A well known, epidemiologically reproducible risk factor for human carcinomas is the long-term consumption of "red meat" of mammalian origin. Although multiple theories have attempted to explain this human-specific association, none have been conclusively proven. We used an improved method to survey common foods for free and glycosidically bound forms of the nonhuman sialic acid N-glycolylneuraminic acid (Neu5Gc), showing that it is highly and selectively enriched in red meat. The bound form of Neu5Gc is bioavailable, undergoing metabolic incorporation into human tissues, despite being a foreign antigen. Interactions of this antigen with circulating anti-Neu5Gc antibodies could potentially incite inflammation. Indeed, when human-like Neu5Gc-deficient mice were fed bioavailable Neu5Gc and challenged with anti-Neu5Gc antibodies, they developed evidence of systemic inflammation. Such mice are already prone to develop occasional tumors of the liver, an organ that can incorporate dietary Neu5Gc. Neu5Gc-deficient mice immunized against Neu5Gc and fed bioavailable Neu5Gc developed a much higher incidence of hepatocellular carcinomas, with evidence of Neu5Gc accumulation. Taken together, our data provide an unusual mechanistic explanation for the epidemiological association between red meat consumption and carcinoma risk. This mechanism might also contribute to other chronic inflammatory processes epidemiologically associated with red meat consumption.

We have profiled, for the first time, an evolving human metastatic microenvironment, measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, ECM organization and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer (HGSOC) metastases that ranged from minimal to extensive disease, we show how non-malignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, whilst also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and twelve other primary solid cancers, suggesting that there may be a common matrix response to human cancer.

During malignant transformation, glycosylation is heavily altered compared with healthy tissue due to differential expression of glycosyltransferases, glycosidases and monosaccharide transporters within the cancer microenvironment. One key change of malignant tissue glycosylation is the alteration of sialic acid processing that leads to a general upregulation of sialylated glycans (hypersialylation) on cell surfaces and an increased introduction of the non-human sialic acid N-glycolyl-neuraminic acid (Neu5Gc) instead of N-acetyl-neuraminic acid into cell surface glycans. These changes have been shown to be the result of altered sialyltransferase and sialidase expression. Functionally, cancer-associated hypersialylation appears to directly impact tumor cell interaction with the microenvironment, in particular the modulation of sialic acid-binding lectins on immune cells. Moreover, Neu5Gc expression in human tissues enhances inflammation due to an anti-Neu5Gc immune response, which can potentially influence inflammation-induced cancer and cancer-associated inflammation. In this review, we summarize the changes of sialic acid biology within the malignant microenvironment and the resulting effect on cancer immunity.

Certain pathogenic bacteria are known to modulate the innate immune response by decorating themselves with sialic acids, which can engage the myelomonocytic lineage inhibitory receptor Siglec-9, thereby evading immunosurveillance. We hypothesized that the well-known up-regulation of sialoglycoconjugates by tumors might similarly modulate interactions with innate immune cells. Supporting this hypothesis, Siglec-9-expressing myelomonocytic cells found in human tumor samples were accompanied by a strong up-regulation of Siglec-9 ligands. Blockade of Siglec-9 enhanced neutrophil activity against tumor cells in vitro. To investigate the function of inhibitory myelomonocytic Siglecs in vivo we studied mouse Siglec-E, the murine functional equivalent of Siglec-9. Siglec-E-deficient mice showed increased in vivo killing of tumor cells, and this effect was reversed by transgenic Siglec-9 expression in myelomonocytic cells. Siglec-Edeficient mice also showed enhanced immunosurveillance of autologous tumors. However, once tumors were established, they grew faster in Siglec-E-deficient mice. In keeping with this, Siglec-E-deficient macrophages showed a propensity toward a tumor-promoting M2 polarization, indicating a secondary role of CD33-related Siglecs in limiting cancer-promoting inflammation and tumor growth. Thus, we define a previously unidentified impact of inhibitory myelomonocytic Siglecs in cancer biology, with distinct roles that reflect the dual function of myelomonocytic cells in cancer progression. In keeping with this, a human polymorphism that reduced Siglec-9 binding to carcinomas was associated with improved early survival in nonsmall-cell lung cancer patients, which suggests that Siglec-9 might be therapeutically targeted within the right time frame and stage of disease.hypersialylation | tumor-associated macrophages | tumor-associated neutrophils | immune evasion | tumor-associated inflammation

The extracellular matrix (ECM) is a complex meshwork of insoluble fibrillar proteins and signaling factors interacting together to provide architectural and instructional cues to the surrounding cells. Alterations in ECM organization or composition and excessive ECM deposition have been observed in diseases such as fibrosis, cardiovascular diseases, and cancer. We provide here optimized protocols to solubilize ECM proteins from normal or tumor tissues, digest the proteins into peptides, analyze ECM peptides by mass spectrometry, and interpret the mass spectrometric data. In addition, we present here two novel R-script-based web tools allowing rapid annotation and relative quantification of ECM proteins, peptides, and intensity/abundance in mass spectrometric data output files. We illustrate this protocol with ECMs obtained from two pairs of tissues, which differ in ECM content and cellularity: triple-negative breast cancer and adjacent mammary tissue, and omental metastasis from high-grade serous ovarian cancer and normal omentum. The complete proteomics data set generated in this study has been deposited to the public repository ProteomeXchange with the data set identifier: PXD005554.