Abstract
IntroductionDecoding transcriptional effects of experimental tissue–tissue or cell–cell interactions is important; for example, to better understand tumor–stroma interactions after transplantation of human cells into mouse (xenografting). Transcriptome analysis of intermixed human and mouse cells has, however, frequently relied on the need to separate the two cell populations prior to transcriptome analysis, which introduces confounding effects on gene expression.MethodsTo circumvent this problem, we here describe a bioinformatics-based, genome-wide transcriptome analysis technique, which allows the human and mouse transcriptomes to be decoded from a mixed mouse and human cell population. The technique is based on a bioinformatic separation of the mouse and human transcriptomes from the initial mixed-species transcriptome resulting from sequencing an excised tumor/stroma specimen without prior cell sorting.ResultsUnder stringent separation criteria, i.e., with a read misassignment frequency of 0.2 %, we show that 99 % of the genes can successfully be assigned to be of mouse or human origin, both in silico, in cultured cells and in vivo. We use a new species-specific sequencing technology—referred to as S3 (“S-cube”)—to provide new insights into the Notch downstream response following Notch ligand-stimulation and to explore transcriptional changes following transplantation of two different breast cancer cell lines (luminal MCF7 and basal-type MDA-MB-231) into mammary fat pad tissue in mice of different immunological status. We find that MCF7 and MDA-MB-231 respond differently to fat pad xenografting and the stromal response to transplantation of MCF7 and MDA-MB-231 cells was also distinct.ConclusionsIn conclusion, the data show that the S3 technology allows for faithful recording of transcriptomic changes when human and mouse cells are intermixed and that it can be applied to address a broad spectrum of research questions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-015-0616-x) contains supplementary material, which is available to authorized users.
Highlights
Decoding transcriptional effects of experimental tissue–tissue or cell–cell interactions is important; for example, to better understand tumor–stroma interactions after transplantation of human cells into mouse
We demonstrate that the S3 technology can identify 99 % of all genes to be of mouse or human origin at a low species misassignment frequency, and we use the technology to provide new insights into transcriptional effects of Notch signaling and tumor–stroma interactions in xenografts
When the MCF7 stromal transcriptome was directly compared to the stroma surrounding MDA-MB-231 cells we identified 4394 genes upregulated in the MCF7 versus the MDA-MB
Summary
Decoding transcriptional effects of experimental tissue–tissue or cell–cell interactions is important; for example, to better understand tumor–stroma interactions after transplantation of human cells into mouse (xenografting). In many situations it would be useful to simultaneously decode the transcriptomes of two different interacting cell types; for example, when human tumor cells are xenografted into mice. Chivukula et al Breast Cancer Research (2015) 17:109 cell mixing is experimentally used: analysis of Notch signaling and xenografting of human breast cancer cells into mammary fat pads in mice. Overexpression of activated forms of Notch in mammary tissue in transgenic mice leads to breast tumor development [11], and engrafting of human breast tumor cells with different levels of Notch has revealed a role for Notch in tumor progression and cellular metabolism [12]. Notch signaling is implicated in tumor–stroma interactions, metastasis and therapy resistance in breast cancer [13,14,15,16]
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