A unique subset of glycolytic tumour-propagating cells drives squamous cell carcinoma

Head and neck squamous cell carcinoma (SCC) remains among the most aggressive human cancers. Tumour progression and aggressiveness in SCC are largely driven by tumour-propagating cells (TPCs). Aerobic glycolysis, also known as the Warburg effect, is a characteristic of many cancers; however, whether this adaptation is functionally important in SCC, and at which stage, remains poorly understood. Here, we show that the NAD+-dependent histone deacetylase sirtuin 6 is a robust tumour suppressor in SCC, acting as a modulator of glycolysis in these tumours. Remarkably, rather than a late adaptation, we find enhanced glycolysis specifically in TPCs. More importantly, using single-cell RNA sequencing of TPCs, we identify a subset of TPCs with higher glycolysis and enhanced pentose phosphate pathway and glutathione metabolism, characteristics that are strongly associated with a better antioxidant response. Together, our studies uncover enhanced glycolysis as a main driver in SCC, and, more importantly, identify a subset of TPCs as the cell of origin for the Warburg effect, defining metabolism as a key feature of intra-tumour heterogeneity

Phenotypic and transcriptomic characterization of canine myeloid-derived suppressor cells

Myeloid-derived suppressor cells (MDSCs) are key players in immune evasion, tumor progression and metastasis. MDSCs accumulate under various pathological states and fall into two functionally and phenotypically distinct subsets that have been identified in humans and mice: polymorphonuclear (PMN)-MDSCs and monocytic (M)-MDSCs. As dogs are an excellent model for human tumor development and progression, we set out to identify PMN-MDSCs and M-MDSCs in clinical canine oncology patients. Canine hypodense MHC class II-CD5-CD21-CD11b+ cells can be subdivided into polymorphonuclear (CADO48A+CD14-) and monocytic (CADO48A-CD14+) MDSC subsets. The transcriptomic signatures of PMN-MDSCs and M-MDSCs are distinct, and moreover reveal a statistically significant similarity between canine and previously published human PMN-MDSC gene expression patterns. As in humans, peripheral blood frequencies of canine PMN-MDSCs and M-MDSCs are significantly higher in dogs with cancer compared to healthy control dogs (PMN-MDSCs: p < 0.001; M-MDSCs: p < 0.01). By leveraging the power of evolution, we also identified additional conserved genes in PMN-MDSCs of multiple species that may play a role in MDSC function. Our findings therefore validate the dog as a model for studying MDSCs in the context of cancer

Programmed cell death 1 as prognostic marker and therapeutic target in upper gastrointestinal cancers

Gastrointestinal (GIs) cancers are among the most common causes of cancer related death, and hence the importance for the identification of novel prognostic/predictive biomarkers for detection of patients at an early stage, and for using these to identify novel targeted therapies to improve the efficacy of existing chemotherapeutic regimens. Programmed cell death 1 has been reported as a potential target in several malignancies, and targeting agents are being developed, some already approved by FDA, such as: pembrolizumab, Atezolizumab, Nivolumab. Pembrolizumab that have been approved for the treatment of metastatic non-small cell lung cancer. Here we provide an overview of the mechanism of action PD-1/PD-L1, prognostic value and current progress in clinical trials using PD-1/PD-L1 inhibitors, and the resistant mechanisms at underlie the inhibitory effect of these agents in the treatment of gastrointestinal cancers

Melanoma Models for the Next Generation of Therapies

There is a lack of appropriate melanoma models that can be used to evaluate the efficacy of novel therapeutic modalities. Here, we discuss the current state of the art of melanoma models including genetically engineered mouse, patient-derived xenograft, zebrafish, and ex&nbsp;vivo and in&nbsp;vitro models. We also identify five major challenges that can be addressed using such models, including metastasis and tumor dormancy, drug resistance, the melanoma immune response, and the impact of aging and environmental exposures on melanoma progression and drug resistance. Additionally, we discuss the opportunity for building models for rare subtypes of melanomas, which represent an unmet critical need. Finally, we identify key recommendations for melanoma models that may improve accuracy of preclinical testing and predict efficacy in clinical trials, to help usher in the next generation of melanoma therapies

Resistance to checkpoint blockade therapy through inactivation of antigen presentation

Treatment with immune checkpoint blockade (CPB) therapies often leads to prolonged responses in patients with metastatic melanoma, but the common mechanisms of primary and acquired resistance to these agents remain incompletely characterized and have yet to be validated in large cohorts. By analyzing longitudinal tumor biopsies from 17 metastatic melanoma patients treated with CPB therapies, we observed point mutations, deletions or loss of heterozygosity (LOH) in beta-2-microglobulin (B2M), an essential component of MHC class I antigen presentation, in 29.4% of patients with progressing disease. In two independent cohorts of melanoma patients treated with anti-CTLA4 and anti-PD1, respectively, we find that B2M LOH is enriched threefold in non-responders (~30%) compared to responders (~10%) and associated with poorer overall survival. Loss of both copies of B2M is found only in non-responders. B2M loss is likely a common mechanism of resistance to therapies targeting CTLA4 or PD1

Role of S100 proteins in health and disease

The S100 family of proteins contains 25 known members that share a high degree of sequence and structural similarity. However, only a limited number of family members have been characterized in depth, and the roles of other members are likely undervalued. Their importance should not be underestimated however, as S100 family members function to regulate a diverse array of cellular processes including proliferation, differentiation, inflammation, migration and/or invasion, apoptosis, Ca2+ homeostasis, and energy metabolism. Here we detail S100 target protein interactions that underpin the mechanistic basis to their function, and discuss potential intervention strategies targeting S100 proteins in both preclinical and clinical situations