Evidence map›Paper›PMID 42793173›Full record

ArticleBiomolecules2026

Identification of Novel Transcriptional Alleles in Primary Prostate Cancer Cells and Cancer Stem Cells by Bulk RNA-Seq and Single-Cell RNA-Seq Analyses.

Wen-Yang Hu, Ranli Lu, Mark Maienschein-Cline, Duoling Xu, Parivash Afradiasbagharani, Lynn A Birch, Larisa Nonn, Andre Kajdacsy-Balla, Toshi Shioda, Gail S Prins

Abstract read
In one paragraph

Article in Biomolecules, 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

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

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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

10 authors.

Wen-Yang HuDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.ORCID 0000-0001-7811-2078
Ranli LuDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.ORCID 0000-0002-7629-2818
Mark Maienschein-ClineResearch Resources Center, Office of the Vice Chancellor for Research, University of Illinois Chicago, Chicago, IL 60612, USA.
Duoling XuDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.
Parivash AfradiasbagharaniDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.ORCID 0000-0003-3212-3155
Lynn A BirchDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.ORCID 0000-0003-1153-625X
Larisa NonnDepartment of Pathology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.
Andre Kajdacsy-BallaDepartment of Pathology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.
Toshi ShiodaCenter for Cancer Research, Massachusetts General Hospital, Harvard Medical School, Charlestown, Boston, MA 02129, USA.
Gail S PrinsDepartment of Urology, College of Medicine, University of Illinois Chicago, Chicago, IL 60612, USA.ORCID 0000-0002-9044-4734

Funding

United States Department of Defense PC180408
6 · The paper itself

Abstract

Genetic alterations are closely associated with prostate cancer development and progression, but the RNA-derived transcriptional allele landscape of prostate cancer and cancer stem cells (CSCs) remains poorly understood. To characterize cancer-associated transcriptional alleles, we analyzed bulk and single-cell RNA sequencing (RNA-seq) data from primary human prostate cancer cells and their matched benign epithelial cells from non-cancerous regions of the same patients. Sequencing reads were aligned to the human reference genome (hg38) using STAR, and sequence variants were annotated with ANNOVAR. Most detected transcriptional alleles were located in noncoding regions, particularly within 3' and 5' untranslated regions, with single-nucleotide variants predominating and C>T substitutions occurring most frequently. Comparison of cancer and matched benign samples identified 223 genes carrying cancer-associated transcriptional alleles consistently detected across three independent patients. Seven of these genes showed differential expression between CSC and non-CSC populations, while 19 contained non-synonymous alleles, including 11 that are predicted to have potentially damaging effects. We identified ATF6 and KDM3A as candidate genes of potential functional interest. Single-cell RNA-seq analyses revealed differences in the number and distribution of detected transcriptional alleles between culture conditions, with 2D cancer cultures detecting more total, coding, and non-synonymous alleles than CSC-enriched 3D spheroids. CSC populations also exhibited fewer detected transcriptional alleles than non-CSC populations. Our findings provide a framework for characterizing transcriptional allele heterogeneity within the prostate cancer cellular hierarchy and identify candidate CSC-associated alterations for further investigation and functional validation. Finally, the cancer-benign matched strategy used in this study provides additional molecular evidence supporting the malignant origin of the tumor-derived cancer cells.

Indexed as

AllelesNeoplastic Stem CellsProstatic NeoplasmsRNA-SeqTranscription, GeneticGene Expression Regulation, NeoplasticHumansMalePolymorphism, Single NucleotideSingle-Cell AnalysisSingle-Cell Gene Expression Analysiscancer stem cellsprostate cancerRNA-seqsingle-cell analysissomatic mutation

Identifiers

PMID42793173
PMCPMC13604742

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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.