PVRIG Expression Is an Independent Prognostic Factor and a New Potential Target for Immunotherapy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a frequent and deadly cancer in need of new treatments. Immunotherapy has shown promising results in several solid tumors. The TIGIT/DNAM-1 axis gathers targets for new immune checkpoint inhibitors (ICIs). Here, we aimed at highlighting the potential of this axis as a new therapeutic option for HCC. For this, we built a large transcriptomic database of 683 HCC samples, clinically annotated, and 319 normal liver tissues. We interrogated this database for the transcriptomic expression of each member of the TIGIT/DNAM-1 axis and tested their prognostic value for survival. We then focused on the most discriminant one for these criteria, i.e., PVRIG, and analyzed the clinical characteristics, the disease-free and overall survivals, and biological pathways associated with PVRIG High tumors. Among all members of the TIGIT/DNAM-1 axis, PVRIG expression was higher in tumors than in normal liver, was heterogeneous across tumors, and was the only member with independent prognostic value for better survival. PVRIG High tumors were characterized by a higher lymphocytic infiltrate and enriched for signatures associated with tertiary lymphoid structures and better anti-tumor immune response. These results suggest that patients with PVRIG High tumors might be good candidates for immune therapy involving ICIs, notably ICIs targeting the TIGIT/DNAM-1 axis. Further functional and clinical validation is urgently required.

Loss of primary cilia promotes inflammation and carcinogenesis

Primary cilia (PC) are important signaling hubs, and we here explored their role in colonic pathology. In the colon, PC are mostly present on fibroblasts, and exposure of mice to either chemically induced colitis-associated colon carcinogenesis (CAC) or dextran sodium sulfate (DSS)-induced acute colitis decreases PC numbers. We generated conditional knockout mice with reduced numbers of PC on colonic fibroblasts. These mice show increased susceptibility to CAC, as well as DSS-induced colitis. Secretome and immunohistochemical analyses of DSS-treated mice display an elevated production of the proinflammatory cytokine IL-6 in PC-deficient colons. An inflammatory environment diminishes PC presence in primary fibroblast cultures, which is triggered by IL-6 as identified by RNA-seq analysis together with blocking experiments. These findings suggest an activation loop between IL-6 production and PC loss. An analysis of PC presence on biopsies of patients with ulcerative colitis or colorectal cancer (CRC) reveals decreased numbers of PC on colonic fibroblasts in pathological compared with surrounding normal tissue. Taken together, we provide evidence that a decrease in colonic PC numbers promotes colitis and CRC.

Ketogenic HMG-CoA lyase and its product β-hydroxybutyrate promote pancreatic cancer progression

Pancreatic ductal adenocarcinoma (PDA) tumor cells are deprived of oxygen and nutrients and therefore must adapt their metabolism to ensure proliferation. In some physiological states, cells rely on ketone bodies to satisfy their metabolic needs, especially during nutrient stress. Here, we show that PDA cells can activate ketone body metabolism and that β-hydroxybutyrate (βOHB) is an alternative cell-intrinsic or systemic fuel that can promote PDA growth and progression. PDA cells activate enzymes required for ketogenesis, utilizing various nutrients as carbon sources for ketone body formation. By assessing metabolic gene expression from spontaneously arising PDA tumors in mice, we find HMG-CoA lyase (HMGCL), involved in ketogenesis, to be among the most deregulated metabolic enzymes in PDA compared to normal pancreas. In vitro depletion of HMGCL impedes migration, tumor cell invasiveness, and anchorage-independent tumor sphere compaction. Moreover, disrupting HMGCL drastically decreases PDA tumor growth in vivo, while βOHB stimulates metastatic dissemination to the liver. These findings suggest that βOHB increases PDA aggressiveness and identify HMGCL and ketogenesis as metabolic targets for limiting PDA progression.

GlcNAc is a mast-cell chromatin-remodeling oncometabolite that promotes systemic mastocytosis aggressiveness

Systemic mastocytosis (SM) is a KIT-driven hematopoietic neoplasm characterized by the excessive accumulation of neoplastic mast cells (MCs) in various organs and, mainly, the bone marrow (BM). Multiple genetic and epigenetic mechanisms contribute to the onset and severity of SM. However, little is known to date about the metabolic underpinnings underlying SM aggressiveness, which has thus far impeded the development of strategies to leverage metabolic dependencies when existing KIT-targeted treatments fail. Here, we show that plasma metabolomic profiles were able to discriminate indolent from advanced forms of the disease. We identified N-acetyl-d-glucosamine (GlcNAc) as the most predictive metabolite of SM severity. High plasma levels of GlcNAc in patients with advanced SM correlated with the activation of the GlcNAc-fed hexosamine biosynthesis pathway in patients BM aspirates and purified BM MCs. At the functional level, GlcNAc enhanced human neoplastic MCs proliferation and promoted rapid health deterioration in a humanized mouse model of SM. In addition, in the presence of GlcNAc, immunoglobulin E-stimulated MCs triggered enhanced release of proinflammatory cytokines and a stronger acute response in a mouse model of passive cutaneous anaphylaxis. Mechanistically, elevated GlcNAc levels promoted the transcriptional accessibility of chromatin regions that contain genes encoding mediators of receptor tyrosine kinases cascades and inflammatory responses, thus leading to a more aggressive phenotype. Therefore, GlcNAc is an oncometabolite driver of SM aggressiveness. This study suggests the therapeutic potential for targeting metabolic pathways in MC-related diseases to manipulate MCs effector functions.

Cyclin A2 maintains colon homeostasis and is a prognostic factor in colorectal cancer

To clarify the function of cyclin A2 in colon homeostasis and colorectal cancer (CRC), we generated mice deficient for cyclin A2 in colonic epithelial cells (CECs). Colons of these mice displayed architectural changes in the mucosa and signs of inflammation, as well as increased proliferation of CECs associated with the appearance of low- and high-grade dysplasias. The main initial events triggering those alterations in cyclin A2-deficient CECs appeared to be abnormal mitoses and DNA damage. Cyclin A2 deletion in CECs promoted the development of dysplasia and adenocarcinomas in a murine colitis-associated cancer model. We next explored the status of cyclin A2 expression in clinical CRC samples at the mRNA and protein levels and found higher expression in tumors of patients with stage 1 or 2 CRC compared with those of patients with stage 3 or 4 CRC. A meta-analysis of 11 transcriptome data sets comprising 2239 primary CRC tumors revealed different expression levels of CCNA2 (the mRNA coding for cyclin A2) among the CRC tumor subtypes, with the highest expression detected in consensus molecular subtype 1 (CMS1) and the lowest in CMS4 tumors. Moreover, we found high expression of CCNA2 to be a new, independent prognosis factor for CRC tumors.

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2).