A let-7 microRNA polymorphism in the KRAS 3'-UTR is prognostic in oropharyngeal cancer

INTRODUCTION

This study aimed to investigate the effect of genetic polymorphisms in miRNA sequences, miRNA target genes and miRNA processing genes as additional biomarkers to HPV for prognosis in oropharyngeal squamous cell carcinoma (OPSCC) patients. Secondarily, the prevalence of HPV-associated OPSCC in a European cohort was mapped.

METHODS

OPSCC patients (n=122) were genotyped for ten genetic polymorphisms in pre-miRNAs (pre-mir-146a, pre-mir-196a2), in miRNA biosynthesis genes (Drosha, XPO5) and in miRNA target genes (KRAS, SMC1B). HPV status was assessed by p16 immunohistochemistry (IHC) and high-risk HPV in situ hybridization (ISH) or by p16 IHC and PCR followed by enzyme-immunoassay (EIA). Overall and disease specific survival were analysed using Kaplan-Meier plots (log-rank test). Cox proportional hazard model was used to calculate hazard ratios (HR).

RESULTS

The overall HPV prevalence rate in our Belgian/Dutch cohort was 27.9%. Patients with HPV(+) tumours had a better 5-years overall survival (78% vs. 46%, p=0.001) and a better 5-years disease specific survival (90% vs. 70%, p=0.016) compared to patients with HPV(-) tumours. In multivariate Cox analysis including clinical, treatment and genetic parameters, HPV negativity (HR=3.89, p=0.005), advanced T-stage (HR=1.81, p=0.050), advanced N-stage (HR=5.86, p=0.001) and >10 pack-years of smoking (HR=3.45, p=0.012) were significantly associated with reduced overall survival. The variant G-allele of the KRAS-LCS6 polymorphism was significantly associated with a better overall survival (HR=0.40, p=0.031).

CONCLUSIONS

Our results demonstrate that OPSCC patients with the KRAS-LCS6 variant have a better outcome and suggest that this variant may be used as a prognostic biomarker for OPSCC.

Radiomics: extracting more information from medical images using advanced feature analysis

Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics--the high-throughput extraction of large amounts of image features from radiographic images--addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory.