Evidence map›Paper›PMID 35117418›Full record

ArticleTranslational cancer research2020

Correlations of AKIP1, CXCL1 and CXCL2 expressions with clinicopathological features and survival profiles in cervical cancer patients.

Xiaoyan Wan, Zubei Hong, Yuhong Mao, Wen Di

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Article in Translational cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.0field-weighted citation impact, top 15% 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

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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

7 citing papers in PubMed, 12 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

4 authors at 2 institutions in 1 country.

Xiaoyan WanDepartment of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Zubei HongDepartment of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Yuhong MaoDepartment of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Wen DiDepartment of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
Shanghai Jiao Tong University · CNRenji Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study aimed to evaluate the correlation of A-kinase-interacting protein 1 (AKIP1) with C-X-C motif chemokine ligand (CXCL) 1 and CXCL2, and their associations with clinical characteristics and prognosis in cervical cancer patients.

methodsOne hundred and fifty early-stage cervical cancer patients treated with surgical resection were reviewed and tumor tissue samples were obtained. Expression of AKIP1, CXCL1 and CXCL2 was detected by immunohistochemistry (IHC). Data of tumor features were retrieved, and disease-free survival (DFS) as well as overall survival (OS) were calculated.

resultsAKIP1 expression was positively correlated with CXCL1 and CXCL2 expression in cervical cancer tissue (both P<0.001). AKIP1 expression was positively correlated with tumor size (P=0.040), lymph node (LYN) metastasis (P=0.034) and International Federation of Gynecology and Obstetrics (FIGO) stage (P=0.021); CXCL1 expression was positively associated with tumor size (P=0.048); and CXCL2 expression was positively correlated with LYN metastasis (P=0.026). As for DFS and OS, AKIP1 high expression was correlated with worse DFS (P=0.016) and OS (P=0.007), CXCL1 high expression was associated with poor DFS (P=0.029) but not OS (P=0.118). No correlation of CXCL2 expression with DFS (P=0.141) or OS (P=0.125) was found.

conclusionsAKIP1 positively correlates with CXCL1/CXCL2, and associates with advanced tumor features as well as unfavorable survival profiles in cervical cancer patients.

Indexed as

A-kinase-interacting protein 1 (AKIP1)Cervical cancerclinical characteristicsCXCL1/CXCL2survival profiles

Identifiers

PMID35117418
PMCPMC8797758
OpenAlexW2997252620

What OpenQuestion holds

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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.