0% Complete
the 4th international edition and 13th Iranian Conference on Bioinformatics
international edition and Iranian Conference on Bioinformatics
صفحه اصلی
/
4th international edition and 13th Iranian Conference on Bioinformatics
Comprehensive integrated single-cell RNA sequencing analysis of brain metastasis and glioma microenvironment: Contrasting heterogeneity landscapes
نویسندگان :
Seyedeh Fatemeh Sajjadi
1
Najmeh Salehi
2
Mehdi Sadeghi
3
1- 1. School of Biological Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
2- University of Tehran
3- 2National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
کلمات کلیدی :
brain metastasis،tumor microenvironment،single-cell RNA sequencing
چکیده :
Understanding the specific type of brain malignancy, source of brain metastasis, and underlying transformation mechanisms can help provide better treatment and less harm to patients. The tumor microenvironment plays a fundamental role in cancer progression and affects both primary and metastatic cancers. The use of single-cell RNA sequencing to gain insights into the heterogeneity profiles in the microenvironment of brain malignancies is useful for guiding treatment decisions. To comprehensively investigate the heterogeneity in gliomas and brain metastasis originating from different sources (lung and breast), we integrated data from three groups of single-cell RNA-sequencing datasets obtained from GEO. We gathered and processed single-cell RNA sequencing data from 90,168 cells obtained from 17 patients. We then employed the R package Seurat for dataset integration. Next, we clustered the data within the UMAP space and acquired differentially expressed genes for cell categorization. Our results underscore the significance of macrophages as abundant and pivotal constituents of gliomas. In contrast, lung-to-brain metastases exhibit elevated numbers of AT2, cytotoxic CD4+ T, and exhausted CD8+ T cells. Conversely, breast-to-brain metastases are characterized by an abundance of epithelial and myCAF cells. Our study not only illuminates the variation in the TME between brain metastasis with different origins but also opens the door to utilizing established markers for these cell types to differentiate primary brain metastatic cancers.
لیست مقالات
لیست مقالات بایگانی شده
Molecular Investigation of Periplasmic Sensor Histidine Kinase Interactions in Regulating UV Shield Formation of Cyanobacteria Nostoc Sp
Maryam Eskafi - Maryam Azimzadeh Irani
Encoding the gRNA-DNA Pairs with Deep Transformers to Predict off-target Effects of CRISPR
Roghayyeh Alipanahi - Leila Safari - Alireza Khanteymoori
Tissue-Specific Gene Co-Expression Analysis in Pediatric Ependymomas Across Different Anatomical Regions
Zahra Eghbali - Mohammad Reza Zabihi - Pedram Jahangiri - Zahra Salehi
Exploring the anti-inflammatory potential of the silymarin against IL-17A: in silico molecular docking
Tooba Abdizadeh
A computational approach to identify the biomarker based on the RNA sequencing data analysis for Alzheimer’s disease
Atena Vaghf - Shahram Tahmasebian - Nayereh Abdali
Novel lncRNA‐miRNA‐mRNA competing endogenous RNA regulatory networks in glioma
Asoo Khani - Amir-Reza Javanmard
Machine Learning-Driven Discovery of JAK2 Inhibitors from ChEMBL Databank
Negar Abdolmaleki - Hamid Mahdiuni
Element-Specific Estimation of Background Mutation Rates in Whole Cancer Genomes Through Transfer Learning
ّFarideh Bahari - Reza Ahangari Cohan - Hesam Montazeri
In Silico Analysis of the R410W Mutation in ZP1: Effects on Protein Stability and Interactions
Seyedeh Zahra Mousavi - Pegah Kouhi - Zeinab Rokhsattalab - Mehdi Totonchi
Comprehensive Analysis of EEG Signals for Machine Learning-Based Depression Detection
Mikaeil Tabarraei - Sepideh Jabbari
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.5.0