Evidence map›Paper›PMID 31774870›Full record

ArticlePloS one2019

Analysis of the characteristics of chemotherapy-resistant renal cell carcinomas based on global transcriptional analysis of their tissues and cell lines.

Takahiro Isono, Masafumi Suzaki

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 75% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Takahiro IsonoCentral Research Laboratory, Shiga University of Medical Science, Otsu, Shiga, Japan.ORCID 0000-0003-2383-0667
Masafumi SuzakiCentral Research Laboratory, Shiga University of Medical Science, Otsu, Shiga, Japan.
Shiga University of Medical Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Starvation-resistant renal cell carcinoma (RCC) cell lines are considered dormant-state cells that survive even under glucose starvation. The cellular biological and global transcriptional analysis using these cells identified potential markers of chemotherapy-resistant RCC and therapeutic agent candidates. Recently, we showed that ARL4C was a predictive biomarker for poor prognosis in patients with chemotherapy-resistant RCC by the global transcriptional analysis of patient primary tissues. The objective of this study was to identify the characteristics of chemotherapy-resistant RCC by the global transcriptional analysis of primary tissues of patients with RCC and RCC cell lines. The connective global transcriptional analysis showed that two starvation-resistant RCC cell lines, SW839 and KMRC-1, were strongly correlated to tissues of patients with chemotherapy-resistant RCC and showed high expressions of invasive- and proliferation-related genes. We found fibronectin (FN1) expression was a predictive biomarker in some patients with chemotherapy-resistant RCC, which especially correlated with two starvation-resistant RCC cell lines. These results indicate these cell lines emulate chemotherapy-resistant RCC and might be useful in the search for markers to predict poor prognosis and in the development of therapeutic agents and their index markers for chemotherapy-resistant RCCs.

Indexed as

Antineoplastic AgentsBiomarkers, TumorCarcinoma, Renal CellDrug Resistance, NeoplasmFibronectinsGene Expression ProfilingHumansKidney NeoplasmsPrognosisSurvival RateTranscriptomeTumor Cells, CulturedAntineoplastic AgentsBiomarkers, TumorFibronectinsFN1 protein, human

Identifiers

PMID31774870
PMCPMC6881023
OpenAlexW2990300409

What OpenQuestion holds

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LicenceCC BY
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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.