Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors

Funding Information: This research was supported by the European Regional Development Fund (ERDF), Measure 1.1.1.1 “Industry-Driven Research” project „Molecular markers of pituitary tumour development, progression and therapy response” (Project No. 1.1.1.1/16/A/066, 2017). The authors acknowledge the Latvian Biomedical Research and Study Centre and the Genome Database of the Latvian Population for providing infrastructure, biological material and data. Publisher Copyright: © 2022 Peculis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Somatic genetic alterations in pituitary neuroendocrine tumors (PitNET) tissues have been identified in several studies, but detection of overlapping somatic PitNET candidate genes is rare. We sequenced and by employing multiple data analysis methods studied the exomes of 15 PitNET patients to improve discovery of novel factors involved in PitNET development. PitNET patients were recruited to the study before PitNET removal surgery. For each patient, two samples for DNA extraction were acquired: venous blood and PitNET tissue. Exome sequencing was performed using Illumina NexSeq 500 sequencer and data analyzed using two separate workflows and variant calling algorithms: GATK and Strelka2. A combination of two data analysis pipelines discovered 144 PitNET specific somatic variants (mean = 9.6, range 0–19 per PitNET) of which all were SNVs. Also, we detected previously known GNAS PitNET mutation and identified somatic variants in 11 genes, which have contained somatic variants in previous WES and WGS studies of PitNETs. Noteworthy, this is the third study detecting somatic variants in gene RYR1 in the exomes of PitNETs. In conclusion, we have identified two novel PitNET candidate genes (AC002519.6 and AHNAK) with recurrent somatic variants in our PitNET cohort and found 13 genes overlapping from previous PitNET studies that contain somatic variants. Our study demonstrated that the use of multiple sequencing data analysis pipelines can provide more accurate identification of somatic variants in PitNETs.Peer reviewe