Evidence map›Paper›PMID 33292226›Full record

ArticleCancer cell international2020

FABP7 is a potential biomarker to predict response to neoadjuvant chemotherapy for breast cancer.

Qin Xie, Ying-Sheng Xiao, Shi-Cheng Jia, Jie-Xuan Zheng, Zhen-Chao Du, Yi-Chun Chen, Mu-Tong Chen, Yuan-Ke Liang, Hao-Yu Lin, De Zeng

Open access · goldAbstract read
In one paragraph

Article in Cancer cell international, 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
0.9field-weighted citation impact, top 26% 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, 26 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.

Qin XieDepartment of Medical Oncology, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou, 515031, People's Republic of China.
Ying-Sheng XiaoDepartment of Thyroid Surgery, Shantou Central Hospital, 114 Waima Road, Shantou, 515031, People's Republic of China.
Shi-Cheng JiaShantou University Medical College, Shantou, 515000, People's Republic of China.
Jie-Xuan ZhengShantou University Medical College, Shantou, 515000, People's Republic of China.
Zhen-Chao DuShantou University Medical College, Shantou, 515000, People's Republic of China.
Yi-Chun ChenShantou University Medical College, Shantou, 515000, People's Republic of China.
Mu-Tong ChenShantou University Medical College, Shantou, 515000, People's Republic of China.
Yuan-Ke LiangDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, 57 Changping Road, Shantou, 515041, People's Republic of China.
Hao-Yu LinDepartment of Thyroid and Breast Surgery, The First Affiliated Hospital of Shantou University Medical College, 57 Changping Road, Shantou, 515041, People's Republic of China.
De ZengDepartment of Medical Oncology, The Cancer Hospital of Shantou University Medical College, 7 Raoping Road, Shantou, 515031, People's Republic of China. dezeng@stu.edu.cn.ORCID http://orcid.org/0000-0002-9141-5505
Shantou University · CNShantou Central Hospital · CN

Funding

National College Students Innovation and Entrepreneurship Training Program (CN) No. 201810560034National College Students Innovation and Entrepreneurship Training Program (CN) No. 201810560038Natural Science Foundation of Guangdong Province (CN) No. 2018A030313562Natural Science Foundation of Guangdong Province (CN) No. 2019A1515010239
6 · The paper itself

Abstract

backgroundEarly prediction of response to neoadjuvant chemotherapy (NAC) is critical in choosing appropriate chemotherapeutic regimen for patients with locally advanced breast cancer. Herein, we sought to identify potential biomarkers to predict the response to neoadjuvant chemotherapy for breast cancer patients.

methodsThree genomic profiles acquired by microarray analysis from subjects with or without residual tumors after NAC downloaded from the GEO database were used to screen the differentially expressed genes (DEGs). An array of public databases, including ONCOMINE, cBioportal, Breast Cancer Gene Expression Miner v4.0, and the Kaplan Meir-plotter, etc., were used to evaluate the potential functions, related signaling pathway, as well as prognostic values of FABP7 in breast cancer. Anti-cancer drug sensitivity assay, real-time PCR, flow cytometry and western-blotting assays were used to investigate the function of FABP7 in breast cancer cells and examine the relevant mechanism.

resultsTwo differentially expressed genes, including FABP7 and ESR1, were identified to be potential indicators of response to anthracycline and taxanes for breast cancer. FABP7 was associated with better chemotherapeutic response, while ESR1 was associated with poorer chemotherapeutic effectiveness. Generally, the expression of FABP7 was significantly lower in breast cancer than normal tissue samples. FABP7 mainly high expressed in ER-negative breast tumor and might regulate cell cycle to enhance chemosensitivity. Moreover, elevated FABP7 expression increased the percentage of cells at both S and G2/M phase in MDA-MB-231-ADR cells, and decreased the percentage of cells at G0/G1 phase, as compared to control group. Western-blotting results showed that elevated FABP7 expression could increase Skp2 expression, while decrease Cdh1 and p27kip1 expression in MDA-MB-231-ADR cells. In addition, FABP7 was correlated to longer recurrence-free survival (RFS) in BC patients with ER-negative subtype of BC treated with chemotherapy.

conclusionFABP7 is a potential favorable biomarker and predicts better response to NAC in breast cancer patients. Future study on the predictive value and detail molecular mechanisms of FABP7 in contribution to chemosensitivity in breast cancer is warranted.

Indexed as

Breast cancerChemosensitivityFatty acid binding protein-7 (FABP7)Prognosis

Identifiers

PMID33292226
PMCPMC7684949
OpenAlexW3107543730

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.