Evidence map›Paper›PMID 33836003›Full record

ArticlePloS one2021

High ELF4 expression in human cancers is associated with worse disease outcomes and increased resistance to anticancer drugs.

Doris Kafita, Victor Daka, Panji Nkhoma, Mildred Zulu, Ephraim Zulu, Rabecca Tembo, Zifa Ngwira, Florence Mwaba, Musalula Sinkala, Sody Munsaka

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

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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

10 authors at 2 institutions in 1 country.

Doris KafitaDepartment of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia.ORCID 0000-0003-4833-3122
Victor DakaDepartment of Pathology and Microbiology, School of Medicine, University of Zambia, Lusaka, Zambia.
Panji NkhomaDepartment of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia.
Mildred ZuluDepartment of Clinical Sciences, School of Medicine, Copperbelt University, Ndola, Zambia.
Ephraim ZuluDepartment of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia.
Rabecca TemboDepartment of Clinical Sciences, School of Medicine, Copperbelt University, Ndola, Zambia.
Zifa NgwiraDepartment of Clinical Sciences, School of Medicine, Copperbelt University, Ndola, Zambia.
Florence MwabaDepartment of Clinical Sciences, School of Medicine, Copperbelt University, Ndola, Zambia.
Musalula SinkalaDepartment of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia.
Sody MunsakaDepartment of Biomedical Sciences, School of Health Sciences, University of Zambia, Lusaka, Zambia.ORCID 0000-0002-6917-3888
University of Zambia · ZMCopperbelt University · ZM

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The malignant phenotype of tumour cells is fuelled by changes in the expression of various transcription factors, including some of the well-studied proteins such as p53 and Myc. Despite significant progress made, little is known about several other transcription factors, including ELF4, and how they help shape the oncogenic processes in cancer cells. To this end, we performed a bioinformatics analysis to facilitate a detailed understanding of how the expression variations of ELF4 in human cancers are related to disease outcomes and the cancer cell drug responses. Here, using ELF4 mRNA expression data of 9,350 samples from the Cancer Genome Atlas pan-cancer project, we identify two groups of patient's tumours: those that expressed high ELF4 transcripts and those that expressed low ELF4 transcripts across 32 different human cancers. We uncover that patients segregated into these two groups are associated with different clinical outcomes. Further, we find that tumours that express high ELF4 mRNA levels tend to be of a higher-grade, afflict a significantly older patient population and have a significantly higher mutation burden. By analysing dose-response profiles to 397 anti-cancer drugs of 612 well-characterised human cancer cell lines, we discover that cell lines that expressed high ELF4 mRNA transcript are significantly less responsive to 129 anti-cancer drugs, and only significantly more response to three drugs: dasatinib, WH-4-023, and Ponatinib, all of which remarkably target the proto-oncogene tyrosine-protein kinase SRC and tyrosine-protein kinase ABL1. Collectively our analyses have shown that, across the 32 different human cancers, the patients afflicted with tumours that overexpress ELF4 tended to have a more aggressive disease that is also is more likely more refractory to most anti-cancer drugs, a finding upon which we could devise novel categorisation of patient tumours, treatment, and prognostic strategies.

Indexed as

Drug Resistance, NeoplasmAntineoplastic AgentsDNA-Binding ProteinsHumansNeoplasmsProtein Kinase InhibitorsProto-Oncogene MasTranscription FactorsTranscriptomeTreatment OutcomeAntineoplastic AgentsDNA-Binding ProteinsELF4 protein, humanMAS1 protein, humanProtein Kinase InhibitorsProto-Oncogene MasTranscription Factors

Identifiers

PMID33836003
PMCPMC8034723
OpenAlexW3147523279

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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.