Search

Your search keyword '"Paterson, Joshua"' showing total 21 results
Start Over Author "Paterson, Joshua"
21 results on '"Paterson, Joshua"'

7. Additional file 2 of Stem/progenitor cell marker expression in clear cell renal cell carcinoma: a potential relationship with the immune microenvironment to be explored

Author

Ju-Yoon Yoon, Gedye, Craig, Paterson, Joshua, and Ailles, Laurie

Abstract

Additional file 2: Supp. Figure 2. Clustered expression heatmap, displaying the expression levels for 13 markers (12 stem/progenitor cell markers and CD10) in the six patient samples, in the four different cell populations as indicated.

Published
2020
Full Text
View/download PDF

8. Additional file 1 of Stem/progenitor cell marker expression in clear cell renal cell carcinoma: a potential relationship with the immune microenvironment to be explored

Author

Ju-Yoon Yoon, Gedye, Craig, Paterson, Joshua, and Ailles, Laurie

Abstract

Additional file 1: Supp. Figure 1. Correlation heatmap displaying the Pearson correlations between the 19 stem/progenitor cell marker genes in the TCGA cohort vs. PTPRC and immune checkpoint inhibitor genes.

Published
2020
Full Text
View/download PDF

9. Distinct fibroblast functional states drive clinical outcomes in ovarian cancer and are regulated by TCF21

Author

Hussain, Ali, primary, Voisin, Veronique, primary, Poon, Stephanie, primary, Karamboulas, Christina, primary, Bui, Ngoc Hoang Bao, primary, Meens, Jalna, primary, Dmytryshyn, Julia, primary, Ho, Victor W., primary, Tang, Kwan Ho, primary, Paterson, Joshua, primary, Clarke, Blaise A., primary, Bernardini, Marcus Q., primary, Bader, Gary D., primary, Neel, Benjamin G., primary, and Ailles, Laurie E., primary

Published
2020
Full Text
View/download PDF

11. Molecular and functional heterogeneity of cancer associated fibroblasts in high-grade serous ovarian cancer

Author

Hussain, Ali, primary, Voisin, Veronique, additional, Poon, Stephanie, additional, Dmytryshyn, Julia, additional, Richman, Cory, additional, Meens, Jalna, additional, Ho, Victor W, additional, Tang, Kwan Ho, additional, Paterson, Joshua, additional, Clarke, Blaise, additional, Bernardini, Marcus Q, additional, Bader, Gary D, additional, Neel, Benjamin G, additional, and Ailles, Laurie E, additional

Published
2019
Full Text
View/download PDF

12. Interrogation of Functional Cell-Surface Markers Identifies CD151 Dependency in High-Grade Serous Ovarian Cancer

Author

Medrano, Mauricio, primary, Communal, Laudine, additional, Brown, Kevin R., additional, Iwanicki, Marcin, additional, Normand, Josee, additional, Paterson, Joshua, additional, Sircoulomb, Fabrice, additional, Krzyzanowski, Paul, additional, Novak, Marian, additional, Doodnauth, Sasha A., additional, Saiz, Fernando Suarez, additional, Cullis, Jane, additional, Al-awar, Rima, additional, Neel, Benjamin G., additional, McPherson, John, additional, Drapkin, Ronny, additional, Ailles, Laurie, additional, Mes-Massons, Anne-Marie, additional, and Rottapel, Robert, additional

Published
2017
Full Text
View/download PDF

14. Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine

Author

Lobo, Nazleen C., primary, Gedye, Craig, additional, Apostoli, Anthony J., additional, Brown, Kevin R., additional, Paterson, Joshua, additional, Stickle, Natalie, additional, Robinette, Michael, additional, Fleshner, Neil, additional, Hamilton, Robert J., additional, Kulkarni, Girish, additional, Zlotta, Alexandre, additional, Evans, Andrew, additional, Finelli, Antonio, additional, Moffat, Jason, additional, Jewett, Michael A. S., additional, and Ailles, Laurie, additional

Published
2016
Full Text
View/download PDF

15. Cell Surface Profiling Using High-Throughput Flow Cytometry: A Platform for Biomarker Discovery and Analysis of Cellular Heterogeneity

Author

Gedye, Craig A., primary, Hussain, Ali, additional, Paterson, Joshua, additional, Smrke, Alannah, additional, Saini, Harleen, additional, Sirskyj, Danylo, additional, Pereira, Keira, additional, Lobo, Nazleen, additional, Stewart, Jocelyn, additional, Go, Christopher, additional, Ho, Jenny, additional, Medrano, Mauricio, additional, Hyatt, Elzbieta, additional, Yuan, Julie, additional, Lauriault, Stevan, additional, Kondratyev, Maria, additional, van den Beucken, Twan, additional, Jewett, Michael, additional, Dirks, Peter, additional, Guidos, Cynthia J., additional, Danska, Jayne, additional, Wang, Jean, additional, Wouters, Bradly, additional, Neel, Benjamin, additional, Rottapel, Robert, additional, and Ailles, Laurie E., additional

Published
2014
Full Text
View/download PDF

19. Additional file 10: Figure S1. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine

Author

Nazleen Lobo, Gedye, Craig, Apostoli, Anthony, Brown, Kevin, Paterson, Joshua, Stickle, Natalie, Robinette, Michael, Fleshner, Neil, Hamilton, Robert, Girish Kulkarni, Zlotta, Alexandre, Evans, Andrew, Finelli, Antonio, Moffat, Jason, Jewett, Michael, and Ailles, Laurie

Subjects
3. Good health
Abstract

Copy number profiles of primary cultures and matched primary tumors and adjacent normal tissues. Figure S2. Morphology of VHLmut vs. VHLwt cultures. Figure S3. VHLwt cells do not express distal tubule markers. Figure S4. Xenografts derived from RCC#243mut and RCC#407mut cultures. Figure S5. Hierarchical clustering heatmap of Pearson correlation coefficients between matched VHLmut cells, VHLwt cells and primary tumor tissues. Figure S6. Functional annotation of 211 VHLmut-associated genes (red) and 382 VHLwt-associated genes. Figure S7. Enrichment map of tumor tissue vs. VHLmut culture gene expression profiles. (PPTX 10688 kb)

20. Additional file 10: Figure S1. of Efficient generation of patient-matched malignant and normal primary cell cultures from clear cell renal cell carcinoma patients: clinically relevant models for research and personalized medicine

Author

Nazleen Lobo, Gedye, Craig, Apostoli, Anthony, Brown, Kevin, Paterson, Joshua, Stickle, Natalie, Robinette, Michael, Fleshner, Neil, Hamilton, Robert, Girish Kulkarni, Zlotta, Alexandre, Evans, Andrew, Finelli, Antonio, Moffat, Jason, Jewett, Michael, and Ailles, Laurie

Subjects
3. Good health
Abstract

Copy number profiles of primary cultures and matched primary tumors and adjacent normal tissues. Figure S2. Morphology of VHLmut vs. VHLwt cultures. Figure S3. VHLwt cells do not express distal tubule markers. Figure S4. Xenografts derived from RCC#243mut and RCC#407mut cultures. Figure S5. Hierarchical clustering heatmap of Pearson correlation coefficients between matched VHLmut cells, VHLwt cells and primary tumor tissues. Figure S6. Functional annotation of 211 VHLmut-associated genes (red) and 382 VHLwt-associated genes. Figure S7. Enrichment map of tumor tissue vs. VHLmut culture gene expression profiles. (PPTX 10688 kb)

21. High Throughput Flow Cytometry for Cell Surface Profiling.

Author

Paterson J and Ailles LE

Subjects
Biomarkers, Data Interpretation, Statistical, Fluorescent Antibody Technique, Humans, Immunophenotyping, Flow Cytometry methods, High-Throughput Screening Assays, Membrane Proteins metabolism
Abstract

Cell surface proteins are widely studied in the search for new biomarkers and therapeutic targets, but there is little information available about the surfaceome of individual cells, and this is difficult to obtain experimentally, especially in heterogeneous samples. Flow cytometry is a simple and robust tool for assessing cell surface protein expression on a single-cell level in a wide variety of cell types. However, due to the cost and relative scarcity of reagents, it is typically limited to interrogating known markers, screening small curated subsets of likely candidates, or validating targets obtained via other high throughput methods such as transcriptional profiling. Given recent advances in our understanding of stem cells, tumor-initiating cells, and other rare populations in seemingly homogenous samples, and the relative lack of correlation between the transcriptome and the surfaceome, large-scale flow cytometry screens have become an appealing option. A relatively exhaustive microarray-like flow cytometry screening platform can reveal unexpected markers or sub-populations that are not readily detected by other methods. The single-cell resolution, reliability, and simplicity of flow cytometry and the additional benefit of sub-population/heterogeneity discrimination with the addition of functional and/or phenotypic co-stains allow for the rapid generation of very reliable data from a wide variety of samples at a low cost per sample. These larger datasets can be used for more elaborate bioinformatics, such as hierarchical clustering. Here we describe a method for high throughput cell surface profiling using conventional single or multicolor flow cytometry, which can be adapted to an antibody panel of any size.

Published
2018
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results