Evidence map›Paper›PMID 37894277›Full record

ArticleCancers2023

Serum Insights: Leveraging the Power of miRNA Profiling as an Early Diagnostic Tool for Non-Small Cell Lung Cancer.

Radoslaw Charkiewicz, Anetta Sulewska, Robert Mroz, Alicja Charkiewicz, Wojciech Naumnik, Marcin Kraska, Attila Gyenesei, Bence Galik, Sini Junttila, Borys Miskiewicz and 5 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. A Robust NSCLC Biomarker- miR-7-5p: ItsMicroRNA (Shariqah, United Arab Emirates) · 2025
    Article
  6. Review
  7. Article
  8. Review
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

15 authors at 4 institutions in 2 countries.

Radoslaw CharkiewiczCenter of Experimental Medicine, Medical University of Bialystok, 15-369 Bialystok, Poland.ORCID 0000-0001-7864-6483
Anetta SulewskaDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, Poland.ORCID 0000-0001-7070-8491
Robert Mroz2nd Department of Lung Diseases and Tuberculosis, Medical University of Bialystok, 15-540 Bialystok, Poland.
Alicja CharkiewiczDepartment of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland.
Wojciech Naumnik1st Department of Lung Diseases and Tuberculosis, Medical University of Bialystok, 15-540 Bialystok, Poland.
Marcin KraskaDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, Poland.
Attila GyeneseiSzentagothai Research Center, Genomic and Bioinformatic Core Facility, H-7624 Pecs, Hungary.
Bence GalikSzentagothai Research Center, Genomic and Bioinformatic Core Facility, H-7624 Pecs, Hungary.ORCID 0000-0002-3949-7005
Sini JunttilaTurku Bioscience Centre, University of Turku & Åbo Akademi University, FI-20520 Turku, Finland.
Borys MiskiewiczDepartment of Thoracic Surgery, Medical University of Bialystok, 15-276 Bialystok, Poland.
Rafal StecDepartment of Oncology, Medical University of Warsaw, 02-091 Warsaw, Poland.
Piotr KarabowiczBiobank, Medical University of Bialystok, 15-269 Bialystok, Poland.
Magdalena ZawadaDepartment of Hematology Diagnostics and Genetics, The University Hospital, 30-688 Krakow, Poland.ORCID 0000-0001-9105-1767
Wojciech MiltykDepartment of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-089 Bialystok, Poland.ORCID 0000-0001-5150-6093
Jacek NiklinskiDepartment of Clinical Molecular Biology, Medical University of Bialystok, 15-269 Bialystok, Poland.
Medical University of Białystok · PLÅbo Akademi University · FIMedical University of Warsaw · PLUniversity School of Physical Education in Kraków · PL

Funding

National Centre for Research and Development STRATEGMED2/266484/2/NCBR/2015
6 · The paper itself

Abstract

Non-small cell lung cancer is the predominant form of lung cancer and is associated with a poor prognosis. MiRNAs implicated in cancer initiation and progression can be easily detected in liquid biopsy samples and have the potential to serve as non-invasive biomarkers. In this study, we employed next-generation sequencing to globally profile miRNAs in serum samples from 71 early-stage NSCLC patients and 47 non-cancerous pulmonary condition patients. Preliminary analysis of differentially expressed miRNAs revealed 28 upregulated miRNAs in NSCLC compared to the control group. Functional enrichment analyses unveiled their involvement in NSCLC signaling pathways. Subsequently, we developed a gradient-boosting decision tree classifier based on 2588 miRNAs, which demonstrated high accuracy (0.837), sensitivity (0.806), and specificity (0.859) in effectively distinguishing NSCLC from non-cancerous individuals. Shapley Additive exPlanations analysis improved the model metrics by identifying the top 15 miRNAs with the strongest discriminatory value, yielding an AUC of 0.96 ± 0.04, accuracy of 0.896, sensitivity of 0.884, and specificity of 0.903. Our study establishes the potential utility of a non-invasive serum miRNA signature as a supportive tool for early detection of NSCLC while also shedding light on dysregulated miRNAs in NSCLC biology. For enhanced credibility and understanding, further validation in an independent cohort of patients is warranted.

Indexed as

biomarkersgradient-boosting decision tree classifierliquid biopsymiRNAnext-generation sequencingnon-small cell lung cancerShapley Additive exPlanations

Identifiers

PMID37894277
PMCPMC10605272
OpenAlexW4387498729

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.