The prognostic genes model of breast cancer drug resistance based on single-cell sequencing analysis and transcriptome analysis

作者全名：Liu, Yao; Dong, Lun; Ma, Jing; Chen, Linghui; Fang, Liaoqiong; Wang, Zhibiao

作者地址：[Liu, Yao; Ma, Jing; Chen, Linghui; Fang, Liaoqiong; Wang, Zhibiao] Chongqing Med Univ, Coll Biomed Engn, State Key Lab Ultrasound Med & Engn, Chongqing 400016, Peoples R China; [Liu, Yao; Ma, Jing; Chen, Linghui; Wang, Zhibiao] Chongqing Med Univ, Chongqing Key Lab Biomed Engn, Chongqing 400016, Peoples R China; [Dong, Lun] Chongqing Med Univ, Affiliated Hosp 2, Dept Endocrinol, Chongqing, Peoples R China; [Fang, Liaoqiong; Wang, Zhibiao] Natl Engn Res Ctr Ultrasound Med, Chongqing 401121, Peoples R China

通信作者：Fang, LQ; Wang, ZB (通讯作者)，Chongqing Med Univ, Coll Biomed Engn, State Key Lab Ultrasound Med & Engn, Chongqing 400016, Peoples R China.; Wang, ZB (通讯作者)，Chongqing Med Univ, Chongqing Key Lab Biomed Engn, Chongqing 400016, Peoples R China.; Fang, LQ; Wang, ZB (通讯作者)，Natl Engn Res Ctr Ultrasound Med, Chongqing 401121, Peoples R China.

来源：CLINICAL AND EXPERIMENTAL MEDICINE

ESI学科分类：CLINICAL MEDICINE

WOS号：WOS:001232470000001

JCR分区：Q2

影响因子：3.2

年份：2024

卷号：24

期号：1

开始页：　

结束页：　

文献类型：Article

关键词：Breast cancer; Exosomes; Drug resistance; Biomarkers; Immunoinfiltration; Prognostic model

摘要：Breast cancer (BC) represents a multifaceted malignancy, with escalating incidence and mortality rates annually. Chemotherapy stands as an indispensable approach for treating breast cancer, yet drug resistance poses a formidable challenge. Through transcriptome data analysis, we have identified two sets of genes exhibiting differential expression in this context. Furthermore, we have confirmed the overlap between these genes and those associated with exosomes, which were subsequently validated in cell lines. The investigation screened the identified genes to determine prognostic markers for BC and utilized them to formulate a prognostic model. The disparities in prognosis and immunity between the high- and low-risk groups were validated using the test dataset. We have discerned different BC subtypes based on the expression levels of prognostic genes in BC samples. Variations in prognosis, immunity, and drug sensitivity among distinct subtypes were examined. Leveraging data from single-cell sequencing and prognostic gene expression, the AUCell algorithm was employed to score individual cell clusters and analyze the pathways implicated in high-scoring groups. Prognostic genes (CCT4, CXCL13, MTDH, PSMD2, and RAB27A) were subsewoquently validated using RT-qPCR. Consequently, we have established a model for predicting prognosis in breast cancer that hinges on drug resistance and ERGs. Furthermore, we have evaluated the prognostic value of this model. The genes identified as prognostic markers can now serve as a reference for precise treatment of this condition.

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