Signatures of micropeptides encoded by lncRNAs in cancer progression and metastasis

Abstract Background Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Although traditionally considered non-coding, 21% of the ~190,000 annotated lncRNA transcripts contain poorly characterized open reading frames with unknown function. Methods We systematically identified lncRNAs encoding micropeptides (MPs) using integrated computational and experimental evidence. Expression profiles across 17 cancer types from The Cancer Genome Atlas (TCGA) were analyzed to identify cancer-associated and transitional lncRNAs (Tr-lncRNAs). Structural modeling using AlphaFold was further applied to predict folding. Results We identified 478 lncRNA genes encoding 1782 MPs (10–100 amino acids). These MPs exhibit distinct amino acid and dipeptide compositions and are enriched for specific 4-mer motifs compared with canonical proteins. A subset of lncRNAs, including TNN-AS1, PVT1, XIST, and SNHG family members, encode multiple MPs. Analysis across cancer stages identified 2399 Tr-lncRNAs, most of them were cancer type and stage specific. Among these, 314 highly confident MPs from 72 Tr-lncRNAs were further analyzed. Pan-cancer analysis suggested MP-like functions for Tr-lncRNAs such as LINC01234, HAND2-AS1, XIST, UCA1, and HOXA11-AS. While most MPs are predicted to be intrinsically disordered, 3D structural modeling revealed several MPs with stable folds, including ubiquitin-like and RNase H-like structures. Conclusions Tr-lncRNA–derived MPs represent a previously underexplored class of potentially functional molecules associated with cancer clinical annotation and may serve as biomarkers for disease progression.

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Publication Details

Journal
British Journal of Cancer
Published
2026-07-27
DOI
https://doi.org/10.1038/s41416-026-03556-1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.00

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article

Signatures of micropeptides encoded by lncRNAs in cancer progression and metastasis

Michal Linial, Stav Zok
British Journal of Cancer
Cancer-related molecular mechanisms research
article

Signatures of micropeptides encoded by lncRNAs in cancer progression and metastasis

Michal Linial, Stav Zok
article en

Abstract

Abstract Background Long non-coding RNAs (lncRNAs) regulate gene expression, chromatin organization, and cellular signaling. Although traditionally considered non-coding, 21% of the ~190,000 annotated lncRNA transcripts contain poorly characterized open reading frames with unknown function. Methods We systematically identified lncRNAs encoding micropeptides (MPs) using integrated computational and experimental evidence. Expression profiles across 17 cancer types from The Cancer Genome Atlas (TCGA) were analyzed to identify cancer-associated and transitional lncRNAs (Tr-lncRNAs). Structural modeling using AlphaFold was further applied to predict folding. Results We identified 478 lncRNA genes encoding 1782 MPs (10–100 amino acids). These MPs exhibit distinct amino acid and dipeptide compositions and are enriched for specific 4-mer motifs compared with canonical proteins. A subset of lncRNAs, including TNN-AS1, PVT1, XIST, and SNHG family members, encode multiple MPs. Analysis across cancer stages identified 2399 Tr-lncRNAs, most of them were cancer type and stage specific. Among these, 314 highly confident MPs from 72 Tr-lncRNAs were further analyzed. Pan-cancer analysis suggested MP-like functions for Tr-lncRNAs such as LINC01234, HAND2-AS1, XIST, UCA1, and HOXA11-AS. While most MPs are predicted to be intrinsically disordered, 3D structural modeling revealed several MPs with stable folds, including ubiquitin-like and RNase H-like structures. Conclusions Tr-lncRNA–derived MPs represent a previously underexplored class of potentially functional molecules associated with cancer clinical annotation and may serve as biomarkers for disease progression.

British Journal of Cancer
Hebrew University of Jerusalem (IL)
Weizmann Institute of Science
Openalex Percentile: Top 100%
Cancer-related molecular mechanisms research
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