Decoding breast cancer tissue-stroma interactions using species-specific sequencing.

Indira V Chivukula; Daniel Ramsköld; Helena Storvall; Charlotte Anderberg; Shaobo Jin; Veronika Mamaeva; Cecilia Sahlgren; Kristian Pietras; Rickard Sandberg; Urban Lendahl

doi:10.1186/s13058-015-0616-x

Decoding breast cancer tissue-stroma interactions using species-specific sequencing.

Indira V Chivukula, Daniel Ramsköld, Helena Storvall, Charlotte Anderberg, Shaobo Jin, Veronika Mamaeva, Cecilia Sahlgren, Kristian Pietras, Rickard Sandberg, Urban Lendahl

Avdelningen för translationell cancerforskning

Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

273 Nedladdningar (Pure)

Sammanfattning

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). 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.

Originalspråk	engelska
Artikelnummer	109
Tidskrift	Breast Cancer Research
Volym	17
DOI	https://doi.org/10.1186/s13058-015-0616-x
Status	Published - 2015

Ämnesklassifikation (UKÄ)

Cancer och onkologi

FN:s Globala mål

Denna forskningsoutput relaterar till följande Globala mål

Tillgång till dokument

10.1186/s13058-015-0616-x

BMC_Chivukula

http://www.ncbi.nlm.nih.gov/pubmed/26265142?dopt=Abstract

Citera det här

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title = "Decoding breast cancer tissue-stroma interactions using species-specific sequencing.",

abstract = "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). 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.",

author = "Chivukula, {Indira V} and Daniel Ramsk{\"o}ld and Helena Storvall and Charlotte Anderberg and Shaobo Jin and Veronika Mamaeva and Cecilia Sahlgren and Kristian Pietras and Rickard Sandberg and Urban Lendahl",

year = "2015",

doi = "10.1186/s13058-015-0616-x",

language = "English",

volume = "17",

journal = "Breast Cancer Research",

issn = "1465-5411",

publisher = "BioMed Central (BMC)",

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T1 - Decoding breast cancer tissue-stroma interactions using species-specific sequencing.

AU - Chivukula, Indira V

AU - Ramsköld, Daniel

AU - Storvall, Helena

AU - Anderberg, Charlotte

AU - Jin, Shaobo

AU - Mamaeva, Veronika

AU - Sahlgren, Cecilia

AU - Pietras, Kristian

AU - Sandberg, Rickard

AU - Lendahl, Urban

PY - 2015

Y1 - 2015

N2 - 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). 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.

AB - 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). 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.

U2 - 10.1186/s13058-015-0616-x

DO - 10.1186/s13058-015-0616-x

M3 - Article

C2 - 26265142

SN - 1465-5411

VL - 17

JO - Breast Cancer Research

JF - Breast Cancer Research

M1 - 109

ER -

Decoding breast cancer tissue-stroma interactions using species-specific sequencing.

Sammanfattning

Ämnesklassifikation (UKÄ)

FN:s Globala mål

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