Dataset Information

Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice.

ABSTRACT: Human pancreatic islets engrafted into immunodeficient mice serve as an important model for in vivo human diabetes studies. Following engraftment, islet function can be monitored in vivo by measuring circulating glucose and human insulin; however, it will be important to recover viable cells for more complex graft analyses. Moreover, RNA analyses of dissected grafts have not distinguished which hormone-specific cell types contribute to gene expression. We developed a method for recovering live cells suitable for fluorescence-activated cell sorting from human islets engrafted in mice. Although yields of recovered islet cells were relatively low, the ratios of bulk-sorted ?, ?, and ? cells and their respective hormone-specific RNA-Seq transcriptomes are comparable pretransplant and posttransplant, suggesting that the cellular characteristics of islet grafts posttransplant closely mirror the original donor islets. Single-cell RNA-Seq transcriptome analysis confirms the presence of appropriate ?, ?, and ? cell subsets. In addition, ex vivo perifusion of recovered human islet grafts demonstrated glucose-stimulated insulin secretion. Viable cells suitable for patch-clamp analysis were recovered from transplanted human embryonic stem cell-derived ? cells. Together, our functional and hormone-specific transcriptome analyses document the broad applicability of this system for longitudinal examination of human islet cells undergoing developmental/metabolic/pharmacogenetic manipulation in vivo and may facilitate the discovery of treatments for diabetes.

SUBMITTER: Redick SD

PROVIDER: S-EPMC6972551 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice.

Redick Sambra D SD Leehy Linda L Rittenhouse Ann R AR Blodgett David M DM Derr Alan G AG Kucukural Alper A Garber Manuel G MG Shultz Leonard D LD Greiner Dale L DL Wang Jennifer P JP Harlan David M DM Bortell Rita R Jurczyk Agata A

FASEB journal : official publication of the Federation of American Societies for Experimental Biology 20191210 1

Human pancreatic islets engrafted into immunodeficient mice serve as an important model for in vivo human diabetes studies. Following engraftment, islet function can be monitored in vivo by measuring circulating glucose and human insulin; however, it will be important to recover viable cells for more complex graft analyses. Moreover, RNA analyses of dissected grafts have not distinguished which hormone-specific cell types contribute to gene expression. We developed a method for recovering live c ...[more]

PMID: 31914605

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Project description:BACKGROUND: Engraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient-derived xenograft (PDX) models is a promising platform for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine tumor environment on the gene expression of the engrafted human tumoral cells. METHODS: We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data of 18 PDX models, 53 primary tumors and 41 cell lines from PDAC. The results obtained in the PDAC system were further compared with public available microarray data from 42 PDX models, 108 primary tumors and 32 cell lines from hepatocellular carcinoma (HCC). We developed a robust analysis protocol to explore the gene expression space. In addition, we completed the analysis with a functional characterization of PDX models, including if changes were caused by murine environment or by serial passing. RESULTS: Our results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable from each other based on their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models can be separated into two different groups that share some partial similarity with their corresponding original primary tumors. Our results point to the lack of human stromal involvement in PDXs as a major factor contributing to their differences from the original primary tumors. The main functional differences between pancreatic PDX models and human PDAC are the lower expression of genes involved in pathways related to extracellular matrix and hemostasis and the up- regulation of cell cycle genes. Importantly, most of these differences are detected in the first passages after the tumor engraftment. CONCLUSIONS: Our results suggest that PDX models of PDAC and HCC retain, to some extent, a gene expression memory of the original primary tumors, while this pattern is not detected in conventional cancer cell lines. Expression changes in PDXs are mainly related to pathways reflecting the lack of human infiltrating cells and the adaptation to a new environment. We also provide evidence of the stability of gene expression patterns over subsequent passages, indicating early phases of the adaptation process.

Project description:The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet’s sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment. Graphical Abstract Highlights • microPOTS enables deep proteome imaging of pancreatic islets and their microenvironment.• We identified and quantified over 6000 proteins from ∼50,000 μm2 tissue area samples.• Differential expression and network analyses identified pathways uniquely active in islets.• Rank-based statistics enable the characterization of gradients across individual tissue images. In Brief We applied our Microdroplet Processing in One pot for Trace Samples (microPOTS) TMT platform to study the pancreatic islet microenvironment in the human pancreas. We were able to quantify over 6000 proteins from seven different regions within the same patient. Here we describe enhancements to existing computational approaches to extract functional hypotheses from this first-of-its-kind dataset. In addition to recapitulating known functions of the islet, we can identify specific immune and RNA processing activities with spatial heterogeneity in expression.

Project description:Engraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient derived xenograft (PDX) models is a promising platform to for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine environment on the gene expression of the engrafted human tumoral cells. We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data from PDAC and hepatocellular carcinoma (HCC). Our results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable one from the other based in their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models are clearly different and more similar to their original tumor than to PDX models from the other tumor type. Interestingly, the main differences between pancreatic PDX models and human PDAC is the expression of genes involved in pathways related with extracellular matrix interactions and cell cycle regulation likely reflecting the adaptations of the tumors to the new environment. Furthermore, most of these differences are detected in the first passages after the tumor engraftment, indicating early phases of the adaptation process. In conclusion, different from conventional cancer cell lines, PDX models of PDAC retain similar gene expression profiles of PDAC. Expression changes are mainly related to genes involved in stromal pathways likely reflecting the adaptation to new environments. We also provide evidence of the stability of gene expression patterns over subsequent passages. We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published in GEO microarray data. We used PDX models, primary tumors and cell lines from PDAC and hepatocellular carcinoma. All these public data were re-process in order to compare with our 35 samples

Dataset Information

Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice.

Publications

Recovery of viable endocrine-specific cells and transcriptomes from human pancreatic islet-engrafted mice.

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