Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series The SNP and expression datasets represent the same samples (i.e., the 26 SNP6 samples are a subset of the 28 expression samples)
Project description:SNP6 profiling of metaplastic breast carcinoma Metaplastic breast carcinoma (MBC) is a rare and aggressive histologic type of breast cancer, preferentially displaying a triple-negative phenotype (i.e. lacking estrogen receptor, progesterone receptor and HER2 expression). We sought to define the transcriptomic heterogeneity of MBCs on the basis of current gene expression microarray-based classifiers and to determine whether MBCs display gene copy number profiles consistent with those of BRCA1-associated breast cancers.
Project description:Metaplastic breast cancer (MpBC) is a rare and aggressive form of breast cancer. Characteristically heterogeneous, MpBC are defined by the presence of various morphological elements, typically biphasic, with epithelial (e.g. non-special type (NST), squamous) and mesenchymal (e.g. spindle, chondroid, osteoid) components. The established clonality of the different components, favours an evolution model encompassing either a multipotent progenitor, or a linear metaplastic conversion. Our study defines the micro-methylome and a spatial transcriptomic profile in MpBC, and identifies potential drivers associated with tumor heterogeneity that supports the conversion model of metaplasia and warrants further functional analysis.
Project description:Metaplastic breast carcinoma (MpBC) typically consists of carcinoma of no special type (NST) with various metaplastic components. The intracase transcriptomic alterations between metaplastic components and paired NST components, which are critical for understanding the pathogenesis underlying the metaplastic processes, remain unclear. Herein, 59 NST components and paired metaplastic components (spindle sarcomatous [SPS], matrix-producing, rhabdomyoid [RHA], and squamous carcinomatous [SQC] components) were microdissected from specimens obtained from 27 patients with MpBC for gene expression profiling. Hierarchical clustering and principal component analysis revealed a heterogeneous gene expression profile (GEP) corresponding to the NST components, but the GEP of metaplastic components exhibited subtype dependence. Compared with the paired NST components, the SPS components demonstrated the upregulation of genes related to stem cells and epithelial–mesenchymal transition, and displayed enrichment in claudin-low and macrophage signatures. Despite certain overlap in the enriched functions and signatures between the RHA and SPS components, the specific differentially expressed genes differed. We observed the RHA-specific upregulation of genes associated with vascular endothelial growth factor signaling. The chondroid matrix-producing components demonstrated the upregulation of hypoxia-related genes and the downregulation of the immune-related MHC2 signature and the TIGIT gene. In the SQC components, TGF-β and genes associated with cell adhesion were upregulated. The differentially expressed genes among metaplastic components in the 22 MpBC cases with one or predominantly one metaplastic component clustered paired NST samples into clusters with correlation with their associated metaplastic types. These genes could be used to separate the 31 metaplastic components according to respective metaplastic types with an accuracy of 74.2%, suggesting that intrinsic signatures of NST may determine paired metaplastic type. The EMT activity and stem cell traits in the NST components were correlated with specimens displaying lymph node metastasis. In summary, we presented the distinct transcriptomic alterations underlying metaplasia into specific metaplastic components in MpBCs.
Project description:In this project we have used single cell RNA-seq to profile pancreatic cancer development in a mouse model, from pre-invasive stage to cancer, and in human PDAC sample. Using a reporter gene, we were able to dissect metaplastic acinar cell heterogeneity, profiled six different acinar metaplastic cell types and states, validated their localization to pre-invasive lesions and correlated findings with human PDAC. In addition, we detected transcription factors, Onecut2 and Foxq1, that strictly expressed in metaplastic cells.
Project description:In this project, we utilized single-cell RNA sequencing (scRNA-seq) and MERFISH spatial transcriptomics to profile the development of pancreatic cancer in a mouse model, tracing its progression from the pre-invasive stage to full malignancy. By employing a reporter gene, we were able to dissect the heterogeneity of metaplastic acinar cells, identifying and profiling six distinct types and states of these cells. We validated their localization within pre-invasive lesions, assessed the heterogeneity across various lesions, and calculated the colocalization of different acinar metaplastic cells with stromal cells.