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Comprehensive analysis of normal adjacent to tumor transcriptomes

Author

Listed:
  • Dvir Aran

    (University of California)

  • Roman Camarda

    (University of California
    University of California)

  • Justin Odegaard

    (Stanford University Medical Center)

  • Hyojung Paik

    (University of California
    Biomedical HPC Research Center)

  • Boris Oskotsky

    (University of California)

  • Gregor Krings

    (University of California)

  • Andrei Goga

    (University of California
    University of California
    University of California)

  • Marina Sirota

    (University of California)

  • Atul J. Butte

    (University of California)

Abstract

Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies. However, little is known about the transcriptomic profile of NAT, how it is influenced by the tumor, and how the profile compares with non-tumor-bearing tissues. Here, we integrate data from the Genotype-Tissue Expression project and The Cancer Genome Atlas to comprehensively analyze the transcriptomes of healthy, NAT, and tumor tissues in 6506 samples across eight tissues and corresponding tumor types. Our analysis shows that NAT presents a unique intermediate state between healthy and tumor. Differential gene expression and protein–protein interaction analyses reveal altered pathways shared among NATs across tissue types. We characterize a set of 18 genes that are specifically activated in NATs. By applying pathway and tissue composition analyses, we suggest a pan-cancer mechanism of pro-inflammatory signals from the tumor stimulates an inflammatory response in the adjacent endothelium.

Suggested Citation

  • Dvir Aran & Roman Camarda & Justin Odegaard & Hyojung Paik & Boris Oskotsky & Gregor Krings & Andrei Goga & Marina Sirota & Atul J. Butte, 2017. "Comprehensive analysis of normal adjacent to tumor transcriptomes," Nature Communications, Nature, vol. 8(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-01027-z
    DOI: 10.1038/s41467-017-01027-z
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    Cited by:

    1. Igor Dolgalev & Hua Zhou & Nina Murrell & Hortense Le & Theodore Sakellaropoulos & Nicolas Coudray & Kelsey Zhu & Varshini Vasudevaraja & Anna Yeaton & Chandra Goparaju & Yonghua Li & Imran Sulaiman &, 2023. "Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    2. Caitriona M. McEvoy & Julia M. Murphy & Lin Zhang & Sergi Clotet-Freixas & Jessica A. Mathews & James An & Mehran Karimzadeh & Delaram Pouyabahar & Shenghui Su & Olga Zaslaver & Hannes Röst & Rangi Ar, 2022. "Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    3. Nan Li & Alex Quan & Dan Li & Jiajia Pan & Hua Ren & Gerard Hoeltzel & Natalia Val & Dana Ashworth & Weiming Ni & Jing Zhou & Sean Mackay & Stephen M. Hewitt & Raul Cachau & Mitchell Ho, 2023. "The IgG4 hinge with CD28 transmembrane domain improves VHH-based CAR T cells targeting a membrane-distal epitope of GPC1 in pancreatic cancer," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    4. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
    5. Weilin Pu & Xiao Shi & Pengcheng Yu & Meiying Zhang & Zhiyan Liu & Licheng Tan & Peizhen Han & Yu Wang & Dongmei Ji & Hualei Gan & Wenjun Wei & Zhongwu Lu & Ning Qu & Jiaqian Hu & Xiaohua Hu & Zaili L, 2021. "Single-cell transcriptomic analysis of the tumor ecosystems underlying initiation and progression of papillary thyroid carcinoma," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    6. Yukinari Haraoka & Yuki Akieda & Yuri Nagai & Chihiro Mogi & Tohru Ishitani, 2022. "Zebrafish imaging reveals TP53 mutation switching oncogene-induced senescence from suppressor to driver in primary tumorigenesis," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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