Smooth muscle cells within the tumor microenvironment play a crucial role in cancer progression. However, their involvement in the local invasion of head and neck squamous cell carcinoma remains poorly understood. In this research, we aim to investigate the role of smooth muscle cells-mediated cell interactions in facilitating the local invasion of head and neck squamous cell carcinoma.

Single-cell sequencing data from the public databases GSE164690 and GSE181919 were utilized to identify a specific smooth muscle cells cluster. Smooth muscle cells were isolated from tumor microenvironment of head and neck squamous cell carcinoma. PHLDA1 expression in smooth muscle cells was assessed through immunofluorescence staining. The role of THBS1 was investigated through in vitro studies.

PHLDA1-positive smooth muscle cells were significantly enriched in head and neck squamous cell carcinoma. PHLDA1 promoted the expression of THBS1 in smooth muscle cells. In vitro, THBS1 facilitated head and neck squamous cell carcinoma migration and invasion through SDC1 receptor.

PHLDA1-positive smooth muscle cells play a critical role in head and neck squamous cell carcinoma invasion through THBS1. Targeting PHLDA1-positive smooth muscle cells or THBS1 may offer a promising therapeutic approach for head and neck squamous cell carcinoma treatment.

Glioblastoma, one of the most aggressive and heterogeneous malignant tumors, presents significant challenges for clinical management due to its cellular and metabolic complexity. This review integrates recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to elucidate glioblastoma's cellular heterogeneity and metabolic reprogramming. Diverse cellular subpopulations, including malignant proliferative cells, stem-like cells, mesenchymal-like cells, and immune-related cells, contribute to tumor progression, treatment resistance, and microenvironmental interactions. Spatial transcriptomics has further revealed distinct spatial distributions of these subpopulations, highlighting differences in metabolic activities between the tumor core and periphery. Key metabolic adaptations, such as enhanced glycolysis, fatty acid oxidation, and glutamine metabolism, play critical roles in supporting tumor growth, immune evasion, and therapeutic resistance. Targeting these metabolic pathways, especially in combination with immunotherapy, represents a promising avenue for glioblastoma treatment. This review emphasizes the importance of integrating single-cell and spatial multi-omics technologies to decode glioblastoma's metabolic landscape and explore novel therapeutic strategies. By addressing current challenges, such as metabolic redundancy and spatiotemporal dynamics, this work provides insights into advancing precision medicine for glioblastoma.

Cancer-associated fibroblasts (CAFs) drive tumor progression through restructuring of the tumor microenvironment. This investigation aim to elucidate the function of molecular subtypes (MS) derived from cancer cells communication with CAFs, depicting the hallmarks of the tumor microenvironment and precise bladder cancer (BLCA) treatment. The BLCA data from TCGA and several external sources are utilized to generate a novel ligand, receptor, and transcription factor (LRT) associated molecular subtype and their corresponding score (LRT score). The LRT-mediated molecular subtype is identified via unsupervised clustering. LRT score is measured by principal component analysis. Then, the association of LRT clusters to established MS, immunophenotypes, and medical endpoints, together with BLCA treatment strategies is investigated. Two LRT clusters (A and B) are identified. LRT cluster (LRT score) can precisely propose immunophenotypes, classical MS, clinical outcomes, and BLCA therapeutic strategies. Cluster B (Low LRT score) represent a basal subtype and inflamed phenotype specified by high immunity against tumors and unfavorable clinical outcomes. Furthermore, it is highly sensitive to cancer immunotherapy; however, it has low sensitivity to antiangiogenic and targeted therapies. The novel LRT clusters with a strong association with biological characteristics and precise BLCA treatment strategies are derived from the communication between cancer cells and cancer-associated fibroblasts. The LRT may be a useful clinician tool for developing individualized treatment strategies.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in adults, characterized by rapid proliferation, extensive infiltration, and significant intratumoral heterogeneity. Despite advancements in conventional treatments, including surgery, radiotherapy, and chemotherapy, the prognosis for GBM patients remains poor, with a median survival of approximately 15 months. Immunotherapy has emerged as a promising alternative; however, the unique biological and immunological features, including its immunosuppressive tumor microenvironment (TME) and low mutational burden, render it resistant to many immunotherapeutic strategies. This review explores the key challenges in GBM immunotherapy, focusing on immune evasion mechanisms, the blood-brain barrier (BBB), and the TME. Immune checkpoint inhibitors and CAR-T cells have shown promise in preclinical models but have limited clinical success due to antigen heterogeneity, immune cell exhaustion, and impaired trafficking across the BBB. Emerging strategies, including dual-targeting CAR-T cells, engineered immune cells secreting therapeutic molecules, and advanced delivery systems to overcome the BBB, show potential for enhancing treatment efficacy. Addressing these challenges is crucial for improving GBM immunotherapy outcomes.

Intestinal barrier dysfunction is a prevalent and varied manifestation of acute pancreatitis (AP). Molecular mechanisms underlying the early intestinal barrier in AP remain poorly understood.

To explore the biological processes and mechanisms of intestinal injury associated with AP, and to find potential targets for early prevention or treatment of intestinal barrier injury.

This study utilized single-cell RNA sequencing of the small intestine, alongside in vitro and in vivo experiments, to examine intestinal barrier function homeostasis during the early stages of AP and explore involved biological processes and potential mechanisms.

Seventeen major cell types and 33232 cells were identified across all samples, including normal, AP1 (4x caerulein injections, animals sacrificed 2 h after the last injection), and AP2 (8x caerulein injections, animals sacrificed 4 h after the last injection). An average of 980 genes per cell was found in the normal intestine, compared to 927 in the AP1 intestine and 1382 in the AP2 intestine. B cells, dendritic cells, mast cells (MCs), and monocytes in AP1 and AP2 showed reduced numbers compared to the normal intestine. Enterocytes, brush cells, enteroendocrine cells, and goblet cells maintained numbers similar to the normal intestine, while cytotoxic T cells and natural killer (NK) cells increased. Enterocytes in early AP exhibited elevated programmed cell death and intestinal barrier dysfunction but retained absorption capabilities. Cytotoxic T cells and NK cells showed enhanced pathogen-fighting abilities. Activated MCs, secreted chemokine (C-C motif) ligand 5 (CCL5), promoted neutrophil and macrophage infiltration and contributed to barrier dysfunction.

These findings enrich our understanding of biological processes and mechanisms in AP-associated intestinal injury, suggesting that CCL5 from MCs is a potential target for addressing dysfunction.

Glioblastomas are the most prevalent primary brain tumors and are associated with a dramatically poor prognosis. Despite an intensive treatment approach, including maximal surgical tumor removal followed by radio- and chemotherapy, the median survival for glioblastoma patients has remained around 18 months for decades. Glioblastoma is distinguished by its highly complex mechanisms of immune evasion and pronounced heterogeneity. This variability is apparent both within the tumor itself, which can exhibit multiple phenotypes simultaneously, and in its surrounding microenvironment. Another key feature of glioblastoma is its "cold" microenvironment, characterized by robust immunosuppression. Recent advances in single-cell RNA sequencing have uncovered new promising insights, revealing previously unrecognized aspects of this tumor. In this review, we consolidate current knowledge on glioblastoma cells and its microenvironment, with an emphasis on their biological properties and unique patterns of molecular communication through signaling pathways. The evidence underscores the critical need for personalized poly-immunotherapy and other approaches to overcome the plasticity of glioblastoma stem cells. Analyzing the tumor microenvironment of individual patients using single-cell transcriptomics and implementing a customized immunotherapeutic strategy could potentially improve survival outcomes for those facing this formidable disease.

Glioma, being one of the malignant tumors with the highest mortality rate globally, has an unclear pathogenesis, and the existing treatment effects still have certain limitations. The tumor microenvironment (TME) plays an important role in the occurrence, development, and recurrence of glioma. As one of the important regulatory factors of TME, the gut microbiota can regulate the progression of glioma not only by interacting with the brain through the brain-gut axis but also by influencing the tumor immune microenvironment (TIME) and inflammatory microenvironment. Recent studies have identified the gut microbiota and TME as potential therapeutic targets for glioma. This paper aims to summarize the role of the gut microbiota in TME, the association between them and glioma, and the potential of developing new intervention measures by targeting the gut microbiota. Understanding the involvement process of the gut microbiota in glioma may pave the way for the development of effective treatment methods that can regulate TME and prevent disease progression.

Fibroinflammation refers to the highly integrated fibrogenic and inflammatory responses mediated by the concerted function of fibroblasts and innate immune cells in response to tissue perturbation. This process underlies the desmoplastic remodelling of the tumour microenvironment and thus plays an important role in tumour initiation, growth and metastasis. More specifically, fibroinflammation alters the biochemical and biomechanical signalling in malignant cells to promote their proliferation and survival and further supports an immunosuppressive microenvironment by polarizing the immune status of tumours. Additionally, the presence of fibroinflammation is often associated with therapeutic resistance. As such, there is increasing interest in targeting this process to normalize the tumour microenvironment and thus enhance the treatment of solid tumours. Herein, we review advances made in unravelling the complexity of cancer-associated fibroinflammation that can inform the rational design of therapies targeting this.

Background and Objective: The discovery of novel molecular biomarkers via next-generation sequencing technologies has revolutionized how glioblastomas (GBMs) are classified nowadays. This has resulted in more precise diagnostic, prognostic, and therapeutic approaches to address this malignancy. The present work examines the applications of single-cell RNA sequencing (scRNA-seq) in GBM, focusing on its potential to address tumor complexity and therapeutic resistance and improve patient outcomes. Methods: A scoping review of original studies published between 2009 and 2024 was conducted using the PUBMED and EMBASE databases. Studies in English or Spanish related to single-cell analysis and GBM were included. Key Findings: The database search yielded 453 publications. Themes related to scRNA-seq applied for the diagnosis, prognosis, treatment, and understanding of the cancer biology of GBM were used as criteria for article selection. Of the 24 studies that were included in the review, 11 focused on the tumor microenvironment and cell subpopulations in GBM samples, 5 investigated the use of sequencing to elucidate the GBM cancer biology, 3 examined disease prognosis using sequencing models, 3 applied translational research through scRNA-seq, and 2 addressed treatment-related problems in GBM elucidated by scRNA-seq. Conclusions: This scoping review explored the various clinical applications of scRNA-seq technologies in approaching GBM. The findings highlight the utility of this technology in unraveling the complex cellular and immune landscapes of GBM, paving the way for improved diagnosis and personalized treatments. This cutting-edge approach might strengthen treatment strategies against tumor progression and recurrence, setting the stage for multi-targeted interventions that could significantly improve outcomes for patients with aggressive, treatment-resistant GBMs.

The tumor microenvironment is a dynamic and complex three-dimensional network comprising the extracellular matrix and diverse non-cancerous cells, including fibroblasts, adipocytes, endothelial cells and various immune cells (lymphocytes T and B, NK cells, dendritic cells, monocytes/macrophages, myeloid-derived suppressor cells, and innate lymphoid cells). A constantly and rapidly growing number of studies highlight the critical role of these cells in shaping cancer survival, metastatic potential and therapy resistance. This review provides a synthesis of current knowledge on the modulating role of the cellular microenvironment in cancer progression and response to treatment.

Despite multimodal therapies, the treatment of glioblastoma remains challenging. In addition to the very complex mechanisms of cancer cells, including specialized phenotypes that enable them to proliferate, invade tissues, and evade immunosurveillance, they exhibit a pronounced resistance to chemo- and radiotherapy. More advanced tumors create a hypoxic environment that supports their proliferation and survival, while robust angiogenesis ensures a constant supply of nutrients. In GBM, these structures are very pronounced and contribute to the creation and maintenance of a highly immunosuppressive microenvironment that promotes tumor growth and immune escape. In addition, the high accumulation of immunosuppressive tumor-infiltrating leukocytes and other cells, the pronounced expression of immune checkpoint molecules, and the low mutational burden, i.e., the low number of neoantigens, are hallmarks of GBM and contribute to the challenge of therapeutic approaches. Here, we review a number of mechanisms that GBM exploits to support tumor growth and potential treatments. These include new chemotherapeutics, tumor treating fields, and small molecules, including compounds targeting angiogenesis or blockers of tyrosine kinases that inhibit tumor cell proliferation and survival. In addition, we focus on immunotherapies such as immune checkpoint blockade or cell therapies, in particular vaccination with dendritic cells and CAR-T cells, which can either kill GBM cells directly or bypass immunosuppression by modulating the tumor microenvironment or boosting the patient's own immune response.

The field of immunology has traditionally focused on immune checkpoint modulation of adaptive immune cells. However, many malignancies such as glioblastoma are mostly devoid of T cells and rather are enriched with immunosuppressive myeloid cells of the innate immune system. While some immune checkpoint targets are shared between adaptive and innate immunity, myeloid-specific checkpoints could also serve as potential therapeutics. To better understand the impact of immune checkpoint blockade on myeloid cells, we systematically summarize the current literature focusing on the direct immunological effects of PD-L1/PD-1, CD24/Siglec-10, collagen/LAIR-1, CX3CL1/CX3CR1, and CXCL10/CXCR3. By synthesizing the molecular mechanisms and the translational implications, we aim to prioritize agents in this category of therapeutics for glioblastoma.

Spatial transcriptomics (ST) represents a revolutionary approach in molecular biology, providing unprecedented insights into the spatial organization of gene expression within tissues. This review aims to elucidate advancements in ST technologies, their computational tools, and their pivotal applications in neuroscience. It is begun with a historical overview, tracing the evolution from early image-based techniques to contemporary sequence-based methods. Subsequently, the computational methods essential for ST data analysis, including preprocessing, cell type annotation, spatial clustering, detection of spatially variable genes, cell-cell interaction analysis, and 3D multi-slices integration are discussed. The central focus of this review is the application of ST in neuroscience, where it has significantly contributed to understanding the brain's complexity. Through ST, researchers advance brain atlas projects, gain insights into brain development, and explore neuroimmune dysfunctions, particularly in brain tumors. Additionally, ST enhances understanding of neuronal vulnerability in neurodegenerative diseases like Alzheimer's and neuropsychiatric disorders such as schizophrenia. In conclusion, while ST has already profoundly impacted neuroscience, challenges remain issues such as enhancing sequencing technologies and developing robust computational tools. This review underscores the transformative potential of ST in neuroscience, paving the way for new therapeutic insights and advancements in brain research.

Glioma evolution is governed by a multitude of dynamic interactions between tumor cells and heterogenous neighboring, non-cancerous cells. This complex ecosystem, termed the tumor microenvironment (TME), includes diverse immune cell types that have gained increasing attention for their critical and paradoxical roles in tumor control and tumorigenesis. Recent work has revealed that the cellular composition and functional state of immune cells in the TME can evolve extensively depending on the tumor stage and intrinsic features of surrounding glioma cells. Concurrently, adaptations to the glioma cellular phenotype, including activation of various cellular states, occur in the context of these immune cell alterations. In this review, we summarize important features of the immune TME that play key roles during each stage of glioma progression, from initiation to immune escape, invasion and recurrence. Understanding the complex interplay between tumor and immune cells is critical for the development of effective immunotherapies for glioma treatment.

Fatty acid binding protein 7 (FABP7) is a multifunctional chaperone involved in lipid metabolism and signaling. It is primarily expressed in astrocytes and neural stem cells (NSCs), as well as their derived malignant glioma cells within the central nervous system. Despite growing evidence for FABP7's tumor-intrinsic onco-metabolic functions, its mechanistic role in regulating the brain tumor immune microenvironment (TIME) and its impact on prognosis at the molecular level remain incompletely understood. Utilizing combined transcriptome profiling and pan-cancer analysis approaches, we report that FABP7 mediates the expression of multiple onco-immune drivers, collectively impacting tumor immunity and clinical outcomes across brain cancer subtypes. An analysis of a single-cell expression atlas revealed that FABP7 is predominantly expressed in the glial lineage and malignant cell populations in gliomas, with nuclear localization in their parental NSCs. Pathway and gene enrichment analysis of RNA sequencing data from wild-type (WT) and Fabp7-knockout (KO) mouse brains, alongside control (CTL) and FABP7-overexpressing (FABP7 OV) human astrocytes, revealed a more pronounced effect of FABP7 levels on multiple cancer-associated pathways. Notably, genes linked to brain cancer progression and tumor immunity (ENO1, MUC1, COL5A1, and IL11) were significantly downregulated (>2-fold) in KO brain tissue but were upregulated in FABP7 OV astrocytes. Furthermore, an analysis of data from The Cancer Genome Atlas (TCGA) showed robust correlations between the expression of these factors, as well as FABP7, and established glioma oncogenes (EGFR, BRAF, NF1, PDGFRA, IDH1), with stronger associations seen in low-grade glioma (LGG) than in glioblastoma (GBM). TIME profiling also revealed that the expression of FABP7 and the genes that it modulates was significantly associated with prognosis and survival, particularly in LGG patients, by influencing the infiltration of immunosuppressive cell populations within tumors. Overall, our findings suggest that FABP7 acts as an intracellular regulator of pro-tumor immunomodulatory genes, exerting a synergistic effect on the TIME and clinical outcomes in brain cancer subtypes.

Adult glioblastoma (GBM) is a highly aggressive primary brain tumor, accounting for nearly half of all malignant brain tumors, with a median survival rate of only 8 months. Treatment for GBM is largely ineffective due to the highly invasive nature and complex tumor composition of this malignancy. MicroRNAs (miRNA) are short, non-coding RNAs that regulate gene expression by binding to messenger RNAs (mRNA). While specific miRNA have been associated with GBM, their precise roles in tumor development and progression remain unclear. In this study, the analysis of miRNA expression data from 743 adult GBM cases and 59 normal brain samples identified 94 downregulated miRNA and 115 upregulated miRNA. Many of these miRNA were previously linked to GBM pathology, confirming the robustness of our approach, while we also identified novel miRNA that may act as potential regulators in GBM. By integrating miRNA predictions with gene expression data, we were able to associate downregulated miRNA with tumor microenvironment factors, including extracellular matrix remodeling and signaling pathways involved in tumor initiation, while upregulated miRNA were found to be associated with essential neuronal processes. This analysis highlights the significance of miRNA in GBM and serves as a foundation for further investigation.

Epithelial ovarian cancer is a significant global health issue among women. Diagnosis and treatment pose challenges due to difficulties in predicting patient responses to therapy, primarily stemming from gaps in understanding tumor chemoresistance mechanisms. Recent advancements in transcriptomic technologies like single-cell RNA sequencing and spatial transcriptomics have greatly improved our understanding of ovarian cancer intratumor heterogeneity and tumor microenvironment composition. Spatial transcriptomics, in particular, comprises a plethora of technologies that enable the detection of hundreds of transcriptomes and their spatial distribution within a histological section, facilitating the study of cell types, states, and interactions within the tumor and its microenvironment. Studies investigating the spatial distribution of gene expression in ovarian cancer masses have identified specific features that impact prognosis and therapy outcomes. Emerging evidence suggests that specific spatial patterns of tumor cells and their immune and non-immune microenvironment significantly influence therapy response, as well as the behavior and progression of primary tumors and metastatic sites. The importance of spatially contextualizing ovarian cancer transcriptomes is underscored by these findings, which will advance our understanding and therapeutic approaches for this complex disease.

Epidermal growth factor receptor wild type lung adenocarcinoma (EGFRWT LUAD) still has limited treatment options and unsatisfactory clinical outcomes. Ferroptosis, as a form of cell death, has been reported to play a dual role in regulating tumor cell survival. In this study, we constructed a 3-ferroptosis-gene signature, FeSig, and verified its accuracy and efficacy in predicting EGFRWT LUAD prognosis at both the RNA and protein levels. Patients with higher FeSig scores were found to have worse clinical outcomes. Additionally, we explored the relationship between FeSig and tumor microenvironment, revealing that enhanced interactions between fibroblasts and tumor cells in FeSighigh patients causing tumor resistance to ferroptosis. To address this challenge, we screened potential drugs from NCI-60 (The US National Cancer Institute 60 human tumour cell line anticancer drug screen) and Connectivity map database, ultimately identifying 6-mercatopurine (6-MP) as a promising candidate. Both in vitro and in vivo experiments demonstrated its efficacy in treating FeSighigh EGFRWT LUAD tumor models. In summary, we develop a novel FeSig for predicting prognosis and guiding drug application.

Diffuse high-grade gliomas are the most common malignant adult neuroepithelial tumors in humans and a leading cause of cancer-related death worldwide. The advancement of high throughput transcriptome sequencing technology enables rapid and comprehensive acquisition of transcriptome data from target cells or tissues. This technology aids researchers in understanding and identifying critical therapeutic targets for the prognosis and treatment of diffuse high-grade glioma.

Spatial transcriptomics was conducted on two cases of isocitrate dehydrogenase (IDH) wild-type diffuse high-grade glioma (Glio-IDH-wt) and two cases of IDH-mutant diffuse high-grade glioma (Glio-IDH-mut). Gene set enrichment analysis and clustering analysis were employed to pinpoint differentially expressed genes (DEGs) involved in the progression of diffuse high-grade gliomas. The spatial distribution of DEGs in the spatially defined regions of human glioma tissues was overlaid in the t-distributed stochastic neighbor embedding (t-SNE) plots.

We identified a total of 10,693 DEGs, with 5,677 upregulated and 5,016 downregulated, in spatially defined regions of diffuse high-grade gliomas. Specifically, SPP1, IGFBP2, CALD1, and TMSB4X exhibited high expression in carcinoma regions of both Glio-IDH-wt and Glio-IDH-mut, and 3 upregulated DEGs (SMOC1, APOE, and HIPK2) and 4 upregulated DEGs (PPP1CB, UBA52, S100A6, and CTSB) were only identified in tumor regions of Glio-IDH-wt and Glio-IDH-mut, respectively. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) enrichment analyses revealed that upregulated DEGs were closely related to PI3K/Akt signaling pathway, virus infection, and cytokine-cytokine receptor interaction. Importantly, the expression of these DEGs was validated using GEPIA databases. Furthermore, the study identified spatial expression patterns of key regulatory genes, including those involved in protein post-translational modification and RNA binding protein-encoding genes, with spatially defined regions of diffuse high-grade glioma.

Spatial transcriptome analysis is one of the breakthroughs in the field of medical biotechnology as this can map the analytes such as RNA information in their physical location in tissue sections. Our findings illuminate previously unexplored spatial expression profiles of key biomarkers in diffuse high-grade glioma, offering novel insight for the development of therapeutic strategies in glioma.

Microscopic examination of cells in their tissue context has been the driving force behind diagnostic histopathology over the past two centuries. Recently, the rise of advanced molecular biomarkers identified through single cell profiling has increased our understanding of cellular heterogeneity in cancer but have yet to significantly impact clinical care. Spatial technologies integrating molecular profiling with microenvironmental features are poised to bridge this translational gap by providing critical in situ context for understanding cellular interactions and organization. Here, we review how spatial tools have been used to study tumor ecosystems and their clinical applications. We detail findings in cell-cell interactions, microenvironment composition, and tissue remodeling for immune evasion and therapeutic resistance. Additionally, we highlight the emerging role of multi-omic spatial profiling for characterizing clinically relevant features including perineural invasion, tertiary lymphoid structures, and the tumor-stroma interface. Finally, we explore strategies for clinical integration and their augmentation of therapeutic and diagnostic approaches.

The extracellular matrix (ECM) is a complex, dynamic network of multiple macromolecules that serve as a crucial structural and physical scaffold for neighboring cells. In the tumor microenvironment (TME), ECM proteins play a significant role in mediating cellular communication between cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs). Revealing the ECM modification of the TME necessitates the intricate signaling cascades that transpire among diverse cell populations and ECM proteins. The advent of single-cell sequencing has enabled the identification and refinement of specific cellular subpopulations, which has substantially enhanced our comprehension of the intricate milieu and given us a high-resolution perspective on the diversity of ECM proteins. However, it is essential to integrate single-cell data and establish a coherent framework. In this regard, we present a comprehensive review of the relationships among ECM, TAMs, and CAFs. This encompasses insights into the ECM proteins released by TAMs and CAFs, signaling integration in the TAM-ECM-CAF axis, and the potential applications and limitations of targeted therapies for CAFs. This review serves as a reliable resource for focused therapeutic strategies while highlighting the crucial role of ECM proteins as intermediates in the TME.

The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co-metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3-kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/β-catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti-tumor immunity, pro-tumor immunity, and microbial-derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM-related mechanisms and TM-based treatment in cancer.

Gliomas, the predominant form of brain cancer, comprise diverse malignant subtypes with limited curative therapies available. The insufficient understanding of their molecular diversity and evolutionary processes hinders the advancement of new treatments. Technical complexities associated with formalin-fixed paraffin-embedded (FFPE) clinical samples hinder molecular-level analyses of gliomas. Current single-cell RNA sequencing (scRNA-seq) platforms are inadequate for large-scale clinical applications. In this study, automated snRandom-seq is developed, a high-throughput single-nucleus total RNA sequencing platform optimized for archival FFPE samples. This platform integrates automated single-nucleus isolation and droplet barcoding systems with the random primer-based scRNA-seq chemistry, accommodating a broad spectrum of sample types. The automated snRandom-seq is applied to analyze 116 492 single nuclei from 17 FFPE samples of various glioma subtypes, including rare clinical samples and matched primary-recurrent glioblastomas (GBMs). The study provides comprehensive insights into the molecular characteristics of gliomas at the single-cell level. Abundant non-coding RNAs (ncRNAs) with distinct expression profiles across different glioma clusters and uncovered promising recurrence-related targets and pathways in primary-recurrent GBMs are identified. These findings establish automated snRandom-seq as a robust tool for scRNA-seq of FFPE samples, enabling exploration of molecular diversities and tumor evolution. This platform holds significant implications for large-scale integrative and retrospective clinical research.

Histopathologic examinations of primary central nervous system lymphoma (PCNSL) reveal concentric accumulation of lymphocytes in the perivascular area with fibrosis. However, the nature of this fibrosis in "stiff" PCNSL remains unclear. We have encountered some PCNSLs with hard masses as surgical findings. This study investigated the dense fibrous status and tumor microenvironment of PCNSLs with or without stiffness. We evaluated by silver-impregnation nine PCNSLs with stiffness and 26 PCNSLs without stiffness. Six of the nine stiff PCNSLs showed pathological features of prominent fibrosis characterized by aggregation of reticulin fibers, and collagen accumulations. Alpha-smooth muscle actin (αSMA)-positive spindle cells as a cancer-associated fibroblast, the populations of T lymphocytes, and macrophages were compared between fibrous and control PCNSLs. Fibrous PCNSLs included abundant αSMA-positive cells in both intra- and extra-tumor environments (5/6, 87% and 3/6, 50%, respectively). Conversely, only one out of the seven control PCNSL contained αSMA-positive cells in the intra-tumoral area. Furthermore, the presence of extra-tumoral αSMA-positive cells was associated with infiltration of T lymphocytes and macrophages. In conclusion, recognizing the presence of dense fibrosis in PCNSL can provide insights into the tumor microenvironment. These results may help stratify patients with PCNSL and improve immunotherapies for these patients.

Glioma is the most prevalent primary malignant tumor in the central nervous system (CNS). It represents a diverse group of brain malignancies characterized by the presence of various cancer cell types as well as an array of noncancerous cells, which together form the intricate glioma tumor microenvironment (TME). Understanding the interactions between glioma cells/glioma stem cells (GSCs) and these noncancerous cells is crucial for exploring the pathogenesis and development of glioma. To invesigate these interactions requires in vitro co-culture models that closely mirror the actual TME in vivo. In this review, we summarize the two- and three-dimensional in vitro co-culture model systems for glioma-TME interactions currently available. Furthermore, we explore common glioma-TME cell interactions based on these models, including interactions of glioma cells/GSCs with endothelial cells/pericytes, microglia/macrophages, T cells, astrocytes, neurons, or other multi-cellular interactions. Together, this review provides an update on the glioma-TME interactions, offering insights into glioma pathogenesis.

Gliomas are the most common and aggressive type of primary brain tumor, with a poor prognosis despite current treatment approaches. Understanding the molecular mechanisms underlying glioma development and progression is critical for improving therapies and patient outcomes.

The current study comprehensively analyzed large-scale single-cell RNA sequencing and bulk RNA sequencing of glioma samples. By utilizing a series of advanced computational methods, this integrative approach identified the gene UPP1 (Uridine Phosphorylase 1) as a novel driver of glioma tumorigenesis and immune evasion.

High levels of UPP1 were linked to poor survival rates in patients. Functional experiments demonstrated that UPP1 promotes tumor cell proliferation and invasion and suppresses anti-tumor immune responses. Moreover, UPP1 was found to be an effective predictor of mutation patterns, drug response, immunotherapy effectiveness, and immune characteristics.

These findings highlight the power of combining diverse machine learning methods to identify valuable clinical markers involved in glioma pathogenesis. Identifying UPP1 as a tumor growth and immune escape driver may be a promising therapeutic target for this devastating disease.

Recent studies have identified the presence of cancer-associated fibroblasts (CAFs) within glioblastoma (GBM), yet their biological roles and underlying mechanisms remain poorly understood. This study aimed to construct a CAF-related prognostic model to guide patient prognosis and treatment strategies.

We employed various bioinformatics methods, including enrichment analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Lasso regression analysis, and machine learning techniques such as XGBoost and Random Forest, to develop a novel risk index termed CAFscore. Patients were stratified into high and low CAFscore groups for subsequent survival analysis. The area under the curve (AUC) and concordance index (C-index) for CAFscore were calculated and compared against other clinical characteristics and existing prognostic models. Drug sensitivity assessments were conducted using the Oncopredict package. Functional validation of key genes was performed through scratch and invasion assays in GBM cells.

Our analyses revealed four core CAF-related genes, leading to the establishment of CAFscore. Notably, patients in the high CAFscore group exhibited significantly reduced survival and exhibited enrichment in epithelial-mesenchymal transition (EMT) and inflammation response pathways. Furthermore, CAFscore showed a significant negative correlation with the sensitivity to irinotecan and its analogs, while demonstrating a positive correlation with sensitivity to 505,124 (a TGFβRI inhibitor). LRP10 emerged as a central gene within the CAFscore, displaying markedly elevated expression in GBM and a strong association with CAF infiltration. Silencing LRP10 significantly inhibited the invasive capabilities of GBM cells.

This study presented the first CAF related prognostic model (CAFscore) in GBM, and demonstrated that the model could effectively guide patient prognosis and potentially inform personalized treatment strategies. The core gene of CAFscore, LRP10, was significantly overexpressed in GBM and might play a pivotal role in regulating CAF infiltration as well as tumor invasion and metastasis, highlighting LRP10 as a promising therapeutic target for GBM management.

Glioblastoma recurrence is currently inevitable despite extensive standard-of-care treatment. In preclinical studies, an alternative strategy of targeting tumor-associated macrophages and microglia through CSF-1R inhibition was previously found to regress established tumors and significantly increase overall survival. However, recurrences developed in ∼50% of mice in long-term studies, which were consistently associated with fibrotic scars. This fibrotic response is observed following multiple anti-glioma therapies in different preclinical models herein and in patient recurrence samples. Multi-omics analyses of the post-treatment tumor microenvironment identified fibrotic areas as pro-tumor survival niches that encapsulated surviving glioma cells, promoted dormancy, and inhibited immune surveillance. The fibrotic treatment response was mediated by perivascular-derived fibroblast-like cells via activation by transforming growth factor β (TGF-β) signaling and neuroinflammation. Concordantly, combinatorial inhibition of these pathways inhibited treatment-associated fibrosis, and significantly improved survival in preclinical trials of anti-colony-stimulating factor-1 receptor (CSF-1R) therapy.

Glioblastoma remains one of the deadliest brain malignancies. First-line therapy consists of maximal surgical tumor resection, accompanied by chemotherapy and radiotherapy. Malignant cells escape surgical resection by migrating into the surrounding healthy brain tissue, where they give rise to the recurrent tumor. Based on gene expression, tumor cores can be subtyped into mesenchymal, proneural, and classical tumors, each being associated with differences in genetic alterations and cellular composition. In contrast, the adjacent brain parenchyma where infiltrating malignant cells escape surgical resection is less characterized in patients. Using spatial transcriptomics (n = 11), we show that malignant cells within proneural or mesenchymal tumor cores display spatially organized differences in gene expression, although such differences decrease within the infiltrated brain tissue. Malignant cells residing in infiltrated brain tissue have increased expression of genes related to neurodevelopmental pathways and glial cell differentiation. Our findings provide an updated view of the spatial landscape of glioblastomas and further our understanding of the malignant cells that infiltrate the healthy brain, providing new avenues for the targeted therapy of these cells after surgical resection.

The intrinsic oncogenic mechanisms and properties of the tumor microenvironment (TME) have been extensively investigated. Primary features of the TME include metabolic reprogramming, hypoxia, chronic inflammation, and tumor immunosuppression. Previous studies suggest that senescence-associated secretory phenotypes that mediate intercellular information exchange play a role in the dynamic evolution of the TME. Specifically, hypoxic adaptation, metabolic dysregulation, and phenotypic shifts in immune cells regulated by cellular senescence synergistically contribute to the development of an immunosuppressive microenvironment and chronic inflammation, thereby promoting the progression of tumor events. This review provides a comprehensive summary of the processes by which cellular senescence regulates the dynamic evolution of the tumor-adapted TME, with focus on the complex mechanisms underlying the relationship between senescence and changes in the biological functions of tumor cells. The available findings suggest that components of the TME collectively contribute to the progression of tumor events. The potential applications and challenges of targeted cellular senescence-based and combination therapies in clinical settings are further discussed within the context of advancing cellular senescence-related research.

Tumor microenvironment (TME) has been demonstrated to play a significant role in tumor initiation, progression, and metastasis. Cancer-associated fibroblasts (CAFs) are the major component of TME and exhibit heterogeneous properties in their communication with tumor cells. This heterogeneity of CAFs can be attributed to various origins, including quiescent fibroblasts, mesenchymal stem cells (MSCs), adipocytes, pericytes, endothelial cells, and mesothelial cells. Moreover, single-cell RNA sequencing has identified diverse phenotypes of CAFs, with myofibroblastic CAFs (myCAFs) and inflammatory CAFs (iCAFs) being the most acknowledged, alongside newly discovered subtypes like antigen-presenting CAFs (apCAFs). Due to these heterogeneities, CAFs exert multiple functions in tumorigenesis, cancer stemness, angiogenesis, immunosuppression, metabolism, and metastasis. As a result, targeted therapies aimed at the TME, particularly focusing on CAFs, are rapidly developing, fueling the promising future of advanced tumor-targeted therapy.

Despite advances in surgery, radiotherapy and immunotherapy, the mortality rate for gastric cancer remains one of the highest in the world. A large body of evidence has demonstrated that cancer-associated fibroblasts (CAFs), as core members of the stroma, can secrete cytokines, proteins and exosomes to create a tumour microenvironment that is conducive to cancer cell survival. CAFs can also interact with cancer cells to form a complex signalling network, enabling cancer cells to more easily metastasise to other organs and tissues in the body and develop metastatic foci. In this review, we provide an overview of the CAFs concept and activators. We focus on elucidating their effects on immune cells, intratumoural vasculature, extracellular matrix, as well as cancer cell activity, metastatic power and metabolism, and on enhancing the metastatic ability of cancer cells through activation of JAK/STAT, NF/κB and CXCL12/CXCR4. Various therapeutic agents targeting CAFs are also under development and are expected to improve the prognosis of gastric cancer in combination with existing treatment options.

Glioblastoma (GBM) is a highly aggressive and malignant brain tumor with limited therapeutic options and a poor prognosis. Despite current treatments, the invasive nature of GBM often leads to recurrence. A promising alternative strategy is to harness the potential of the immune system against tumor cells. Our previous data showed that the BVax (B cell-based vaccine) can induce therapeutic responses in preclinical models of GBM. In this study, we aimed to characterize the antigenic reactivity of BVax-derived Abs and evaluate their therapeutic potential. We performed immunoproteomics and functional assays in murine models and samples from patients with GBM. Our investigations revealed that BVax distributed throughout the GBM tumor microenvironment and then differentiated into Ab-producing plasmablasts. Proteomics analyses indicated that the Abs produced by BVax had unique reactivity, predominantly targeting factors associated with cell motility and the extracellular matrix. Crucially, these Abs inhibited critical processes such as GBM cell migration and invasion. These findings provide valuable insights into the therapeutic potential of BVax-derived Abs for patients with GBM, pointing toward a novel direction for GBM immunotherapy.

Cancer associated fibroblasts (CAF), an important cancer-promoting and immunosuppressive component of the tumor immune microenvironment (TIME), have recently been found to infiltrate adult diffuse highest-grade gliomas (ADHGG) (gliomas of grade IV).

Gene expression and clinical data of ADHGG patients were obtained from the CGGA and TCGA databases. Consensus clustering was used to identify CAF subtypes based on CAF key genes acquired from single-cell omics and spatial transcriptomomics. CIBERSORT, ssGSEA, MCPcounter, and ESTIMATE analyses were used to assess the TIME of GBM. Survival analysis, drug sensitivity analysis, TCIA database, TIDE and cMap algorithms were used to compare the prognosis and treatment response between patients with different CAF subtypes. An artificial neural network (ANN) model based on random forest was constructed to exactly identify CAF subtypes, which was validated in a real-world patient cohort of ADHGG.

Consensus clustering classified ADHGG into two CAF subtypes. Compared with subtype B, patients with ADHGG subtype A had a poorer prognosis, worse responsiveness to immunotherapy and radiotherapy, higher CAF infiltration in TIME, but higher sensitivity to temozolomide. Furthermore, patients with subtype A had a much lower proportion of IDH mutations. Finally, the ANN model based on five genes (COL3A1, COL1A2, CD248, FN1, and COL1A1) could exactly discriminate CAF subtypes, and the validation of the real-world cohort indicated consistent results with the bioinformatics analyses.

This study revealed a novel CAF subtype to distinguish ADHGG patients with different prognosis and treatment responsiveness, which may be helpful for accurate clinical decision-making of ADHGG.

Cancer-associated fibroblasts (CAFs) are the prominent cell type in the tumor microenvironment (TME), and CAF subsets have been identified in various tumors. However, how CAFs spatially coordinate other cell populations within the liver TME to promote cancer progression remains unclear.

We combined multi-region proteomics (6 patients, 24 samples), 10X Genomics Visium spatial transcriptomics (11 patients, 25 samples), and multiplexed imaging (92 patients, 264 samples) technologies to decipher the expression heterogeneity, functional diversity, spatial distribution, colocalization, and interaction of fibroblasts. The newly identified CAF subpopulation was validated by cells isolated from 5 liver cancer patients and in vitro functional assays.

We identified a liver CAF subpopulation, marked by the expression of COL1A2, COL4A1, COL4A2, CTGF, and FSTL1, and named F5-CAF. F5-CAF is preferentially located within and around tumor nests and colocalizes with cancer cells with higher stemness in hepatocellular carcinoma (HCC). Multiplexed staining of 92 patients and the bulk transcriptome of 371 patients demonstrated that the abundance of F5-CAFs in HCC was associated with a worse prognosis. Further in vitro experiments showed that F5-CAFs isolated from liver cancer patients can promote the proliferation and stemness of HCC cells.

We identified a CAF subpopulation F5-CAF in liver cancer, which is associated with cancer stemness and unfavorable prognosis. Our results provide potential mechanisms by which the CAF subset in the TME promotes the development of liver cancer by supporting the survival of cancer stem cells.

CD39 is a pivotal enzyme in cancer, regulating immune response and tumor progression via extracellular ATP and adenosine in the tumor microenvironment (TME). Beyond its established immunoregulatory function, CD39 influences cancer cell angiogenesis and metabolism, opening new frontiers for therapeutic interventions. Current research faces gaps in understanding CD39's full impact across cancer types, with ongoing debates about its potential beyond modulating immune evasion. This review distills CD39's multifaceted roles, examining its dual actions and implications for cancer prognosis and treatment. We analyze the latest therapeutic strategies, highlighting the need for an integrated approach that combines molecular insights with TME dynamics to innovate cancer care. This synthesis underscores CD39's integral role, charting a course for precision oncology that seeks to unravel controversies and harness CD39's therapeutic promise for improved cancer outcomes.