Evidence map›Paper›PMID 42400790›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Mass Spectrometry-Based Validation of Chimeric RNAs.

Shafaque Zahra, Justin Elfman, Hui Li

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shafaque ZahraDepartment of Pathology, University of Virginia, Charlottesville, VA, USA.
Justin ElfmanDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA.
Hui LiDepartment of Pathology, School of Medicine, University of Virginia, Charlottesville, VA, USA. hl9r@virginia.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric RNAs, formed by the fusion of exons from two or more distinct genes, represent a significant class of noncanonical transcripts with increasing implications in cancer biology, development, and other biological processes. Their inherent novelty and the potential for sequence similarity with parental transcripts pose significant challenges for accurate detection and validation. While next-generation sequencing (NGS) has become the primary tool for chimeric RNA discovery, orthogonal validation methods are crucial to confirm their existence, delineate their precise structure, and quantify their abundance. Mass spectrometry (MS)-based approaches offer a powerful and complementary strategy for the robust validation of chimeric RNAs. This chapter will delve into the principles and applications of MS-based techniques for the definitive characterization of these fusion transcripts, highlighting their strengths in providing direct evidence of the chimeric junction at the peptide level, confirming the reading frame, and offering quantitative insights. We will explore various MS workflows, including targeted and untargeted peptidomics, and discuss the critical considerations for sample preparation, data acquisition, and bioinformatic analysis to ensure reliable and high-confidence validation of chimeric RNAs.

Indexed as

Gene FusionMass SpectrometryRNAComputational BiologyHigh-Throughput Nucleotide SequencingHumansRNAChimeric RNAFusion junctionFusion transcriptMass spectrometry (MS)Peptide validationProtein validationRNA sequencing (RNA-Seq)

Identifiers

PMID42400790

What Socratic holds

Textmetadata
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Registered trials

None linked

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 Socratic graph.