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Distant metastasis remains the primary cause of morbidity in patients with breast cancer. Hence, the development of more efficacious strategies and the exploration of potential targets for patients with metastatic breast cancer are urgently needed. The data of six patients with breast cancer brain metastases (BCBrM) from two centres were collected, and a comprehensive landscape of the entire tumour ecosystem was generated through the utilisation of single‐cell RNA sequencing. We utilised the Monocle2 and CellChat algorithms to investigate the interrelationships among each subcluster. In addition, multiple signatures were collected to evaluate key components of the subclusters through multi‐omics methodologies. Finally, we elucidated common expression programs of malignant cells, and experiments were conducted in vitro and in vivo to determine the functions of interleukin enhancer‐binding factor 2 (ILF2), which is a key gene in the metastasis module, in BCBrM progression. We found that subclusters in each major cell type exhibited diverse characteristics. Besides, our study indicated that ILF2 was specifically associated with BCBrM, and experimental validations further demonstrated that ILF2 deficiency hindered BCBrM progression. Our study offers novel perspectives on the heterogeneity of BCBrM and suggests that ILF2 could serve as a promising biomarker or therapeutic target for BCBrM. [ABSTRACT FROM AUTHOR]

Glioma, a highly aggressive neuroepithelial malignant brain tumor, is associated with high disability and recurrence rates. Enhancer RNA (eRNA) plays a significant role in tumor proliferation and metastasis; however, their functions in gliomas need further evaluation. We used the computational pipeline, PreSTIGE, to predict tissue-specific enhancer-derived RNAs and the underlying regulatory genes. Using data retrieved from the TCGA and CGGA databases, a LASSO regression analysis and multiCox proportional hazards regression analyses were performed to determine the hub eRNAs associated with glioma prognosis. Quantitative reverse transcription PCR was performed on the glioma samples to evaluate the expression characteristics of the identified hub eRNAs. To construct a risk signature, we selected three eRNAs, including CRNDE, MRPS31P5, and LINC00844, for their significant prognostic values. The predictive value of the risk signature was validated using the CGGA and Rembrandt cohorts. Apart from the risk signature, the nomogram performed well at predicting OS in glioma patients. An eRNA-target gene regulatory network was established, which we evaluated using a target gene enrichment analysis. Pathway and gene ontology (GO) analyses demonstrated that the risk signature is associated with mRNA processing and spliceosome in glioma. Furthermore, we found that hub eRNAs potentially regulate the expressions of numerous splicing factors, such as MOV10 and SEC31B, and are correlated with prognosis-associated alteration splicing (AS). In conclusion, we established a risk signature that comprises three eRNAs, which can accurately be utilized as targets to predict prognosis in glioma patients., Competing Interests: None., (AJTR Copyright © 2021.)