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In this study, we performed single-cell transcriptome data analysis of fifty primary and metastatic lung adenocarcinoma (LUAD) samples from the GSE123902 and GSE131907 datasets to determine the landscape of inter-patient and intra-tumoral heterogeneity. The gene expression profiles and copy number variations (CNV) showed significant heterogeneity in the primary and metastatic LUAD samples. We observed upregulation of pathways related to translational initiation, endoplasmic reticulum stress, exosomes, and unfolded protein response in the brain metastasis samples as compared to the primary tumor samples. Pathways related to exosomes, cell adhesion and metabolism were upregulated and the epithelial-to-mesenchymal-transition (EMT) pathway was downregulated in brain metastasis samples from chemotherapy-treated LUAD patients as compared to those from the untreated LUAD patients. Tumor cell subgroups in the brain metastasis samples showed differential expression of genes related to type II alveolar cells, chemoresistance, glycolysis and oxidative phosphorylation (metabolic reprogramming), and EMT. Thus, single-cell transcriptome analysis demonstrated intra-patient and intra-tumor heterogeneity in the regulation of pathways related to tumor progression, chemoresistance and metabolism in the primary and metastatic LUAD tissues. Moreover, our study demonstrates that single cell transcriptome analysis is a potentially useful tool for accurate diagnosis and personalized targeted treatment of LUAD patients.
Pubmed ID: 33170151 RIS Download
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Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsA Cytoscape plug-in that visualizes the non-redundant biological terms for large clusters of genes in a functionally grouped network. It can be used in combination with GOlorize. The identifiers can be uploaded from a text file or interactively from a network of Cytoscape. The type of identifiers supported can be easily extended by the user. ClueGO performs single cluster analysis and comparison of clusters. From the ontology sources used, the terms are selected by different filter criteria. The related terms which share similar associated genes can be combined to reduce redundancy. The ClueGO network is created with kappa statistics and reflects the relationships between the terms based on the similarity of their associated genes. On the network, the node colour can be switched between functional groups and clusters distribution. ClueGO charts are underlying the specificity and the common aspects of the biological role. The significance of the terms and groups is automatically calculated. ClueGO is easy updatable with the newest files from Gene Ontology and KEGG. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsEncyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsSoftware as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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