Poster Presentation 35th Lorne Cancer Conference 2023

Whole genome and transcriptome sequencing to support diagnostic classification of challenging cancers: The COLUMN-Pathologist-Initiated study. (#344)

Joseph H.A. Vissers 1 2 , Wing-Yee Lo 1 , Tran Pham 1 , Oliver Hofmann 1 , Stephen Fox 2 , Sean Grimmond 1 , Owen Prall 2 , Catherine Mitchell 2
  1. Centre for Cancer Research and Dept of Clinical Pathology, University of Melbourne, Melbourne, VIC, Australia
  2. Dept of Pathology, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia

Despite advances in cancer pathology, defining the diagnostic classification of some cancers remains a significant challenge. Examples include dedifferentiated tumours, tumours occurring in clinically unusual scenarios and tumours belonging to rare or recently identified classes. This presents a barrier to optimal care as cancer management and treatment is typically streamed by the diagnosis.

Standard diagnostic work up of cancer tissues involves histological examination, immunohistochemical staining, and other microscopy-based approaches. However, there is a growing appreciation that the genetic alterations in tumours are also diagnostically informative. Examples are tumour type-specific combinations of driver mutations, mutational burden and signatures.

The Cancer Of Low sUrvival and unMet Need (COLUMN) initiative is a flagship project of The Advanced Genomics Collaboration between the University of Melbourne and Illumina (https://www.tagcaustralia.com/). COLUMN aims to support comprehensive genomic testing by whole genome and transcriptome sequencing (WGTS) of 1000 challenging patients. The COLUMN-Pathologist-Initiated sub study leverages this opportunity to test the utility of WGTS in informing diagnosis of tumours for which the primary site is known but that are difficult to classify. Uniquely, WGTS testing is initiated by pathologists rather than treating clinicians, reflecting the focus on diagnostic utility rather than identification of treatment targets for precision oncology.

A total of 45 samples from 43 patients have been successfully sequenced to date, of which 7 failed due to poor sample quality or tissue cellularity (77% technical success rate). Cases that met selection criteria fell into 4 distinct categories, based on tumour histology and origin. WGTS fully elucidated diagnosis in 23 cases (62%), identified a rare, or potential novel diagnostic class in 4 cases (11%), or supported exclusion of possible diagnoses in 8 cases (22%). WGTS was not diagnostically informative in only 2 cases (5%). Other benefits included identification of therapeutic targets in 8 cases, and reportable germline variants in 2 cases.

In conclusion, WGTS is a powerful approach to improve classification of diagnostic conundrums in cancer pathology.