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He specializes in the molecular characterization of solid tumors, with a specific focus on pancreatic and colorectal cancer, and runs a joint laboratory with Dr. Brian Wolpin focused on tissue-based analysis of human pancreatic cancer specimens.
The Wolpin-Nowak lab employs multiplexed immunofluorescence, digital image analysis and machine learning to study the microenvironment of pancreatic cancer using human tumor tissue specimens. The combination of these approaches allows us to study the components of the pancreatic cancer microenvironment at single cell resolution in their native, spatially-resolved configuration. This methodology provides rich, quantitative data that enable analyses not possible with traditional qualitative pathology approaches. We have developed assays to analyze both protein and RNA expression across a wide variety of cell types in pancreatic cancer. In particular, we have focused on immune cell infiltrates, tumor cell-specific markers indicative of different states of tumor differentiation, measuring cell cycle state, and analyzing stromal fibroblast composition.
A key advantage of our tissue-based assays is that they can be run at a large scale across hundreds of specimens. This allows us to generate uniform data sets across large cohorts of primary resected pancreatic cancer, neoadjuvant-treated pancreatic cancer and tissue specimens from patients who present with metastatic disease. The ability to customize targets of interest also makes our approach amenable to studying patient specimens collected from clinical trials and allows for biomarker discovery and validation using assays that can be implemented for routine clinical care.
The Wolpin-Nowak lab employs multiplexed immunofluorescence, digital image analysis and machine learning to study the microenvironment of pancreatic cancer using human tumor tissue specimens. The combination of these approaches allows us to study the components of the pancreatic cancer microenvironment at single cell resolution in their native, spatially-resolved configuration. This methodology provides rich, quantitative data that enable analyses not possible with traditional qualitative pathology approaches. We have developed assays to analyze both protein and RNA expression across a wide variety of cell types in pancreatic cancer. In particular, we have focused on immune cell infiltrates, tumor cell-specific markers indicative of different states of tumor differentiation, measuring cell cycle state, and analyzing stromal fibroblast composition.
A key advantage of our tissue-based assays is that they can be run at a large scale across hundreds of specimens. This allows us to generate uniform data sets across large cohorts of primary resected pancreatic cancer, neoadjuvant-treated pancreatic cancer and tissue specimens from patients who present with metastatic disease. The ability to customize targets of interest also makes our approach amenable to studying patient specimens collected from clinical trials and allows for biomarker discovery and validation using assays that can be implemented for routine clinical care.
Research Interests
Papers共 283 篇Author StatisticsCo-AuthorSimilar Experts
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crossref(2024)
crossref(2024)
Larissa V Furtado,Carlo Bifulco, Daniel Dolderer,Susan J Hsiao,Benjamin R Kipp,Neal I Lindeman,Lauren L Ritterhouse, Robyn L Temple-Smolkin,Ahmet Zehir,Jonathan A Nowak
The Journal of molecular diagnostics : JMD (2024)
MODERN PATHOLOGYno. 4 (2024): 100450-100450
Cancer Researchno. 6_Supplement (2024): 3467-3467
Annals of surgery (2024)
crossref(2024)
Laleh Abbassi, Jullien Dilly,Annan Yang,Giselle Uribe, Branden Parent,Connor Hennessey,Kevin Kapner,Alexander Jordan, Shatavisha Dasgupta, Micaela Morgado, Taimour Baslan,Li Qiang,
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