Tumor pre-conditioning of draining lymph node stroma by lactic acid

Abstract

Corresponding author, lead contactCommunication between tumors and the stroma of tumor draining lymph nodes (TDLNs) exists before metastasis arises, altering structure and function of the TDLN niche. Transcriptional profiling of fibroblastic reticular cells (FRCs), the dominant stromal population of the LN, revealed reprogramming of these cells in immune related pathways, but also in fibroblast activation and mitochondrial function. However, tumor derived factors driving the changes in FRCs remained to be identified. Taking an unbiased approach, we show that lactate, a metabolite released by cancer cells, elicits upregulation of Pdpn and Thy1 in FRCs of TDLNs, making them akin to activated fibroblasts found at the primary tumor site. Furthermore, we show that tumor-derived lactate alters mitochondrial function of FRCs of TDLNs. Thus, our results demonstrate a novel mechanism by which a tumor-derived metabolite modulates the function of fibroblasts in TDLNs.

Constructing and Analyzing Computational Models of Cell Signaling with BioModelAnalyzer

“…We have focused here on the construction of gene regulatory networks, but this approach can be applied to a wide range of biological systems. These have included such diverse systems as metabolic networks (Riedel et al., 2018) and ion flow across membranes (Shorthouse et al., 2018). This work and others like it illustrate that the methods are not tied to a specific class of models, and can be broadly applied to different problems.…”

“…Computational modeling represents a major strand of research in the life sciences. Over the past two decades, advances in modeling biological processes at the level of the cellular network have enabled novel insights into a wide range of processes including fundamental biological questions of organ development (Bonzanni et al., 2009; Hall, Piterman, Hajnal, & Fisher, 2015; Nusser‐Stein et al., 2012), blood cell fate determination (Bonzanni et al., 2013; Chuang et al., 2015; Moignard et al., 2015; Silverbush et al., 2017), and the dynamics of metabolic systems (Riedel et al., 2018) and ion channel networks (Shorthouse et al., 2018), among others. This progress has also led directly to contributions in the biomedical sciences, allowing for new discoveries with clinical relevance in diseases such as cancer.…”