Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 25 von 1848

Details

Autor(en) / Beteiligte
Titel
Treatment Outcome and Prognostic Molecular Markers of Supratentorial Primitive Neuroectodermal Tumors
Ist Teil von
  • PloS one, 2016-04, Vol.11 (4), p.e0153443-e0153443
Ort / Verlag
United States: Public Library of Science
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Free E-Journal (出版社公開部分のみ)
Beschreibungen/Notizen
  • To identify prognostic factors and define the optimal management of patients with supratentorial primitive neuroectodermal tumors (sPNETs), we investigated treatment outcomes and explored the prognostic value of specific molecular markers. A total of 47 consecutive patients with pathologically confirmed sPNETs between May 1985 and June 2012 were included. Immunohistochemical analysis of LIN28, OLIG2, and Rad51 expression was performed and correlated with clinical outcome. With a median follow-up of 70 months, 5-year overall survival (OS) and progression-free survival (PFS) was 55.5% and 40%, respectively, for all patients. Age, surgical extent, and radiotherapy were significant prognostic factors for OS and PFS. Patients who received initially planned multimodal treatment without interruption (i.e., radiotherapy and surgery (≥subtotal resection), with or without chemotherapy) showed significantly higher 5-year OS (71.2%) and PFS (63.1%). In 29 patients with available tumor specimens, tumors with high expression of either LIN28 or OLIG2 or elevated level of Rad51 were significantly associated with poorer prognosis. We found that multimodal treatment improved outcomes for sPNET patients, especially when radiotherapy and ≥subtotal resection were part of the treatment regimen. Furthermore, we confirmed the prognostic significance of LIN28 and OLIG2 and revealed the potential role of Rad51 in sPNETs.

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX