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Related Concept Videos

lncRNA - Long Non-coding RNAs02:39

lncRNA - Long Non-coding RNAs

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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...
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Updated: Jul 27, 2025

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
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Circulating hsa-miR-5096 predicts

Martine Bocchini1, Marcella Tazzari1, Sara Ravaioli2

  • 1Immunotherapy, Cell Therapy and Biobank (ITCB), IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.

Frontiers in Oncology
|June 8, 2023
PubMed
Summary
This summary is machine-generated.

New circulating biomarkers, including hsa-miR-5096, show promise for predicting treatment response and prognosis in patients with gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) undergoing Peptide Receptor Radionuclide Therapy (PRRT). These microRNAs correlate with imaging findings and patient outcomes, aiding in GEP-NET management.

Keywords:
PRRT (peptide receptor radionuclide therapy)SSTR2functional imaging (positron-emission tomography)miRNA – microRNApancreatic neuroendocrine tumors

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Area of Science:

  • Oncology
  • Molecular Biology
  • Biomarker Discovery

Background:

  • Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) are rare, with limited treatment options for inoperable cases.
  • Peptide Receptor Radionuclide Therapy (PRRT) shows variable responses, necessitating prognostic biomarkers.
  • 18F-FDG uptake on PET/CT indicates tumor aggressiveness in GEP-NETs.

Purpose of the Study:

  • To identify circulating microRNAs (miRNAs) associated with 18F-FDG-PET/CT status in GEP-NETs.
  • To find miRNAs that predict higher risk and lower response to PRRT.
  • To establish measurable prognostic biomarkers for GEP-NET patient management.

Main Methods:

  • Whole miRNome Next-Generation Sequencing (NGS) profiling of plasma samples from GEP-NET patients before PRRT.
  • Differential expression analysis between 18F-FDG positive and negative patient groups.
  • Validation using Real-Time quantitative PCR, Cox regression for progression-free survival (PFS), and in situ hybridization for miR-protein correlation.

Main Results:

  • hsa-miR-5096, hsa-let-7i-3p, and hsa-miR-4311 correlated with 18F-FDG-PET/CT in pancreatic NETs (PanNETs).
  • hsa-miR-5096 predicted 6-month PFS and 12-month Overall Survival post-PRRT, and identified 18F-FDG-PET/CT positive PanNETs with worse prognosis.
  • hsa-miR-5096 inversely correlated with SSTR2 expression and 68Gallium-DOTATOC uptake, decreasing SSTR2 in vitro.

Conclusions:

  • hsa-miR-5096 serves as a biomarker for 18F-FDG-PET/CT and an independent predictor of PFS in PanNETs.
  • Exosomal hsa-miR-5096 may contribute to SSTR2 heterogeneity and PRRT resistance.
  • Circulating miRNAs offer potential for improved GEP-NET prognostication and treatment stratification.