Evidence mapPaperPMID 40861865Full record

ArticleTargets (Basel)2025

Approaches for Identifying LncRNA-Associated Proteins for Therapeutic Targets and Cancer Biomarker Discovery.

Mohammad Shabir Hussain, Puneet Vij, Sudhir Kotnala, Shadab Ahmad, Subhash C Chauhan, Manish K Tripathi

Abstract read
In one paragraph

Article in Targets (Basel), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Mohammad Shabir HussainMedicine and Oncology ISU, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.ORCID 0000-0002-5349-1136
Puneet VijDepartment of Pharmaceutical Sciences, St. John's University, Queens, NY 11439, USA.ORCID 0000-0003-2155-6254
Sudhir KotnalaMedicine and Oncology ISU, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.ORCID 0000-0001-7070-532X
Shadab AhmadCentre for Cellular and Molecular Platforms (C-CAMP), GKVK Post, Bellary Rd, Bengaluru 560065, Karnataka, India.
Subhash C ChauhanMedicine and Oncology ISU, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.
Manish K TripathiMedicine and Oncology ISU, School of Medicine, The University of Texas Rio Grande Valley, McAllen, TX 78504, USA.ORCID 0000-0002-9959-8668

Funding

Role of lncRNA UCA1 in anoikis resistantce and colorectal cancer metastasisR16GM146696 · NIGMS · UNIVERSITY OF TEXAS RIO GRANDE VALLEY · PI TRIPATHI, MANISH K · 2022 to 2025
$740k
NIGMS NIH HHS R16 GM146696
6 · The paper itself

Abstract

Long non-coding RNAs (lncRNAs) are increasingly recognized as key regulators of gene expression and cellular signaling in cancer. Their functions are primarily mediated through interactions with specific protein partners that modulate chromatin structure, epigenetic remodeling, transcription, and signal transduction. In this review, we explore reports and strategies for the proteomic characterization of lncRNA-associated proteins, particularly emphasizing high-throughput liquid chromatography-mass spectrometry (LC-MS)-based techniques. Affinity-based methods such as RNA pull-down, ChIRP MS, RAP-MS, BioID-MS, and SILAC-MS enable sensitive and specific mapping of lncRNA and protein complexes. These approaches reveal cancer-specific proteomic signatures, post-translational modifications, and mechanistic insights into tumor biology. The use of label-free quantification, bituminization, and crosslinking strategies further enhances the resolution of dynamic RNA-protein networks. Validation tools following bioinformatic analyses, such as Western blotting, immunohistochemistry, immunofluorescence, and ELISA, are used to prioritize and confirm findings. Candidate biomarkers from hepatocellular carcinoma to colorectal and prostate cancers, profiling lncRNA-associated proteins, hold promise for identifying clinically actionable biomarkers and therapeutic targets. This review highlights the translational relevance of lncRNA protein studies and advocates for their broader adoption in oncological research. In LC-MS workflows, proteins bound to lncRNAs are enzymatically digested into peptides, separated via nano-LC, and analyzed using high-resolution tandem MS. Label-free or isotope-labeled methods quantify differential enrichment, followed by bioinformatics-driven pathway annotation.

Indexed as

cancer biomarkersLC–mass spectrometrylong non-coding RNAs (LncRNAs)protein interactionsproteomicstherapeutic targets

Identifiers

PMID40861865
PMCPMC12377401

What Socratic holds

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LicenceCC BY
Read underepoch 390

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.