Project description:The mouse stomach secrets digestive enzymes and stomach acid, and plays a key role in food digestion. While there are a few studies on the morphological changes during the stomach development, a comprehensive, systematic omics study is still missing. Here, we present a comprehensive, temporal proteome atlas of the mouse stomach by sequential mapping stomach tissues at multiple developmental stages. The quantitative analysis of 12,108 gene products provides coverage sufficient to observe the protein dynamics of the developing stomach. The whole process of stomach development can be roughly divided into three phases according to changes of RNAs or proteins. The molecular functions of protein modules pinpoint the gain of stomach functions at the longitudinal scale. Dissection of 8 key signaling pathways identified master regulators in governing stomach development and gastric cancer. Remarkably, many proteins differentially expressed in stomach development are also significantly overexpressed in diffuse-type gastric cancer, suggesting a close correlation between development and tumorigenesis. The transcriptome of the developing stomach reveals functionally important isoforms relevant to development. When combined with the proteomes, several functionally unannotated novel splicing junction transcripts were identified and validated at the peptide level. Overall, our study provides a valuable resource to understand stomach development and its connection to gastric cancer.
Project description:We collected 3 replicates of whole stomach organs at 15 time points that covered embryonic days (E12.5, E13.5, E14.5, E15.5, E16.5, E17.5, E18.5), postnatal days (D1, D3, D5), and postnatal weeks (W1, W2, W3, W6, W8). The sampling time window covered from the earliest day that stomach sampling is anatomically feasible to the latest weeks when stomachs are close to mature. We applied a fast-seq proteomics workflow, a label-free quantitative proteomics approach in combination with small scale reverse phase pre-fractionation strategy.
Project description:Liver organogenesis and development is composed of a series of complex, well-orchestrated events. Identification of key factors and pathways governing liver development will help understand this process and may also provide insights for other physiological and pathological processes including cancer. For this purpose, we conducted multi-dimensional omics measurements including profiling of protein, mRNA, and transcription factor (TF) DNA binding activity from mouse liver tissues collected at embryonic day E12.5 to postnatal week W8, encompassing the major developmental stages to provide a molecular and integrative panoramic view of mouse liver development. These datasets revealed dynamic changes of core liver functions as well as canonical signaling pathways governing development at both mRNA and protein levels, and identified novel RNA splicing variants that are confirmed at the peptide level. The TF DNA binding activity dataset provided the first glimpse of liver development from four waves of TF activations and major TFs that may be responsible to drive the transcriptional program to govern liver development. A comparison between mouse liver development and human hepatocellular carcinoma (HCC) proteomic profiles revealed that more aggressive tumors are characterized with the activation of early embryonic development pathways, whereas less aggressive ones maintain liver-function related pathways that are elevated in the mature liver. This work provided a rich resource for liver development research community for future in-depth functional characterization.
Project description:Tumors show substantial amounts of cellular heterogeneity by forming complex ecosystems of malignant and non-malignant cells. Herein, we present a comprehensive multi-omic cell atlas of matched single-cell transcriptome and single-cell chromatin accessibility profiles spanning over 150,000 cells from 11 human gynecologic tumors. By jointly analyzing these transcriptomic and chromatin accessibility profiles at single-cell resolution, we identify 115,734 total peak-to-gene links representing putative regulatory interactions. We find some of these regulatory interactions explain cell type-specific expression patterns of hallmark cancer pathway regulators such as the mTOR activator RHEB. We also leverage these data to infer differential transcription factor activity, such as ZEB1, across cell type-specific enhancers between two different fractions of the same patient tumor. Our work highlights the importance of precision medicine in the treatment of gynecologic cancers and we show that this resource will deepen our understanding of non-coding genomic regions in the context of tumor biology.