The Prognostic Value of the Expression of SMC4 mRNA in Breast Cancer

Identification of SMC2 and SMC4 as prognostic markers in breast cancer through bioinformatics analysis

BACKGROUND

Breast cancer (BRCA) is one of the most common malignant tumors. The structural maintenance of chromosome (SMC) gene family has been shown to play an important role in human cancers. However, the role of SMC families in BRCA is unclear. This study aimed to explore the role and potential clinical value of whole SMCs in BRCA.

METHODS

TIMER and UALCAN database were used to analysis the expression level. Genetic variations were analyzed by cBioPortal. Promoter methylation and protein level were analyzed by UCLCAN. GO and KEGG were analyzed by Metascape database. Prognostic value of SMCs was analyzed by Kaplan-Meier and multivariate cox regression analyses. Immune infiltration analysis was conducted by CIBERSORT. Immunotherapy outcome prediction was conducted by Cancer Immunome Atlas. Targeted drug therapy outcome prediction was taken by GDSC and R language. The cell viability was tested by CCK8 and migration was tested by wound healing assay. Xenograft model was used to investigate the in vivo role of SMC2.

RESULTS

Expression levels of SMC1A, SMC2, SMC4, SMC5 and SMC6 mRNA were increased in BRCA tissues, and negatively correlated with promoter methylation. Overexpression of SMC2 and SMC4 was negatively correlated with survival. Function of SMCs family regulatory genes was mainly related to ATPase activity. Expression of most SMCs was negatively correlated with immunotherapy and drug therapy outcomes. Interfere SMC2 and SMC4 decreased IC50 values of 5-fluorouracil and oxaliplatin and inhibited the migration of MCF7 cells. Tumor growth and weights were significantly decreased in si-SMC2 groups.

CONCLUSIONS

Combined bioinformatics and clinical specimen analysis verified SMC2 and SMC4 as independent prognostic factors in BRCA, suggesting their significance for the diagnosis and treatment of BRCA.

SMC4 serves as a potential marker for the diagnosis and prognosis of colon adenocarcinoma

OBJECTIVE

We aimed to explore the role of structural maintenance of chromosomes 4 (SMC4) in malignant progression and immunology of colon adenocarcinoma (COAD).

METHODS

The expression, genetic and protein features, and immune cell infiltration of SMC4 in pan-cancer were provided by public databases and websites. The protein expression of SMC4 in COAD tissues was screened by immunohistochemical assay. Si-RNA-mediated transfection was performed in COAD cells and the proliferation viability was measured using MTT, colony formation and EdU assays. Cell autophagy was detected by AO staining, western blots, and immunofluorescence staining. The migratory ability was determined using scratch and transwell assays. The expression of epithelial-to-mesenchymal transition (EMT) markers and transcriptional factors were detected using western blots.

RESULTS

The expression of SMC4 was upregulated in pan-cancer and had relationships with prognosis, TMB, and MSI of cancer patients. Particularly, SMC4 protein was highly expressed in COAD tissues and correlated with poor prognosis of patients. Depletion of SMC4 inhibited cell proliferation, induced autophagy, and decreased migration through EMT progression in COAD cells. In addition, SMC4 was associated with infiltration of neutrophils, M2 macrophages, and CD4 + T cells in COAD, and had positive association with M2 macrophage markers and immune checkpoints.

CONCLUSION

SMC4 was correlated with patients' poor prognosis, proliferation, metastasis, and immune cell infiltrates, and might function as a potential diagnosis and prognostic biomarker in COAD.

Structural Maintenance of Chromosome Protein 4 Promotes the Progression of Cardia Adenocarcinoma via Regulation of the Wnt/β-catenin Signaling Pathway

BACKGROUND

Structural maintenance of chromosome protein 4 (SMC4) is crucial for chromosome assembly and separation, but its role and mechanism in cardia adenocarcinoma (CA) are unknown.

METHODS

SMC4 expression levels were initially detected by protein profiling in 20 pairs of CA tumor tissues and adjacent normal tissues. The level of SMC4 expression in CA cells was then evaluated using a western blot analysis. Cell proliferation was evaluated by CCK-8 and clone formation tests. Scratch and transwell tests were used to investigate cell migration as well as invasion, while through the flow cytometry, we examined the cell apoptosis and progression of the cell cycle. The regulatory effects of the epithelial-mesenchymal transition (EMT) and the Wnt/β- catenin pathway were investigated using western blot. A tumorigenesis experiment was used to investigate the influence of SMC4 on tumor development in nude mice.

RESULTS

This study showed overexpression of SMC4 in CA tissues and cells. Knockdown of SMC4 can significantly inhibit the proliferation, migration and invasion, stimulate cell apoptosis, induce cell cycle arrest in the G0/G1 phase of CA cells, and inhibit tumor growth in vivo. In addition, down-regulation of SMC4 resulted in decreased expression of Bcl-2, Cyclin D1, CDK4, CDK6, β-catenin, phosphorylated GSK-3β, N-cadherin, and Vimentin, with an increased level of proteins, i.e., Bax, cleaved-caspase3, and E-cadherin. When SMC4 was overexpressed, these effects were reversed.

CONCLUSION

SMC4 can facilitate the biological progression of CA, suggesting that SMC4 could be a potential therapeutic target for the disease.

Association of SMC4 with prognosis and immune infiltration of sarcoma

OBJECTIVE

This study was performed to explore the prognostic relevance of structural maintenance of chromosomes 4 (SMC4) in pan-cancer and explore the association between SMC4 and immune infiltration of sarcoma.

RESULTS

Elevated expression of SMC4 was detected in cancer tissues compared to normal tissue, which was confirmed in synovial sarcoma tissues with immunohistochemistry (IHC). Additionally, higher expression of SMC4 was connected to worse outcomes of sarcoma, gastric cancer, breast cancer, liver cancer or ovarian cancer. Moreover, SMC4 was positively connected to immune cell infiltrates in sarcoma. In addition, infiltrating immune cell markers including monocyte, TAM, M1 and M2 presented different SMC4-associated immune infiltration patterns.

CONCLUSION

The results from our study showed that SMC4 was positively related to the prognosis and immunological status of sarcoma. SMC4 could be a potential biomarker for prognosis and immune cell infiltrates in sarcoma.

METHODS

Several databases including ONCOMINE, GEPIA, and Kaplan-Meier Plotter were adopted to explore the expression pattern of SMC4 in sarcoma, which was confirmed by IHC. The GEPIA and TIMER datasets were adopted to investigate the associations between SMC4 and prognosis in various cancers, especially in sarcoma.

Correlation between DNA Methylation and Cell Proliferation Identifies New Candidate Predictive Markers in Meningioma

Meningiomas are the most common primary tumors of the central nervous system. Based on the 2021 WHO classification, they are classified into three grades reflecting recurrence risk and aggressiveness. However, the WHO's histopathological criteria defining these grades are somewhat subjective. Together with reliable immunohistochemical proliferation indices, other molecular markers such as those studied with genome-wide epigenetics promise to revamp the current prognostic classification. In this study, 48 meningiomas of various grades were randomly included and explored for DNA methylation with the Infinium MethylationEPIC microarray over 850k CpG sites. We conducted differential and correlative analyses on grade and several proliferation indices and markers, such as mitotic index and Ki-67 or MCM6 immunohistochemistry. We also set up Cox proportional hazard models for extensive associations between CpG methylation and survival. We identified loci highly correlated with cell growth and a targeted methylation signature of regulatory regions persistently associated with proliferation, grade, and survival. Candidate genes under the control of these regions include SMC4, ESRRG, PAX6, DOK7, VAV2, OTX1, and PCDHA-PCDHB-PCDHG, i.e., the protocadherin gene clusters. This study highlights the crucial role played by epigenetic mechanisms in shaping dysregulated cellular proliferation and provides potential biomarkers bearing prognostic and therapeutic value for the clinical management of meningioma.

Development and validation of a prognostic model and gene co-expression networks for breast carcinoma based on scRNA-seq and bulk-seq data

Background

Breast carcinoma is the most common malignancy among women worldwide. It is characterized by a complex tumor microenvironment (TME), in which there is an intricate combination of different types of cells, which can cause confusion when screening tumor-cell-related signatures or constructing a gene co-expression network. The recent emergence of single-cell RNA sequencing (scRNA-seq) is an effective method for studying the changing omics of cells in complex TMEs.

Methods

The Dysregulated genes of malignant epithelial cells was screened by performing a comprehensive analysis of the public scRNA-seq data of 58 samples. Co-expression and Gene Set Enrichment Analysis (GSEA) analysis were performed based on scRNA-seq data of malignant cells to illustrate the potential function of these dysregulated genes. Iterative LASSO-Cox was used to perform a second-round screening among these dysregulated genes for constructing risk group. Finally, a breast cancer prognosis prediction model was constructed based on risk grouping and other clinical characteristics.

Results

Our results indicated a transcriptional signature of 1,262 genes for malignant breast cancer epithelial cells. To estimate the function of these genes in breast cancer, we also constructed a co-expression network of these dysregulated genes at single-cell resolution, and further validated the results using more than 300 published transcriptomics datasets and 31 Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) screening datasets. Moreover, we developed a reliable predictive model based on the scRNA-seq and bulk-seq datasets.

Conclusions

Our findings provide insights into the transcriptomics and gene co-expression networks during breast carcinoma progression and suggest potential candidate biomarkers and therapeutic targets for the treatment of breast carcinoma. Our results are available via a web app (https://prognosticpredictor.shinyapps.io/GCNBC/).

Expression profile and prognostic values of SMC family members in HCC

OBJECTIVE

The structural maintenance of chromosome (SMC) gene family, including 6 proteins, is involved in a wide range of biological functions in different human cancers. Nevertheless, there is little research on the expression patterns, potential functions and prognostic value of SMC genes in hepatocellular carcinoma (HCC). Based on publicly available databases and integrative bioinformatics analysis, we tried to determine the value of SMC gene expression in predicting the risk of developing HCC.

METHODS

The expression and copy number variations data of SMC family members were obtained from TCGA (The Cancer Genome Atlas). We identified the prognostic values of SMC family members and their clinical features. GSEA (Gene Set Enrichment Analysis) was conducted to detect the mechanism underlying the involvement of SMC family members in liver cancer. We used Tumor Immune Estimation Resource database to explore the associations between TIICs (Tumor Immune Infiltrating Cells) and the SMC family members.

RESULTS

Our analysis proved that downregulation of SMC family members was common modification in HCC patients. In HCC, the expression of SMC1A, SMC2, SMC3, SMC4, SMC6 were upregulated. Upregulation of SMC2, SMC3, and SMC4, along with the clinical stage of HCC, were associated with a poor prognosis according to the results of univariate and multivariate Cox proportional hazards regression analysis. SMC2, SMC3, and SMC4 are also related to tumor purity and immune infiltration levels of HCC. The GSEA results proved that SMC family members take part in numerous biological processes underlying tumorigenesis.

CONCLUSION

In this study, we comprehensively analyzed the expression of SMC family members in patients with HCC. This can provide insights for further investigation of the SMC members as potential therapeutic targets in HCC and suggest that the use of SMC inhibitor targeting SMC2, SMC3, and SMC4 can be a practical strategy for the therapy of HCC.

Kidney Cancer Biomarker Selection Using Regularized Survival Models

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC showing a significant percentage of mortality. One of the priorities of kidney cancer research is to identify RCC-specific biomarkers for early detection and screening of the disease. With the development of high-throughput technology, it is now possible to measure the expression levels of thousands of genes in parallel and assess the molecular profile of individual tumors. Studying the relationship between gene expression and survival outcome has been widely used to find genes associated with cancer survival, providing new information for clinical decision-making. One of the challenges of using transcriptomics data is their high dimensionality which can lead to instability in the selection of gene signatures. Here we identify potential prognostic biomarkers correlated to the survival outcome of ccRCC patients using two network-based regularizers (EN and TCox) applied to Cox models. Some genes always selected by each method were found (COPS7B, DONSON, GTF2E2, HAUS8, PRH2, and ZNF18) with known roles in cancer formation and progression. Afterward, different lists of genes ranked based on distinct metrics (logFC of DEGs or β coefficients of regression) were analyzed using GSEA to try to find over- or under-represented mechanisms and pathways. Some ontologies were found in common between the gene sets tested, such as nuclear division, microtubule and tubulin binding, and plasma membrane and chromosome regions. Additionally, genes that were more involved in these ontologies and genes selected by the regularizers were used to create a new gene set where we applied the Cox regression model. With this smaller gene set, we were able to significantly split patients into high/low risk groups showing the importance of studying these genes as potential prognostic factors to help clinicians better identify and monitor patients with ccRCC.

Clinical Significance and Integrative Analysis of the SMC Family in Hepatocellular Carcinoma

Worldwide, hepatocellular carcinoma (HCC) is one of the most malignant cancers with poor prognosis. The structural maintenance of chromosomes (SMC) gene family has been shown to play important roles in human cancers. Nevertheless, the role of SMC members in HCC is not well-understood. In this study, we comprehensively explored the role of the SMC family in HCC using a series of bioinformatic analysis tools. Studies have demonstrated that the mRNA expression levels of SMC1A, SMC1B, SMC2, SMC4, and SMC6 are significantly overexpressed in HCC, and the protein levels of SMC1A, SMC2, SMC3, SMC4, SMC5, and SMC6 are similarly elevated. Moreover, HCC patients with high SMC2 and SMC4 expression levels exhibit poor survival. Using KEGG and GO analyses, we analyzed the enrichment of gene expression in the biological functions and pathways of the SMC family in HCC. Immune infiltration analysis revealed that the expression of the SMC family is closely associated with B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and DCs. In conclusion, our findings will enhance a more thorough understanding of the SMC family in HCC progression and provide new directions for the diagnosis and treatment of HCC in the future.

Development of a Prognostic Five-Gene Signature for Diffuse Lower-Grade Glioma Patients

Background: Diffuse lower-grade gliomas (LGGs) are infiltrative and heterogeneous neoplasms. Gene signature including multiple protein-coding genes (PCGs) is widely used as a tumor marker. This study aimed to construct a multi-PCG signature to predict survival for LGG patients.

Methods: LGG data including PCG expression profiles and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Survival analysis, receiver operating characteristic (ROC) analysis, and random survival forest algorithm (RSFVH) were used to identify the prognostic PCG signature.

Results: From the training (n = 524) and test (n = 431) datasets, a five-PCG signature which can classify LGG patients into low- or high-risk group with a significantly different overall survival (log rank P < 0.001) was screened out and validated. In terms of prognosis predictive performance, the five-PCG signature is stronger than other clinical variables and IDH mutation status. Moreover, the five-PCG signature could further divide radiotherapy patients into two different risk groups. GO and KEGG analysis found that PCGs in the prognostic five-PCG signature were mainly enriched in cell cycle, apoptosis, DNA replication pathways.

Conclusions: The new five-PCG signature is a reliable prognostic marker for LGG patients and has a good prospect in clinical application.

MiR-433-3p restrains the proliferation, migration and invasion of glioma cells via targeting SMC4

OBJECTIVE

Glioma is a common primary malignant brain tumor characterized by high mortality and poor prognosis. The purpose of this study is to explore the molecular mechanism underlying glioma, aiming to provide a new target for the treatment of glioma to improve the prognosis of patients.

METHODS

The differentially expressed genes and regulatory axis affecting the prognosis of glioma were identified with bioinformatics analysis, and the expression of miR-433-3p and SMC4 mRNA was detected with qRT-PCR. The expression of SMC4 and epithelial-mesenchymal transition (EMT)-associated proteins were detected with western blot. The targeting relationship between miR-433-3p and SMC4 was verified with dual-luciferase reporter gene assay. The proliferative ability of glioma cells was detected with CCK-8 assay, while the migration and invasion of glioma cells were detected with Transwell assay.

RESULTS

We found that the expression of SMC4 was significantly up-regulated in glioma, showing that SMC4 was an unfavorable factor for prognosis and could promote the progression of cancer cells. Its upstream regulator miR-433-3p was significantly down-regulated in glioma, which inhibited the development of cancer cells. Moreover, miR-433-3p could target to inhibit the expression of SMC4. Rescue assay showed that miR-433-3p could affect the development of glioma by regulating the expression of SMC4.

CONCLUSION

Our data demonstrate for the first time that SMC4 is a direct target of miR-433-3p, and elucidate the molecular mechanism by which miR-433-3p inhibits the malignant progression of glioma by targeting and down-regulating the expression of SMC4.

Changes of EGFR and SMC4 expressions in triple-negative breast cancer and their early diagnostic value

Background

To explore the diagnostic value of epidermal growth factor receptor (EGFR) and structural maintenance of chromosome protein 4 (SMC4) for triple-negative breast cancer.

Methods

A total of 213 breast cancer patients were selected and divided into triple-negative breast cancer (100 cases) and non-triple-negative breast cancer (113 cases) according to the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Patient information including age, body mass index (BMI), smoking history, drinking history, menopause, tumor classification, lymph node metastasis, distant metastasis, clinical stage, and EGFR and SMC4 expression were collected for all subjects. Logistic regression analysis was then used to evaluate the risk factors for triple-negative breast cancer. The ROC curve was also used to evaluate the clinical value of EGFR and SMC4 in the diagnosis of triple-negative breast cancer.

Results

Logistic regression analysis showed that high expression of SMC4 and high expression of EGFR were both risk factors for triple-negative breast cancer, with an odds ratio (OR) of 1.72 and 1.56, respectively (both P<0.05). ROC curve analysis results showed that the areas under the curve with high SMC4 expression and high EGFR expression for the diagnosis of triple-negative breast cancer were 0.84 and 0.78, respectively.

Conclusions

High expression of SMC4 and EGFR is significantly correlated with triple-negative breast cancer, and can be used as an auxiliary diagnostic indicator for triple-negative breast cancer.

Prognostic relevance of SMC family gene expression in human sarcoma

Objective: To explore the prognostic value of the expression of genes encoding structural maintenance of chromosomes (SMCs) in human sarcoma.

Results: We found that the levels of SMC1A, SMC2, SMC3, SMC4, SMC5 and SMC6 mRNA were all higher in most tumors compared to normal tissues, and especially in sarcoma. According to the Cancer Cell Line Encyclopedia (CCLE), SMC1A, SMC2, SMC3, SMC4, SMC5 and SMC6 are also highly expressed in sarcoma cell lines. Results of Gene Expression Profiling Interactive Analysis (GEPIA) indicated that high expression of SMC1A was significantly related to poor overall survival (OS) (p<0.05) and disease-free survival (DFS) in sarcoma (p<0.05). Additionally, strong expression of SMC2 was significantly related to poor OS in sarcoma (p<0.05). In contrast, SMC3, SMC4, SMC5, and SMC6 expression had no significant impact on OS or DFS in sarcoma.

Conclusions: Expression of SMC family members is significantly different in sarcoma relative to normal tissues, and SMC1A and SMC2 may be useful as prognostic biomarkers.

Methods: We performed a detailed comparison of cancer and normal tissues regarding the expression levels of mRNA for SMC family members in various cancers including sarcoma through ONCOMINE and GEPIA (Gene Expression Profile Interactive Analysis) databases.

DEC2 Serves as Potential Tumor Suppressor in Breast Carcinoma

Background

Identification of new biomarkers can facilitate the development of effective therapeutic strategies in breast cancer (BC). Data from previous studies have revealed that differentiated embryonic chondrocyte gene (DEC) 1 and DEC2 might involve in the progression of various cancer types. We explored the expression profiles and function of DEC1/2 in BC patients in this study.

Methods

The mRNA expression of DEC1/2 in BC patients and cell lines were taken from the Oncomine and Cancer Cell Line Encyclopedia database. The prognostic impacts of DEC1/2 were mined from the bc-GenExMiner and Kaplan-Meier plotter database. The impact of DEC1/2 genomic alterations on patient survival was calculated by cBioPortal. DEC2 protein expressions were confirmed by Western blotting (WB) in 10 pairs of BC samples. In addition, DEC2 sgRNA was constructed to confirm its affection on cell viability, invasion, and colony formation.

Results

The DEC1 and DEC2 mRNA levels are both lower in BC tissues than normal tissues. DEC1/2 expression was high in progesterone receptor (PR) positive BC patients (P = 0.0023), but low in human epidermal growth factor receptor 2 (HER2) positive patients (P < 0.0001). Lower DEC2 mRNA level has significant association with more aggressive pathogenic grade (P < 0.0001) and worse overall survival (OS) of BC patients (P = 5.2 × 10^-6). Subgroup analysis showed that low DEC2 level was correlated with worse OS in estrogen receptor (ER) positive BC (P = 0.008). DEC2 (P = 0.00029) alteration was significantly correlated with worse OS in BC patients. WB results also confirmed the lower DEC2 protein levels in BC samples than their paired normal tissues. And, DEC2 silencing by sgRNA resulted in a significant increasing in cell viability, invasion, and colony formation.

Conclusion

DEC2 might serve as a tumor suppressor, and its disfunction may involve in the tumorigenesis and indicate bad clinical outcomes in BC patients.