense mutation sites were shown, one of which was K879N, suggesting that this is one of the protein activation hotspots, as well as two SMC2 truncating mutation sites ( Fig. 8F ). Association between SMC2 expression and immune characteristics in LUAD To further understand the role of SMC2 in LUAD, we first analyzed the correlation between SMC2 and TILs. Based on the ssGSEA algorithm, we found that SMC2 was negatively correlated with CD8 + T cells, Th 17 cells, mast cells, dendritic cells (DC), T follicular helper cells (TFH), B cells, etc ( Fig. 9, A and B ). On the other hand, using the TIMER algorithm and the TIDE algorithm in the TIMER database, we found that SMC2 was negatively and positively correlated with activated B cells and MDSC, respectively ( Fig. 9C ). Notably, when activated B cells were enriched, the OS of LUAD patients was significantly better, however, when MDSC was enriched, the OS of LUAD patients was dramatically worse ( Fig. 9, D and E ). Taking the above information together, it is reasonable to hypothesize that the cancer-promoting effects of SMC2 may be related to a certain extent to the low enrichment of B cells as well as the high enrichment of MDSC. In Fig. 9F , the arm-level deletion of SMC2 copy number was associated with reduced abundance of CD8 + T cells, CD4 + T cells, neutrophils, and dendritic cells when compared with the diploid/normal state. These results indicate that copy number changes of SMC2 in LUAD may be an element that regulates the immune microenvironment. Immune checkpoints play a vital role in the immune microenvironment of LUAD, and these directly regulate the resident's anti-tumor immune response(Chi et al. 2021). Therefore, in this case, we next analyzed the association between SMC2 and immunoinhibitor ( Fig. 10A ). Interestingly, SMC2 was significantly positively correlated with CD274 (r = 0.298, p < 6.26e-12), PDCD1LG2 (r = 0.226, p < 2.29e-07), TGFBR1 (r = 0.208, p < 1.85e-06), and LAG3 (r = 0.181, p < 3.54e-05) ( Fig. 10B ). We also analyzed beside the association between SMC2 and immunostimulator ( Fig. 10D ). It is also intriguing that SMC2 was markedly negatively correlated with TNFSF13 (r = -0.471, p < 2.2e-16), TMEM173 (r = -0.404, p < 2.2e-16), TNFRSF14 (r = -0.399, p < 2.2e-16), and HHLA2 (r = -0.282, p < 7.53e-11) ( Fig. 10C ). Chemokines and chemokine receptors are essential for tumor infiltration by immune cells(Li et al. 2015). Therefore, we analyzed the correlation between SMC2 expression levels and immune cell chemokines and receptors in LUAD using the TISIDB database. Heatmap results showed that several chemokines and receptors were significantly correlated with SMC2 expression in LUAD ( Fig. 11, A and D ). Next, we concretely analyzed the correlation between SMC2 expression and chemokines/receptors. The results showed that SMC2 expression was negatively correlated with CCL14 (r = -0.378, p < 2.2e-16), CCL17 (r = -0.363, p < 5.74e-18), CXCL16 (r = -0.347, p < 5.66e-16), CX3CL1 (r = -0.268, p < 6.93e-10), CX3CR1 (r = -0.31, p < 7.89e-13), CCR6 (r = -0.246, p < 1.56e-08), CCR7 (r = -0.197, p < 6.6e-06), and CXCR5 (r = -0.14, p =0.00146) ( Fig. 11, B and C ), and these results revealed that the SMC2 gene may play an influential role in tumor immune. In addition, we analyzed the relationship between SMC2 and LUAD immune subtypes. As shown in Fig. 11E , SMC2 was highly expressed in type C2 (IFN-γ-dominant) and type C4 (lymphocyte-depleted), while it was least expressed in type C3 (inflammatory). This implies that the expression of SMC2 is directly related to the immune microenvironment of LUAD. Finally, The Tumor Immune Dysfunction and Rejection (TIDE) algorithm is extensively used to predict cancer immunotherapy response, with higher TIDE scores being associated with poorer immunotherapy outcomes (Jiang et al. 2018). TIDE scores were dramatically higher in those with high SMC2 expression compared to those with low expression, which resulted in a notably lower rate of response to their immunotherapy ( Fig. 11F ). 4. Conclusion In this article, we have presented the first systematic evidence for SMC2 in LUAD; we found that SMC2 expression is up-regulated in LUAD and correlates with poor clinical prognosis of patients. In addition, SMC2 expression was negatively correlated with inhibitory TILs, immunostimulator, chemokines, and receptors; its cross-talk with these factors may contribute to the malignant phenotype of LUAD and may provide a potential therapeutic target for LUAD patients. Discussion The structural maintenance of chromosomes(SMC) family is a group of prokaryotic and eukaryotic chromosomal proteins that may be one of the crucial components in establishing the ordered structure of chromosomes.SMC2 is the second member of the SMC family from budding yeast, and contains all the putative structural domains characteristic of a typical SMC family member: a nucleotide-binding region, two coiled-coil regions separated by a "hinge," and the carboxy-terminus of Smclp (DA box) itself(Strunnikov, Hogan and Koshland 1995). The SMC2 protein has also been demonstrated to be a subunit of the human condensin complex(Hudson, Marshall and Earnshaw 2009). In recent years, there is evidence that the SMC family is associated with human cancers, including pancreatic, hepatocellular, and colorectal cancers, etc(Feng et al. 2019; Je, Yoo and Lee 2014; Nie et al. 2021; Yan et al. 2022). SMC2 belongs to the condensin complex, which has also been reported to be associated with apoptosis in neuroblastoma cells(Murakami-Tonami et al. 2014). Here, we found by bioinformatics analysis that SMC2 expression was up-regulated in LUAD samples, had a favorable diagnostic effect on LUAD, and was associated with worsening of OS, DSS and PFI in patients. Obviously, these findings are similar to those reported in previous studies, which implies that SMC2 may be a promising biological marker for LUAD. It is well-known that the molecular crosstalk in the LUAD tumor microenvironment is a complicated network. In this study, we revealed some key proteins that may be closely related to SMC2 by correlation analysis and PPI network construction, including TTK, TOP2A, TICRR, NCAPH, SKA1, TPX2, NDC80 and SGO1, etc(Chen et al. 2020; Li, Meng and Zhang 2022; Xu et al. 2023; Zhou et al. 2020). It is interesting to point out that these molecules have been shown to be associated with the malignant phenotype and poor prognosis of LUAD in previous studies. These evidences not only provide a possible regulation network, but also seem to validate indirectly the malicious function of SMC2 in LUAD. Genetic alterations are closely associated with cancer. Several genetic alterations have been shown to be associated with the occurrence and development of LUAD(Ricciuti et al. 2022; Wohlhieter et al. 2020). We found that missense substitutions were the most common type of mutation followed by synonymous substitutions in 734 samples. And G>A (27.95%), C>T (14.77%) and A>G (14.55%) were the most common substitution mutations. Furthermore, the frequency of SMC2 gene mutation was only 2.4% in LUAD, which was mainly missense mutation. Thus, exploring the mechanism by which mutation affects the prognosis and therapeutic response of patients with LUAD could bring more benefits to the patients. Similar to other members of the SMC family, SMC2 is thought to be involved in cell cycle regulation(Thadani et al. 2018). In this paper, the results of GO, KEGG and GSEA also confirmed the applicability of this property of SMC2 in LUAD. On the other hand, tumor development is related to the tumor microenvironment (TME). TME consists of immune cells, extracellular matrix, mesenchymal stromal cells and inflammatory mediators, which have an impact on tumor growth, metastasis and clinical survival outcomes(Wang et al. 2022a). Previous studies have reported that immune infiltration can influence patient prognosis, and tumor-infiltrating lymphocyte grading is an independent predictor of sentinel lymph node status in patients with tumors(Slack and Chinnaiyan 2019). It has been found that B cells are the tumor-infiltrating lymphocytes with the highest correlation with risk scores, especially in patients with metastatic LUAD(Shao et al. 2023). Research has amply demonstrated the ability of CD8 + T cells to recognize and eradicate cancer cells(van der Leun, Thommen and Schumacher 2020). The use of CD8 + T cells for the detection and eradication of cancer cells has been a focus of clinical cancer therapy for more than 20 years(Wang et al. 2022b). Guo et al. identify circulating T follicular helper (TFH) cells that may play an essential role in the development of NSCLC pathogenesis(Guo et al. 2017). Interestingly, we found that SMC2 expression was negatively correlated with the level of infiltration of these cells, which is consistent with previous findings, suggesting to some extent that tumorigenesis may be associated with the absence or low enrichment of lymphocytes, which further contributes to the malignant progression of the disease. In addition, it is notable that the low enrichment of B cells in LUAD was associated with the deterioration of OS ( Fig. 9D ), which also seems to further corroborate the results of ssGSEA with TIMER. MDSC are immature myeloid cells that promote tumor growth and metastasis by inducing immunosuppression, which ultimately affects patient outcomes(Kalathil and Thanavala 2021). In our study, SMC2 expression was positively correlated with the level of MDSC infiltration, and highly enriched MDSC led to a worse prognosis ( Fig. 9E ). Therefore, SMC2 may inhibit the function of immune cells by increasing the level of MDSC infiltration, thus becoming a potential immunotherapeutic target. In recent years, systemic treatment options for patients with advanced LUAD have been dramatically expanded to include not only chemotherapy and targeted therapy, but also immune checkpoint inhibitors (ICIs)(Chi et al. 2021). Encouragingly, our study showed that SMC2 was positively correlated with immune checkpoints such as CD274, PDCD1LG2, TGFBR1 and LAG3 in LUAD. This evidence suggests that SMC2 may synergize with immune checkpoints, thus further exacerbating the immunosuppressive state in the TME. Recent studies have shown that chemokines can directly or indirectly regulate the TME and biological phenotype, affecting angiogenesis, tumorigenesis, malignant metastasis, etc(Nagarsheth, Wicha and Zou 2017). The correlation between the expression level of SMC2 and the expression of chemokines and receptors in LUAD was analyzed using the TISIDB database. The results showed that the expression level of SMC2 was negatively correlated with the expression of CCL14, CCL17, CXCL16, CX3CL1, CX3CR1, CCR6, CCR7 and CXCR5, suggesting that high expression of SMC2 may inhibit the migration of immune cells to the TME. CCL17, also known as Thymus and activation-regulated chemokine (TARC), is a C-C chemokine often associated with type 2 immune responses(Islam and Luster 2012), and CCR6 controls integrin-mediated adhesion in B cells(Matsukawa et al. 2000; Zlotnik and Yoshie 2012). The CXCR5 + subpopulation of CD8 + T cells may contribute to antitumor activity(Xing et al. 2017), and the receptor for CX3CL1, CX3CR1, in turn, controls leukocyte survival and NK cell activation(Ness et al. 2006). The strong correlation of SMC2 with these molecules may explain how SMC2 regulates immune infiltration in LUAD, and means that its interaction with chemokines in tumors may also be one of the factors contributing to the malignant phenotype of tumors. Additionally, the TIDE algorithm was employed to investigate the responsiveness of patients in different SMC2 expression groups to immune checkpoint therapy. Our finding that the TIDE score of the SMC2 high expression group was obviously higher than the SMC2 low expression group, which suggested that the immunotherapy response rate of patients in the SMC2 high expression group was lower. Consequently, based on this evidence, combined blockade of SMC2 and immune checkpoints may be a promising strategy for the treatment of LUAD in the foreseeable future. Finally, although we performed a systematic analysis of SMC2, there are some limitations of this study. First, the data in this study were obtained from public databases, and experimental validation was limited to SMC2 expression in lung adenocarcinoma cell lines and tissues. Secondly, the exact mechanism of SMC2 in LUAD tumorigenesis and development is still unclear and needs to be further refined in subsequent in vivo and in vitro experiments. Third, despite the fact that we believe that SMC2 expression is closely related to immune infiltration and prognosis in LUAD, we lack direct evidence that SMC2 affects prognosis through its involvement in immune infiltration. These issues above deserve further exploration in the future. Abbreviations SMC2, Structural maintenance of chromosomes 2; LUAD, lung adenocarcinoma; TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; qPCR, quantitative polymerase chain reaction；OS, overall survival; DSS, disease-specific survival; PFI, progression-free interval; GO: Gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; GSEA, gene set enrichment analysis; TILs, tumor-infiltrating lymphocytes; TFH, T follicular helper; TIDE, tumor immune dysfunction and exclusion; ssGSEA, Single-sample gene set enrichment analysis. MDSC, Myeloid-derived suppressor cells. Declarations Acknowledgments: Not applicable. Authors’ contributions: XCT and FQZ designed the study. YL, HGC and YP were responsible for the statistical analysis. FQZ wrote and plotted the manuscript as well as performed the experiments. XCT reviewed and revised the manuscript. All authors carefully read and approved the final manuscript. Funding ： This study was funded by Ren-Shu Fund of Hunan Provincial People's Hospital (Grant No. RS201819). Availability of data and materials: The data supporting the findings of the article are available within the article. Ethical approval and Consent to participate: All experiments involving human tissues complied with the principles of the Declaration of Helsinki. The patient data in this study, both from public databases and studies involving human subjects, was reviewed and approved by the Ethics Committee of Hunan Provincial People's Hospital（NO.2023-187）. All patients/participants provided written informed consent to participate in this study. Consent for publication: Not applicable. Competing interests ： All authors declare that they have no conflict of interest related to this manuscript. References 2015. Human genomics. The genotype-tissue expression (gtex) pilot analysis: Multitissue gene regulation in humans. 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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-4659994","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324799586,"identity":"e25093d7-7c53-45a2-8f07-2874bc3f25f2","order_by":0,"name":"Fu-Qiang Zheng","email":"","orcid":"","institution":"Hunan Provincial People’s Hospital/First Affiliated Hospital of Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Fu-Qiang","middleName":"","lastName":"Zheng","suffix":""},{"id":324799587,"identity":"cfec5d97-231f-4871-af41-95d24dfdbd5d","order_by":1,"name":"Yu Li","email":"","orcid":"","institution":"Hunan Provincial People’s Hospital/First Affiliated Hospital of Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Li","suffix":""},{"id":324799588,"identity":"fac5452b-a45f-410b-aeed-32efd8d9577f","order_by":2,"name":"Hui-Guo Chen","email":"","orcid":"","institution":"Hunan Provincial People’s Hospital/First Affiliated Hospital of Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"Hui-Guo","middleName":"","lastName":"Chen","suffix":""},{"id":324799589,"identity":"2121eaac-d2a0-4a8f-b9d0-4a76d90f3317","order_by":3,"name":"You Peng","email":"","orcid":"","institution":"Hunan Provincial People’s Hospital/First Affiliated Hospital of Hunan Normal University","correspondingAuthor":false,"prefix":"","firstName":"You","middleName":"","lastName":"Peng","suffix":""},{"id":324799590,"identity":"e602285f-d152-4d4e-8c29-d9a24dfd04ec","order_by":4,"name":"Xiao-Cai Tian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDACZjApwcDGwMD4GCYoQYwWCaAWZmPitCApYpMmSovBceaHD37UWNTxsZ89Vl3YdifP4ADzwds8DHZ5uLRINrMZG/YcAzqMJy/t9sy2Z8UGB9iSrXkYkotxaeFnZjCTZmAD+SXH7DZv2+HEDQd4zKR5GA4kNuDQwsbM/k2a4R9QC/8bs2KIFv5veLXwMwPNZGwDapHIMWOG2sKGV4tkM0+xYW+fhGSbxBtjaZ5zhxNnHmYztpxjkIxTi8H54xsf/PhWxy/fn2P4mafscGLf8eaHN95U2OHUggWAI9eAePWjYBSMglEwCjABAB1+Sior3WK3AAAAAElFTkSuQmCC","orcid":"","institution":"Hunan Provincial People’s Hospital/First Affiliated Hospital of Hunan Normal University","correspondingAuthor":true,"prefix":"","firstName":"Xiao-Cai","middleName":"","lastName":"Tian","suffix":""}],"badges":[],"createdAt":"2024-06-29 15:40:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4659994/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4659994/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61177054,"identity":"14e82141-0a17-4387-98be-5798904bd03b","added_by":"auto","created_at":"2024-07-26 15:49:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":840253,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the expression level of SMC2 in LUAD tissues and pathology grading as well as alterations in signaling pathways. \u003cstrong\u003e(A)\u003c/strong\u003e SMC2 protein expression is higher than normal tissues in LUAD tissues.\u003cstrong\u003e (B)\u003c/strong\u003e Immunohistochemical staining showing SMC2 expression in lung adenocarcinoma tissues and normal lung tissues. \u003cstrong\u003e(C)\u003c/strong\u003e SMC2 protein expression in pathological G2 and G3 stages was higher than that in normal group. \u003cstrong\u003e(D-F)\u003c/strong\u003e SMC2 protein expression levels were higher in the mTOR and HIPPO and WNT pathway alteration groups than in the normal group. SMC2, Structural maintenance of chromosomes 2. LUAD, Lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/7cc3365ded36c43a49b7324b.jpg"},{"id":61176134,"identity":"fb7e786b-05f7-4e98-b5ee-4996b858385e","added_by":"auto","created_at":"2024-07-26 15:41:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":381749,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between SMC2 mRNA expression and clinicopathologic features. Expression was upregulated in T2-T4 stage \u003cstrong\u003e(A)\u003c/strong\u003e, N1-N3 stage \u003cstrong\u003e(B)\u003c/strong\u003e, distant metastasis \u003cstrong\u003e(C)\u003c/strong\u003e, gender \u003cstrong\u003e(D)\u003c/strong\u003e, smoker\u003cstrong\u003e (E)\u003c/strong\u003e, high pathologic stage \u003cstrong\u003e(F) \u003c/strong\u003eand OS fatal events \u003cstrong\u003e(G)\u003c/strong\u003e, as well as in patients with DSS/PFI events\u003cstrong\u003e (H-I)\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003e*, p \u0026lt; 0.05, **, p \u0026lt; 0.01, ***, p \u0026lt; 0.001. SMC2, Structural maintenance of chromosomes 2. OS, overall survival. DSS, disease-specific survival. PFI, progression-free interval.\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/dd584ecddb5805898c158d88.jpg"},{"id":61176143,"identity":"5b52bf51-1f86-42a8-984a-dabec322ab27","added_by":"auto","created_at":"2024-07-26 15:41:55","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":985520,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of the diagnostic and prognostic value of SMC2 in LUAD. \u003cstrong\u003e(A)\u003c/strong\u003e ROC curves of SMC2 expression in normal and tumor tissues. Kaplan-Meier analysis showed that LUAD patients with up-regulated SMC2 expression had worse OS \u003cstrong\u003e(B)\u003c/strong\u003e, DSS \u003cstrong\u003e(C)\u003c/strong\u003e and PFI \u003cstrong\u003e(D)\u003c/strong\u003e. Univariate \u003cstrong\u003e(E) \u003c/strong\u003eand multivariate \u003cstrong\u003e(F)\u003c/strong\u003e COX regression analyses identified SMC2 as an independent prognostic factors in LUAD patients. \u003cstrong\u003e(G-J)\u003c/strong\u003eA nomogram and its calibration curve was constructed according to the independent prognostic factors of LUAD. SMC2, Structural maintenance of chromosomes 2. OS, overall survival. DSS, disease-specific survival. PFI, progression-free interval. LUAD, Lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/99accb8edbbc28da6a83eb5c.jpg"},{"id":61176141,"identity":"c30f6b69-56ee-4d40-9041-597070c3c5f1","added_by":"auto","created_at":"2024-07-26 15:41:55","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2134232,"visible":true,"origin":"","legend":"\u003cp\u003eSMC2-related gene analysis, PPI network construction. \u003cstrong\u003e(A)\u003c/strong\u003e The top 20 genes most related to SMC2. \u003cstrong\u003e(B)\u003c/strong\u003e Volcano map showing DEGs in LUAD. \u003cstrong\u003e(C) \u003c/strong\u003eThe intersection of related genes in SMC2 with DEGs in LUAD. \u003cstrong\u003e(D)\u003c/strong\u003e PPI network of DEGs correlated with SMC2. PPI,\u003cstrong\u003e \u003c/strong\u003eProtein–protein interaction. SMC2, Structural maintenance of chromosomes 2. DEGs: differentially expressed genes. LUAD, Lung adenocarcinoma. GO, Gene Ontology. KEGG, Kyoto Encyclopedia of Genes and Genomes.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/a2a1c195c0e497e17cfebd48.jpg"},{"id":61177055,"identity":"532c1289-e15a-452a-baf7-484ed5dbb4a7","added_by":"auto","created_at":"2024-07-26 15:49:55","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1709185,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier analysis to explored the effect of hub gene expression on OS in patients with LUAD. \u003cstrong\u003eA\u003c/strong\u003e NDC80. \u003cstrong\u003eB\u003c/strong\u003e KIFC1.\u003cstrong\u003eC\u003c/strong\u003e SKA1.\u003cstrong\u003eD\u003c/strong\u003e NCAPH.\u003cstrong\u003eE\u003c/strong\u003e ESPL1.\u003cstrong\u003eF\u003c/strong\u003e MELK.\u003cstrong\u003eG\u003c/strong\u003e KIF11.\u003cstrong\u003eH\u003c/strong\u003e SGO1.\u003cstrong\u003eI\u003c/strong\u003e TOP2A. \u003cstrong\u003eJ\u003c/strong\u003e KNL1. \u003cstrong\u003eK\u003c/strong\u003e KIF4A.\u003cstrong\u003eL\u003c/strong\u003e TPX2. \u003cstrong\u003eM\u003c/strong\u003e TICRR. \u003cstrong\u003eN\u003c/strong\u003e TTK. \u003cstrong\u003eO\u003c/strong\u003e KIF14. \u003cstrong\u003eP\u003c/strong\u003e NCAPG. SMC2, Structural maintenance of chromosomes 2. LUAD, Lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/170fdaccbe9a24bab9c9a979.jpg"},{"id":61176139,"identity":"f4764327-bb70-4e9a-9e44-d1da6d51e21d","added_by":"auto","created_at":"2024-07-26 15:41:55","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":688816,"visible":true,"origin":"","legend":"\u003cp\u003eGO and KEGG analysis based on SMC2-related differential genes as well as GSEA. \u003cstrong\u003e(A) \u003c/strong\u003eGO analysis: biological processes. \u003cstrong\u003e(B)\u003c/strong\u003e GO analysis: molecular functions and cellular composition. \u003cstrong\u003e(C)\u003c/strong\u003e KEGG analysis: KEGG analysis based on SMC2-related differential genes. \u003cstrong\u003e(D)\u003c/strong\u003e Enrichment plots by GSEA. GO, Gene Ontology. KEGG, Kyoto Encyclopedia of Genes and Genomes. GSEA, gene set enrichment analysis. SMC2, Structural maintenance of chromosomes 2.\u003c/p\u003e","description":"","filename":"Fig.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/c3a1ec3ed5fbbe0e089ba710.jpg"},{"id":61176140,"identity":"dd69c7e4-25d1-4794-8c55-62223f497952","added_by":"auto","created_at":"2024-07-26 15:41:55","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1777780,"visible":true,"origin":"","legend":"\u003cp\u003eMutations in SMC2 in LUAD patients. \u003cstrong\u003e(A-B)\u003c/strong\u003e Distribution of different types of SMC2 mutations in cancers (in the COSMIC database). \u003cstrong\u003e(C)\u003c/strong\u003e Summary of OncoPrint visualization of SMC2 changes (in the cBioPortal database). \u003cstrong\u003e(D)\u003c/strong\u003e Summary of SMC2 alterations in LUAD from TCGA, TCGA, Firehose Legacy; TCGA, Nature 2014 and TCGA, PanCancer Atlas. \u003cstrong\u003e(E)\u003c/strong\u003e Relationship between SMC2 gene alterations and SMC2 expression levels. \u003cstrong\u003e(F) \u003c/strong\u003eSchematic representation of SMC2 mutations.SMC2, Structural maintenance of chromosomes 2. LUAD, Lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Fig.8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/128cd9713d43515066457bb2.jpg"},{"id":61177058,"identity":"2e3bca91-ae5b-4b90-a6f9-2b3108235fe7","added_by":"auto","created_at":"2024-07-26 15:49:55","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2022674,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation of SMC2 mRNA expression with TILs in LUAD.\u003cstrong\u003e (A)\u003c/strong\u003e The ssGSEA-based algorithm shows the TILs associated with SMC2. \u003cstrong\u003e(B)\u003c/strong\u003e The expression level of SMC2 is negatively correlated with the enrichment of CD8+ T cells, Th 17 cells, mast cells, DC, TFH cells, and B cells. \u003cstrong\u003e(C)\u003c/strong\u003e Demonstration of B cells and MDSC associated with SMC2 using TIMER- and TIDE-based algorithms. \u003cstrong\u003e(D)\u003c/strong\u003e Low enrichment of activated B cells correlates with poor OS. \u003cstrong\u003e(E)\u003c/strong\u003e Enrichment of MDSC is associated with poor OS. \u003cstrong\u003e(F)\u003c/strong\u003e Changes in SMC2 immune subpopulation infiltration in different copy number states. TILs, tumor-infiltrating lymphocytes. SMC2, Structural maintenance of chromosomes 2. LUAD, Lung adenocarcinoma. DC, Dendritic cells. TFH, T follicular helper. ssGSEA, Single-sample gene set enrichment analysis. MDSC, Myeloid-derived suppressor cells. OS, Overall survival. TIDE, Tumor immune dysfunction and exclusion.\u003c/p\u003e","description":"","filename":"Fig.9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/da7333855432f1e92892ab3a.jpg"},{"id":71503262,"identity":"76018e7a-006d-4cbd-b48d-603da04b9c5b","added_by":"auto","created_at":"2024-12-16 09:24:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":11292109,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4659994/v1/8818b859-9e7a-47cd-9bfb-02f139342bfc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"SMC2 as a potential prognostic biomarker in lung adenocarcinoma and its correlation with immune microenvironment","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLung cancer is one of the most prevalent malignant tumors with the worst prognosis worldwide. Lung cancer is divided into two types: non-small cell lung cancer (NSCLC, about 85%) and small cell lung cancer (SCLC, about 15%)(Siegel, Miller and Jemal 2020), while lung adenocarcinoma (LUAD) is the most frequent histologic subtype of NSCLC, accounting for about 60% of cases(Denisenko, Budkevich and Zhivotovsky 2018), and its 5-year survival rate is only 22.1%(Kim et al. 2019). In recent years, new therapies for NSCLC have emerged, including surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy(Herbst, Morgensztern and Boshoff 2018). Nevertheless, the recurrence and mortality rates of LUAD are still high, and the prognosis of patients is poor. Therefore, it is imperative to find more effective biomarkers to facilitate new therapeutic treatments.\u003c/p\u003e \u003cp\u003eStructural maintenance of chromosomes (SMC) proteins, a family of DNA-binding ATPases, are vital for maintaining chromosome integration during cell division(Hirano 2006). Whereas SMC2 is one of the six members of the SMC family, it forms a dimer with SMC4, which binds to three non-SMC proteins to form a pentameric complex called condensin(D\u0026aacute;valos et al. 2012). Condensin has DNA supercoiling activity, which is necessary for chromatin packaging prior to cell division. It has also been shown to be required for the disassembly of sister chromatids at later stages(Hudson, Marshall and Earnshaw 2009; Paliulis and Nicklas 2004). Thus, SMC2 proteins play an important role in the organization of chromatin packaging prior to cell division and the DNA damage response, which is needed for the maintenance of chromosome stability(Murakami-Tonami et al. 2014). It has been revealed that it may have pro-carcinogenic functions, and SMC2 knockdown inhibits tumor growth in colorectal cancer and is involved in cell mitosis(D\u0026aacute;valos et al. 2012). In addition, experimental studies have shown that SMC2 knockdown increased apoptosis in neuroblastoma cells(Murakami-Tonami et al. 2014). Badea et al. demonstrated that the expression level of SMC2 mRNA was significantly higher in human pancreatic cancer tissues than in adjacent normal tissues (Badea et al. 2008). Meanwhile, several other genes of the SMC family have been found to be closely associated with tumorigenesis, such as SMC1A(Yadav et al. 2019), SMC3(Kraft et al. 2019), and SMC4(Jiang et al. 2017). Obviously, to some extent this supports the connection between SMC2 and cancer aggressiveness.\u003c/p\u003e \u003cp\u003eInterestingly, firstly, with the help of RNA sequencing data from TCGA database and a series of bioinformatics analysis tools such as HPA and UALCAN, we found that SMC2 mRNA expression was significantly up-regulated in LUAD tissues, and verified the trend in cell lines and tissues. Secondly, with the help of gene set enrichment analysis (GSEA), we explored its potential pathways of action in LUAD. In addition, the cBioPortal database was utilized to analyze SMC2 mutations in LUAD. TIMER and ssGSEA algorithm were further utilized to analyze the relationship between SMC2 expression and immune cell infiltration in LUAD. Finally, the relationship of SMC2 with immune checkpoints and chemokines and receptors was analyzed using the TISIDB database. Taken together, our findings provide new perspectives on the prognosis and mutation and immunity of SMC2 in LUAD.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003eEthical statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was performed in compliance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Hunan Provincial People\u0026apos;s Hospital. We also selected 8 pairs of fresh LUAD and adjacent non-tumor tissues from our study center. Use of these samples was authorized by the Ethics Committee, and all the patients enrolled in the study gave their informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAccess to RNA sequencing data and clinical information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequencing data and corresponding clinicopathologic information for 539 LUAD samples and 59 adjacent normal samples were downloaded from the TCGA database (https://portal.gdc.cancer.gov/)(Tomczak, Czerwińska and Wiznerowicz 2015). In order to compensate for the relative lack of normal samples when performing differential gene expression analysis, we obtained SMC2 expression data in 347 normal lung tissue samples from the GTEx database (https://www.gtexportal.org/)(2015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative polymerase chain reaction (qPCR)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted from cell lines (BEAS-2B, A549, H1975 and PC9) and 8 pairs of lung adenocarcinoma tissues, and then reverse transcription and qPCR were performed using cDNA synthesis kit (Qiagen, USA) and SYBR real-time PCR kit (Qiagen, USA) according to the instructions of the kits; quantitative analysis was performed using the 2-\u0026Delta;\u0026Delta;Ct method. The primer sequences were as follows: SMC2_F: TCTCAGGTTCGGGCTTCTAAT; SMC2_R: CCTGTACTCTGGTGTTGTTGG; the internal reference gene was \u0026beta;-actin.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUALCAN and HPA database\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUALCAN (http://ualcan.path.uab.edu/) is an interactive web resource that is comprehensive and user-friendly, allowing users to recognize biomarkers or validate potential genes of interest in silico (Chandrashekar et al. 2022). It was used here to assess the protein expression levels of SMC2 at different levels. In addition, the immunohistochemistry of SMC2 was obtained from the Human Protein Atlas(HPA)(Asplund et al. 2012).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNomogram construction and evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndexes with independent prognostic value screened in multivariate COX analyses were included in Nomogram constructs predicting 1-, 3-, and 5-year disease-specific survival (DSS) in patients with LUAD; predictive effects were assessed by calibration curves drawn by the \u0026quot;rms \u0026quot;R software package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein\u0026ndash;protein interaction (PPI)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe first performed gene correlation analysis on SMC2, then, we screened differentially expressed genes (DEGs) with |log2FoldChange| \u0026gt; 1.2 in LUAD to draw volcano plots. Subsequently, the top 800 genes and DEGs most closely related to SMC2 in the TCGA database were cross-tabulated by Venn diagrams, and the target molecules were used for the next step of PPI and Genetic Ontology (GO) analyses. The PPI network was constructed in the STRING(Szklarczyk et al. 2021)\u0026nbsp;database (https://cn.string-db.org/) and then imported into Cytoscape (version 3.10.0) for adjustments to find molecules more related to SMC2 in LUAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO and gene set enrichment analysis (GSEA)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferential genes associated with SMC2 were used for GO and KEGG pathway analysis to explore the biological processes in which SMC2 may be involved in LUAD.GO analysis was used to estimate the biological processes, molecular functions, and cellular compositions of the mRNAs. GSEA is a pathway enrichment analysis algorithm that well controls type I and type II errors and is therefore extensively used in the processing of multi-omics data\u0026nbsp;(Canzler and Hackerm\u0026uuml;ller 2020). The analysis was performed using the \u0026apos;clusterprofiler\u0026apos; in the R package; 1000 operations were performed per analysis, with normalized enrichment scores (NES) \u0026gt;1, false discovery rates (FDR) \u0026lt;0.25 and adjusted p-values \u0026lt;0.05 were considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic alterations in the SMC2 gene in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOn one hand, we analyzed the distribution of different types of SMC2 mutations in cancer using the COSMIC(Bamford et al. 2004)\u0026nbsp;website (https://cancer.sanger.ac.uk/cosmic/); on the other hand, we analyzed the distribution of SMC2 mutations in cancer using three datasets of LUAD from the cBioPortal(Cerami et al. 2012; Gao et al. 2013)\u0026nbsp;(\u003ca href=\"http://www.cbioportal.org/\"\u003ehttp://www.cbioportal.org/\u003c/a\u003e) platform (TCGA, Firehose Legacy; TCGA, Nature 2014; TCGA, PanCancer Atlas) analyzed SMC2 gene alterations in LUAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-sample GSEA (ssGSEA) and TIMER 2.0\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003essGSEA is an extension of the GSEA method that calculates enrichment scores for each sample and gene set pair. In this way, ssGSEA converts gene expression profiles of individual samples into gene set enrichment profiles. Thus, ssGESA was used to analyze the relationship between SMC2 and several tumor-infiltrating immune cells. TIMER 2.0\u0026nbsp;(Li et al. 2020) (http://timer.comp-genomics.org/) is a well-rounded resource that systematically analyzes the relationship between genes and the abundance of immune-infiltrating cells in different types of cancers, enabling users to explore the full range of immunological, clinical, and genomic features of tumors. This study used these data to analyze the correlation between SMC2 and the abundance of immune-infiltrating lymphocytes in the tumor microenvironment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTISIDB databases\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTISIDB\u0026nbsp;(Ru et al. 2019)\u0026nbsp;(http://cis.hku.hk/TISIDB/) is a portal for exploring tumor-immune system interactions. We used this platform to systematically analyze the correlation between SMC2 and immune checkpoint inhibitors, stimulators and chemokines, and receptors in LUAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll RNA sequencing data were performed using R software (version 3.6.3); pROC software package was used to plot ROC curves, Kaplan-Meier analysis and COX analysis were used to assess the effect of SMC2 on LUAD patients\u0026apos; survival outcomes, and spearman correlation analysis was used to describe the correlation between SMC2 expression and tumor-infiltrating lymphocytes (TILs), immune correlations between checkpoint inhibitors, chemokines and related genes, etc., and P\u0026lt;0.05 was considered statistically significantly different.\u003c/p\u003e"},{"header":"3.\tResults","content":"\u003cp\u003e\u003cstrong\u003ePan-cancer analysis of SMC2 mRNA and up-regulation of expression in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven the role of SMC2 in a variety of human cancers, we performed a pan-cancer analysis of SMC2 mRNA levels by using the TCGA database. The results revealed that SMC2 was highly expressed in a number of cancers, including lung adenocarcinoma and uterine corpus endometrial carcinoma, as well as colon adenocarcinoma (see \u003cstrong\u003eFig.\u0026nbsp;1A\u003c/strong\u003e for details). Then, we comprehensively analyzed the effects of SMC2 on overall survival (OS), DSS, and progression-free interval (PFI) in cancer patients, and the results revealed that the upregulation of SMC2 might be adverse to the prognosis of LUAD patients (\u003cstrong\u003eFig. 1, B to D\u003c/strong\u003e). As a result, we chose LUAD as the targeted carcinoma in this study. Subsequently, the expression levels of SMC2 in LUAD are shown in \u003cstrong\u003eFig. 1, E and F\u003c/strong\u003e. This indicates that the expression levels of SMC2 are up-regulated in LUAD tissues, regardless of the inclusion of data from the GTEx database. This trend was as well observed in paired samples (\u003cstrong\u003eFig. 1G\u003c/strong\u003e). Finally, high expression of SMC2 was verified in LUAD cell lines (A549, H1975 and PC9) and human bronchial epithelial cells BEAS-2B, as well as in 8 pairs of LUAD tissues and adjacent normal tissues from our medical center (\u003cstrong\u003eFig. 1, H and I\u003c/strong\u003e). Taken together, these results suggest that SMC2 is highly expressed in LUAD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe expression of SMC at the protein level in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo begin with, in the CPTAC database of the UALCAN platform, we found that the protein expression level of SMC2 in LUAD was increased relative to normal tissues (\u003cstrong\u003eFig. 2A\u003c/strong\u003e). Next, SMC2 protein expression levels in LUAD were derived from immunohistochemical staining data in the HPA database (antibody HPA071309). Consistent with the upregulation of mRNA levels, SMC2 protein expression was also significantly upregulated in LUAD tissues (Patient ID: 1907, 2003, and 4923) relative to normal tissues (Patient ID: 1470, 1678, and 2643) (\u003cstrong\u003eFig. 2B\u003c/strong\u003e). Likewise, protein expression levels of SMC2 were progressively higher in pathological grades 2 and 3 compared with the normal group, although there was no significant change in grade 1 (\u003cstrong\u003eFig. 2C\u003c/strong\u003e). As shown in \u003cstrong\u003eFig. 2, D to F\u003c/strong\u003e, alterations in the mTOR and HIPPO pathways combined with the WNT pathway also contributed to elevated SMC2 protein expression levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelationship between SMC2 and clinicopathologic features\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom \u003cstrong\u003eFig. 3, A to I\u003c/strong\u003e, we can observe that SMC2 was remarkably overexpressed in LUAD patients with T2-T4 stage, N1-N3 stage, M1 stage, higher pathologic stage and OS\u0026nbsp;fatal\u0026nbsp;event,\u0026nbsp;along with in patients with DSS/PFI events. In view of these evidences, we can speculate that SMC2 may adversely influence the survival of patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic and prognostic value of SMC2 in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo start with, the diagnostic effect of SMC2 in LUAD was assessed using ROC curves. As shown in \u003cstrong\u003eFig. 4A\u003c/strong\u003e, the AUC value of SMC2 in distinguishing LUAD tissues from normal tissues was 0.787. The Kaplan-Meier curve revealed the effect of SMC2 expression on the tumor prognosis of patients with LUAD, the SMC2 high-expression group was correlated with poorer OS, DSS, and PFI in LUAD patients, with the risk ratios (HR) of 1.49, 1.72, and 1.51, respectively (\u003cstrong\u003eFig. 4, B to D\u003c/strong\u003e) (p\u0026lt;0.05). In the meantime, we performed univariate (\u003cstrong\u003eFig, 4E\u003c/strong\u003e) and multivariate (\u003cstrong\u003eFig, 4F\u003c/strong\u003e) COX regression analyses, which further confirmed that SMC2 might be an independent prognostic factor for LUAD. In addition, according to the results of COX analysis, we further constructed Nomogram to predict the DSS of LUAD patients at 1-, 3-, and 5 years (\u003cstrong\u003eFig, 4G\u003c/strong\u003e). It was reassuring that the C-index for evaluating its predictive effect was 0.701, and the calibration curve objectively demonstrated the comparatively good agreement between the predicted and actual values (\u003cstrong\u003eFig. 4, H to J\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFiltering mRNA potentially relevant to SMC2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe first selected the top 800 mRNAs that were closely associated with SMC2 in LUAD, and the heatmap in \u003cstrong\u003eFig. 5A\u003c/strong\u003e shows the top 20 molecules. Then, differentially expressed mRNAs in LUAD were screened by volcano plots according to the filtering standard, in which 750 mRNAs were either up- or down-regulated (\u003cstrong\u003eFig. 5B\u003c/strong\u003e). Besides, Venn diagrams further identified overlapping genes in the two groups (\u003cstrong\u003eFig. 5C\u003c/strong\u003e). These 46 target molecules were then constructed into a PPI network through the STRING database, and the hub genes were selected based on the centrality of the nodes (\u003cstrong\u003eFig. 5D\u003c/strong\u003e).\u0026nbsp;In the end, Kaplan-Meier survival analysis of mRNAs (NDC80, KIFC1, SKA1, NCAPH, ESPL1, MELK, KIF11, SGO1, TOP2A, KNL1, KIF4A, TPX2, TICRR, TTK, KIF14, NCAPG) was performed to explore more about their effects on OS in LUAD patients. Interestingly, upregulation of all these molecules in LUAD exacerbated the poor prognosis of OS in patients (\u003cstrong\u003eFig. 6, A to P\u003c/strong\u003e). Apparently, the detrimental effect of these mRNAs on the survival prognosis of LUAD patients is consistent with the tendency of SMC2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExploring the potential mechanisms of SMC2 in LUAD\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the 46 targets mRNA obtained from the pre-screening, we performed GO analysis and found that SMC2 may be involved in the following biological processes, including:\u0026nbsp;nuclear division, mitotic sister chromatid segregation,\u0026nbsp;cellular process involved in reproduction in multicellular\u0026nbsp;organism, DNA replication, et al. Meanwhile, it is involved in cellular components such as condensed chromosome, centromeric region, kinetochore and mitotic spindle, and its potential molecular function is mainly to influence tubulin binding (\u003cstrong\u003eFig.7, A and B\u003c/strong\u003e). In addition, we explored the potential pathway of SMC2 in LUAD using GSEA. As shown in \u003cstrong\u003eFig. 7, C and D\u003c/strong\u003e, the significantly enriched KEGG pathways included\u0026nbsp;cell cycle,\u0026nbsp;oocyte meiosis,\u0026nbsp;homologous recombination,\u0026nbsp;human T-cell leukemia virus 1 infection. The REACTOME pathways included DNA damage telomere stress induced senescence, DNA replication, cell cycle checkpoints, epigenetic regulation of gene expression as well as cellular senescence.\u0026nbsp;These findings may provide a reference for further studies in the future!\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSMC2 genetic alteration in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe COSMIC website shows the distribution of different types of SMC2 mutations in cancer (\u003cstrong\u003eFig. 8, A and B\u003c/strong\u003e). Missense substitutions were the most common type of mutation, following by synonymous substitutions, and G\u0026gt;A, C\u0026gt;T and A\u0026gt;G were the most common substitution mutations. Next, the SMC2 gene mutations in LUAD were analyzed by three datasets in the cBioPortal database. The results indicated that SMC2 was genetic alteration in 2.4% of LUAD patients (\u003cstrong\u003eFig. 8C\u003c/strong\u003e). As shown in \u003cstrong\u003eFig. 8D\u003c/strong\u003e, we can visualize the specific types and frequency of gene mutations. SMC2 mRNA expression was elevated in the shallow deletion group compared with the diploid group, and interestingly, the expression of gain groups was also increased (\u003cstrong\u003eFig. 8E\u003c/strong\u003e). In the LUAD samples, 23 SMC2 missense mutation sites were shown, one of which was K879N, suggesting that this is one of the protein activation hotspots, as well as two SMC2 truncating mutation sites (\u003cstrong\u003eFig. 8F\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between SMC2 expression and immune characteristics in LUAD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further understand the role of SMC2 in LUAD, we first analyzed the correlation between SMC2 and TILs. Based on the ssGSEA algorithm, we found that SMC2 was negatively correlated with CD8\u003csup\u003e+\u003c/sup\u003e T cells, Th 17 cells, mast cells, dendritic cells (DC), T follicular helper cells (TFH), B cells, etc (\u003cstrong\u003eFig. 9, A and B\u003c/strong\u003e). On the other hand, using the TIMER algorithm and the TIDE algorithm in the TIMER database, we found that SMC2 was negatively and positively correlated with activated B cells and MDSC, respectively (\u003cstrong\u003eFig. 9C\u003c/strong\u003e). Notably, when activated B cells were enriched, the OS of LUAD patients was significantly better, however, when MDSC was enriched, the OS of LUAD patients was dramatically worse (\u003cstrong\u003eFig. 9, D and E\u003c/strong\u003e). Taking the above information together, it is reasonable to hypothesize that the cancer-promoting effects of SMC2 may be related to a certain extent to the low enrichment of B cells as well as the high enrichment of MDSC. In \u003cstrong\u003eFig. 9F\u003c/strong\u003e, the arm-level deletion of SMC2 copy number was associated with reduced abundance of CD8\u003csup\u003e+\u003c/sup\u003e T cells, CD4\u003csup\u003e+\u003c/sup\u003e T cells, neutrophils, and dendritic cells when compared with the diploid/normal state. These results indicate that copy number changes of SMC2 in LUAD may be an element that regulates the immune microenvironment.\u003c/p\u003e\n\u003cp\u003eImmune checkpoints play a vital role in the immune microenvironment of LUAD, and these directly regulate the resident's anti-tumor immune response(Chi et al. 2021). Therefore, in this case, we next analyzed the association between SMC2 and immunoinhibitor (\u003cstrong\u003eFig. 10A\u003c/strong\u003e). Interestingly, SMC2 was significantly positively correlated with CD274 (r = 0.298, \u003cem\u003ep\u003c/em\u003e \u0026lt; 6.26e-12), PDCD1LG2 (r = 0.226, \u003cem\u003ep\u003c/em\u003e \u0026lt; 2.29e-07), TGFBR1 (r = 0.208, \u003cem\u003ep\u003c/em\u003e \u0026lt; 1.85e-06), and LAG3 (r = 0.181, \u003cem\u003ep\u003c/em\u003e \u0026lt; 3.54e-05) (\u003cstrong\u003eFig. 10B\u003c/strong\u003e). We also analyzed beside the association between SMC2 and immunostimulator (\u003cstrong\u003eFig. 10D\u003c/strong\u003e). It is also intriguing that SMC2 was markedly negatively correlated with TNFSF13 (r = -0.471, \u003cem\u003ep\u003c/em\u003e \u0026lt; 2.2e-16), TMEM173 (r = -0.404, \u003cem\u003ep\u003c/em\u003e \u0026lt; 2.2e-16), TNFRSF14 (r = -0.399, \u003cem\u003ep\u003c/em\u003e \u0026lt; 2.2e-16), and HHLA2 (r = -0.282, \u003cem\u003ep\u003c/em\u003e \u0026lt; 7.53e-11) (\u003cstrong\u003eFig. 10C\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eChemokines and chemokine receptors are essential for tumor infiltration by immune cells(Li et al. 2015). Therefore, we analyzed the correlation between SMC2 expression levels and immune cell chemokines and receptors in LUAD using the TISIDB database. Heatmap results showed that several chemokines and receptors were significantly correlated with SMC2 expression in LUAD (\u003cstrong\u003eFig. 11, A and D\u003c/strong\u003e). Next, we concretely analyzed the correlation between SMC2 expression and chemokines/receptors. The results showed that SMC2 expression was negatively correlated with CCL14 (r = -0.378, \u003cem\u003ep\u003c/em\u003e \u0026lt; 2.2e-16), CCL17 (r = -0.363, \u003cem\u003ep\u003c/em\u003e \u0026lt; 5.74e-18), CXCL16 (r = -0.347, \u003cem\u003ep\u003c/em\u003e \u0026lt; 5.66e-16), CX3CL1 (r = -0.268, \u003cem\u003ep\u003c/em\u003e \u0026lt; 6.93e-10), CX3CR1 (r = -0.31, \u003cem\u003ep\u003c/em\u003e \u0026lt; 7.89e-13), CCR6 (r = -0.246, \u003cem\u003ep\u003c/em\u003e \u0026lt; 1.56e-08), CCR7 (r = -0.197, \u003cem\u003ep\u003c/em\u003e \u0026lt; 6.6e-06), and CXCR5 (r = -0.14, \u003cem\u003ep\u003c/em\u003e =0.00146) (\u003cstrong\u003eFig. 11, B and C\u003c/strong\u003e), and these results revealed that the SMC2 gene may play an influential role in tumor immune. In addition, we analyzed the relationship between SMC2 and LUAD immune subtypes. As shown in \u003cstrong\u003eFig. 11E\u003c/strong\u003e, SMC2 was highly expressed in type C2 (IFN-γ-dominant) and type C4 (lymphocyte-depleted), while it was least expressed in type C3 (inflammatory). This implies that the expression of SMC2 is directly related to the immune microenvironment of LUAD. Finally, The Tumor Immune Dysfunction and Rejection (TIDE) algorithm is extensively used to predict cancer immunotherapy response, with higher TIDE scores being associated with poorer immunotherapy outcomes\u0026nbsp;(Jiang et al. 2018). TIDE scores were dramatically higher in those with high SMC2 expression compared to those with low expression, which resulted in a notably lower rate of response to their immunotherapy (\u003cstrong\u003eFig. 11F\u003c/strong\u003e).\u003c/p\u003e"},{"header":"4.\tConclusion","content":"\u003cp\u003eIn this article, we have presented the first systematic evidence for SMC2 in LUAD; we found that SMC2 expression is up-regulated in LUAD and correlates with poor clinical prognosis of patients. In addition, SMC2 expression was negatively correlated with inhibitory TILs, immunostimulator, chemokines, and receptors; its cross-talk with these factors may contribute to the malignant phenotype of LUAD and may provide a potential therapeutic target for LUAD patients.\u003c/p\u003e"},{"header":"Discussion ","content":"\u003cp\u003eThe structural maintenance of chromosomes(SMC) family is a group of prokaryotic and eukaryotic chromosomal proteins that may be one of the crucial components in establishing the ordered structure of chromosomes.SMC2 is the second member of the SMC family from budding yeast, and contains all the putative structural domains characteristic of a typical SMC family member: a nucleotide-binding region, two coiled-coil regions separated by a \"hinge,\" and the carboxy-terminus of Smclp (DA box) itself(Strunnikov, Hogan and Koshland 1995). The SMC2 protein has also been demonstrated to be a subunit of the human condensin complex(Hudson, Marshall and Earnshaw 2009). In recent years, there is evidence that the SMC family is associated with human cancers, including pancreatic, hepatocellular, and colorectal cancers, etc(Feng et al. 2019; Je, Yoo and Lee 2014; Nie et al. 2021; Yan et al. 2022). SMC2 belongs to the condensin complex, which has also been reported to be associated with apoptosis in neuroblastoma cells(Murakami-Tonami et al. 2014). Here, we found by bioinformatics analysis that SMC2 expression was up-regulated in LUAD samples, had a favorable diagnostic effect on LUAD, and was associated with worsening of OS, DSS and PFI in patients. Obviously, these findings are similar to those reported in previous studies, which implies that SMC2 may be a promising biological marker for LUAD.\u003c/p\u003e\n\u003cp\u003eIt is well-known that the molecular crosstalk in the LUAD tumor microenvironment is a complicated network. In this study, we revealed some key proteins that may be closely related to SMC2 by correlation analysis and PPI network construction, including TTK, TOP2A, TICRR, NCAPH, SKA1, TPX2, NDC80 and SGO1, etc(Chen et al. 2020; Li, Meng and Zhang 2022; Xu et al. 2023; Zhou et al. 2020). It is interesting to point out that these molecules have been shown to be associated with the malignant phenotype and poor prognosis of LUAD in previous studies. These evidences not only provide a possible regulation network, but also seem to validate indirectly the malicious function of SMC2 in LUAD. Genetic alterations are closely associated with cancer. Several genetic alterations have been shown to be associated with the occurrence and development of LUAD(Ricciuti et al. 2022; Wohlhieter et al. 2020). We found that missense substitutions were the most common type of mutation followed by synonymous substitutions in 734 samples. And G\u0026gt;A (27.95%), C\u0026gt;T (14.77%) and A\u0026gt;G (14.55%) were the most common substitution mutations. Furthermore, the frequency of SMC2 gene mutation was only 2.4% in LUAD, which was mainly missense mutation. Thus, exploring the mechanism by which mutation affects the prognosis and therapeutic response of patients with LUAD could bring more benefits to the patients.\u003c/p\u003e\n\u003cp\u003eSimilar to other members of the SMC family, SMC2 is thought to be involved in cell cycle regulation(Thadani et al. 2018). In this paper, the results of GO, KEGG and GSEA also confirmed the applicability of this property of SMC2 in LUAD. On the other hand, tumor development is related to the tumor microenvironment (TME). TME consists of immune cells, extracellular matrix, mesenchymal stromal cells and inflammatory mediators, which have an impact on tumor growth, metastasis and clinical survival outcomes(Wang et al. 2022a). Previous studies have reported that immune infiltration can influence patient prognosis, and tumor-infiltrating lymphocyte grading is an independent predictor of sentinel lymph node status in patients with tumors(Slack and Chinnaiyan 2019). It has been found that B cells are the tumor-infiltrating lymphocytes with the highest correlation with risk scores, especially in patients with metastatic LUAD(Shao et al. 2023). Research has amply demonstrated the ability of CD8\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eT cells to recognize and eradicate cancer cells(van der Leun, Thommen and Schumacher 2020). The use of CD8\u003csup\u003e+\u003c/sup\u003e T cells for the detection and eradication of cancer cells has been a focus of clinical cancer therapy for more than 20 years(Wang et al. 2022b). Guo et al. identify circulating T follicular helper (TFH) cells that may play an essential role in the development of NSCLC pathogenesis(Guo et al. 2017). Interestingly, we found that SMC2 expression was negatively correlated with the level of infiltration of these cells, which is consistent with previous findings, suggesting to some extent that tumorigenesis may be associated with the absence or low enrichment of lymphocytes, which further contributes to the malignant progression of the disease. In addition, it is notable that the low enrichment of B cells in LUAD was associated with the deterioration of OS (\u003cstrong\u003eFig. 9D\u003c/strong\u003e), which also seems to further corroborate the results of ssGSEA with TIMER. MDSC are immature myeloid cells that promote tumor growth and metastasis by inducing immunosuppression, which ultimately affects patient outcomes(Kalathil and Thanavala 2021). In our study, SMC2 expression was positively correlated with the level of MDSC infiltration, and highly enriched MDSC led to a worse prognosis (\u003cstrong\u003eFig. 9E\u003c/strong\u003e). Therefore, SMC2 may inhibit the function of immune cells by increasing the level of MDSC infiltration, thus becoming a potential immunotherapeutic target.\u003c/p\u003e\n\u003cp\u003eIn recent years, systemic treatment options for patients with advanced LUAD have been dramatically expanded to include not only chemotherapy and targeted therapy, but also immune checkpoint inhibitors (ICIs)(Chi et al. 2021). Encouragingly, our study showed that SMC2 was positively correlated with immune checkpoints such as CD274, PDCD1LG2, TGFBR1 and LAG3 in LUAD. This evidence suggests that SMC2 may synergize with immune checkpoints, thus further exacerbating the immunosuppressive state in the TME.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecent studies have shown that chemokines can directly or indirectly regulate the TME and biological phenotype, affecting angiogenesis, tumorigenesis, malignant metastasis, etc(Nagarsheth, Wicha and Zou 2017). The correlation between the expression level of SMC2 and the expression of chemokines and receptors in LUAD was analyzed using the TISIDB database. The results showed that the expression level of SMC2 was negatively correlated with the expression of CCL14, CCL17, CXCL16, CX3CL1, CX3CR1, CCR6, CCR7 and CXCR5, suggesting that high expression of SMC2 may inhibit the migration of immune cells to the TME. CCL17, also known as Thymus and activation-regulated chemokine (TARC), is a C-C chemokine often associated with type 2 immune responses(Islam and Luster 2012), and CCR6 controls integrin-mediated adhesion in B cells(Matsukawa et al. 2000; Zlotnik and Yoshie 2012). The CXCR5\u003csup\u003e+\u003c/sup\u003e subpopulation of CD8\u003csup\u003e+\u003c/sup\u003e T cells may contribute to antitumor activity(Xing et al. 2017), and the receptor for CX3CL1, CX3CR1, in turn, controls leukocyte survival and NK cell activation(Ness et al. 2006). The strong correlation of SMC2 with these molecules may explain how SMC2 regulates immune infiltration in LUAD, and means that its interaction with chemokines in tumors may also be one of the factors contributing to the malignant phenotype of tumors. Additionally, the TIDE algorithm was employed to investigate the responsiveness of patients in different SMC2 expression groups to immune checkpoint therapy. Our finding that the TIDE score of the SMC2 high expression group was obviously higher than the SMC2 low expression group, which suggested that the immunotherapy response rate of patients in the SMC2 high expression group was lower. Consequently, based on this evidence, combined blockade of SMC2 and immune checkpoints may be a promising strategy for the treatment of LUAD in the foreseeable future.\u003c/p\u003e\n\u003cp\u003eFinally, although we performed a systematic analysis of SMC2, there are some limitations of this study. First, the data in this study were obtained from public databases, and experimental validation was limited to SMC2 expression in lung adenocarcinoma cell lines and tissues. Secondly, the exact mechanism of SMC2 in LUAD tumorigenesis and development is still unclear and needs to be further refined in subsequent in vivo and in vitro experiments. Third, despite the fact that we believe that SMC2 expression is closely related to immune infiltration and prognosis in LUAD, we lack direct evidence that SMC2 affects prognosis through its involvement in immune infiltration. These issues above deserve further exploration in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSMC2, Structural maintenance of chromosomes 2; LUAD, lung adenocarcinoma; TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus;\u0026nbsp;qPCR, quantitative polymerase chain reaction；OS, overall survival; DSS, disease-specific survival; PFI, progression-free interval; GO: Gene ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes;\u0026nbsp;GSEA, gene set enrichment analysis;\u0026nbsp;TILs,\u0026nbsp;tumor-infiltrating lymphocytes; TFH,\u0026nbsp;T follicular helper;\u0026nbsp;TIDE,\u0026nbsp;tumor immune dysfunction and exclusion; ssGSEA, Single-sample\u0026nbsp;gene set enrichment analysis.\u0026nbsp;MDSC, Myeloid-derived suppressor cells.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXCT and FQZ designed the study. YL, HGC and YP were responsible for the statistical analysis. FQZ wrote and plotted the manuscript as well as performed the experiments. XCT reviewed and revised the manuscript. All authors carefully read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Ren-Shu Fund of Hunan Provincial People's Hospital (Grant No. RS201819).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of the article are available within the article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and Consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments involving human tissues complied with the principles of the Declaration of Helsinki.\u0026nbsp;The patient data in this study, both from public databases and studies involving human subjects, was reviewed and approved by the Ethics Committee of Hunan Provincial People's Hospital（NO.2023-187）. All patients/participants provided written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare that they have no conflict of interest related to this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e2015. Human genomics. The genotype-tissue expression (gtex) pilot analysis: Multitissue gene regulation in humans. \u003cem\u003eScience (New York, N.Y.)\u003c/em\u003e 348:648-660. doi: 10.1126/science.1262110.\u003c/li\u003e\n \u003cli\u003eAsplund, A., P. H. Edqvist, J. M. Schwenk, F. Pont\u0026eacute;n. 2012. 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The chemokine superfamily revisited. \u003cem\u003eImmunity\u003c/em\u003e 36:705-716. doi: 10.1016/j.immuni.2012.05.008.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SMC2, Lung adenocarcinoma, Poor prognosis, Immune infiltration, Biomarker.","lastPublishedDoi":"10.21203/rs.3.rs-4659994/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4659994/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStructural maintenance of chromosome 2 (SMC2) has been recognized to play an important role in a variety of cancers, but its function in lung adenocarcinoma (LUAD) remains poorly understood.First, we explored the expression level of SMC2 and its relationship with clinical pathological features using the LUAD dataset from the TCGA database. The expression of SMC2 in LUAD cell lines and tissues was verified using quantitative polymerase chain reaction (qPCR). Secondly, Kaplan-Meier analysis, COX regression analysis and Nomogram construction were employed to assess the prognostic potential of SMC2 in LUAD. In addition, the biological behavior and possible signaling pathways of SMC2 were forecasted by protein-protein interaction (PPI) networks, single-gene correlation analysis, genetic ontology (GO) and genome enrichment analysis (GSEA), together with Kyoto Encyclopedia of Genes and Genomes (KEGG). At last, a systematic analysis of crosstalk and mutations between SMC2 and immune features in the tumor microenvironment (TME) was conducted using a single-sample GSEA algorithm, the Tumor Immune Dysfunction and Rejection (TIDE) algorithm, the TIMER 2.0 and TISIDB databases, as well as the cBioportal database.SMC2 was markedly up-regulated in LUAD cell lines and tissues and was strongly correlated with adverse clinicopathological features and prognosis. ROC curves showed a good diagnostic effect (AUC value: 0.787). The enrichment analysis suggested that SMC2 might be involved in the regulation of LUAD cell cycle. The TIMER algorithm and ssGSEA algorithm showed that SMC2 was associated with suppressive immune cells (e.g., B cells) in LUAD. In addition, SMC2 may interact with the expression of molecules such as NDC80, KIFC1, SKA1, NCAPH, ESPL1, MELK, KIF11, SGO1, TOP2A, KNL1, KIF4A, TPX2, TICRR, TTK, KIF14, NCAPG and others to promote LUAD progression. Evidence from the TISIDB database shows that SMC2 is positively associated with immunosuppressive genes such as CD274, PDCD1LG2, TGFBR1 and LAG3. However, it is inversely associated with chemokines and receptors such as CCL14, CCL17, CXCL16, CX3CL1, CX3CR1, CCR6, CCR7 and CXCR5. Also, as predicted by the TIDE algorithm, patients with high SMC2 expression responded poorly to immunotherapy.Our analysis shows that the high expression status of SMC2 in LUAD is associated with poor patient outcomes and describes some potential reasons for this poor prognosis. These findings suggest that SMC2 is associated with the malignant progression of LUAD and therefore may be a potential target for improving outcomes in LUAD in the foreseeable future.\u003c/p\u003e","manuscriptTitle":"SMC2 as a potential prognostic biomarker in lung adenocarcinoma and its correlation with immune microenvironment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-26 15:41:50","doi":"10.21203/rs.3.rs-4659994/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c087b2f-9e0a-4a9a-9f6e-8f1d7c930036","owner":[],"postedDate":"July 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-16T09:24:13+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-26 15:41:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4659994","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4659994","identity":"rs-4659994","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}