Small-cell neuroendocrine carcinoma (SCNC) is a rare but highly malignant tumor subtype that primarily arises in the lung, also rarely in other organs, and as a consequence of treatment induced lineage transdifferentiation of prostate adenocarcinomas. The molecular convergence of SCNC across diverse tissues enables its identification through conserved SCNC-specific molecular markers, facilitating tumor subtype classification. As a critical post-transcriptional regulatory mechanism, alternative polyadenylation (APA) modulates 3'UTR length and significantly impacts tumor progression. However, its role in SCNC remains largely unclear. Here, we report a global 3'UTR lengthening pattern driven by APA in SCNC. We identified a set of conserved 3'UTR lengthening events across SCNCs of different tissue origins, which are strongly associated with neural development and related signaling pathways. Furthermore, we developed a neural network-based prediction model to classify SCNC by leveraging these specific APA signatures. Our study provides new insights into the post-transcriptional landscape of SCNCs and highlights APA signatures as promising biomarkers for SCNC identification.
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Zhang et al. (Wed,) studied this question.
synapsesocial.com/papers/69a75da3c6e9836116a27d2b — DOI: https://doi.org/10.64898/2026.01.26.701900
Yi Zhang
Xiaofan Zhao
Oregon Health & Science University
Huan Wang
University of Washington
University of Michigan
Oregon Health & Science University
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