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Transcriptomic analysis identifies a tumor subtype mRNA classifier for invasive non-functioning pituitary
Xinjie Bao1, Gengchao Wang2,3, Shan Yu2,3
1Department of Neurosurgery, Pituitary Center, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences (CAMS) & Peking Union Medical College (PUMC), Beijing 100730, PR China.
Identifying invasive non-functioning pituitary neuroendocrine tumors (NF-PitNETs) is crucial for treatment. Gene expression analysis revealed a molecular signature that accurately predicts tumor invasiveness, aiding surgical decisions and patient prognosis.
Area of Science:
- Endocrinology
- Oncology
- Genomics
Background:
- Invasive non-functioning pituitary neuroendocrine tumors (NF-PitNETs) complicate surgical resection and indicate a poor prognosis.
- Reliable diagnostic tools are needed to guide surgical decisions and follow-up treatment for invasive PitNETs.
Purpose of the Study:
- To identify molecular markers for predicting the invasiveness of NF-PitNETs.
- To develop a diagnostic tool for assessing invasive PitNET potential.
Main Methods:
- Differential gene expression profiling using high-throughput sequencing in 61 NF-PitNET samples.
- Validation of 21 transcripts by Taqman-qPCR in 143 NF-PitNET samples.
- Analysis of histological expression and serum-exosomal mRNA of candidate genes.
Main Results:
- Distinct gene expression profiles were observed between non-invasive and invasive NF-PitNETs.
- A gene signature enriched in 'Pathways in cancers' and 'MAPK pathway' was associated with invasiveness.
- A gene-subtype panel achieved 80.00-90.24% diagnostic accuracy for NF-PitNET invasiveness.
Conclusions:
- New molecular characteristics of invasive NF-PitNETs have been defined.
- This approach represents a significant clinical advance in the diagnostics of invasive PitNETs.
- Identified markers can help identify patients at risk for invasive NF-PitNET.
