Evidence map›Paper›PMID 38324167›Full record

ArticleFunctional & integrative genomics2024

Low FHL1 expression indicates a good prognosis and drug sensitivity in ovarian cancer.

Xiaoying Chen, Yue Yu, Yuting Su, Lizhou Shi, Shanzhou Xie, Yi Hong, Xia Liu, Fuqiang Yin

Erratum issuedAbstract read
PubMed Publisher
In one paragraph

Article in Functional & integrative genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Xiaoying ChenKey Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Centre for Translational Medicine and School of Basic Medical Sciences, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Yue YuLife Sciences Institute, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Yuting SuLife Sciences Institute, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Lizhou ShiLife Sciences Institute, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Shanzhou XieKey Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Centre for Translational Medicine and School of Basic Medical Sciences, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Yi HongKey Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Centre for Translational Medicine and School of Basic Medical Sciences, Guangxi Medical University, Nanning, 530021, Guangxi, China.
Xia LiuKey Laboratory of Longevity and Ageing-Related Disease of Chinese Ministry of Education, Centre for Translational Medicine and School of Basic Medical Sciences, Guangxi Medical University, Nanning, 530021, Guangxi, China. realliuxia@sina.com.
Fuqiang YinLife Sciences Institute, Guangxi Medical University, Nanning, 530021, Guangxi, China. yinfq@mail2.sysu.edu.cn.
Guangxi Medical University · CNGuangxi University · CN

Funding

Advanced Innovation Teams and Xinghu Scholars Program of Guangxi Medical University 24/02304001018XGuangxi Natural Science Foundation 2021GXNSFAA075002, 2018GXNSFAA281227National Natural Science Foundation of China 81860458, 81903644Program Foundation of Key Laboratory of High-Incidence Tumor Prevention and Treatment, Ministry of Education GKE2019-20, GKE-ZZ202148
6 · The paper itself

Abstract

Chemotherapy resistance is the main reason for the poor prognosis of ovarian cancer (OC). FHL1 is an important tumour regulator, but its relationship with the prognosis, drug resistance, and tumour microenvironment of OC is unknown. Immunohistochemistry was used to determine FHL1 expression in OC. Kaplan‒Meier plotter was used for survival analysis. The value of gene expression in predicting drug resistance was estimated using the area under the curve (AUC). Bivariate correlation was used to determine the coexpression of two genes. Functional cluster and pathway enrichment were used to uncover hidden signalling pathways. The relationship between gene levels and the tumour microenvironment was visualised through the ggstatsplot and pheatmap packages. The mRNA and protein levels of FHL1 were downregulated in 426 and 100 OC tissues, respectively. Low FHL1 expression was correlated with good progression-free survival (PFS), postprogression survival, and overall survival (OS) in 1815 OC patients, and was further confirmed to be associated with good OS by immunohistochemistry in 152 OC tissues. Furthermore, FHL1 was downregulated in drug-sensitive tissues, while its high expression predicted drug resistance (AUC > 0.65). Mechanistically, FHL1 was coexpressed with FLNC, CAV1, PPP1R12B, and FLNA at the mRNA and protein levels in 558 and 174 OC tissues, respectively, and their expression was downregulated in OC. Additionally, very strong coexpression of FHL1 with the four genes was identified in at least 23 different tumours. Low expression of the four genes was associated with good PFS, and the combination of FHL1 with the four genes provided better prognostic power. Meanwhile, the expression of all five genes was strongly and positively associated with the abundance of macrophages. Low FHL1 expression acts as a favourable factor in OC, probably via positive coexpression with FLNC, CAV1, PPP1R12B, and FLNA.

Indexed as

Ovarian NeoplasmsDrug ResistanceFemaleHumansIntracellular Signaling Peptides and ProteinsLIM Domain ProteinsMacrophagesMuscle ProteinsRNA, MessengerTumor MicroenvironmentFHL1 protein, humanIntracellular Signaling Peptides and ProteinsLIM Domain ProteinsMuscle ProteinsRNA, MessengerBiomarkerDrug resistanceFHL1Ovarian cancerPrognosis

Identifiers

PMID38324167
OpenAlexW4391611261

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.