ReviewCancers2022
Are Transcription Factors Plausible Oncotargets for Triple Negative Breast Cancers?
Review in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- POU6F1 Expression Predicts Favorable Prognosis in Lung Adenocarcinoma: Validation Using Patient Cohort and TCGA Data.Current issues in molecular biology · 2026Article
- Targeting SOX9: designing a novel vaccine against triple-negative breast cancer.Scientific reports · 2025Article
- Computer-Aided Drug Design Across Breast Cancer Subtypes: Methods, Applications and Translational Outlook.International journal of molecular sciences · 2025Review
- Latest Therapeutical Approaches for Triple-Negative Breast Cancer: From Preclinical to Clinical Research.International journal of molecular sciences · 2024Review
- Article
- Applications of CRISPR Technology to Breast Cancer and Triple Negative Breast Cancer Research.Cancers · 2023Review
- Application of Novel Transcription Factor Machine Learning Model and Targeted Drug Combination Therapy Strategy in Triple Negative Breast Cancer.International journal of molecular sciences · 2023Article
- Designing a novel SOX9 based multi-epitope vaccine to combat metastatic triple-negative breast cancer using immunoinformatics approach.Molecular diversity · 2023Article
- Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Breast cancer (BC) is the most diagnosed cancer worldwide and one of the main causes of cancer deaths. BC is a heterogeneous disease composed of different BC intrinsic subtypes such as triple-negative BC (TNBC), which is one of the most aggressive subtypes and which lacks a targeted therapy. Recent comprehensive analyses across cell types and cancer types have outlined a vast network of protein-protein associations between transcription factors (TFs). Not surprisingly, protein-protein networks central to oncogenesis and disease progression are highly altered during TNBC pathogenesis and are responsible for the activation of oncogenic programs, such as uncontrollable proliferation, epithelial-to-mesenchymal transition (EMT) and stemness. From the therapeutic viewpoint, inhibiting the interactions between TFs represents a very significant challenge, as the contact surfaces of TFs are relatively large and featureless. However, promising tools have emerged to offer a solution to the targeting problem. At the clinical level, some TF possess diagnostic and prognostic value in TNBC. In this review, we outline the recent advances in TFs relevant to TNBC growth and progression. Moreover, we highlight different targeting approaches to inhibit these TFs. Furthermore, the validity of such TFs as clinical biomarkers has been explored. Finally, we discuss how research is likely to evolve in the field.
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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.