A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer
Abstract 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...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-023-39085-1 |
| _version_ | 1797801316548870144 |
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| author | Connor Stashko Mary-Kate Hayward Jason J. Northey Neil Pearson Alastair J. Ironside Johnathon N. Lakins Roger Oria Marie-Anne Goyette Lakyn Mayo Hege G. Russnes E. Shelley Hwang Matthew L. Kutys Kornelia Polyak Valerie M. Weaver |
| author_facet | Connor Stashko Mary-Kate Hayward Jason J. Northey Neil Pearson Alastair J. Ironside Johnathon N. Lakins Roger Oria Marie-Anne Goyette Lakyn Mayo Hege G. Russnes E. Shelley Hwang Matthew L. Kutys Kornelia Polyak Valerie M. Weaver |
| author_sort | Connor Stashko |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-13T04:48:35Z |
| format | Article |
| id | doaj.art-8eef1f697e6d46898510e81e54f4c1d8 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-03-13T04:48:35Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-8eef1f697e6d46898510e81e54f4c1d82023-06-18T11:19:50ZengNature PortfolioNature Communications2041-17232023-06-0114111610.1038/s41467-023-39085-1A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancerConnor Stashko0Mary-Kate Hayward1Jason J. Northey2Neil Pearson3Alastair J. Ironside4Johnathon N. Lakins5Roger Oria6Marie-Anne Goyette7Lakyn Mayo8Hege G. Russnes9E. Shelley Hwang10Matthew L. Kutys11Kornelia Polyak12Valerie M. Weaver13Department of Surgery, University of CaliforniaDepartment of Surgery, University of CaliforniaDepartment of Surgery, University of CaliforniaHarvey Mudd CollegeDepartment of Pathology, Western General Hospital, NHS LothianDepartment of Surgery, University of CaliforniaDepartment of Surgery, University of CaliforniaDepartment of Medical Oncology, Dana-Farber Cancer InstituteDepartment of Cell and Tissue Biology, School of Dentistry, University of California, San FranciscoDepartment of Pathology and Department of Cancer Genetics, Institute for Cancer Research, Oslo University HospitalDepartment of Surgery, Duke University Medical CenterDepartment of Cell and Tissue Biology, School of Dentistry, University of California, San FranciscoDepartment of Medical Oncology, Dana-Farber Cancer InstituteDepartment of Surgery, University of CaliforniaAbstract 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.https://doi.org/10.1038/s41467-023-39085-1 |
| spellingShingle | Connor Stashko Mary-Kate Hayward Jason J. Northey Neil Pearson Alastair J. Ironside Johnathon N. Lakins Roger Oria Marie-Anne Goyette Lakyn Mayo Hege G. Russnes E. Shelley Hwang Matthew L. Kutys Kornelia Polyak Valerie M. Weaver A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer Nature Communications |
| title | A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer |
| title_full | A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer |
| title_fullStr | A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer |
| title_full_unstemmed | A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer |
| title_short | A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer |
| title_sort | convolutional neural network stifmap reveals associations between stromal stiffness and emt in breast cancer |
| url | https://doi.org/10.1038/s41467-023-39085-1 |
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