Tumor cells express and maintain HMGB1 in the reduced isoform to enhance CXCR4-mediated migration.

During inflammation and tissue regeneration, the alarmin High Mobility Group Box 1 (HMGB1), in its reduced isoform, enhances the activity of the chemokine CXCL12, forming a heterocomplex that acts via the chemokine receptor CXCR4. Despite the established roles of both HMGB1 and CXCL12 in tumor progression and metastatic spread to distal sites, the role of the CXCL12/HMGB1 heterocomplex in cancer has never been investigated. By employing a newly established mass spectrometry protocol that allows an unambiguous distinction between reduced (red-HMGB1) and oxidized (ox-HMGB1) HMGB1 isoforms in cell lysates, we demonstrate that human epithelial cells derived from breast (MCF-7 and MDA-MB-231) and prostate (PC-3) cancer predominantly express red-HMGB1, while primary CD3+ T lymphocytes from peripheral blood express both HMGB1 isoforms. All these cancer cells release HMGB1 in the extracellular microenvironment together with varying concentrations of thioredoxin and thioredoxin reductase. The CXCL12/HMGB1 heterocomplex enhances, via CXCR4, the directional migration and invasiveness of cancer cells characterized by high metastatic potential that possess a fully active thioredoxin system, contributing to maintain red-HMGB1. On the contrary, cancer cells with low metastatic potential, lack thioredoxin reductase, promptly uptake CXCL12 and fail to respond to the heterocomplex. Our study demonstrates that the responsiveness of cancer cells to the CXCL12/HMGB1 heterocomplex, resulting in enhanced cell migration and invasiveness, depends on the maintenance of HMGB1 in its reduced isoform, and suggests disruption of the heterocomplex as a potential therapeutic target to inhibit invasion and metastatic spread in cancer therapies.

The chemokine landscape: one system multiple shades.

Leukocyte trafficking is mainly governed by chemokines, chemotactic cytokines, which can be concomitantly produced in tissues during homeostatic conditions or inflammation. After the discovery and characterization of the individual chemokines, we and others have shown that they present additional properties. The first discoveries demonstrated that some chemokines act as natural antagonists on chemokine receptors, and prevent infiltration of leukocyte subsets in tissues. Later on it was shown that they can exert a repulsive effect on selective cell types, or synergize with other chemokines and inflammatory mediators to enhance chemokine receptors activities. The relevance of the fine-tuning modulation has been demonstrated in vivo in a multitude of processes, spanning from chronic inflammation to tissue regeneration, while its role in the tumor microenvironment needs further investigation. Moreover, naturally occurring autoantibodies targeting chemokines were found in tumors and autoimmune diseases. More recently in SARS-CoV-2 infection, the presence of several autoantibodies neutralizing chemokine activities distinguished disease severity, and they were shown to be beneficial, protecting from long-term sequelae. Here, we review the additional properties of chemokines that influence cell recruitment and activities. We believe these features need to be taken into account when designing novel therapeutic strategies targeting immunological disorders.

Tracking unlabeled cancer cells imaged with low resolution in wide migration chambers via U-NET class-1 probability (pseudofluorescence).

Cell migration is a pivotal biological process, whose dysregulation is found in many diseases including inflammation and cancer. Advances in microscopy technologies allow now to study cell migration in vitro, within engineered microenvironments that resemble in vivo conditions. However, to capture an entire 3D migration chamber for extended periods of time and with high temporal resolution, images are generally acquired with low resolution, which poses a challenge for data analysis. Indeed, cell detection and tracking are hampered due to the large pixel size (i.e., cell diameter down to 2 pixels), the possible low signal-to-noise ratio, and distortions in the cell shape due to changes in the z-axis position. Although fluorescent staining can be used to facilitate cell detection, it may alter cell behavior and it may suffer from fluorescence loss over time (photobleaching).Here we describe a protocol that employs an established deep learning method (U-NET), to specifically convert transmitted light (TL) signal from unlabeled cells imaged with low resolution to a fluorescent-like signal (class 1 probability). We demonstrate its application to study cancer cell migration, obtaining a significant improvement in tracking accuracy, while not suffering from photobleaching. This is reflected in the possibility of tracking cells for three-fold longer periods of time. To facilitate the application of the protocol we provide WID-U, an open-source plugin for FIJI and Imaris imaging software, the training dataset used in this paper, and the code to train the network for custom experimental settings.