Project description:To obtain more information about the lymph node metastasis of breast cancer cells, we performed spatial transcriptomics analysis of the positive lymph node (PL) with the 10× Genomics Visium platform, which allows characterization of the spatial topography of gene expression.
Project description:Neuroblastoma, a deadly pediatric cancer from the sympathetic ganglia of the peripheral nervous system, frequently metastasizes, driving poor outcomes in high-risk cases. While primary tumors are well-characterized, the cellular and molecular dynamics of metastasis remain poorly understood. Here, we employed single-cell multi-omics and spatial transcriptomics to profile lymph node metastases in high-risk neuroblastoma compared to primary adrenal masses. We found that lymph node metastases displayed unique cellular heterogeneity and plasticity marked by a shift toward mesenchymal-like and cancer stem cell states, with enriched epithelial-to-mesenchymal transition (EMT) programs. Lymph node metastatic niche exhibited altered tumor microenvironment dynamics, characterized by increased immunosuppressive myeloid subsets, heightened immune checkpoint signaling and lymphocyte exhaustion, indicative of immune evasion and dysfunction. Our multi-omics studies reveal distinct features of high-risk neuroblastoma that contribute to metastasis and therapy resistance, pointing to potential therapeutic vulnerabilities of the aggressive metastatic disease.
Project description:Bulk sequencing and copy number analysis of seven colon cancer patient primary tumors and their lymph node metastases were analyzed. Tumor heterogeneity and subclonality were profiled for each lymph sample and mapped to multiple, spacially distinct primary samples to explore lymph node tumor seeding models.
Project description:We performed a quantitative proteome comparison on formalin-fixed paraffin embedded (FFPE) tissue of metastasized and non-metastasized primary prostate cancer (PCa) and on recurrent lymph node metastases. Comparing these three sample groups, we aimed to identify proteins, that might potentially promote/supress tumor progression or metastasis formation. Proteins were quantified label-free. Proteins with interesting biological functions were followed-up by immunohistochemistry.
Project description:Expression data from 4T1 subclones derived from mammary fat pad tumors (MFP), axillary lymph node tumors (AxLN), and axillary lymph node-derived lung metastases (AxLN-LuM). In parallel, expression data, in the same subclones, of tail vein-derived (TV) lung metastases. The mechanism of how lymph node metastases seed distant metastases is unknown. We used the 4T1 breast cancer cell line, which is an immune competent model of triple negative breast cancer and spontaneously metastasizes in balb/c mice. 4T1-GFP/fLuc cells were injected into MFP to form tumors and 4T1-mCherry/rLuc cells were injected into axillary lymph nodes to form tumors and then allowed to metastasize to lung. TV cells were allowed to metastasize in the lung. Cells were harvested at different time intervals after the injection. Tumors were extracted, dissociated, and then expanded in vitro to obtain MFP, AxLN, AxLN-LuM and TV-LuM subclones isolated after different time lags with respect to the injection.
Project description:To identify the lymph node (LN) metastasis-associated genes in primary ESCC tumors, gene expression profiling assay (GEP) was performed to identify the differences in gene expression profiles between primary ESCC tumors that were with LN metastases (N+) and those without LN metastases (N-).
Project description:This SuperSeries is composed of the following subset Series: GSE32488: Expression profiling of formalin-fixed, paraffin-embedded (FFPE) breast cancer metastases of the lymph node and autopsy tissues [DASL HT-12 samples] GSE32489: Expression profiling of formalin-fixed, paraffin-embedded (FFPE) breast cancer metastases of the lymph node and autopsy tissues [DASL HumanRef-v3 samples] Refer to individual Series
Project description:Lymph node metastases (LNM) and primary tumour samples were analysed using desorption electrospray ionisation mass spectrometry imaging (DESI MSI). Current assessment of LNM depends on subjective histopathological assessment, whereas analysis by DESI MSI permits an entirely objective assessment. The mass spectral data revealed specific lipidomic patterns across samples, which were shown to correspond to the immunohistochemical image. Statistical prediction of LNM samples was performed using the esophageal adenocarcinoma samples with sensitivity and specificity of 89.5% and 100%, respectively.