Evidence map›Paper›PMID 42134687›Full record

ArticleMolecular & cellular proteomics : MCP2026

A Proteogenomic Approach to Discover Novel lncRNA-Derived Microproteins and Their Potential Clinical Utility in Hepatocellular Carcinoma.

Bingwu Li, Kandarp Joshi, Dan Ohtan Wang

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Bingwu LiBiology Program, Division of Science, New York University Abu Dhabi, Abu Dhabi, UAE.
Kandarp JoshiDepartment of Oncology, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Johns Hopkins All Children's Hospital, St Petersburg, Florida, USA.
Dan Ohtan WangBiology Program, Division of Science, New York University Abu Dhabi, Abu Dhabi, UAE. Electronic address: ohtan.wang@nyu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microproteins (i.e., peptides) are increasingly recognized for their functions in versatile biological contexts, but their clinical relevance and utility remain largely unexplored. Proteogenomic approaches can accelerate microprotein discovery in clinical samples by integrating proteomic data with genomics and transcriptomics evidence. However, long noncoding RNA (lncRNA)-derived microproteins (lncPeps) remain largely unidentified, resulting in unmatchable MS/MS spectra. To solve this problem, we have used high-quality Ribo-seq translatomic datasets to generate an extensive database of human liver lncRNA-derived open reading frames (lncORFs), which we subsequently applied to proteomics data of tumor-adjacent normal tissue pairs from hepatocellular carcinoma (HCC) patients. Using the new database, we discovered 104 novel lncPeps, including 46 lncPeps differentially expressed between tumor and nontumor tissues, and 13 lncPeps with significant correlation with prognosis. Remarkably, combining the expression of lncPeps with canonical proteins in a LASSO regression model improved predictive performance for recurrence, increasing the AUC by 0.005 to 0.085 across three recurrence time points. These findings suggest that the discovery of lncPeps contributes to our understanding of the molecular heterogeneity and progression of HCC and broadens the range of potential biomarker candidates and treatment targets for the disease.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsProteogenomicsRNA, Long NoncodingBiomarkers, TumorGene Expression Regulation, NeoplasticHumansMicropeptidesOpen Reading FramesPrognosisBiomarkers, TumorMicropeptidesRNA, Long NoncodingBiomarkerHCClncPepproteogenomic

Identifiers

PMID42134687
PMCPMC13272525

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Registered trials

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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 OpenQuestion graph.