Oncology clinic-based germline genetic testing for exocrine pancreatic cancer enables timely return of results and unveils low uptake of cascade testing

BackgroundTraditional medical genetics models are unable to meet the growing demand for germline genetic testing (GT) in patients with exocrine pancreatic cancer (PC). This study investigates the impact of an ambulatory oncology clinic-based GT model.MethodsFrom 2012 to 2021, patients with PC were prospectively enrolled and considered for GT. Two chronological cohorts were compared: (1) the preuniversal genetic testing (pre-UGT) cohort, which received GT based on clinical criteria or family history; and (2) the post-UGT cohort, where an 86-gene panel was offered to all patients with PC.ResultsOf 847 eligible patients, 735 (86.8%) were enrolled (pre-UGT, n=579; post-UGT, n=156). A higher proportion of the post-UGT cohort received prospective GT (97.4% vs 58.5%, p<0.001). The rate of pathogenic germline alterations (PGA) across both cohorts was 9.9%, with 8.0% of PGAs in PC susceptibility genes. The post-UGT cohort had a higher prevalence of overall PGAs (17.2% vs 6.6%, p<0.001) and PGAs in PC susceptibility genes (11.9% vs 6.3%, p<0.001). The median turnaround time from enrolment to GT report was shorter in the post-UGT cohort (13 days vs 42 days, p<0.001). Probands with a PGA disclosed their GT results to 84% of their first-degree relatives (FDRs). However, only 31% of informed FDRs underwent GT, and the number of new cases per index case was 0.52.ConclusionA point-of-care GT model is feasible and expedites access to GT for patients with PC. Strategies to increase the uptake of cascade testing are needed to maximise the clinical impact of an oncology clinic-based GT model.

Merging Genomics Public Datasets with Clinical Cancer Registry Data – Lessons Learned

Publicly available datasets – for example via cBioPortal for Cancer Genomics – could be a valuable source for benchmarks and comparisons with local patient records. However, such an approach is only valid if patient cohorts are comparable to each other and if the documentation is complete and sufficient. In this paper, records from exocrine pancreatic cancer patients documented in a local cancer registry are compared with two public datasets to calculate overall survival. Several data preprocessing steps were necessary to ensure comparability of the different datasets and a common database schema was created. Our assumption that the public datasets could be used to augment the data of the local cancer registry could not be validated, since the analysis on overall survival showed a significant difference. We discuss several reasons and explanations for this finding. So far, comparing different datasets with each other and drawing medical conclusions on such comparisons should be conducted with great caution.