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Principal Investigator: Michelle C Barbeau
Organization: UNIVERSITY OF VIRGINIA
Fiscal Year: 2024
Award: $40,415
Funding agency: National Cancer Institute
PROJECT SUMMARY
The epithelial-mesenchymal transition (EMT) is a developmental process that is aberrantly reactivated in
pancreatic ductal adenocarcinoma (PDAC) to promote disease progression and chemoresistance. PDAC tumors
and cell lines typically contain a heterogeneous mixture of transformed cells displaying epithelial or mesenchymal
characteristics, complicating efforts to understand the regulatory mechanisms that govern this important
phenotypic switching. The observation that EMT can be initiated by a variety of different growth factors, low
oxygen tension, and matrix-mediated signaling strongly suggests that multiple signaling pathways cooperate to
drive robust EMT and raises the possibility that EMT heterogeneity is explained by the ability of only some cells
to activate robustly the pathways that cooperate to drive EMT. Another potential, but not necessarily mutually
exclusive, explanation for phenotypic heterogeneity is that some PDAC cells are primed to undergo EMT due to
transcriptional differences that enable utilization of specific transcription factors or signaling pathways. Based on
our preliminary data, we hypothesize that certain PDAC cells are transcriptionally primed to undergo EMT
and that EMT heterogeneity further depends upon cell-to-cell variations in kinase-regulated signaling
processes within cell populations. The objective of the work proposed here is to test these hypotheses through
the development of quantitative systems biology methods to study the basis of EMT heterogeneity regulation via
transcriptional and kinase-mediated signaling processes. In Aim 1, an iterative immunofluorescence imaging
pipeline will be developed to gather multiplexed signaling data on populations of PDAC cells treated with different
EMT agonists. Based on preliminary studies, we propose to measure markers for seven distinct signaling
pathway nodes and two EMT markers to create a dataset with nine features measured for thousands of cells for
each experimental condition. We will then apply a mutual information data science approach for the quantitative
identification of the signaling pathways that cooperate to drive robust EMT. Model predictions will be tested using
small molecule inhibitors and siRNA-mediated knockdowns. In Aim 2, we will use genetic barcoding for the
transcriptomic profiling of EMT-resistant or -compliant lineages within cell populations. Single-cell RNA
sequencing data from cells before and after EMT induction will be analyzed to identify transcriptional states that
preferentially enable PDAC cells to undergo the mesenchymal transition. The relevance of candidate transcripts
for explaining EMT priming will be tested through knockdown experiments. The methods developed in this work
will be broadly applicable to the study of EMT in other cancer settings and to the study of alternative types of
phenotypic switching. Moreover, the specific results will have implications for the design of novel combination
therapies for PDAC based on the objective of suppressing EMT to promote responsiveness to chemotherapy.
Terms: <Agonist><Antibodies><Bar Codes><Basal Transcription Factor><Basal transcription factor genes><Biochemical><Cancers><Candidate Disease Gene><Candidate Gene><Carcinoma><Cell Body><Cell Communication and Signaling><Cell Line><Cell Lineage><Cell Signaling><CellLine><Cells><Characteristics><Chemoresistance><Combined Modality Therapy><Computer Models><Computerized Models><Computing Methodologies><Data><Data Science><Data Set><Development><Developmental Process><Disease Progression><Epithelial cancer><Epithelium><Exhibits><Expression Signature><Gene Expression Profile><Gene Transcription><General Transcription Factor Gene><General Transcription Factors><Genetic><Genetic Transcription><Growth Agents><Growth Factor><Growth Substances><Heterogeneity><Human><Hypoxia><Hypoxic><Image><Immunofluorescence><Immunofluorescence Immunologic><Indirect Immunofluorescence><Individual><Infection><Information Theory><Intracellular Communication and Signaling><Kinases><Lead><Libraries><Maintenance><Malignant Epithelial Neoplasms><Malignant Epithelial Tumors><Malignant Neoplasms><Malignant Tumor><Measures><Mediating><Mesenchymal><Metastasis><Metastasize><Metastatic Lesion><Metastatic Mass><Metastatic Neoplasm><Metastatic Tumor><Methods><Modeling><Modern Man><Molecular><Multimodal Therapy><Multimodal Treatment><Neoplasm Metastasis><O element><O2 element><Oxygen><Oxygen Deficiency><PDAC cancer cell><PDAC cell><Pancreas Ductal Adenocarcinoma><Pancreatic Ductal Adenocarcinoma><Pathway interactions><Pb element><Phenotype><Phosphoproteins><Phosphotransferase Gene><Phosphotransferases><Population><Process><Proteins Growth Factors><Protocol><Protocols documentation><RNA Expression><RNA Seq><RNA sequencing><RNAseq><Regulation><Resistance><Secondary Neoplasm><Secondary Tumor><Short interfering RNA><Signal Pathway><Signal Transduction><Signal Transduction Systems><Signaling><Small Interfering RNA><Sorting><Strains Cell Lines><Systems Biology><Testing><Transcript><Transcription><Transcription Factor Proto-Oncogene><Transcription factor genes><Transphosphorylases><Treatment Factor><Uncertainty><Variant><Variation><Work><Wound Repair><barcode><biological signal transduction><cancer metastasis><cell population study><cell transformation><chemoresistant><chemotherapy><chemotherapy resistance><chemotherapy resistant><combination therapy><combined modality treatment><combined treatment><computational methodology><computational methods><computational modeling><computational models><computer based method><computer based models><computer based prediction><computer methods><computerized modeling><computing method><cultured cell line><cytokine><design><designing><developmental><differential expression><differentially expressed><doubt><epithelial carcinoma><epithelial to mesenchymal transition><experiment><experimental research><experimental study><experiments><fluorescence imaging><fluorescent imaging><gene expression pattern><gene expression signature><heavy metal Pb><heavy metal lead><human imaging><imaging><information model><insight><interest><knock-down><knockdown><malignancy><multi-modal therapy><multi-modal treatment><neoplasm/cancer><novel><overexpress><overexpression><pancreatic ductal adenocarcinoma cell><pathway><predictive modeling><prevent><preventing><programs><resistant><response><scRNA-seq><siRNA><single cell RNA-seq><single cell RNAseq><single cell analysis><single cell expression profiling><single cell transcriptomic profiling><single-cell RNA sequencing><small molecular inhibitor><small molecule inhibitor><transcription factor><transcriptional differences><transcriptional profile><transcriptional signature><transcriptome profiling><transcriptome sequencing><transcriptomic profiling><transcriptomic sequencing><transformed cells><tumor><tumor cell metastasis><wound healing><wound recovery><wound resolution>