Identification of Somatic Mutation-Driven Immune Cells by Integrating Genomic and Transcriptome Data

Tumor somatic mutations in protein-coding regions may generate neoantigens which may trigger antitumor immune cell response. Increasing evidence supports that immune cell response may profoundly influence tumor progression. However, there are no calculated tools to systematically identify immune cells driven by specific somatic mutations. It is urgent to develop a calculated method to comprehensively detect tumor-infiltrating immune cells driven by the specific somatic mutations in cancer. We developed a novel software package (SMDIC) that enables the automated identification of somatic mutation-driven immune cell. SMDIC provides a novel pipeline to discover mutation-specific immune cells by integrating genomic and transcriptome data. The operation modes include inference of the relative abundance matrix of tumor-infiltrating immune cells, detection of differential abundance immune cells with respect to the gene mutation status, conversion of the abundance matrix of significantly dysregulated cells into two binary matrices (one for upregulated and one for downregulated cells), identification of somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and visualization of immune cell abundance of samples in different mutation status for each gene. SMDIC provides a user-friendly tool to identify somatic mutation-specific immune cell response. SMDIC may contribute to understand the mechanisms underlying anticancer immune response and find targets for cancer immunotherapy. The SMDIC was implemented as an R-based tool which was freely available from the CRAN website https://CRAN.R-project.org/package=SMDIC.

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Immune cells as targets for cardioprotection: new players and novel therapeutic opportunities

Cardiovascular Research ◽

10.1093/cvr/cvz050 ◽

2019 ◽

Vol 115 (7) ◽

pp. 1117-1130 ◽

Cited By ~ 33

Author(s):

Ioanna Andreadou ◽

Hector A Cabrera-Fuentes ◽

Yvan Devaux ◽

Nikolaos G Frangogiannis ◽

Stefan Frantz ◽

...

Keyword(s):

Heart Failure ◽

Inflammatory Reaction ◽

Immune Cells ◽

Cell Response ◽

Immune Cell ◽

Left Ventricular ◽

Lymphoid Cells ◽

Inflammatory Phase ◽

Anti Inflammatory ◽

Immune Cell Response

Abstract New therapies are required to reduce myocardial infarct (MI) size and prevent the onset of heart failure in patients presenting with acute myocardial infarction (AMI), one of the leading causes of death and disability globally. In this regard, the immune cell response to AMI, which comprises an initial pro-inflammatory reaction followed by an anti-inflammatory phase, contributes to final MI size and post-AMI remodelling [changes in left ventricular (LV) size and function]. The transition between these two phases is critical in this regard, with a persistent and severe pro-inflammatory reaction leading to adverse LV remodelling and increased propensity for developing heart failure. In this review article, we provide an overview of the immune cells involved in orchestrating the complex and dynamic inflammatory response to AMI—these include neutrophils, monocytes/macrophages, and emerging players such as dendritic cells, lymphocytes, pericardial lymphoid cells, endothelial cells, and cardiac fibroblasts. We discuss potential reasons for past failures of anti-inflammatory cardioprotective therapies, and highlight new treatment targets for modulating the immune cell response to AMI, as a potential therapeutic strategy to improve clinical outcomes in AMI patients. This article is part of a Cardiovascular Research Spotlight Issue entitled ‘Cardioprotection Beyond the Cardiomyocyte’, and emerged as part of the discussions of the European Union (EU)-CARDIOPROTECTION Cooperation in Science and Technology (COST) Action, CA16225.

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RhoA Signaling in Immune Cell Response and Cardiac Disease

Cells ◽

10.3390/cells10071681 ◽

2021 ◽

Vol 10 (7) ◽

pp. 1681

Author(s):

Lucia Sophie Kilian ◽

Derk Frank ◽

Ashraf Yusuf Rangrez

Keyword(s):

Cardiac Disease ◽

Cell Response ◽

Cell Activation ◽

Immune Cell ◽

Inflammatory Diseases ◽

Heart Diseases ◽

Small Gtpase ◽

Cardiac Inflammation ◽

Immune Cell Activation ◽

Immune Cell Response

Chronic inflammation, the activation of immune cells and their cross-talk with cardiomyocytes in the pathogenesis and progression of heart diseases has long been overlooked. However, with the latest research developments, it is increasingly accepted that a vicious cycle exists where cardiomyocytes release cardiocrine signaling molecules that spiral down to immune cell activation and chronic state of low-level inflammation. For example, cardiocrine molecules released from injured or stressed cardiomyocytes can stimulate macrophages, dendritic cells, neutrophils and even T-cells, which then subsequently increase cardiac inflammation by co-stimulation and positive feedback loops. One of the key proteins involved in stress-mediated cardiomyocyte signal transduction is a small GTPase RhoA. Importantly, the regulation of RhoA activation is critical for effective immune cell response and is being considered as one of the potential therapeutic targets in many immune-cell-mediated inflammatory diseases. In this review we provide an update on the role of RhoA at the juncture of immune cell activation, inflammation and cardiac disease.

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IMMU-68. SINGLE-CELL PROTEOMIC ANALYSIS OF IMMUNE CELL RESPONSE TO CHECKPOINT BLOCKADE USING 30-PARAMETER FLOW CYTOMETRY

Neuro-Oncology ◽

10.1093/neuonc/noy148.571 ◽

2018 ◽

Vol 20 (suppl_6) ◽

pp. vi137-vi137

Author(s):

Amber Giles ◽

Leonard Nettey ◽

Thomas Liechti ◽

Margaret Beddall ◽

Elizabeth Vera ◽

...

Keyword(s):

Flow Cytometry ◽

Single Cell ◽

Cell Response ◽

Proteomic Analysis ◽

Immune Cell ◽

Checkpoint Blockade ◽

Immune Cell Response

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Postoperative cellular stress in the kidney is associated with an early systemic γδ T-cell immune cell response

Critical Care ◽

10.1186/s13054-018-2094-x ◽

2018 ◽

Vol 22 (1) ◽

Cited By ~ 1

Author(s):

Ivan Göcze ◽

Katharina Ehehalt ◽

Florian Zeman ◽

Paloma Riquelme ◽

Karin Pfister ◽

...

Keyword(s):

T Cell ◽

Cell Response ◽

Immune Cell ◽

Cellular Stress ◽

Γδ T Cell ◽

Immune Cell Response

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Upregulation of IL15RA in Triple Negative Breast Cancer (TNBC) Promotes Tumour Cell Growth and Motility and Can Activate an Immune Cell Response

Annals of Oncology ◽

10.1093/annonc/mdt085.2 ◽

2013 ◽

Vol 24 ◽

pp. iii38

Author(s):

P. Marra ◽

S. Mathew ◽

A. Grigoriadis ◽

Y. Wu ◽

F. Kyle-Cezar ◽

...

Keyword(s):

Breast Cancer ◽

Cell Growth ◽

Triple Negative Breast Cancer ◽

Tumour Cell ◽

Cell Response ◽

Triple Negative ◽

Immune Cell ◽

Immune Cell Response ◽

Tumour Cell Growth

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Analysis of multi-omics differences in left-side and right-side colon cancer

PeerJ ◽

10.7717/peerj.11433 ◽

2021 ◽

Vol 9 ◽

pp. e11433

Author(s):

Yanyi Huang ◽

Jinzhong Duanmu ◽

Yushu Liu ◽

Mengyun Yan ◽

Taiyuan Li ◽

...

Keyword(s):

Colon Cancer ◽

Cancer Patients ◽

Gene Mutation ◽

Somatic Mutation ◽

Transcriptome Data ◽

Characteristic Analysis ◽

Immune Microenvironment ◽

Mutation Data ◽

Upregulated Genes ◽

Testing Set

Background Colon cancer is one of the most common tumors in the digestive tract. Studies of left-side colon cancer (LCC) and right-side colon cancer (RCC) show that these two subtypes have different prognoses, outcomes, and clinical responses to chemotherapy. Therefore, a better understanding of the importance of the clinical classifications of the anatomic subtypes of colon cancer is needed. Methods We collected colon cancer patients’ transcriptome data, clinical information, and somatic mutation data from the Cancer Genome Atlas (TCGA) database portal. The transcriptome data were taken from 390 colon cancer patients (172 LCC samples and 218 RCC samples); the somatic mutation data included 142 LCC samples and 187 RCC samples. We compared the expression and prognostic differences of LCC and RCC by conducting a multi-omics analysis of each using the clinical characteristics, immune microenvironment, transcriptomic differences, and mutation differences. The prognostic signatures was validated using the internal testing set, complete set, and external testing set (GSE39582). We also verified the independent prognostic value of the signature. Results The results of our clinical characteristic analysis showed that RCC had a significantly worse prognosis than LCC. The analysis of the immune microenvironment showed that immune infiltration was more common in RCC than LCC. The results of differential gene analysis showed that there were 360 differentially expressed genes, with 142 upregulated genes in LCC and 218 upregulated genes in RCC. The mutation frequency of RCC was generally higher than that of LCC. BRAF and KRAS gene mutations were the dominant genes mutations in RCC, and they had a strong mutual exclusion with APC, while APC gene mutation was the dominant gene mutation in LCC. This suggests that the molecular mechanisms of RCC and LCC differed. The 4-mRNA and 6-mRNA in the prognostic signatures of LCC and RCC, respectively, were highly predictive and may be used as independent prognostic factors. Conclusion The clinical classification of the anatomic subtypes of colon cancer is of great significance for early diagnosis and prognostic risk assessment. Our study provides directions for individualized treatment of left and right colon cancer.

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