ArticleOncology letters2012
Differential proteomic analysis of pathway biomarkers in human breast cancer by integrated bioinformatics.
Article in Oncology letters, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 10 citations in OpenAlex.
- Genetic evidence for causal roles of circulating proteins on breast cancer susceptibility.iScience · 2026Article
- Multiomics insights on the onset, progression, and metastatic evolution of breast cancer.Frontiers in oncology · 2023Review
- Identification of Key Genes and Key Pathways in Breast Cancer Based on Machine Learning.Medical science monitor : international medical journal of experimental and clinical research · 2022Article
- Breast cancer in the era of integrating "Omics" approaches.Oncogenesis · 2022Review
- Screening and functional analysis of a differential protein profile of human breast cancer.Oncology letters · 2014Article
- Functional analysis of human cancer-associated genes and their association with the testes and epididymis.Oncology letters · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this study was to better understand the altered functional modules in breast cancer at pathway and network levels. An integrated bioinformatics analysis of differentially expressed proteins in human breast cancer was performed. Breast cancer protein profiles were constructed by data mining proteins in literature and public databases, including 1031 proteins with 153 secretory and 69 cell surface proteins. An experimental investigation was performed by two-dimensional electrophoresis, and 4 proteins were further validated by western blotting. Enriched bioinformatics functions were clustered. This study may be used as a reference in further studies to help identify the underlying biological interactions associated with breast cancer and discover potential cancer targets.
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.