ArticleFrontiers in cell and developmental biology2021
Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer.
Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 14 citations in OpenAlex.
- Genetic and Pharmacologic Targeting of Eya3 in Macrophages Drives Anti-Tumor Immunity in Triple-Negative Breast Cancer.bioRxiv : the preprint server for biology · 2026Article
- Comprehensive insight into nimbolide response against breast cancer treatment: present evidence, emerging strategy and future direction.Molecular biology reports · 2026Review
- A comparative analysis of mutational profiles between triple-negative breast cancer and non-triple-negative breast cancer.Discover oncology · 2026Article
- Integrative systematic review and transcriptomic -machine learning analysis of molecular signatures in metaplastic breast cancer.Ecancermedicalscience · 2026Article
- RIOK1: A Novel Oncogenic Driver in Hepatocellular Carcinoma.Cancer medicine · 2025Article
- Mechanisms and Therapeutic Strategies to Overcome Immune Checkpoint Inhibitor Resistance in Melanoma, Head and Neck, and Triple-Negative Breast Cancers.Journal of cellular immunology · 2025Article
- FEN1 Inhibition as a Potential Novel Targeted Therapy against Breast Cancer and the Prognostic Relevance of FEN1.International journal of molecular sciences · 2024Article
- Emerging role and function of SPDL1 in human health and diseases.Open medicine (Warsaw, Poland) · 2024Review
- The NF-κB Transcriptional Network Is a High-Dose Vitamin C-Targetable Vulnerability in Breast Cancer.Biomedicines · 2023Review
- Genome instability-derived genes as a novel prognostic signature for lung adenocarcinoma.Frontiers in cell and developmental biology · 2023Article
- Prognostic Capability of TNBC 3-Gene Score among Triple-Negative Breast Cancer Subtypes.Cancers · 2022Article
- SPDL1 Is an Independent Predictor of Patient Outcome in Colorectal Cancer.International journal of molecular sciences · 2022Article
- A novel risk model based on immune response predicts clinical outcomes and characterizes immunophenotypes in triple-negative breast cancer.American journal of cancer research · 2022Article
- Genomic Instability-Related LncRNA Signature Predicts the Prognosis and HighlightsFrontiers in oncology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTriple-negative breast cancer (TNBC) is an aggressive disease. Recent studies have identified genome instability-derived genes for patient outcomes. However, most of the studies mainly focused on only one or a few genome instability-related genes. Prognostic potential and clinical significance of genome instability-associated genes in TNBC have not been well explored.
methodsIn this study, we developed a computational approach to identify TNBC prognostic signature. It consisted of (1) using somatic mutations and copy number variations (CNVs) in TNBC to build a binary matrix and identifying the top and bottom 25% mutated samples, (2) comparing the gene expression between the top and bottom 25% samples to identify genome instability-related genes, and (3) performing univariate Cox proportional hazards regression analysis to identify survival-associated gene signature, and Kaplan-Meier, log-rank test, and multivariate Cox regression analyses to obtain overall survival (OS) information for TNBC outcome prediction.
resultsFrom the identified 111 genome instability-related genes, we extracted a genome instability-derived gene signature (GIGenSig) of 11 genes. Through survival analysis, we were able to classify TNBC cases into high- and low-risk groups by the signature in the training dataset (log-rank test
conclusionThe identified novel signature provides a better understanding of genome instability in TNBC and can be applied as prognostic markers for clinical TNBC management.
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.