M1 Macrophages Are More Susceptible to Necroptosis

Anti-lung cancer synergy of low-dose doxorubicin and PD-L1 blocker co-delivered via mild photothermia-responsive black phosphorus

We have previously identified a latent interaction mechanism between non-small cell lung cancer cells (NSCLCC) and their associated macrophages (TAM) mediated by mutual paracrine activation of the HMGB1/RAGE/NF-κB signaling. Activation of this mechanism results in TAM stimulation and PD-L1 upregulation in the NSCLCC. In the present work, we found that free DOX at a low concentration that does not cause DNA damage could activate the HMGB1/RAGE/NF-κB/PD-L1 pathway byinducing oxidative stress. It was thus proposed that a combination of low-dose DOX and a PD-L1 blocker delivered in the NSCLC tumor would achieve synergistic TAM stimulation and thereby synergetic anti-tumor potency. To prove this idea, DOX and BMS-202 (a PD-L1 blocker) were loaded to black phosphorus (BP) nanoparticles after dosage titration to yield the BMS-202/DOX@BP composites that rapidly disintegrated and released drug cargo upon mild photothermal heating at 40 °C. In vitro experiments then demonstrated that low-dose DOX and BMS-202 delivered via BMS-202/DOX@BP under mild photothermia displayed enhanced tumor cell toxicity with a potent synergism only in the presence of TAM. This enhanced synergism was due to an anti-tumor M1-like TAM phenotype that was synergistically induced by low dose DOX plus BMS-202 only in the presence of the tumor cells, indicating the damaged tumor cells to be the cardinal contributor to the M1-like TAM stimulation. In vivo, BMS-202/DOX@BP under mild photothermia exhibited targeted delivery to NSCLC graft tumors in mice and synergistic anti-tumor efficacy of delivered DOX and BMS-202. In conclusion, low-dose DOX in combination with a PD-L1 blocker is an effective strategy to turn TAM against their host tumor cells exploiting the HMGB1/RAGE/NF-κB/PD-L1 pathway. The synergetic actions involved highlight the value of TAM and the significance of modulating tumor cell-TAM cross-talk in tumor therapy. Photothermia-responsive BP provides an efficient platform to translate this strategy into targeted, efficacious tumor therapy.

Necroptosis-based glioblastoma prognostic subtypes: implications for TME remodeling and therapy response

BACKGROUND

Glioblastoma (GBM) is an aggressive primary brain tumor with a high recurrence rate and poor prognosis. Necroptosis, a pathological hallmark of GBM, is poorly understood in terms of its role in prognosis, tumor microenvironment (TME) alteration, and immunotherapy.

METHODS & RESULTS

We assessed the expression of 55 necroptosis-related genes in GBM and normal brain tissues. We identified necroptosis-stratified clusters using Uni-Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish the 10-gene Glioblastoma Necroptosis Index (GNI). GNI demonstrated significant prognostic efficacy in the TCGA dataset (n = 160) and internal validation dataset (n = 345) and in external validation cohorts (n = 591). The GNI-high subgroup displayed a mesenchymal phenotype, lacking the IDH1 mutation, and MGMT methylation. This subgroup was characterized by significant enrichment in inflammatory and humoral immune pathways with prominent cell adhesion molecules (CD44 and ICAM1), inflammatory cytokines (TGFB1, IL1B, and IL10), and chemokines (CX3CL1, CXCL9, and CCL5). The TME in this subgroup showed elevated infiltration of M0 macrophages, neutrophils, mast cells, and regulatory T cells. GNI-related genes appeared to limit macrophage polarization, as confirmed by immunohistochemistry and flow cytometry. The top 30% high-risk score subset exhibited increased CD8 T cell infiltration and enhanced cytolytic activity. GNI showed promise in predicting responses to immunotherapy and targeted treatment.

CONCLUSIONS

Our study highlights the role of necroptosis-related genes in glioblastoma (GBM) and their effects on the tumor microenvironment and patient prognosis. TheGNI demonstrates potential as a prognostic marker and provides insights into immune characteristics and treatment responsiveness.

Diesel exhaust particles induce polarization state-dependent functional and transcriptional changes in human monocyte-derived macrophages

Macrophage populations exist on a spectrum between the proinflammatory M1 and proresolution M2 states and have demonstrated the ability to reprogram between them after exposure to opposing polarization stimuli. Particulate matter (PM) has been repeatedly linked to worsening morbidity and mortality following respiratory infections and has been demonstrated to modify macrophage function and polarization. The purpose of this study was to determine whether diesel exhaust particles (DEP), a key component of airborne PM, would demonstrate polarization state-dependent effects on human monocyte-derived macrophages (hMDMs) and whether DEP would modify macrophage reprogramming. CD14+CD16- monocytes were isolated from the blood of healthy human volunteers and differentiated into macrophages with macrophage colony-stimulating factor (M-CSF). Resulting macrophages were left unpolarized or polarized into the proresolution M2 state before being exposed to DEP, M1-polarizing conditions (IFN-γ and LPS), or both and tested for phagocytic function, secretory profile, gene expression patterns, and bioenergetic properties. Contrary to previous reports, we observed a mixed M1/M2 phenotype in reprogrammed M2 cells when considering the broader range of functional readouts. In addition, we determined that DEP exposure dampens phagocytic function in all polarization states while modifying bioenergetic properties in M1 macrophages preferentially. Together, these data suggest that DEP exposure of reprogrammed M2 macrophages results in a highly inflammatory, highly energetic subpopulation of macrophages that may contribute to the poor health outcomes following PM exposure during respiratory infections.NEW & NOTEWORTHY We determined that reprogramming M2 macrophages in the presence of diesel exhaust particles (DEP) results in a highly inflammatory mixed M1/M2 phenotype. We also demonstrated that M1 macrophages are particularly vulnerable to particulate matter (PM) exposure as seen by dampened phagocytic function and modified bioenergetics. Our study suggests that PM causes reprogrammed M2 macrophages to become a highly energetic, highly secretory subpopulation of macrophages that may contribute to negative health outcomes observed in humans after PM exposure.

Identification and Validation of Necroptosis-Related LncRNA Signature in Hepatocellular Carcinoma for Prognosis Estimation and Microenvironment Status

Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy. Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO-Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan-Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC₅₀) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro. Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC₅₀ analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues. Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.