Oncotarget: Novel markers of colorectal tumors exhibiting microsatellite instability


Oncotarget published "Controlling for cellular heterogeneity using single-cell deconvolution of gene expression reveals novel markers of colorectal tumors exhibiting microsatellite instability" which reported that Bulk RNA-sequencing approaches have been employed to elucidate transcriptional differences between MSI-H and microsatellite stable CRC tumors.

The authors performed single-cell deconvolution of bulk RNA-sequencing on The Cancer Genome Atlas colon adenocarcinoma dataset. Cell composition within each dataset was estimated using CIBERSORTx.

Significant differences in abundance were observed for 13 of 19 cell types between MSI-H and MSS/MSI-L tumors in TCGA-COAD.

The authors were able to validate some of these differences in an independent biopsy dataset. By incorporating cell composition into their regression model, they identified 3,193 differentially expressed genes, of which 556 were deemed novel.

By incorporating cell composition into their regression model, they identified 3,193 differentially expressed genes, of which 556 were deemed novel

They subsequently validated many of these genes in an independent dataset of colon cancer cell lines.

Dr. Graham Casey from The University of Virginia said, "Colorectal cancer (CRC) is a complex, heterogenous disease."

The majority of MSI-H tumors occur via acquired epigenetic silencing of the MMR gene MLH1. In contrast, microsatellite stable tumors account for the majority of CRC tumors, and are defined by increased loss or gain and rearrangement of chromosomes.

MSI-H and MSS tumors have been shown to differ with regards to survival and response to treatment, but the molecular mechanisms driving the differences between these tumor types remain poorly understood.

Figure 7: Overview of the brown4 module.

Figure 7: Overview of the brown4 module. For visualization, the network was imported into Cytoscape. Grey lines reflect edges (connections) between hubs (genes).

The application of single-cell deconvolution approaches using bulk RNA-seq data therefore provides an opportunity to infer cell composition differences of large tumor datasets at reduced cost.

They estimate cell type abundance and identify novel cellular composition differences between MSI-H and MSS/MSI-L tumors, which we then validate in an independent cohort of CRC tumors.

Following adjustment for cell composition, the authors identified novel differentially expressed genes between MSI-H and MSS/MSI-L tumors in TCGA-COAD and replicate many of these DEGs in an independent analysis of colon cancer cell lines derived from Cancer Cell Line Encyclopedia.

The Casey Research Team concluded in their Oncotarget Research Output, "we employ a machine learning approach to deconvolute MSI-H and MSS/MSI-L tumor gene expression across TCGA-COAD and two additional cohorts. We identify novel changes in cell composition for EECs and colonocytes that suggests previously uncharacterized roles for these cell populations in contributing to MSI-H tumor development. Finally we use both single-gene and network analysis to identify several novel genes that may play an important role in MSI-H tumor biology."

DOI - https://doi.org/10.18632/oncotarget.27935

Full text - https://www.oncotarget.com/article/27935/text/

Correspondence to - Graham Casey - [email protected]

Keywords - colorectal cancer, single-cell deconvolution, microsatellite instability, RNA-sequencing, enteroendocrine

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