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Splicing diversity enhances the molecular classification of pituitary neuroendocrine tumors.

Yue Huang1,2,3, Jing Guo4, Xueshuai Han1,2

  • 1China National Center for Bioinformation, Beijing, China.

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|February 11, 2025
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Summary

Alternative splicing (AS) patterns reveal new pituitary neuroendocrine tumor (PitNET) subtypes. This study identifies novel molecular markers for better PitNET classification and understanding tumor heterogeneity.

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Area of Science:

  • Endocrinology
  • Oncology
  • Molecular Biology

Background:

  • Pituitary neuroendocrine tumors (PitNETs) are common intracranial tumors with varied clinical presentations.
  • Current classification relies on hormone staining and transcription factors (TFs), which have limited resolution for tumor heterogeneity.
  • Alternative splicing (AS) offers a potential avenue to explore deeper molecular characteristics.

Purpose of the Study:

  • To comprehensively investigate alternative splicing (AS) dysregulation across all PitNET lineages.
  • To identify novel molecular markers for improved PitNET subtyping and understanding of tumor heterogeneity.
  • To delineate splicing heterogeneity at the single-cell level.

Main Methods:

  • Bulk and full-length single-cell RNA sequencing were employed.
  • Analysis focused on identifying and characterizing alternative splicing events in PitNETs.
  • Differential splicing analysis was performed across various PitNET subtypes.

Main Results:

  • Pervasive splicing dysregulations were identified, offering better depiction of tumor heterogeneity.
  • Fundamental splicing heterogeneity was confirmed at single-cell resolution.
  • A distinct TPIT lineage subtype was defined, associated with worse outcomes and increased splicing abnormalities linked to ESRP1 expression. The silent corticotroph subtype was also distinguished.

Conclusions:

  • The study characterizes the subtype-specific AS landscape in PitNETs.
  • Alternative splicing provides enhanced resolution for PitNET subtyping.
  • Findings contribute to a deeper understanding of PitNET molecular diversity and clinical outcomes.