Comprehensive analysis of metastatic gastric cancer tumour cells using single-cell RNA-seq

Analysis of lymph node metastasis and survival prognosis in early gastric cancer patients: A retrospective study

BACKGROUND

Early gastric cancer (EGC) is a common malignant tumor of the digestive system, and its lymph node metastasis and survival prognosis have been concerning. By retrospectively analyzing the clinical data of EGC patients, we can better understand the status of lymph node metastasis and its impact on survival and prognosis.

AIM

To evaluate the prognosis of EGC patients and the factors that affect lymph node metastasis.

METHODS

The clinicopathological data of 1011 patients with EGC admitted to our hospital between January 2015 and December 2023 were collected in a retrospective cohort study. There were 561 males and 450 females. The mean age was 58 ± 11 years. The patient underwent radical gastrectomy. The status of lymph node metastasis in each group was determined according to the pathological examination results of surgical specimens. The outcomes were as follows: (1) Lymph node metastasis in EGC patients; (2) Analysis of influencing factors of lymph node metastasis in EGC; and (3) Analysis of prognostic factors in patients with EGC. Normally distributed measurement data are expressed as mean ± SD, and a t test was used for comparisons between groups. The data are expressed as absolute numbers or percentages, and the chi-square test was used for comparisons between groups. Rank data were compared using a nonparametric rank sum test. A log-rank test and a logistic regression model were used for univariate analysis. A logistic stepwise regression model and a Cox stepwise regression model were used for multivariate analysis. The Kaplan-Meier method was used to calculate the survival rate and construct survival curves. A log-rank test was used for survival analysis.

RESULTS

Analysis of influencing factors of lymph node metastasis in EGC. The results of the multifactor analysis showed that tumor length and diameter, tumor site, tumor invasion depth, vascular thrombus, and tumor differentiation degree were independent influencing factors for lymph node metastasis in patients with EGC (odds ratios = 1.80, 1.49, 2.65, 5.76, and 0.60; 95%CI: 1.29-2.50, 1.11-2.00, 1.81-3.88, 3.87-8.59, and 0.48-0.76, respectively; P < 0.05). Analysis of prognostic factors in patients with EGC. All 1011 patients with EGC were followed up for 43 (0-13) months. The 3-year overall survival rate was 97.32%. Multivariate analysis revealed that age > 60 years and lymph node metastasis were independent risk factors for prognosis in patients with EGC (hazard ratio = 9.50, 2.20; 95%CI: 3.31-27.29, 1.00-4.87; P < 0.05). Further analysis revealed that the 3-year overall survival rates of gastric cancer patients aged > 60 years and ≤ 60 years were 99.37% and 94.66%, respectively, and the difference was statistically significant (P < 0.05). The 3-year overall survival rates of patients with and without lymph node metastasis were 95.42% and 97.92%, respectively, and the difference was statistically significant (P < 0.05).

CONCLUSION

The lymph node metastasis rate of EGC patients was 23.64%. Tumor length, tumor site, tumor infiltration depth, vascular cancer thrombin, and tumor differentiation degree were found to be independent factors affecting lymph node metastasis in EGC patients. Age > 60 years and lymph node metastasis are independent risk factors for EGC prognosis.

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.

Exploring the metastasis-related biomarker and carcinogenic mechanism in liver cancer based on single cell technology

Background

Hepatocellular carcinoma (HCC) is a fatal primary malignancy characterized by high invasion and migration. We aimed to explore the underlying metastasis-related mechanism supporting the development of HCC.

Methods

The dataset of single cell RNA-seq (GSE149614) were collected for cell clustering by using the Seurat R package, the FindAllMarkers function was used to find the highly expression and defined the cell cluster. The WebGestaltR package was used for the GO and KEGG function analysis of shared genes, the Gene Set Enrichment Analysis (GSVA) was performed by clusterProfiler R package, the hTFtarget database was used to identify the crucial transcription factors (TFs), the Genomics of Drug Sensitivity in Cancer (GDSC) database was used for the drug sensitivity analysis. Finally, the overexpression and trans-well assay was used for gene function analysis.

Results

We obtained 9 cell clusters from the scRNA-seq data, including the nature killer (NK)/T cells, Myeloid cells, Hepatocytes, Epithelial cells, Endothelial cells, Plasma B cells, Smooth muscle cells, B cells, Liver bud hepatic cells. Further cell ecological analysis indicated that the Hepatocytes and Endothelial cell cluster were closely related to the cancer metastasis. Subsequently, the NDUFA4L2-Hepatocyte, GTSE1-Hepatocyte, ENTPD1-Endothelial and NDUFA4L2-Endothelial were defined as metastasis-supporting cell clusters, in which the NDUFA4L2-Hepatocyte cells was closely related to angiogenesis, while the NDUFA4L2-Endothelial was related with the inflammatory response and complement response. The overexpression and trans-well assay displayed that NDUFA4L2 exhibited clearly metastasis-promoting role in HCC progression.

Conclusion

We identified and defined 4 metastasis-supporting cell clusters by using the single cell technology, the specify shared gene was observed and played crucial role in promoting cancer progression, our findings were expected to provide new insight in control cancer metastasis.

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.

Targeting FAPα-positive lymph node metastatic tumor cells suppresses colorectal cancer metastasis

Lymphatic metastasis is the main metastatic route for colorectal cancer, which increases the risk of cancer recurrence and distant metastasis. The properties of the lymph node metastatic colorectal cancer (LNM-CRC) cells are poorly understood, and effective therapies are still lacking. Here, we found that hypoxia-induced fibroblast activation protein alpha (FAPα) expression in LNM-CRC cells. Gain- or loss-function experiments demonstrated that FAPα enhanced tumor cell migration, invasion, epithelial-mesenchymal transition, stemness, and lymphangiogenesis via activation of the STAT3 pathway. In addition, FAPα in tumor cells induced extracellular matrix remodeling and established an immunosuppressive environment via recruiting regulatory T cells, to promote colorectal cancer lymph node metastasis (CRCLNM). Z-GP-DAVLBH, a FAPα-activated prodrug, inhibited CRCLNM by targeting FAPα-positive LNM-CRC cells. Our study highlights the role of FAPα in tumor cells in CRCLNM and provides a potential therapeutic target and promising strategy for CRCLNM.

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.

Expression patterns of claudins in cancer

Claudins are four-transmembrane proteins, which were found in tight junctions. They maintain cell barriers and regulate cell differentiation and proliferation. They are involved in maintaining cellular polarity and normal functions. Different claudins show different expression patterns. The expression level and localization of claudins are altered in various cancers. They promote or inhibit proliferation, invasion, and migration of cancer cells through multiple signaling pathways. Therefore, claudins may serve as diagnostic markers, novel therapeutic targets, and prognostic risk factors. The important roles of claudins in cancer aroused our great interest. In the present review, we provide a summary of insights into expression patterns of claudins in cancer, which is more comprehensive and provides new ideas for further research.

Gastric cancer metastasis-related NT5DC2 indicates unfavorable prognosis of patients

PURPOSE

Approximately 80 to 90% of patients with gastric cancer (GC) eventually develop into metastatic GC nowadays,because GC is difficult to be diagnosed at an early stage. GC patients with metastases typically have a poor prognosis. It is necessary to explore a potential prognostic marker in metastatic GC.

METHODS

All GC data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The metastasis-related candidate gene and its role in GC were analyzed by comprehensive analysis.

RESULTS

Totally 1049 metastasis-related genes were identified in GC. Univariate Cox regression analysis screened the top 10 genes (PDHX, SLC43A1, CSAG2, NT5DC2, CSAG1, FMN1, MED1, HIVEP2, FNDC3A, and PPP1R2) that were closely correlated with prognosis of GC patients. Among which, NT5DC2 was screened as the target gene for subsequent study. The NT5DC2 expression were increased in primary GC and metastatic GC samples. Moreover, GC patients with high NT5DC2 expression exhibited shorter overall survival and post progression survival, and the NT5DC2 was metastatic GC patients' independent prognostic factor. Totally 29 pathways were activated in metastatic GC samples with high NT5DC2 expression. Four immune cells' infiltration were significantly different between NT5DC2 high and low expressed metastatic GC patients. NT5DC2 showed significantly negative correlations with 6 types of immune cells' critical marker genes and 5 types of immune cell infiltration. The 10 immune checkpoint expressions were decreased in high NTDC2 expression metastatic GC patients.

CONCLUSIONS

NT5DC2 plays a prognostic role in metastatic GC. GC patients with high NT5DC2 expression indicates unfavorable prognosis.

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.

circRPS19 affects HK2‑mediated aerobic glycolysis and cell viability via the miR‑125a‑5p/USP7 pathway in gastric cancer

Despite advances in diagnosis and treatment, gastric cancer (GC) remains a refractory disease, which limits overall survival. Therefore, it is key to identify novel targets to develop more effective and precise treatment. Circular RNAs (circRNAs) serve essential roles in the process of various human cancers. Through analyzing GSE83521 dataset, the present study identified a novel circRNA derived from ribosomal protein S19 (circRPS19), which was considered a potential treatment target for GC. Results of RT‑qPCR indicated that circRPS19 was upregulated in GC compared with normal gastric epithelial cells. Loss‑of function assays revealed that silencing of circRPS19 suppressed proliferation and aerobic glycolysis but increased apoptosis of GC cells. circRPS19 upregulated ubiquitin‑specific processing protease 7 (USP7) expression by sponging microRNA (miR)‑125a‑5p. circRPS19 stabilized hexokinase 2 (HK2) protein by USP7‑mediated deubiquitination of HK2. In vivo experiments confirmed that circRPS19 promoted GC progression and aerobic glycolysis. Taken together, circRPS19 induced aerobic glycolysis of GC cells by stabilizing HK2 protein via the miR‑125a‑5p/USP7 axis and thus promoting the progression of GC. These findings suggested that circRPS19 served a critical role in the progression of GC and may be a novel therapeutic target for GC.

Identification and validation of biomarkers for epithelial-mesenchymal transition-related cells to estimate the prognosis and immune microenvironment in primary gastric cancer by the integrated analysis of single-cell and bulk RNA sequencing data

BACKGROUND

The epithelial-mesenchymal transition (EMT) is associated with gastric cancer (GC) progression and immune microenvironment. To better understand the heterogeneity underlying EMT, we integrated single-cell RNA-sequencing (scRNA-seq) data and bulk sequencing data from GC patients to evaluate the prognostic utility of biomarkers for EMT-related cells (ERCs), namely, cancer-associated fibroblasts (CAFs) and epithelial cells (ECs).

METHODS

scRNA-seq data from primary GC tumor samples were obtained from the Gene Expression Omnibus (GEO) database to identify ERC marker genes. Bulk GC datasets from the Cancer Genome Atlas (TCGA) and GEO were used as training and validation sets, respectively. Differentially expressed markers were identified from the TCGA database. Univariate Cox, least-absolute shrinkage, and selection operator regression analyses were performed to identify EMT-related cell-prognostic genes (ERCPGs). Kaplan-Meier, Cox regression, and receiver-operating characteristic (ROC) curve analyses were adopted to evaluate the prognostic utility of the ERCPG signature. An ERCPG-based nomogram was constructed by integrating independent prognostic factors. Finally, we evaluated the correlations between the ERCPG signature and immune-cell infiltration and verified the expression of ERCPG prognostic signature genes by in vitro cellular assays.

RESULTS

The ERCPG signature was comprised of seven genes (COL4A1, F2R, MMP11, CAV1, VCAN, FKBP10, and APOD). Patients were divided into high- and low-risk groups based on the ERCPG risk scores. Patients in the high-risk group showed a poor prognosis. ROC and calibration curves suggested that the ERCPG signature and nomogram had a good prognostic utility. An immune cell-infiltration analysis suggested that the abnormal expression of ERCPGs induced the formation of an unfavorable tumor immune microenvironment. In vitro cellular assays showed that ERCPGs were more abundantly expressed in GC cell lines compared to normal gastric tissue cell lines.

CONCLUSIONS

We constructed and validated an ERCPG signature using scRNA-seq and bulk sequencing data from ERCs of GC patients. Our findings support the estimation of patient prognosis and tumor treatment in future clinical practice.

Single-cell transcriptome sequencing reveals heterogeneity of gastric cancer: progress and prospects

Gastric cancer is one of the most serious malignant tumor and threatens the health of people worldwide. Its heterogeneity leaves many clinical problems unsolved. To treat it effectively, we need to explore its heterogeneity. Single-cell transcriptome sequencing, or single-cell RNA sequencing (scRNA-seq), reveals the complex biological composition and molecular characteristics of gastric cancer at the level of individual cells, which provides a new perspective for understanding the heterogeneity of gastric cancer. In this review, we first introduce the current procedure of scRNA-seq, and discuss the advantages and limitations of scRNA-seq. We then elaborate on the research carried out with scRNA-seq in gastric cancer in recent years, and describe how it reveals cell heterogeneity, the tumor microenvironment, oncogenesis and metastasis, as well as drug response in to gastric cancer, to facilitate early diagnosis, individualized therapy, and prognosis evaluation.

Uncovering the special microbiota associated with occurrence and progression of gastric cancer by using RNA-sequencing

Gastric cancer (GC) has been identified as the third deadly cancer in the world. Accumulating researches suggest a potential role of microorganisms in tumorigenesis. However, the composition of microbiota in GC tissues is not clear and it changes throughout the different stages of GC remain mostly elusive. Our study integrated RNA-Seq data of 727 samples derived from gastric tissues across four datasets and revealed its microbial composition. In order to remove the false positive results, core taxa were defined and characterized. Based on it, we analyzed the influence of biological factors on its composition. The pan-microbiome of gastric tissues was estimated to be over than 1400 genera. Seventeen core genera were identified. Among them, Helicobacter, Lysobacter were significantly enriched in normal tissues, while Pseudomonas was enriched in tumor tissues. Interestingly, Acinetobacter, Pasteurella, Streptomyces, Chlamydia, and Lysobacter, showed a significant increase trend during tumor development and formed strong intra/inter-correlations among them or with other genera. Furthermore, we found that tumor stage played an important role in altering the microbial composition of GC tissues. This study provides support for the in-depth study of tumor microbiome, and the specific microbiome excavated provides a possibility for the subsequent identification of potential biomarkers for GC.

Testing for Phylogenetic Signal in Single-Cell RNA-Seq Data

Phylogenetic methods are emerging as a useful tool to understand cancer evolutionary dynamics, including tumor structure, heterogeneity, and progression. Most currently used approaches utilize either bulk whole genome sequencing or single-cell DNA sequencing and are based on calling copy number alterations and single nucleotide variants (SNVs). Single-cell RNA sequencing (scRNA-seq) is commonly applied to explore differential gene expression of cancer cells throughout tumor progression. The method exacerbates the single-cell sequencing problem of low yield per cell with uneven expression levels. This accounts for low and uneven sequencing coverage and makes SNV detection and phylogenetic analysis challenging. In this article, we demonstrate for the first time that scRNA-seq data contain sufficient evolutionary signal and can also be utilized in phylogenetic analyses. We explore and compare results of such analyses based on both expression levels and SNVs called from scRNA-seq data. Both techniques are shown to be useful for reconstructing phylogenetic relationships between cells, reflecting the clonal composition of a tumor. Both standardized expression values and SNVs appear to be equally capable of reconstructing a similar pattern of phylogenetic relationship. This pattern is stable even when phylogenetic uncertainty is taken in account. Our results open up a new direction of somatic phylogenetics based on scRNA-seq data. Further research is required to refine and improve these approaches to capture the full picture of somatic evolutionary dynamics in cancer.

A classification method of gastric cancer subtype based on residual graph convolution network

Background: Clinical diagnosis and treatment of tumors are greatly complicated by their heterogeneity, and the subtype classification of cancer frequently plays a significant role in the subsequent treatment of tumors. Presently, the majority of studies rely far too heavily on gene expression data, omitting the enormous power of multi-omics fusion data and the potential for patient similarities. Method: In this study, we created a gastric cancer subtype classification model called RRGCN based on residual graph convolutional network (GCN) using multi-omics fusion data and patient similarity network. Given the multi-omics data's high dimensionality, we built an artificial neural network Autoencoder (AE) to reduce the dimensionality of the data and extract hidden layer features. The model is then built using the feature data. In addition, we computed the correlation between patients using the Pearson correlation coefficient, and this relationship between patients forms the edge of the graph structure. Four graph convolutional network layers and two residual networks with skip connections make up RRGCN, which reduces the amount of information lost during transmission between layers and prevents model degradation. Results: The results show that RRGCN significantly outperforms other classification methods with an accuracy as high as 0.87 when compared to four other traditional machine learning methods and deep learning models. Conclusion: In terms of subtype classification, RRGCN excels in all areas and has the potential to offer fresh perspectives on disease mechanisms and disease progression. It has the potential to be used for a broader range of disorders and to aid in clinical diagnosis.

Molecular pathogenesis, targeted therapies, and future perspectives for gastric cancer

Gastric cancer is a major source of global cancer mortality with limited treatment options and poor patient survival. As our molecular understanding of gastric cancer improves, we are now beginning to recognize that these cancers are a heterogeneous group of diseases with incredibly unique pathogeneses and active oncogenic pathways. It is this molecular diversity and oftentimes lack of common oncogenic driver mutations that bestow the poor treatment responses that oncologists often face when treating gastric cancer. In this review, we will examine the treatments for gastric cancer including up-to-date molecularly targeted therapies and immunotherapies. We will then review the molecular subtypes of gastric cancer to highlight the diversity seen in this disease. We will then shift our discussion to basic science and gastric cancer mouse models as tools to study gastric cancer molecular heterogeneity. Furthermore, we will elaborate on a molecular process termed paligenosis and the cyclical hit model as key events during gastric cancer initiation that impart nondividing mature differentiated cells the ability to re-enter the cell cycle and accumulate disparate genomic mutations during years of chronic inflammation and injury. As our basic science understanding of gastric cancer advances, so too must our translational and clinical efforts. We will end with a discussion regarding single-cell molecular analyses and cancer organoid technologies as future translational avenues to advance our understanding of gastric cancer heterogeneity and to design precision-based gastric cancer treatments. Elucidation of interpatient and intratumor heterogeneity is the only way to advance future cancer prevention, diagnoses and treatment.

Identification of novel tumor microenvironment-associated genes in gastric cancer based on single-cell RNA-sequencing datasets

Tumor microenvironment and heterogeneity play vital roles in the development and progression of gastric cancer (GC). In the past decade, a considerable amount of single-cell RNA-sequencing (scRNA-seq) studies have been published in the fields of oncology and immunology, which improve our knowledge of the GC immune microenvironment. However, much uncertainty still exists about the relationship between the macroscopic and microscopic data in transcriptomics. In the current study, we made full use of scRNA-seq data from the Gene Expression Omnibus database (GSE134520) to identify 25 cell subsets, including 11 microenvironment-related cell types. The MIF signaling pathway network was obtained upon analysis of receptor–ligand pairs and cell–cell interactions. By comparing the gene expression in a wide variety of cells between intestinal metaplasia and early gastric cancer, we identified 64 differentially expressed genes annotated as immune response and cellular communication. Subsequently, we screened these genes for prognostic clinical value based on the patients’ follow-up data from The Cancer Genome Atlas. TMPRSS15, VIM, APOA1, and RNASE1 were then selected for the construction of LASSO risk scores, and a nomogram model incorporating another five clinical risk factors was successfully created. The effectiveness of least absolute shrinkage and selection operator risk scores was validated using gene set enrichment analysis and levels of immune cell infiltration. These findings will drive the development of prognostic evaluations affected by the immune tumor microenvironment in GC.

Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

Single-cell RNA sequencing (scRNAseq) technology is still relatively new in the field of gastric cancer immunology but gaining significant traction. This technology now provides unprecedented insights into the intratumoral and intertumoral heterogeneities at the immunological, cellular, and molecular levels. Within the last few years, a volume of publications reported the usefulness of scRNAseq technology in identifying thus far elusive immunological mechanisms that may promote and impede gastric cancer development. These studies analyzed datasets generated from primary human gastric cancer tissues, metastatic ascites fluid from gastric cancer patients, and laboratory-generated data from in vitro and in vivo models of gastric diseases. In this review, we overview the exciting findings from scRNAseq datasets that uncovered the role of critical immune cells, including T cells, B cells, myeloid cells, mast cells, ILC2s, and other inflammatory stromal cells, like fibroblasts and endothelial cells. In addition, we also provide a synopsis of the initial scRNAseq findings on the interesting epithelial cell responses to inflammation. In summary, these new studies have implicated roles for T and B cells and subsets like NKT cells in tumor development and progression. The current studies identified diverse subsets of macrophages and mast cells in the tumor microenvironment, however, additional studies to determine their roles in promoting cancer growth are needed. Some groups specifically focus on the less prevalent ILC2 cell type that may contribute to early cancer development. ScRNAseq analysis also reveals that stromal cells, e.g., fibroblasts and endothelial cells, regulate inflammation and promote metastasis, making them key targets for future investigations. While evaluating the outcomes, we also highlight the gaps in the current findings and provide an assessment of what this technology holds for gastric cancer research in the coming years. With scRNAseq technology expanding rapidly, we stress the need for periodic review of the findings and assess the available scRNAseq analytical tools to guide future work on immunological mechanisms of gastric carcinogenesis.  

Single-cell RNA-seq dissecting heterogeneity of tumor cells and comprehensive dynamics in tumor microenvironment during lymph nodes metastasis in gastric cancer

Lymph node metastasis is the common metastasis route of gastric cancer. However, until now, heterogeneities of tumor cells and tumor microenvironment in primary tumors (PT) and metastatic lymph nodes (MLN) of gastric cancer (GC) remains uncharacterized. In this study, scRNA-seq was performed on tissues from PT and MLN of gastric cancer. Trajectory analysis and function enrichment analyses were conducted to decode the underlying mechanisms contributing to LN metastasis of gastric cancer. Heterogeneous composition of immune cells and distant intercellular interactions in PT and MLN were analyzed. Based on the generated single cell transcriptome profiles, dynamics of gene expressions in cancer cells between PT and MLN were characterized. Moreover, we reconstructed the developmental trajectory of GC cells' metastasis to LN and identified two sub-types of GC cells with distinct potentials of having malignant biological behaviors. We characterized the repression of neutrophil polarization associated genes, like LCN2, which would contribute to LN metastasis, and histochemistry experiments validated our findings. Additionally, heterogeneity in neutrophils, rather than macrophages, was characterized. Immune checkpoint associated interaction of SPP1 was found active in MLN. In conclusion, we decode the dynamics of tumor cells during LN metastasis in GC and to identify a sub-type of GC cells with potentials of LN metastasis. Our data indicated that the disordering the neutrophils polarization and maturation and the activation of immune checkpoint SPP1 might contribute to LN metastasis in GC, providing a novel insight on the mechanism and potential therapeutic targets of LN metastasis in GC. This article is protected by copyright. All rights reserved.

circFCHO2 promotes gastric cancer progression by activating the JAK1/STAT3 pathway via sponging miR-194-5p

circFCHO2 has been revealed to be overexpressed in gastric cancer (GC) patients. This article identified the function of circFCHO2 on GC progression. The expression of circFCHO2, miR-194-5p and JAK1 in 30 GC patients and cells was monitored by quantitative reverse transcription-polymerase chain reaction. circFCHO2 localization in GC cells was monitored by RNA fluorescence in situ hybridization. Cell counting kit-8 assay, 5-ethynyl-2-deoxyuridine staining, transwell experiment, tube formation and sphere formation experiments were applied to detect GC cell proliferation, invasion, angiogenesis and cancer stem cell characteristics. Dual-luciferase reporter gene assay, RNA pull down assay and RNA immunoprecipitation experiment were utilized to research the binding between two genes. In vivo tumorigenesis and lung metastasis were studied using nude mice. Immunohistochemistry and hematoxylin-eosin staining were conducted. Protein expression was assessed by Western blot. Serum exosomes of GC patients and healthy participants were isolated. circFCHO2 up-modulation in GC patients was related to poor outcome. circFCHO2 was located in the cytoplasm of GC cells. circFCHO2 silencing weakened the proliferation, invasion, angiogenesis and stem cell characteristics of GC cells. miR-194-5p knockdown counteracted this effect. circFCHO2 activated the JAK1/STAT3 pathway by sponging miR-194-5p. miR-194-5p overexpression attenuated the malignant phenotypes of GC cells. JAK1 overexpression abrogated this effect. circFCHO2 silencing weakened GC cells growth and lung metastasis in vivo. circFCHO2 was up-modulated in serum exosomes of GC patients. circFCHO2 was an oncogene in GC by activating the JAK1/STAT3 pathway via sponging miR-194-5p. circFCHO2 might be a novel target and diagnostic marker for GC.

Applications and Achievements of Single-Cell Sequencing in Gastrointestinal Cancer

Gastrointestinal cancer represents a public health concern that seriously endangers human health. The emerging single-cell sequencing (SCS) technologies are different from the large-scale sequencing technologies which provide inaccurate data. SCS is a powerful tool for deciphering the single-cell resolutions of cellular and molecular landscapes, revealing the features of single-cell genomes, transcriptomes, and epigenomes. Recently, SCS has been applied in the field of gastrointestinal cancer research for clarifying the origin and heterogeneity of gastrointestinal cancer, acquiring micro-environmental information, and improving diagnostic and treatment methods. This review outlines the applications of SCS in gastrointestinal cancer research and summarizes the most recent advances in the field.

Tumor-derived IL-8 facilitates lymph node metastasis of gastric cancer via PD-1 up-regulation in CD8+ T cells

Background

The pretherapeutic serum interleukin-8 (sIL-8) levels have been revealed to be increased in about half of patients with locally advanced gastric cancer. However, the roles of IL-8 in lymph node metastasis (LNM) and the underlying mechanisms remain unclear.

Methods

146 patients with primary gastric carcinoma were enrolled in this study. ELISA was used to measure IL-8 levels. The CD4/CD8 ratio and programmed cell death-1 (PD-1) expression of T cells in primary tumor tissues, tumor-draining lymph nodes (TDLNs) and non-draining lymph nodes (NDLNs) were assayed with flow cytometry. Protein expression of the molecules was determined with immunohistochemistry, western blotting or immunoprecipitation. The gastric cancer mouse tumor model with LNM was utilized to determine the role of IL-8 in regulation of tumor metastasis and progression.

Results

The elevated sIL-8 levels were associated with LNM and poor prognosis in gastric cancer. Furthermore, sIL-8 was identified to be prominently produced by gastric cancer-associated fibroblasts (CAFs). Elevated IL-8 can up-regulate PD-1 expression in CD8⁺ T cells, resulting in immunosuppression in primary tumors and TDLNs, which enhances LNM of gastric cancer. Molecularly, IL-8 increases PD-1 expression through JAK2/STAT3 signaling activation, and inhibits its ubiquitination via Fbxo38 down-regulation. In addition, the in vivo studies in mouse gastric cancer model demonstrated that IL-8 promotes LNM via PD-1 up-regulation in CD8⁺ T cells.

Conclusion

The present study elucidates the pro-metastatic role of elevated IL-8 in gastric cancer, and provides novel insights to enhance immune checkpoint blockade therapy for anti-PD-1 in gastric cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00262-022-03223-3.

Recent advances in targeted drug delivery systems for resistant colorectal cancer

Colorectal cancer (CRC) is one of the deadliest cancers in the world, the incidences and morality rate are rising and poses an important threat to the public health. It is known that multiple drug resistance (MDR) is one of the major obstacles in CRC treatment. Tumor microenvironment plus genomic instability, tumor derived exosomes (TDE), cancer stem cells (CSCs), circulating tumor cells (CTCs), cell-free DNA (cfDNA), as well as cellular signaling pathways are important issues regarding resistance. Since non-targeted therapy causes toxicity, diverse side effects, and undesired efficacy, targeted therapy with contribution of various carriers has been developed to address the mentioned shortcomings. In this paper the underlying causes of MDR and then various targeting strategies including exosomes, liposomes, hydrogels, cell-based carriers and theranostics which are utilized to overcome therapeutic resistance will be described. We also discuss implication of emerging approaches involving single cell approaches and computer-aided drug delivery with high potential for meeting CRC medical needs.

ACAN, MDFI, and CHST1 as Candidate Genes in Gastric Cancer: A Comprehensive Insilco Analysis

BACKGROUND

Gastric cancer (GC) is a complex disorder with an inadequate response to treatment. Although many efforts have been made to clarify the development of GC, the exact etiology and molecular mechanisms of this malignancy remain unclear. This study was designed to identify and characterize essential associated genes with GC to construct a prognostic model.

METHODS

In this Insilco study, the gene expression microarray dataset GSE122401 was downloaded from the Gene Expression Omnibus (GEO). The raw data were processed and quantile-normalized with the edgeR package of R ver.3.5.3. The module-trait relationship and hub-genes associated with GC were analyzed with Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by Cluepedia and Enrichr Database. Finally, hub-genes were screened and validated by GEPIA online database.

RESULTS

According to the WGCNA results, the blue module was found to be strongly correlated with the GC (r=0.91, p-value=1e-57). DEGs analysis was performed by edgeR package of R and indicated a total of 47 genes as hub-genes. Verifying the hub-genes expression using GEPIA online database showed a significantly increased level of ACAN gene expression in primary cancer cell line compared to metastatic cell line. On the other hand, the expression of MDFI and CHST1 genes in primary cell lines were lower compared to metastatic cancer cell lines.

CONCLUSIONS

This study provides a framework of the co-expression gene modules ACAN, MDFI, and CHST1 as hub-genes. These hub-genes might offer candidate biomarkers to targeted therapy against GC. Further experiment validation and animal models are needed to reveal the exact mechanism of the above-mentioned genes in the pathogenesis and prognoses of GC.

Long non-coding RNAs: Biogenesis, functions, and clinical significance in gastric cancer

Gastric cancer (GC) is one of the most prevalent malignant tumor types and the third leading cause of cancer-related death worldwide. Its morbidity and mortality are very high due to a lack of understanding about its pathogenesis and the slow development of novel therapeutic strategies. Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs with a length of more than 200 nt. They play crucial roles in a wide spectrum of physiological and pathological processes by regulating the expression of genes involved in proliferation, differentiation, apoptosis, cell cycle, invasion, metastasis, DNA damage, and carcinogenesis. The aberrant expression of lncRNAs has been found in various cancer types. A growing amount of evidence demonstrates that lncRNAs are involved in many aspects of GC pathogenesis, including its occurrence, metastasis, and recurrence, indicating their potential role as novel biomarkers in the diagnosis, prognosis, and therapeutic targets of GC. This review systematically summarizes the biogenesis, biological properties, and functions of lncRNAs and highlights their critical role and clinical significance in GC. This information may contribute to the development of better diagnostics and treatments for GC.

Analyzing Modern Biomolecules: The Revolution of Nucleic-Acid Sequencing - Review

Recent developments have revolutionized the study of biomolecules. Among them are molecular markers, amplification and sequencing of nucleic acids. The latter is classified into three generations. The first allows to sequence small DNA fragments. The second one increases throughput, reducing turnaround and pricing, and is therefore more convenient to sequence full genomes and transcriptomes. The third generation is currently pushing technology to its limits, being able to sequence single molecules, without previous amplification, which was previously impossible. Besides, this represents a new revolution, allowing researchers to directly sequence RNA without previous retrotranscription. These technologies are having a significant impact on different areas, such as medicine, agronomy, ecology and biotechnology. Additionally, the study of biomolecules is revealing interesting evolutionary information. That includes deciphering what makes us human, including phenomena like non-coding RNA expansion. All this is redefining the concept of gene and transcript. Basic analyses and applications are now facilitated with new genome editing tools, such as CRISPR. All these developments, in general, and nucleic-acid sequencing, in particular, are opening a new exciting era of biomolecule analyses and applications, including personalized medicine, and diagnosis and prevention of diseases for humans and other animals.