17P - Identifying the genetic landscape of squamous cell carcinoma (SCC) and adenosquamous carcinoma (ASC) of the lung using next-generation sequencing (N...

Date 17 April 2015
Event ELCC 2015
Session Poster lunch
Topics Non-Small-Cell Lung Cancer, Metastatic
Pathology/Molecular Biology
Personalised Medicine
Translational Research
Presenter Nataliya Chilingirova
Citation Annals of Oncology (2015) 26 (suppl_1): 1-5. 10.1093/annonc/mdv043
Authors N. Chilingirova1, L. Balabanski2, D. Toncheva3, G. Kurteva1, D. Damyanov1, P. Chilingirov4
  • 1Chemotherapy, National Center of Oncology-SBALO EAD, 1756 - Sofia/BG
  • 2Genomics Laboratory, Malinov Clinic, 1620 - Sofia/BG
  • 3Medical Genetics, Medical University, 1417 - Sofia/BG
  • 4Medical Oncology, Complex Oncology Center, 6000 - Stara Zagora/BG

Abstract

Aim/Background

Genetic tests have become an important part of oncology, as the number of molecular markers and viable targets for the treatment of patients with non-small cell lung cancer (NSCLC) continues to expand. Squamous cell carcinoma (SCC) of the lung is the main histotype where molecular testing is not routinely performed, since driver mutations are uncommon in this subset. The aim of this study is to identify the mutation profile of SCC and adenosquamous carcinoma (ASC) and to provide more information in order to fulfill the needs of personalized medicine.

Methods

In this prospective study we included 15 patients (13 male, 2 female) stage IIIB-IV with histology for NSCLC: 9 SCCs, 6 ASCs. DNA was extracted from paraffin-embedded (FFPE) tumor tissue. Sequencing was performed on an Illumina MiSeq platform using a TruSight Cancer Panel targeting the coding sequence of 94 genes and 284 SNPs. BaseSpace was used for alignment and variant calling, and VariantStudio – for further analysis. The effect of rare (<3% global frequency) missense variants was predicted using RadialSVM and LR scores. Variants were classified into 3 groups – pathogenic mutations associated with cancer development (driver mutations), presumed pathogenic variants that might contribute to its growth, and variants with unknown clinical significance.

Results

In total, 243 variants were identified - median 13 (4-26) variants per sample for SCC and 22 (4-57) for ASC. Loss-of-function variants including nonsense, frameshift and splicesite mutations were detected in all patients. In 14/15 those mutations were in haploinsufficient genes. The genes affected were ATM, NF1, APC, TP53, BRCA2, APC, CDKN1C, EZH2, PTEN in ASC, and NF1, TP53, KIT, XPC, WT1, TSC1, MSH2, GPC3 in SCC revealing the role of NF1 and TP53 in both histotypes.

Conclusions

This study successfully provided insights into the complex genetic landscape of SCC and ASC tumor cells. After clinical validation, molecular profiling by NGS could be integrated into practice for patients with SCC in order to build a large database of potential driver mutations that could in turn be utilized for future research and discovery of new targets and treatments for SCC.

Disclosure

All authors have declared no conflicts of interest.