Evidence map›Paper›PMID 38607736›Full record

ReviewAging and disease2024

Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer.

Guanhua Yi, Haixin Luo, Yalin Zheng, Wenjing Liu, Denian Wang, Yong Zhang

Abstract readReview
In one paragraph

Review in Aging and disease, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–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

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
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

6 authors.

Guanhua YiDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Haixin LuoDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Yalin ZhengDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Wenjing LiuDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Denian WangDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.
Yong ZhangDepartment of Pulmonary and Critical Care Medicine and Institutes for Systems Genetics, West China Hospital, Sichuan University, Chengdu 610041, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although significant progress has been made in early lung cancer screening over the past decade, it remains one of the most prevalent and deadliest forms of cancer worldwide. Exosomal proteomics has emerged as a transformative field in lung cancer research, with the potential to redefine diagnostics, prognostic assessments, and therapeutic strategies through the lens of precision medicine. This review discusses recent advances in exosome-related proteomic and glycoproteomic technologies, highlighting their potential to revolutionise lung cancer treatment by addressing issues of heterogeneity, integrating multiomics data, and utilising advanced analytical methods. While these technologies show promise, there are obstacles to overcome before they can be widely implemented, such as the need for standardization, gaps in clinical application, and the importance of dynamic monitoring. Future directions should aim to overcome the challenges to fully utilize the potential of exosomal proteomics in lung cancer. This promises a new era of personalized medicine that leverages the molecular complexity of exosomes for groundbreaking advancements in detection, prognosis, and treatment.

Indexed as

ExosomesLung NeoplasmsProteomicsBiomarkers, TumorHumansPrecision MedicineBiomarkers, Tumor

Identifiers

PMID38607736
PMCPMC11964432

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.