ArticlePloS one2022
Whole exome sequencing reveals novel risk genes of pituitary neuroendocrine tumors.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Genomic and Transcriptomic Landscapes of MEN1-Wild-Type Low-Grade Metastatic Pancreatic NETs Uncover Key Oncogenic Drivers and Targetable Pathways.International journal of biological sciences · 2026Article
- Whole genome sequencing and single-cell transcriptomics identify KMT2D inactivation as a potential new driver for pituitary tumors: a case report.BJC reports · 2025Article
- Transcriptome-Derived Ligand-Receptor Interactome of Major PitNET Subgroups.Journal of neurological surgery. Part B, Skull base · 2024Article
- Biomimetic composite hydrogel promotes new bone formation in rat bone defects through regulation of miR-19b-3p/WWP1 axis by loaded extracellular vesicles.Journal of nanobiotechnology · 2023Article
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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