The CXCL12/CXCR4/ACKR3 Signaling Axis Regulates PKM2 and Glycolysis

Immunometabolic Signatures of Circulating Monocytes in Humans With Obesity and Insulin Resistance

Obesity is associated with chronic inflammation and metabolic complications, including insulin resistance (IR). Immune cells drive inflammation through the rewiring of intracellular metabolism. However, the impact of obesity-related IR on the metabolism and functionality of circulating immune cells, like monocytes, remains poorly understood. To increase insight into the interindividual variation of immunometabolic signatures among individuals and their role in the development of IR, we assessed systemic and tissue-specific IR and circulating immune markers, and we characterized metabolic signatures and cytokine secretion of circulating monocytes from 194 individuals with a BMI ≥25 kg/m2. Monocyte metabolic signatures were defined using extracellular acidification rates (ECARs) to estimate glycolysis and oxygen consumption rates (OCRs) for oxidative metabolism. Although monocyte metabolic signatures and function based on cytokine secretion varied greatly among study participants, they were strongly associated with each other. The ECAR-to-OCR ratio, representing the balance between glycolysis and oxidative metabolism, was negatively associated with fasting insulin levels, systemic IR, and liver-specific IR. These results indicate that monocytes from individuals with IR were relatively more dependent on oxidative metabolism, whereas monocytes from more insulin-sensitive individuals were more dependent on glycolysis. Additionally, circulating CXCL11 was negatively associated with the degree of systemic IR and positively with the ECAR-to-OCR ratio in monocytes, suggesting that individuals with high IR and a monocyte metabolic dependence on oxidative metabolism also have lower levels of circulating CXCL11. Our findings suggest that monocyte metabolism is related to obesity-associated IR progression and deepen insights into the interplay between innate immune cell metabolism and IR development in humans.

ARTICLE HIGHLIGHTS

Analysis of C-X-C motif chemokine receptors in breast cancer: potential value in immunotherapy and prognostic prediction

Background

The concept of individualized therapy has advanced the development of prognostic biomarkers to manage patients with breast cancer (BRCA). Immunotherapy has shown great potential in treating BRCA, and the C-X-C motif chemokine receptor (CXCR) has generated interest in regulating tumor progression through the immune microenvironment. Although CXCRs were utilized for prognosis prediction in glioma with favourable capability, the prognostic and therapeutic role of CXCR in BRCA is unclear.

Methods

We used The Cancer Genome Atlas (TCGA) database to analyze 1,095 BRCA patients' transcription, mutation, survival time and survival status. Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE), Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT), quanTIseq, and Estimating the Proportion of Immune and Cancer cells (EPIC) algorithms were performed to infer the association of CXCR genes with immune cells. We randomly divided the TCGA dataset into a training set and a validation set according to 1:1, constructed a LASSO Cox regression model based on CXCR family genes using the glmnet R package in the training set, assembled clinical variables to draw a visual Nomogram using the R package rms, and validated the model by receiver operating characteristic (ROC) curves, calibration curves with clinical decision curves in the validation set efficacy.

Results

Compared to normal samples, CXCR3/4/5 messenger RNA (mRNA) expression levels were upregulated in BRCA samples, whereas CXCR1/2 mRNA expression levels were downregulated. High CXCR3/5/6 expression was associated with a good prognosis. Subsequently, we divided the CXCRs into 2 molecular subgroups based on their expression patterns and explored prognosis, immune infiltration, functional enrichment, hallmarks, and immune response differentiation between the two subgroups. After LASSO Cox regression modeling, a CXCR score predicting overall survival (OS) was constructed, and the predictive accuracy was assessed. By pooling clinical variables, a nomogram individual risk assessment method was established to measure the identification of genuinely high-risk patients who should receive interventions.

Conclusions

In summary, CXCR genes were associated with immune infiltration and survival in BRCA patients, and our CXCR-based prognostic model could better predict the prognosis of BRCA patients and provide potential immunotherapy targets for clinical purposes.