TY - JOUR
T1 - Alteration of specific cytokine expression patterns in patients with breast cancer
AU - Kawaguchi, Kosuke
AU - Sakurai, Masashi
AU - Yamamoto, Yasuko
AU - Suzuki, Eiji
AU - Tsuda, Moe
AU - Kataoka, Tatsuki R.
AU - Hirata, Masahiro
AU - Nishie, Mariko
AU - Nojiri, Takashi
AU - Kumazoe, Motofumi
AU - Saito, Kuniaki
AU - Toi, Masakazu
N1 - Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Systemic inflammation has been associated with aggressive tumor growth, invasion, and metastasis. Here we performed a comprehensive analysis of 26 kinds of inflammatory cytokine expression patterns among 185 patients with breast cancer and 54 healthy volunteers followed by chemometric analysis. We identified the specific cytokine expression patterns of breast cancer patients compared to healthy volunteers with (1) VEGF, IL-9, GM-CSF, IL-13, IL-4, and IFNγ, (2) IL-8, IL-10, IL-12, IL-5, IL-7, IL-1α, GCSF, IL-1β, and TNFα and (3) IL-2, Eotaxin, MIP1β, MIP1α, IL-17, and bFGF. Among the patients with breast cancer, we identified the specific cytokine signature of metastatic patients compared to non-metastatic patients. We also established a mathematical model for distinguishing patients with breast cancer from healthy volunteers and metastatic patients from non-metastatic patients. This cytokine network analysis could provide new insights into early intervention and effective therapeutic strategy for patients with breast cancer.
AB - Systemic inflammation has been associated with aggressive tumor growth, invasion, and metastasis. Here we performed a comprehensive analysis of 26 kinds of inflammatory cytokine expression patterns among 185 patients with breast cancer and 54 healthy volunteers followed by chemometric analysis. We identified the specific cytokine expression patterns of breast cancer patients compared to healthy volunteers with (1) VEGF, IL-9, GM-CSF, IL-13, IL-4, and IFNγ, (2) IL-8, IL-10, IL-12, IL-5, IL-7, IL-1α, GCSF, IL-1β, and TNFα and (3) IL-2, Eotaxin, MIP1β, MIP1α, IL-17, and bFGF. Among the patients with breast cancer, we identified the specific cytokine signature of metastatic patients compared to non-metastatic patients. We also established a mathematical model for distinguishing patients with breast cancer from healthy volunteers and metastatic patients from non-metastatic patients. This cytokine network analysis could provide new insights into early intervention and effective therapeutic strategy for patients with breast cancer.
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U2 - 10.1038/s41598-019-39476-9
DO - 10.1038/s41598-019-39476-9
M3 - Article
C2 - 30814616
AN - SCOPUS:85062156913
SN - 2045-2322
VL - 9
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 2924
ER -
