Revealing the transcriptional heterogeneity of organ‐specific metastasis in human gastric cancer using single‐cell RNA Sequencing

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Construction of a TAN-associated risk score model with integrated multi-omics data analysis and clinical validation in gastric cancer

AIMS

An increasing number of studies have highlighted the biological significance of neutrophil activation and polarization in tumor progression. However, the characterization of tumor-associated neutrophils (TANs) is inadequately investigated.

MATERIALS AND METHODS

Patients' expression profiles were obtained from TCGA, GEO, and IMvigor210 databases. Six algorithms were used to assess immune cell infiltration. RNA sequencing was conducted to evaluate the differentially expressed genes between induced N1- and N2-like neutrophils. A TAN-associated risk score (TRS) model was established using a combination of weighted gene co-expression network analysis (WGCNA) and RNA-seq data and further assessed in pan-cancer. A clinical cohort of 117 GC patients was enrolled to assess the role of TANs in GC via immunohistochemistry (IHC).

KEY FINDINGS

A TRS signature was built with 10 TAN-related genes (TRGs) and most TRGs were highly abundant in the TANs of the GC microenvironment. The TRS model could accurately predict patients' prognosis, as well as their responses to chemotherapy and immunotherapy. The TRS was positively correlated with pro-tumor immune cells and exhibited negative relationship with anti-tumor immune cells. Additional functional analyses revealed that the signature was positively related to pro-tumor and immunosuppression pathways, such as the hypoxia pathway, across pan-cancer. Furthermore, our clinical cohort demonstrated TANs as an independent prognostic factor for GC patients.

SIGNIFICANCE

This study constructed and confirmed the value of a novel TRS model for prognostic prediction of GC and pan-cancer. Further evaluation of TRS and TANs will help strengthen the understanding of the tumor microenvironment and guide more effective therapeutic strategies.

The tumor immune microenvironment remodeling and response to HER2-targeted therapy in HER2-positive advanced gastric cancer

Combination therapy with anti-HER2 agents and immunotherapy has demonstrated significant clinical benefits in gastric cancer (GC), but the underlying mechanism remains unclear. In this study, we used multiplex immunohistochemistry to assess the changes of the tumor microenvironment in 47 advanced GC patients receiving anti-HER2 therapy. Additionally, we performed single-cell transcriptional sequencing to investigate potential cell-to-cell communication and molecular mechanisms in four HER2-positive GC baseline samples. We observed that post-treated the infiltration of NK cells, CD8+ T cells, and B lymphocytes were significantly higher in patients who benefited from anti-HER2 treatment than baseline. Further spatial distribution analysis demonstrated that the interaction scores between NK cells and CD8+ T cells, B lymphocytes and M2 macrophages, B lymphocytes and Tregs were also significantly higher in benefited patients. Cell-cell communication analysis from scRNA sequencing showed that NK cells utilized CCL3/CCL4-CCR5 to recruit CD8+ T cell infiltration. B lymphocytes employed CD74-APP/COPA/MIF to interact with M2 macrophages, and utilized TNF-FAS/ICOS/TNFRSR1B to interact with Tregs. These cell-cell interactions contribute to inhibit the immune resistance of M2 macrophages and Tregs. Our research provides potential guidance for the use of anti-HER2 therapy in combination with immune therapy.

The Advancement and Application of the Single-Cell Transcriptome in Biological and Medical Research

Single-cell RNA sequencing technology (scRNA-seq) has been steadily developing since its inception in 2009. Unlike bulk RNA-seq, scRNA-seq identifies the heterogeneity of tissue cells and reveals gene expression changes in individual cells at the microscopic level. Here, we review the development of scRNA-seq, which has gone through iterations of reverse transcription, in vitro transcription, smart-seq, drop-seq, 10 × Genomics, and spatial single-cell transcriptome technologies. The technology of 10 × Genomics has been widely applied in medicine and biology, producing rich research results. Furthermore, this review presents a summary of the analytical process for single-cell transcriptome data and its integration with other omics analyses, including genomes, epigenomes, proteomes, and metabolomics. The single-cell transcriptome has a wide range of applications in biology and medicine. This review analyzes the applications of scRNA-seq in cancer, stem cell research, developmental biology, microbiology, and other fields. In essence, scRNA-seq provides a means of elucidating gene expression patterns in single cells, thereby offering a valuable tool for scientific research. Nevertheless, the current single-cell transcriptome technology is still imperfect, and this review identifies its shortcomings and anticipates future developments. The objective of this review is to facilitate a deeper comprehension of scRNA-seq technology and its applications in biological and medical research, as well as to identify avenues for its future development in alignment with practical needs.

Potential therapeutic targets of gastric cancer explored under endogenous network modeling of clinical data

Improvement in the survival rate of gastric cancer, a prevalent global malignancy and the leading cause of cancer-related mortality calls for more avenues in molecular therapy. This work aims to comprehend drug resistance and explore multiple-drug combinations for enhanced therapeutic treatment. An endogenous network modeling clinic data with core gastric cancer molecules, functional modules, and pathways is constructed, which is then transformed into dynamics equations for in-silicon studies. Principal component analysis, hierarchical clustering, and K-means clustering are utilized to map the attractor domains of the stochastic model to the normal and pathological phenotypes identified from the clinical data. The analyses demonstrate gastric cancer as a cluster of stable states emerging within the stochastic dynamics and elucidate the cause of resistance to anti-VEGF monotherapy in cancer treatment as the limitation of the single pathway in preventing cancer progression. The feasibility of multiple objectives of therapy targeting specified molecules and/or pathways is explored. This study verifies the rationality of the platform of endogenous network modeling, which contributes to the development of cross-functional multi-target combinations in clinical trials.

Single-cell analysis uncovers high-proliferative tumour cell subtypes and their interactions in the microenvironment of gastric cancer

Gastric cancer (GC) remains a prominent malignancy that poses a significant threat to human well-being worldwide. Despite advancements in chemotherapy and immunotherapy, which have effectively augmented patient survival rates, the mortality rate associated with GC remains distressingly high. This can be attributed to the elevated proliferation and invasive nature exhibited by GC. Our current understanding of the drivers behind GC cell proliferation remains limited. Hence, in order to reveal the molecular biological mechanism behind the swift advancement of GC, we employed single-cell RNA-sequencing (scRNA-seq) to characterize the tumour microenvironment in this study. The scRNA-seq data of 27 patients were acquired from the Gene Expression Omnibus database. Differential gene analysis, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and Gene Set Enrichment Analysis were employed to investigate 38 samples. The copy number variation level exhibited by GC cells was determined using InferCNV. The CytoTRACE, Monocle and Slingshot analysis were used to discern the cellular stemness and developmental trajectory of GC cells. The CellChat package was utilized for the analysis of intercellular communication crosstalk. Moreover, the findings of the data analysis were validated through cellular functional tests conducted on the AGS cell line and SGC-7901 cell line. Finally, this study constructed a risk scoring model to evaluate the differences of different risk scores in clinical characteristics, immune infiltration, immune checkpoints, functional enrichment, tumour mutation burden and drug sensitivity. Within the microenvironment of GC, we identified the presence of 8 cell subsets, encompassing NK_T cells, B_Plasma cells, epithelial cells, myeloid cells, endothelial cells, mast cells, fibroblasts, pericytes. By delving deeper into the characterization of GC cells, we identified 6 specific tumour cell subtypes: C0 PSCA+ tumour cells, C1 CLDN7+ tumour cells, C2 UBE2C+ tumour cells, C3 MUC6+ tumour cells, C4 CHGA+ tumour cells and C5 MUC2+ tumour cells. Notably, the C2 UBE2C+ tumour cells demonstrated a close association with cell mitosis and the cell cycle, exhibiting robust proliferative capabilities. Our findings were fortified through enrichment analysis, pseudotime analysis and cell communication analysis. Meanwhile, knockdown of the transcription factor CREB3, which is highly active in UBE2C+ tumour cells, significantly impedes the proliferation, migration and invasion of GC cells. And the prognostic score model constructed with CREB3-related genes showcased commendable clinical predictive capacity, thus providing valuable guidance for patients' prognosis and clinical treatment decisions. We have identified a highly proliferative cellular subgroup C2 UBE2C+ tumour cells in GC for the first time. The employment of a risk score model, which is based on genes associated with UBE2C expression, exhibits remarkable proficiency in predicting the prognosis of GC patients. In our investigation, we observed that the knockdown of the transcription factor CREB3 led to a marked reduction in cellular proliferation, migration and invasion in GC cell line models. Implementing a stratified treatment approach guided by this model represents a judicious and promising methodology.

Interactions between LAMP3+ dendritic cells and T-cell subpopulations promote immune evasion in papillary thyroid carcinoma

BACKGROUND

The incidence of papillary thyroid cancer (PTC) continues to rise all over the world, 10-15% of the patients have a poor prognosis. Although immunotherapy has been applied in clinical practice, its therapeutic efficacy remains far from satisfactory, necessitating further investigation of the mechanism of PTC immune remodeling and exploration of novel treatment targets.

METHODS

This study conducted a single-cell RNA sequencing (scRNA-seq) analysis using 18 surgical tissue specimens procured from 14 patients diagnosed with adjacent tissues, non-progressive PTC or progressive PTC. Key findings were authenticated through spatial transcriptomics RNA sequencing, immunohistochemistry, multiplex immunohistochemistry, and an independent bulk RNA-seq data set containing 502 samples.

RESULTS

A total of 151,238 individual cells derived from 18 adjacent tissues, non-progressive PTC and progressive PTC specimens underwent scRNA-seq analysis. We found that progressive PTC exhibits the following characteristics: a significant decrease in overall immune cells, enhanced immune evasion of tumor cells, and disrupted antigen presentation function. Moreover, we identified a subpopulation of lysosomal associated membrane protein 3 (LAMP3+) dendritic cells (DCs) exhibiting heightened infiltration in progressive PTC and associated with advanced T stage and poor prognosis of PTC. LAMP3+ DCs promote CD8+ T cells exhaustion (mediated by NECTIN2-TIGIT) and increase infiltration abundance of regulatory T cells (mediated by chemokine (C-C motif) ligand 17 (CCL17)-chemokine (C-C motif) receptor 4 (CCR4)) establishing an immune-suppressive microenvironment. Ultimately, we unveiled that progressive PTC tumor cells facilitate the retention of LAMP3+ DCs within the tumor microenvironment through NECTIN3-NECTIN2 interactions, thereby rendering tumor cells more susceptible to immune evasion.

CONCLUSION

Our findings expound valuable insights into the role of the interaction between LAMP3+ DCs and T-cell subpopulations and offer new and effective ideas and strategies for immunotherapy in patients with progressive PTC.

Metastasis-associated fibroblasts in peritoneal surface malignancies

Over decades, peritoneal surface malignancies (PSMs) have been associated with limited treatment options and poor prognosis. However, advancements in perioperative systemic chemotherapy, cytoreductive surgery (CRS), and hyperthermic intraperitoneal chemotherapy (HIPEC) have significantly improved clinical outcomes. PSMs predominantly result from the spread of intra-abdominal neoplasia, which then form secondary peritoneal metastases. Colorectal, ovarian, and gastric cancers are the most common contributors. Despite diverse primary origins, the uniqueness of the peritoneum microenvironment shapes the common features of PSMs. Peritoneal metastization involves complex interactions between tumour cells and the peritoneal microenvironment. Fibroblasts play a crucial role, contributing to tumour development, progression, and therapy resistance. Peritoneal metastasis-associated fibroblasts (MAFs) in PSMs exhibit high heterogeneity. Single-cell RNA sequencing technology has revealed that immune-regulatory cancer-associated fibroblasts (iCAFs) seem to be the most prevalent subtype in PSMs. In addition, other major subtypes as myofibroblastic CAFs (myCAFs) and matrix CAFs (mCAFs) were frequently observed across PSMs studies. Peritoneal MAFs are suggested to originate from mesothelial cells, submesothelial fibroblasts, pericytes, endothelial cells, and omental-resident cells. This plasticity and heterogeneity of CAFs contribute to the complex microenvironment in PSMs, impacting treatment responses. Understanding these interactions is crucial for developing targeted and local therapies to improve PSMs patient outcomes.

ScRNA-seq of gastric cancer tissues reveals differences in the immune microenvironment of primary tumors and metastases

Gastric carcinoma (GC) is regarded as one of the deadliest cancer characterized by diversity and haste metastasis and suffers limited understanding of the spatial variation between primary and metastatic GC tumors. In this project, transcriptome analysis on 46 primary tumorous, adjacent non-tumorous, and metastatic GC tissues was performed. The results demonstrated that metastatic tumorous tissues had diminished CD8+ T cells compared to primary tumors, which is mechanistically attributed to being due to innate immunity differences represented by marked differences in macrophages between metastatic and primary tumors, particularly those expressing ApoE, where their abundance is linked to unfavorable prognoses. Examining variations in gene expression and interactions indicated possible strategies of immune evasion hindering the growth of CD8+ T cells in metastatic tumor tissues. More insights could be gained into the immune evasion mechanisms by portraying information about the GC ecosystem.

Single-cell transcriptome reveals highly complement activated microglia cells in association with pediatric tuberculous meningitis

Background

Tuberculous meningitis (TBM) is a devastating form of tuberculosis (TB) causing high mortality and disability. TBM arises due to immune dysregulation, but the underlying immune mechanisms are unclear.

Methods

We performed single-cell RNA sequencing on peripheral blood mononuclear cells (PBMCs) and cerebrospinal fluid (CSF) cells isolated from children (n=6) with TBM using 10 xGenomics platform. We used unsupervised clustering of cells and cluster visualization based on the gene expression profiles, and validated the protein and cytokines by ELISA analysis.

Results

We revealed for the first time 33 monocyte populations across the CSF cells and PBMCs of children with TBM. Within these populations, we saw that CD4_C04 cells with Th17 and Th1 phenotypes and Macro_C01 cells with a microglia phenotype, were enriched in the CSF. Lineage tracking analysis of monocyte populations revealed myeloid cell populations, as well as subsets of CD4 and CD8 T-cell populations with distinct effector functions. Importantly, we discovered that complement-activated microglial Macro_C01 cells are associated with a neuroinflammatory response that leads to persistent meningitis. Consistently, we saw an increase in complement protein (C1Q), inflammatory markers (CRP) and inflammatory factor (TNF-α and IL-6) in CSF cells but not blood. Finally, we inferred that Macro_C01 cells recruit CD4_C04 cells through CXCL16/CXCR6.

Discussion

We proposed that the microglial Macro_C01 subset activates complement and interacts with the CD4_C04 cell subset to amplify inflammatory signals, which could potentially contribute to augment inflammatory signals, resulting in hyperinflammation and an immune response elicited by Mtb-infected tissues.

Unraveling the prognostic significance of RGS gene family in gastric cancer and the potential implication of RGS4 in regulating tumor-infiltrating fibroblast

Regulator of G-protein signaling (RGS) proteins are regulators of signal transduction mediated by G protein-coupled receptors (GPCRs). Current studies have shown that some molecules in the RGS gene family are related to the occurrence, development and poor prognosis of malignant tumors. However, the RGS gene family has been rarely studied in gastric cancer. In this study, we explored the mutation and expression profile of RGS gene family in gastric cancer, and evaluated the prognostic value of RGS expression. Then we established a prognostic model based on RGS gene family and performed functional analysis. Further studies showed that RGS4, as an independent prognostic predictor, may play an important role in regulating fibroblasts in the immune microenvironment. In conclusion, this study explores the value of RGS gene family in gastric cancer, which is of great significance for predicting the prognosis and guiding the treatment of gastric cancer.

Gastric cancer immunosuppressive microenvironment heterogeneity: implications for therapy development

Although immunotherapy has revolutionized solid tumor treatment, durable responses in gastric cancer (GC) remain limited. The heterogeneous tumor microenvironment (TME) facilitates immune evasion, contributing to resistance to conventional and immune therapies. Recent studies have highlighted how specific TME components in GC acquire immune escape capabilities through cancer-specific factors. Understanding the underlying molecular mechanisms and targeting the immunosuppressive TME will enhance immunotherapy efficacy and patient outcomes. This review summarizes recent advances in GC TME research and explores the role of the immune-suppressive system as a context-specific determinant. We also provide insights into potential treatments beyond checkpoint inhibition.

HSPA4 upregulation induces immune evasion via ALKBH5/CD58 axis in gastric cancer

INTRODUCTION

Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. Recently, targeted therapies including PD1 (programmed cell death 1) antibodies have been used in advanced GC patients. However, identifying new biomarker for immunotherapy is still urgently needed. The objective of this study is to unveil the immune evasion mechanism of GC cells and identify new biomarkers for immune checkpoint blockade therapy in patients with GC.

METHODS

Coimmunoprecipitation and meRIP were performed to investigate the mechanism of immune evasion of GC cells. Cocuture system was established to evaluate the cytotoxicity of cocultured CD8+ T cells. The clinical significance of HSPA4 upregulation was analyzed by multiplex fluorescent immunohistochemistry staining in GC tumor tissues.

RESULTS

Histone acetylation causes HSPA4 upregulation in GC tumor tissues. HSPA4 upregulation increases the protein stability of m6A demethylase ALKBH5. ALKBH5 decreases CD58 in GC cells through m6A methylation regulation. The cytotoxicity of CD8+ T cells are impaired and PD1/PDL1 axis is activated when CD8+ T cells are cocultured with HSPA4 overexpressed GC cells. HSPA4 upregulation is associated with worse 5-year overall survival of GC patients receiving only surgery. It is an independent prognosis factor for worse survival of GC patients. In GC patients receiving the combined chemotherapy with anti-PD1 immunotherapy, HSPA4 upregulation is observed in responders compared with non-responders.

CONCLUSION

HSPA4 upregulation causes the decrease of CD58 in GC cells via HSPA4/ALKBH5/CD58 axis, followed by PD1/PDL1 activation and impairment of CD8+ T cell's cytotoxicity, finally induces immune evasion of GC cells. HSPA4 upregulation is associated with worse overall survival of GC patients with only surgery. Meanwhile, HSPA4 upregulation predicts for better response in GC patients receiving the combined immunotherapy.

Pathways and molecules for overcoming immunotolerance in metastatic gastrointestinal tumors

Worldwide, gastrointestinal (GI) cancer is recognized as one of the leading malignancies diagnosed in both genders, with mortality largely attributed to metastatic dissemination. It has been identified that in GI cancer, a variety of signaling pathways and key molecules are modified, leading to the emergence of an immunotolerance phenotype. Such modifications are pivotal in the malignancy's evasion of immune detection. Thus, a thorough analysis of the pathways and molecules contributing to GI cancer's immunotolerance is vital for advancing our comprehension and propelling the creation of efficacious pharmacological treatments. In response to this necessity, our review illuminates a selection of groundbreaking cellular signaling pathways associated with immunotolerance in GI cancer, including the Phosphoinositide 3-kinases/Akt, Janus kinase/Signal Transducer and Activator of Transcription 3, Nuclear Factor kappa-light-chain-enhancer of activated B cells, Transforming Growth Factor-beta/Smad, Notch, Programmed Death-1/Programmed Death-Ligand 1, and Wingless and INT-1/beta-catenin-Interleukin 10. Additionally, we examine an array of pertinent molecules like Indoleamine-pyrrole 2,3-dioxygenase, Human Leukocyte Antigen G/E, Glycoprotein A Repetitions Predominant, Clever-1, Interferon regulatory factor 8/Osteopontin, T-cell immunoglobulin and mucin-domain containing-3, Carcinoembryonic antigen-related cell adhesion molecule 1, Cell division control protein 42 homolog, and caspases-1 and -12.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Exploring the current landscape of single-cell RNA sequencing applications in gastric cancer research

Gastric cancer (GC) represents a major global health burden and is responsible for a significant number of cancer-related fatalities. Its complex nature, characterized by heterogeneity and aggressive behaviour, poses considerable challenges for effective diagnosis and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as an important technique, offering unprecedented precision and depth in gene expression profiling at the cellular level. By facilitating the identification of distinct cell populations, rare cells and dynamic transcriptional changes within GC, scRNA-seq has yielded valuable insights into tumour progression and potential therapeutic targets. Moreover, this technology has significantly improved our comprehension of the tumour microenvironment (TME) and its intricate interplay with immune cells, thereby opening avenues for targeted therapeutic strategies. Nonetheless, certain obstacles, including tumour heterogeneity and technical limitations, persist in the field. Current endeavours are dedicated to refining protocols and computational tools to surmount these challenges. In this narrative review, we explore the significance of scRNA-seq in GC, emphasizing its advantages, challenges and potential applications in unravelling tumour heterogeneity and identifying promising therapeutic targets. Additionally, we discuss recent developments, ongoing efforts to overcome these challenges, and future prospects. Although further enhancements are required, scRNA-seq has already provided valuable insights into GC and holds promise for advancing biomedical research and clinical practice.

Xenograft and organoid models in developing precision medicine for gastric cancer (Review)

Gastric cancer (GC), a highly heterogeneous disease, has diverse histological and molecular subtypes. For precision medicine, well‑characterized models encompassing the full spectrum of subtypes are necessary. Patient‑derived tumor xenografts and organoids serve as important preclinical models in GC research. The main advantage of these models is the retention of phenotypic and genotypic heterogeneity present in parental tumor tissues. Utilizing diverse sequencing techniques and preclinical models for GC research facilitates accuracy in predicting personalized clinical responses to anti‑cancer treatments. The present review summarizes the latest advances of these two preclinical models in GC treatment and drug response assessment.

Analysis of the impact of immunotherapy efficacy and safety in patients with gastric cancer and liver metastasis

BACKGROUND

Gastric cancer (GC) is the fifth most common type of cancer and has the fourth highest death rate among all cancers. There is a lack of studies examining the impact of liver metastases on the effectiveness of immunotherapy in individuals diagnosed with GC.

AIM

To investigate the influence of liver metastases on the effectiveness and safety of immunotherapy in patients with advanced GC.

METHODS

This retrospective investigation collected clinical data of patients with advanced stomach cancer who had immunotherapy at our hospital from February 2021 to January 2023. The baseline attributes were compared using either the Chi-square test or the Fisher exact probability method. The chi-square test and Kaplan-Meier survival analysis were employed to assess the therapeutic efficacy and survival duration in GC patients with and without liver metastases.

RESULTS

The analysis comprised 48 patients diagnosed with advanced GC, who were categorized into two groups: A liver metastasis cohort (n = 20) and a non-liver metastatic cohort (n = 28). Patients with liver metastasis exhibited a more deteriorated physical condition compared to those without liver metastasis. The objective response rates in the cohort with metastasis and the cohort without metastasis were 15.0% and 35.7% (P > 0.05), respectively. Similarly, the disease control rates in these two cohorts were 65.0% and 82.1% (P > 0.05), respectively. The median progression-free survival was 5.0 months in one group and 11.2 months in the other group, with a hazard ratio of 0.40 and a significance level (P) less than 0.05. The median overall survival was 12.0 months in one group and 19.0 months in the other group, with a significance level (P) greater than 0.05.

CONCLUSION

Immunotherapy is less effective in GC patients with liver metastases compared to those without liver metastasis.

Advancements in technology for characterizing the tumor immune microenvironment

Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.

Integrated single-cell sequencing, spatial transcriptome sequencing and bulk RNA sequencing highlights the molecular characteristics of parthanatos in gastric cancer

BACKGROUND

Parthanatos is a novel programmatic form of cell death based on DNA damage and PARP-1 dependency. Nevertheless, its specific role in the context of gastric cancer (GC) remains uncertain.

METHODS

In this study, we integrated multi-omics algorithms to investigate the molecular characteristics of parthanatos in GC. A series of bioinformatics algorithms were utilized to explore clinical heterogeneity of GC and further predict the clinical outcomes.

RESULTS

Firstly, we conducted a comprehensive analysis of the omics features of parthanatos in various human tumors, including genomic mutations, transcriptome expression, and prognostic relevance. We successfully identified 7 cell types within the GC microenvironment: myeloid cell, epithelial cell, T cell, stromal cell, proliferative cell, B cell, and NK cell. When compared to adjacent non-tumor tissues, single-cell sequencing results from GC tissues revealed elevated scores for the parthanatos pathway across multiple cell types. Spatial transcriptomics, for the first time, unveiled the spatial distribution characteristics of parthanatos signaling. GC patients with different parthanatos signals often exhibited distinct immune microenvironment and metabolic reprogramming features, leading to different clinical outcomes. The integration of parthanatos signaling and clinical indicators enabled the creation of novel survival curves that accurately assess patients' survival times and statuses.

CONCLUSIONS

In this study, the molecular characteristics of parthanatos' unicellular and spatial transcriptomics in GC were revealed for the first time. Our model based on parthanatos signals can be used to distinguish individual heterogeneity and predict clinical outcomes in patients with GC.

Rebuilding the microenvironment of primary tumors in humans: a focus on stroma

Conventional tumor models have critical shortcomings in that they lack the complexity of the human stroma. The heterogeneous stroma is a central compartment of the tumor microenvironment (TME) that must be addressed in cancer research and precision medicine. To fully model the human tumor stroma, the deconstruction and reconstruction of tumor tissues have been suggested as new approaches for in vitro tumor modeling. In this review, we summarize the heterogeneity of tumor-associated stromal cells and general deconstruction approaches used to isolate patient-specific stromal cells from tumor tissue; we also address the effect of the deconstruction procedure on the characteristics of primary cells. Finally, perspectives on the future of reconstructed tumor models are discussed, with an emphasis on the essential prerequisites for developing authentic humanized tumor models.

Molecular Classifications in Gastric Cancer: A Call for Interdisciplinary Collaboration

Gastric cancer (GC) is a heterogeneous disease, often diagnosed at advanced stages, with a 5-year survival rate of approximately 20%. Despite notable technological advancements in cancer research over the past decades, their impact on GC management and outcomes has been limited. Numerous molecular alterations have been identified in GC, leading to various molecular classifications, such as those developed by The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG). Other authors have proposed alternative perspectives, including immune, proteomic, or epigenetic-based classifications. However, molecular stratification has not yet transitioned into clinical practice for GC, and little attention has been paid to alternative molecular classifications. In this review, we explore diverse molecular classifications in GC from a practical point of view, emphasizing their relationships with clinicopathological factors, prognosis, and therapeutic approaches. We have focused on classifications beyond those of TCGA and the ACRG, which have been less extensively reviewed previously. Additionally, we discuss the challenges that must be overcome to ensure their impact on patient treatment and prognosis. This review aims to serve as a practical framework to understand the molecular landscape of GC, facilitate the development of consensus molecular categories, and guide the design of innovative molecular studies in the field.

Potential crosstalk between SPP1 + TAMs and CD8 + exhausted T cells promotes an immunosuppressive environment in gastric metastatic cancer

BACKGROUND

Immunotherapy brings new hope to patients with advanced gastric cancer. However, liver metastases can reduce the efficacy of immunotherapy in patients. Tumor-associated macrophages (TAMs) may be the cause of this reduction in efficacy. SPP1 + TAMs are considered to have immunosuppressive properties. We aimed to investigate the involvement of SPP1 + TAMs in the metastasis of gastric cancer.

METHODS

The single-cell transcriptome was combined with batched BULK datasets for analysis. Animal models were used to verify the analysis results.

RESULTS

We reveal the interaction of SPP1 + TAMs with CD8 + exhausted T cells in metastatic cancer. Among these interactions, GDF15-TGFBR2 may play a key immunosuppressive role. We constructed an LR score to quantify interactions based on ligands and receptors. The LR score is highly correlated with various immune features and clinical molecular subtypes. The LR score may also guide the prediction of the efficacy of immunotherapy and prognosis.

CONCLUSIONS

The crosstalk between SPP1 + TAMs and CD8 + exhausted T cells plays a key immunosuppressive role in the gastric metastatic cancer microenvironment.

Comprehensive profiling of cell subsets of gastric cancer and liver metastasis based on single cell RNA-sequencing analysis

Background

Liver metastasis (Li) is one of the most common distant metastatic sites for gastric cancer. A deeper understanding of its mechanism of action from a bioinformatics perspective may provide new insights. Therefore, the aim of this study was to use single cell RNA sequencing (scRNA-seq) to evaluate cell subtypes and understand the molecular mechanism of gastric cancer Li.

Methods

The scRNA-seq data GSE163558 of gastric cancer and Li were downloaded from Gene Expression Omnibus (GEO). Single cell data were analyzed by various R packages such as Seurat, CellChat, gene set variation analysis (GSVA), monocle, gene set enrichment analysis (GSEA), and survival analysis and the results were plotted by ggplot2, R4.1.1. Protein expression was confirmed by immunohistochemistry in an additional patient cohort.

Results

The genes APOD, CXCL5, and JUN are involved in epithelial cell metastasis. The infiltration of cytotoxic CD8 T cells was more frequent in gastric primary tumors (PTs) than in Lis. IL7R high natural killer (NK) cells that had high TXNIP and RIPOR2 expression were located at the site of Li and corresponded to a favorable prognosis. NK cells with high TNFAIP3 expression were located at the PT site and corresponded to a poor prognosis. Furthermore, the gene expression of myeloid cells was different depending on their localization in the PT site or Li. MHC-I signaling pathway was found to be activated in the PT compared to MHC-II at the site of Li, as revealed by cell-cell interaction, and HLA-E-CD94/NKG2A of NK cells was only activated in the PT and not in the Li.

Conclusions

The present study revealed the difference between Li and gastric PT by scRNA-seq, demonstrating the impact of partial gene expression on patient prognosis. Our study provides new insights into gastric cancer and Li.

Upregulation of E-cadherin by the combination of methionine restriction and HDAC2 intervention for inhibiting gastric carcinoma metastasis

Invasion and metastasis are the leading causes of death in individuals with malignant tumors, including gastric cancer. In this study, we aim to explore the effect and related mechanisms of methionine restriction (MR) on gastric carcinoma metastasis. In the MR cell model, gastric carcinoma cells are cultured in the MR medium, and in the animal model, BALB/c nude rodents are administered with a methionine-free diet after receiving injections of MKN45 cells into the caudal vein. Transwell assay is used to detect cell invasion and migration. Chromatin immunoprecipitation is performed to investigate the levels of H3K9me2, H3K27Ac, and H3K27me3 in the E-cadherin promoter. The results show that MR inhibits gastric carcinoma cell migration, invasion, and lung metastasis. MR increases E-cadherin while reducing the H3K27me3 level in the E-cadherin promoter. E-cadherin expression in gastric carcinoma cells is adversely regulated by HDAC2. Overexpressing HDAC2 reduces the H3K27Ac level in the E-cadherin promoter, while interfering with HDAC2 increases the H3K27Ac level. HDAC2 interference under MR conditions further upregulates E-cadherin expression and inhibits gastric carcinoma cell migration, invasion, and lung metastasis. MR combined with HDAC2 interference promotes E-cadherin expression by mediating the methylation and acetylation of E-cadherin, thus inhibiting the invasion, migration, and lung metastasis of gastric carcinoma cells. Our study provides a new theoretical basis for the inhibitory effect of MR on gastric cancer.

Single cell sequencing revealed the mechanism of CRYAB in glioma and its diagnostic and prognostic value

Background

We explored the characteristics of single-cell differentiation data in glioblastoma and established prognostic markers based on CRYAB to predict the prognosis of glioblastoma patients. Aberrant expression of CRYAB is associated with invasive behavior in various tumors, including glioblastoma. However, the specific role and mechanisms of CRYAB in glioblastoma are still unclear.

Methods

We assessed RNA-seq and microarray data from TCGA and GEO databases, combined with scRNA-seq data on glioma patients from GEO. Utilizing the Seurat R package, we identified distinct survival-related gene clusters in the scRNA-seq data. Prognostic pivotal genes were discovered through single-factor Cox analysis, and a prognostic model was established using LASSO and stepwise regression algorithms. Moreover, we investigated the predictive potential of these genes in the immune microenvironment and their applicability in immunotherapy. Finally, in vitro experiments confirmed the functional significance of the high-risk gene CRYAB.

Results

By analyzing the ScRNA-seq data, we identified 28 cell clusters representing seven cell types. After dimensionality reduction and clustering analysis, we obtained four subpopulations within the oligodendrocyte lineage based on their differentiation trajectory. Using CRYAB as a marker gene for the terminal-stage subpopulation, we found that its expression was associated with poor prognosis. In vitro experiments demonstrated that knocking out CRYAB in U87 and LN229 cells reduced cell viability, proliferation, and invasiveness.

Conclusion

The risk model based on CRYAB holds promise in accurately predicting glioblastoma. A comprehensive study of the specific mechanisms of CRYAB in glioblastoma would contribute to understanding its response to immunotherapy. Targeting the CRYAB gene may be beneficial for glioblastoma patients.

Single-cell transcriptomic analyses of tumor microenvironment and molecular reprograming landscape of metastatic laryngeal squamous cell carcinoma

Laryngeal squamous cell carcinoma (LSCC) is a malignant tumor with a high probability of metastasis. The tumor microenvironment (TME) plays a critical role in cancer metastasis. To gain insights into the TME of LSCC, we conducted single-cell RNA-seq (scRNA-seq) on samples collected from LSCC patients with or without lymphatic metastasis. The stem and immune cell signatures in LSCC suggest their roles in tumor invasion and metastasis. Infiltration of a large number of regulatory T cells, dysplastic plasma cells, and macrophages that are at the early development stage in the cancerous tissue indicates an immunosuppressive state. Abundant neutrophils detected at the cancer margins reflect the inflammatory microenvironment. In addition to dynamic ligand-receptor interactions between the stromal and myeloid cells, the enhanced autophagy in endothelial cells and fibroblasts implies a role in nutrient supply. Taken together, the comprehensive atlas of LSCC obtained allowed us to identify a complex yet unique TME of LSCC, which may help identify potential diagnostic biomarkers and therapeutic targets for LSCC.

From LncRNA to metastasis: The MALAT1-EMT axis in cancer progression

Cancer is a complex disease that causes abnormal genetic changes and unchecked cellular growth. It also causes a disruption in the normal regulatory processes that leads to the creation of malignant tissue. The complex interplay of genetic, environmental, and epigenetic variables influences its etiology. Long non-coding RNAs (LncRNAs) have emerged as pivotal contributors within the intricate landscape of cancer biology, orchestrating an array of multifaceted cellular processes that substantiate the processes of carcinogenesis and metastasis. Metastasis is a crucial driver of cancer mortality. Among these, MALAT1 (Metastasis-Associated Lung Adenocarcinoma Transcript 1) has drawn a lot of interest for its function in encouraging metastasis via controlling the Epithelial-Mesenchymal Transition (EMT) procedure. MALAT1 exerts a pivotal influence on the process of EMT, thereby promoting metastasis to distant organs. The mechanistic underpinning of this phenomenon involves the orchestration of an intricate regulatory network encompassing transcription factors, signalling cascades, and genes intricately associated with the EMT process by MALAT1. Its crucial function in transforming tumor cells into an aggressive phenotype is highlighted by its capacity to influence the expression of essential EMT effectors such as N-cadherin, E-cadherin, and Snail. An understanding of the MALAT1-EMT axis provides potential therapeutic approaches for cancer intervention. Targeting MALAT1 or its downstream EMT effectors may reduce the spread of metastatic disease and improve the effectiveness of already available therapies. Understanding the MALAT1-EMT axis holds significant clinical implications. Therefore, directing attention towards MALAT1 or its downstream mediators could present innovative therapeutic strategies for mitigating metastasis and improving patient prognosis. This study highlights the importance of MALAT1 in cancer biology and its potential for cutting back on metastatic disease with novel treatment strategies.

SINGLE-CELL TRANSCRIPTOME ANALYSIS IN HEALTH AND DISEASE

ABSTRACT

The analysis of the single-cell transcriptome has emerged as a powerful tool to gain insights on the basic mechanisms of health and disease. It is widely used to reveal the cellular diversity and complexity of tissues at cellular resolution by RNA sequencing of the whole transcriptome from a single cell. Equally, it is applied to discover an unknown, rare population of cells in the tissue. The prime advantage of single-cell transcriptome analysis is the detection of stochastic nature of gene expression of the cell in tissue. Moreover, the availability of multiple platforms for the single-cell transcriptome has broadened its approaches to using cells of different sizes and shapes, including the capture of short or full-length transcripts, which is helpful in the analysis of challenging biological samples. And with the development of numerous packages in R and Python, new directions in the computational analysis of single-cell transcriptomes can be taken to characterize healthy versus diseased tissues to obtain novel pathological insights. Downstream analysis such as differential gene expression analysis, gene ontology term analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, cell-cell interaction analysis, and trajectory analysis has become standard practice in the workflow of single-cell transcriptome analysis to further examine the biology of different cell types. Here, we provide a broad overview of single-cell transcriptome analysis in health and disease conditions currently applied in various studies.

Death receptor 5 promotes tumor progression in gastric cancer

Death receptor 5 (DR5) can inhibit malignant proliferation via tumor necrosis factor-related apoptosis-inducing ligand (TRAIL)-induced apoptosis in many cancers. Here we examined the expression and sublocalization of DR5 in gastric cancer, as well as its effects on clinical prognosis and cellular processes. Our analysis included a cohort of 240 gastric cancer patients. Bioinformatic analysis showed a significant correlation between DR5 and DNA replication, tumor mutation burden (TMB), and tumor stemness. Unlike death receptor 4 (DR4TRAIL-R1), DR5 was expressed in the cytoplasm and nucleus, and was found to be positively correlated with lymphovascular invasion, lymph node metastasis, and TNM stage. Patients with positive DR5 had worse overall survival (OS) (P = 0.006). The multivariate Cox model showed that DR5 is an independent poor prognostic factor (hazard ratio = 1.693). Furthermore, knockdown of DR5 inhibited aggressive behaviors, including proliferation and metastasis in gastric cancer cells, and inhibited lung metastasis in vivo. In summary, nuclear localization of DR5 expression is a poor prognosis factor in gastric cancer and promotes growth, invasion, and metastasis of tumor cells in vitro and in vivo.

Deciphering tumor-infiltrating dendritic cells in the single-cell era

Dendritic cells (DCs) serve as a pivotal link connecting innate and adaptive immunity by processing tumor-derived antigens and activating T cells. The advent of single-cell sequencing has revolutionized the categorization of DCs, enabling a high-resolution characterization of the previously unrecognized diversity of DC populations infiltrating the intricate tumor microenvironment (TME). The application of single-cell sequencing technologies has effectively elucidated the heterogeneity of DCs present in the tumor milieu, yielding invaluable insights into their subpopulation structures and functional diversity. This review provides a comprehensive summary of the current state of knowledge regarding DC subtypes in the TME, drawing from single-cell studies conducted across various human tumors. We focused on the categorization, functions, and interactions of distinct DC subsets, emphasizing their crucial roles in orchestrating tumor-related immune responses. Additionally, we delve into the potential implications of these findings for the identification of predictive biomarkers and therapeutic targets. Enhanced insight into the intricate interplay between DCs and the TME promises to advance our comprehension of tumor immunity and, in turn, pave the way for the development of more efficacious cancer immunotherapies.

Research progress on the immune microenvironment and immunotherapy in gastric cancer

The tumor microenvironment, particularly the immune microenvironment, plays an indispensable role in the malignant progression and metastasis of gastric cancer (GC). As our understanding of the GC microenvironment continues to evolve, we are gaining deeper insights into the biological mechanisms at the single-cell level. This, in turn, has offered fresh perspectives on GC therapy. Encouragingly, there are various monotherapy and combination therapies in use, such as immune checkpoint inhibitors, adoptive cell transfer therapy, chimeric antigen receptor T cell therapy, antibody-drug conjugates, and cancer vaccines. In this paper, we review the current research progress regarding the GC microenvironment and summarize promising immunotherapy research and targeted therapies.

Mucosal-associated invariant T cells in digestive tract: Local guardians or destroyers?

Mucosa-associated invariant T cells (MAIT) are a class of innate-like T lymphocytes mainly presenting CD8+ phenotype with a semi-invariant αβ T-cell receptor, which specifically recognises MR1-presented biosynthetic derivatives of riboflavin synthesis produced by various types of microbiomes. As innate-like T lymphocytes, MAIT can be activated by a variety of cytokines, leading to immediate immune responses to infection and tumour cues. As an organ that communicates with the external environment, the digestive tract, especially the gastrointestinal tract, contains abundant microbial populations. Communication between MAIT and local microbiomes is important for the homeostasis of mucosal immunity. In addition, accumulating evidence suggests changes in the abundance and structure of the microbial community during inflammation and tumorigenesis plays a critical role in disease progress partly through their impact on MAIT development and function. Therefore, it is essential for the understanding of MAIT response and their interaction with microbiomes in the digestive tract. Here, we summarised MAIT characteristics in the digestive tract and its alteration facing inflammation and tumour, raising that targeting MAIT can be a candidate for treatment of gastrointestinal diseases.

Integrated single-cell RNA sequencing analysis reveals a mesenchymal stem cell-associated signature for estimating prognosis and drug sensitivity in gastric cancer

BACKGROUND

Mesenchymal stem cells (MSCs) play an important role in regulating all stages of the immune response, angiogenesis, and transformation of matrix components in the tumor microenvironment. The aim of this study was to identify the prognostic value of MSC-related signatures in patients with gastric cancer (GC).

METHODS

MSC marker genes were identified by analyzing single-cell RNA sequencing (scRNA-seq) data for GC from the Gene Expression Omnibus (GEO) database. Using bulk sequencing data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD), as a training cohort, and data from GEO, as a validation cohort, we developed a risk model consisting of MSC prognostic signature genes, and classified GC patients into high- and low-MSC risk subgroups. Multifactorial Cox regression was used to evaluate whether MSC prognostic signature was an independent prognostic factor. An MSC nomogram was constructed combining clinical information and risk grouping. Subsequently, we evaluated the effect of MSC prognostic signature on immune cell infiltration, antitumor drugs and immune checkpoints and verified the expression of MSC prognostic signature by in vitro cellular assays.

RESULTS

In this study, 174 MSC marker genes were identified by analyzing scRNA-seq data. We identified seven genes (POSTN, PLOD2, ITGAV, MMP11, SDC2, MARCKS, ANXA5) to construct MSC prognostic signature. MSC prognostic signature was an independent risk factor in the TCGA and GEO cohorts. GC patients in the high-MSC risk group had worse prognoses. In addition, the MSC nomogram has a high clinical application value. Notably, the MSC signature can induce the development of a poor immune microenvironment. GC patients in the high MSC-risk group were more sensitive to anticancer drugs and tended to have higher levels of immune checkpoint markers. In qRT-PCR assays, the MSC signature was more highly expressed in GC cell lines.

CONCLUSIONS

The MSC marker gene-based risk signature developed in this study can not only be used to predict the prognosis of GC patients, but also has the potential to reflect the efficacy of antitumor therapies.

Transcriptional landscape of Kaposi sarcoma tumors identifies unique immunologic signatures and key determinants of angiogenesis

BACKGROUND

Kaposi sarcoma (KS) is a multicentric tumor caused by Kaposi sarcoma herpesvirus (KSHV) that leads to morbidity and mortality among people with HIV worldwide. KS commonly involves the skin but can occur in the gastrointestinal tract (GI) in severe cases.

METHODS

RNA sequencing was used to compare the cellular and KSHV gene expression signatures of skin and GI KS lesions in 44 paired samples from 19 participants with KS alone or with concurrent KSHV-associated diseases. Analyses of KSHV expression from KS lesions identified transcriptionally active areas of the viral genome.

RESULTS

The transcript of an essential viral lytic gene, ORF75, was detected in 91% of KS lesions. Analyses of host genes identified 370 differentially expressed genes (DEGs) unique to skin KS and 58 DEGs unique to GI KS lesions as compared to normal tissue. Interleukin (IL)-6 and IL-10 gene expression were higher in skin lesions as compared to normal skin but not in GI KS lesions. Twenty-six cellular genes were differentially expressed in both skin and GI KS tissues: these included Fms-related tyrosine kinase 4 (FLT4), encoding an angiogenic receptor, and Stanniocalcin 1 (STC1), a secreted glycoprotein. FLT4 and STC1 were further investigated in functional studies using primary lymphatic endothelial cells (LECs). In these models, KSHV infection of LECs led to increased tubule formation that was impaired upon knock-down of STC1 or FLT4.

CONCLUSIONS

This study of transcriptional profiling of KS tissue provides novel insights into the characteristics and pathogenesis of this unique virus-driven neoplasm.

Identification of memory B-cell-associated miRNA signature to establish a prognostic model in gastric adenocarcinoma

BACKGROUND

Memory B cells and microRNAs (miRNAs) play important roles in the progression of gastric adenocarcinoma (GAC), also known as stomach adenocarcinoma (STAD). However, few studies have investigated the use of memory B-cell-associated miRNAs in predicting the prognosis of STAD.

METHODS

We identified the marker genes of memory B cells by single-cell RNA sequencing (scRNA-seq) and identified the miRNAs associated with memory B cells by constructing an mRNA‒miRNA coexpression network. Then, univariate Cox, random survival forest (RSF), and stepwise multiple Cox regression (StepCox) algorithms were used to identify memory B-cell-associated miRNAs that were significantly related to overall survival (OS). A prognostic risk model was constructed and validated using these miRNAs, and patients were divided into a low-risk group and a high-risk group. In addition, the differences in clinicopathological features, tumour microenvironment, immune blocking therapy, and sensitivity to anticancer drugs in the two groups were analysed.

RESULTS

Four memory B-cell-associated miRNAs (hsa-mir-145, hsa-mir-125b-2, hsa-mir-100, hsa-mir-221) with significant correlations to OS were identified and used to construct a prognostic model. Time-dependent receiver operating characteristic (ROC) curve analysis confirmed the feasibility of the model. Kaplan‒Meier (K‒M) survival curve analysis showed that the prognosis was poor in the high-risk group. Comprehensive analysis showed that patients in the high-risk group had higher immune scores, matrix scores, and immune cell infiltration and a poor immune response. In terms of drug screening, we predicted eight drugs with higher sensitivity in the high-risk group, of which CGP-60474 was associated with the greatest sensitivity.

CONCLUSIONS

In summary, we identified memory B-cell-associated miRNA prognostic features and constructed a novel risk model for STAD based on scRNA-seq data and bulk RNA-seq data. Among patients in the high-risk group, STAD showed the highest sensitivity to CGP-60474. This study provides prognostic insights into individualized and precise treatment for STAD patients.

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.

Cancer-associated fibroblast expression of glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a prognostic marker in gastric cancer

Glutamine fructose-6-phosphate aminotransferase 2 (GFPT2) is a rate-limiting enzyme in hexosamine biosynthesis involved in the occurrence and progress of many cancers. What role it plays in gastric cancer (GC) is still unclear. In this study, transcriptome sequencing data from the Harbin Medical University (HMU)-GC cohort and The Cancer Genome Atlas (TCGA) dataset were combined with the HMU-TCGA training cohort to analyze the biological function and clinical significance of GFPT2. The correlation of GFPT2 with immune cells and stromal cells was analyzed in the GC immune microenvironment through transcriptome sequencing data and a public single-cell sequencing database. In cell lines, GC tissues, and the tissue microarray, GFPT2 protein expression was confirmed by western blotting and immunohistochemistry. The mRNA of GFPT2 was highly expressed in the tumor (p < 0.001), and GC cells and tumors expressed high levels of GFPT2 protein. Compared to low expression, high GFPT2 mRNA expression was associated with higher levels of tumor invasion, higher pathological stages, and poor prognosis (p = 0.02) in GC patients. In a drug susceptibility analysis, GFPT2 mRNA expression was associated with multiple chemotherapeutic drug sensitivity, including docetaxel, paclitaxel, and cisplatin. Gene enrichment analysis found that GFPT2 was mainly primarily involved in the extracellular matrix receptor interaction pathway. The ESTIMATE, CIBERSORT, and ssGSEA algorithms showed that GFPT2 was associated with immune cell infiltration. In addition, GFPT2 was more likely to be expressed within cancer-associated fibroblasts (CAFs), and high levels of GFPT2 expression were highly correlated with four CAFs scores (all p < 0.05). Finally, a prognostic model to assess the risk of death in GC patients was constructed based on GFPT2 protein expression and lymph node metastasis rate. In conclusion, GFPT2 plays an essential role in the function of CAFs in GC. It can be used as a biomarker to assess GC prognosis and immune infiltration.

Single-cell RNA sequencing reveals small extracellular vesicles derived from malignant cells that contribute to angiogenesis in human breast cancers

BACKGROUND

Breast cancer is the most common cancer affecting women across the world. Tumor endothelial cells (TECs) and malignant cells are the major constituents of the tumor microenvironment (TME), but their origin and role in shaping disease initiation, progression, and treatment responses remain unclear due to significant heterogeneity.

METHODS

Tissue samples were collected from eight patients presenting with breast cancer. Single-cell RNA sequencing (scRNA-seq) analysis was employed to investigate the presence of distinct cell subsets in the tumor microenvironment. InferCNV was used to identify cancer cells. Pseudotime trajectory analysis revealed the dynamic process of breast cancer angiogenesis. We validated the function of small extracellular vesicles (sEVs)-derived protein phosphatase 1 regulatory inhibitor subunit 1B (PPP1R1B) in vitro experiments.

RESULTS

We performed single-cell transcriptomics analysis of the factors associated with breast cancer angiogenesis and identified twelve subclusters of endothelial cells involved in the tumor microenvironment. We also identified the role of TECs in tumor angiogenesis and confirmed their participation in different stages of angiogenesis, including communication with other cell types via sEVs. Overall, the research uncovered the TECs heterogeneity and the expression levels of genes at different stages of tumor angiogenesis.

CONCLUSIONS

This study showed sEVs derived from breast cancer malignant cells promote blood vessel formation by activating endothelial cells through the transfer of PPP1R1B. This provides a new direction for the development of anti-angiogenic therapies for human breast cancer.

Advances in single-cell RNA sequencing and its applications in cancer research

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.

Integration of single-cell RNA sequencing and bulk RNA transcriptome sequencing reveals a heterogeneous immune landscape and pivotal cell subpopulations associated with colorectal cancer prognosis

Introduction

Colorectal cancer (CRC) is a highly heterogeneous cancer. The molecular and cellular characteristics differ between the colon and rectal cancer type due to the differences in their anatomical location and pathological properties. With the advent of single-cell sequencing, it has become possible to analyze inter- and intra-tumoral tissue heterogeneities.

Methods

A comprehensive CRC immune atlas, comprising 62,398 immune cells, was re-structured into 33 immune cell clusters at the single-cell level. Further, the immune cell lineage heterogeneity of colon, rectal, and paracancerous tissues was explored. Simultaneously, we characterized the TAM phenotypes and analyzed the transcriptomic factor regulatory network of each macrophage subset using SCENIC. In addition, monocle2 was used to elucidate the B cell developmental trajectory. The crosstalk between immune cells was explored using CellChat and the patterns of incoming and outgoing signals within the overall immune cell population were identified. Afterwards, the bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) were combined and the relative infiltration abundance of the identified subpopulations was analyzed using CIBERSORT. Moreover, cell composition patterns could be classified into five tumor microenvironment (TME) subtypes by employing a consistent non-negative matrix algorithm. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells in the tumor microenvironment were analyzed by multiplex immunohistochemistry.

Results

In the T cell lineage, we found that CXCL13+T cells were more widely distributed in colorectal cancer tissues, and the proportion of infiltration was increased. In addition, Th17 was found accounted for the highest proportion in CD39+CD101+PD1+T cells. Mover, Ma1-SPP1 showed the characteristics of M2 phenotypes and displayed an increased proportion in tumor tissues, which may promote angiogenesis. Plasma cells (PCs) displayed a significantly heterogeneous distribution in tumor as well as normal tissues. Specifically, the IgA+ PC population could be shown to be decreased in colorectal tumor tissues whereas the IgG+ PC one was enriched. In addition, information flow mediated by SPP1 and CD44, regulate signaling pathways of tumor progression. Among the five TME subtypes, the TME-1 subtype displayed a markedly reduced proportion of T-cell infiltration with the highest proportion of macrophages which was correlated to the worst prognosis. Finally, the co-expression and interaction between SPP1+TAMs and Treg cells were observed in the CD44 enriched region.

Discussion

The heterogeneity distribution and phenotype of immune cells were analyzed in colon cancer and rectal cancer at the single-cell level. Further, the prognostic role of major tumor-infiltrating lymphocytes and TME subtypes in CRC was evaluated by integrating bulk RNA. These findings provide novel insight into the immunotherapy of CRC.

Plasma Exosome Proteins ILK1 and CD14 Correlated with Organ-Specific Metastasis in Advanced Gastric Cancer Patients

The exosome plays important roles in driving tumor metastasis, while the role of exosome proteins during organ-specific metastasis in gastric cancer has not been fully understood. To address this question, peripheral blood samples from 12 AGC patients with organ-specific metastasis, including distant lymphatic, hepatic and peritoneal metastasis, were collected to purify exosomes and to detect exosome proteins by Nano-HPLC-MS/MS. Gastric cancer cell lines were used for in vitro experiments. Peripheral blood sample and ascites sample from one patient were further analyzed by single-cell RNA sequencing. GO and KEGG enrichment analysis showed different expression proteins of hepatic metastasis were correlated with lipid metabolism. For peritoneal metastasis, actin cytoskeleton regulation and glycolysis/gluconeogenesis could be enriched. ILK1 and CD14 were correlated with hepatic and peritoneal metastasis, respectively. Overexpression of CD14 and ILK1 impacted the colony formation ability of gastric cancer and increased expression of Vimentin. CD14 derived from immune cells in malignant ascites correlated with high activation of chemokine- and cytokine-mediated signaling pathways. In summary, biological functions of plasma exosome proteins among AGC patients with different metastatic modes were distinct, in which ILK1 and CD14 were correlated with organ-specific metastasis.

The double-edged role of neutrophil heterogeneity in inflammatory diseases and cancers

Neutrophils are important immune cells act as the body's first line of defense against infection and respond to diverse inflammatory cues. Many studies have demonstrated that neutrophils display plasticity in inflammatory diseases and cancers. Clarifying the role of neutrophil heterogeneity in inflammatory diseases and cancers will contribute to the development of novel treatment strategies. In this review, we have presented a review on the development of the understanding on neutrophil heterogeneity from the traditional perspective and a high-resolution viewpoint. A growing body of evidence has confirmed the double-edged role of neutrophils in inflammatory diseases and tumors. This may be due to a lack of precise understanding of the role of specific neutrophil subsets in the disease. Thus, elucidating specific neutrophil subsets involved in diseases would benefit the development of precision medicine. Thusly, we have summarized the relevance and actions of neutrophil heterogeneity in inflammatory diseases and cancers comprehensively. Meanwhile, we also discussed the potential intervention strategy for neutrophils. This review is intended to deepen our understanding of neutrophil heterogeneity in inflammatory diseases and cancers, while hold promise for precise treatment of neutrophil-related diseases.

Single-cell RNA sequencing reveals enhanced antitumor immunity after combined application of PD-1 inhibitor and Shenmai injection in non-small cell lung cancer

BACKGROUND

Immune checkpoint inhibitors (ICIs) have altered the clinical management of non-small cell lung cancer (NSCLC). However, the low response rate, severe immune-related adverse events (irAEs), and hyperprogressive disease following ICIs monotherapy require attention. Combination therapy may overcome these limitations and traditional Chinese medicine with immunomodulatory effects provides a promising approach. Shenmai injection (SMI) is a clinically effective adjuvant treatment for cancer with chemotherapy and radiotherapy. Therefore, the combined effects and mechanisms of SMI and programmed death-1 (PD-1) inhibitor against NSCLC was focused on this study.

METHODS

A Lewis lung carcinoma mouse model and a lung squamous cell carcinoma humanized mouse model were used to investigate the combined efficacy and safety of SMI and PD-1 inhibitor. The synergistic mechanisms of the combination therapy against NSCLC were explored using single-cell RNA sequencing. Validation experiments were performed using immunofluorescence analysis, in vitro experiment, and bulk transcriptomic datasets.

RESULTS

In both models, combination therapy alleviated tumor growth and prolonged survival without increasing irAEs. The GZMA^high and XCL1^high natural killer (NK) cell subclusters with cytotoxic and chemokine signatures increased in the combination therapy, while malignant cells from combination therapy were mainly in the apoptotic state, suggesting that mediating tumor cell apoptosis through NK cells is the main synergistic mechanisms of combination therapy. In vitro experiment confirmed that combination therapy increased secretion of Granzyme A by NK cells. Moreover, we discovered that PD-1 inhibitor and SMI combination blocked inhibitory receptors on NK and T cells and restores their antitumoral activity in NSCLC better than PD-1 inhibitor monotherapy, and immune and stromal cells exhibited a decrease of angiogenic features and attenuated cancer metabolism reprogramming in microenvironment of combination therapy.

CONCLUSIONS

This study demonstrated that SMI reprograms tumor immune microenvironment mainly by inducing NK cells infiltration and synergizes with PD-1 inhibitor against NSCLC, suggested that targeting NK cells may be an important strategy for combining with ICIs. Video Abstract.

Development and validation of a ligand-receptor pairs signature to predict outcome and provide a therapeutic strategy in gastric cancer

BACKGROUND

An important factor in tumor development and progression is the tumor microenvironment (TME), which is heterogeneous. Previous studies have mainly investigated the expression profile and prognostic values of genes in gastric cancer (GC) at the cell population level but neglected the interactions and heterogeneity between cells.

METHODS

The pattern of ligand-receptor (LR) interactions was delineated on a scRNA-seq dataset containing 44,953 cells from nine GC patients and a fourth bulk RNA-seq dataset including data from 1159 GC patients. We then constructed an LR.Score scoring model to comprehensively evaluate the influence of LR-pairs on the TME, overall survival, and immunotherapy response in GC patients from several cohorts.

RESULTS

Cell communication network among 13 cell types was constructed based on the LR-pairs. We proposed a new molecular subtyping model for GC based on the LR-pairs and revealed the differences in prognosis, pathophysiologic features, mutation characteristics, function enrichment, and immunological characteristics among the three subtypes. Finally, an LR.Score model based on LR-pairs was developed and validated on several datasets.

CONCLUSIONS

Based on the selected LR-pairs, we successfully constructed a novel prediction model and observed its well performance on molecular subtyping, target and pathway screening, prognosis judging, and immunotherapy response predicting.

Understanding tumour endothelial cell heterogeneity and function from single-cell omics

Anti-angiogenic therapies (AATs) are used to treat different types of cancers. However, their success is limited owing to insufficient efficacy and resistance. Recently, single-cell omics studies of tumour endothelial cells (TECs) have provided new mechanistic insight. Here, we overview the heterogeneity of human TECs of all tumour types studied to date, at the single-cell level. Notably, most human tumour types contain varying numbers but only a small population of angiogenic TECs, the presumed targets of AATs, possibly contributing to the limited efficacy of and resistance to AATs. In general, TECs are heterogeneous within and across all tumour types, but comparing TEC phenotypes across tumours is currently challenging, owing to the lack of a uniform nomenclature for endothelial cells and consistent single-cell analysis protocols, urgently raising the need for a more consistent approach. Nonetheless, across most tumour types, universal TEC markers (ACKR1, PLVAP and IGFBP3) can be identified. Besides angiogenesis, biological processes such as immunomodulation and extracellular matrix organization are among the most commonly predicted enriched signatures of TECs across different tumour types. Although angiogenesis and extracellular matrix targets have been considered for AAT (without the hoped success), the immunomodulatory properties of TECs have not been fully considered as a novel anticancer therapeutic approach. Therefore, we also discuss progress, limitations, solutions and novel targets for AAT development.

Cellular barcoding: From developmental tracing to anti-tumor drug discovery

Clonal evolution has gained immense attention in explaining cancer cell status, history, and fate during cancer progression. Current single-cell or spatial transcriptome technologies have broadened our understanding of various mechanisms underlying cancer initiation, relapse, and drug resistance. However, technical challenges still hinder a better understanding of the dynamics of distinctive phenotypic states and abnormal trajectories from normal physiological transition to malignant stages. Cellular barcoding enabled lineage tracing on parallelly massive cells at single-cell resolution through different mechanisms lately, enabling new insights into exploring developmental trajectories, cancer progression, and targeted therapies. This review summarizes the latest noteworthy and robust strategies for different types of cellular barcodes. To introduce the major characteristics, advantages and limitations of these different strategies, this review will further guide in choosing or improving cellular barcoding technologies and their applications in cancer research.

Transcriptomic Analysis Reveals Candidate Ligand-Receptor Pairs and Signaling Networks Mediating Intercellular Communication between Hair Matrix Cells and Dermal Papilla Cells from Cashmere Goats

Hair fiber growth is determined by the spatiotemporally controlled proliferation, differentiation, and apoptosis of hair matrix cells (HMCs) inside the hair follicle (HF); however, dermal papilla cells (DPCs), the cell population surrounded by HMCs, manipulate the above processes via intercellular crosstalk with HMCs. Therefore, exploring how the mutual commutations between the cells are molecularly achieved is vital to understanding the mechanisms underlying hair growth. Here, based on our previous successes in cultivating HMCs and DPCs from cashmere goats, we combined a series of techniques, including in vitro cell coculture, transcriptome sequencing, and bioinformatic analysis, to uncover ligand-receptor pairs and signaling networks mediating intercellular crosstalk. Firstly, we found that direct cellular interaction significantly alters cell cycle distribution patterns and changes the gene expression profiles of both cells at the global level. Next, we constructed the networks of ligand-receptor pairs mediating intercellular autocrine or paracrine crosstalk between the cells. A few pairs, such as LEP-LEPR, IL6-EGFR, RSPO1-LRP6, and ADM-CALCRL, are found to have known or potential roles in hair growth by acting as bridges linking cells. Further, we inferred the signaling axis connecting the cells from transcriptomic data with the advantage of CCCExplorer. Certain pathways, including INHBA-ACVR2A/ACVR2B-ACVR1/ACVR1B-SMAD3, were predicted as the axis mediating the promotive effect of INHBA on hair growth via paracrine crosstalk between DPCs and HMCs. Finally, we verified that LEP-LEPR and IL1A-IL1R1 are pivotal ligand-receptor pairs involved in autocrine and paracrine communication of DPCs and HMCs to DPCs, respectively. Our study provides a comprehensive landscape of intercellular crosstalk between key cell types inside HF at the molecular level, which is helpful for an in-depth understanding of the mechanisms related to hair growth.

Integrative single-cell multiomics analyses dissect molecular signatures of intratumoral heterogeneities and differentiation states of human gastric cancer

Human gastric cancer is a highly lethal disease, but the underlying multiomic molecular signatures remain largely unclear. Here, we performed multi-regional sampling, parallel single-cell multiomics sequencing and integrated analyses of human gastric cancer. We identified common transcriptomic alterations of gastric cancer cells, such as aberrant down-regulation of genes associated with normal stomach function and up-regulation of KRT7, PI3, S100A4, etc. Surprisingly, aberrant and prevalent up-regulation of genes highly expressed in normal colorectal epithelial cells were also identified in cancer cells, which may be partially regulated by promoter chromatin accessibility and DNA methylation levels. We revealed the single-cell DNA methylome landscape of gastric cancer, and identified candidate DNA methylation biomarkers, such as hypermethylated promoters of TMEM240 and HAGLROS, and hypomethylated promoters of TRPM2-AS and HRH1. Additionally, the relationships between genetic lineages, DNA methylation and transcriptomic clusters were systematically revealed at single-cell level. We showed that DNA methylation heterogeneities were mainly among different genetic lineages of cancer cells. Moreover, we found that DNA methylation levels of cancer cells with poorer differentiation states tend to be higher than those of cancer cells with better differentiation states in the primary tumor within the same patient, although still lower than in normal gastric epithelial cells. Cancer cells with poorer differentiation states also prevalently down-regulated MUC1 expression and immune-related pathways, and had poor infiltration of CD8⁺ T cells. Our study dissected the molecular signatures of intratumoral heterogeneities and differentiation states of human gastric cancer using integrative single-cell multiomics analyses.