Evidence map›Paper›PMID 29387235›Full record

ArticleOncology letters2018

Predictive relevance of miR-34a, miR-224 and miR-342 in patients with advanced squamous cell carcinoma of the lung undergoing palliative chemotherapy.

Vlastimil Kulda, Martin Svaton, Petr Mukensnabl, Kristyna Hrda, Pavel Dvorak, Zbynek Houdek, Katerina Houfkova, Radana Vrzakova, Vaclav Babuska, Milos Pesek and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
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  5. 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

11 authors at 1 institution in 1 country.

Vlastimil KuldaDepartment of Medical Chemistry and Biochemistry, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Martin SvatonDepartment of Pneumology and Phthisiology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Petr MukensnablDepartment of Pathology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Kristyna HrdaDepartment of Medical Chemistry and Biochemistry, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Pavel DvorakDepartment of Biology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Zbynek HoudekDepartment of Biology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Katerina HoufkovaDepartment of Biology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Radana VrzakovaDepartment of Medical Chemistry and Biochemistry, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Vaclav BabuskaDepartment of Medical Chemistry and Biochemistry, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Milos PesekDepartment of Pneumology and Phthisiology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Martin PestaDepartment of Biology, Faculty of Medicine in Pilsen, Charles University, 30166 Pilsen, Czech Republic.
Charles University · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Attributing to their pathophysiological role and stability in biological samples, microRNAs (miRNAs) have the potential to become valuable predictive markers for non-small cell lung cancer (NSCLC). Samples of biopsy tissue constitute suitable material for miRNA profiling with the aim of predicting the effect of palliative chemotherapy. The present study group included 81 patients (74 males, 7 females, all smokers or former smokers) with the squamous cell carcinoma (SCC) histological subtype of NSCLC at a late stage (3B or 4). All patients received palliative chemotherapy based on platinum derivatives in combination with paclitaxel or gemcitabine. The expression of 17 selected miRNAs was measured by reverse transcription-quantitative polymerase chain reaction in tumor tissue macrodissected from formalin-fixed paraffin-embedded (FFPE) tissue samples. To predict the effect of palliative chemotherapy, the association between gene expression levels and overall survival (OS) time was analyzed. From the 17 miRNAs of interest, low expression levels of miR-342 and high expression levels of miR-34a and miR-224 were associated with a reduced OS time in subgroups of patients based on smoking status and treatment modality. Using cluster analysis, associations between combinations of miR-34a, -224 and -342 expression levels with patient survival were identified. The present study revealed that patients with the simultaneous high expression of miR-224 and -342 had a similar prognostic outcome to those with the low expression of miR-224 and -342, which was significantly reduced, compared with patients exhibiting high expression of either miR-224 or miR-342 with low expression of the other. We hypothesize that the effect of a particular miRNA is dependent on the expression level of other members of the miRNA network. This finding appears to complicate survival analyses based on individual miRNAs as markers. In conclusion, the present study provides evidence that specific miRNAs were associated with OS time, which may be candidate predictors for the effectiveness of palliative treatment in SCC lung cancer patients. This objective can be better achieved by combining more markers together than by using individual miRNAs.

Indexed as

biomarkerslung cancermicroRNApalliative treatment

Identifiers

PMID29387235
PMCPMC5769371
OpenAlexW2766748410

What OpenQuestion holds

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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.