ADEPT: Autoencoder with differentially expressed genes and imputation for robust spatial transcriptomics clustering.

Advancements in spatial transcriptomics (ST) have enabled an in-depth understanding of complex tissues by quantifying gene expression at spatially localized spots. Several notable clustering methods have been introduced to utilize both spatial and transcriptional information in the analysis of ST datasets. However, data quality across different ST sequencing techniques and types of datasets influence the performance of different methods and benchmarks. To harness spatial context and transcriptional profile in ST data, we developed a graph-based, multi-stage framework for robust clustering, called ADEPT. To control and stabilize data quality, ADEPT relies on a graph autoencoder backbone and performs an iterative clustering on imputed, differentially expressed genes-based matrices to minimize the variance of clustering results. ADEPT outperformed other popular methods on ST data generated by different platforms across analyses such as spatial domain identification, visualization, spatial trajectory inference, and data denoising.

Matrix stiffness regulates tumor cell intravasation through expression and ESRP1-mediated alternative splicing of MENA.

During intravasation, cancer cells cross the endothelial barrier and enter the circulation. Extracellular matrix stiffening has been correlated with tumor metastatic potential; however, little is known about the effects of matrix stiffness on intravasation. Here, we utilize in vitro systems, a mouse model, specimens from patients with breast cancer, and RNA expression profiles from The Cancer Genome Atlas Program (TCGA) to investigate the molecular mechanism by which matrix stiffening promotes tumor cell intravasation. Our data show that heightened matrix stiffness increases MENA expression, which promotes contractility and intravasation through focal adhesion kinase activity. Further, matrix stiffening decreases epithelial splicing regulatory protein 1 (ESRP1) expression, which triggers alternative splicing of MENA, decreases the expression of MENA11a, and enhances contractility and intravasation. Altogether, our data indicate that matrix stiffness regulates tumor cell intravasation through enhanced expression and ESRP1-mediated alternative splicing of MENA, providing a mechanism by which matrix stiffness regulates tumor cell intravasation.

Weakly migratory metastatic breast cancer cells activate fibroblasts via microvesicle-Tg2 to facilitate dissemination and metastasis.

Cancer cell migration is highly heterogeneous, and the migratory capability of cancer cells is thought to be an indicator of metastatic potential. It is becoming clear that a cancer cell does not have to be inherently migratory to metastasize, with weakly migratory cancer cells often found to be highly metastatic. However, the mechanism through which weakly migratory cells escape from the primary tumor remains unclear. Here, utilizing phenotypically sorted highly and weakly migratory human breast cancer cells, we demonstrate that weakly migratory metastatic cells disseminate from the primary tumor via communication with stromal cells. While highly migratory cells are capable of single cell migration, weakly migratory cells rely on cell-cell signaling with fibroblasts to escape the primary tumor. Weakly migratory cells release microvesicles rich in tissue transglutaminase 2 (Tg2) which activate murine fibroblasts and lead weakly migratory cancer cell migration in vitro. These microvesicles also induce tumor stiffening and fibroblast activation in vivo and enhance the metastasis of weakly migratory cells. Our results identify microvesicles and Tg2 as potential therapeutic targets for metastasis and reveal a novel aspect of the metastatic cascade in which weakly migratory cells release microvesicles which activate fibroblasts to enhance cancer cell dissemination.