Discovery of RNA Biomarkers for Prostate Cancer Using Cross-Platform Transcriptomics

Microarray and Single-Molecule Molecular Inversion Probe (smMIP)-based targeted RNA sequencing are two RNA profiling platforms for identifying disease-associated biomarkers. The microarray uses a GeneChip array with oligonucleotide probes to measure expression levels across thousands of genes, while smMIPs capture and quantify RNA transcripts and transcript variants via next-generation sequencing. To evaluate the strengths and weaknesses of both platforms, a comparative gene expression profiling study was conducted using RNA samples from 52 prostate tissues (normal, benign prostatic hyperplasia (BPH) and various prostate cancer (PCa) grades). Of all genes covered by both platforms, only 35% of the expression levels aligned, with 45% showing discrepancies. Both platforms identified the same 17 genes as potential PCa biomarkers. Microarray analysis identified an additional 253 genes that were not covered or not identified by smMIP technology, while smMIP technology identified eight markers not covered or not identified in the microarray core gene analysis, including fusion genes and splice variants. For high-grade prostate cancer (HG-PCa), the smMIP-method identified 8 markers, and the microarray identified 17 markers, with <i>FOLH1, FAP</i> and <i>CLDN3</i> being common across both platforms. The choice of RNA expression analysis technology depends on research objectives; microarray technology is useful for the evaluation of a wide range of genes but has low throughput. In contrast, smMIP-based RNA sequencing enables sensitive analysis with minimal RNA in a medium- to high-throughput setting.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-11-06
DOI
https://doi.org/10.3390/ijms252211907
Citations
2
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.47
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article

Discovery of RNA Biomarkers for Prostate Cancer Using Cross-Platform Transcriptomics

Willem J. G. Melchers, Wieke C. H. Visser, Hans de Jong, William P. J. Leenders et al.
2 citations
International Journal of Molecular Sciences
Molecular Biology Techniques and Applications
0.47
article

Discovery of RNA Biomarkers for Prostate Cancer Using Cross-Platform Transcriptomics

Willem J. G. Melchers, Wieke C. H. Visser, Hans de Jong, William P. J. Leenders, Jason C. Poole, Jack A. Schalken, Peter F.A. Mulders, Jolly Shrivastava, Frank Smit
article en
2 citations

Abstract

Microarray and Single-Molecule Molecular Inversion Probe (smMIP)-based targeted RNA sequencing are two RNA profiling platforms for identifying disease-associated biomarkers. The microarray uses a GeneChip array with oligonucleotide probes to measure expression levels across thousands of genes, while smMIPs capture and quantify RNA transcripts and transcript variants via next-generation sequencing. To evaluate the strengths and weaknesses of both platforms, a comparative gene expression profiling study was conducted using RNA samples from 52 prostate tissues (normal, benign prostatic hyperplasia (BPH) and various prostate cancer (PCa) grades). Of all genes covered by both platforms, only 35% of the expression levels aligned, with 45% showing discrepancies. Both platforms identified the same 17 genes as potential PCa biomarkers. Microarray analysis identified an additional 253 genes that were not covered or not identified by smMIP technology, while smMIP technology identified eight markers not covered or not identified in the microarray core gene analysis, including fusion genes and splice variants. For high-grade prostate cancer (HG-PCa), the smMIP-method identified 8 markers, and the microarray identified 17 markers, with <i>FOLH1, FAP</i> and <i>CLDN3</i> being common across both platforms. The choice of RNA expression analysis technology depends on research objectives; microarray technology is useful for the evaluation of a wide range of genes but has low throughput. In contrast, smMIP-based RNA sequencing enables sensitive analysis with minimal RNA in a medium- to high-throughput setting.

International Journal of Molecular SciencesVol. 25(22)
Radboud University Nijmegen (NL), University Medical Center (US), Radboud University Medical Center (NL), MDxHealth (Netherlands) (NL)
Good health and well-being
Openalex Percentile: Top 34%
Molecular Biology Techniques and Applications
0.47
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