FSCN1 induced PTPRF-dependent tumor microenvironment inflammatory reprogramming promotes lung adenocarcinoma progression via regulating macrophagic glycolysis

Energy metabolism as the hub of advanced non-small cell lung cancer management: a comprehensive view in the framework of predictive, preventive, and personalized medicine

Energy metabolism is a hub of governing all processes at cellular and organismal levels such as, on one hand, reparable vs. irreparable cell damage, cell fate (proliferation, survival, apoptosis, malignant transformation etc.), and, on the other hand, carcinogenesis, tumor development, progression and metastazing versus anti-cancer protection and cure. The orchestrator is the mitochondria who produce, store and invest energy, conduct intracellular and systemically relevant signals decisive for internal and environmental stress adaptation, and coordinate corresponding processes at cellular and organismal levels. Consequently, the quality of mitochondrial health and homeostasis is a reliable target for health risk assessment at the stage of reversible damage to the health followed by cost-effective personalized protection against health-to-disease transition as well as for targeted protection against the disease progression (secondary care of cancer patients against growing primary tumors and metastatic disease). The energy reprogramming of non-small cell lung cancer (NSCLC) attracts particular attention as clinically relevant and instrumental for the paradigm change from reactive medical services to predictive, preventive and personalized medicine (3PM). This article provides a detailed overview towards mechanisms and biological pathways involving metabolic reprogramming (MR) with respect to inhibiting the synthesis of biomolecules and blocking common NSCLC metabolic pathways as anti-NSCLC therapeutic strategies. For instance, mitophagy recycles macromolecules to yield mitochondrial substrates for energy homeostasis and nucleotide synthesis. Histone modification and DNA methylation can predict the onset of diseases, and plasma C7 analysis is an efficient medical service potentially resulting in an optimized healthcare economy in corresponding areas. The MEMP scoring provides the guidance for immunotherapy, prognostic assessment, and anti-cancer drug development. Metabolite sensing mechanisms of nutrients and their derivatives are potential MR-related therapy in NSCLC. Moreover, miR-495-3p reprogramming of sphingolipid rheostat by targeting Sphk1, 22/FOXM1 axis regulation, and A2 receptor antagonist are highly promising therapy strategies. TFEB as a biomarker in predicting immune checkpoint blockade and redox-related lncRNA prognostic signature (redox-LPS) are considered reliable predictive approaches. Finally, exemplified in this article metabolic phenotyping is instrumental for innovative population screening, health risk assessment, predictive multi-level diagnostics, targeted prevention, and treatment algorithms tailored to personalized patient profiles-all are essential pillars in the paradigm change from reactive medical services to 3PM approach in overall management of lung cancers. This article highlights the 3PM relevant innovation focused on energy metabolism as the hub to advance NSCLC management benefiting vulnerable subpopulations, affected patients, and healthcare at large.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-024-00357-5.

Roles of IL-4, IL-13, and Their Receptors in Lung Cancer

Interleukin (IL)-4 and IL-13 are the main effectors of innate lymphoid cells (ILC2) of the type 2 innate immune response, which can carry out specific signal transmission between multiple cells in the tumor immune microenvironment. IL-4 and IL-13 mediate signal transduction and regulate cellular functions in a variety of solid tumors through their shared receptor chain, the transmembrane heterodimer interleukin-4 receptor alpha/interleukin-13 receptor alpha-1 (type II IL-4 receptor). IL-4, IL-13, and their receptors can induce the formation of a variety of malignant tumors and play an important role in their progression, growth, and tumor immunity. In order to explore possible targets for lung cancer prediction and treatment, this review summarizes the characteristics and signal transduction pathways of IL-4 and IL-13, and their respective receptors, and discusses in depth their possible role in the occurrence and development of lung cancer.

TPX2 influences the regulation of macrophage polarization via the NF-κB pathway in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most prevalent subtype of lung cancer. Xklp2 targeting protein (TPX2), a crucial oncogene exhibits high expression levels in various cancers including LUAD, may serve as a potential target for clinical intervention. Additionally, the growth of lung cancer is significantly influenced by the tumor microenvironment (TME). However, there have been no reports on experiments investigating TPX2 in tumor-infiltrating immune cells (TIICs) in LUAD. Therefore, we verified the effect of TPX2 on macrophage polarization both in vitro and in vivo.

METHODS

We silenced TPX2 the gene in A549 cells and collected supernatants for macrophage culture. We then used flow cytometry and Western blot analysis to assess macrophage polarization. Additionally, we verified the expression of macrophage colony-stimulating factor (M-CSF), and CD163 by immunohistochemistry (IHC) in tissue specimens from LUAD patients. Finally, pathways related to TPX2's regulatory function in macrophage polarization were analyzed through whole genome sequencing, Western blotting, and immunofluorescence (IF).

RESULTS

Silencing TPX2 can affect the ratio of CD80+ M1/CD163+ M2 and reduce the polarization of M0 macrophages to CD163+ M2 macrophages mainly by inhibiting the expression of M-CSF. In human LUAD tissues, the expression levels of TPX2, M-CSF and CD163 increased with the degree of differentiation. Silencing TPX2 inhibits the NF-κB signaling pathway, thereby reducing the expression of M-CSF, and affecting macrophage polarization.

CONCLUSION

Silencing TPX2 can inhibit the expression of M-CSF by blocking the NF-κB signal, thereby reducing CD163+ M2 macrophage polarization. The TPX2/NF-κB/M-CSF signaling axis may be involved in regulating macrophage polarization.

Identification of prognostic risk score of disulfidptosis-related genes and molecular subtypes in glioma

Background

Programmed cell death is closely related to glioma. As a novel kind of cell death, the mechanism of disulfidptosis in glioma remains unclear. Therefore, it is of great importance to study the role of disulfidptosis-related genes (DRGs) in glioma.

Methods

We first investigated the genetic and transcriptional alterations of 15 DRGs. Two consensus cluster analyses were used to evaluate the association between DRGs and glioma subtypes. In addition, we constructed prognostic DRG risk scores to predict overall survival (OS) in glioma patients. Furthermore, we developed a nomogram to enhance the clinical utility of the DRG risk score. Finally, the expression levels of DRGs were verified by immunohistochemistry (IHC) staining.

Results

Most DRGs (14/15) were dysregulated in gliomas. The 15 DRGs were rarely mutated in gliomas, and only 50 of 987 samples (5.07 %) showed gene mutations. However, most of them had copy number variation (CNV) deletions or amplifications. Two distinct molecular subtypes were identified by cluster analysis, and DRG alterations were found to be related to the clinical characteristics, prognosis, and tumor immune microenvironment (TIME). The DRG risk score model based on 12 genes was developed and showed good performance in predicting OS. The nomogram confirmed that the risk score had a particularly strong influence on the prognosis of glioma. Furthermore, we discovered that low DRG scores, low tumor mutation burden, and immunosuppression were features of patients with better prognoses.

Conclusion

The DRG risk model can be used for the evaluation of clinical characteristics, prognosis prediction, and TIME estimation of glioma patients. These DRGs may be potential therapeutic targets in glioma.

Glycolysis regulation in tumor-associated macrophages: Its role in tumor development and cancer treatment

Tumor-associated macrophages constitute the main cell population in the tumor microenvironment and play a crucial role in regulating the microenvironment composition. Emerging evidence has revealed that the metabolic profile determines the tumor-associated macrophage phenotype. Tumor-associated macrophage function is highly dependent on glucose metabolism, with glycolysis being the major metabolic pathway. Recent reports have demonstrated diversity in glucose flux of tumor-associated macrophages and complex substance communication with cancer cells. However, how the glucose flux in tumor-associated macrophages connects with glycolysis to influence tumor progression and the tumor microenvironment is still obscure. Moreover, while the development of single-cell sequencing technology allows a clearer and more accurate classification of tumor-associated macrophages, the metabolic profiles of tumor-associated macrophages from the perspective of single-cell omics has not been well summarized. Here, we review the current state of knowledge on glucose metabolism in tumor-associated macrophages and summarize the metabolic profiles of different tumor-associated macrophage subtypes from the perspective of single-cell omics. Additionally, we describe the current strategies targeting glycolysis in tumor-associated macrophages for cancer therapy.

Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma

Mounting evidence has found that tumor microenvironment (TME) plays an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of tumor microenvironment-related genes in immunotherapy and clinical outcomes remain unclear. In this study, 6 TME-related genes (PLK1, LDHA, FURIN, FSCN1, RAB27B, and MS4A1) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. In conclusion, the TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in LUAD patients, which provides recommendations for improving patients' response to immunotherapy and promoting personalized tumor immunotherapy in the future.