Expression Profile and Prognostic Values of SMC Family Members in HCC

Wei Yan,Dan-Dan Wang,He-Da Zhang,Jinny Huang,Jun-Chen Hou,Su-Jin Yang,Jian Zhang,Ling Lu,Qian Zhang

Medicine（2022）SCI 4区

Nanjing Med Univ | Johns Hopkins Univ | Chinese Acad Med Sci

Cited 8|Views25

Abstract

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.

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Key words

bioinformatics,HCC,SMC family,therapy

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
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Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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