Evidence map›Paper›PMID 32764988›Full record

ArticleOncoTargets and therapy2020

Co-Expression Network Analysis Identified LTF in Association with Metastasis Risk and Prognosis in Clear Cell Renal Cell Carcinoma.

Lihua Ni, Cheng Yuan, Changjiang Zhang, Yuandi Xiang, Juan Wu, Xiaolong Wang, Xiaoyan Wu

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.4field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 29 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

7 authors at 4 institutions in 2 countries.

Lihua Ni *Department of Nephrology, Zhongnan Hospital of Wuhan University, Wuhan 430071, People's Republic of China.
Cheng Yuan *Department of Gynecological Oncology, Zhongnan Hospital of Wuhan University, Wuhan 430071, People's Republic of China.
Changjiang Zhang *Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, People's Republic of China.
Yuandi XiangDepartment of Otorhinolaryngology, Wuhan First Hospital, Wuhan, Hubei, People's Republic of China.
Juan WuDepartment of Dermatology, Wuhan First Hospital, Wuhan, Hubei, People's Republic of China.
Xiaolong WangDepartment of Urology, Research Lab/LIFE-Zentrum, University of Munich (LMU), München, Germany.
Xiaoyan WuDepartment of Nephrology, Zhongnan Hospital of Wuhan University, Wuhan 430071, People's Republic of China.
Wuhan University · CNWuhan Third Hospital · CNLudwig-Maximilians-Universität München · DEZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveClear cell renal cell carcinoma (ccRCC) is the most common renal cancer in adults. The 5-year survival rate of patients with advanced ccRCC is less than 30%. Lack of potential biomarkers for treatment and prognosis is a limitation for early diagnosis and treatment of ccRCC.

methodsWe collected microarray profiles of 39 ccRCC and matched normal samples to identify differential expression genes (DEGs). Then, a weighted gene co-expression network analysis (WGCNA) was constructed to identify gene modules associated with the metastasis in ccRCC. The Cancer Genome Atlas (TCGA) database and the Human Protein Atlas (HPA, https://www.proteinatlas.org/) database were used for verification set. Finally, we used biological experiments to preliminary investigate the impact of LTF on the tumor biological behavior of ccRCC, including proliferation, migration, invasion, and apoptosis.

resultsA total of 15 genetic modules were identified, and the light-green module is considered the most relevant to tumor metastasis. (

conclusionLTF might be a novel prognostic biomarker for ccRCC.

Indexed as

clear cell renal cell carcinomaLTFmetastasis

Identifiers

PMID32764988
PMCPMC7381825
OpenAlexW3042548450

What OpenQuestion holds

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LicenceCC BY-NC
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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 OpenQuestion graph.