Extracellular nicotinamide phosphoribosyltransferase (eNAMPT) neutralization counteracts T cell immune evasion in breast cancer

Biological Functions and Therapeutic Potential of NAD+ Metabolism in Gynecological Cancers

Nicotinamide adenine dinucleotide (NAD+) is an important cofactor for both metabolic and signaling pathways, with the dysregulation of NAD+ levels acting as a driver for diseases such as neurodegeneration, cancers, and metabolic diseases. NAD+ plays an essential role in regulating the growth and progression of cancers by controlling important cellular processes including metabolism, transcription, and translation. NAD+ regulates several metabolic pathways such as glycolysis, the citric acid (TCA) cycle, oxidative phosphorylation, and fatty acid oxidation by acting as a cofactor for redox reactions. Additionally, NAD+ acts as a cofactor for ADP-ribosyl transferases and sirtuins, as well as regulating cellular ADP-ribosylation and deacetylation levels, respectively. The cleavage of NAD+ by CD38-an NAD+ hydrolase expressed on immune cells-produces the immunosuppressive metabolite adenosine. As a result, metabolizing and maintaining NAD+ levels remain crucial for the function of various cells found in the tumor microenvironment, hence its critical role in tissue homeostasis. The NAD+ levels in cells are maintained by a balance between NAD+ biosynthesis and consumption, with synthesis being controlled by the Preiss-Handler, de novo, and NAD+ salvage pathways. The primary source of NAD+ synthesis in a variety of cell types is directed by the expression of the enzymes central to the three biosynthesis pathways. In this review, we describe the role of NAD+ metabolism and its synthesizing and consuming enzymes' control of cancer cell growth and immune responses in gynecologic cancers. Additionally, we review the ongoing efforts to therapeutically target the enzymes critical for NAD+ homeostasis in gynecologic cancers.

Pro- and anti-inflammatory cytokines: the hidden keys to autoimmune gastritis therapy

Autoimmune gastritis (AIG) is an autoimmune disorder characterized by the destruction of gastric parietal cells and atrophy of the oxyntic mucosa which induces intrinsic factor deficiency and hypo-achlorhydria. AIG predominantly affects the antral mucosa with AIG patients experiencing increased inflammation and a predisposition toward the development of gastric adenocarcinoma and type I neuroendocrine tumors. The exact pathogenesis of this autoimmune disorder is incompletely understood although dysregulated immunological mechanisms appear to major contributors. This review of autoimmune gastritis, an unmet medical need, summarizes current knowledge on pro- and anti-inflammatory cytokines and strategies for the discovery of novel biomarkers and potential pharmacological targets.

Design of FK866-Based Degraders for Blocking the Nonenzymatic Functions of Nicotinamide Phosphoribosyltransferase

Nicotinamide phosphoribosyltransferase (NAMPT) is an attractive therapeutic target for treating select cancers. There are two forms of NAMPT: intracellular NAMPT (iNAMPT, the rate-limiting enzyme in the mammalian NAD+ main synthetic pathway) and extracellular NAMPT (eNAMPT, a cytokine with protumorigenic function). Reported NAMPT inhibitors only inhibit iNAMPT and show potent activities in preclinical studies. Unfortunately, they failed to show efficacy due to futility and toxicity. We developed a series of FK866-based NAMPT-targeting PROTACs and identified LYP-8 as a potent and effective NAMPT degrader that simultaneously diminished iNAMPT and eNAMPT. Importantly, LYP-8 demonstrated superior efficacy and safety in mice when compared to the clinical candidate, FK866. This study highlights the importance and feasibility of applying PROTACs as a superior strategy for interfering with both the enzymatic function of NAMPT (iNAMPT) and nonenzymatic function of NAMPT (eNAMPT), which is difficult to achieve with conventional NAMPT inhibitors.

Robust machine-learning based prognostic index using cytotoxic T lymphocyte evasion genes highlights potential therapeutic targets in colorectal cancer

BACKGROUND

A minute fraction of patients stands to derive substantial benefits from immunotherapy, primarily attributable to immune evasion. Our objective was to formulate a predictive signature rooted in genes associated with cytotoxic T lymphocyte evasion (CERGs), with the aim of predicting outcomes and discerning immunotherapeutic response in colorectal cancer (CRC).

METHODS

101 machine learning algorithm combinations were applied to calculate the CERGs prognostic index (CERPI) under the cross-validation framework, and patients with CRC were separated into high- and low-CERPI groups. Relationship between immune cell infiltration levels, immune-related scores, malignant phenotypes and CERPI were further analyzed. Various machine learning methods were used to identify key genes related to both patient survival and immunotherapy benefits. Expression of HOXC6, G0S2, and MX2 was evaluated and the effects of HOXC6 and G0S2 on the viability and migration of a CRC cell line were in-vitro verified.

RESULTS

The CERPI demonstrated robust prognostic efficacy in predicting the overall survival of CRC patients, establishing itself as an independent predictor of patient outcomes. The low-CERPI group exhibited elevated levels of immune cell infiltration and lower scores for tumor immune dysfunction and exclusion, indicative of a greater potential benefit from immunotherapy. Moreover, there was a positive correlation between CERPI levels and malignant tumor phenotypes, suggesting that heightened CERPI expression contributes to both the occurrence and progression of tumors. Thirteen key genes were identified, and their expression patterns were scrutinized through the analysis of single-cell datasets. Notably, HOXC6, G0S2, and MX2 exhibited upregulation in both CRC cell lines and tissues. Subsequent knockdown experiments targeting G0S2 and HOXC6 resulted in a significant suppression of CRC cell viability and migration.

CONCLUSION

We developed the CERPI for effectively predicting survival and response to immunotherapy in patients, and these results may provide guidance for CRC diagnosis and precise treatment.