Abstract Library

#3146 Transcriptomic deconvolution of neuroendocrine neoplasms predicts clinically relevant characteristics

Introduction: Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. However, a comprehensive training of machine-learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types.

Conference: 18th Annual ENETS Concerence (2021)

Presenting Author: Otto R

Authors: Otto R, Detjen K, Riemer P, Grötzinger C, Rindi G,

Keywords: bioinformatics, NET, PanNEN, deconvolution, transcriptomics, RNA-seq, neuroendocrine cancer,

#1551 Establishment and Characterization of Three GEP-NEC Cell Lines for In Vitro and In Vivo Studies

Introduction: To date chemotherapeutic concepts applying cisplatin/etoposide for the treatment of highly aggressive GEP-NEC do not provide convincing results. Thus, there is an urgent need for NEC cell line models that provide a reliable experimental system in identifying novel therapeutic targets.

Conference: 13th Annual ENETSConcerence (2016)

Presenting Author: Krieg A

Authors: Krieg A, Riemer J, Dizdar L, Mersch S, Anlauf M,

Keywords: GEP-NEC,

#1545 In Vivo Expression of Survivin and XIAP in Medullary Thyroid Carcimoma

Introduction: Medullary thyroid carcinoma (MTC) accounts for approximately 5 % of all thyroid malignancies. Although surgery remains the first line therapy with curative intention, for advanced MTC current chemotherapeutic regimes do not provide promising results. Consequently, the identification of biologically relevant biomarkers that are associated with MTC progression may provide novel therapeutic targets.

Conference: 13th Annual ENETSConcerence (2016)

Presenting Author: Werner T

Authors: Werner T, Riemer J, Dizdar L, Wolf A, Cupisti K,

Keywords: MTC, IAP, survivin, XIAP,