Pyroptosis is a form of programmed cell death characterized by inflammasome activation and the release of inflammatory cytokines, which induce a strong immune response. Unlike apoptosis, pyroptosis can elicit potent immune stimulation, potentially playing a crucial role in anti-tumor immunity. However, it may also promote tumor progression by altering the tumor microenvironment and facilitating immune evasion. This study investigates pyroptosis-related gene expression in hepatocellular carcinoma (HCC), with a focus on identifying key genes that influence prognosis and tumor microenvironment dynamics.

Single-cell RNA sequencing (scRNA-seq) data from 10 HCC patients were obtained from the GEO database (GSE149614), along with spatial transcriptomic data and bulk RNA-seq data from TCGA. We performed data processing and quality control using the Seurat package and applied machine learning techniques, including LASSO regression, to identify key pyroptosis-related genes. Functional analyses, including Gene Ontology (GO), KEGG, and GSVA, were conducted to explore biological pathways. Pyroptosis levels were quantified across cell types, and survival analysis was performed to evaluate prognostic impacts. Cell communication and immune infiltration were also assessed to understand the tumor microenvironment.

We identified CHMP4B as a key pyroptosis-related gene in HCC, significantly associated with poor prognosis. High CHMP4B expression was correlated with shorter overall survival (OS) and disease-free survival (DFS). Functional enrichment analysis showed that CHMP4B is involved in cell cycle regulation, DNA repair, and cytoskeletal organization. Spatial transcriptomics revealed heterogeneous CHMP4B expression in the tumor microenvironment, with higher levels found in advanced tumor stages. Moreover, high CHMP4B expression was associated with increased infiltration of immunosuppressive cells, such as monocytes and macrophages, and upregulation of immune checkpoint molecules (PD-L1, CTLA4), suggesting its role in promoting immune evasion.

Our findings highlight CHMP4B as a critical regulator of pyroptosis in HCC, influencing tumor progression and immune modulation. High CHMP4B expression may facilitate the development of an immunosuppressive microenvironment, enabling immune escape and tumor growth. The study underscores CHMP4B's potential as a prognostic biomarker and therapeutic target in HCC. However, the limited sample size calls for further validation using larger datasets and multi-omics approaches, such as proteomics and metabolomics, to fully elucidate its functional role in HCC pathogenesis.

This study aimed to explore the heterogeneity of tumor endothelial cells (TECs) in hepatocellular carcinoma (HCC) and their role in tumor progression, with the goal of identifying new therapeutic targets and strategies to improve patient prognosis.

Single-cell RNA sequencing data from nine primary liver cancer samples were analyzed, obtained from the Gene Expression Omnibus (GEO) database. Data preprocessing, normalization, dimensionality reduction, and batch effect correction were performed based on the Seurat package. HCC cell types were identified using uniform manifold approximation and projection (UMAP) and cluster analysis, and the different cell types were annotated using the CellMarker database. Pseudotime trajectory analysis was conducted with Monocle to explore the differentiation trajectory of TECs. MAPK signaling pathway activity and copy number variations (CNV) in TECs were analyzed in conjunction with data from The Cancer Genome Atlas (TCGA), the trans-well and wound healing assay was used for cell invasion and migration activity assessment.

Two subgroups of TECs (TECs 1 and TECs 2) were identified, exhibiting distinct functional activities and signaling pathways. Specifically, TECs 1 may be involved in tumor cell proliferation and inflammatory responses, whereas TECs 2 is not only involved in cell proliferation pathways, but also enriched in pathways such as metabolic synthesis. Pseudotime analysis revealed dynamic changes in TECs subgroups during HCC progression, correlating specific gene expressions (such as PDGFRB, PGF, JUN, and NR4A1). Subsequently, the JUN gene was predicted by performing binding sites and was shown to act as a transcription factor that may regulate the expression of the PGF gene. CNV analysis highlighted key genes and pathways in TECs that might influence HCC progression, and the PGF as key regulatory factor mediated cell proliferation and migration.

The study revealed the heterogeneity of TECs in HCC and their potential roles in tumor progression, offering new perspectives and potential therapeutic targets for HCC molecular mechanisms. The findings emphasize the importance of further exploring TECs heterogeneity for understanding HCC pathogenesis and developing personalized treatment strategies.

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide and is associated with high morbidity and mortality. One of the main challenges in the management of HCC is late clinical presentation and thus diagnosis of the disease, which results in poor survival. The pathogenesis of HCC is complex and involves chronic liver injury and genetic alterations. Diagnosis of HCC can be made either by biopsy or imaging; however, conventional tissue-based biopsy methods and serological biomarkers such as AFP have limited clinical applications. While hepatocellular carcinoma is associated with a range of molecular alterations, including the activation of oncogenic signaling pathways, such as Wnt-TGFβ, PI3K-AKT-mTOR, RAS-MAPK, MET, IGF, and Wnt-β-catenin and TP53 and TERT promoter mutations, microfluidic applications have been limited. Early diagnosis is crucial for advancing treatments that would address the heterogeneity of HCC. In this context, microfluidic droplet-based methods are crucial, as they enable comprehensive analysis of the genome and transcriptome of individual cells. Single-cell RNA sequencing (scRNA-seq) allows the examination of individual cell transcriptomes, identifying their heterogeneity and cellular evolutionary relationships. Other microfluidic methods, such as Drop-seq, InDrop, and ATAC-seq, are also employed for single-cell analysis. Here, we examine and compare these microfluidic droplet-based methods, exploring their advantages and limitations in liver cancer research. These technologies provide new opportunities to understand liver cancer biology, diagnosis, treatment, and prognosis, contributing to scientific efforts in combating this challenging disease.

Ovarian cancer is a malignant tumor of ovary. It has the characteristics of difficult early diagnosis, poor late curative effect and high recurrence rate. It is the biggest disease that seriously threatens women's health. Single cell sequencing technology refers to sequencing the genetic information carried by it at the single cell level to obtain the gene sequence, transcript, protein and epigenetic expression profile information of a certain cell type and conduct integrated analysis. It has unique advantages in the study of tumor occurrence and evolution, and can provide new methods for the study of ovarian cancer. This paper reviews the single cell sequencing technology and its application in ovarian cancer.

Deciphering cellular components and the spatial interaction network of the tumor immune microenvironment (TIME) of solid tumors is pivotal for understanding biologically relevant cross-talks and, ultimately, advancing therapies. Multiplexed tissue imaging provides a powerful tool to elucidate spatial complexity in a holistic manner. We established and cross-validated a comprehensive immunophenotyping panel comprising over 121 markers for multiplexed tissue imaging using MACSima™ imaging cyclic staining (MICS) alongside an end-to-end analysis workflow. Applying this panel and workflow to primary cancer tissues, we characterized tumor heterogeneity, investigated potential therapeutical targets, conducted in-depth profiling of cell types and states, sub-phenotyped T cells within the TIME, and scrutinized cellular neighborhoods of diverse T cell subsets. Our findings highlight the advantage of spatial profiling, revealing immunosuppressive molecular signatures of tumor-associated myeloid cells interacting with neighboring exhausted, PD1high T cells in the TIME of hepatocellular carcinoma (HCC). This study establishes a robust framework for spatial exploration of TIMEs in solid tumors and underscores the potency of multiplexed tissue imaging and ultra-deep cell phenotyping in unraveling clinically relevant tumor components.

Tumor-infiltrating immune cells and their crosstalk with cancer cells in the tumor microenvironment (TME) play a crucial role in shaping tumor progression and response to therapy. We utilized 3-dimensional liver cancer spheroids incorporating human primary monocytes to investigate the crosstalk between tumor-associated macrophages (TAMs) and Hepatocellular carcinoma (HCC) cells, HepG2 and PLC/PRF/5. Using multiplexed gene expression panels, the critical pathways involved in shaping primary human monocytes to adopt TAMs phenotypes were identified. The specific inhibitor for an identified pathway was used to explore its involvement in polarization of TAMs. In the cocultured spheroids comprising the human HCC cell lines, the infiltrating monocytes resembled protumor M2-like macrophage phenotypes. Gene expression panels of the infiltrating monocytes demonstrated that the upregulated genes were enriched in the cholesterol metabolism pathway. Cholesterol metabolism-related genes were upregulated together with the nuclear receptors, PPARG and LXR. When lysosomal acid lipase (LAL), the key enzyme necessary for the hydrolysis of lipoprotein, was inhibited, infiltrating monocytes in 3-dimensional spheroid coculture showed significantly decreased M2 marker and lipid uptake receptor expression as well as increased cellular lipid content, which indicated that cholesterol metabolism was important for conditioning the TAMs. Moreover, LAL inhibition reduced the spheroid growth and invasiveness of HCC cell lines. Small interfering RNA-mediated LAL silencing in monocytes yielded similar results upon spheroid coculture. These data indicated that liver cancer cells and infiltrating monocytes participate in crosstalk via cholesterol metabolism to condition monocytes toward TAMs, which favors tumor growth and survival, thereby promoting liver cancer progression.

Background: Single-cell sequencing (SCS) is a technique used to analyze the genome, transcriptome, epigenome, and other genetic data at the level of a single cell. The procedure is commonly utilized in multiple fields, including neurobiology, immunology, and microbiology, and has emerged as a key focus of life science research. However, a thorough and impartial analysis of the existing state and trends of SCS-related research is lacking. The current study aimed to map the development trends of studies on SCS during the years 2010-2022 through bibliometric software. Methods: Pertinent papers on SCS from 2010 to 2022 were obtained using the Web of Science Core Collection. Research categories, nations/institutions, authors/co-cited authors, journals/co-cited journals, co-cited references, and keywords were analyzed using VOSviewer, the R package "bibliometric", and CiteSpace. Results: The bibliometric analysis included 9,929 papers published between 2010 and 2022, and showed a consistent increase in the quantity of papers each year. The United States was the source of the highest quantity of articles and citations in this field. The majority of articles were published in the periodical Nature Communications. Butler A was the most frequently quoted author on this topic, and his article "Integrating single-cell transcriptome data across diverse conditions, technologies, and species" has received numerous citations to date. The literature and keyword analysis showed that studies involving single-cell RNA sequencing (scRNA-seq) were prominent in this discipline during the study period. Conclusion: This study utilized bibliometric techniques to visualize research in SCS-related domains, which facilitated the identification of emerging patterns and future directions in the field. Current hot topics in SCS research include COVID-19, tumor microenvironment, scRNA-seq, and neuroscience. Our results are significant for scholars seeking to identify key issues and generate new research ideas.

Over the past decade, the detection and analysis of liquid biopsy biomarkers such as circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) have advanced significantly. They have received recognition for their clinical usefulness in detecting cancer at an early stage, monitoring disease, and evaluating treatment response. The emergence of liquid biopsy has been a helpful development, as it offers a minimally invasive, rapid, real-time monitoring, and possible alternative to traditional tissue biopsies. In resource-limited settings, the ideal platform for liquid biopsy should not only extract more CTCs or ctDNA from a minimal sample volume but also accurately represent the molecular heterogeneity of the patient's disease. This review covers novel strategies and advancements in CTC and ctDNA-based liquid biopsy platforms, including microfluidic applications and comprehensive analysis of molecular complexity. We discuss these systems' operational principles and performance efficiencies, as well as future opportunities and challenges for their implementation in clinical settings. In addition, we emphasize the importance of integrated platforms that incorporate machine learning and artificial intelligence in accurate liquid biopsy detection systems, which can greatly improve cancer management and enable precision diagnostics.

To investigate the expression of EBV products and frequency of gallstone disease (GD) among different microsatellite status in colorectal cancer (CRC) with BRAFV600E mutation.

We collected 30 CRC patients with BRAFV600E mutation and 10 BRAF ( -) CRC patients as well as 54 healthy subjects. Tumor tissue samples were collected to detect the mutation of BRAF, KRAS, and TP53. Microsatellite status was determined by immunohistochemistry and PCR. EBER in situ hybridization was performed to detect EBV. In addition, we also collected clinical information about the patients.

We found that although EBV products were detected in CRC, there were no significant differences in the EBV distribution between the different BRAF groups. Our study demonstrated that BRAFV600E mutation and BRAFV600E with MSI were significantly more frequent in the right CRC. Furthermore, the KRAS mutation rate in the BRAF-wild-type group was proved to be significantly higher than that in the BRAF mutation group. In addition, we revealed that BRAF mutation and MSI were independent risk factors of TNM stage. The frequency of GD was higher in CRC patients than in general population, and although there was no significant difference between CRC with or without BRAFV600E mutation, the highest frequency of GD was found in MSS CRC with BRAFV600E mutation.

EBV plays a role in CRC, but is not a determinant of different microsatellite status in CRC with BRAFV600E mutation. The frequency of GD in MSS CRC with BRAFV600E mutation is significantly higher than that in the general population.

Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

The high incidence of hepatocellular carcinoma (HCC) recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies. Over the past few decades, the emergence of transcriptome analysis tools, including real-time quantitative reverse transcription PCR, microarrays, and RNA sequencing, has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures. In recent years, the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment, which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets. In the present article, we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains: primary cancer cells; carcinogenic stimuli; and tumor microenvironment. We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics, surveillance, and treatment of HCC recurrence.

Antibody-mediated rejection (ABMR) is the major cause of chronic allograft dysfunction and loss in kidney transplantation. The immunological mechanisms of ABMR that have been featured in the latest studies indicate a highly complex interplay between various immune and nonimmune cell types. Clinical diagnostic standards have long been criticized for being arbitrary and the lack of accuracy. Transcriptomic approaches, including microarray and RNA sequencing of allograft biopsies, enable the identification of differential gene expression and the continuous improvement of diagnostics. Given that conventional bulk transcriptomic approaches only reflect the average gene expression but not the status at the single-cell level, thereby ignoring the heterogeneity of the transcriptome across individual cells, single-cell RNA sequencing is rising as a powerful tool to provide a high-resolution transcriptome map of immune cells, which allows the elucidation of the pathogenesis and may facilitate the development of novel strategies for clinical treatment of ABMR.