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Updated: Jul 3, 2026

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening

Published on: October 26, 2017

Established and Emerging Less Invasive Biomarkers and Technologies for Lung Cancer Screening: Puerto Rican Context.

Keisy Rodriguez-Villafañe1, Clara Santiago2, Juan E Figueroa3

  • 1Pharmaceutical Sciences Department, School of Pharmacy, University of Puerto Rico, Medical Sciences Campus, San Juan, PR 00936, USA.

Onco
|July 2, 2026
PubMed
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A new biomarker-first approach can improve early lung cancer detection in Puerto Rico. This strategy uses non-invasive tests before low-dose computed tomography (LDCT) screening to reduce costs and improve outcomes.

Area of Science:

  • Oncology
  • Biomarker Discovery
  • Health Services Research

Background:

  • Lung cancer mortality in Puerto Rico is high due to late-stage diagnoses.
  • Low-dose computed tomography (LDCT) screening is challenged by false positives, limited radiology capacity, and geographic barriers in Puerto Rico.

Purpose of the Study:

  • To review established and emerging lung cancer detection strategies.
  • To assess the feasibility and health-system fit of these strategies in Puerto Rico.
  • To develop an implementable biomarker-first triage workflow.

Main Methods:

  • Narrative literature review (2001-2026) of LDCT, serum biomarkers, breath analysis, and liquid biopsy.
  • Assessment of technical performance, feasibility, and health-system fit for Puerto Rico.
Keywords:
CEACYFRA 21–1HE4NSEProGRPSCC-Agbiomarkersearly detectionlung cancernitric oxide

Related Experiment Videos

Last Updated: Jul 3, 2026

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening
08:14

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier (MSC) for Lung Cancer Screening

Published on: October 26, 2017

  • Synthesis into a stepwise, biomarker-guided triage pathway.

    • Main Results:

    • Multiplex serum panels with machine learning and tumor-associated antibody (TAAb) show promise as triage tools.
    • Breath analysis is feasible at the point of care.
    • Liquid biopsy aids in indeterminate nodules; a stepwise pathway can optimize screening.

    Conclusions:

    • An integrated, non-invasive, biomarker-first triage model is pragmatic and equitable for earlier lung cancer detection in Puerto Rico.
    • This approach supports resource stewardship and reduces health disparities.
    • It aims to enrich pre-test probability and reduce unnecessary LDCT scans.