Evidence map›Paper›PMID 28851367›Full record

ReviewMolecular cancer2017

Role of exosomal proteins in cancer diagnosis.

Weihua Li, Chuanyun Li, Tong Zhou, Xiuhong Liu, Xiaoni Liu, Xiuhui Li, Dexi Chen

Abstract readReview
In one paragraph

Review in Molecular cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 230 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
230citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

230 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. CRISPR/Cas13a: Compensatory Target Activation Mechanism.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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170 more citing papers are in PubMed but not listed here.

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

7 authors.

Weihua LiYouAn Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-8560-4644
Chuanyun LiYouAn Hospital, Capital Medical University, Beijing, China.
Tong ZhouXinjiang Medical University, Wulumuqi, China.
Xiuhong LiuBeijing Institute of Hepatology, Beijing, China.
Xiaoni LiuBeijing Institute of Hepatology, Beijing, China.
Xiuhui LiYouAn Hospital, Capital Medical University, Beijing, China. lixiuhui@sohu.com.
Dexi ChenBeijing Institute of Hepatology, Beijing, China. dexichen@ccmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomes are emerging as a new type of cancer biomarkers. Exosome is a bilayered nano-sized vesicle secreted by various living cells in all body fluids. Based on the expanding albeit incomplete knowledge of their biogenesis, secretion by cells and cancer cell-specific molecular and genetic contents, exosomes are viewed as promising, clinically-relevant surrogates of cancer progression and response to therapy. Preliminary proteomic, genetic and functional profiling of cancer cell-derived or cancer plasma-derived exosomes confirms their unique characteristics. Alterations in protein or nucleic acid profiles of exosomes in plasma correlate with pathological processes of many diseases including cancer. However, previous studies on exosome application in cancer diagnosis and treatment mainly focussed on miRNAs. With the development of rapid large-scale production, purification, extraction and screening of exosomal contents, exosomal protein application can be explored for early stage cancer diagnosis, monitoring and prognosis evaluation. Here, we summarized the recent developments in application of exosomal proteins for cancer diagnosis.

Indexed as

Biomarkers, TumorExosomesNeoplasm ProteinsNeoplasmsHumansBiomarkers, TumorNeoplasm ProteinsBiomarkerCancerDiagnoseExosome

Identifiers

PMID28851367
PMCPMC5576100

What OpenQuestion holds

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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.