Identifying Diagnostic and Prognostic Biomarkers and Candidate Therapeutic Drugs of Gastric Cancer Based on Transcriptomics and Single-Cell Sequencing

Background and Objective: Gastric cancer (GC) is an important health burden and the prognosis of GC is poor. We aimed to explore new diagnostic and prognostic indicators as well as potential therapeutic targets for GC in the current study.Methods: We screened the overlapped differentially expressed genes (DEGs) from GSE54129 and TCGA STAD datasets. Protein-protein interaction network analysis recognized the hub genes among the DEGs. The roles of these genes in diagnosis, prognosis, and their relationship with immune infiltrates and drug sensitivity of GC were analyzed using R studio. Finally, the clinically significant hub genes were verified using single-cell RNA sequencing (scRNA-seq) data.Results: A total of 222 overlapping genes were screened, which were enriched in extracellular matrix-related pathways. Further, 17 hub genes were identified, and our findings demonstrated that BGN, COMP, COL5A2, and SPARC might be important diagnostic and prognostic indicators of GC, which were also correlated with immune cell infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and sensitivity of therapeutic drugs. The scRNA-seq results further confirmed that all four hub genes were highly expressed in GC.Conclusion: Based on transcriptomics and single-cell sequencing, we identified four diagnostic and prognostic biomarkers of GC, including BGN, COMP, COL5A2, and SPARC, which can help predict drug sensitivity for GC as well.

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Identification of the hub genes and prognostic indicators of gastric cancer and correlation of indicators with tumor-infiltrating immune cell levels

Journal of Cancer ◽

10.7150/jca.52105 ◽

2021 ◽

Vol 12 (13) ◽

pp. 4025-4038

Author(s):

Yun Ji ◽

Lu Gao ◽

Can Zhang ◽

Xu Sun ◽

Liping Dai ◽

...

Keyword(s):

Gastric Cancer ◽

Immune Cell ◽

Prognostic Indicators ◽

Hub Genes

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484 Bioturing browser: interactively explore public single cell sequencing data

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2020-sitc2020.0484 ◽

2020 ◽

Vol 8 (Suppl 3) ◽

pp. A520-A520

Author(s):

Son Pham ◽

Tri Le ◽

Tan Phan ◽

Minh Pham ◽

Huy Nguyen ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Expression Profiles ◽

Meta Analysis ◽

Cell Types ◽

Sequencing Data ◽

Single Cell Sequencing ◽

Data Formats ◽

Cancer Types ◽

Cell Data

BackgroundSingle-cell sequencing technology has opened an unprecedented ability to interrogate cancer. It reveals significant insights into the intratumoral heterogeneity, metastasis, therapeutic resistance, which facilitates target discovery and validation in cancer treatment. With rapid advancements in throughput and strategies, a particular immuno-oncology study can produce multi-omics profiles for several thousands of individual cells. This overflow of single-cell data poses formidable challenges, including standardizing data formats across studies, performing reanalysis for individual datasets and meta-analysis.MethodsN/AResultsWe present BioTuring Browser, an interactive platform for accessing and reanalyzing published single-cell omics data. The platform is currently hosting a curated database of more than 10 million cells from 247 projects, covering more than 120 immune cell types and subtypes, and 15 different cancer types. All data are processed and annotated with standardized labels of cell types, diseases, therapeutic responses, etc. to be instantly accessed and explored in a uniform visualization and analytics interface. Based on this massive curated database, BioTuring Browser supports searching similar expression profiles, querying a target across datasets and automatic cell type annotation. The platform supports single-cell RNA-seq, CITE-seq and TCR-seq data. BioTuring Browser is now available for download at www.bioturing.com.ConclusionsN/A

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Identification of key genes related to macrophage infiltration in gastric cancer based on WGCNA

10.21203/rs.3.rs-56342/v1 ◽

2020 ◽

Author(s):

Haiyan Chen ◽

Cangang Zhang ◽

Shuai Cao ◽

Meng Cao ◽

Nana Zhang ◽

...

Keyword(s):

Gastric Cancer ◽

Immune Cell ◽

Accurate Diagnosis ◽

Marker Genes ◽

Hub Genes ◽

Normal Tissues ◽

Tumor Tissues ◽

New Strategy ◽

Tumor Environment ◽

Advanced Stages

Abstract Background: Gastric cancer (GC) is rampant around the world. Most of the GC cases are detected in advanced stages with poor prognosis. The identification of marker genes for early diagnosis is of great significance. Studying the tumor environment is helpful to acknowledge the process of tumorigenesis, development, and metastasis.Methods: In GEO, 22 kinds of immune cell infiltration were calculated by CIBERSORT. Macrophages were discovered remarkably infiltrated higher in GC compared with normal tissues. WGCNA was utilized to construct the network and then identify key modules and genes related to macrophages in TCGA.Results: Finally, 18 hub genes were verified. In the PPI bar chart, the top 3 genes were chosen as hub genes involved in most pathways. On the TIMER and THPA websites, it is verified that the expression levels of CYBB, CD86 and C3AR1 genes in tumor tissues were higher than those in normal tissues.Conclusion: These genes may work as biomarkers or targets for accurate diagnosis and treatment of GC in the future. Our findings may be a new strategy for the treatment of GC.

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Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing

Cell Discovery ◽

10.1038/s41421-020-0168-9 ◽

2020 ◽

Vol 6 (1) ◽

Cited By ~ 142

Author(s):

Wen Wen ◽

Wenru Su ◽

Hao Tang ◽

Wenqing Le ◽

Xiaopeng Zhang ◽

...

Keyword(s):

Single Cell ◽

Immune Cell ◽

Recovery Stage ◽

Single Cell Sequencing

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Applications of Single-Cell Omics to Dissect Tumor Microenvironment

Frontiers in Genetics ◽

10.3389/fgene.2020.548719 ◽

2020 ◽

Vol 11 ◽

Author(s):

Tingting Guo ◽

Weimin Li ◽

Xuyu Cai

Keyword(s):

Tumor Microenvironment ◽

Single Cell ◽

Immune Cells ◽

Immune Cell ◽

Cell Types ◽

Immune Checkpoint Blockade ◽

Lineage Tracing ◽

Great Success ◽

Novel Technologies ◽

Single Cell Sequencing

The recent technical and computational advances in single-cell sequencing technologies have significantly broaden our toolkit to study tumor microenvironment (TME) directly from human specimens. The TME is the complex and dynamic ecosystem composed of multiple cell types, including tumor cells, immune cells, stromal cells, endothelial cells, and other non-cellular components such as the extracellular matrix and secreted signaling molecules. The great success on immune checkpoint blockade therapy has highlighted the importance of TME on anti-tumor immunity and has made it a prime target for further immunotherapy strategies. Applications of single-cell transcriptomics on studying TME has yielded unprecedented resolution of the cellular and molecular complexity of the TME, accelerating our understanding of the heterogeneity, plasticity, and complex cross-interaction between different cell types within the TME. In this review, we discuss the recent advances by single-cell sequencing on understanding the diversity of TME and its functional impact on tumor progression and immunotherapy response driven by single-cell sequencing. We primarily focus on the major immune cell types infiltrated in the human TME, including T cells, dendritic cells, and macrophages. We further discuss the limitations of the existing methodologies and the prospects on future studies utilizing single-cell multi-omics technologies. Since immune cells undergo continuous activation and differentiation within the TME in response to various environmental cues, we highlight the importance of integrating multimodal datasets to enable retrospective lineage tracing and epigenetic profiling of the tumor infiltrating immune cells. These novel technologies enable better characterization of the developmental lineages and differentiation states that are critical for the understanding of the underlying mechanisms driving the functional diversity of immune cells within the TME. We envision that with the continued accumulation of single-cell omics datasets, single-cell sequencing will become an indispensable aspect of the immune-oncology experimental toolkit. It will continue to drive the scientific innovations in precision immunotherapy and will be ultimately adopted by routine clinical practice in the foreseeable future.

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Identification of Methylated Differentially Expressed Hub Genes and Immune Infiltration in Diabetic Retinopathy

10.21203/rs.3.rs-1136469/v1 ◽

2021 ◽

Author(s):

Qi Zhou ◽

Xin Xiong ◽

Min Tang ◽

Yingqing Lei ◽

Hongbin Lv

Keyword(s):

Gene Expression ◽

Extracellular Matrix ◽

Immune Cell ◽

Interaction Network ◽

Bioinformatic Analysis ◽

Differentially Expressed ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Hub Genes ◽

Critical Pathways

Abstract BackgroundDiabetic retinopathy (DR), a severe complication of diabetes mellitus (DM), is a global social and economic burden. However, the pathological mechanisms mediating DR are not well-understood. This study aimed to identify differentially methylated and differentially expressed hub genes (DMGs and DEGs, respectively) and associated signaling pathways, and to evaluate immune cell infiltration involved in DR. MethodsTwo publicly available datasets were downloaded from the Gene Expression Omnibus database. Transcriptome and epigenome microarray data and multi-component weighted gene coexpression network analysis (WGCNA) were utilized to determine hub genes within DR. One dataset was utilized to screen DEGs and to further explore their potential biological functions using functional annotation analysis. A protein-protein interaction network was constructed. Gene set enrichment and variation analyses (GSVA and GSEA, respectively) were utilized to identify the potential mechanisms mediating the function of hub genes in DR. Infiltrating immune cells were evaluated in one dataset using CIBERSORT. The Connectivity Map (CMap) database was used to predict potential therapeutic agents. ResultsIn total, 673 DEGs (151 upregulated and 522 downregulated genes) were detected. Gene expression was significantly enriched in the extracellular matrix and sensory organ development, extracellular matrix organization, and glial cell differentiation pathways. Through WGCNA, one module was found to be significantly related with DR (r=0.34, P =0.002), and 979 hub genes were identified. By comparing DMGs, DEGs, and genes in WGCNA, we identified eight hub genes in DR ( AKAP13, BOC, ACSS1, ARNT2, TGFB2, LHFPL2, GFPT2, TNFRSF1A ), which were significantly enriched in critical pathways involving coagulation, angiogenesis, TGF-β, and TNF-α-NF-κB signaling via GSVA and GSEA. Immune cell infiltration analysis revealed that activated natural killer cells, M0 macrophages, resting mast cells, and CD8 + T cells may be involved in DR. ARNT2, TGFB2, LHFPL2 , and AKAP13 expression were correlated with immune cell processes, and ZG-10, JNK-9L, chromomycin-a3, and calyculin were identified as potential drugs against DR. Finally, TNFRSF1A , GFPT2 , and LHFPL2 expression levels were consistent with the bioinformatic analysis. ConclusionsOur results are informative with respect to correlations between differentially methylated and expressed hub genes and immune cell infiltration in DR, providing new insight towards DR drug development and treatment.

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CXCR4 negatively correlates with NKT cell infiltration during gastric precancerous lesions progression to early gastric cancer

10.21203/rs.3.rs-79316/v1 ◽

2020 ◽

Author(s):

Xiaotao Jiang ◽

Kunhai Zhuang ◽

Kailin Jiang ◽

Yi Wen ◽

Linling Xie ◽

...

Keyword(s):

Gastric Cancer ◽

Immune Cells ◽

Immune Cell ◽

Precancerous Lesions ◽

Clinical Information ◽

Cell Infiltration ◽

Hub Genes ◽

Nkt Cell ◽

Hub Gene ◽

Correlation Test

Abstract Background: With the coming of immunotherapy era, immunotherapy is gradually playing a vital role in the treatment of gastric cancer (GC). However, immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. Methods: From the Gene Expression Omnibus (GEO), data of three GPL-related gene expression profiles (GSE55696, GSE87666 and GSE130823) and three GC data sets with clinical information (GSE66229, GSE15459 and GSE34942) were downloaded. Three GC data were consolidated as a GC meta-GEO cohort. RNA sequencing data of 375 stomach adenocarcinoma (STAD) samples with clinical information from The Cancer Genome Atlas (TCGA) and 175 stomach normal controls (NC) from Genotype-Tissue Expression (GTEx) datasets were obtained from the UCSC Xena browser, which were merged as a STAD TCGA-GTEx cohort. The abundance of immune cells in above datasets were estimated using Immune Cell Abundance Identifier (ImmuCellAI) algorithm. Firstly, key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test as well as Spearman’s correlation test in two GPL and EGC related datasets (GSE55696 and GSE87666). Then, weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network. Candidate hub genes were identified based on network parameters. Combining expression comparison and prognosis analysis in STAD TCGA-GTEx and GC meta-GEO cohort, Genes with significant difference between GC and NC and prognostic significance were identified as real hub genes. Correlation between real hub genes and key immune cells was evaluated using Pearson’s correlation test. The pattern of key immune cells infiltration and hub genes expression as well as their correlation during GPL progression to EGC were validated in an independent cohort GSE130823. The correlation was also verified in the GC datasets (STAD TCGA-GTEx and GC meta-GEO cohort).Results: Combining with GSE55696 and GSE87666 cohorts, NKT cell was found gradually decreased with GPL progression and negatively correlated with tumorigenesis significantly. It was identified as the key immune cell associated with GPL progression to EGC based on one-way ANOVA test and Spearman’s correlation test. Further verification indicated that it was significantly downregulated in GC in meta-GEO cohort and STAD TCGA-GTEx cohort. According to the results of WGCNA and KEGG pathway enrichment, green modules in GSE55696 and GSE87666 cohorts were considered as hub modules as they were negatively associated with NKT cell infiltration at a significant level and their overlapping genes were significantly enriched in immune-related pathways. In further screening, CXCR4 was found to be significantly upregulated in GC and had a poor prognosis, which was determined as the real hub gene. CXCR4 expression was found increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly. The pattern of NKT cell infiltration and CXCR4 expression as well as their relationship stay consistent in the independent GPL cohort GSE130823. The negative correlation of CXCR4 with NKT cell infiltration was also confirmed in GC datasets (GC meta-GEO cohort and STAD TCGA-GTEx cohort).Conclusion: CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

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Identification of Enhancer RNA CDK6-AS1 as a Potential Novel Prognostic Biomarker in Gastric Cancer

10.21203/rs.3.rs-1159260/v1 ◽

2021 ◽

Author(s):

Shifeng Yang ◽

Xiaoming Zou ◽

Hao Yang ◽

Jiacheng Li ◽

Ange Zhang ◽

...

Keyword(s):

Gastric Cancer ◽

Target Gene ◽

Drug Sensitivity ◽

Immune Cell ◽

Prognostic Biomarker ◽

Driver Genes ◽

Pathway Enrichment ◽

Enhancer Rna ◽

Oncogenic Pathway ◽

Pan Cancer

Abstract Background:The aim of this study was to confirm enhancer RNAs (eRNAs) in gastric cancer and its clincial utility. Methods:We used cox survival analysis and relevance analysis to identify the candidate eRNAs in gastric cancer. Moreover, we performed GO and Reactome pathway enrichment to found the potential functions of eRNAs.Correlation between eRNA, tumor-infiltrating immune cells and drug sensitivity was then analyzed. Results: CDK6-AS1 may serve as a poor independent prognostic biomarker candidate in gastric cancer with positive correlation with its target gene CDK6. Low CDK6-AS1 expression group showed more frequent mutated driver genes than high expression ones. Moreover, CDK6-AS1 is involved in key oncogenic pathway as cell cycle and RNA transcription. CDK6-AS1 also shows dysregulations and associations with prognosis at pan-cancer level. This eRNA may also associated with immune cell infiltration and drug sensitivity. Conclusion:CDK6-AS1 may be a potential prognostic biomarker for gastric cancer, predict chemotherapeutic drugs sensitivity of gastric cancer.

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CXCR4 Negatively Correlates with NKT Cell Infiltration During Gastric Precancerous Lesions Progression to Early Gastric Cancer

10.21203/rs.3.rs-88936/v1 ◽

2020 ◽

Author(s):

Xiaotao Jiang ◽

Kunhai Zhuang ◽

Kailin Jiang ◽

Yi Wen ◽

Linling Xie ◽

...

Keyword(s):

Gastric Cancer ◽

Early Gastric Cancer ◽

Immune Cells ◽

Immune Cell ◽

Precancerous Lesions ◽

Expression Profiles ◽

Cell Infiltration ◽

Hub Genes ◽

Nkt Cell ◽

Hub Gene

Abstract Background Immune microenvironment in gastric precancerous lesions (GPL) and early gastric cancer (EGC) still remain largely unknown. This study aims to identify key immune cells and hub genes associated with GPL progression to EGC. Methods Immune Cell Abundance Identifier (ImmuCellAI) algorithm was used to quantify the proportions of immune cells of GPL and GC samples based on gene expression profiles. Key immune cells associated with GPL progression to EGC were identified using one‐way analysis of variance (ANOVA) test and Spearman’s correlation test. Weighted gene co-expression analysis (WGCNA) and pathway enrichment were adopted to identify hub gene co-expression network and hub genes associated with the key immune cells infiltration. The pattern of key immune cells infiltration, hub genes expression and their correlation were verified in an independent GPL-EGC cohort and GC datasets.Results NKT cell was found gradually decreased during GPL progression to EGC and negatively correlated with tumorigenesis. According to WGCNA and hub genes screening, CXCR4, having a poor prognosis, increased with GPL progression, positively correlated with tumorigenesis and negatively correlated with NKT cell infiltration significantly, was identified as the real hub gene. The negative correlation between CXCR4 and NKT cell infiltration was successfully verified in an independent GPL-EGC cohort and GC datasets.Conclusion CXCR4 and NKT cell are possible to serve as biomarkers in monitoring GPL progression to EGC. Besides, CXCR4 may be involved in regulating NKT cell infiltration during GPL progression to EGC, which may provide a new immunotherapeutic target.

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ITGA5 Is a Prognostic Biomarker and Correlated with Immune Infiltration In Gastrointestinal Cancers

10.21203/rs.3.rs-58757/v1 ◽

2020 ◽

Author(s):

Hai Zhu ◽

Gang Wang ◽

Haixing Zhu ◽

Aman Xu

Keyword(s):

Gastric Cancer ◽

Immune Cell ◽

Prognostic Biomarker ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Th2 Cells ◽

Integrin Subunit ◽

Expression Levels ◽

Immune Infiltration

Abstract Background: Integrin Subunit Alpha 5 (ITGA5) belongs to the integrin alpha chain family, is vital for promoting cancer cell invasion, metastasis. However, the correlation between ITGA5 expression and immune infiltration in gastrointestinal (GI) tumors remain unclear.Methods: The expression levels of ITGA5 were detected by Oncomine and Tumor Immune Estimation Resource (TIMER). The association between ITGA5 and prognosis of patients was identified by Kaplan–Meier plotter, Gene Expression Profiling Interactive Analysis 2(GEPIA2) and PrognoScan. We evaluated the correlation between ITGA5 expression and immune infiltrating level via TIMER. Besides, TIMER and immunohistochemistry (IHC) staining were used to explore correlations between ITGA5 expression and markers of immune infiltrates cells. Furthermore, we constructed protein-protein interaction (PPI) network and performed functional enrichment by GeneMANIA and Metascape.Results: ITGA5 was generally overexpressed and correlated with worse prognosis in multiple types of GI tumors. In addition, ITGA5 expression levels was significantly associated with tumor purity and immune infiltration levels of different immune cells in GI tumors. Interestingly, Immune markers for monocytes, tumor - associated macrophages (TAMs), macrophages 2 (M2) cells and T-helper 2 (Th2) cells were found to be significantly and positively correlated with ITGA5 expression levels in colon and gastric cancer. Results from IHC staining further proved that markers of Th2 and M2 cell were significantly increased in gastric cancer patients with high ITGA5 expression levels. Lastly, interaction network and function enrichment analysis revealed ITGA5 were mainly involved in “integrin mediated signaling pathway”, “leukocyte migration”, “cell-substrate adhesion”.Conclutions: our study demonstrated that ITGA5 may act as an essential regulator of tumor immune cell infiltration and a valuable prognostic biomarker in GI tumors. Additional work is needed to fully elucidate the underlying mechanisms behind these observations.

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