Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

JUNB transcriptional regulation of KRT20 via ITGB1 activates PI3K/AKT signaling pathway against fibrosis-induced by renal injury.

Biology direct·2026

Same author

Impact of Different Delivery Modalities on Maternal and Neonatal Outcomes During Prolonged Deceleration in the Second Stage of Labor: A Retrospective Study.

International journal of women's health·2026

Same author

The G9a-TRIM21 axis exacerbates diabetic renal ischemia-reperfusion injury by inducing methylation-dependent ubiquitination and degradation of FoxO3a to promote oxidative stress and pyroptosis.

Redox biology·2025

Same author

The novel circular RNA circG6pc attenuates oxidative stress and mitochondrial damage through miR-7018-5p/Aldh6a1 axis in kidney fibrosis.

Cellular & molecular biology letters·2025

Same author

Silibinin mitigates AKI-to-CKD transition via MAPK and PI3K/AKT signaling pathways in Ischemia-Reperfusion injury.

Scientific reports·2025

Same author

Integrative Analysis of GEO Datasets and Mendelian Randomization Reveals a Potential Role ofISOC1 in Renal Cell Carcinoma.

Journal of Cancer·2025

Search research articles

Related Experiment Video

Updated: Jan 13, 2026

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

Published on: December 1, 2013

Machine Learning Integration Framework Constructs a Lactylation-Associated Gene Signature to Improve Prognosis in

Jingsong Wang^1,2, Qianxue Lu^1,2, Panpan Jiao^1,2

¹Department of Urology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.

Cancer Medicine

|January 8, 2026

Summary

Researchers identified an eight-gene signature linked to lactylation in bladder cancer. This signature predicts patient prognosis and response to immunotherapy, offering new targets for precision therapy.

Keywords:

bladder cancer lactylation machine learning integration prognosis

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Related Experiment Videos

Last Updated: Jan 13, 2026

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

An Orthotopic Bladder Cancer Model for Gene Delivery Studies

Published on: December 1, 2013

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

Area of Science:

Oncology
Molecular Biology
Genomics

Background:

Bladder cancer presents significant challenges due to high recurrence and treatment resistance.
Limited therapeutic options necessitate novel approaches for patient management.

Purpose of the Study:

To identify a lactylation-associated gene signature for predicting bladder cancer prognosis.
To provide a basis for drug development and precision therapy in bladder cancer.

Main Methods:

Utilized RNA sequencing data from TCGA and GEO databases.
Employed a machine learning framework to identify an eight-gene prognostic signature.
Validated findings through in vitro experiments and the Human Protein Atlas.

Main Results:

An eight-gene signature accurately predicted patient outcomes, including survival and immunotherapy response.
Functional analyses elucidated mechanisms of lactylation-associated genes in cancer progression.
Knockdown of AHNAK inhibited bladder cancer cell proliferation and invasion while promoting apoptosis.

Conclusions:

Lactylation-associated genes serve as crucial prognostic markers in bladder cancer.
This gene signature offers potential therapeutic targets for personalized treatment strategies.
The findings support enhanced patient management and precision oncology in clinical practice.