Journal of Shandong University (Health Sciences) ›› 2021, Vol. 59 ›› Issue (7): 74-84.doi: 10.6040/j.issn.1671-7554.0.2021.0002

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Construct of a risk assessment model of breast cancer immune-related lncRNAs based on the database information

LI Wanwan1, ZHOU Wenkai1, DONG Shuqing1, HE Shiqing1, LIU Zhao2, ZHANG Jiaxin2, LIU Bin3   

  1. 1.Xuzhou Medical University, Xuzhou 221000, Jiangsu, China;
    2. Department of Thyroid and Breast Surgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China;
    3. Department of Hepatobiliary and Pancreatic Hernia, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu, China
  • Online:2021-07-10 Published:2021-07-16

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Abstract: Objective To screen the immune-related long non-coding RNA(lncRNA)in breast cancer, construct a breast cancer prognostic risk assessment model, and explore the prognostic factors. Methods The sequencing data, clinical information and immune gene set of breast cancer patients from the official websites of UCSC Xena(https://xena.ucsc.edu/), TCGA, and immport(https://www.immport.org/home)were downloaded. The data were sorted and cleaned, and finally breast cancer immune-related lncRNA expression matrix and clinical information were got. Univariate Cox regression analysis and Multivariate Cox regression analysis were used to screen out lncRNAs related to prognosis, so as to construct a prognostic risk score. According to the median risk score, the patients were divided into high-risk and low-risk groups. Kaplan-Meier(K-M)survival analysis, receiver operating characteristic(ROC)curve analysis and independent prognostic factor evaluation were used to evaluate the model. Combined with other clinical factors and risk scores of breast cancer, a nomogram was drawn to predict the individual survival rate of breast cancer patients. Results Ten immune-related lncRNAs were determined to construct a risk scoring model. The high-risk group had a poorer prognosis compared with the low-risk group. Risk score could be used as an independent prognostic factor for breast cancer. The C-index(CI)of the nomogram was 0.751. The calibration chart showed that the predicted value was in good agreement with the actual observation value. Conclusion A risk scoring model composed of 10 immune-related lncRNAs can be used to assess the prognosis of the breast cancer patients, and the corresponding nomogram can further predict the survival rate.

Key words: Breast cancer, Long non-coding RNA, Immunity, Prognosis, Predictive model

CLC Number: 

  • R736.3
[1] DeSantis CE, Ma J, Gaudet MM, et al. Breast cancer statistics, 2019[J]. CA Cancer J Clin, 2019, 69(6): 438-451.
[2] Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries [J]. CA Cancer J Clin, 2018, 68(6): 394-424.
[3] Amelio I, Bernassola F, Candi E. Emerging roles of long non-coding RNAs in breast cancer biology and management [J]. Semin Cancer Biol, 2021, 72: 36-45. doi: 10.1016/j.semcancer.2020.06.019.
[4] Harbeck N, Penault-Llorca F, Cortes J, et al. Breast cancer [J]. Nat Rev Dis Primers, 2019, 5(1): 66. doi: 10.1038/s41572-019-0111-2.
[5] Shen Y, Peng X, Shen C. Identification and validation of immune-related lncRNA prognostic signature for breast cancer [J]. Genomics, 2020, 112(3): 2640-2646.
[6] Saleh R, Elkord E. Acquired resistance to cancer immunotherapy: role of tumor-mediated immunosuppression [J]. Semin Cancer Biol, 2020, 65: 13-27. doi:10.1016/j.semcancer.2019.07.017.
[7] Vishnubalaji R, Shaath H, Elango R, et al. Noncoding RNAs as potential mediators of resistance to cancer immunotherapy [J]. Semin Cancer Biol, 2020, 65: 65-79. doi: 10.1016/j.semcancer.2019.11.006.
[8] Iyer MK, Niknafs YS, Malik R, et al. The landscape of long noncoding RNAs in the human transcriptome [J]. Nat Genet, 2015, 47(3): 199-208.
[9] Nagano T, Fraser P. No-nonsense functions for long noncoding RNAs [J]. Cell, 2011, 145(2): 178-181.
[10] Fatica A, Bozzoni I. Long non-coding RNAs: new players in cell differentiation and development [J]. Nat Rev Genet, 2014, 15(1): 7-21.
[11] Han CL, Ge M, Liu YP, et al. Long non-coding RNA H19 contributes to apoptosis of hippocampal neurons by inhibiting let-7b in a rat model of temporal lobe epilepsy [J]. Cell Death Dis, 2018, 9(6): 617. doi: 10.1038/s41419-018-0496-y.
[12] Lin YH, Wu MH, Yeh CT, et al. Long non-coding RNAs as mediator of tumor microenvironment and live cancer cell communication [J]. Int J Mol Sci, 2018, 19(12): 3742. doi: 10.3390/ijms19123742.
[13] Dykes IM, Emanueli C. Transcriptional and post-transcriptional gene regulation by long non-coding RNA [J]. Genomics Proteomics Bioinformatics, 2017, 15(3): 177-186. doi:10.1016/j.gpb.2016.12.005.
[14] Wang P, Xue Y, Han Y, et al. The STAT3-binding long noncoding RNA lnc-DC controls human dendritic cell differentiation [J]. Science, 2014, 344(6181): 310-313.
[15] Xin J, Li J, Feng Y, et al. Downregulation of long noncoding RNA HOTAIRM1 promotes monocyte/dendritic cell differentiation through competitivel binding to endogenous miR-3960 [J]. Onco Targets Ther, 2017, 10: 1307-1315. doi: 10.2147/OTT.S124201.
[16] Fang P, Xiang L, Chen W, et al. LncRNA GAS5 enhanced the killing effect of NK cell on liver cancer through regulating miR-544/RUNX3 [J]. Innate Immun, 2019, 25(2): 99-109.
[17] Chang L, Li C, Lan T, et al. Decreased expression of long non-coding RNAGAS5 indicates a poor prognosis and promotescell proliferation and invasion in hepatocellular carcinoma by regulating vimentin [J]. Mol Med Rep, 2016, 13(2): 1541-1550.
[18] Tian X, Wu Y, Yang Y. Long noncoding RNA LINC00662 promotes M2 macrophage polarization and Hepatocellular carcinoma progression via activating Wnt/beta-catenin signaling [J]. Mol Oncol, 2020, 14(2): 462-483.
[19] Liu J, Ding D, Jiang Z, et al. Long non-coding RNA CCAT1/miR-148a/PKCzet prevents cell migration of prostate cancerby altering macrophage polarization [J]. Prostate, 2019, 79(1): 105-112.
[20] Zhang L, Li C, Su X. Emerging impact of the long noncoding RNA MIR22HG and apoptosis in multiple human cancers [J]. J Exp Clin Cancer Res, 2020, 39(1): 271. doi:10.1186/s13046-020-01784-8.
[21] Zhou L, Zhu Y, Sun D, et al. Emerging roles of Long non-coding RNAs in the tumor microenvironment [J]. Int J Biol Sci, 2020, 16(12): 2094-2103.
[22] Wang Y, Battseren B, Yin W, et al. Predictive and prognostic value of prognostic nutritional index for locally advanced breast cancer [J]. Gland Surg, 2019, 8(6): 618-626.
[23] Ma W, Zhao F, Yu X, et al. Immune-related lncRNAs as predictors of Survival in breast cancer: a prognostic signature [J]. J Transl Med, 2020, 18(1): 442. doi:10.1186/s12967-020-02522-6.
[24] 吴彬, 姚颐, 董熠, 等.构建结肠癌免疫相关长链非编码RNA风险评分模型[J].肿瘤学杂志, 2020, 26(11): 966-971. WU Bin, YAO Yi, DONG Yi, et al. Construction of risk score nodel for prognosis of colon cancer with immune-related long non-coding RNA[J]. Journal of Chinese Oncology, 2020, 26(11): 966-971.
[25] 底斐瑶, 王一鹤, 底泽亚, 等.基于TCGA数据库确定宫颈癌预后免疫相关性长链非编码RNA并构建预后模型[J].世界最新医学信息文摘, 2020, 20(87): 34-39. DI Feiyao, WANG Yihe, DI Zeya, et al. Identifying immune-related lncRNA and constructing prognostic model in cervical cancer patients based on TCGA database[J]. World Latest Medicine Informatio(Electronic Version), 2020, 20(87): 34-39.
[26] 陈晓旭, 于洋, 张天雪. 基于免疫相关lncRNA 建立胰腺癌预后风险评估模型[J].国际肿瘤学杂志, 2020, 47(8): 472-479. CHEN Xiaoxu, YU Yang, ZHANG Tianxue. Aprognosis crisk assessment model for pancreatic cancer stablished based on immune related lncRNAs[J]. Journal of International Oncology, 2020, 47(8): 472-479.
[27] 王尧, 周旻, 柳子川, 等.免疫相关LncRNA与膀胱癌预后关系分析及预测模型建立[J].遵义医科大学学报, 2020, 43(1): 76-80. WANG Yao, ZHOU Min, LIU Zichuan, et al. Analysis of prognostic immune-related lncRNA and development of prognostic model for bladder cancer patients[J]. Journal of Zunyi Medical University, 2020, 43( 1): 76-80.
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