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Background Due to continued advances in sequencing technology, the limitation in understanding biological systems through an “-omics” lens is no longer the generation of data, but the ability to analyze it. Importantly, much of this rich -omics data is publicly available waiting to be further investigated. Although many code-based pipelines exist, there is a lack of user-friendly and accessible applications that enable rapid analysis or visualization of data. Results GECO (Gene Expression Clustering Optimization; http://www.theGECOapp.com) is a minimalistic GUI app that utilizes non-linear reduction techniques to rapidly visualize expression trends in many types of biological data matrices (such as bulk RNA-seq or proteomics). The required input is a data matrix with samples and any type of expression level of genes/protein/other with a unique ID. The output is an interactive t-SNE or UMAP analysis that clusters genes (or proteins/other unique IDs) based on their expression patterns across the multiple samples enabling visualization of expression trends. Customizable settings for dimensionality reduction, data normalization, along with visualization parameters including coloring and filters, ensure adaptability to a variety of user uploaded data. Conclusion This local and cloud-hosted web browser app enables investigation of any -omic data matrix in a rapid and code-independent manner. With the continued growth of available -omic data, the ability to quickly evaluate a dataset, including specific genes of interest, is more important than ever. GECO is intended to supplement traditional statistical analysis methods and is particularly useful when visualizing clusters of genes with similar trajectories across many samples (ex: multiple cell types, time course, dose response). Users will be empowered to investigate -omic data with a new lens of visualization and analysis that has the potential to uncover genes of interest, cohorts of co-regulated genes programs, and previously undetected patterns of expression.

BackgroundThere is increasing evidence that oncogenic Wnt signaling directs metabolic reprogramming of cancer cells to favor aerobic glycolysis or Warburg metabolism. In colon cancer, this reprogramming is due to direct regulation of pyruvate dehydrogenase kinase 1 (PDK1) gene transcription. Additional metabolism genes are sensitive to Wnt signaling and exhibit correlative expression with PDK1. Whether these genes are also regulated at the transcriptional level, and therefore a part of a core metabolic gene program targeted by oncogenic WNT signaling, is not known.ResultsHere, we identify monocarboxylate transporter 1 (MCT-1; encoded by SLC16A1) as a direct target gene supporting Wnt-driven Warburg metabolism. We identify and validate Wnt response elements (WREs) in the proximal SLC16A1 promoter and show that they mediate sensitivity to Wnt inhibition via dominant-negative LEF-1 (dnLEF-1) expression and the small molecule Wnt inhibitor XAV939. We also show that WREs function in an independent and additive manner with c-Myc, the only other known oncogenic regulator of SLC16A1 transcription. MCT-1 can export lactate, the byproduct of Warburg metabolism, and it is the essential transporter of pyruvate as well as a glycolysis-targeting cancer drug, 3-bromopyruvate (3-BP). Using sulforhodamine B (SRB) assays to follow cell proliferation, we tested a panel of colon cancer cell lines for sensitivity to 3-BP. We observe that all cell lines are highly sensitive and that reduction of Wnt signaling by XAV939 treatment does not synergize with 3-BP, but instead is protective and promotes rapid recovery.ConclusionsWe conclude that MCT-1 is part of a core Wnt signaling gene program for glycolysis in colon cancer and that modulation of this program could play an important role in shaping sensitivity to drugs that target cancer metabolism.Electronic supplementary materialThe online version of this article (doi:10.1186/s40170-016-0159-3) contains supplementary material, which is available to authorized users.

This article is part of a themed section on WNT Signalling: Mechanisms and Therapeutic Opportunities. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.24/issuetoc.

Intestinal stem cells are non-quiescent, dividing epithelial cells that rapidly differentiate into progenitor cells of the absorptive and secretory cell lineages. The kinetics of this process is rapid such that the epithelium is replaced weekly. To determine how the transcriptome and proteome keep pace with rapid differentiation, we developed a new cell sorting method to purify mouse colon epithelial cells. Here we show that alternative mRNA splicing and polyadenylation dominate changes in the transcriptome as stem cells differentiate into progenitors. In contrast, as progenitors differentiate into mature cell types, changes in mRNA levels dominate the transcriptome. RNA processing targets regulators of cell cycle, RNA, cell adhesion, SUMOylation, and Wnt and Notch signaling. Additionally, global proteome profiling detected >2,800 proteins and revealed RNA:protein patterns of abundance and correlation. Paired together, these data highlight new potentials for autocrine and feedback regulation and provide new insights into cell state transitions in the crypt.