Analysis of genomics and immune infiltration patterns of epithelial-mesenchymal transition related to metastatic breast cancer to bone

Autor: Yong Liu, An Song, Wu Yunxiao, Zhen Huo, Muchuan Wang, Siyuan Yao, Ziquan Li, Xi Zhou, Yipeng Wang, Bo Yang, Shuzhong Liu, Tong Niu, Chengao Gao
Jazyk: angličtina
Rok vydání: 2021
Předmět:
0301 basic medicine
Cancer Research
Cell type
ROC curve
receiver operating characteristic curve
Runx2
runt related transcription factor 2
TNM
Tumor
Node
Metastases
Biology
lcsh:RC254-282
TOM
topological overlap measure
Metastasis
03 medical and health sciences
0302 clinical medicine
Immune system
KEGG
kyoto encyclopedia of genes and genomes
ME
module eigengene
medicine
Epithelial–mesenchymal transition
Cytokine binding
BMP
Bone morphogenetic protein
Immune infiltration pattern
Differential gene expression
Original Research
GO
gene ontology
IPA
Ingenuity Pathway Analysis
WGCNA
GEO
gene expression omnibus
Bone metastases
PCC
Pearson correlation coefficient
Breast cancer metastases
AUC
Area under curve
Cancer
Bone metastasis
medicine.disease
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
DE
differentially expressed
030104 developmental biology
medicine.anatomical_structure
Oncology
WGCNA
weighted co-expression network analysis
030220 oncology & carcinogenesis
Mrna
messenger rna
Cancer research
EMT
epithelial-mesenchymal transition
Prognostic model
Memory T cell
Zdroj: Translational Oncology, Vol 14, Iss 2, Pp 100993-(2021)
Translational Oncology
ISSN: 1936-5233
Popis: Highlights • Differential expression analysis showed a total of 304 differentially expressed genes, which were mainly related to proteoglycans in cancer, the PI3K/Akt signaling pathway, and the TGF-beta signaling pathway. • The survival-related linear risk assessment model consisting of eight genes (FERMT2, ITGA5, ITGB1, MCAM, CEMIP, HGF, TGFBR1, F2RL2) was constructed. The survival rates of high-risk patients were significantly lower than that of the low-risk group, and the 3-, 5-, and 10-year AUCs were satisfactory. • BMP2, BMPR2, and GREM1 were differentially expressed in both data sets of breast cancer bone metastasis. • In GSE20685 and GSE45255, significant differences in immune infiltration patterns were found between high- and low-risk groups. • BMP-2 may regulate the immune infiltration process in breast cancer tissues through the PI3K/Akt signaling pathway.
Objective This study aimed to design a weighted co-expression network and a breast cancer (BC) prognosis evaluation system using a specific whole-genome expression profile combined with epithelial-mesenchymal transition (EMT)-related genes; thus, providing the basis and reference for assessing the prognosis risk of spreading of metastatic breast cancer (MBC) to the bone. Methods Four gene expression datasets of a large number of samples from GEO were downloaded and combined with the dbEMT database to screen out EMT differentially expressed genes (DEGs). Using the GSE20685 dataset as a training set, we designed a weighted co-expression network for EMT DEGs, and the hub genes most relevant to metastasis were selected. We chose eight hub genes to build prognostic assessment models to estimate the 3-, 5-, and 10-year survival rates. We evaluated the models’ independent predictive abilities using univariable and multivariable Cox regression analyses. Two GEO datasets related to bone metastases from BC were downloaded and used to perform differential genetic analysis. We used CIBERSORT to distinguish 22 immune cell types based on tumor transcripts. Results Differential expression analysis showed a total of 304 DEGs, which were mainly related to proteoglycans in cancer, and the PI3K/Akt and the TGF-β signaling pathways, as well as mesenchyme development, focal adhesion, and cytokine binding functionally. The 50 hub genes were selected, and a survival-related linear risk assessment model consisting of eight genes (FERMT2, ITGA5, ITGB1, MCAM, CEMIP, HGF, TGFBR1, F2RL2) was constructed. The survival rate of patients in the high-risk group (HRG) was substantially lower than that of the low-risk group (LRG), and the 3-, 5-, and 10-year AUCs were 0.68, 0.687, and 0.672, respectively. In addition, we explored the DEGs of BC bone metastasis, and BMP2, BMPR2, and GREM1 were differentially expressed in both data sets. In GSE20685, memory B cells, resting memory T cell CD4 cells, T regulatory cells (Tregs), γδ T cells, monocytes, M0 macrophages, M2 macrophages, resting dendritic cells (DCs), resting mast cells, and neutrophils exhibited substantially different distribution between HRG and LRG. In GSE45255, there was a considerable difference in abundance of activated NK cells, monocytes, M0 macrophages, M2 macrophages, resting DCs, and neutrophils in HRG and LRG. Conclusions Based on the weighted co-expression network for breast-cancer-metastasis-related DEGs, we screened hub genes to explore a prognostic model and the immune infiltration patterns of MBC. The results of this study provided a factual basis to bioinformatically explore the molecular mechanisms of the spread of MBC to the bone and the possibility of predicting the survival of patients.
Databáze: OpenAIRE
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