PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data.

Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research.

Three-dimensional molecular architecture of mouse organogenesis.

Mammalian embryos exhibit sophisticated cellular patterning that is intricately orchestrated at both molecular and cellular level. It has recently become apparent that cells within the animal body display significant heterogeneity, both in terms of their cellular properties and spatial distributions. However, current spatial transcriptomic profiling either lacks three-dimensional representation or is limited in its ability to capture the complexity of embryonic tissues and organs. Here, we present a spatial transcriptomic atlas of all major organs at embryonic day 13.5 in the mouse embryo, and provide a three-dimensional rendering of molecular regulation for embryonic patterning with stacked sections. By integrating the spatial atlas with corresponding single-cell transcriptomic data, we offer a detailed molecular annotation of the dynamic nature of organ development, spatial cellular interactions, embryonic axes, and divergence of cell fates that underlie mammalian development, which would pave the way for precise organ engineering and stem cell-based regenerative medicine.

Precision length determination and in silico simulation in PCR of microsatellite repeat sequences.

Despite being commonplace, polymerase chain reactions (PCRs) still contain many unknown aspects. One example is microsatellite PCR, which is now widely used for various purposes from ecology to cancer medicine. Since this category of repetitive DNA sequences induces polymerase slippage not only in vivo but also in vitro, microsatellite PCR products comprise a complex combination of DNA fragments with various lengths and have, therefore, been empirically interpreted. The primary obstacle for understanding microsatellite PCR was the intrinsic inaccuracy in sizing of DNA fragments in capillary electrophoresis (CE), which, however, has been overcome by elucidating intrinsic sizing errors in each fragment length range. Secondly, the slippage properties of the thermostable polymerases were first clarified in detail using primer extension assays. Furthermore, using the obtained slippage parameters and our original program, we have first reconstructed microsatellite PCR in silico. The entire processes of complex microsatellite PCR have, thus, been more clearly understood.