Project description:Identifying the cells from which cancers arise, and the paths they take towards malignancy is critical for understanding the molecular basis of tumor initiation and progression. To determine whether stem and progenitor cells can serve as cells of origin for cancer, we created a new Msi2-CreERT2 knock-in strain. When crossed to a conditional CAG-LSL-MycT58A model, Msi2-CreERT2 mice developed multiple pancreatic cancer subtypes: pancreatic ductal adenocarcinoma (PDAC), adenosquamous carcinoma of the pancreas (ASCP), acinar cell carcinoma (ACC), and rare anaplastic tumors. Combining single-cell genomics with computational analysis of developmental states and lineage trajectories, we demonstrate that oncogenic MYC preferentially triggers the transformation of the most immature subset of Msi2+ cells, leading to the rise of a common pool of pre-cancer cells with multi-lineage properties. These pre-cancer cells subsequently diverge to distinct pancreatic cancer subtypes by activation of distinct transcriptional programs and large-scale genomic changes. Importantly, the enforced expression of specific molecular signals can redirect cells toward specific subtypes. This study shows that multiple pancreatic cancer subtypes can arise from a common pool of Msi2+ cells and provides a powerful framework to understand and control the programs that shape divergent fates in pancreatic cancer.
Project description:Identifying the cells from which cancers arise, and the paths they take towards malignancy is critical for understanding the molecular basis of tumor initiation and progression. To determine whether stem and progenitor cells can serve as cells of origin for cancer, we created a new Msi2-CreERT2 knock-in strain. When crossed to a conditional CAG-LSL-MycT58A model, Msi2-CreERT2 mice developed multiple pancreatic cancer subtypes: pancreatic ductal adenocarcinoma (PDAC), adenosquamous carcinoma of the pancreas (ASCP), acinar cell carcinoma (ACC), and rare anaplastic tumors. Combining single-cell genomics with computational analysis of developmental states and lineage trajectories, we demonstrate that oncogenic MYC preferentially triggers the transformation of the most immature subset of Msi2+ cells, leading to the rise of a common pool of pre-cancer cells with multi-lineage properties. These pre-cancer cells subsequently diverge to distinct pancreatic cancer subtypes by activation of distinct transcriptional programs and large-scale genomic changes. Importantly, the enforced expression of specific molecular signals can redirect cells toward specific subtypes. This study shows that multiple pancreatic cancer subtypes can arise from a common pool of Msi2+ cells and provides a powerful framework to understand and control the programs that shape divergent fates in pancreatic cancer.
Project description:scRNA-seq analysis evaluating transcriptional heterogeneity in mouse pre-cancer and pancreas tumors in an effort to model the progression of pancreas tumors. Single cells were captured at t=0 (before tamoxifen induction), t=5 (5 weeks after tamoxifen induction) and t=12 (12 weeks after tamoxifen induction).
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in MYCWT+shCtrl, MYCWT+shTRIB3, MYCT58A+shCtrl and MYCT58A+shTRIB3 lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: MYCWT+shCtrl, MYCWT+shTRIB3, MYCT58A+shCtrl and MYCT58A+shTRIB3 cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of MYCWT+shCtrl, MYCWT+shTRIB3, MYCT58A+shCtrl and MYCT58A+shTRIB3 cells' transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
Project description:Genetically engineered mice developed spontaneous pancreas cancer (Pdx-Cre;LSL-KRASG12D;P53Mut). Mice were also engineered to develop similar spontaneous pancreas cancer without Twist or Snail (conditional gene knockout). The pancreas tumors were harvested and analysed for gene expression profiles comparisons. Total RNA was isolated from the pancreas tumors of 2 mice with wild-type Twist and Snail, from 2 mice without Twist expression in the pancreas, and from 2 mice without Snail expression in the pancreas.
