ReviewFrontiers in medicine2025
The evolution and application of multi-omic analysis for pituitary neuroendocrine tumors.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- A stacking model for AI-assisted diagnosis of suspected pituitary microadenomas on non-contrast T1COR MRI: a multicenter reader study on bridging the experience gap.Neuroradiology · 2026Article
- Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.Molecular brain · 2026Review
- A multicenter-validated interpretable transformer model for pituitary microadenoma detection on non-contrast multiparametric MRI.BMC medical imaging · 2026Article
- Metabolomics identifies candidate diagnostic biomarkers for pituitary apoplexy.Frontiers in endocrinology · 2026Article
- Proteoformics-driven new concept of human growth hormone in clinical endocrinology.Frontiers in endocrinology · 2026Review
- The metastatic spectrum in functional and non-functional NENs: mechanistic insights from multi-omics.Frontiers in endocrinology · 2026Review
- Targeting lineage-specific heterogeneity and hypovascular-fibrotic barriers may enable precision immunotherapy in pituitary neuroendocrine tumors.Frontiers in immunology · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pituitary neuroendocrine tumors (PitNETs) are a heterogeneous group of intracranial neoplasms that vary in hormonal activity, histological features, and clinical behavior. The rise of high-throughput sequencing and molecular profiling technologies has enabled multiomic approaches-including genomics, transcriptomics, epigenomics, proteomics, and metabolomics-to deepen our understanding of PitNET pathogenesis. These studies have identified key mutations, transcriptional lineages, epigenetic modifications, and proteomic features that contribute to tumor subtype classification, invasiveness, and treatment response. Integrative multi-omic analyses have further revealed distinct molecular subtypes, complex regulatory networks, and molecular profiles that can predict recurrence and therapeutic efficacy. These approaches hold strong potential for advancing personalized medicine in PitNETs, supporting patient-specific diagnosis, prognostication, and therapeutic strategies. Future directions include the application of emerging -omic technologies and the development of robust computational tools to integrate and translate multi-layered data into clinically actionable insights.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.