Abstract 3543
Background
Non-small cell lung cancer is a major killer world-wide. While some lung adenocarcinomas have mutations qualifying for targeted therapy, this is not the case for the squamous cell carcinomas (SqCC). TP53 mutations exist in around 85% of squamous cell carcinomas, but the mutations are difficult to target directly. We explore the biology of TP53 mutated SqCC and search for putative targets for therapy.
Methods
Patients undergoing surgery for squamous cell lung carcinoma from 2006 to 2015 were included in the study (n = 198). Tumours were analysed using Illumina SNP6 for copy number alterations and Agilent 60K arrays for gene expression. TP53 mutations were analysed by Sanger sequencing. For 140 patients both gene expression and copy number data were available.
Results
Frequency plots for tumours harbouring TP53 mutations and TP53 wild type tumours were generated separately identifying genomic regions with differential frequency of copy number alterations. TP53 mutations are more frequent in the previously published gene expression subtypes Classical and Primitive compared with Basal and Secretory, but this does not seem to affect survival. Amplifications are particularly frequent in the Classical subtype. Target gene search was performed, identifying 148 genes with amplification and over-expression in TP53 mutated tumours compared with wild type tumours. Several of these putative target genes are previously studied as putative targets of therapy. The majority of the putative target genes are located on the chromosomal arms 2p for samples of the Secretory subtype, 2q for samples of the Primitive subtype and on 12p and 17q for samples of the Classical subtype.
Conclusions
There are distinct copy number alterations and gene expression patterns in TP53 mutated squamous cell lung cancers that can be used to identify novel targets of therapy.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Oslo University Hospital.
Funding
The Norwegian Cancer Society, South-Eastern Norway Regional Health Authority.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
5678 - Nanomaterials Augmented LDI-TOF-MS for Hepatocellular Carcinoma Diagnosis and Classification
Presenter: Jian Zhou
Session: Poster Display session 3
Resources:
Abstract
2436 - Development and Validation of an RNA-Seq Assay for Gene Fusions Detection in Formalin-Fixed Paraffin-Embedded Samples
Presenter: Hua Dong
Session: Poster Display session 3
Resources:
Abstract
5271 - A Pilot Study to Implement an Artificial Intelligence (AI) System for Gastrointestinal Cancer Clinical Trial Matching
Presenter: Zhaohui Jin
Session: Poster Display session 3
Resources:
Abstract
4787 - A Blinded Comparison of Patient Treatments to Therapeutic Options Presented by an Artificial Intelligence-based Clinical Decision-support system
Presenter: Suthida Suwanvecho
Session: Poster Display session 3
Resources:
Abstract
5744 - OncOS: scalable and accurate next-generation sequencing analytics for precision oncology and personalized patient care
Presenter: Joe Thompson
Session: Poster Display session 3
Resources:
Abstract
3752 - The association between wearable device physical activity metrics and performance status in oncology: a systematic review
Presenter: Milan Kos
Session: Poster Display session 3
Resources:
Abstract
5820 - SomaticNET: neural network evaluation of somatic mutations in cancer
Presenter: Geoffroy Dubourg-Felonneau
Session: Poster Display session 3
Resources:
Abstract
4771 - Is there a role for Next-generation sequencing (NGS) profiling on metastatic non-colorectal gastrointestinal carcinomas (MNCGIC) in developing countries? A single center experience.
Presenter: Mauricio Ribeiro
Session: Poster Display session 3
Resources:
Abstract
1209 - Metastatic Cancer Whole-Exome Sequencing in daily practice
Presenter: Manon Réda
Session: Poster Display session 3
Resources:
Abstract
5702 - Genomic-Guided Individualized Precision Therapy in Refractory Metastatic Solid Tumor Patients with Extensively Poor Performance Status: A Chinese single institutional prospective observational real-world study
Presenter: Haitao Wang
Session: Poster Display session 3
Resources:
Abstract