scholarly journals Multidimensional transcriptomics provides detailed information about immune cell distribution and identity in HER2+ breast tumors

2018 ◽  
Author(s):  
Fredrik Salmén ◽  
Sanja Vickovic ◽  
Ludvig Larsson ◽  
Linnea Stenbeck ◽  
Johan Vallon-Christersson ◽  
...  
Keyword(s):  
Tumor Tissue ◽  
Immune Cell ◽  
Three Dimensional ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Cell Distribution ◽  
Tissue Sections ◽  
Disease States ◽  
Her2 Breast Cancer ◽  
Transcriptomics Data

AbstractThe comprehensive analysis of tumor tissue heterogeneity is crucial for determining specific disease states and establishing suitable treatment regimes. Here, we analyze tumor tissue sections from ten patients diagnosed with HER2+ breast cancer. We obtain and analyze multidimensional, genome-wide transcriptomics data to resolve spatial immune cell distribution and identity within the tissue sections. Furthermore, we determine the extent of immune cell infiltration in different regions of the tumor tissue, including invasive cancer regions. We combine cross-sectioning and computational alignment to build three-dimensional images of the transcriptional landscape of the tumor and its microenvironment. The three-dimensional data clearly demonstrates the heterogeneous nature of tumor-immune interactions and reveal interpatient differences in immune cell infiltration patterns. Our study shows the potential for an improved stratification and description of the tumor-immune interplay, which is likely to be essential in treatment decisions.

scholarly journals C3aR1 Correlates With Immune Cell Infiltration and Serves as Prognostic and Therapeutic Biomarker in Gastric Cancer

2021 ◽  
Author(s):  
weifeng liu ◽  
Zhijie Chu ◽  
Cheng Yang ◽  
Tianbao Yang ◽  
Yanhui Yang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
T Cell ◽  
Differentially Expressed Genes ◽  
Tumor Tissue ◽  
Immune Cell ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Expression Levels

Abstract As the fourth most common malignancy worldwide, gastric cancer can lead more than 720 000 patient death every year. Precisely therapeutic intervention can significantly improve patients’ survival status underlying the precise clarification by molecular indexes. Identifying the biomarkers highly associated with disease prognosis will be helpful to guide the clinical therapy. C3ar1 is an essential receptor in the complement system, and participates in various biological processes associated with immunological responses. To identify the crucial roles of C3AR1 in gastric cancer tmorigenesis, we determined the mRNA profile, protein expression levels and the clinicopathological indexes using cBioportal, Kaplan-Meier plotter and the Human Protein Atlas databases. To identify the molecular network in C3AR1-expressed gastric cancer, we obtained the differentially expressed genes using the GEPIA database compared with normal stomach tissues. Furthermore, we analyzed the biological impact of these differentially expressed genes using protein-protein interaction network and gene set enrichment analysis, in which we identified the hub genes and critical pathways influenced by over-expressed C3AR1 in gastric cancer. Finally, we evaluated the correlation between the C3AR1 expression levels and immune cell infiltration levels utilizing the Tumor Immunoassay Resource database. Our results revealed that the higher expression level of C3AR1 can lead higher infiltration of T cell CD8+, T cell CD4+, macrophage, neutrophil, B cell and myeloid dendritic cells into tumor tissue. Moreover, we also found that higher infiltration of macrophage cells into tumor tissue can worsen the survival of patients with gastric cancer, which may be highly associated with the polarization states of macrophages (TAM and M2 status). Our investigation suggest that C3AR1 can be as an efficient diagnostic biomarkers for gastric cancer therapy.

scholarly journals TMC5 is Highly Expressed in Human Cancers and Corelates to Prognosis and Immune Cell Infiltration: A Comprehensive Bioinformatics Analysis

2022 ◽  
Vol 8 ◽  
Author(s):  
Hui Zhang ◽  
Xu Zhang ◽  
Weiguo Xu ◽  
Jian Wang
Keyword(s):  
Tumor Tissue ◽  
Bioinformatics Analysis ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Drug Responses ◽  
Normal Tissues ◽  
Human Cancers ◽  
Potential Marker ◽  
Pathological Stages

Background: The oncological role of TMC5 in human cancers has only been revealed partially. We performed integrated bioinformatics analysis to provide a thorough and detailed insight of associations between TMC5 and tumorigenesis, cancer progression, and prognosis.Methods: With reference to the accessible online databases, the TMC5 expressions in tumor tissues and corresponding normal tissues, different pathological stages, and various cancer cells were analyzed, while the protein levels of TMC5 in different cancers were also inspected. Meanwhile, the prognostic value of TMC5 expression in multiple cancers as well as in advanced-stage patients was investigated. Furthermore, the mutational data of TMC5 and its correlation with cancer prognosis were assessed. Moreover, the association between the TMC5 level and immune cell infiltration was evaluated. Next, TMC5-related pathway alterations and drug responses were summarized. Finally, the TMC5 based protein network was generated, and relevant enrichment was performed.Results: In our study, the expression level of TMC5 was significantly higher in the tumor tissue than that of the normal tissues in most cancer types. Fluctuations of TMC5 levels were also observed among different pathological stages. In the meantime, the protein level elevated in the tumor tissue in the cancers enrolled. Moreover, the expression of TMC5 was not only prognostic for overall survival (OS) or recurrence free survival (RFS) in various types of cancers but also correlated to OS in patients with more advanced cancers. Additionally, the mutational status of TMC5 is also associated with prognosis in cancer patients. It is worth noting that the TMC5 level was closely related to immune cell infiltrations, especially in ESCA, TGCT, and USC. The TMC5 expression was also identified as an activator for pathways including PI3K/AKT, RAS/MAPK, and TSC/mTOR, proved to be associated with multiple drug responses and assessed to be interactive with the TMEM family.Conclusion: TMC5 might function as a potential marker for cancer survival and immune responses.

scholarly journals N6-Methyladenosine Related Long Non-Coding RNAs and Immune Cell Infiltration in the Tumor Microenvironment of Gastric Cancer

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Zhong lin Yu ◽  
Zheng ming Zhu
Keyword(s):  
Gastric Cancer ◽  
Tumor Microenvironment ◽  
Prognostic Model ◽  
Tumor Tissue ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Non Coding Rnas ◽  
The Relationship ◽  
Cluster 2

Abstract Aim To illustrate the influence of N6-methyladenosine long non-coding RNAs and immune cell infiltration in gastric cancer. Methods We downloaded workflow-type data and clinical data from The Cancer Genome Atlas project. The relationship of lncRNA and m6A was identified. Kyoto Encyclopedia of Genes and Genomes gene expression enrichment analysis was performed. Lasso regression was utilized to construct a prognostic model. Survival analysis to explore the relationship between m6A lncRNA and clinical survival data. Differential analysis of the tumor microenvironment and immune correlation analysis to determine immune cell infiltration levels and their correlation with clinical prognosis. Results Co-expression analysis indicated that lncRNA expression was associated closely with m6A. m6A-lncRNAs were partially highly expressed in tumor tissue and could be used in a prognostic model to predict GC prognosis, independent of other clinical characteristics. “ADIPPOCYTOKINE SIGNALING PATHWAY” was most significantly enriched according to GSEA. ACBD3-AS1 was overexpressed in tumor tissue. Naïve B cell, Plasma cells, resting CD4 memory T cell were highly infiltrated tissues in cluster 2, while Macrophages M2, resting Mast cells, Monocytes, regulates T cells were lowly in cluster 1. All related scores were higher in cluster 2, indicating a lower purity of tumor cells and higher density of immune-related cells in the tumor microenvironment. Conclusion m6A lncRNA is closely related to the occurrence and progression of GC. The corresponding prognostic model can be utilized to evaluate the prognosis of GC. m6A lncRNA and related immune cell infiltration in the tumor microenvironment can provide novel therapeutic targets for further research.

WISP1 modulates immune cell infiltration upon drug-induced liver injury (DILI)

2015 ◽  
Vol 53 (12) ◽  
Author(s):  
AB Widera ◽  
L Pütter ◽  
S Leserer ◽  
G Campos ◽  
K Rochlitz ◽  
...  
Keyword(s):  
Liver Injury ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Drug Induced ◽  
Drug Induced Liver Injury

scholarly journals SFTPA1 is a potential prognostic biomarker correlated with immune cell infiltration and response to immunotherapy in lung adenocarcinoma

2021 ◽  
Author(s):  
Lu Yuan ◽  
Xixi Wu ◽  
Longshan Zhang ◽  
Mi Yang ◽  
Xiaoqing Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
T Cells ◽  
Lung Adenocarcinoma ◽  
Expression Profile ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Regulatory Pathways ◽  
Chronic Lung Diseases ◽  
Potential Biomarker

AbstractPulmonary surfactant protein A1 (SFTPA1) is a member of the C-type lectin subfamily that plays a critical role in maintaining lung tissue homeostasis and the innate immune response. SFTPA1 disruption can cause several acute or chronic lung diseases, including lung cancer. However, little research has been performed to associate SFTPA1 with immune cell infiltration and the response to immunotherapy in lung cancer. The findings of our study describe the SFTPA1 expression profile in multiple databases and was validated in BALB/c mice, human tumor tissues, and paired normal tissues using an immunohistochemistry assay. High SFTPA1 mRNA expression was associated with a favorable prognosis through a survival analysis in lung adenocarcinoma (LUAD) samples from TCGA. Further GeneOntology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses showed that SFTPA1 was involved in the toll-like receptor signaling pathway. An immune infiltration analysis clarified that high SFTPA1 expression was associated with an increased number of M1 macrophages, CD8+ T cells, memory activated CD4+ T cells, regulatory T cells, as well as a reduced number of M2 macrophages. Our clinical data suggest that SFTPA1 may serve as a biomarker for predicting a favorable response to immunotherapy for patients with LUAD. Collectively, our study extends the expression profile and potential regulatory pathways of SFTPA1 and may provide a potential biomarker for establishing novel preventive and therapeutic strategies for lung adenocarcinoma.

scholarly journals Enhanced CD4+ and CD8+ T cell infiltrate within convex hull defined pancreatic islet borders as autoimmune diabetes progresses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alexander J. Dwyer ◽  
Jacob M. Ritz ◽  
Jason S. Mitchell ◽  
Tijana Martinov ◽  
Mohannad Alkhatib ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Convex Hull ◽  
Pancreatic Islets ◽  
Immune Cell ◽  
Nod Mice ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Analytical Strategy ◽  
Islet Mass

AbstractThe notion that T cell insulitis increases as type 1 diabetes (T1D) develops is unsurprising, however, the quantitative analysis of CD4+ and CD8+ T cells within the islet mass is complex and limited with standard approaches. Optical microscopy is an important and widely used method to evaluate immune cell infiltration into pancreatic islets of Langerhans for the study of disease progression or therapeutic efficacy in murine T1D. However, the accuracy of this approach is often limited by subjective and potentially biased qualitative assessment of immune cell subsets. In addition, attempts at quantitative measurements require significant time for manual analysis and often involve sophisticated and expensive imaging software. In this study, we developed and illustrate here a streamlined analytical strategy for the rapid, automated and unbiased investigation of islet area and immune cell infiltration within (insulitis) and around (peri-insulitis) pancreatic islets. To this end, we demonstrate swift and accurate detection of islet borders by modeling cross-sectional islet areas with convex polygons (convex hulls) surrounding islet-associated insulin-producing β cell and glucagon-producing α cell fluorescent signals. To accomplish this, we used a macro produced with the freeware software ImageJ equipped with the Fiji Is Just ImageJ (FIJI) image processing package. Our image analysis procedure allows for direct quantification and statistical determination of islet area and infiltration in a reproducible manner, with location-specific data that more accurately reflect islet areas as insulitis proceeds throughout T1D. Using this approach, we quantified the islet area infiltrated with CD4+ and CD8+ T cells allowing statistical comparison between different age groups of non-obese diabetic (NOD) mice progressing towards T1D. We found significantly more CD4+ and CD8+ T cells infiltrating the convex hull-defined islet mass of 13-week-old non-diabetic and 17-week-old diabetic NOD mice compared to 4-week-old NOD mice. We also determined a significant and measurable loss of islet mass in mice that developed T1D. This approach will be helpful for the location-dependent quantitative calculation of islet mass and cellular infiltration during T1D pathogenesis and can be combined with other markers of inflammation or activation in future studies.

scholarly journals Comprehensive analysis of lncRNA-miRNA-mRNA regulatory networks for microbiota-mediated colorectal cancer associated with immune cell infiltration

Bioengineered ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 3410-3425
Author(s):  
Xiangzhou Tan ◽  
Linfeng Mao ◽  
Changhao Huang ◽  
Weimin Yang ◽  
Jianping Guo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Networks ◽  
Immune Cell ◽  
Comprehensive Analysis ◽  
Cell Infiltration ◽  
Immune Cell Infiltration
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