Evidence map›Paper›PMID 33622273›Full record

ArticleBMC gastroenterology2021

V-Raf murine sarcoma viral oncogene homolog B1 (BRAF) as a prognostic biomarker of poor outcomes in esophageal cancer patients.

Aihemaijiang Kuerbanjiang, Maimaitiyiming Maimaituerxun, Yanjun Zhang, Yiliang Li, Gang Cui, Aibaidula Abuduhabaier, Abuduwaili Aierken, Buya Miranbieke, Meilikezati Anzaer, Yusufu Maimaiti

Open access · goldAbstract read
In one paragraph

Article in BMC gastroenterology, 2021. 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
0.7field-weighted citation impact, top 29% 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, 7 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 1 institution in 1 country.

Aihemaijiang Kuerbanjiang *Department of Gastroenterology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Maimaitiyiming Maimaituerxun *Department of General Surgery, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Yanjun ZhangDepartment of Clinical Research Center, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Yiliang LiDepartment of General Surgery, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Gang CuiDepartment of Clinical Research Center, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Aibaidula AbuduhabaierDepartment of General Surgery, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Abuduwaili AierkenDepartment of General Surgery, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Buya MiranbiekeDepartment of Gastroenterology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China.
Meilikezati AnzaerDepartment of Gastroenterology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China. anzar1204@sina.cn.
Yusufu MaimaitiDepartment of General Surgery, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi, 830000, China. docyusufu@163.com.ORCID http://orcid.org/0000-0003-0573-2465
People's Hospital of Xinjiang Uygur Autonomous Region · CN

Funding

Natural Science Foundation of Xinjiang Province 218D03018
6 · The paper itself

Abstract

backgroundEsophageal cancer is one of the most aggressive malignancies, and is associated with multiple genetic mutations. At present, the v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) gene mutation has been observed in esophageal cancer and is associated with poor prognosis. This study aimed to investigate the protein expression of BRAF in esophageal cancer and determine its effect on patient outcomes.

methodsWe used immunohistochemistry to detect the expression of BRAF via tissue microarrays in esophageal cancer samples, the Kaplan-Meier method to perform survival analysis, and the Cox proportional hazards regression model to explore the risk factors of esophageal cancer. The role of BRAF in the proliferation, invasion, and metastasis of esophageal cancer was studied by clone formation, scratch test, Transwell invasion and migration test. The tumor-bearing model of BRAF inhibitor was established using TE-1 cells, and corresponding negative control was set up to observe the growth rate of the two models.

resultsThe results revealed that BRAF overexpression was significantly correlated with Ki67 (P < 0.05). Survival analysis showed that BRAF overexpression contributed to a shorter overall survival (P = 0.014) in patients with esophageal cancer. Univariate and multivariate regression analyses demonstrated that BRAF was a prognostic factor for poor esophageal cancer outcomes (P < 0.05). Small interfering RNA knockdown of BRAF significantly reduced the cell clone formation rate compared to the control group. Transwell assay analysis showed that the migration and invasion of cells in the experimental group were significantly inhibited relative to the control group, and the inhibition rates of the small interfering RNA group were 67% and 60%, respectively. In the scratch test, the wound healing ability of the BRAF knockdown group was significantly weaker than that of the control group. There were significant differences in tumor growth volume and weight between the two groups in nude mice.

conclusionBRAF overexpression may serve as an effective predictive factor for poor prognosis.

Indexed as

Colorectal NeoplasmsEsophageal NeoplasmsAnimalsBiomarkersHumansMiceMice, NudeMutationOncogenesPrognosisProto-Oncogene Proteins B-rafBiomarkersBRAF protein, humanProto-Oncogene Proteins B-rafBiomarkerBRAFEsophageal cancerPrognosisV-Raf murine sarcoma viral oncogene homolog B1

Identifiers

PMID33622273
PMCPMC7903799
OpenAlexW3131627286

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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.