Immune checkpoint inhibitor (ICI) therapy continues to revolutionize melanoma treatment, but only a subset of patients respond. Major efforts are underway to develop minimally invasive predictive assays of ICI response. Using single-cell transcriptomics, we discovered a unique CD8 T cell blood/tumor-shared subpopulation in melanoma patients with high levels of oxidative phosphorylation (OXPHOS), the ectonucleotidases CD38 and CD39, and both exhaustion and cytotoxicity markers. We called this population with high levels of OXPHOS “CD8+ TOXPHOS cells.” We validated that higher levels of OXPHOS in tumor- and peripheral blood–derived CD8+ TOXPHOS cells correlated with ICI resistance in melanoma patients. We then developed an ICI therapy response predictive model using a transcriptomic profile of CD8+ TOXPHOS cells. This model is capable of discerning responders from nonresponders using either tumor or peripheral blood CD8 T cells with high accuracy in multiple validation cohorts. In sum, CD8+ TOXPHOS cells represent a critical immune population to assess ICI response with the potential to be a new target to improve outcomes in melanoma patients.

Background: Whereas several interventions can effectively lower lipid levels in people at risk for atherosclerotic cardiovascular disease (ASCVD), cardiovascular event risks remain, suggesting an unmet medical need to identify factors contributing to cardiovascular event risk. Monocytes and macrophages play central roles in atherosclerosis, but studies have yet to provide a detailed view of macrophage populations involved in increased ASCVD risk. Methods: A novel macrophage foaming analytics tool, AtheroSpectrum, was developed using 2 quantitative indices depicting lipid metabolism and the inflammatory status of macrophages. A machine learning algorithm was developed to analyze gene expression patterns in the peripheral monocyte transcriptome of MESA participants (Multi-Ethnic Study of Atherosclerosis; set 1; n=911). A list of 30 genes was generated and integrated with traditional risk factors to create an ASCVD risk prediction model (30-gene cardiovascular disease risk score [CR-30]), which was subsequently validated in the remaining MESA participants (set 2; n=228); performance of CR-30 was also tested in 2 independent human atherosclerotic tissue transcriptome data sets (GTEx [Genotype–Tissue Expression] and GSE43292). Results: Using single-cell transcriptomic profiles (GSE97310, GSE116240, GSE97941, and FR-FCM-Z23S), AtheroSpectrum detected 2 distinct programs in plaque macrophages—homeostatic foaming and inflammatory pathogenic foaming—the latter of which was positively associated with severity of atherosclerosis in multiple studies. A pool of 2209 pathogenic foaming genes was extracted and screened to select a subset of 30 genes correlated with cardiovascular event in MESA set 1. A cardiovascular disease risk score model (CR-30) was then developed by incorporating this gene set with traditional variables sensitive to cardiovascular event in MESA set 1 after cross-validation generalizability analysis. The performance of CR-30 was then tested in MESA set 2 ( P =2.60×10 ⁻⁴ ; area under the receiver operating characteristic curve, 0.742) and 2 independent data sets (GTEx: P =7.32×10 ^–17 ; area under the receiver operating characteristic curve, 0.664; GSE43292: P =7.04×10 ⁻² ; area under the receiver operating characteristic curve, 0.633). Model sensitivity tests confirmed the contribution of the 30-gene panel to the prediction model (likelihood ratio test; df =31, P =0.03). Conclusions: Our novel computational program (AtheroSpectrum) identified a specific gene expression profile associated with inflammatory macrophage foam cells. A subset of 30 genes expressed in circulating monocytes jointly contributed to prediction of symptomatic atherosclerotic vascular disease. Incorporating a pathogenic foaming gene set with known risk factors can significantly strengthen the power to predict ASCVD risk. Our programs may facilitate both mechanistic investigations and development of therapeutic and prognostic strategies for ASCVD risk.

Macrophages are central players in systemic inflammation associated with obesity and aging, termed meta-inflammation and inflammaging. Activities of macrophages elicited by the two chronic conditions display shared and distinct patterns mechanistically, resulting in multifaceted actions for their pathogenic roles. Drastically expanded tissue macrophage populations under obesity and aging stress attribute to both enhanced recruitment and local expansion. Importantly, molecular networks governing the multifaceted actions of macrophages are directly altered by environmental cues and subsequently contribute to metabolic reprogramming, resulting in meta-inflammation in obesity or inflammaging in aging. In this review, we will summarize how meta-inflammation and inflammaging affect macrophages and the molecular mechanisms involved in these processes.

Obesity-induced adipose tissue dysfunction is bolstered by chronic, low-grade inflammation and impairs systemic metabolic health. Adipose tissue macrophages (ATMs) perpetuate local inflammation but are crucial to adipose tissue homeostasis, exerting heterogeneous, niche-specific functions. Diversified macrophage actions are shaped through finely regulated factors, including microRNAs, which post-transcriptionally alter macrophage activation. Numerous studies have highlighted microRNAs’ importance to immune function and potential as inflammation-modulatory. This review summarizes current knowledge of regulatory networks governed by microRNAs in ATMs in white adipose tissue under obesity stress.

Residual risk of cardiovascular events remains despite treatments that effectively lower cholesterol levels and hypertension, suggesting that there must be more variables to consider in atherosclerosis treatment. Several studies have suggested sex ^1,2,3 and inflammation ^4,5 as important variables. However, a cross-cohort analysis of sex and risk factors like inflammation and lipid-handling dysfunction is needed to strengthen their connection to atherosclerosis. By using blood transcriptomic profiles of 391 male and female participants, this study revealed that inflammation and lipid-handling dysfunction have sex-specific roles in atherosclerosis. Transcriptomics of 391 human blood samples with varying degrees of atherosclerosis were used to identify sex-specific changes in immune response and lipid-handling in circulating blood cells. Preliminary analyses of both FPKM and normalized counts datasets showed that inflammatory pathway activation and enrichment increased as atherosclerotic disease severity increased across all sexes. Analysis of sex-specific differentially expressed genes (DEGs) using IPA’s Canonical Pathways showed that severely impacted females had more enriched inflammatory pathways than severely impacted males. Further cross-cohort analysis of sex-specific inflammation and lipid-handling dysfunction was performed using AtheroSpectrum, a single-sample macrophage annotation tool. AtheroSpectrum confirmed that inflammation was more critical to female atherogenesis and revealed that lipid-handling dysfunction was more critical to male atherogenesis. Our study underscored the importance of inflammation and sex as variables to consider in atherosclerosis treatment, suggesting that treatment should target inflammation and consider sex. Our findings may be used for generating a model to predict atherosclerosis risk based on key DEGs, pathways, sex, and other clinical parameters when available.