Exploratory Small RNA Sequencing in Localized Versus Locally Advanced Prostate Cancer: Putative Roles of CLTC and CDK6 as Downstream Targets of Differentially Expressed MicroRNAs

Background/Objectives: Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men. While localized PCa carries a favorable prognosis, progression to locally advanced disease substantially worsens outcomes. There is an unmet need for molecular markers that reliably distinguish indolent from aggressive tumors. MicroRNAs (miRNAs), small non-coding RNAs that post-transcriptionally regulate gene expression, are implicated in cancer development and progression, and their expression profiles may serve as putative biomarkers of disease stage. Methods: We performed small RNA sequencing on formalin-fixed paraffin-embedded (FFPE) prostate tumor tissues from nine patients (five localized, four locally advanced-stage). Differentially expressed miRNAs were identified using a bioinformatics pipeline (fold-change ≥ 2, p < 0.05). Target gene prediction, KEGG pathway enrichment, and miRNA–mRNA interaction network analyses were conducted, followed by in silico validation using two independent public mRNA datasets (GSE46602 and GSE21034, a subseries of GSE21032). Results: Seven unique mature miRNAs were differentially expressed between localized and locally advanced PCa. Five miRNAs (miR-145-5p, miR-205-5p, miR-206, miR-24-1-5p, and hsa-miR-3648) were downregulated in locally advanced tumors, while hsa-miR-625-3p and miR-324-5p were upregulated. Network analysis identified CLTC and CDK6 as putative downstream targets co-targeted by multiple downregulated miRNAs. Independent validation using GSE46602 and GSE21034 consistently demonstrated significantly higher expression of CLTC and CDK6 in locally advanced prostate cancer following Benjamini–Hochberg correction. Conclusions: This exploratory pilot analysis identified several miRNAs that differ between localized (pT2) and locally advanced (pT3–T4/N+) prostate cancer. Independent validation across two publicly available mRNA cohorts supports CLTC and CDK6 as candidate stage-associated genes. However, these findings remain hypothesis-generating and require validation in larger prospective cohorts together with functional confirmation before biomarker or therapeutic claims can be made.

Authors

Institutions

Publication Details

Journal
Pharmaceuticals
Published
2026-07-23
DOI
https://doi.org/10.3390/ph19081141
Primary Topic
MicroRNA in disease regulation
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploratory Small RNA Sequencing in Localized Versus Locally Advanced Prostate Cancer: Putative Roles of CLTC and CDK6 as Downstream Targets of Differentially Expressed MicroRNAs

Hui Ji Kim, Kwang Woo Lee, Jae Heon Kim, Seongho Ryu et al.
Pharmaceuticals
MicroRNA in disease regulation
article

Exploratory Small RNA Sequencing in Localized Versus Locally Advanced Prostate Cancer: Putative Roles of CLTC and CDK6 as Downstream Targets of Differentially Expressed MicroRNAs

Hui Ji Kim, Kwang Woo Lee, Jae Heon Kim, Seongho Ryu, Ahrim Moon, Ki Soo Lee, Miho Song, Yun‐Seob Song, Luis Alfonso Pefianco, Kevin Andrean, Soo Min Suh
article en

Abstract

Background/Objectives: Prostate cancer (PCa) remains a leading cause of cancer-related mortality in men. While localized PCa carries a favorable prognosis, progression to locally advanced disease substantially worsens outcomes. There is an unmet need for molecular markers that reliably distinguish indolent from aggressive tumors. MicroRNAs (miRNAs), small non-coding RNAs that post-transcriptionally regulate gene expression, are implicated in cancer development and progression, and their expression profiles may serve as putative biomarkers of disease stage. Methods: We performed small RNA sequencing on formalin-fixed paraffin-embedded (FFPE) prostate tumor tissues from nine patients (five localized, four locally advanced-stage). Differentially expressed miRNAs were identified using a bioinformatics pipeline (fold-change ≥ 2, p < 0.05). Target gene prediction, KEGG pathway enrichment, and miRNA–mRNA interaction network analyses were conducted, followed by in silico validation using two independent public mRNA datasets (GSE46602 and GSE21034, a subseries of GSE21032). Results: Seven unique mature miRNAs were differentially expressed between localized and locally advanced PCa. Five miRNAs (miR-145-5p, miR-205-5p, miR-206, miR-24-1-5p, and hsa-miR-3648) were downregulated in locally advanced tumors, while hsa-miR-625-3p and miR-324-5p were upregulated. Network analysis identified CLTC and CDK6 as putative downstream targets co-targeted by multiple downregulated miRNAs. Independent validation using GSE46602 and GSE21034 consistently demonstrated significantly higher expression of CLTC and CDK6 in locally advanced prostate cancer following Benjamini–Hochberg correction. Conclusions: This exploratory pilot analysis identified several miRNAs that differ between localized (pT2) and locally advanced (pT3–T4/N+) prostate cancer. Independent validation across two publicly available mRNA cohorts supports CLTC and CDK6 as candidate stage-associated genes. However, these findings remain hypothesis-generating and require validation in larger prospective cohorts together with functional confirmation before biomarker or therapeutic claims can be made.

PharmaceuticalsVol. 19(8)
Soonchunhyang University (KR), Soonchunhyang University Hospital Seoul (KR), Dong-A University (KR)
Ministry of Education, Science and Technology, Ministry of Science and ICT, South Korea
Good health and well-being
Openalex Percentile: Top 11%
MicroRNA in disease regulation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.