A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA746133 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15115207_1.fastq.gz | Fastqsanger.gz | |||
| SRR15115207_2.fastq.gz | Fastqsanger.gz | |||
| SRR15115208_1.fastq.gz | Fastqsanger.gz | |||
| SRR15115208_2.fastq.gz | Fastqsanger.gz | |||
| SRR15115209_1.fastq.gz | Fastqsanger.gz |
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Project description:Intratumor heterogeneity associates with poor patient outcome. Stromal stiffening also accompanies cancer. Whether cancers demonstrate stiffness heterogeneity, and if this is linked to tumor cell heterogeneity remains unclear. We developed a method to measure the stiffness heterogeneity in human breast tumors that quantifies the stromal stiffness each cell experiences and permits visual registration with biomarkers of tumor progression. We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer vision to precisely automate atomic force microscopy (AFM) indentation combined with a trained convolutional neural network to predict stromal elasticity with micron-resolution using collagen morphological features and ground truth AFM data. We registered high-elasticity regions within human breast tumors colocalizing with markers of mechanical activation and an epithelial-to-mesenchymal transition (EMT). The findings highlight the utility of STIFMaps to assess mechanical heterogeneity of human tumors across length scales from single cells to whole tissues and implicates stromal stiffness in tumor cell heterogeneity.
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Project description:Intratumor heterogeneity associates with poor patient outcome. Stromal stiffening also accompanies cancer. Whether cancers demonstrate stiffness heterogeneity, and if this is linked to tumor cell heterogeneity remains unclear. We developed a method to measure the stiffness heterogeneity in human breast tumors that quantifies the stromal stiffness each cell experiences and permits visual registration with biomarkers of tumor progression. We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer vision to precisely automate atomic force microscopy (AFM) indentation combined with a trained convolutional neural network to predict stromal elasticity with micron-resolution using collagen morphological features and ground truth AFM data. We registered high-elasticity regions within human breast tumors colocalizing with markers of mechanical activation and an epithelial-to-mesenchymal transition (EMT). The findings highlight the utility of STIFMap to assess mechanical heterogeneity of human tumors across length scales from single cells to whole tissues and implicates stromal stiffness in tumor cell heterogeneity.
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Project description:Oral Squamous Cell Carcinoma (OSCC) contains diverse communities of cells within the oral mucosa. A subset of the epithelia is highly responsive to changing niche conditions, resulting in their loss of polarity, epithelial-to-mesenchymal transition (EMT), and invasion in tumor-adjacent stroma. Given the range of cell states, we sought to understand how cytokine-mediated signaling from mesenchymal SCC25 cells or stiffness induced-mesenchymal (simCal27) cells caused EMT in naïve Cal27 epithelial cells. Media conditioned by SCC25 enhanced Cal27 cell migration, nuclear localization of EMT markers, and caused transcriptomic changes related to cytokine response ontological terms. SCC and simCal27 cells have unique cytokine profiles–which when regressed against transcriptomic changes–suggested that higher expression of IL-1a, IL-6, IL-8, Angiogenin and PAI-1 in conditioned media could drive EMT; upregulation of these cytokines also appears impactful for overall survival and progression-free interval. However, depletion and supplementation assays clearly show that the presence of these specific cytokines is critical to induce a migratory phenotype and that naïve Cal27’s motility is regulated by MAPK and AKT signaling pathways; loss or inhibition of these pathways reduced migration. These data suggest that paracrine signals from stiffness induced-mesenchymal cells act via distinct kinase pathways and may be necessary for cooperative dissemination of OSCC.
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Project description:Cells sense the biophysical properties of the surrounding microenvironment. In particular, the stiffness of the extracellular milieu can be interrogated by cells and integrated through mechanotransduction. Many cellular processes (like proliferation, migration, or differentiation) depend on the mechanical status of the cell (being largely dictated by actomyosin-dependent intracellular contractility), which in turn is influenced by the mechanical properties of the microenvironment. In this study, we explored the influence of substrate stiffness on the proteome of undifferentiated human umbilical cord matrix mesenchymal stem/stromal cells (hUCM-MSCs). The relative abundance of several identified proteins suffered significant changes when comparing between substrates. Interestingly, many of such proteins are related to the regulation of the actin cytoskeleton, a main player of mechanotransduction and cell physiology in response to mechanical cues.
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