Evidence map›Paper›PMID 36768794›Full record

ArticleInternational journal of molecular sciences2023

A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants.

Mahdieh Labani, Amin Beheshti, Ahmadreza Argha, Hamid Alinejad-Rokny

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Serum lncRNA RAMP2-AS1 Served as a Biomarker of Deep Vein Thrombosis Occurrence and Development in Elderly.Indian journal of hematology & blood transfusion : an official journal of Indian Society of Hematology and Blood Transfusion · 2024
    Article
  2. 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

4 authors.

Mahdieh LabaniBioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
Amin BeheshtiData Analytic Lab, Department of Computing, Macquarie University, Sydney, NSW 2109, Australia.ORCID 0000-0002-5988-5494
Ahmadreza ArghaThe Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.
Hamid Alinejad-RoknyBioMedical Machine Learning Lab (BML), The Graduate School of Biomedical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.

Funding

UNSW Sydney p24333
6 · The paper itself

Abstract

Prostate cancer (PC) is the most frequently diagnosed non-skin cancer in the world. Previous studies have shown that genomic alterations represent the most common mechanism for molecular alterations responsible for the development and progression of PC. This highlights the importance of identifying functional genomic variants for early detection in high-risk PC individuals. Great efforts have been made to identify common protein-coding genetic variations; however, the impact of non-coding variations, including regulatory genetic variants, is not well understood. Identification of these variants and the underlying target genes will be a key step in improving the detection and treatment of PC. To gain an understanding of the functional impact of genetic variants, and in particular, regulatory variants in PC, we developed an integrative pipeline (AGV) that uses whole genome/exome sequences, GWAS SNPs, chromosome conformation capture data, and ChIP-Seq signals to investigate the potential impact of genomic variants on the underlying target genes in PC. We identified 646 putative regulatory variants, of which 30 significantly altered the expression of at least one protein-coding gene. Our analysis of chromatin interactions data (Hi-C) revealed that the 30 putative regulatory variants could affect 131 coding and non-coding genes. Interestingly, our study identified the 131 protein-coding genes that are involved in disease-related pathways, including Reactome and MSigDB, for most of which targeted treatment options are currently available. Notably, our analysis revealed several non-coding RNAs, including

Indexed as

Genome-Wide Association StudyProstatic NeoplasmsChromatinGenetic Predisposition to DiseaseGenomicsHumansMalePolymorphism, Single NucleotideChromatinbiomedical machine learningcopy number variationHi-Cpersonalized medicineprostate cancerregulatory variantsomatic point mutations

Identifiers

PMID36768794
PMCPMC9916892

What Socratic 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 Socratic graph.