Evidence map›Paper›PMID 35723406›Full record

ArticleCurrent issues in molecular biology2022

Personalized 3-Gene Panel for Prostate Cancer Target Therapy.

Sanda Iacobas, Dumitru Andrei Iacobas

Open access · goldAbstract read
In one paragraph

Article in Current issues in molecular biology, 2022. 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
1.5field-weighted citation impact, top 17% 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, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Molecules at Play in Cancer.Current issues in molecular biology · 2023
    Article
  7. Gene Therapeutic Delivery to the Salivary Glands.Advances in experimental medicine and biology · 2023
    Article
  8. 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

2 authors at 2 institutions in 1 country.

Sanda IacobasDepartment of Pathology, New York Medical College, Valhalla, NY 10595, USA.
Dumitru Andrei IacobasPersonalized Genomics Laboratory, Center for Computational Systems Biology, Roy G. Perry College of Engineering, Prairie View A&M University, Prairie View, TX 77446, USA.ORCID 0000-0001-9700-6537
New York Medical College · USPrairie View A&M University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many years and billions spent for research did not yet produce an effective answer to prostate cancer (PCa). Not only each human, but even each cancer nodule in the same tumor, has unique transcriptome topology. The differences go beyond the expression level to the expression control and networking of individual genes. The unrepeatable heterogeneous transcriptomic organization among men makes the quest for universal biomarkers and "fit-for-all" treatments unrealistic. We present a bioinformatics procedure to identify each patient's unique triplet of PCa Gene Master Regulators (GMRs) and predict consequences of their experimental manipulation. The procedure is based on the Genomic Fabric Paradigm (GFP), which characterizes each individual gene by the independent expression level, expression variability and expression coordination with each other gene. GFP can identify the GMRs whose controlled alteration would selectively kill the cancer cells with little consequence on the normal tissue. The method was applied to microarray data on surgically removed prostates from two men with metastatic PCas (each with three distinct cancer nodules), and DU145 and LNCaP PCa cell lines. The applications verified that each PCa case is unique and predicted the consequences of the GMRs' manipulation. The predictions are theoretical and need further experimental validation.

Indexed as

AP5M1BAIAP2L1CRISPRENTPD2LOC145474master regulatorMTORPRRG1VIMWFDC3

Identifiers

PMID35723406
PMCPMC8929157
OpenAlexW4206136164

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.