Evidence map›Paper›PMID 39068454›Full record

ArticleJournal of ovarian research2024

Unveiling G-protein coupled receptors as potential targets for ovarian cancer nanomedicines: from RNA sequencing data analysis to in vitro validation.

Riya Khetan, Preethi Eldi, Noor A Lokman, Carmela Ricciardelli, Martin K Oehler, Anton Blencowe, Sanjay Garg, Katherine Pillman, Hugo Albrecht

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of ovarian research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

9 authors.

Riya KhetanCentre of Pharmaceutical Innovation, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia.
Preethi EldiUniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia.
Noor A LokmanDiscipline of Obstetrics and Gynaecology, Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, South Australia, 5000, Australia.
Carmela RicciardelliDiscipline of Obstetrics and Gynaecology, Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, South Australia, 5000, Australia.
Martin K OehlerDiscipline of Obstetrics and Gynaecology, Adelaide Medical School, Robinson Research Institute, University of Adelaide, Adelaide, South Australia, 5000, Australia.
Anton BlencoweApplied Chemistry and Translational Biomaterials Group, Centre of Pharmaceutical Innovation, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia.
Sanjay GargCentre of Pharmaceutical Innovation, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia.
Katherine PillmanCentre for Cancer Biology, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia. katherine.pillman@unisa.edu.au.
Hugo AlbrechtCentre of Pharmaceutical Innovation, UniSA Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, 5000, Australia. hugo.albrecht@unisa.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic heterogeneity in ovarian cancer indicates the need for personalised treatment approaches. Currently, very few G-protein coupled receptors (GPCRs) have been investigated for active targeting with nanomedicines such as antibody-conjugated drugs and drug-loaded nanoparticles, highlighting a neglected potential to develop personalised treatment. To address the genetic heterogeneity of ovarian cancer, a future personalised approach could include the identification of unique GPCRs expressed in cancer biopsies, matched with personalised GPCR-targeted nanomedicines, for the delivery of lethal drugs to tumour tissue before, during and after surgery. Here we report on the systematic analysis of public ribonucleic acid-sequencing (RNA-seq) gene expression data, which led to prioritisation of 13 GPCRs as candidates with frequent overexpression in ovarian cancer tissues. Subsequently, primary ovarian cancer cells derived from ascites and ovarian cancer cell lines were used to confirm frequent gene expression for the selected GPCRs. However, the expression levels showed high variability within our selection of samples, therefore, supporting and emphasising the need for the future development of case-to-case personalised targeting approaches.

Indexed as

NanomedicineOvarian NeoplasmsReceptors, G-Protein-CoupledSequence Analysis, RNACell Line, TumorFemaleGene Expression Regulation, NeoplasticHumansReceptors, G-Protein-CoupledDrug deliveryGPCRNanomedicineOvarian cancerPersonalised medicineRNA-seq

Identifiers

PMID39068454
PMCPMC11282829

What OpenQuestion holds

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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.