Dissecting transcriptional heterogeneity in primary gastric adenocarcinoma by single cell RNA sequencing

Co-Expression with Membrane CMTM6/4 on Tumor Epithelium Enhances the Prediction Value of PD-L1 on Anti-PD-1/L1 Therapeutic Efficacy in Gastric Adenocarcinoma

Simple Summary

Immunotherapeutic efficacy is low even in PD-L1 positive patients with advanced gastric adenocarcinoma. Based on the results of 6-color multiplex immunofluorescence staining of the gastric tumor tissues in tissue array and 48-case pre-immunotherapy patients, a better prognostic value was found in the membrane co-expression of CMTM6/4 and PD-L1 in tumor epithelial cells than PD-L1 alone. The membrane co-expression of CMTM6/4 and PD-L1 can be used as a valuable tool for precision pre-immunotherapy patient screening in gastric adenocarcinoma.

Abstract

Anti-PD-1/L1 immunotherapy has been intensively used in heavily treated population with advanced gastric adenocarcinoma. However, the immunotherapeutic efficacy is low even in PD-L1 positive patients. We aimed to establish a new strategy based on the co-expression of CMTM6/4 and PD-L1 for patient stratification before immunotherapy. By analyzing the data obtained from TCGA and single-cell RNA sequencing at the mRNA level, and 6-color multiplex immunofluorescence staining of tumor tissues in tissue array and 48-case pre-immunotherapy patients at the protein level, we found that CMTM6/4 and PD-L1 co-expressed in both epithelial and mesenchymal regions of gastric adenocarcinoma. The tumor tissues had higher levels of CMTM6/4 expression than their adjacent ones. A positive correlation was found between the expression of CMTM6/4 and the expression of PD-L1 in tumor epithelium. Epithelial co-expression of CMTM6/4 and PD-L1 in gastric tumor region was associated with shorter overall survival but better short-term response to anti-PD-1/L1 immunotherapy. Thus, we developed a predictive model and three pathological patterns based on the membrane co-expression of CMTM6/4 and PD-L1 in tumor epithelial cells for pre-immunotherapy patient screening in gastric adenocarcinoma.

Single-cell profiling of infiltrating B cells and tertiary lymphoid structures in the TME of gastric adenocarcinomas

The occurrence and development of gastric adenocarcinoma (gADC) is closely related to the interaction between tumor cells and immune cells in the tumor microenvironment (TME). Our objective was to characterize the repertoire of immune cells in the TME of gADC. To analyze the transcriptomic, immune, and spatial information of TME in gADC, we constructed single-cell RNA sequencing, 10 × Genomics V(D)J analysis, multiple immunofluorescence techniques, and OSCmap analysis of 49,765 single cells in seven samples from four gADC patients. Our integrative analysis of B cells demonstrated that a large number of mucosal associated lymphoid tissue (MALT)-B cells were detected in the gADC tissues, which have mature tertiary lymphatic structures (mTLSs), and almost no MALT-B cells in peripheral blood sample. Moreover, MALT-B cells are a class of IgA⁺ plasma cells, which are characterized with high expression of complement pathway activation-related genes. Next, natural killer T (NKT) cells mainly exist in gADC tissues accompanied by mTLSs. This study also classified monocytes/macrophages and epithelial cells into benign and malignant types. Interestingly, CSOmap (q < .05) and multiple immunofluorescence (p < .05) results indicated more types of immune cells can be enriched in tissues with mTLSs than normal TLSs, and the density of mTLSs were higher than normal TLSs. Our findings provide novel insights for the signature of immune cells and tumor cells in the TME of gADC with TLSs and highlight the potential importance of IgA-mediated humoral immunity in gADC patients with TLSs.

Comprehensive Analysis of E2F Family Members in Human Gastric Cancer

Gastric cancer (GC) is the second most common cancer and the third most frequent cause of cancer-related deaths in China. E2Fs are a family of transcription factors reported to be involved in the tumor progression of various cancer types; however, the roles of individual E2Fs are still not known exactly in tumor progression of GC. In this study, we examined the expression of E2Fs to investigate their roles in tumor progression in GC patients using multiple databases, including ONCOMINE, GEPIA2, Kaplan-Meier plotter, cBioPortal, Metascape, LinkedOmics, GeneMANIA, STRING and UCSC Xena. We also performed real-time polymerase chain reaction (RT-PCR) to validate the expression levels of individual E2Fs in several GC cell lines. Our results demonstrated that the mRNA levels of E2F1/2/3/5/8 were significantly higher both in GC tissues and cell lines. The expression levels of E2F1 and E2F4 were correlated with poor overall survival (OS), decreased post-progression survival (PPS), and decreased progression-free survival (FP) in patients with GC. However, overexpression of E2F2, E2F5, E2F7 and E2F8 is significantly associated with disease-free survival and overall survival in patients with GC. In addition, higher E2F3 and E2F6 mRNA expression was found to increase GC patients' OS and PPS. 224 of 415 patients with STAD (54%) had gene mutations that were associated with longer disease-free survival (DFS) but not OS. Cell cycle pathway was closely associated with mRNA level of more than half of E2Fs (E2F1/2/3/7/8). There were close and complicated interactions among E2F family members. Finally, our results indicated the gene expressions of E2Fs had a positive relationship with its copy numbers. Taken together, E2F1/2/3/5/8 can serve as biomarkers for GC patients with high prognostic value for OS of GC patients or therapeutic targets for GC.

Spatially distinct reprogramming of the tumor microenvironment based on tumor invasion in diffuse-type gastric cancers

PURPOSE

Histological features of diffuse-type gastric cancer (GC) indicate that the tumor microenvironment (TME) may substantially impact tumor invasiveness. However, cellular components and molecular features associated with cancer invasiveness in the TME of diffuse-type GCs are poorly understood.

EXPERIMENTAL DESIGN

We performed single-cell RNA-sequencing (scRNA-seq) using tissue samples from superficial and deep invasive layers of cancerous and paired normal tissues freshly harvested from five patients with diffuse-type GC. The scRNA-seq results were validated by immunohistochemistry and duplex in situ hybridization (ISH) in formalin-fixed paraffin-embedded tissues.

RESULTS

Seven major cell types were identified. Fibroblasts, endothelial cells, and myeloid cells were categorised as being enriched in the deep layers. Cell type-specific clustering further revealed that the superficial-to-deep layer transition is associated with enrichment in inflammatory endothelial cells and fibroblasts with upregulated CCL2 transcripts. Immunohistochemistry and duplex ISH revealed the distribution of the major cell types and CCL2-expressing endothelial cells and fibroblasts, indicating tumor invasion. Elevation of CCL2 levels along the superficial-to-deep layer axis revealed the immunosuppressive immune cell sub-types that may contribute to tumor cell aggressiveness in the deep invasive layers of diffuse-type GC. The analyses of public datasets revealed the high-level co-expression of stromal cell-specific genes and that CCL2 correlated with poor survival outcomes in GC patients.

CONCLUSIONS

This study reveals the spatial reprogramming of the TME that may underlie invasive tumor potential in diffuse-type GC. This TME profiling across tumor layers suggests new targets, such as CCL2, that can modify the TME to inhibit tumor progression in diffuse-type 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.

Development of a quantitative prediction algorithm for target organ-specific similarity of human pluripotent stem cell-derived organoids and cells

Human pluripotent stem cell (hPSC)-derived organoids and cells have similar characteristics to human organs and tissues. Thus, in vitro human organoids and cells serve as a superior alternative to conventional cell lines and animal models in drug development and regenerative medicine. For a simple and reproducible analysis of the quality of organoids and cells to compensate for the shortcomings of existing experimental validation studies, a quantitative evaluation method should be developed. Here, using the GTEx database, we construct a quantitative calculation system to assess similarity to the human organs. To evaluate our system, we generate hPSC-derived organoids and cells, and detected organ similarity. To facilitate the access of our system by researchers, we develop a web-based user interface presenting similarity to the appropriate organs as percentages. Thus, this program could provide valuable information for the generation of high-quality organoids and cells and a strategy to guide proper lineage-oriented differentiation.

Quantitative methods to assess the quality of hPSC-derived organoids have not been developed. Here they present a prediction algorithm to assess the transcriptomic similarity between hPSC-derived organoids and the corresponding human target organs and perform validation on lung bud organoids, antral gastric organoids, and cardiomyocytes.

Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges

Cancer has become one of the greatest threats to human health, and new technologies are urgently needed to further clarify the mechanisms of cancer so that better detection and treatment strategies can be developed. At present, extensive genomic analysis and testing of clinical specimens shape the insights into carcinoma. Nevertheless, carcinoma of humans is a complex ecosystem of cells, including carcinoma cells and immunity-related and stroma-related subsets, with accurate characteristics obscured by extensive genome-related approaches. A growing body of research shows that sequencing of single-cell RNA (scRNA-seq) is emerging to be an effective way for dissecting human tumor tissue at single-cell resolution, presenting one prominent way for explaining carcinoma biology. This review summarizes the research progress of scRNA-seq in the field of tumors, focusing on the application of scRNA-seq in tumor circulating cells, tumor stem cells, tumor drug resistance, the tumor microenvironment, and so on, which provides a new perspective for tumor research.

Visual Genomics Analysis Studio as a Tool to Analyze Multiomic Data

Type B adverse drug reactions (ADRs) are iatrogenic immune-mediated syndromes with mechanistic etiologies that remain incompletely understood. Some of the most severe ADRs, including delayed drug hypersensitivity reactions, are T-cell mediated, restricted by specific human leukocyte antigen risk alleles and sometimes by public or oligoclonal T-cell receptors (TCRs), central to the immunopathogenesis of tissue-damaging response. However, the specific cellular signatures of effector, regulatory, and accessory immune populations that mediate disease, define reaction phenotype, and determine severity have not been defined. Recent development of single-cell platforms bringing together advances in genomics and immunology provides the tools to simultaneously examine the full transcriptome, TCRs, and surface protein markers of highly heterogeneous immune cell populations at the site of the pathological response at a single-cell level. However, the requirement for advanced bioinformatics expertise and computational hardware and software has often limited the ability of investigators with the understanding of diseases and biological models to exploit these new approaches. Here we describe the features and use of a state-of-the-art, fully integrated application for analysis and visualization of multiomic single-cell data called Visual Genomics Analysis Studio (VGAS). This unique user-friendly, Windows-based graphical user interface is specifically designed to enable investigators to interrogate their own data. While VGAS also includes tools for sequence alignment and identification of associations with host or organism genetic polymorphisms, in this review we focus on its application for analysis of single-cell TCR-RNA-Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE)-seq, enabling holistic cellular characterization by unbiased transcriptome and select surface proteome. Critically, VGAS does not require user-directed coding or access to high-performance computers, instead incorporating performance-optimized hidden code to provide application-based fast and intuitive tools for data analyses and production of high-resolution publication-ready graphics on standard specification laptops. Specifically, it allows analyses of comprehensive single-cell TCR sequencing (scTCR-seq) data, detailing (i) functional pairings of α-β heterodimer TCRs, (ii) one-click histograms to display entropy and gene rearrangements, and (iii) Circos and Sankey plots to visualize clonality and dominance. For unbiased single-cell RNA sequencing (scRNA-seq) analyses, users extract cell transcriptome signatures according to global structure via principal component analysis, t-distributed stochastic neighborhood embedding, or uniform manifold approximation and projection plots, with overlay of scTCR-seq enabling identification and selection of the immunodominant TCR-expressing populations. Further integration with similar sequence-based detection of surface protein markers using oligo-labeled antibodies (CITE-seq) provides comparative understanding of surface protein expression, with differential gene or protein analyses visualized using volcano plot or heatmap functions. These data can be compared to reference cell atlases or suitable controls to reveal discrete disease-specific subsets, from epithelial to tissue-resident memory T-cells, and activation status, from senescence through exhaustion, with more finite transcript expression displayed as violin and box plots. Importantly, guided tutorial videos are available, as are regular application updates based on the latest advances in bioinformatics and user feedback.

Applications of single-cell sequencing in cancer research: progress and perspectives

Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

Genomic Heterogeneity and Clonal Evolution in Gastroesophageal Junction Cancer Revealed by Single Cell DNA Sequencing

Gastroesophageal junction (GEJ) cancer is a tumor that occurs at the junction of stomach and esophagus anatomically. GEJ cancer frequently metastasizes to lymph nodes, however the heterogeneity and clonal evolution process are unclear. This study is the first of this kind to use single cell DNA sequencing to determine genomic variations and clonal evolution related to lymph node metastasis. Multiple Annealing and Looping Based Amplification Cycles (MALBAC) and bulk exome sequencing were performed to detect single cell copy number variations (CNVs) and single nucleotide variations (SNVs) respectively. Four GEJ cancer patients were enrolled with two (Pt.3, Pt.4) having metastatic lymph nodes. The most common mutation we found happened in the TTN gene, which was reported to be related with the tumor mutation burden in cancers. Significant intra-patient heterogeneity in SNVs and CNVs were found. We identified the SNV subclonal architecture in each tumor. To study the heterogeneity of CNVs, the single cells were sequenced. The number of subclones in the primary tumor was larger than that in lymph nodes, indicating the heterogeneity of primary site was higher. We observed two patterns of multi-station lymph node metastasis: one was skip metastasis and the other was to follow the lymphatic drainage. Taken together, our single cell genomic analysis has revealed the heterogeneity and clonal evolution in GEJ cancer.

Gastric Cancer: Advances in Carcinogenesis Research and New Therapeutic Strategies

Gastric cancer’s bad incidence, prognosis, cellular and molecular heterogeneity amongst others make this disease a major health issue worldwide. Understanding this affliction is a priority for proper patients’ management and for the development of efficient therapeutical strategies. This review gives an overview of major scientific advances, made during the past 5-years, to improve the comprehension of gastric adenocarcinoma. A focus was made on the different actors of gastric carcinogenesis, including, Helicobacter pylori cancer stem cells, tumour microenvironment and microbiota. New and recent potential biomarkers were assessed as well as emerging therapeutical strategies involving cancer stem cells targeting as well as immunotherapy. Finally, recent experimental models to study this highly complex disease were discussed, highlighting the importance of gastric cancer understanding in the hard-fought struggle against cancer relapse, metastasis and bad prognosis.

Insights Gained from Single-Cell Analysis of Immune Cells in the Tumor Microenvironment

Understanding tumor immune microenvironments is critical for identifying immune modifiers of cancer progression and developing cancer immunotherapies. Recent applications of single-cell RNA sequencing (scRNA-seq) in dissecting tumor microenvironments have brought important insights into the biology of tumor-infiltrating immune cells, including their heterogeneity, dynamics, and potential roles in both disease progression and response to immune checkpoint inhibitors and other immunotherapies. This review focuses on the advances in knowledge of tumor immune microenvironments acquired from scRNA-seq studies across multiple types of human tumors, with a particular emphasis on the study of phenotypic plasticity and lineage dynamics of immune cells in the tumor environment. We also discuss several imminent questions emerging from scRNA-seq observations and their potential solutions on the horizon.

Gene expression barcode values reveal a potential link between Parkinson's disease and gastric cancer

Gastric cancer is a disease that develops from the lining of the stomach, whereas Parkinson’s disease is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. Although these two diseases seem to be distinct from each other, increasing evidence suggests that they might be linked. To explore the linkage between these two diseases, differentially expressed genes between the diseased people and their normal controls were identified using the barcode algorithm. This algorithm transforms actual gene expression values into barcode values comprised of 1’s (expressed genes) and 0’s (silenced genes). Once the overlapped differentially expressed genes were identified, their biological relevance was investigated. Thus, using the gene expression profiles and bioinformatics methods, we demonstrate that Parkinson’s disease and gastric cancer are indeed linked. This research may serve as a pilot study, and it will stimulate more research to investigate the relationship between gastric cancer and Parkinson’s disease from the perspective of gene profiles and their functions.

Single-Cell Gene Network Analysis and Transcriptional Landscape of MYCN-Amplified Neuroblastoma Cell Lines

Neuroblastoma (NBL) is a pediatric cancer responsible for more than 15% of cancer deaths in children, with 800 new cases each year in the United States alone. Genomic amplification of the MYC oncogene family member MYCN characterizes a subset of high-risk pediatric neuroblastomas. Several cellular models have been implemented to study this disease over the years. Two of these, SK-N-BE-2-C (BE2C) and Kelly, are amongst the most used worldwide as models of MYCN-Amplified human NBL. Here, we provide a transcriptome-wide quantitative measurement of gene expression and transcriptional network activity in BE2C and Kelly cell lines at an unprecedented single-cell resolution. We obtained 1105 Kelly and 962 BE2C unsynchronized cells, with an average number of mapped reads/cell of roughly 38,000. The single-cell data recapitulate gene expression signatures previously generated from bulk RNA-Seq. We highlight low variance for commonly used housekeeping genes between different cells (ACTB, B2M and GAPDH), while showing higher than expected variance for metallothionein transcripts in Kelly cells. The high number of samples, despite the relatively low read coverage of single cells, allowed for robust pathway enrichment analysis and master regulator analysis (MRA), both of which highlight the more mesenchymal nature of BE2C cells as compared to Kelly cells, and the upregulation of TWIST1 and DNAJC1 transcriptional networks. We further defined master regulators at the single cell level and showed that MYCN is not constantly active or expressed within Kelly and BE2C cells, independently of cell cycle phase. The dataset, alongside a detailed and commented programming protocol to analyze it, is fully shared and reusable.

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

Gastric cancer (GC) is a leading cause of cancer-induced mortality, with poor prognosis with metastasis. The mechanism of gastric carcinoma lymph node metastasis remains unknown due to traditional bulk-leveled approaches masking the roles of subpopulations. To answer questions concerning metastasis from the gastric carcinoma intratumoural perspective, we performed single-cell level analysis on three gastric cancer patients with primary cancer and paired metastatic lymph node cancer tissues using single-cell RNA-seq (scRNA-seq). The results showed distinct carcinoma profiles from each patient, and diverse microenvironmental subsets were shared across different patients. Clustering data showed significant intratumoural heterogeneity. The results also revealed a subgroup of cells bridging the metastatic group and primary group, implying the transition state of cancer during the metastatic process. In the present study, we obtained a more comprehensive picture of gastric cancer lymph node metastasis, and we discovered some GC lymph node metastasis marker genes (ERBB2, CLDN11 and CDK12), as well as potential gastric cancer evolution-driving genes (FOS and JUN), which provide a basis for the treatment of GC.

Potentiality of multiple modalities for single-cell analyses to evaluate the tumor microenvironment in clinical specimens

Single-cell level analysis is powerful tool to assess the heterogeneity of cellular components in tumor microenvironments (TME). In this study, we investigated immune-profiles using the single-cell analyses of endoscopically- or surgically-resected tumors, and peripheral blood mononuclear cells from gastric cancer patients. Furthermore, we technically characterized two distinct platforms of the single-cell analysis; RNA-seq-based analysis (scRNA-seq), and mass cytometry-based analysis (CyTOF), both of which are broadly embraced technologies. Our study revealed that the scRNA-seq analysis could cover a broader range of immune cells of TME in the biopsy-resected small samples of tumors, detecting even small subgroups of B cells or Treg cells in the tumors, although CyTOF could distinguish the specific populations in more depth. These findings demonstrate that scRNA-seq analysis is a highly-feasible platform for elucidating the complexity of TME in small biopsy tumors, which would provide a novel strategies to overcome a therapeutic difficulties against cancer heterogeneity in TME.

Benchmarking algorithms for pathway activity transformation of single-cell RNA-seq data

Biological pathway analysis provides new insights for cell clustering and functional annotation from single-cell RNA sequencing (scRNA-seq) data. Many pathway analysis algorithms have been developed to transform gene-level scRNA-seq data into functional gene sets representing pathways or biological processes. Here, we collected seven widely-used pathway activity transformation algorithms and 32 available datasets based on 16 scRNA-seq techniques. We proposed a comprehensive framework to evaluate their accuracy, stability and scalability. The assessment of scRNA-seq preprocessing showed that cell filtering had the less impact on scRNA-seq pathway analysis, while data normalization of sctransform and scran had a consistent well impact across all tools. We found that Pagoda2 yielded the best overall performance with the highest accuracy, scalability, and stability. Meanwhile, the tool PLAGE exhibited the highest stability, as well as moderate accuracy and scalability.

High MHC-II expression in Epstein-Barr virus-associated gastric cancers suggests that tumor cells serve an important role in antigen presentation

EBV-associated gastric adenocarcinomas (EBVaGCs) often exhibit better clinical outcomes than EBV negative gastric cancers (GCs), which could be related to their consistent expression of foreign viral antigens. Antigen-presenting cells (APCs) present peptide antigens in the context of the class-II major histocompatibility complex (MHC-II). During inflammatory conditions, epithelial cells express MHC-II and function as accessory APCs. Utilizing RNA-seq data from nearly 400 GC patients, we determined the impact of EBV-status on expression of MHC-II components, genes involved in their regulation, and T-cell co-stimulation. Virtually all MHC-II genes were significantly upregulated in EBVaGCs compared to normal tissues, or other GC subtypes. Genes involved in antigen presentation were also significantly upregulated in EBVaGCs, as were the key MHC-II transcriptional regulators CIITA and RFX5. This was unexpected as the EBV encoded BZLF1 protein can repress CIITA transcription and is expressed in many EBVaGCs. Furthermore, MHC-II upregulation was strongly correlated with elevated intratumoral levels of interferon-gamma. In addition, expression of co-stimulatory molecules involved in T-cell activation and survival was also significantly increased in EBVaGCs. Thus, gastric adenocarcinoma cells may functionally contribute to the highly immunogenic tumor microenvironment observed in EBVaGCs via a previously unappreciated role in interferon-induced antigen presentation.