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Immune signature of pheochromocytoma and paraganglioma in context of neuroendocrine neoplasms associated with prognosis

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12310%2F23%3A43906645" target="_blank" >RIV/60076658:12310/23:43906645 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://link.springer.com/article/10.1007/s12020-022-03218-1" target="_blank" >https://link.springer.com/article/10.1007/s12020-022-03218-1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s12020-022-03218-1" target="_blank" >10.1007/s12020-022-03218-1</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Immune signature of pheochromocytoma and paraganglioma in context of neuroendocrine neoplasms associated with prognosis

  • Popis výsledku v původním jazyce

    Purpose To understand prognostic immune cell infiltration signatures in neuroendocrine neoplasms (NENs), particularly pheochromocytoma and paraganglioma (PCPG), we analyzed tumor transcriptomic data from The Cancer Genome Atlas (TCGA) and other published tumor transcriptomic data of NENs. Methods We used CIBERSORT to infer immune cell infiltrations from bulk tumor transcriptomic data from PCPGs, in comparison to gastroenteropancreatic neuroendocrine tumors (GEPNETs) and small cell lung carcinomas (SCLCs). PCPG immune signature was validated with NanoString immune panel in an independent cohort. Unsupervised clustering of the immune infiltration scores from CIBERSORT was used to find immune clusters. A prognostic immune score model for PCPGs and the other NENs were calculated as a linear combination of the estimated infiltration of activated CD8(+)/CD4(+) T cells, activated NK cells, and M0 and M2 macrophages. Results In PCPGs, we found five dominant immune clusters, associated with M2 macrophages, monocytes, activated NK cells, M0 macrophages and regulatory T cells, and CD8(+)/CD4(+) T cells respectively. Non-metastatic tumors were associated with activated NK cells and metastatic tumors were associated with M0 macrophages and regulatory T cells. In GEPNETs and SCLCs, M0 macrophages and regulatory T cells were associated with unfavorable outcomes and features, such as metastasis and high-grade tumors. The prognostic immune score model for PCPGs and the NENs could predict non-aggressive and non-metastatic diseases. In PCPGs, the immune score was also an independent predictor of metastasis-free survival in a multivariate Cox regression analysis. Conclusion The transcriptomic immune signature in PCPG correlates with clinical features like metastasis and prognosis.

  • Název v anglickém jazyce

    Immune signature of pheochromocytoma and paraganglioma in context of neuroendocrine neoplasms associated with prognosis

  • Popis výsledku anglicky

    Purpose To understand prognostic immune cell infiltration signatures in neuroendocrine neoplasms (NENs), particularly pheochromocytoma and paraganglioma (PCPG), we analyzed tumor transcriptomic data from The Cancer Genome Atlas (TCGA) and other published tumor transcriptomic data of NENs. Methods We used CIBERSORT to infer immune cell infiltrations from bulk tumor transcriptomic data from PCPGs, in comparison to gastroenteropancreatic neuroendocrine tumors (GEPNETs) and small cell lung carcinomas (SCLCs). PCPG immune signature was validated with NanoString immune panel in an independent cohort. Unsupervised clustering of the immune infiltration scores from CIBERSORT was used to find immune clusters. A prognostic immune score model for PCPGs and the other NENs were calculated as a linear combination of the estimated infiltration of activated CD8(+)/CD4(+) T cells, activated NK cells, and M0 and M2 macrophages. Results In PCPGs, we found five dominant immune clusters, associated with M2 macrophages, monocytes, activated NK cells, M0 macrophages and regulatory T cells, and CD8(+)/CD4(+) T cells respectively. Non-metastatic tumors were associated with activated NK cells and metastatic tumors were associated with M0 macrophages and regulatory T cells. In GEPNETs and SCLCs, M0 macrophages and regulatory T cells were associated with unfavorable outcomes and features, such as metastasis and high-grade tumors. The prognostic immune score model for PCPGs and the NENs could predict non-aggressive and non-metastatic diseases. In PCPGs, the immune score was also an independent predictor of metastasis-free survival in a multivariate Cox regression analysis. Conclusion The transcriptomic immune signature in PCPG correlates with clinical features like metastasis and prognosis.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    30102 - Immunology

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2023

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    ENDOCRINE

  • ISSN

    1355-008X

  • e-ISSN

    1559-0100

  • Svazek periodika

    79

  • Číslo periodika v rámci svazku

    1

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    9

  • Strana od-do

    171-179

  • Kód UT WoS článku

    000882355400001

  • EID výsledku v databázi Scopus

    2-s2.0-85141741022