Poster Presentation NSW State Cancer Conference 2023

More than just single nucleotide alterations: Delving into the genome of paediatric cancer predisposition (#234)

Safaa Al Haj Hussein 1 2 , Dianne Sylvester 1 2 , Bhavna Padhye 1 2 3 , Noemi Fuentes-Bolanos 4 5 , Mark Pinese 5 , Meera Warby 5 6 , Eliza Courtney 4 5 , Macabe Daley 4 5 , Paulette Barahona 5 , Pamela Ajuyah 5 , Ann-Kristin Altekoester 5 , Sarah Josephi-Taylor 7 , Margaret Gleeson 8 9 , Dustin Hewett 3 , Geraldine O'Neill 1 2 , Katherine Tucker 4 , Tracey O’Brien 4 5 , Luciano Dalla-Pozza 3 , Yuyan Chen 1 2
  1. The Children's Hospital at Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
  2. Children's Cancer Research Unit, Kids Research, The Children's Hospital at Westmead, Sydney, NSW, Australia
  3. Cancer Centre for Children, The Children's Hospital at Westmead, Sydney, NSW, Australia
  4. Kids Cancer Centre, Sydney Children's Hospital, Sydney, NSW, Australia
  5. Children's Cancer Institute, Lowy Cancer Research Centre, University of NSW Sydney, Sydney, NSW, Australia
  6. Hereditary Cancer Centre, Nelune Comprehensive Cancer Centre, Prince of Wales Hospital, Randwick, NSW, Australia
  7. Clinical Genetics Department, The Children's Hospital at Westmead, Sydney, NSW, Australia
  8. Paediatric Oncology, John Hunter Children's Hospital, Newcastle, NSW , Australia
  9. Hunter Family Cancer Service, Waratah, NSW, Australia

Introduction: Germline alterations in cancer predisposition genes (CPGs) are associated with increased risk of developing certain cancers. Identification of the underlying germline genetic cause in childhood cancer patients can assist in personalised treatment, early detection/prevention, and facilitate appropriate clinical management for the family. The PREDICT study aims to identify germline alterations in patients (age < 21 years) newly diagnosed with cancer across NSW, together with their biological parents (trio analysis), using comprehensive whole genome sequencing (WGS) analysis.

Objective: My PhD project aims to establish bioinformatics pipelines to analyse PREDICT germline WGS data against a panel of approximately 1000 cancer-related genes to investigate genome regions beyond exonic small alterations. The pipelines will identify (1) single nucleotide variants (SNVs) and small insertions/deletions (indels), (2) canonical and non-canonical splicing variants, (3) structural variants (SVs)/copy number variations (CNVs), and (4) regulatory element variants.

Methods: In parallel with the clinical pipeline analysing known CPGs (<200 genes) using a commercial pipeline by the PREDICT team, development of multiple bioinformatics pipelines for research was conducted through my project, which enabled detection of different types of genomic alterations beyond exonic regions. Trio-based WGS data were run through established pipelines on The University of Sydney's High Performance Computing system, with analysis incorporating RStudio and online curation tools.

Results: Currently, 90 out of approximately 200 recruited patients have been analysed. Twenty-one clinically relevant pathogenic/likely pathogenic variants (e.g. PMS2, NF1) were detected in 19/90 (21.1%) patients, including 16 SNVs/small indels, 2 splicing variants and 3 CNVs. In addition, 24 novel candidate variants predicted to be deleterious were identified (including variants in promoter regions), which require validation.

Conclusions: Comprehensive WGS analysis has successfully identified known and novel germline alterations. Further characterisation of novel findings in those understudied regions of the genome may lead to discovery of novel variants/mechanisms of cancer predisposition and identification of novel genotype-phenotype associations.