TLR3 Expression is a Potential Prognosis Biomarker and Shapes the Immune-Active Tumor Microenvironment in Esophageal Squamous Cell Carcinoma

Pirarubicin combined with TLR3 or TLR4 agonists enhances anti-tumor efficiency

BACKGROUND

Triple-negative breast cancer (TNBC) is prone to relapse due to the lack of effective therapeutic targets. Macrophages are the most abundant immune cells in the tumor microenvironment (TME) of breast cancer. Targeting the cross-talk between macrophages and cancer cells provides a more efficient strategy for anti-tumor therapy. Toll-like receptors (TLRs) are important players involved in macrophage activation, and TLR agonists are known to play roles in cancer therapy. However, the combination strategy of TLR agonists with chemotherapy drugs is still not well characterized.

METHODS

RT-PCR and Western blot were used to detect the expression of TLRs. The communication between breast cancer cells and macrophages were determined by co-culture in vitro. Tumor cells proliferation and migration were investigated by MTT assay and scratch wound assay. The effects of drug combinations and toxic side effects were assessed by immunohistochemistry and Hematoxylin & Eosin staining.

RESULTS

Expression of TLR3 and TLR4 were lower in breast tumor tissues compared with adjacent normal tissues. Patients with higher TLR3 or TLR4 expression levels had a better prognosis than those with lower expression levels. TLR3/4 expression was significantly inhibited when breast cancer cells MDA-MB-231 and E0771 were conditioned-cultured with macrophages in vitro and was also inhibited by pirarubicin (THP). However, the combination of TLR agonists and THP could reverse this response and inhibit the proliferation and migration of breast cancer cells. Additionally, this combination significantly reduced the tumor volume and weight in the murine model, increased the expression of TLR3/4 in mouse breast tumors.

CONCLUSIONS

Our results provide new ideas for the combination strategy of THP with TLR agonists which improves prognosis of breast cancer.

Immunological Strategies in Gastric Cancer: How Toll-like Receptors 2, -3, -4, and -9 on Monocytes and Dendritic Cells Depend on Patient Factors?

(1) Introduction: Toll-like receptors (TLRs) are key in immune response by recognizing pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs). In gastric cancer (GC), TLR2, TLR3, TLR4, and TLR9 are crucial for modulating immune response and tumor progression. (2) Objective: This study aimed to assess the percentage of dendritic cells and monocytes expressing TLR2, TLR3, TLR4, and TLR9, along with the concentration of their soluble forms in the serum of GC patients compared to healthy volunteers. Factors such as disease stage, tumor type, age, and gender were also analyzed. (3) Materials and Methods: Blood samples from newly diagnosed GC patients and healthy controls were immunophenotyped using flow cytometry to assess TLR expression on dendritic cell subpopulations and monocytes. Serum-soluble TLRs were measured by ELISA. Statistical analysis considered clinical variables such as tumor type, stage, age, and gender. (4) Results: TLR expression was significantly higher in GC patients, except for TLR3 on classical monocytes. Soluble forms of all TLRs were elevated in GC patients, with significant differences based on disease stage but not tumor type, except for serum TLR2, TLR4, and TLR9. (5) Conclusions: Elevated TLR expression and soluble TLR levels in GC patients suggest a role in tumor pathogenesis and progression, offering potential biomarkers and therapeutic targets.

Stimuli-Mediated Macrophage Switching, Unraveling the Dynamics at the Nanoplatforms-Macrophage Interface

Macrophages play an essential role in immunotherapy and tissue regeneration owing to their remarkable plasticity and diverse functions. Recent bioengineering developments have focused on using external physical stimuli such as electric and magnetic fields, temperature, and compressive stress, among others, on micro/nanostructures to induce macrophage polarization, thereby increasing their therapeutic potential. However, it is difficult to find a concise review of the interaction between physical stimuli, advanced micro/nanostructures, and macrophage polarization. This review examines the present research on physical stimuli-induced macrophage polarization on micro/nanoplatforms, emphasizing the synergistic role of fabricated structure and stimulation for advanced immunotherapy and tissue regeneration. A concise overview of the research advancements investigating the impact of physical stimuli, including electric fields, magnetic fields, compressive forces, fluid shear stress, photothermal stimuli, and multiple stimulations on the polarization of macrophages within complex engineered structures, is provided. The prospective implications of these strategies in regenerative medicine and immunotherapeutic approaches are highlighted. This review will aid in creating stimuli-responsive platforms for immunomodulation and tissue regeneration.

Narrow band imaging-based radiogenomics for predicting radiosensitivity in nasopharyngeal carcinoma

Objectives

This study aims to assess the efficacy of narrow band imaging (NBI) endoscopy in utilizing radiomics for predicting radiosensitivity in nasopharyngeal carcinoma (NPC), and to explore the associated molecular mechanisms.

Materials

The study included 57 NPC patients who were pathologically diagnosed and underwent RNA sequencing. They were categorized into complete response (CR) and partial response (PR) groups after receiving radical concurrent chemoradiotherapy. We analyzed 267 NBI images using ResNet50 for feature extraction, obtaining 2048 radiomic features per image. Using Python for deep learning and least absolute shrinkage and selection operator for feature selection, we identified differentially expressed genes associated with radiomic features. Subsequently, we conducted enrichment analysis on these genes and validated their roles in the tumor immune microenvironment through single-cell RNA sequencing.

Results

After feature selection, 54 radiomic features were obtained. The machine learning algorithm constructed from these features showed that the random forest algorithm had the highest average accuracy rate of 0.909 and an area under the curve of 0.961. Correlation analysis identified 30 differential genes most closely associated with the radiomic features. Enrichment and immune infiltration analysis indicated that tumor-associated macrophages are closely related to treatment responses. Three key NBI differentially expressed immune genes (NBI-DEIGs), namely CCL8, SLC11A1, and PTGS2, were identified as regulators influencing treatment responses through macrophages.

Conclusion

NBI-based radiomics models introduce a novel and effective method for predicting radiosensitivity in NPC. The molecular mechanisms may involve the functional states of macrophages, as reflected by key regulatory genes.

Predictive and Prognostic Relevance of Tumor-Infiltrating Immune Cells: Tailoring Personalized Treatments against Different Cancer Types

TIICs are critical components of the TME and are used to estimate prognostic and treatment responses in many malignancies. TIICs in the tumor microenvironment are assessed and quantified by categorizing immune cells into three subtypes: CD66b+ tumor-associated neutrophils (TANs), FoxP3+ regulatory T cells (Tregs), and CD163+ tumor-associated macrophages (TAMs). In addition, many cancers have tumor-infiltrating M1 and M2 macrophages, neutrophils (Neu), CD4+ T cells (T-helper), CD8+ T cells (T-cytotoxic), eosinophils, and mast cells. A variety of clinical treatments have linked tumor immune cell infiltration (ICI) to immunotherapy receptivity and prognosis. To improve the therapeutic effectiveness of immune-modulating drugs in a wider cancer patient population, immune cells and their interactions in the TME must be better understood. This study examines the clinicopathological effects of TIICs in overcoming tumor-mediated immunosuppression to boost antitumor immune responses and improve cancer prognosis. We successfully analyzed the predictive and prognostic usefulness of TIICs alongside TMB and ICI scores to identify cancer's varied immune landscapes. Traditionally, immune cell infiltration was quantified using flow cytometry, immunohistochemistry, gene set enrichment analysis (GSEA), CIBERSORT, ESTIMATE, and other platforms that use integrated immune gene sets from previously published studies. We have also thoroughly examined traditional limitations and newly created unsupervised clustering and deconvolution techniques (SpatialVizScore and ProTICS). These methods predict patient outcomes and treatment responses better. These models may also identify individuals who may benefit more from adjuvant or neoadjuvant treatment. Overall, we think that the significant contribution of TIICs in cancer will greatly benefit postoperative follow-up, therapy, interventions, and informed choices on customized cancer medicines.

Development and Validation of the Oxidative Stress Related lncRNAs for Prognosis in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell cancer (ESCC) is an aggressive disease associated with a poor prognosis. Long non-coding RNAs (lncRNAs) and oxidative stress play crucial roles in tumor progression. We aimed to identify an oxidative stress-related lncRNA signature that could predict the prognosis in ESCC. In the GSE53625 dataset, we identified 332 differentially expressed lncRNAs (DElncRNAs) between ESCC and control samples, out of which 174 were oxidative stress-related DElncRNAs. Subsequently, seven oxidative stress-related DElncRNAs (CCR5AS, LINC01749, PCDH9-AS1, TMEM220-AS1, KCNMA1-AS1, SNHG1, LINC01672) were selected based on univariate and LASSO Cox to build a prognostic risk model, and their expression was detected by RT-qPCR. The model exhibited an excellent ability for the prediction of overall survival (OS) and other clinicopathological traits using Kaplan-Meier (K-M) survival curves, receiver operating characteristic (ROC) curves, and the Wilcoxon test. Additionally, analysis of infiltrated immune cells and immune checkpoints indicated differences in immune status between the two risk groups. Finally, the in vitro experiments showed that PCDH9-AS1 overexpression inhibited proliferation ability and promoted apoptosis and oxidative stress levels in ESCC cells. In conclusion, our study demonstrated that a novel oxidative stress-related DElncRNA prognostic model performed favorably in predicting ESCC patient prognosis and benefits personalized clinical applications.

Damage-mediated macrophage polarization in sterile inflammation

Most of the leading causes of death, such as cardiovascular diseases, cancer, dementia, neurodegenerative diseases, and many more, are associated with sterile inflammation, either as a cause or a consequence of these conditions. The ability to control the progression of inflammation toward tissue resolution before it becomes chronic holds significant clinical potential. During sterile inflammation, the initiation of inflammation occurs through damage-associated molecular patterns (DAMPs) in the absence of pathogen-associated molecules. Macrophages, which are primarily localized in the tissue, play a pivotal role in sensing DAMPs. Furthermore, macrophages can also detect and respond to resolution-associated molecular patterns (RAMPs) and specific pro-resolving mediators (SPMs) during sterile inflammation. Macrophages, being highly adaptable cells, are particularly influenced by changes in the microenvironment. In response to the tissue environment, monocytes, pro-inflammatory macrophages, and pro-resolution macrophages can modulate their differentiation state. Ultimately, DAMP and RAMP-primed macrophages, depending on the predominant subpopulation, regulate the balance between inflammatory and resolving processes. While sterile injury and pathogen-induced reactions may have distinct effects on macrophages, most studies have focused on macrophage responses induced by pathogens. In this review, which emphasizes available human data, we illustrate how macrophages sense these mediators by examining the expression of receptors for DAMPs, RAMPs, and SPMs. We also delve into the signaling pathways induced by DAMPs, RAMPs, and SPMs, which primarily contribute to the regulation of macrophage differentiation from a pro-inflammatory to a pro-resolution phenotype. Understanding the regulatory mechanisms behind the transition between macrophage subtypes can offer insights into manipulating the transition from inflammation to resolution in sterile inflammatory diseases.

TLR3 serves as a novel diagnostic and prognostic biomarker and is closely correlated with immune microenvironment in three types of cancer

Background: Toll-like receptor 3 (TLR3) plays an important role in both innate and adaptive immunity, but the prognostic value of TLR3 in heterogeneous tumors and the correlations between TLR3 expression and immune infiltration of heterogeneous tumors remain unclear. Methods: We investigated the expression of TLR3 in a variety of tumors and focused on the diagnostic and prognostic values of TLR3 in kidney renal clear cell carcinoma (KIRC), pancreatic adenocarcinoma (PAAD) and brain lower grade glioma (LGG) by GEPIA, DriverDBv3, UALCAN, TIMER, LinkedOmics, STRING, GeneMANIA and FunRich, as well as the possible mechanisms of TLR3 affecting tumor prognosis were discussed. Additionally, real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) was used to validate TLR3 expression in early KIRC. We also compared the expression of TLR3 in the plasma of early KIRC patients and normal controls by enzyme linked immunosorbent assay (ELISA). Results: TLR3 expression was significantly different in multiple tumors compared with paracancerous nontumor tissues. Elevated expression of TLR3 contributed to the prolonged survival outcome in KIRC patients. Suppressed expression of TLR3 contributed to the prolonged survival outcome in LGG and PAAD patients. Moreover, TLR3 was significantly elevated in stage1, grade1 and N0 of KIRC. The expression and function of TLR3 in KIRC, LGG and PAAD were closely related to tumor immune microenvironment. TRAF6 was a key gene in the interactions between TLR3 and its interacting genes. Finally, the results of RT-qPCR and ELISA indicated that TLR3 expression levels were significantly raised in renal tissue and plasma of early KIRC patients. Conclusion: TLR3 has the potential to be a diagnostic biomarker of KIRC, LGG and PAAD as well as a biomarker for evaluating the prognosis of KIRC, LGG and PAAD, particularly for the early diagnosis of KIRC. TLR3 affects tumors mainly by acting on the immune microenvironment of KIRC, LGG and PAAD. These findings could lead to new insights into the immunotherapeutic targets for KIRC, LGG, and PAAD.

Establishment and validation of a novel prognostic model for lower-grade glioma based on senescence-related genes

Objective

Increasing studies have indicated that senescence was associated with tumorigenesis and progression. Lower-grade glioma (LGG) presented a less invasive nature, however, its treatment efficacy and prognosis prediction remained challenging due to the intrinsic heterogeneity. Therefore, we established a senescence-related signature and investigated its prognostic role in LGGs.

Methods

The gene expression data and clinicopathologic features were from The Cancer Genome Atlas (TCGA) database. The experimentally validated senescence genes (SnGs) from the CellAge database were obtained. Then LASSO regression has been performed to build a prognostic model. Cox regression and Kaplan-Meier survival curves were performed to investigate the prognostic value of the SnG-risk score. A nomogram model has been constructed for outcome prediction. Immunological analyses were further performed. Data from the Chinese Glioma Genome Atlas (CGGA), Repository of Molecular Brain Neoplasia Data (REMBRANDT), and GSE16011 were used for validation.

Results

The 6-SnG signature has been established. The results showed SnG-risk score could be considered as an independent predictor for LGG patients (HR=2.763, 95%CI=1.660-4.599, P<0.001). The high SnG-risk score indicated a worse outcome in LGG (P<0.001). Immune analysis showed a positive correlation between the SnG-risk score and immune infiltration level, and the expression of immune checkpoints. The CGGA datasets confirmed the prognostic role of the SnG-risk score. And Kaplan-Meier analyses in the additional datasets (CGGA, REMBRANDT, and GSE16011) validated the prognostic role of the SnG-signature (P<0.001 for all).

Conclusion

The SnG-related prognostic model could predict the survival of LGG accurately. This study proposed a novel indicator for predicting the prognosis of LGG and provided potential therapeutic targets.