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Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.

ABSTRACT: As interactions between the immune system and tumour cells are governed by a complex network of cell-cell interactions, knowing the specific immune cell composition of a solid tumour may be essential to predict a patient's response to immunotherapy. Here, we analyse in depth how to derive the cellular composition of a solid tumour from bulk gene expression data by mathematical deconvolution, using indication-specific and cell type-specific reference gene expression profiles (RGEPs) from tumour-derived single-cell RNA sequencing data. We demonstrate that tumour-derived RGEPs are essential for the successful deconvolution and that RGEPs from peripheral blood are insufficient. We distinguish nine major cell types, as well as three T cell subtypes. Using the tumour-derived RGEPs, we can estimate the content of many tumours associated immune and stromal cell types, their therapeutically relevant ratios, as well as an improved gene expression profile of the malignant cells.

SUBMITTER: Schelker M

PROVIDER: S-EPMC5725570 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.

Schelker Max M Feau Sonia S Du Jinyan J Ranu Nav N Klipp Edda E MacBeath Gavin G Schoeberl Birgit B Raue Andreas A

Nature communications 20171211 1

As interactions between the immune system and tumour cells are governed by a complex network of cell-cell interactions, knowing the specific immune cell composition of a solid tumour may be essential to predict a patient's response to immunotherapy. Here, we analyse in depth how to derive the cellular composition of a solid tumour from bulk gene expression data by mathematical deconvolution, using indication-specific and cell type-specific reference gene expression profiles (RGEPs) from tumour-d ...[more]

PMID: 29230012

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Project description:Thyroid hormones mediate a remarkable range of functions in many tissues and organ systems through the thyroid hormone receptors-THRA and THRB. Tissues and organs are composed of heterogeneous cells of different cell types. These different cell types have varying receptor expression abilities, which lead to variable responses in thyroid hormone regulation. The tissue-specific Thra and Thrb gene expression patterns help us understand the action of thyroid hormones at the tissue level. However, the situation becomes complicated if we wish to focus on tissues more closely to trace the responsive cells, which is a vital step in the process of understanding the molecular mechanism of diseases related to thyroid hormone regulation. Single-cell RNA sequencing technology is a powerful tool used to profile gene expression programs in individual cells. The Tabula Muris Consortium generates a single-cell transcriptomic atlas across the life span of Mus musculus that includes data from 23 tissues and organs. It provides an unprecedented opportunity to understand thyroid hormone regulation at the cell type resolution. We demonstrated the approaches that allow application of the single-cell RNA-Seq data generated by the Tabula Muris Consortium to trace responsive cells in tissues. First, employing the single-cell RNA-Seq data, we calculated the ability of different cell types to express Thra and Thrb, which direct us to the cell types sensitive to thyroid hormone regulation in tissues and organs. Next, using a cell clustering algorithm, we explored the subtypes with low Thra or Thrb expression within the different cell types and identified the potentially responsive cell subtypes. Finally, in the liver tissue treated with thyroid hormones, using the single-cell RNA-Seq data, we successfully traced the responsive cell types. We acknowledge that the computational predictions reported here need to be further validated using wet-lab experiments. However, we believe our results provide powerful information and will be beneficial for wet lab researchers.

Dataset Information

Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.

Publications

Estimation of immune cell content in tumour tissue using single-cell RNA-seq data.

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