A Ligand Peptide Motif Selected from a Cancer Patient Is a Receptor-Interacting Site within Human Interleukin-11

Interleukin-11 (IL-11) is a pleiotropic cytokine approved by the FDA against chemotherapy-induced thrombocytopenia. From a combinatorial selection in a cancer patient, we isolated an IL-11-like peptide mapping to domain I of the IL-11 (sequence CGRRAGGSC). Although this motif has ligand attributes, it is not within the previously characterized interacting sites. Here we design and validate in-tandem binding assays, site-directed mutagenesis and NMR spectroscopy to show (i) the peptide mimics a receptor-binding site within IL-11, (ii) the binding of CGRRAGGSC to the IL-11Rα is functionally relevant, (iii) Arg4 and Ser8 are the key residues mediating the interaction, and (iv) the IL-11-like motif induces cell proliferation through STAT3 activation. These structural and functional results uncover an as yet unrecognized receptor-binding site in human IL-11. Given that IL-11Rα has been proposed as a target in human cancer, our results provide clues for the rational design of targeted drugs

Adipocyte mesenchymal transition contributes to mammary tumor progression

Obesity is associated with increased cancer incidence and progression. However, the relationship between adiposity and cancer remains poorly understood at the mechanistic level. Here, we report that adipocytes from tumor-invasive mammary fat undergo de-differentiation to fibroblast-like precursor cells during tumor progression and integrate into the tumor microenvironment. Single-cell sequencing reveals that these de-differentiated adipocytes lose their original identities and transform into multiple cell types, including myofibroblast- and macrophage-like cells, with their characteristic features involved in immune response, inflammation, and extracellular matrix remodeling. The de-differentiated cells are metabolically distinct from tumor-associated fibroblasts but exhibit comparable effects on tumor cell proliferation. Inducing de-differentiation by Xbp1s overexpression promotes tumor progression despite lower adiposity. In contrast, promoting lipid-storage capacity in adipocytes through MitoNEET overexpression curbs tumor growth despite greater adiposity. Collectively, the metabolic interplay between tumor cells and adipocytes induces adipocyte mesenchymal transition and contributes to reconfigure the stroma into a more tumor-friendly microenvironment

Adipose tissue-derived progenitor cells and cancer

Recruitment of stem cells and partially differentiated progenitor cells is a process which accompanies and facilitates the progression of cancer. One of the factors complicating the clinical course of cancer is obesity, a progressively widespread medical condition resulting from overgrowth of white adipose tissue (WAT), commonly known as white fat. The mechanisms by which obesity influences cancer risk and progression are not completely understood. Cells of WAT secret soluble molecules (adipokines) that could stimulate tumor growth, although there is no consensus on which cell populations and which adipokines are important. Recent reports suggest that WAT-derived mesenchymal stem (stromal) cells, termed adipose stem cells (ASC), may represent a cell population linking obesity and cancer. Studies in animal models demonstrate that adipokines secreted by ASC can promote tumor growth by assisting in formation of new blood vessels, a process necessary for expansion of tumor mass. Importantly, migration of ASC from WAT to tumors has been demonstrated, indicating that the tumor microenvironment in cancer may be modulated by ASC-derived trophic factors in a paracrine rather than in an endocrine manner. Here, we review possible positive and adverse implications of progenitor cell recruitment into the diseased sites with a particular emphasis on the role in cancer progression of progenitors that are expanded in obesity

Adipose Stromal Cell Expansion and Exhaustion: Mechanisms and Consequences

Adipose tissue (AT) is comprised of a diverse number of cell types, including adipocytes, stromal cells, endothelial cells, and infiltrating leukocytes. Adipose stromal cells (ASCs) are a mixed population containing adipose progenitor cells (APCs) as well as fibro-inflammatory precursors and cells supporting the vasculature. There is growing evidence that the ability of ASCs to renew and undergo adipogenesis into new, healthy adipocytes is a hallmark of healthy fat, preventing disease-inducing adipocyte hypertrophy and the spillover of lipids into other organs, such as the liver and muscles. However, there is building evidence indicating that the ability for ASCs to self-renew is not infinite. With rates of ASC proliferation and adipogenesis tightly controlled by diet and the circadian clock, the capacity to maintain healthy AT via the generation of new, healthy adipocytes appears to be tightly regulated. Here, we review the contributions of ASCs to the maintenance of distinct adipocyte pools as well as pathogenic fibroblasts in cancer and fibrosis. We also discuss aging and diet-induced obesity as factors that might lead to ASC senescence, and the consequences for metabolic health

Bayesian mixture models for complex high dimensional count data in phage display experiments

Phage display is a biological process that is used to screen random peptide libraries for ligands that bind to a target of interest with high affinity. On the basis of a count data set from an innovative multistage phage display experiment, we propose a class of Bayesian mixture models to cluster peptide counts into three groups that exhibit different display patterns across stages. Among the three groups, the investigators are particularly interested in that with an ascending display pattern in the counts, which implies that the peptides are likely to bind to the target with strong affinity. We apply a Bayesian false discovery rate approach to identify the peptides with the strongest affinity within the group. A list of peptides is obtained, among which important ones with meaningful functions are further validated by biologists. To examine the performance of the Bayesian model, we conduct a simulation study and obtain desirable results. Copyright 2007 Royal Statistical Society.