Evidence map›Paper›PMID 37953280›Full record

ArticleBiological procedures online2023

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer.

Bin Luo, Zujun Que, Xinyi Lu, Dan Qi, Zhi Qiao, Yun Yang, Fangfang Qian, Yi Jiang, Yan Li, Ronghu Ke and 5 more

Open access · goldAbstract read
In one paragraph

Article in Biological procedures online, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.0field-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

16 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

15 authors at 5 institutions in 2 countries.

Bin Luo *Clinical Oncology Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Zujun Que *Institute of Oncology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Xinyi Lu *Clinical Oncology Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Dan Qi *Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76502, USA.
Zhi QiaoState Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China.
Yun YangClinical Oncology Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Fangfang QianDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Yi JiangDepartment of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China.
Yan LiClinical Oncology Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China.
Ronghu KeDepartment of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76502, USA.
Xiaoyun ShenPrism Genomic Medicine, Sugar Land, TX, 77478, USA.
Hua Xiao *State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China. huaxiao@sjtu.edu.cn.
Hegen Li *Department of Oncology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 200032, China. shlaogen@163.com.
Erxi Wu *Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX, 76502, USA. erxi.wu@bswhealth.org.
Jianhui Tian *Clinical Oncology Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, China. tjhhawk@shutcm.edu.cn.
Shanghai University of Traditional Chinese Medicine · CNLonghua Hospital Shanghai University of Traditional Chinese Medicine · CNBaylor Scott & White Health · USShanghai Jiao Tong University · CNBaylor College of Medicine · US

Funding

National Natural Science Foundation of China 82104943, 82174245, 82174017, and 21675110the Corbett Estate Fund for Cancer Research 62285-531021-41800, 62285-531021-51800, 62285-531021-61800, and 62285-531021-71800
6 · The paper itself

Abstract

backgroundNon-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes.

methodsHere, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes.

resultsOur study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients.

conclusionsThese findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

Indexed as

BiomarkersExosomesMetastasisNon-small cell lung cancer (NSCLC)Proteomics

Identifiers

PMID37953280
PMCPMC10641949
OpenAlexW4388617176

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.