Evidence map›Paper›PMID 34189028›Full record

ArticleJournal of bone oncology2021

A predictive biomarker panel for bone metastases: Liquid biopsy approach.

Kinjal P Bhadresha, Maulikkumar Patel, Nayan K Jain, Rakesh M Rawal

Open access · goldAbstract read
In one paragraph

Article in Journal of bone oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Observational
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Liquid biopsies in primary and secondary bone cancers.Cancer drug resistance (Alhambra, Calif.) · 2022
    Review
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

4 authors at 1 institution in 1 country.

Kinjal P BhadreshaDepartment of Life Science, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Maulikkumar PatelDepartment of Botany, Bioinformatics and Climate Change Impacts Management School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Nayan K JainDepartment of Life Science, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Rakesh M RawalDepartment of Life Science, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Gujarat University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bone metastases is one of the common metastatic site and leading cause of cancer-related mortality in progressive cancer patients. The purpose of the present study is to establish a liquid biopsy based multi-gene classifier and associated signalling pathways for early diagnosis of bone metastases. We used publically available microarray datasets and analysed them in a platform/chip-specific manner using GeneSpring software. Analyses of gene expression datasets identified 15 consistently over-expressed genes with statistical significance. Further, expression profile of same set of 15 genes were compared in breast and lung cancer exosome derived mRNA with (n = 10) and without (n = 10) bone metastases against healthy controls. ROC curve analysis performed individually for all the 15 genes shortlisted the 5 most relevant genes with significant sensitivity and specificity in both cancers. This liquid biopsy-based bone metastases predictor using multi-gene panel is a unique approach with potential clinical applications for effective management of aggressive cancers.

Indexed as

Bone metastasesExosomeLiquid biopsyMeta-analysis

Identifiers

PMID34189028
PMCPMC8220227
OpenAlexW3166051057

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.