Dataset Information

Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.

ABSTRACT:

Background

Colorectal Cancer (CRC) is a highly heterogeneous disease. RNA profiles of bulk tumors have enabled transcriptional classification of CRC. However, such ways of sequencing can only target a cell colony and obscure the signatures of distinct cell populations. Alternatively, single-cell RNA sequencing (scRNA-seq), which can provide unbiased analysis of all cell types, opens the possibility to map cellular heterogeneity of CRC unbiasedly.

Methods

In this study, we utilized scRNA-seq to profile cells from cancer tissue of a CRC patient. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to understand the roles of genes within the clusters.

Results and conclusion

The 2824 cells were analyzed and categorized into 5 distinct clusters by scRNA-seq. For every cluster, specific cell markers can be applied, indicating each 1 of them different from another. We discovered that the tumor of CRC displayed a clear sign of heterogenicity, while genes within each cluster serve different functions. GO term analysis also stated that different cluster's relatedness towards the tumor of CRC differs. Three clusters participate in peripheral works in cells, including, energy transport, extracellular matrix generation, etc; Genes in other 2 clusters participate more in immunology processes. Lastly, trajectory plot analysis also supports the viewpoint, in that some clusters present in different states and pseudo-time, while others present in a single state or pseudo time. Our analysis provides more insight into the heterogeneity of CRC, which can provide assistance to further researches on this topic.

SUBMITTER: Dai W

PROVIDER: S-EPMC6716720 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Publications

Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.

Dai Weier W Zhou Fangbin F Tang Donge D Lin Liewen L Zou Chang C Tan Wenyong W Dai Yong Y

Medicine 20190801 34

<h4>Background</h4>Colorectal Cancer (CRC) is a highly heterogeneous disease. RNA profiles of bulk tumors have enabled transcriptional classification of CRC. However, such ways of sequencing can only target a cell colony and obscure the signatures of distinct cell populations. Alternatively, single-cell RNA sequencing (scRNA-seq), which can provide unbiased analysis of all cell types, opens the possibility to map cellular heterogeneity of CRC unbiasedly.<h4>Methods</h4>In this study, we utilized ...[more]

PMID: 31441872

Similar Datasets

Project description:BackgroundWith functionally heterogeneous cells, tumors comprise a complex ecosystem to promote tumor adaptability and evolution under strong selective pressure from the given microenvironment. Diversifying tumor cells or intra-tumor heterogeneity is essential for tumor growth, invasion, and immune evasion. However, no reliable method to classify tumor cell subtypes is yet available. In this study, we introduced the single-cell sequencing combined with copy number characteristics to identify the types of tumor cells in microsatellite stable (MSS) colorectal cancer (CRC).MethodsTo characterize the somatic copy number alteration (SCNA) of MSS CRC in a single cell profile, we analyzed 26 tissue samples from 19 Korean patients (GSE132465, the Samsung Medical Center [SMC] dataset) and then verified our findings with 15 tissue samples from five Belgian patients (GSE144735, the Katholieke Universiteit Leuven 3 [KUL3] dataset). The Cancer Genome Atlas (TCGA) cohort, GSE39582 cohort, and National Cancer Center (NCC) cohort (24 MSS CRC patients were enrolled in this study between March 2017 and October 2017) were used to validate the clinical features of prognostic signatures.ResultsWe employed single cell RNA-sequencing data to identify three types of tumor cells in MSS CRC by their SCNA characteristics. Among these three types of tumor cells, C1 and C3 had a higher SCNA burden; C1 had significant chromosome 13 and 20 amplification, whereas C3 was the polar opposite of C1, which exhibited deletion in chromosome 13 and 20. The three types of tumor cells exhibited various functions in the tumor microenvironment and harbored different mutations. C1 and C2 were linked to the immune response and hypoxia, respectively, while C3 was critical for cell adhesion activity and tumor angiogenesis. Additionally, one gene ( OLFM4 ) was identified as epithelium-specific biomarker of better prognosis of CRC (TCGA cohort: P = 0.0110; GSE39582 cohort: P = 0.0098; NCC cohort: P = 0.0360).ConclusionsOn the basis of copy number characteristics, we illustrated tumor heterogeneity in MSS CRC and identified three types of tumor cells with distinct roles in tumor microenvironment. By understanding heterogeneity in the intricate tumor microenvironment, we gained an insight into the mechanisms of tumor evolution, which may support the development of therapeutic strategies.

Dataset Information

Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.

Background

Methods

Results and conclusion

Publications

Single-cell transcriptional profiling reveals the heterogenicity in colorectal cancer.

Similar Datasets

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