The transcriptome difference between colorectal tumor and normal tissues revealed by single-cell sequencing

Zhang, Guoliang; Pan, Lelin; Huang, Tao; Wang, Jinhai

doi:10.7150/jca.32267

Cited by 30 publications

(23 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our data highlights a clear shift in the transcriptome of PBMCs from cancer patients, suggesting such alterations are not restricted to the tumor microenvironment but rather are reflected systematically. Our data is in agreement with previous reports also documenting changes in gene expression in peripheral blood and/or tumor tissue from patients with CRC using digital gene expression-tag profiling approach [18], high through-put real time polymerase chain reaction (PCR) [11], single-cell sequencing [19], human transcriptome array (HTA) [20] and whole genome sequencing [21,22].…”

Section: Discussionsupporting

confidence: 93%

Transcriptomic Analyses Revealed Systemic Alterations in Gene Expression in Circulation and Tumor Microenvironment of Colorectal Cancer Patients

Shaath

Toor

Nair

et al. 2019

Cancers

View full text Add to dashboard Cite

Colorectal cancer (CRC) is among the leading causes of cancer-related deaths worldwide, underscoring a need for better understanding of the disease and development of novel diagnostic biomarkers and therapeutic interventions. Herein, we performed transcriptome analyses on peripheral blood mononuclear cells (PBMCs), CRC tumor tissue and adjacent normal tissue from 10 CRC patients and PBMCs from 15 healthy controls. Up regulated transcripts from CRC PBMCs were associated with functions related to immune cell trafficking and cellular movement, while downregulated transcripts were enriched in cellular processes related to cell death. Most affected signaling networks were those involved in tumor necrosis factor (TNF) and interleukin signaling. The expression of selected immune-related genes from the RNA-Seq data were further validated using qRT-PCR. Transcriptome analysis of CRC tumors and ingenuity pathway analysis revealed enrichment in several functional categories related to cellular movement, cell growth and proliferation, DNA replication, recombination and repair, while functional categories related to cell death were suppressed. Upstream regulator analysis revealed activation of ERBB2 and FOXM1 networks. Interestingly, there were 18 common upregulated and 36 common downregulated genes when comparing PBMCs and tumor tissue, suggesting transcriptomic changes in the tumor microenvironment could be reflected, in part, in the periphery with potential utilization as disease biomarkers.

show abstract

Section: Discussionsupporting

confidence: 93%

Transcriptomic Analyses Revealed Systemic Alterations in Gene Expression in Circulation and Tumor Microenvironment of Colorectal Cancer Patients

Shaath

Toor

Nair

et al. 2019

Cancers

View full text Add to dashboard Cite

show abstract

“…If several genes are similar, only the most representative gene will be selected. This approach has been proven to be effective and has been widely used for many biomedical feature selection problems (Niu et al, 2013;Zhao et al, 2013;Zhou et al, 2015;Zhang et al, 2016;Liu et al, 2017), especially in single cell RNA-Seq analysis (Zhang et al, 2019). The sample size of single cell data was large and the gene expression was spare.…”

Section: The Mrmr Ranking Of Discriminative Genesmentioning

confidence: 99%

Identification and Analysis of Glioblastoma Biomarkers Based on Single Cell Sequencing

Cheng

Fan

et al. 2020

Front. Bioeng. Biotechnol.

View full text Add to dashboard Cite

Glioblastoma (GBM) is one of the most common and aggressive primary adult brain tumors. Tumor heterogeneity poses a great challenge to the treatment of GBM, which is determined by both heterogeneous GBM cells and a complex tumor microenvironment. Single-cell RNA sequencing (scRNA-seq) enables the transcriptomes of great deal of individual cells to be assayed in an unbiased manner and has been applied in head and neck cancer, breast cancer, blood disease, and so on. In this study, based on the scRNA-seq results of infiltrating neoplastic cells in GBM, computational methods were applied to screen core biomarkers that can distinguish the discrepancy between GBM tumor and pericarcinomatous environment. The gene expression profiles of GBM from 2343 tumor cells and 1246 periphery cells were analyzed by maximum relevance minimum redundancy (mRMR). Upon further analysis of the feature lists yielded by the mRMR method, 31 important genes were extracted that may be essential biomarkers for GBM tumor cells. Besides, an optimal classification model using a support vector machine (SVM) algorithm as the classifier was also built. Our results provided insights of GBM mechanisms and may be useful for GBM diagnosis and therapy.

show abstract

“…These were downloaded from the Gene Ontology database 1 and the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were downloaded from the KEGG database 2 . Hypergeometric distribution test (Li et al, 2019a;Pan et al, 2019b;Zhang et al, 2019) was applied to detect enrichment terms and p-values were corrected by False Discovery Rate (FDR) methods with a cutoff FDR < 0.05. Significantly enriched entries in all modules were sorted in ascending order by FDR value.…”

Section: Functional Enrichment Analysis Of Module Genesmentioning

confidence: 99%

Investigation of miRNA and mRNA Co-expression Network in Ependymoma

Liu

Dong

Mei

et al. 2020

Front. Bioeng. Biotechnol.

Self Cite

View full text Add to dashboard Cite

Ependymoma (EPN) is a rare primary tumor of the central nervous system (CNS) that affects both children and adults. Despite the definition and classification of distinct molecular subgroups, there remains a group of EPNs with a balanced genome, which makes it difficult to predict a prognosis of patients with EPN. The role of miRNA-mRNA network on EPN is still poorly understood. We assessed the involvement of miRNA-mRNA pairs in EPN by applying a weighted co-expression network analysis (WGCNA) approach. Using whole genome expression profile analysis followed by functional enrichment, we detected hub genes involved in active proliferation and DNA replication of nerve cells. Key genes including CYP11B1, KRT33B, RUNX1T1, SIK1, MAP3K4, MLANA, and SFRP5 identified in co-expression networks were regulated by miR-15a and miR-24-1. These seven miRNA-mRNA pairs were considered to influence not only pathways in cancer and tumor suppression process, but also MAPK, NF-kappaB, and WNT signaling pathways which were associated with tumorigenesis and development. This study provides a novel insight into potential diagnostic biomarkers of EPN and may have value in choosing therapeutic targets with clinical utility.

show abstract

The transcriptome difference between colorectal tumor and normal tissues revealed by single-cell sequencing

Cited by 30 publications

References 56 publications

Transcriptomic Analyses Revealed Systemic Alterations in Gene Expression in Circulation and Tumor Microenvironment of Colorectal Cancer Patients

Transcriptomic Analyses Revealed Systemic Alterations in Gene Expression in Circulation and Tumor Microenvironment of Colorectal Cancer Patients

Identification and Analysis of Glioblastoma Biomarkers Based on Single Cell Sequencing

Investigation of miRNA and mRNA Co-expression Network in Ependymoma

Contact Info

Product

Resources

About