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lncRNA - Long Non-coding RNAs

lncRNA - Long Non-coding RNAs

In humans, more than 80% of the genome gets transcribed. However, only around 2% of the genome codes for proteins. The remaining part produces non-coding RNAs which includes ribosomal RNAs, transfer RNAs, telomerase RNAs, and regulatory RNAs, among other types. A large number of regulatory non-coding RNAs have been classified into two groups depending upon their length – small non-coding RNAs, such as microRNA, which are less than 200 nucleotides in length, and long non-coding RNA (lncRNA)...

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Updated: Jun 18, 2026

Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients

Sequencing Small Non-coding RNA from Formalin-fixed Tissues and Serum-derived Exosomes from Castration-resistant Prostate Cancer Patients

Published on: November 19, 2019

Novel biomarkers for prostate cancer including noncoding transcripts.

Tammy L Romanuik¹, Takeshi Ueda, Nhu Le

¹Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, Canada.

The American Journal of Pathology

|November 7, 2009

Summary

This summary is machine-generated.

Researchers identified 27 novel gene transcripts as potential prostate cancer biomarkers. Several transcripts showed differential expression in malignant versus benign prostate tissues, aiding in diagnosis and prognosis.

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miRNA Expression Analyses in Prostate Cancer Clinical Tissues

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Area of Science:

Oncology
Molecular Biology
Biomarker Discovery

Background:

Prostate cancer diagnosis and prognosis rely on accurate biomarkers.
Identifying novel molecular markers is crucial for improving patient outcomes.

Purpose of the Study:

To investigate 27 novel transcripts as potential biomarkers for prostate cancer.
To assess the expression patterns and clinical relevance of these transcripts.

Main Methods:

Analysis of 27 transcripts, including plasma membrane, secreted, intracellular, and noncoding RNAs.
Differential expression analysis between malignant and benign prostate tissues.
Correlation of transcript levels with clinical parameters and disease progression.

Main Results:

POP3 expression was prostate-specific; ADAM2, POP1, POP4, POP10, ELOVL5, RAMP1, and SPON2 showed limited tissue expression.
Significant differential expression was observed for ELOVL5, MARCKSL1, NGFRAP1, PGK1, POP2, POP5, POP8, PSMA7, RAMP1, and SPON2 in malignant vs. benign tissues.
Specific transcripts (CAMK2N1, GLO1, SDBS, TMEM30A) increased in primary tumors predicting biochemical failure; others (GLO1, DHCR24, NGFRAP1, KLK3, RAMP1) decreased in metastatic disease.

Conclusions:

The investigated transcripts show promise as novel biomarkers for prostate cancer diagnosis and prognosis.
Differential expression patterns correlate with disease state and progression.
Further validation is warranted to establish their clinical utility.