Evidence map›Paper›PMID 23029380›Full record

ArticlePloS one2012

MicroRNA expression profiles of whole blood in lung adenocarcinoma.

Santosh K Patnaik, Sai Yendamuri, Eric Kannisto, John C Kucharczuk, Sunil Singhal, Anil Vachani

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 2 pooled it
–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

60 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Plasma microRNA Profiling in Type 2 Diabetes Mellitus: A Pilot Study.International journal of molecular sciences · 2023
    Article
  8. Review
  9. MiRNAs in Lung Adenocarcinoma: Role, Diagnosis, Prognosis, and Therapy.International journal of molecular sciences · 2023
    Review
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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

6 authors.

Santosh K PatnaikDepartment of Thoracic Surgery, Roswell Park Cancer Institute, Buffalo, New York, United States of America.
Sai Yendamuri
Eric Kannisto
John C Kucharczuk
Sunil Singhal
Anil Vachani

Funding

Two-Spirit Films in Indigenous Cancer HealthP30CA016056 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI MARK G FRATTINI · 1985 to 2026
$116.6M
Molecular epidemiology of lung cancerK07CA111952 · NCI · UNIVERSITY OF PENNSYLVANIA · PI VACHANI, ANIL · 2006 to 2010
$692k
Peripheral Blood Gene Expression for the Diagnosis of Indeterminate Lung NodulesR21CA156087 · NCI · UNIVERSITY OF PENNSYLVANIA · PI VACHANI, ANIL · 2011 to 2012
$414k
NCI NIH HHS 1R21CA156087-01A1NCI NIH HHS K07 CA111952NCI NIH HHS K07CA111952NCI NIH HHS P30 CA016056NCI NIH HHS R21 CA156087
6 · The paper itself

Abstract

The association of lung cancer with changes in microRNAs in plasma shown in multiple studies suggests a utility for circulating microRNA biomarkers in non-invasive detection of the disease. We examined if presence of lung cancer is reflected in whole blood microRNA expression as well, possibly because of a systemic response. Locked nucleic acid microarrays were used to quantify the global expression of microRNAs in whole blood of 22 patients with lung adenocarcinoma and 23 controls, ten of whom had a radiographically detected non-cancerous lung nodule and the other 13 were at high risk for developing lung cancer because of a smoking history of >20 pack-years. Cases and controls differed significantly for age with a mean difference of 10.7 years, but not for gender, race, smoking history, blood hemoglobin, platelet count, or white blood cell count. Of 1282 quantified human microRNAs, 395 (31%) were identified as expressed in the study's subjects, with 96 (24%) differentially expressed between cases and controls. Classification analyses of microRNA expression data were performed using linear kernel support vector machines (SVM) and top-scoring pairs (TSP) methods, and classifiers to identify presence of lung adenocarcinoma were internally cross-validated. In leave-one-out cross-validation, the TSP classifiers had sensitivity and specificity of 91% and 100%, respectively. The values with SVM were both 91%. In a Monte Carlo cross-validation, average sensitivity and specificity values were 86% and 97%, respectively, with TSP, and 88% and 89%, respectively, with SVM. MicroRNAs miR-190b, miR-630, miR-942, and miR-1284 were the most frequent constituents of the classifiers generated during the analyses. These results suggest that whole blood microRNA expression profiles can be used to distinguish lung cancer cases from clinically relevant controls. Further studies are needed to validate this observation, including in non-adenocarcinomatous lung cancers, and to clarify upon the confounding effect of age.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticAdenocarcinomaAdenocarcinoma of LungAdultAgedAged, 80 and overBiomarkers, TumorFemaleHumansLung NeoplasmsMaleMicroRNAsMiddle AgedOligonucleotide Array Sequence AnalysisPrognosisBiomarkers, TumorMicroRNAsMIRN942 microRNA, human

Identifiers

PMID23029380
PMCPMC3460960

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Registered trials

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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.