Poster Presentation 29th Lorne Cancer Conference 2017

Cancer genetic mutation profiling in Cancer 2015 cohort (#292)

Huiling Xu 1 , So Young Moon 2 , David choong 1 , Christopher McEvoy 1 , Ravikiran Vedururu 1 , Stephen Wong 1 2 , Mark Lucas 3 , Ken Doig 4 , Christine Khoo 1 , Prue Allan 1 , Somatic Scientists 1 , Angela yc Tan 1 , Gareth Reid 1 , John McNeil 3 , David Ashley 5 , Ian Collins 4 , Theresa Hayes 4 , Lara Lipton 6 , Gary Richardson 7 , David Thomas 8 , Alex Dobrovic 9 , John Parisot 2 , Anthony Bell 1 , Andrew Fellowes 1 , Stephen B Fox 1
  1. Pathology, Peter MacCallum Cancer Centre, East Melbourne, VIC, Australia
  2. Cancer Research Division, Peter MacCallum Cancer Centre, East Melbourne, VIC, Australia
  3. Department of Epidemiology and Preventative Medicine, Alfred Centre, Monash University, Melbourne, Vic
  4. SouthWest Regional Cancer Centre (SWRCC), Warrnambool, Vic, Australia
  5. The Andrew Love Cancer Centre, Geelong Hospital, Barwon Health, Geelong, Vic, australia
  6. Peter MacCallum Cancer Centre, East Melbounre, VIC, Australia
  7. Department of Haematology & Oncology, Cabrini Institute, VIC, Australia, Malvern, VIC, Australia
  8. The Kinghorn Cancer Centre and Garvan Institute , Darlinghurst, NSW, Australia
  9. The Olivia Newton-John Cancer Research Institute, Heidelberg, Victoria, Australia

Cancer 2015 is a large-scale population-based cancer genomic cohort study. The cohort consists of approximately 3000 treatment-naïve cases including mainstream as well as rare solid tumour types with associate clinico-pathological data, treatment and follow-up of clinical outcomes (see Abstract #43219; http://www.cancer2015.org). To facilitate the identification of potential diagnostic, prognostic and predictive biomarkers, genetic mutations in common cancer genes were determined using targeted exon sequencing. To date, more than 50% specimens have been tested with a success rate of 78%. Depending on testing panels, variants of clinical relevance have been identified in approximately 39-68% of samples passed QC metric filters.

The prevalence of common mutations in mainstream cancers in the Cancer 2015 dataset tracks that in other publically available datasets in breast and colorectal cancer while noticeable difference was observed in lung adenocarcinoma and Head and Neck squamous cell carcinoma [1]. Likewise, comparison of mutational profiles in common cancer genes such as PIK3CA across different tumour types identified mutational hotspots which are preferentially associated with certain tumour types, suggesting new mechanisms underlying disease pathogenesis. TP53 remains the top mutated gene across all tumour types, with 34% cases harbouring TP53 mutations. In addition to known common cancer mutations, the study identified a number of novel mutations. Further investigation will provide new insight into the biological and clinical significance of these novel variants.

Cancer 2015 genomic dataset has two unique features: (1). Somatic variants identified in the cohort have been curated and interpreted in the context of the biological and clinical significance; (2). A collection of rare cancer types. These features provide a valuable resource for clinical and research applications. Cancer 2015 dataset is available to clinicians and researchers.

  1. Wong, S.Q., et al., Assessing the clinical value of targeted massively parallel sequencing in a longitudinal, prospective population-based study of cancer patients. Br J Cancer, 2015. 112(8): p. 1411-20.