TBX1 functions as a putative oncogene of breast cancer through promoting cell cycle progression

Transcriptomic analysis reveals transcription factors implicated in radon-induced lung carcinogenesis

Background

Radon, a potent carcinogen, is a significant catalyst for lung cancer development. However, the molecular mechanisms triggering radon-induced lung cancer remain elusive.

Methods

Utilizing a radon exposure concentration of 20,000 Bq/m3 for 20 min/session, malignant transformation was induced in human bronchial epithelial cells (BEAS-2B).

Results

Radon-exposed cells derived from passage 25 (BEAS-2B-Rn) exhibited enhanced proliferation and increased colony formation. Analysis of differential gene expression (DEG) through transcription factors revealed 663 up-regulated and 894 down-regulated genes in radon-exposed cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed significant alterations in the malignant transformation pathway of cells, including those related to cancer and the PI3K/AKT signaling pathway. A PPI network analysis indicated a significant association of oncogenes, such as CCND1, KIT, and GATA3, with lung cancer among differentially expressed genes. In addition, the stability of the housekeeping gene was determined through RT-qPCR analysis, which also confirmed the results of transcriptome analysis.

Conclusions

The results suggest that transcription factors may play a pivotal role in conferring a survival advantage to radon-exposed cells. This is achieved by malignant transformation of human bronchial epithelial cells into lung carcinogenesis cell phenotypes.

Integrating spatial transcriptomics and bulk RNA-seq: predicting gene expression with enhanced resolution through graph attention networks

Spatial transcriptomics data play a crucial role in cancer research, providing a nuanced understanding of the spatial organization of gene expression within tumor tissues. Unraveling the spatial dynamics of gene expression can unveil key insights into tumor heterogeneity and aid in identifying potential therapeutic targets. However, in many large-scale cancer studies, spatial transcriptomics data are limited, with bulk RNA-seq and corresponding Whole Slide Image (WSI) data being more common (e.g. TCGA project). To address this gap, there is a critical need to develop methodologies that can estimate gene expression at near-cell (spot) level resolution from existing WSI and bulk RNA-seq data. This approach is essential for reanalyzing expansive cohort studies and uncovering novel biomarkers that have been overlooked in the initial assessments. In this study, we present STGAT (Spatial Transcriptomics Graph Attention Network), a novel approach leveraging Graph Attention Networks (GAT) to discern spatial dependencies among spots. Trained on spatial transcriptomics data, STGAT is designed to estimate gene expression profiles at spot-level resolution and predict whether each spot represents tumor or non-tumor tissue, especially in patient samples where only WSI and bulk RNA-seq data are available. Comprehensive tests on two breast cancer spatial transcriptomics datasets demonstrated that STGAT outperformed existing methods in accurately predicting gene expression. Further analyses using the TCGA breast cancer dataset revealed that gene expression estimated from tumor-only spots (predicted by STGAT) provides more accurate molecular signatures for breast cancer sub-type and tumor stage prediction, and also leading to improved patient survival and disease-free analysis. Availability: Code is available at https://github.com/compbiolabucf/STGAT.

Multiwalled Carbon Nanotubes-Reprogrammed Macrophages Facilitate Breast Cancer Metastasis via NBR2/TBX1 Axis

In recent years, carbon nanotubes have emerged as a widely used nanomaterial, but their human exposure has become a significant concern. In our former study, we reported that pulmonary exposure of multiwalled carbon nanotubes (MWCNTs) promoted tumor metastasis of breast cancer; macrophages were key effectors of MWCNTs and contributed to the metastasis-promoting procedure in breast cancer, but the underlying molecular mechanisms remain to be explored. As a follow-up study, we herein demonstrated that MWCNT exposure in breast cancer cells and macrophage coculture systems promoted metastasis of breast cancer cells both in vitro and in vivo; macrophages were skewed into M2 polarization by MWCNT exposure. LncRNA NBR2 was screened out to be significantly decreased in MWCNTs-stimulated macrophages through RNA-seq; depletion of NBR2 led to the acquisition of M2 phenotypes in macrophages by activating multiple M2-related pathways. Specifically, NBR2 was found to positively regulate the downstream gene TBX1 through H3k27ac activation. TBX1 silence rescued NBR2-induced impairment of M2 polarization in IL-4 & IL-13-stimulated macrophages. Moreover, NBR2 overexpression mitigated the enhancing effects of MWCNT-exposed macrophages on breast cancer metastasis. This study uncovered the molecular mechanisms underlying breast cancer metastasis induced by MWCNT exposure.