Demonstration of Temporal Heterogeneity Identified By Genome Sequencing and the Potential Effect on Treatment Decisions for Advanced Cancer Patients

Abstract

ABSTRACT Aim: Tumour heterogeneity poses a significant challenge to the success of treatment; tumours with similar histological features may have substantially different biological drivers. This analysis is part of a study in which we use whole genome and transcriptome sequencing to aid in therapeutic decision-making in patients (pts) with advanced cancers. Analysis of tumours at different time points is an integral feature to our study design. Methods: Eligible pts with incurable cancers with limited or no standard chemotherapy options, have several samples analyzed: a fresh tumour biopsy; a blood sample for normal comparison; and archival tumours if available. Samples undergo comprehensive DNA (40X-80X) and RNA sequencing (fresh biopsy) and in-depth bioinformatic analysis to identify somatic mutations, copy number alterations, structural rearrangements, and corresponding gene expression changes that may provide informative (diagnostic) or actionable targets. Results: Between July 2012- May 2014, 80 pts have consented, representing 28 different tumour types. Median number of lines of chemo prior to sequencing was 3. Of the 51 pts analyzed, 21 have matched archival and fresh biopsy material. Typically the archival material is from the primary and the fresh tissue is from a metastatic site. We compared the genetic variants between the primary tumors and metastases, and those identified in both samples. The number of shared non-synonymous single nucleotide variants (SNV) between the archival and fresh samples varied considerably from 0 to 117 with the most overlap observed in the 3 colorectal cancer pts. In the pts with no shared SNV, germline variants, copy number profiles and other variants clearly demonstrated the metastatic biopsy was from the same primary. Non-synonymous SNV were detected in individual pt DNA in both the fresh biopsy (range 21-423) and the archival (range 7-338). These included actionable variants in genes such as KRAS, TP53 and BRCA2. There was the suggestion that some genes may be more stable over time (TP53). Conclusions: Our data demonstrates the large and variable heterogeneity of advanced cancer when compared to archival samples. This included important actionable and druggable targets that would influence treatment decisions. This highlights the importance of repeat biopsies to guide treatment decisions wherever possible. Disclosure: All authors have declared no conflicts of interest.