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From Splicing to Survival: Understanding the Molecular Basis of Prognostic Differences in advanced Small Intestine Neuroendocrine Tumors

Created on 26 Oct 2026

Abstract

Small intestine neuroendocrine tumors (SI-NETs) represent a challenging neoplasm due to their high rate of metastasis and the limited availability of effective therapies. Recent evidence has unveiled altered splicing as an influential player in tumor progression, linked to patient prognosis, which provides a powerful source of novel biomarkers and therapeutic targets in cancer. Here, we conducted a comprehensive analysis regarding the possible connection of the spliceosomic landscape of metastatic SI-NETs with patient survival. Initial analyses revealed a distinctive pattern of splicing events between the two conditions, short (< 5 years, n = 17 patients), vs. long survival ([≥] 5 years, n = 26 patients), with strong discrimination capacity. Furthermore, numerous key splicing events were associated with relevant clinical parameters in SI-NETs. The observed impairments in spliceosomic parameters led us to interrogate the integrity of the splicing machinery. This revealed striking changes in the expression of a high proportion of core spliceosome components and splicing factors between short vs. longsurvival groups, suggesting a possible mechanistic link with the distinct profile of splicing events observed. Among them, CPSF2, a core component of the CPSF complex, stands out as its higher expression is associated with worse survival and vascular and perineural invasion. Interestingly, the shifts potentially generated by this factor supported a possible role in tumor plasticity oriented to higher tumor aggressiveness and treatment resistance. In sum, this study offers the first detailed snapshot of the status of the spliceosomic landscape in SI-NETs and its molecular linkage to patient survival, thus offering a new window towards identification of novel candidate biomarkers and/or therapeutic targets.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 26 Oct 2026.

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