Evidence map›Paper›PMID 34289901›Full record

ArticleClinical epigenetics2021

Abnormal methylation characteristics predict chemoresistance and poor prognosis in advanced high-grade serous ovarian cancer.

Li-Yuan Feng, Bing-Bing Yan, Yong-Zhi Huang, Li Li

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  14. Computational Analysis of High-Dimensional DNA Methylation Data for Cancer Prognosis.Journal of computational biology : a journal of computational molecular cell biology · 2022
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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.

Li-Yuan FengDepartment of Gynecology and Oncology, Guangxi Medical University Cancer Hospital and Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, 71 Hedi Road, Nanning, 530021, Guangxi, People's Republic of China.ORCID 0000-0002-0699-0645
Bing-Bing YanDepartment of Gynecology and Oncology, Guangxi Medical University Cancer Hospital and Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, 71 Hedi Road, Nanning, 530021, Guangxi, People's Republic of China.
Yong-Zhi HuangDepartment of Gynecology and Oncology, Guangxi Medical University Cancer Hospital and Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, 71 Hedi Road, Nanning, 530021, Guangxi, People's Republic of China.
Li LiDepartment of Gynecology and Oncology, Guangxi Medical University Cancer Hospital and Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor, Ministry of Education, 71 Hedi Road, Nanning, 530021, Guangxi, People's Republic of China. lili@gxmu.edu.cn.
Tumor Hospital of Guangxi Medical University · CNGuangxi Medical University · CN

Funding

Science and Technology Department of Guangxi Zhuang Autonomous 1140003A-33
6 · The paper itself

Abstract

backgroundPrimary or acquired chemoresistance is a key link in the high mortality rate of ovarian cancer. There is no reliable method to predict chemoresistance in ovarian cancer. We hypothesized that specific methylation characteristics could distinguish chemoresistant and chemosensitive ovarian cancer patients.

methodsIn this study, we used 450 K Infinium Methylation BeadChip to detect the different methylation CpGs between ovarian cancer patients. The differential methylation genes were analyzed by GO and KEGG Pathway bioinformatics analysis. The candidate CpGs were confirmed by pyrosequencing. The expression of abnormal methylation gene was identified by QRT-PCR and IHC. ROC analysis confirmed the ability to predict chemotherapy outcomes. Prognosis was evaluated using Kaplan-Meier.

resultsIn advanced high-grade serous ovarian cancer, 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) remained hypermethylated in chemoresistant patients. The sensitivity, specificity and AUC of 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) methylation to predict chemotherapy sensitivity were 63.60-97.00%, 46.40-89.30% and 0.774-0.846. PFS of 6 candidate genes (ITGB6:cg21105318, cg07896068; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934) hypermethylation patients was significantly shorter. The expression of NCALD and LAMA3 in chemoresistant patients was lower than that of chemosensitive patients. Spearman analysis showed that NCALD and LAMA3 methylations were negatively correlated with their expression.

conclusionsAs a new biomarker of chemotherapy sensitivity, hypermethylation of NCALD and LAMA3 is associated with poor PFS in advanced high-grade serous ovarian cancer. In the future, further research on NCALD and LAMA3 will be needed to provide guidance for clinical stratification of demethylation therapy.

Indexed as

AdultChinaDNA MethylationDrug TherapyFemaleHumansMiddle AgedOvarian NeoplasmsPrognosis450 K Infinium Methylation BeadChipChemotherapy resistanceDNA methylationOvarian cancerPrognosis

Identifiers

PMID34289901
PMCPMC8296752
OpenAlexW3184366570

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.