Characteristics of immunophenotypes and immunological in tumor microenvironment and analysis of immune implication of CXCR4 in gastric cancer

Macrophage polarization-mediated PKM2/mTORC1/YME1L signaling pathway activation in fibrosis associated with Cardiorenal syndrome

BACKGROUND

Cardiorenal syndrome (CRS) is a complex condition characterized by the interplay between cardiac and renal dysfunction, often culminating in renal fibrosis. The role of macrophage polarization and its downstream effects in CRS-induced renal fibrosis remains an area of active investigation.

METHODS

Single-cell RNA sequencing (scRNA-seq) and immune infiltration analyses were employed to identify key immune cells and genes involved in renal fibrosis in CRS. Meta-analysis and pseudo-time analysis were conducted to validate the functional relevance of these genes. Functional studies utilizing CRISPR/Cas9 gene editing and lentiviral vectors assessed macrophage polarization and epithelial-to-mesenchymal transition (EMT). In vivo, a CRS mouse model was established, and fibrosis progression was tracked using histological and imaging methods.

RESULTS

The PKM2/mTORC1/YME1L signaling axis was identified as a critical pathway driving renal fibrosis, mediated by HIF-1α-induced M1 macrophage polarization. Inhibition of HIF-1α significantly alleviated renal fibrosis by restricting M1 polarization and suppressing the PKM2/mTORC1/YME1L axis. Co-culture models further demonstrated the involvement of EMT and metabolic reprogramming in affected cells.

CONCLUSION

Targeting the HIF-1α signaling pathway offers a promising therapeutic strategy for renal fibrosis by modulating macrophage polarization and the PKM2/mTORC1/YME1L axis.

Novel molecular mechanisms of immune evasion in hepatocellular carcinoma: NSUN2-mediated increase of SOAT2 RNA methylation

BACKGROUND

Hepatocellular carcinoma (HCC) is a deadly malignancy known for its ability to evade immune surveillance. NOP2/Sun RNA methyltransferase family member 2 (NSUN2), an RNA methyltransferase involved in carcinogenesis, has been associated with immune evasion and energy metabolism reprogramming. This study aimed to examine the molecular mechanisms underlying the involvement of NSUN2 in immune evasion and metabolic reprogramming of HCC.

METHODS

Single-cell transcriptomic sequencing was applied to examine cellular composition changes, particularly immune cell dynamics, in HCC and adjacent normal tissues. Bulk RNA-seq and proteomics identified key genes and proteins. Methylation sequencing and methylated RNA immunoprecipitation (MeRIP) were carried out to characterize the role of NSUN2 in 5-methylcytosine (m5C) modification of sterol O-acyltransferase 2 (SOAT2). Clinical samples from 30 HCC patients were analyzed using reverse transcription-quantitative polymerase chain reaction and Western blotting. Gene expression was manipulated using CRISPR/Cas9 and lentiviral vectors. In vitro co-culture models and metabolomics were used to study HCC cell-T cell interactions, energy metabolism, and immune evasion. Tumor growth in an orthotopic mouse model was monitored by bioluminescence imaging, with subsequent measurements of tumor weight, volume, and immunohistochemical staining.

RESULTS

Single-cell transcriptomic analysis identified a marked increase in malignant cells in HCC tissues. Cell communication analysis indicated that tumor cells might promote cancer progression by evading immune clearance. Multi-omics analyses identified NSUN2 as a key regulator in HCC development. MeRIP confirmed that NSUN2 facilitated the m5C modification of SOAT2. Analysis of human HCC tissue samples demonstrated pronounced upregulation of NSUN2 and SOAT2, along with elevated m5C levels in HCC tissues. In vitro experiments uncovered that NSUN2 augmented the reprogramming of energy metabolism and repressed the activity and cytotoxicity of CD8+ T cells, contributing to immune evasion. In vivo studies further substantiated the role of NSUN2 in fostering immune evasion and tumor formation of HCC by modulating the m5C modification of SOAT2.

CONCLUSIONS

The findings highlight the critical role of NSUN2 in driving HCC progression through the regulation of m5C modification on SOAT2. These findings present potential molecular markers for HCC diagnosis and therapeutic targets for its treatment.

Decellularized tissue matrices hydrogels functionalized with extracellular vesicles promote macrophage reprogramming and neural stem cell differentiation for spinal cord injury repair

This study investigates the application of decellularized tissue matrices (DSCM) hydrogels functionalized with extracellular vesicles (EVs) derived from mesenchymal stromal cells (MSCs) for spinal cord injury (SCI) treatment. The primary focus is on how these composites influence macrophage reprogramming and neural stem cell (NSC) differentiation by modulating Slamf9 expression. MSC-derived EVs were successfully isolated, and DSCM hydrogels were prepared from porcine spinal cords. The composite material, EVs derived from MSCs (DSCM@EVs), was constructed and applied to a mouse SCI model, showing significant enhancement in NSC differentiation and axonal growth, thereby alleviating SCI. Bioinformatics and in vitro cell experiments revealed that DSCM@EVs promote the reprogramming of M1 macrophages to the M2 phenotype, reducing inflammatory responses and facilitating NSC differentiation. RNA-seq analysis identified Slamf9 as a key regulatory gene, with its suppression linked to the observed therapeutic effects. This novel approach demonstrates the potential of DSCM@EVs in SCI repair by modulating the inflammatory environment and promoting neural regeneration, offering a promising strategy for treating SCI and potentially other inflammatory neurological disorders.

Integrating transcriptomic data and digital pathology for NRG-based prediction of prognosis and therapy response in gastric cancer

BACKGROUND

Cancer is characterized by its ability to resist cell death, and emerging evidence suggests a potential correlation between non-apoptotic regulated cell death (RCD), tumor progression, and therapy response. However, the prognostic significance of non-apoptotic RCD-related genes (NRGs) and their relationships with immune response in gastric cancer (GC) remain unclear.

METHODS

In this study, RNA-seq gene expression and clinical information of GC patients were acquired from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Cox and LASSO regression analyses were used to construct the NRG signature. Moreover, we developed a deep learning model based on ResNet50 to predict the NRG signature from digital pathology slides. The expression of signature hub genes was validated using real-time quantitative PCR and single-cell RNA sequencing data.

RESULTS

We identified 13 NRGs as signature genes for predicting the prognosis of patients with GC. The high-risk group, characterized by higher NRG scores, demonstrated a shorter overall survival rate, increased immunosuppressive cell infiltration, and immune dysfunction. Moreover, associations were observed between the NRG signature and chemotherapeutic drug responsiveness, as well as immunotherapy effectiveness in GC patients. Furthermore, the deep learning model effectively stratified GC patients based on the NRG signature by leveraging morphological variances, showing promising results for the classification of GC patients. Validation experiments demonstrated that the expression level of SERPINE1 was significantly upregulated in GC, while the expression levels of GPX3 and APOD were significantly downregulated.

CONCLUSION

The NRG signature and its deep learning model have significant clinical implications, highlighting the importance of individualized treatment strategies based on GC subtyping. These findings provide valuable insights for guiding clinical decision-making and treatment approaches for GC.

Microfluidic systems for modeling digestive cancer: a review of recent progress

Purpose. This review aims to highlight current improvements in microfluidic devices designed for digestive cancer simulation. The review emphasizes the use of multicellular 3D tissue engineering models to understand the complicated biology of the tumor microenvironment (TME) and cancer progression. The purpose is to develop oncology research and improve digestive cancer patients' lives.Methods. This review analyzes recent research on microfluidic devices for mimicking digestive cancer. It uses tissue-engineered microfluidic devices, notably organs on a chip (OOC), to simulate human organ function in the lab. Cell cultivation on modern three-dimensional hydrogel platforms allows precise geometry, biological components, and physiological qualities. The review analyzes novel methodologies, key findings, and technical progress to explain this field's advances.Results. This study discusses current advances in microfluidic devices for mimicking digestive cancer. Micro physiological systems with multicellular 3D tissue engineering models are emphasized. These systems capture complex biochemical gradients, niche variables, and dynamic cell-cell interactions in the tumor microenvironment (TME). These models reveal stomach cancer biology and progression by duplicating the TME. Recent discoveries and technology advances have improved our understanding of gut cancer biology, as shown in the review.Conclusion. Microfluidic systems play a crucial role in modeling digestive cancer and furthering oncology research. These platforms could transform drug development and treatment by revealing the complex biology of the tumor microenvironment and cancer progression. The review provides a complete summary of recent advances and suggests future research for field professionals. The review's major goal is to further medical research and improve digestive cancer patients' lives.

Targeting JUNB to modulate M2 macrophage polarization in preeclampsia

Preeclampsia (PE) is a complex disorder affecting pregnant women, leading to significant maternal and fetal morbidity and mortality. Understanding the cellular dynamics and molecular mechanisms underlying PE is crucial for developing effective therapeutic strategies. This study utilized single-cell RNA sequencing (scRNA-seq) to delineate the cellular landscape of the placenta in PE, identifying 11 distinct cell subpopulations, with macrophages playing a pivotal role in mediating cell-cell communication. Specifically, the transcription factor JUNB was found to be a key gene in macrophages from PE samples, influencing the interaction between macrophages and both epithelial and endothelial cells. Functional experiments indicated that interference with JUNB expression promoted macrophage polarization towards an M2 phenotype, which facilitated trophoblast invasion, migration, and angiogenesis. Mechanistically, JUNB regulated the MIIP/PI3K/AKT pathway, as evidenced by gene expression analysis following JUNB knockdown. The study further demonstrated that targeting JUNB could activate the PI3K/AKT pathway by transcriptionally activating MIIP, thus promoting M2 polarization and potentially delaying the onset of PE. These findings present new insights into the pathogenesis of PE and suggest a novel therapeutic approach by modulating macrophage polarization.

Remodeling the immune microenvironment for gastric cancer therapy through antagonism of prostaglandin E2 receptor 4

Gastric cancer is highly prevalent among digestive tract tumors. Due to the intricate nature of the gastric cancer immune microenvironment, there is currently no effective treatment available for advanced gastric cancer. However, there is promising potential for immunotherapy targeting the prostaglandin E2 receptor subtype 4 (EP4) in gastric cancer. In our previous study, we identified a novel small molecule EP4 receptor antagonist called YY001. Treatment with YY001 alone demonstrated a significant reduction in gastric cancer growth and inhibited tumor metastasis to the lungs in a mouse model. Furthermore, administration of YY001 stimulated a robust immune response within the tumor microenvironment, characterized by increased infiltration of antigen-presenting cells, T cells, and M1 macrophages. Additionally, our research revealed that YY001 exhibited remarkable synergistic effects when combined with the PD-1 antibody and the clinically targeted drug apatinib, rather than fluorouracil. These findings suggest that YY001 holds great promise as a potential therapeutic strategy for gastric cancer, whether used as a standalone treatment or in combination with other drugs.

Unraveling IGFBP3-mediated m6A modification in fracture healing

BACKGROUND

This study investigates the role of IGFBP3-mediated m6A modification in regulating the miR-23a-3p/SMAD5 axis and its impact on fracture healing, aiming to provide insights into potential therapeutic targets.

METHODS

Utilizing fracture-related datasets, we identified m6A modification-related mRNA and predicted miR-23a-3p as a regulator of SMAD5. We established a mouse fracture healing model and conducted experiments, including Micro-CT, RT-qPCR, Alizarin Red staining, and Alkaline phosphatase (ALP) staining, to assess gene expression and osteogenic differentiation.

RESULTS

IGFBP3 emerged as a crucial player in fracture healing, stabilizing miR-23a-3p through m6A modification, leading to SMAD5 downregulation. This, in turn, inhibited osteogenic differentiation and delayed fracture healing. Inhibition of IGFBP3 partially reversed through SMAD5 inhibition, restoring osteogenic differentiation and fracture healing in vivo.

CONCLUSION

The IGFBP3/miR-23a-3p/SMAD5 axis plays a pivotal role in fracture healing, highlighting the relevance of m6A modification. IGFBP3's role in stabilizing miR-23a-3p expression through m6A modification offers a potential therapeutic target for enhancing fracture healing outcomes.

The regulatory role of cancer stem cell marker gene CXCR4 in the growth and metastasis of gastric cancer

Single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (bulk RNA-seq) are increasingly used for screening genes involved in carcinogenesis due to their capacity for dissecting cellular heterogeneity. This study aims to reveal the molecular mechanism of the cancer stem cells (CSCs) marker gene CXCR4 in gastric cancer (GC) growth and metastasis through scRNA-seq combined with bulk RNA-seq. GC-related scRNA-seq data were downloaded from the GEO database, followed by UMAP cluster analysis. Non-malignant cells were excluded by the K-means algorithm. Bulk RNA-seq data and clinical sample information were downloaded from the UCSC Xena database. GO and KEGG pathway analyses validated the correlation between genes and pathways. In vitro and in vivo functional assays were used to examine the effect of perturbed CXCR4 on malignant phenotypes, tumorigenesis, and liver metastasis. A large number of highly variable genes were identified in GC tissue samples. The top 20 principal components were selected, and the cells were clustered into 6 cell types. The C4 cell cluster from malignant epithelial cells might be CSCs. CXCR4 was singled out as a marker gene of CSCs. GC patients with high CXCR4 expression had poor survival. Knockdown of CXCR4 inhibited the malignant phenotypes of CSCs in vitro and curtailed tumorigenesis and liver metastasis in nude mice. CSC marker gene CXCR4 may be a key gene facilitating malignant phenotypes of CSCs, which thus promotes tumor growth and liver metastasis of GC.

Integrative analysis of cancer-associated fibroblast signature in gastric cancer

Background

CAFs regulate the signaling of GC cells by promoting their migration, invasion, and proliferation and the function of immune cells as well as their location and migration in the TME by remodeling the extracellular matrix (ECM). This study explored the understanding of the heterogeneity of CAFs in TME and laid the groundwork for GC biomarker and precision treatment development.

Methods

The scRNA-seq and bulk RNA-seq datasets were obtained from GEO and TCGA. The prognostic significance of various CAFs subtypes was investigated using ssGSEA combined with Kaplan-Meier analysis. POSTN expression in GC tissues and CAFs was detected using immunohistochemistry, immunofluorescence, and Western blotting. Differential expression analysis identified the differentially expressed genes (DEGs) between normal and tumor samples in TCGA-STAD. Pearson correlation analysis identified DEGs associated with adverse prognosis CAF subtype, and univariate Cox regression analysis determined prognostic genes associated with CAFs. LASSO regression analysis and Multivariate Cox regression were used to build a prognosis model for CAFs.

Results

We identified five CAFs subtypes in GC, with the CAF_0 subtype associated with poor prognosis. The abundance of CAF_0 correlated with T stage, clinical stage, histological type, and immune cell infiltration levels. Periostin (POSTN) exhibited increased expression in both GC tissues and CAFs and was linked to poor prognosis in GC patients. Through LASSO and multivariate Cox regression analysis, three genes (CXCR4, MATN3, and KIF24) were selected to create the CAFs-score. We developed a nomogram to facilitate the clinical application of the CAFs-score. Notably, the CAFs signature showed significant correlations with immune cells, stromal components, and immunological scores, suggesting its pivotal role in the tumor microenvironment (TME). Furthermore, CAFs-score demonstrated prognostic value in assessing immunotherapy outcomes, highlighting its potential as a valuable biomarker to guide therapeutic decisions.

Conclusion

CAF_0 subtype in TME is the cause of poor prognosis in GC patients. Furthermore, CAFs-score constructed from the CAF_0 subtype can be used to determine the clinical prognosis, immune infiltration, clinicopathological characteristics, and assessment of personalized treatment of GC patients.

Artificial intelligence for prediction of response to cancer immunotherapy

Artificial intelligence (AI) indicates the application of machines to imitate intelligent behaviors for solving complex tasks with minimal human intervention, including machine learning and deep learning. The use of AI in medicine improves health-care systems in multiple areas such as diagnostic confirmation, risk stratification, analysis, prognosis prediction, treatment surveillance, and virtual health support, which has considerable potential to revolutionize and reshape medicine. In terms of immunotherapy, AI has been applied to unlock underlying immune signatures to associate with responses to immunotherapy indirectly as well as predict responses to immunotherapy responses directly. The AI-based analysis of high-throughput sequences and medical images can provide useful information for management of cancer immunotherapy considering the excellent abilities in selecting appropriate subjects, improving therapeutic regimens, and predicting individualized prognosis. In present review, we aim to evaluate a broad framework about AI-based computational approaches for prediction of response to cancer immunotherapy on both indirect and direct manners. Furthermore, we summarize our perspectives about challenges and opportunities of further AI applications on cancer immunotherapy relating to clinical practicability.

Identification and validation of prognostic autophagy-related genes associated with immune microenvironment in human gastric cancer

Autophagy-related genes (ATGs) play critical roles in tumorigenesis and progression in gastric cancer (GC). The present study aimed to identify immune-based prognostic ATGs and verify their functions in tumor immune microenvironment (TIME) in GC. Macrophage infiltration was found to negatively correlate with prognosis in GC patients. After stratifying by infiltration levels of macrophages, we screened The Cancer Genome Atlas and Human Autophagy Database to identify the differentially expressed ATGs (DE-ATGs). Of 1,433 differentially expressed genes between the two groups, seven genes qualified as DE-ATGs. Of these, CXCR4, DLC1, and MAP1LC3C, exhibited strong prognostic prediction ability in Kaplan-Meier survival–log-rank test. High expression of these genes correlated with increased occurrence of advanced grade 3 tumors and poor prognoses. Furthermore, GSEA indicated that they were significantly associated with oncogenic and immune-related pathways. The comprehensive evaluation of TIME via GEPIA, ESTIMATE, CIBERSORT, and TIMER suggested that the three DE-ATGs were closely associated with immune condition, both in terms of immune cells and immune scores. Thus, the outcome of this study may aid in better understanding of the ATGs and their interaction with the immune microenvironment, which would allow the development of novel inhibitors, personalized treatment, and immunotherapy in gastric cancer.

Current Status of 68Ga-Pentixafor in Solid Tumours

Chemokine receptor CXCR4 is overexpressed in neoplasms and its expression is related to tumour invasion, metastasis and aggressiveness. ⁶⁸Ga-Pentixafor is used to non-invasively image the expression of CXCR4 in tumours and has been widely used in haematological malignancies. Recent evidence shows that therapies targeting CXCR4 can increase the chemosensitivity of the tumour as well as inhibit tumour metastasis and aggressiveness. ⁶⁸Ga-Pentixafor has shown promise as an elegant radiotracer to aid in the selection of patients whose tumours demonstrate CXCR4 overexpression and who therefore may benefit from novel therapies targeting CXCR4. In addition, its therapeutic partners ¹⁷⁷Lu- and ⁹⁰Y-Pentixather have been investigated in the treatment of patients with advanced haematological malignancies, and initial studies have shown a good treatment response in metabolically active lesions. ⁶⁸Ga-Pentixafor in solid tumours complements ¹⁸F-FDG by providing prognostic information and selecting patients who may benefit from therapies targeting CXCR4. This review summarises the available literature on the potential applications of ⁶⁸Ga-Pentixafor in solid tumours.

Immune Profiling in Gastric Cancer Reveals the Dynamic Landscape of Immune Signature Underlying Tumor Progression

The profiling of the tumor immune microenvironment (TIME) is critical for guiding immunotherapy strategies. However, how the composition of the immune landscape affects the tumor progression of gastric cancer (GC) is ill-defined. Here, we used mass cytometry to perform simultaneous in-depth immune profiling of the tumor, adjacent tissues, and blood cells from GC patients and revealed a unique GC tumor-immune signature, where CD8⁺ T cells were present at a lower frequency in tumor tissues compared to adjacent tissues, whereas regulatory T cells and tumor-associated macrophages (TAMs) were significantly increased, indicating strong suppressive TIME in GC. Incorporated with oncogenic genomic traits, we found that the unique immunophenotype was interactively shaped by a specific GC gene signature across tumor progression. Earlier-stage GC lesions with IFN signaling enrichment harbored significantly altered T-cell compartments while advanced GC featured by metabolism signaling activation was accumulated by TAMs. Interestingly, PD-1 expression on CD8⁺ T cells was relatively higher in earlier-stage GC patients, indicating that these patients may derive more benefits from PD-1 inhibitors. The dynamic properties of diverse immune cell types revealed by our study provide new dimensions to the immune landscape of GC and facilitate the development of novel immunotherapy strategies for GC patients.