
Non-chromosomal structure maintenance protein condensin complex I subunit H (NCAPH) has been reported to play a regulatory role in a variety of cancers and is associated with tumor poor prognosis. This study aims to explore the potential role of NCAPH with a view to providing insights on pathologic mechanisms.
The expression of NCAPH in different tumors was explored by The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx). The prognostic value of NCAPH was retrieved through GEPIA and Kaplan-Meier Plotter databases. Tumor Immunity Estimation Resource (TIMER) and Single-Sample Gene Set Enrichment Analysis (GSEA) to search for the association of NCAPH with tumor immune infiltration. The cBioPortal and PhosphoSite Plus databases showed NCAPH phosphorylation status in tumors. Gene set enrichment analysis (GSEA) was performed using bioinformatics.
Our findings revealed that NCAPH showed high expression levels in a wide range of tumor types, and was strongly correlated with the prognosis of patients. Moreover, a higher phosphorylation level at S59, S67, S76, S190, S222 and T38 site was discovered in head and neck squamous cell carcinoma (HNSC). NCAPH overexpression was positively correlated with the infiltration level of CD8+T cells and myeloid dendritic infiltration in breast cancer and thymoma.
The up-regulation of NCAPH was significantly correlated with the poor prognosis and immune infiltration in pan-cancer, and NCAPH could be served as a potential immunotherapeutic target for cancers.
Citation: Ying Liu, Xiao Ma, Linyuan Feng, Zhenhua Lin, Xianchun Zhou. An integrative pan-cancer analysis reveals the carcinogenic effects of NCAPH in human cancer[J]. Mathematical Biosciences and Engineering, 2023, 20(1): 76-92. doi: 10.3934/mbe.2023005
[1] | Ye Hu, Meiling Wang, Kainan Wang, Jiyue Gao, Jiaci Tong, Zuowei Zhao, Man Li . A potential role for metastasis-associated in colon cancer 1 (MACC1) as a pan-cancer prognostic and immunological biomarker. Mathematical Biosciences and Engineering, 2021, 18(6): 8331-8353. doi: 10.3934/mbe.2021413 |
[2] | Sidan Long, Shuangshuang Ji, Kunmin Xiao, Peng Xue, Shijie Zhu . Prognostic and immunological value of LTB4R in pan-cancer. Mathematical Biosciences and Engineering, 2021, 18(6): 9336-9356. doi: 10.3934/mbe.2021459 |
[3] | Tongmeng Jiang, Pan Jin, Guoxiu Huang, Shi-Cheng Li . The function of guanylate binding protein 3 (GBP3) in human cancers by pan-cancer bioinformatics. Mathematical Biosciences and Engineering, 2023, 20(5): 9511-9529. doi: 10.3934/mbe.2023418 |
[4] | Chunpei Ou, Qin Peng, Changchun Zeng . An integrative prognostic and immune analysis of PTPRD in cancer. Mathematical Biosciences and Engineering, 2022, 19(6): 5361-5379. doi: 10.3934/mbe.2022251 |
[5] | Tao Huang . TRPV1 is a potential biomarker for the prediction and treatment of multiple cancers based on a pan-cancer analysis. Mathematical Biosciences and Engineering, 2022, 19(8): 8361-8379. doi: 10.3934/mbe.2022389 |
[6] | Dong-feng Li, Aisikeer Tulahong, Md. Nazim Uddin, Huan Zhao, Hua Zhang . Meta-analysis identifying epithelial-derived transcriptomes predicts poor clinical outcome and immune infiltrations in ovarian cancer. Mathematical Biosciences and Engineering, 2021, 18(5): 6527-6551. doi: 10.3934/mbe.2021324 |
[7] | Jie Wang, Md. Nazim Uddin, Rehana Akter, Yun Wu . Contribution of endothelial cell-derived transcriptomes to the colon cancer based on bioinformatics analysis. Mathematical Biosciences and Engineering, 2021, 18(6): 7280-7300. doi: 10.3934/mbe.2021360 |
[8] | Jianpei Hu, Zengnan Mo . Dissection of tumor antigens and immune landscape in clear cell renal cell carcinoma: Preconditions for development and precision medicine of mRNA vaccine. Mathematical Biosciences and Engineering, 2023, 20(2): 2157-2182. doi: 10.3934/mbe.2023100 |
[9] | Urszula Foryś, Jan Poleszczuk . A delay-differential equation model of HIV related cancer--immune system dynamics. Mathematical Biosciences and Engineering, 2011, 8(2): 627-641. doi: 10.3934/mbe.2011.8.627 |
[10] | Linlin Tan, Dingzhuo Cheng, Jianbo Wen, Kefeng Huang, Qin Zhang . Identification of prognostic hypoxia-related genes signature on the tumor microenvironment in esophageal cancer. Mathematical Biosciences and Engineering, 2021, 18(6): 7743-7758. doi: 10.3934/mbe.2021384 |
Non-chromosomal structure maintenance protein condensin complex I subunit H (NCAPH) has been reported to play a regulatory role in a variety of cancers and is associated with tumor poor prognosis. This study aims to explore the potential role of NCAPH with a view to providing insights on pathologic mechanisms.
The expression of NCAPH in different tumors was explored by The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx). The prognostic value of NCAPH was retrieved through GEPIA and Kaplan-Meier Plotter databases. Tumor Immunity Estimation Resource (TIMER) and Single-Sample Gene Set Enrichment Analysis (GSEA) to search for the association of NCAPH with tumor immune infiltration. The cBioPortal and PhosphoSite Plus databases showed NCAPH phosphorylation status in tumors. Gene set enrichment analysis (GSEA) was performed using bioinformatics.
Our findings revealed that NCAPH showed high expression levels in a wide range of tumor types, and was strongly correlated with the prognosis of patients. Moreover, a higher phosphorylation level at S59, S67, S76, S190, S222 and T38 site was discovered in head and neck squamous cell carcinoma (HNSC). NCAPH overexpression was positively correlated with the infiltration level of CD8+T cells and myeloid dendritic infiltration in breast cancer and thymoma.
The up-regulation of NCAPH was significantly correlated with the poor prognosis and immune infiltration in pan-cancer, and NCAPH could be served as a potential immunotherapeutic target for cancers.
Cancer is considered to be the "number one killer" of human beings and is called an incurable disease [1]. Cancer has become a major enemy that endangers human health and life, and it predicts a poor prognosis of patients with cancer [2]. In recent years, relevant studies have shown that the occurrence and development of cancer are closely related to environmental factors and lifestyle changes [3]. To better understand the progression of cancer, joint efforts are needed in many aspects.
Non-chromosomal structure maintenance protein condensin complex I subunit H (non-SMC condensing I complex subunit H, NCAPH) encoded by a gene located on chromosome 2q11.2, belongs to the bar gene family and a regulatory subunit of the condensin complex [4,5,6,7]. It has been found to be associated with cell proliferation and plays a key role in mitotic chromosome structure and segregation [8,9,10]. Many studies have shown that NCAPH is involved in the evolution of various malignant tumors. Sun et al. found that NCAPH is significantly higher in cancer tissues than in normal non-cancerous tissue, and its high expression is closely correlated with the poor prognosis of patients in hepatocellular carcinoma [11]. It has been reported that high expression of NCAPH promoted the proliferation, migration, and invasion of gastric cancer cells in vitro and in vivo [12]. However, the progression of the specific mechanism of NCAPH in cancer immunology has not been well validated yet.
It is well known that tumor microenvironment (TME) is mainly composed of immune cells including CD8+T cells, CD4+T cells, regulatory T cells, tumor-associated macrophages (TAMs), tumor-associated neutrophils, and natural killer (NK) cells. They interact in the complex TME to regulate tumor development, invasion and metastasis [13,14]. In most cases, the main role of the TME is immunosuppression, which is able to inhibit the activation of lymphocytes in tumor tissue and significantly affect the antitumor effects of drugs. However, current immunotherapy works only in a subset of patients, so we need to find more effective therapeutic targets.
In this study, we accessed the TCGA and GEO databases to analyze the significance of NCAPH in cancer. Various databases such as TIMER, GSEA, Kaplan-Meier Plotter, etc. have shown that NCAPH has significant clinical correlations with the poor prognosis, DNA repair and replication, protein phosphorylation, immune cell infiltration and immune markers. These results revealed the prognostic value of NCAPH and a clear correlation between NCAPH and immune infiltration in pan-cancer.
TIMER2 database (http://timer.cistrome.org/) uses RNA-Seq expression profiling data to detect the infiltration of immune cells in tumor tissues. TIMER provides the infiltration of six types of immune cells (B cells, CD4+T cells, CD8+T cells, Neutrphils, Macrophages and Dendritic cells). We analyzed the different expression of NCAPH in tumor tissues and the correlation with immune infiltration with TIMER algorithm [15].
For tumors that are without normal tissues data, the module of GEPIA2 (http://gepia2.cancer-pku.cn/#analysis) was further adopted to analyze the box plots of NCAPH expression in the remaining cancers [16]. GEPIA2 also contains cancers of genotype-tissue expression (GTEx) database, which provides more convincing evidence. Moreover, the GEPIA2 database could also be utilized to retrieve the NCAPH expression in different pathological stages (including stage Ⅰ–Ⅳ).
The UALCAN portal (http://ualcan.path.uab.edu/analysis-prot.html) was intended to analyze protein expression by taking advantage of data from clinical proteomic tumor analysis consortium (CPTAC) [17]. We obtained available datasets of multiple tumors to explore the total protein expression of NCAPH, including its expression in liver, lung, cervical, glioma, and pancreatic cancers.
GEPIA2 database was performed to generate the survival significance map data of NCAPH more than 30 different forms of cancer, consisting of RFS (Recurrence Free Survival), DMFS (Distant Metastasis Free Survival), PPS (Post Progression Survival), PFS (Progression Free Survival), DSS (Disease Specific Survival), and FP (Full Period of Service). We also obtained the survival plots through the Kaplan-Meier plotter database, which utilized the log-rank test for hypothesis test.
The cBioPortal (http://www.cbioportal.org) web was applied to explore the mutation frequency, copy number alteration and mutation type of NCAPH [18]. We also obtained the detailed genetic alteration information in the mutations section. In addition, database searches also uncovered associations of NCAPH gene alterations with specific cancer prognoses (OS, DSS, DFS, RFS, and PFS).
PhosphoSite Plus (https://www.phosphosite.org) website supplied comprehensive information support to study on protein post-translational modifications (PTMs) [19]. Using this website, we obtained the phosphorylation features of the NCAPH protein. The diversity of phosphorylation alteration of NCAPH protein in tumor and normal tissues was further analyzed via the UALCAN portal. The expression and localization of human proteins in different tissues and organs can be retrieved through HPA (https://www.proteinatlas.org) [20]. Furthermore, HPA detected NCAPH expression in a number of different cancer types.
The TIMER1 database (https://cistrome.shinyapps.io/timer/) was originally a database used to retrieve tumor-infiltrating immune cell (TIIC) abundance in all TCGA tumors, and it was the first version of TIMER2 database [21]. Herein, the TIMER1 database was used to analyze the relevance of NCAPH and TIICs in different cancers. Then, the TIMER2 database further performed to re-evaluate the relationship among three TIICs and NCAPH expression in the overall cancer level.
The STRING (https://string-db.org/) was defined to display protein-protein interaction networks, and can be used for functional enrichment analysis [22]. Therefore, we first retrieved the top 50 proteins with potential binding to NCAPH via the site. Subsequently, we identified the top 100 targeted genes that may be related to NCAPH from the "Similar Gene Detection" module of GEPIA2. Jvenn supported intersection analysis and produce Venn diagrams [23].
We performed gene ontology (GO) enrichment and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis through bioinformatics resources web server applied for annotation, visualization and integrated discovery (DAVID) [24,25]. Functional annotation charts of KEGG pathway and GO enrichment analysis which that included biological process (BP), cellular component (CC), and molecular function (MF), were plotted using bioinformatics, freely available online. (http://www.bioinformatics.com.cn) [26].
Data changes on NCAPH were obtained through the cBioPortal website, and data related to its mRNA expression were retrieved. The prognostic significance of each variable in the articles was assessed by Kaplan-Meier survival curves and compared using the log-rank test [27]. Meanwhile, Spearman's correlation test was used for correlation analysis. Unless otherwise specified (P < 0.05), the difference was statistically significant.
Difference in expression of NCAPH between human cancer and normal tissues was discovered via TIMER2 database. According to Figure 1A, NCAPH in tumor tissues was obviously higher than that of normal tissues, including bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), 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), pancreatic adenocarcinoma (PAAD), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), uterine corpus endometrial carcinoma (UCEC) (P < 0.05), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and pheochromocytoma and paraganglioma (PCPG) (P < 0.01), but it was no markedly change in thyroid carcinoma (THCA). Similarly, the GEPIA2 database was searched for NCAPH mRNA expression in pan-cancer tissues. It was up-regulated significantly in lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), PAAD, thymoma (THYM), sarcoma (SARC) and uterine carcinosarcoma (UCS) compared with that of normal tissues, while down-regulated in acute myeloid leukemia (LAML) (Figure 1B, P < 0.05).
Consistent with the results, we found that the total protein level of NCAPH was markedly elevated in primary tissues than in normal tissues based on the CPTAC dataset (Figure 1C, P < 0.001). The correlation between NCAPH and the clinical stage of various tumors suggested that the expression of NCAPH was related to the clinical stage of certain cancers, consisting of KICH, adrenocortical carcinoma (ACC), KIRC, KIPR, OV, LUSC, LIHC, LUAD, UCS, TGCT, SKCM, BRCA and thyroid carcinoma (THCA). In contrast, the expression of NCAPH in clinical stage Ⅳ was lower in LUSC and LIHC than in other stages (Figure 1D, P < 0.05). These data suggested that NCAPH expression was generally overexpression in cancer tissues, and it might be involved in the malignant progression of tumors.
The prognostic significance of NCAPH expression in different tumor patients was evaluated using the TCGA and GEO datasets. It turned out that the OS of patients with NCAPH overexpression was significantly shorter than patients in the low expression group, covering ACC, KIRC, KIRP, brain lower grade glioma (LGG), LIHC, LUAD, MESO, PAAD, SARC and uveal melanoma (UVM) (P < 0.05) (Figure 2A). At the same time, NCAPH overexpression was also turned out to reduce DFS in ACC, KICH, KIRC, KIRP, LGG, LIHC, PAAD, PRAD, SARC, TGCT, THCA and UVM (P < 0.05) (Figure 2B). We further found that the overexpression of NCAPH could predict unfavorable outcome in Breast Cancer (P < 0.01), Liver Cancer (P < 0.01), Lung Cancer (P < 0.01) and Ovarian Cancer (P < 0.05) through Kaplan-Meier plotter database (P < 0.05). While the overexpression of NCAPH showed patients with gastric cancer have a longer survival period, the specific molecular mechanism needs to be further studied (P < 0.05) (Figure 3). Thus, the results indicated that overexpression of NCAPH in most tumors predicts a short survival in patients.
To further elucidate the potential molecular mechanism of NCAPH in tumorigenesis, NCAPH-related genes were screened for biological function analysis. Based on STRING, we retrieved the top 50 NCAPH-binding proteins validated by experimental data, and exhibited their PPI network (Figure 4A). Figure 4B showed that NCAPH expression was notably related to cell proliferation-related genes (BUB1, R = 0.84; CCNB2, R = 0.82; CDCA5, R = 0.82) and cell cycle regulation genes (KIF2C, R = 0.84; KIFC1, R = 0.81; TPX2, R = 0.81) of the top 100 genes (P < 0.01). We also illustrated that NCAPH was positively related to the six genes (BUB1, CCNB, CDCA, KIF2C, KIFC1 and TPX2) in most types of cancer (Figure 4C). Further searching through the Venn diagram database revealed that a total of 29 genes overlapped with each other in the two groups, they are closely related to proliferation function and cell cycle regulation function (Figure 4D).
We then performed KEGG and GO enrichment analysis by combining these two datasets, which contain a total of NCAPH-related genes. The KEGG analysis revealed that these genes were primarily concentrated in ways related to DNA replication and cell cycle signaling pathway (Figure 4E). Interestingly, it was also related to the PD-L1 checkpoint pathway and the inflammatory pathway NF-kB, suggesting that there was a certain relationship between NCAPH and the immune process. GO analysis revealed that the major BP contained cell division and DNA repair (Figure 4F). From the distribution of CC, most of the CC terms were associated with the nucleoplasm (Figure 4G). For the analysis of MF (Figure 4H), it was revealed that NCAPH was mainly related to protein binding. Consistent with our previous gene association findings, these results further suggested that NCAPH may be involved in molecular mechanisms regulating cell cycle and immune escape.
With the previous results (Figure 1), the mRNA and total protein of NCAPH were overexpressed in BRCA, COAD and other cancers. The TIMER database was further selected to investigate the potential association between the expression level of NCAPH and the level of tumor-infiltrating immune cells (TIICs) in diverse cancer types. The present database showed that NCAPH expression in THCA and KIRC was positively correlated with B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils and DCs (P < 0.05). In contrast, NCAPH expression was significantly negatively correlated with macrophages (r = −0.014, P = 6.68e−01) in BRCA, CD8+T cells (r = −0.129, P = 4.56e−03) in OV, CD4+T cells (r = −0.143, P = 6.32e−02) in PAAD, and neutrophils (r = −0.122, P = 1.96e−01) in THYM (Figure 5A). Figure 5B exhibited the correlation of NCAPH with the level of immune cell infiltration in other types of cancer based on sangerbox. As shown in supplementary Figures S1 and S2, which demonstrates the correlation between NCAPH and the level of immune infiltration in a variety of cancers. Next, the potential relationship between NCAPH expression and immune cell infiltration in different TCGA tumors was considered. The results displayed that NCAPH expression and CD8+T cell infiltration showed a positive correlation in KIRP, LUAD, BRCA and THYM, while negatively correlated in HNSC (HPV-) and UCEC cancers. Consistently, we observed a positive relationship between NCAPH expression and myeloid dendritic infiltration in BRCA and THYM (Figure 6A, B, P < 0.05).
Correspondingly, there was also a clear correlation between NCAPH expression levels and immune marker genes in BRCA (Figure 6C). The results suggested that in BRCA, there was a positive association with NCAPH expression in M2 (ARG1, MRC1, both P < 0.05), TAM (CD80, CD86, both P < 0.05) and B cell (CD38, P < 0.05). In particular, the expression of NCAPH was most significantly correlated with CD80 (P = 5.67e-39, R = 0.379). Moreover, Figure S3 also showed the correlation between NCAPH and immune infiltration markers in other tumors. Therefore, NCAPH may play an immunosuppressive role in tumors through CD80 and assist tumor immune escape.
To identify the mechanism by which NCAPH impacts survival, we used cBioPortal to explore alteration frequencies, including mutation, structural variant, amplification, deep deletion, and multiple alterations, of NCAPH in different cancer types (Figure 7A). Results showed that the top five cancer types with more total mutations were UCEC (5.1%), SKCM (3.38%), STAD (3.18%), KICH (3.08%), and LUAD (2.12%). For specific alteration types, amplifications of NCAPH were enriched in UCS (3.5%), BLCA (1.7%), LUSC (1.64%), HNSC (0.96%), and LUAD (0.88%). We also found one NCAPH-deep deletion was enriched in DLBC (2.08%). At the same time, missense mutation was the commonest mutational style of NCAPH gene in TCGA tumors, and D469lfs/Rfs alteration in the Cnd2 bind domain was discovered in COAD, UCEC and STAD (Figure 7B). Based on these results, we further studied the correlation of NCAPH alteration with prognosis in the top five cancer types and found the prognostic value of NCAPH alteration. The results are summarized in Figure 7C. Altered NCAPH is significantly associated with a good prognosis in HNSC (OS (p = 0.0408), PFS (p = 0.0137), DSS (p = 0.0499)) and BLCA (DSS (p = 0.0229)). In addition, NCAPH has different protein phosphorylation sites in HNSC, and its expression in tumors was also different (P < 0.001). Higher NCAPH phosphorylation level was attended in HNSC (S59, S67, S76, S190, S222 and T38, P < 0.05). Conversely, NCAPH phosphorylated S16 was downregulated in tumor tissues, with no significant difference in phosphorylated S14 (Figure 7D).
It has been reported that NCAPH is a mitosis-associated protein that plays an important role in tumorigenesis and tumor prognosis assessment [28]. However, it was unclear whether NCAPH has a common pathway in different tumor pathogenesis. We also failed to retrieve any literature or report about NCAPH in pan-cancer. Thus, the objective was to evaluate the prognostic value and the latent biological functions of NCAPH in different types of cancer.
Our analysis demonstrated that NCAPH was highly expressed in most cancers compared with normal controls and positively correlated with the clinical stage. Interestingly, NCAPH overexpression in clinical stage Ⅳ was lower in LUSC and LIHC, which may be related to factors such as cancer type and the number of patients in the database, which further leads to the heterogeneity of NCAPH function. Likewise, the aberrant NCAPH expression usually indicates an adverse prognosis for many kinds of cancer, which may serve as a prognostic biomarker in cancer patients. Lu et al. found that NCAPH protein was highly expressed in breast cancer, and its overexpression predicts poor prognosis in patients [29]. Cui et al. demonstrated that the OS was lower in prostate cancer patients with high NCAPH expression [30]. This finding was in line with our previous analysis. Whereas, we still need to fully consider other clinical features and provide more direct evidence to confirm whether the over- expression of NCAPH was involved in the regulation of tumor malignant evolution, or was merely an outcome of anti-tumor changes in normal tissue. Together, these results strongly indicated that NCAPH may have value as a prognostic indicator for cancer.
Genetic mutations acted as a significant player in the development and growth of cancer, and they can also be targets for effective treatments [31,32]. It has been reported that the NCAPH gene with a high mutation rate in cancer, and it has an aggressive phenotype [33]. Meanwhile, our research identified that missense mutation was the most frequent mutational style of NCAPH gene in TCGA tumors. Noteworthy, NCAPH gene mutations were significantly enriched in STAD, the overexpression of NCAPH in gastric cancer predicts a longer survival of patients. Therefore, we conjecture that the mutation of NCAPH at the gene locus may be closely related to the longer survival of patients. Studies had reported that phosphorylated NCAPH in multiple tumors was well correlated with tumorigenesis [34,35,36]. The phosphorylation of NCAPH at ser988 had been found to promote the occurrence of BRCA1 [37]. Herein, our results noted that NCAPH phosphorylation (S59, S67, S76, S90, S222 and S38) is higher in HNSCs, but S16 is lower in HNSCs. Whether these post-translational modification sites have clinical significance remains unclear, and further clarification was required by subsequent molecular biology experiments.
Recently, multiple related reports have obtained that protein gene mutations and protein phosphorylation modifications also affect the level of tumor immune infiltration in different cancer types [38,39,40]. Our study elucidated the correlation between NCAPH expression and immune cell infiltration levels in various tumors, especially CD8+T cells, DCs and neutrophils. Consistent with our research, Yin et al. proposed that NCAPH overexpression is associated with poor prognosis and immune infiltration in COAD [41]. Moreover, macrophages as the first line of immune defense play an important role in every stage of tumor development and are the core regulators in the TME [42]. Interestingly, NCAPH was mainly positively correlated with M2 macrophage markers, such as CD80. Meanwhile, in our study, NCAPH expression was significantly enriched in PD-L1/NF-kB pathway, DNA replication and DNA repair pathways. The discovery that the NCAPH has plays an important role in cancer immunology and facilitates future studies with larger patient populations that could determine the feasibility of clinically integrated therapy.
In summary, NCAPH is correlated with the poor prognosis of patients, protein phosphorylation, immune cell infiltration, and immunity markers in multiple cancers. NCAPH may serve as a pan-cancer prognostic biomarker and play a key role in cancer as a new immunotherapeutic target. However, there is still a shortcoming in the molecular mechanism of NCAPH regulating tumors, and the specific cell function experiments need to be further explored. It is worth noting that although we have found NCAPH in multiple online datasets as a potential cancer biomarker and associated with poor prognosis for multiple cancer patients. But so far there is no report on the expression of NCAPH in BLCA, UCEC, GBM, CHOL, etc. This requires us to carry out more studies to improve the significance of the differential expression of NCAPH in different types of cancer in prognostic evaluation.
This research was supported by the Project from the Department of Health of Jilin Province (2020J002). The National Natural Science Foundation of China (No. 82160552).
The authors declare that there is no conflict of interest.
[1] |
T. G. Phan, P. I. Croucher, The dormant cancer cell life cycle, Nat. Rev. Cancer, 20 (2020), 398–411. https://doi.org/10.1038/s41568-020-0263-0 doi: 10.1038/s41568-020-0263-0
![]() |
[2] |
Y. Nie, X. Wang, F. Yang, Z. Zhou, J. Wang, K. Chen, Surgical prognosis of synchronous multiple primary lung cancer: Systematic review and meta-analysis, Clin. Lung Cancer, 22 (2021), 341–350.e3. https://doi.org/10.1016/j.cllc.2020.10.022 doi: 10.1016/j.cllc.2020.10.022
![]() |
[3] |
T. J. Willenbrink, E. S. Ruiz, C. M. Cornejo, C. D. Schmults, S. T. Arron, A. Jambusaria-Pahlajani, Field cancerization: Definition, epidemiology, risk factors, and outcomes, J. Am. Acad. Dermatol., 83 (2020), 709–717. https://doi.org/10.1016/j.jaad.2020.03.126 doi: 10.1016/j.jaad.2020.03.126
![]() |
[4] |
X. Qiu, Z. Gao, J. Shao, H. Li, NCAPH is upregulated in endometrial cancer and associated with poor clinicopathologic characteristics, Ann. Hum. Genet., 84 (2020), 437–446. https://doi.org/10.1111/ahg.12398 doi: 10.1111/ahg.12398
![]() |
[5] |
Y. Sun, X. Wang, H. Wen, B. Zhu, L. Yu, Expression and clinical significance of the NCAPH, AGGF1, and FOXC2 proteins in serous ovarian cancer, Cancer Manag. Res., 13 (2021), 7253–7262. https://doi.org/10.2147/CMAR.S329688 doi: 10.2147/CMAR.S329688
![]() |
[6] |
Q. Xiong, S. Fan, L. Duan, B. Liu, X. Jiang, X. Chen, et al., NCAPH is negatively associated with Mcl-1 in non-small cell lung cancer, Mol. Med. Rep., 22 (2020), 2916–2924. https://doi.org/10.3892/mmr.2020.11359 doi: 10.3892/mmr.2020.11359
![]() |
[7] |
B. Kim, S. W. Kim, J. Y. Lim, S. J. Park, NCAPH is required for proliferation, migration and invasion of non-small-cell lung cancer cells, Anticancer Res., 40 (2020), 3239–3246. https://doi.org/10.21873/anticanres.14305 doi: 10.21873/anticanres.14305
![]() |
[8] |
M. Wang, X. Qiao, T. Cooper, W. Pan, L. Liu, J. Hayball, et al., HPV E7-mediated NCAPH ectopic expression regulates the carcinogenesis of cervical carcinoma via PI3K/AKT/SGK pathway, Cell Death Dis., 11 (2020), 1049. https://doi.org/10.1038/s41419-020-03244-9 doi: 10.1038/s41419-020-03244-9
![]() |
[9] |
B. Li, Q. Xiao, L. Shan, Y. Song, NCAPH promotes cell proliferation and inhibits cell apoptosis of bladder cancer cells through MEK/ERK signaling pathway, Cell Cycle, 21 (2022), 427–438. https://doi.org/10.1080/15384101.2021.2021050 doi: 10.1080/15384101.2021.2021050
![]() |
[10] |
W. Zhou, J. Hu, J. Zhao, Non-SMC condensin I complex subunit H (NCAPH), a regulator of cell cycle, predicts poor prognosis in lung adenocarcinoma patients: a study mainly based on TCGA and GEO database, Transl. Cancer Res., 9 (2020), 7572–7587. https://doi.org/10.21037/tcr-20-2217 doi: 10.21037/tcr-20-2217
![]() |
[11] |
C. Sun, S. Huang, H. Wang, R. Xie, L. Zhang, Q. Zhou, et al., Non-SMC condensin I complex subunit H enhances proliferation, migration, and invasion of hepatocellular carcinoma, Mol. Carcinog., 58 (2019), 2266–2275. https://doi.org/10.1002/mc.23114 doi: 10.1002/mc.23114
![]() |
[12] |
Y. Wang, J. Q. Li, Z. L. Yang, L. Wang, J. C. Zhang, Y. F. Sun, et al., NCAPH regulates gastric cancer progression through DNA damage response, Neoplasma, 69 (2021), 283–291. https://doi.org/10.4149/neo_2021_210607N761 doi: 10.4149/neo_2021_210607N761
![]() |
[13] |
A. Rojas, P. Araya, I. Gonzalez, E. Morales, Gastric tumor microenvironment, Adv. Exp. Med. Biol., 1226 (2020), 23–35. https://doi.org/10.1007/978-3-030-36214-0_2 doi: 10.1007/978-3-030-36214-0_2
![]() |
[14] |
R. J. DeBerardinis, Tumor microenvironment, metabolism, and immunotherapy, N. Engl. J. Med., 382 (2020), 869–871. https://doi.org/10.1056/NEJMcibr1914890 doi: 10.1056/NEJMcibr1914890
![]() |
[15] |
Y. Ding, Y. Yan, Y. Dong, J. Xu, W. Su, W. Shi, et al., NLRP3 promotes immune escape by regulating immune checkpoints: A pan-cancer analysis, Int. Immunopharmacol., 104 (2022), 108512. https://doi.org/10.1016/j.intimp.2021.108512 doi: 10.1016/j.intimp.2021.108512
![]() |
[16] |
X. Nie, M. Zheng, L. Gao, Y. Hu, Y. Zhuang, X. Li, et al., Interaction between TMEFF1 and AHNAK proteins in ovarian cancer cells: Implications for clinical prognosis, Int. Immunopharmacol., 107 (2022), 108726. https://doi.org/10.1016/j.intimp.2022.108726 doi: 10.1016/j.intimp.2022.108726
![]() |
[17] |
X. F. Wang, W. Lei, C. M. Liu, J. Yang, Y. H. Zhu, BOLA3 is a prognostic-related biomarker and correlated with immune infiltrates in lung adenocarcinoma, Int. Immunopharmacol., 107 (2022), 108652. https://doi.org/10.1016/j.intimp.2022.108652 doi: 10.1016/j.intimp.2022.108652
![]() |
[18] |
P. Brlek, A. Kafka, A. Bukovac, N. Pećina-Šlaus, Integrative cBioPortal analysis revealed molecular mechanisms that regulate EGFR-PI3K-AKT-mTOR pathway in diffuse gliomas of the brain, Cancers (Basel), 13 (2021), 3247. https://doi.org/10.3390/cancers13133247 doi: 10.3390/cancers13133247
![]() |
[19] |
J. Watson, J. M. Schwartz, C. Francavilla, Using multilayer heterogeneous networks to infer functions of phosphorylated sites, J. Proteome Res., 20 (2021), 3532–3548. https://doi.org/10.1021/acs.jproteome.1c00150 doi: 10.1021/acs.jproteome.1c00150
![]() |
[20] |
X. Zhou, J. Du, C. Liu, H. Zeng, Y. Chen, L. Liu, et al., A pan-cancer analysis of CD161, a potential new immune checkpoint, Front. Immunol., 12 (2021), 688215. https://doi.org/10.3389/fimmu.2021.688215 doi: 10.3389/fimmu.2021.688215
![]() |
[21] |
M. He, Y. Han, C. Cai, P. Liu, Y. Chen, H. Shen, et al., CLEC10A is a prognostic biomarker and correlated with clinical pathologic features and immune infiltrates in lung adenocarcinoma, J. Cell. Mol. Med., 25 (2021), 3391–3399. https://doi.org/10.1111/jcmm.16416 doi: 10.1111/jcmm.16416
![]() |
[22] |
D. Szklarczyk, A. L. Gable, K. C. Nastou, D. Lyon, R. Kirsch, S. Pyysalo, et al., The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets, Nucleic Acids Res., 49 (2021), D605–D612. https://doi.org/10.1093/nar/gkaa1074 doi: 10.1093/nar/gkaa1074
![]() |
[23] |
A. Jia, L. Xu, Y. Wang, Venn diagrams in bioinformatics, Brief. Bioinf., 22 (2021), bbab108. https://doi.org/10.1093/bib/bbab108 doi: 10.1093/bib/bbab108
![]() |
[24] |
W. Liang, F. Sun, Y. Zhao, L. Shan, H. Lou, Identification of susceptibility modules and genes for cardiovascular disease in diabetic patients using WGCNA analysis, J. Diabetes Res., 2020 (2020), 4178639. https://doi.org/10.1155/2020/4178639 doi: 10.1155/2020/4178639
![]() |
[25] |
C. van Mourik, R. Ehsani, F. Drabløs, GAPGOM—an R package for gene annotation prediction using GO Metrics, BMC Res. Notes, 14 (2021), 162. https://doi.org/10.1186/s13104-021-05580-1 doi: 10.1186/s13104-021-05580-1
![]() |
[26] |
C. Chen, J. Hou, J. J. Tanner, J. Cheng, Bioinformatics methods for mass spectrometry-based proteomics data analysis, Int. J. Mol. Sci., 21 (2020), 2873. https://doi.org/10.3390/ijms21082873 doi: 10.3390/ijms21082873
![]() |
[27] |
A. A. Tavakoli, Einstieg ins programmieren für radiologen mit der software R, Die Radiol., 61 (2021), 296–299. https://doi.org/10.1007/s00117-021-00813-7 doi: 10.1007/s00117-021-00813-7
![]() |
[28] |
Y. Qi, K. Mo, T. Zhang, A transcription factor that promotes proliferation, migration, invasion, and epithelial-mesenchymal transition of ovarian cancer cells and its possible mechanisms, Biomed. Eng. Online, 20 (2021), 83. https://doi.org/10.1186/s12938-021-00919-y doi: 10.1186/s12938-021-00919-y
![]() |
[29] |
H. Lu, C. Shi, S. Wang, C. Yang, X. Wan, Y. Luo, et al., Identification of NCAPH as a biomarker for prognosis of breast cancer, Mol. Biol. Rep., 47 (2020), 7831–7842. https://doi.org/10.1007/s11033-020-05859-9 doi: 10.1007/s11033-020-05859-9
![]() |
[30] |
F. Cui, J. Hu, Z. Xu, J. Tan, H. Tang, Overexpression of NCAPH is upregulated and predicts a poor prognosis in prostate cancer, Oncol. Lett., 17 (2019), 5768–5776. https://doi.org/10.3892/ol.2019.10260 doi: 10.3892/ol.2019.10260
![]() |
[31] |
W. Na, H. Moon, D. Song, A comprehensive review of SARS-CoV-2 genetic mutations and lessons from animal coronavirus recombination in one health perspective, J. Microbiol., 59 (2021), 332–340. https://doi.org/10.1007/s12275-021-0660-4 doi: 10.1007/s12275-021-0660-4
![]() |
[32] |
L. J. Jilderda, L. Zhou, F. Foijer, Understanding how genetic mutations collaborate with genomic instability in cancer, Cells, 10 (2021), 342. https://doi.org/10.3390/cells10020342 doi: 10.3390/cells10020342
![]() |
[33] |
C. A. Martin, J. E. Murray, P. Carroll, A. Leitch, K. J. Mackenzie, M. Halachev, Mutations in genes encoding condensin complex proteins cause microcephaly through decatenation failure at mitosis, Genes Dev., 30 (2016), 2158–2172. https://doi.org/10.1101/gad.286351.116 doi: 10.1101/gad.286351.116
![]() |
[34] |
K. Shimizu, H. Shirataki, T. Honda, S. Minami, Y. Takai, Complex formation of SMAP/KAP3, a KIF3A/B ATPase motor-associated protein, with a human chromosome-associated polypeptide, J. Biol. Chem., 273 (1998), 6591–6594. https://doi.org/10.1074/jbc.273.12.6591 doi: 10.1074/jbc.273.12.6591
![]() |
[35] |
J. A. Schmiesing, H. C. Gregson, S. Zhou, K. Yokomori, A human condensin complex containing hCAP-C-hCAP-E and CNAP1, a homolog of Xenopus XCAP-D2, colocalizes with phosphorylated histone H3 during the early stage of mitotic chromosome condensation, Mol. Cell. Biol., 20 (2000), 6996–7006. https://doi.org/10.1128/MCB.20.18.6996-7006.2000 doi: 10.1128/MCB.20.18.6996-7006.2000
![]() |
[36] |
O. A. Cabello, E. Eliseeva, W. G. He, H. Youssoufian, S. E. Plon, B. R. Brinkley, et al., Cell cycle-dependent expression and nucleolar localization of hCAP-H, Mol. Biol. Cell., 12 (2001), 3527–3537. https://doi.org/10.1091/mbc.12.11.3527 doi: 10.1091/mbc.12.11.3527
![]() |
[37] |
S. H. Chen, W. T. Huang, W. C. Kao, S. Y. Hsiao, H. Y. Pan, C. W. Fang, et al., O6-methylguanine-DNA methyltransferase modulates cisplatin-induced DNA double-strand breaks by targeting the homologous recombination pathway in nasopharyngeal carcinoma, J. Biomed. Sci., 28 (2021), 2. https://doi.org/10.1186/s12929-020-00699-y doi: 10.1186/s12929-020-00699-y
![]() |
[38] |
X. Huang, Q. Zhang, Y. Lou, J. Wang, X. Zhao, L. Wang, et al., USP22 deubiquitinates CD274 to suppress anticancer immunity, Cancer Immunol. Res., 7 (2019), 1580–1590. https://doi.org/10.1158/2326-6066.CIR-18-0910 doi: 10.1158/2326-6066.CIR-18-0910
![]() |
[39] |
Q. Liu, T. Gu, L. Y. Su, L. Jiao, X. Qiao, M. Xu, et al., GSNOR facilitates antiviral innate immunity by restricting TBK1 cysteine S-nitrosation, Redox Biol., 47 (2021), 102172. https://doi.org/10.1016/j.redox.2021.102172 doi: 10.1016/j.redox.2021.102172
![]() |
[40] |
M. Z. Jin, Y. G. Zhang, W. L. Jin, X. P. Wang, A pan-cancer analysis of the oncogenic and immunogenic role of m6Am methyltransferase PCIF1, Front. Oncol., 11 (2021), 753393. https://doi.org/10.3389/fonc.2021.753393 doi: 10.3389/fonc.2021.753393
![]() |
[41] |
L. Yin, L. P. Jiang, Q. S. Shen, Q. X. Xiong, X. Zhuo, L. L. Zhang, et al., NCAPH plays important roles in human colon cancer, Cell Death Dis., 8 (2017), e2680. https://doi.org/10.1038/cddis.2017.88 doi: 10.1038/cddis.2017.88
![]() |
[42] |
M. Casanova-Acebes, E. Dalla, A. M. Leader, J. LeBerichel, J. Nikolic, B. M. Morales, et al., Tissue-resident macrophages provide a pro-tumorigenic niche to early NSCLC cells, Nature, 595 (2021), 578–584. https://doi.org/10.1038/s41586-021-03651-8 doi: 10.1038/s41586-021-03651-8
![]() |
![]() |
![]() |
1. | Ying Liu, Aihua Jin, Xianglan Quan, Xionghu Shen, Houkun Zhou, Xingyu Zhao, Zhenhua Lin, miR-590-5p/Tiam1-mediated glucose metabolism promotes malignant evolution of pancreatic cancer by regulating SLC2A3 stability, 2023, 23, 1475-2867, 10.1186/s12935-023-03159-3 | |
2. | Mahshid Arastonejad, Daniyal Arab, Somayeh Fatemi, Pezhman Golshanrad, Unveiling the Significance of NCAP Family Genes in Adrenocortical Carcinoma and Adenoma Pathogenesis: A Molecular Bioinformatics Exploration, 2024, 23, 1176-9351, 10.1177/11769351241262211 | |
3. | Caiyan Liu, Xiao Han, Siqi Zhang, Manru Huang, Bin Guo, Zixuan Zhao, Shenshen Yang, Jun Jin, Weiling Pu, Haiyang Yu, The role of NCAPH in cancer treatment, 2024, 121, 08986568, 111262, 10.1016/j.cellsig.2024.111262 | |
4. | Luyu Liu, Pan Yin, Ruida Yang, Guanfei Zhang, Cong Wu, Yan Zheng, Shaobo Wu, Meng Liu, Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma, 2024, 15, 1664-3224, 10.3389/fimmu.2024.1351908 | |
5. | Yali Zhao, Yan He, Zhiyuan Xiao, Le Xin, Mingjing Deng, Mingxia Yao, Guan Huang, circEIF3I Promotes Colorectal Cancer Metastasis by Regulating the miR‐328‐3p/NCAPH Axis, 2024, 0899-1987, 10.1002/mc.23860 |