ArticleCarcinogenesis2018
Identification of cancer biomarkers of prognostic value using specific gene regulatory networks (GRN): a novel role of RAD51AP1 for ovarian and lung cancers.
Article in Carcinogenesis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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.
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.
Who cites it
34 citing papers in PubMed, 53 citations in OpenAlex.
- Biochemical and Comparative Proteomic Analyses Delineate the Anti-Ovarian Carcinogenic Roles of Modified Calycosin.Food science & nutrition · 2026Article
- Identification of Proteins Associated with Ovarian Cancer Chemotherapy Resistance Using MALDI-MSI.International journal of molecular sciences · 2025Article
- Type XII collagen is elevated in serum from patients with solid tumors: a non-invasive biomarker of activated fibroblasts.Clinical and experimental medicine · 2024Article
- Genomic Alterations Affecting Competitive Endogenous RNAs (ceRNAs) and Regulatory Networks (ceRNETs) with Clinical Implications in Triple-Negative Breast Cancer (TNBC).International journal of molecular sciences · 2024Review
- [Research Advances of RAD51AP1 in Tumor Progression and Drug Resistance].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023Review
- Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells.Biomedicines · 2022Article
- Odd-skipped related 1 plays a tumor suppressor role in ovarian cancer via promoting follistatin-like protein 1 transcription.Human cell · 2022Article
- Knockdown of RAD51AP1 suppressed cell proliferation and invasion in esophageal squamous cell carcinoma.Discover oncology · 2022Article
- Differential Expression of RAD51AP1 in Ovarian Cancer: Effects of siRNA In Vitro.Journal of personalized medicine · 2022Article
- Systematic pan-cancer analysis showed that RAD51AP1 was associated with immune microenvironment, tumor stemness, and prognosis.Frontiers in genetics · 2022Article
- RAD51AP1 and RAD54L Can Underpin Two Distinct RAD51-Dependent Routes of DNA Damage RepairFrontiers in cell and developmental biology · 2022Article
- Preclinical Studies on the Effect of Rucaparib in Ovarian Cancer: Impact of BRCA2 Status.Cells · 2021Article
- Review
- RAD51AP1 promotes progression of ovarian cancer via TGF-β/Smad signalling pathway.Journal of cellular and molecular medicine · 2021Article
- Six Novel Biomarkers for Diagnosis and Prognosis of Esophageal squamous cell carcinoma: validated by scRNA-seq and qPCR.Journal of Cancer · 2021Article
- Article
- Development of a novel embryonic germline gene-related prognostic model of lung adenocarcinoma.PeerJ · 2021Article
- Identification and validation of core genes for serous ovarian adenocarcinoma via bioinformatics analysis.Oncology letters · 2020Article
- Investigating the Role of Telomere and Telomerase Associated Genes and Proteins in Endometrial Cancer.Methods and protocols · 2020Article
- Integrated bioinformatics analysis of expression and gene regulation network of COL12A1 in colorectal cancer.Cancer medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 6 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
To date, microarray analyses have led to the discovery of numerous individual 'molecular signatures' associated with specific cancers. However, there are serious limitations for the adoption of these multi-gene signatures in the clinical environment for diagnostic or prognostic testing as studies with more power need to be carried out. This may involve larger richer cohorts and more advanced analyses. In this study, we conduct analyses-based on gene regulatory network-to reveal distinct and common biomarkers across cancer types. Using microarray data of triple-negative and medullary breast, ovarian and lung cancers applied to a combination of glasso and Bayesian networks (BNs), we derived a unique network-containing genes that are uniquely involved: small proline-rich protein 1A (SPRR1A), follistatin like 1 (FSTL1), collagen type XII alpha 1 (COL12A1) and RAD51 associated protein 1 (RAD51AP1). RAD51AP1 and FSTL1 are significantly overexpressed in ovarian cancer patients but only RAD51AP1 is upregulated in lung cancer patients compared with healthy controls. The upregulation of RAD51AP1 was mirrored in the bloods of both ovarian and lung cancer patients, and Kaplan-Meier (KM) plots predicted poorer overall survival (OS) in patients with high expression of RAD51AP1. Suppression of RAD51AP1 by RNA interference reduced cell proliferation in vitro in ovarian (SKOV3) and lung (A549) cancer cells. This effect appears to be modulated by a decrease in the expression of mTOR-related genes and pro-metastatic candidate genes. Our data describe how an initial in silico approach can generate novel biomarkers that could potentially support current clinical practice and improve long-term outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.