Evidence map›Paper›PMID 36428585›Full record

ArticleCancers2022

Plasma Extracellular Vesicle Long RNA in Diagnosis and Prediction in Small Cell Lung Cancer.

Chang Liu, Jinying Chen, Jiatao Liao, Yuchen Li, Hui Yu, Xinmin Zhao, Si Sun, Zhihuang Hu, Yao Zhang, Zhengfei Zhu and 3 more

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

Article in Cancers, 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
1.0field-weighted citation impact, top 25% 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, 13 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

13 authors at 2 institutions in 1 country.

Chang LiuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Jinying ChenDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Jiatao LiaoDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Yuchen LiDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Hui YuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Xinmin ZhaoDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Si SunDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Zhihuang HuDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.ORCID 0000-0002-6547-3832
Yao ZhangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Zhengfei ZhuInstitute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Min FanInstitute of Thoracic Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
Shenglin HuangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Jialei WangDepartment of Thoracic Medical Oncology, Fudan University Shanghai Cancer Center, and Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Institutes of Biomedical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Shanghai Medical College of Fudan University · CNFudan University Shanghai Cancer Center · CN

Funding

Collaborative Innovation Cluster Program of Shanghai Municipal Health Commission 2020CXJQ02
6 · The paper itself

Abstract

(1) Introduction: The aim of this study was to identify the plasma extracellular vesicle (EV)-specific transcriptional profile in small-cell lung cancer (SCLC) and to explore the application value of plasma EV long RNA (exLR) in SCLC treatment prediction and diagnosis. (2) Methods: Plasma samples were collected from 57 SCLC treatment-naive patients, 104 non-small-cell lung cancer (NSCLC) patients and 59 healthy participants. The SCLC patients were divided into chemo-sensitive and chemo-refractory groups based on the therapeutic effects. The exLR profiles of the plasma samples were analyzed by high-throughput sequencing. Bioinformatics approaches were used to investigate the differentially expressed exLRs and their biofunctions. Finally, a t-signature was constructed using logistic regression for SCLC treatment prediction and diagnosis. (3) Results: We obtained 220 plasma exLRs profiles in all the participants. Totals of 5787 and 1207 differentially expressed exLRs were identified between SCLC/healthy controls, between the chemo-sensitive/chemo-refractory groups, respectively. Furthermore, we constructed a t-signature that comprised ten exLRs, including EPCAM, CCNE2, CDC6, KRT8, LAMB1, CALB2, STMN1, UCHL1, HOXB7 and CDCA7, for SCLC treatment prediction and diagnosis. The exLR t-score effectively distinguished the chemo-sensitive from the chemo-refractory group (

Indexed as

extracellular vesiclelong RNASCLCt-signature

Identifiers

PMID36428585
PMCPMC9688902
OpenAlexW4308868577

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.