Evidence map›Paper›PMID 35434581›Full record

ArticleEClinicalMedicine2022

Identification of clinical and molecular features of recurrent serous borderline ovarian tumour.

Ziyang Lu, Fanghe Lin, Tao Li, Jinhui Wang, Cenxi Liu, Guangxing Lu, Bin Li, MingPei Pan, Shaohua Fan, Junqiu Yue and 4 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EClinicalMedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 14 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

14 authors at 6 institutions in 2 countries.

Ziyang LuState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Fanghe LinState Key Laboratory for Physical Chemistry of Solid Surfaces, Key Laboratory for Chemical Biology of Fujian Province, Key Laboratory of Analytical Chemistry, Department of Chemical Biology, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.
Tao LiDepartment of Obstetrics and Gynecology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China.
Jinhui WangState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Cenxi LiuState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Guangxing LuState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Bin LiState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
MingPei PanState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Shaohua FanState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Junqiu YueDepartment of Pathology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430079, China.
He HuangState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Jia SongInstitute of Molecular Medicine, School of Medicine, Renji Hospital, Shanghai Jiao Tong University, Shanghai 200127, China.
Chao GuState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Jin LiState Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Institute of Metabolism and Integrative Biology, Obstetrics and Gynecology Hospital of Fudan University, Fudan University, Shanghai 200438, China.
Fudan University · CNHubei Cancer Hospital · CNLeibniz University Hannover · DEShandong Provincial Hospital · CNShanghai Jiao Tong University · CNXiamen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Serous borderline ovarian tumour (SBOT) is the most common type of BOT. Fertility sparing surgery (FSS) is an option for patients with SBOT, though it may increase the risk of recurrence. The clinical and molecular features of its recurrence are important and need to be investigated in detail. Methods: An internal cohort of 319 patients with SBOT was collected from Aug 1, 2009 to July 31, 2019 from the Obstetrics and Gynecology Hospital of Fudan University in China. An external cohort of 100 patients with SBOT was collected from Aug 1, 2009 to Nov 30, 2019 from the Shandong Provincial Hospital in China. The risk factors for the recurrence were identified by multivariate cox analysis. Several computational methods were tested to establish a prediction tool for recurrence. Whole genome sequencing, RNA-seq, metabolomics and lipidomics were used to understand the molecular characteristics of the recurrence of SBOT. Findings: Five factors were significantly correlated with SBOT recurrence in a Han population: micropapillary pattern, advanced stage, FSS, microinvasion, and lymph node invasion. A random forest-based online recurrence prediction tool was established and validated using an internal cohort and an independent external cohort for patients with SBOT. The multi-omics analysis on the original SBOT samples revealed that recurrence is related to metabolic regulation of immunological suppression. Interpretation: Our study identified several important clinical and molecular features of recurrent SBOT. The prediction tool we established could help physicians to estimate the prognosis of patients with SBOT. These findings will contribute to the development of personalised and targeted therapies to improve prognosis. Funding: JL was funded by MOST 2020YFA0803600, 2018YFA0801300, NSFC 32071138, and SKLGE-2118 to Jin Li; JY was funded by the Initial Project for Young and Middle-aged Medical Talents of Wuhan City, Hubei Province ([2014] 41); HH was funded by MOST 2019YFA0801900 and 2020YF1402600 to He Huang; JS was funded by NSFC 22,104,080; CG was funded by Natural Science Foundation of Shanghai 20ZR1408800 and NSFC82171633; BL was funded by Natural Science Foundation of Shanghai 19ZR1406800.

Indexed as

Immunological suppressionPrediction modelSBOT

Identifiers

PMID35434581
PMCPMC9011028
OpenAlexW4224228643

What OpenQuestion holds

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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.