Through whole genome sequencing, the DNA of normal cells was compared with the DNA of cells from biopsies of pancreatic adenocarcinoma from three patients. An average of 132 billion mappable bases, or data points, was generated for each patient through next-generation sequencing. Then, 142 cellular genetic coding events were identified, including mutations, insertions and deletions, and chromosomal copy number variants.

“This study is the first to report whole genome sequencing findings in paired tumor/normal samples collected from (three) separate pancreatic adenocarcinoma patients,” said the study, which was a collaboration between the Translational Genomics Research Institute (TGen), Mayo Clinic in Arizona, and the Virginia G. Piper Cancer Center Clinical Trials at Scottsdale Healthcare.

The report found multiple potential therapeutic targets in all three case studies, which highlights the need to study the full spectrum of the genome. It also re-emphasizes the need to develop multiple avenues of therapeutics to match the specific medical challenges of each patient.

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“Cancer, and specifically here pancreatic cancer, is a highly complex disease that ultimately will require a variety of treatment methods to control, and ultimately to cure,” said Daniel Von Hoff, MD, FACP, TGen’s Physician-In-Chief, and Chief Scientific Officer for the Virginia G. Piper Cancer Center at Scottsdale Healthcare. He added, “This study shows that, as we continue to generate more information by sequencing the whole genomes of patients, we will continue to discover—with ever more confidence—the specific mechanisms that cause this cancer.”

For Patient 1 in the study, genes previously associated with pancreatic adenocarcinoma were identified, including BRCA1, TP53, CDKN2A, MYC, SMAD4, and KRAS. New discoveries included a deletion in exon 10 of BRCA2. These findings led to Patient 1 receiving multiple therapeutics, resulting in an initial complete response. Drug resistance developed after 6 months.

Whole genome sequencing of Patients 2 and 3 also uncovered multiple potential therapeutic targets. Further, RNA sequencing that analyzed the whole transcriptome revealed gene expression data that provided more information about likely affected biological processes. Analyzing the cellular pathways of all the sequencing data identified those processes that may be most heavily impacted by cellular and gene expression alterations.