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Non-LTR Retrotransposons

Non-LTR Retrotransposons

As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...

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Plasma-based transcriptomic non-coding signature for predicting relapse in pediatric acute lymphoblastic leukemia.

Yaping Wang¹, Xiaopeng Ma¹, Huimin Li¹

¹Department of Hematology and Oncology, Children's Hospital of Nanjing Medical University, Nanjing Medical University, 72# Guangzhou Road, Nanjing, Jiangsu Province, China.

|January 6, 2025

Summary

A new blood test using non-coding RNAs can predict relapse in children with Acute Lymphoblastic Leukemia (ALL) at diagnosis. This non-invasive method aids in early risk stratification for better patient outcomes.

Keywords:

Fingerprint Leukemia MRD Recurrence Risk score

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Comprehensive Protocol to Sample and Process Bone Marrow for Measuring Measurable Residual Disease and Leukemic Stem Cells in Acute Myeloid Leukemia

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Area of Science:

Pediatric Hematology
Oncology
Molecular Diagnostics

Background:

Pediatric Acute Lymphoblastic Leukemia (ALL) relapse significantly impacts prognosis.
Current relapse prediction methods have limitations.
Need for non-invasive, early diagnostic tools in pediatric ALL.

Purpose of the Study:

Develop a blood-based, non-invasive method for predicting ALL relapse in children.
Identify novel non-coding RNA biomarkers for relapse prediction.
Create a risk stratification model incorporating these biomarkers.

Main Methods:

Analysis of two pediatric ALL patient cohorts.
High-throughput profiling to identify miRNA and circRNA expression.
Logistic regression and nomogram development for predictive modeling.

Main Results:

Identified three miRNAs and three circRNAs as potential relapse biomarkers.
Expression of these non-coding RNAs increased from healthy controls to relapsed ALL.
Combined non-coding RNA panel showed superior predictive ability and formed an independent predictor of relapse.

Conclusions:

A blood-based non-coding RNA panel offers a promising non-invasive method for predicting pediatric ALL relapse.
Integration with clinical features enhances predictive accuracy and risk stratification.
This approach may significantly improve patient care and outcomes for pediatric ALL.