ArticleClinical cancer research : an official journal of the American Association for Cancer Research2020
Genome Instability Profiles Predict Disease Outcome in a Cohort of 4,003 Patients with Breast Cancer.
Article in Clinical cancer research : an official journal of the American Association for Cancer Research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 10 citations in OpenAlex.
- Genome stability disrupted by the circRBM39(4,5,6)-RPA2 axis represses breast tumorigenesis.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Comprehensive analysis of ACKR family members in breast cancer using prognostic values.Oncology letters · 2023Article
- S-phase fraction, lymph node status and disease staging as the main prognostic factors to differentiate between young and older patients with invasive breast carcinoma.Oncology letters · 2022Article
- CLEC10A can serve as a potential therapeutic target and its level correlates with immune infiltration in breast cancer.Oncology letters · 2022Article
- Unique ER PR expression pattern in breast cancers with CHEK2 mutation: a hormone receptor and HER2 analysis based on germline cancer predisposition genes.Breast cancer research : BCR · 2022Article
- Article
- Identification of Mutator-Derived lncRNA Signatures of Genomic Instability for Promoting the Clinical Outcome in Hepatocellular Carcinoma.Computational and mathematical methods in medicine · 2021Article
- High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients.The American journal of pathology · 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
9 authors at 3 institutions in 3 countries.
Funding
Abstract
purposeThe choice of therapy for patients with breast cancer is often based on clinicopathologic parameters, hormone receptor status, and EXPERIMENTAL
designWe retrospectively assessed clinical data of 4,003 patients with breast cancer with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves, and multivariable Cox proportional hazard models, to ascertain the potential of standard clinicopathologic data and genome instability profiles as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment.
resultsIn Cox regression analyses, two parameters of the genome instability profiles, the S-phase fraction and the stemline scatter index, emerged as independent predictors in premenopausal women, outperforming all clinicopathologic parameters. In postmenopausal women, age and hormone receptor status were the predominant prognostic factors. However, by including S-phase fraction and 2.5c exceeding rate, we could improve disease outcome prediction in pT1 tumors irrespective of the lymph node status. In pT3-pT4 tumors, a higher S-phase fraction led to poorer prognosis. In patients who received adjuvant endocrine therapy, chemotherapy or radiotherapy, or a combination, the ploidy profiles improved prognostication.
conclusionsGenome instability profiles predict disease outcome in patients with breast cancer independent of clinicopathologic parameters. This applies especially to premenopausal patients. In patients receiving adjuvant therapy, the profiles improve identification of high-risk patients.
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.