Evidence map›Paper›PMID 41373464›Full record

ReviewInternational journal of molecular sciences2025

Comprehensive Liquid Biopsy Approaches for the Clinical Management of Lung Cancer Using Multiple Biological Matrices.

Areti Strati, Martha Zavridou, Kostas A Papavassiliou, Athanasios G Papavassiliou

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Areti StratiDepartment of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.ORCID 0000-0001-9644-5538
Martha ZavridouDepartment of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
Kostas A PapavassiliouFirst University Department of Respiratory Medicine, 'Sotiria' Chest Hospital, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.ORCID 0000-0001-9620-745X
Athanasios G PapavassiliouDepartment of Biological Chemistry, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece.ORCID 0000-0001-5803-4527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in both men and women. It is broadly classified into two main histological subtypes, with non-small cell lung cancer (NSCLC) being the most prevalent, accounting for approximately 85-90% of all cases. Liquid biopsy refers to the analysis of tumor-derived material circulating in body fluids. This minimally invasive technique can be performed repeatedly over time and enables the detection of a tumor's genomic profile without tissue samples. Liquid biopsies have the potential to identify biomarkers across different lung cancer subtypes that may be associated with early detection, prognosis, and prediction of response to targeted therapies. In this context, bioinformatics tools play a critical role in analyzing large-scale, high-dimensional omics datasets, which can be transformed into clinically meaningful insights. This article emphasizes the significance of prognostic, predictive, and diagnostic biomarkers in lung cancer, which can be detected in various biological fluids. Furthermore, it highlights how integrating bioinformatics approaches can facilitate the development of a personalized molecular profile, ultimately supporting individualized treatment strategies for each patient.

Indexed as

Biomarkers, TumorCarcinoma, Non-Small-Cell LungLung NeoplasmsComputational BiologyHumansLiquid BiopsyPrognosisBiomarkers, Tumorbiomarkersliquid biopsylung cancer

Identifiers

PMID41373464
PMCPMC12692596

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.