CC BY-NC-ND 4.0 · Laryngorhinootologie 2019; 98(S 02): S262-S263
DOI: 10.1055/s-0039-1686013
Poster
Oncology

The smLRP1/LRP1 Score is a predictor of progression-free (PFS) and overall survival (OS) in patients with head and neck squamous cell carcinoma (HNSCC)

M Kolb
1   HNO-Universitätsklinik Leipzig, Leipzig
,
S Wiegand
1   HNO-Universitätsklinik Leipzig, Leipzig
,
A Dietz
1   HNO-Universitätsklinik Leipzig, Leipzig
,
G Wichmann
1   HNO-Universitätsklinik Leipzig, Leipzig
› Author Affiliations
 

Introduction:

The Low density lipoprotein receptor-related protein 1 (LRP1) is an ubiquitously expressed endocytosis receptor. Its expression status is associated with clinical outcome of patients suffering from different tumour entities. So far, its function and those of its 19 splice variants are unknown in head and neck squamous cell carcinoma (HNSCC).

Methods:

Expression of LRP1 and its splice variant „small LRP1“ (smLRP1) was determined in 35 HNSCC. In a retrospective, explorative analysis, patient's survival was compared corresponding to the LRP1 and smLRP1 expression status in Kaplan-Meier-Analysis regarding progression-free (PFS) and overall survival (OS). Based on relative gene expression, a smLRP1/LRP1-score was developed and tested in multivariate Cox-regression analysis.

Results:

LRP1- and smLRP1-expression differs between early and advanced HNSCC. Patients with smLRP1 ≤0.08 and LRP1 ≤0.05 had a significantly worse PFS and OS independent of classical risk factors. Finally, the established smLRP1/LRP1-score was identified as an independent significant predictor of PFS and OS in multivariate Cox regression analyses.

Conclusions:

Here, we demonstrate for the first time an association of LRP1- and smLRP1-expression with the clinical outcome of HNSCC patients. Interestingly, neither expression of LRP1- or smLRP1-mRNA alone, but the established smLRP1/LRP1-Score is a potential prognostic biomarker for HNSCC-patients.



Publication History

Publication Date:
23 April 2019 (online)

© 2019. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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