ArticleBMC genomics2016
AID/APOBEC-network reconstruction identifies pathways associated with survival in ovarian cancer.
Article in BMC genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 15 citations in OpenAlex.
- Singularity and Commonality in Response to SARS-CoV-2 in Lung and Colon Cell Models.International journal of molecular sciences · 2022Article
- Development and validation of a chromatin regulator prognostic signature in colon adenocarcinoma.Frontiers in genetics · 2022Article
- Shaping Immune Responses in the Tumor Microenvironment of Ovarian Cancer.Frontiers in immunology · 2021Review
- The other side of the coin: IgE deficiency, a susceptibility factor for malignancy occurrence.The World Allergy Organization journal · 2021Review
- AID and APOBECs as Multifaceted Intrinsic Virus-Restricting Factors: Emerging Concepts in the Light of COVID-19.Frontiers in immunology · 2021Article
- The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort.PloS one · 2021Article
- Comprehensive Analyses Identify APOBEC3A as a Genomic Instability-Associated Immune Prognostic Biomarker in Ovarian Cancer.Frontiers in immunology · 2021Article
- Identification of a Combined RNA Prognostic Signature in Adenocarcinoma of the Lung.Medical science monitor : international medical journal of experimental and clinical research · 2019Article
- Interrelations of Sphingolipid and Lysophosphatidate Signaling with Immune System in Ovarian Cancer.Computational and structural biotechnology journal · 2019Article
- APOBEC3B up-regulation independently predicts ovarian cancer prognosis: a cohort study.Cancer cell international · 2018Article
- Clinical Significance of Organic Anion Transporting Polypeptide Gene Expression in High-Grade Serous Ovarian Cancer.Frontiers in pharmacology · 2018Article
- [Researcher of the month].Wiener klinische Wochenschrift · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 8 institutions in 3 countries.
Funding
Abstract
backgroundBuilding up of pathway-/disease-relevant signatures provides a persuasive tool for understanding the functional relevance of gene alterations and gene network associations in multifactorial human diseases. Ovarian cancer is a highly complex heterogeneous malignancy in respect of tumor anatomy, tumor microenvironment including pro-/antitumor immunity and inflammation; still, it is generally treated as single disease. Thus, further approaches to investigate novel aspects of ovarian cancer pathogenesis aiming to provide a personalized strategy to clinical decision making are of high priority. Herein we assessed the contribution of the AID/APOBEC family and their associated genes given the remarkable ability of AID and APOBECs to edit DNA/RNA, and as such, providing tools for genetic and epigenetic alterations potentially leading to reprogramming of tumor cells, stroma and immune cells.
resultsWe structured the study by three consecutive analytical modules, which include the multigene-based expression profiling in a cohort of patients with primary serous ovarian cancer using a self-created AID/APOBEC-associated gene signature, building up of multivariable survival models with high predictive accuracy and nomination of top-ranked candidate/target genes according to their prognostic impact, and systems biology-based reconstruction of the AID/APOBEC-driven disease-relevant mechanisms using transcriptomics data from ovarian cancer samples. We demonstrated that inclusion of the AID/APOBEC signature-based variables significantly improves the clinicopathological variables-based survival prognostication allowing significant patient stratification. Furthermore, several of the profiling-derived variables such as ID3, PTPRC/CD45, AID, APOBEC3G, and ID2 exceed the prognostic impact of some clinicopathological variables. We next extended the signature-/modeling-based knowledge by extracting top genes co-regulated with target molecules in ovarian cancer tissues and dissected potential networks/pathways/regulators contributing to pathomechanisms. We thereby revealed that the AID/APOBEC-related network in ovarian cancer is particularly associated with remodeling/fibrotic pathways, altered immune response, and autoimmune disorders with inflammatory background.
conclusionsThe herein study is, to our knowledge, the first one linking expression of entire AID/APOBECs and interacting genes with clinical outcome with respect to survival of cancer patients. Overall, data propose a novel AID/APOBEC-derived survival model for patient risk assessment and reconstitute mapping to molecular pathways. The established study algorithm can be applied further for any biologically relevant signature and any type of diseased tissue.
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.