Abstract

Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death among women worldwide. Therefore, the need for effective breast cancer treatment is urgent. Transcription factors (TFs) directly participate in gene transcription, and their dysregulation plays a key role in breast cancer. Our study identified 459 differentially expressed TFs between tumor and normal samples from The Cancer Genome Atlas database. Based on gene expression analysis and weighted gene co-expression network analysis, the co-expression yellow module was found to be integral for breast cancer progression. A total of 121 genes in the yellow module were used for function enrichment. To further confirm prognosis-related TFs, COX regression and LASSO analyses were performed; consequently, a prognostic risk model was constructed, and its validity was verified. Ten prognosis-related TFs were identified according to their expression profile, survival probability, and target genes. COPS5, HDAC2, and NONO were recognized as hub TFs in breast cancer. These TFs were highly expressed in human breast cancer cell lines and clinical breast cancer samples; this result was consistent with the information from multiple databases. Immune infiltration analysis revealed that the proportions of resting dendritic and mast cells were greater in the low-risk group than those in the high-risk group. Thus, in this study, we identified three hub biomarkers related to breast cancer prognosis. The results provide a framework for the co-expression of TF modules and immune infiltration in breast cancer.

Highlights

  • Transcription factors (TFs) identify specific DNA promoters to control chromatin and transcription in the process from gene to protein [1]

  • In order to further analyze the function of these TFs, the “clusterProfiler” R package was used to conduct the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation analyses for the 459 differential TFs (Supplemental Table 2)

  • TFs are involved in various human diseases, such as cancers, for which they account for about 20% of all oncogenes identified so far

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Summary

Introduction

Transcription factors (TFs) identify specific DNA promoters to control chromatin and transcription in the process from gene to protein [1]. TFs are spatially, temporally, and sequentially expressed in tissues during cell development, proliferation, or differentiation processes; and any modification of their expression and functional disorder may result in master deregulation of cell integrity or organism homeostasis leading to pathologies. TFs are able to activate or repress gene transcription depending on the specific structure of their DNA-binding domain, including structural motifs, such as the C2H2 homeodomain, helix–loop–helix, helix–turn–helix, and leucine zipper [2]. MLL-AF9 is a driver of the leukemia stem cell population [7]; GABP increases expression of TERT in glioblastomas with a mutant TERT promoter [8]; PML–RARa blocks cell differentiation in acute promyelocytic leukemia [9]; RUNX1–ETO reduces CD48, thereby decreasing NK cell killing [10]; Runx and SIX1 induce epithelial-mesenchymal transition (EMT) and breast cell invasion [11, 12]

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