ReviewFrontiers in medicine2017
Tumor Heterogeneity in Breast Cancer.
Review in Frontiers in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06097156 (Feasibility Evaluation of See.d Pre-Analytical Platform Performance), which is not on this map. Cited by 333 papers.
What it found
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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.
Feasibility Evaluation of See.d Pre-Analytical Platform Performance: From Whole Blood to Plasma and SBS Slides for Liquid Biopsy Applications
Who cites it
333 citing papers in PubMed, 550 citations in OpenAlex.
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- Performance of MRI-based deep learning models in differentiation of triple negative breast cancer from other breast cancer subtypes: A systematic review and meta-analysis.European journal of radiology open · 2026Article
- Breast cancer-associated fibroblast-derived exosomal miR-1290 promotes triple-negative breast cancer cell proliferation.Signal transduction and targeted therapy · 2026Article
- Patient characteristics, treatment patterns, and survival across estrogen receptor expression subgroups in HER2-negative breast cancer: a population-based cohort study.The Lancet regional health. Europe · 2026Article
- Postoperative cutaneous metastasis of breast cancer with phenotypic conversion to triple-negative subtype: A case report.Medicine · 2026Article
- Amine-Functionalized and Gold-Decorated Amine-Functionalized TiOInternational journal of molecular sciences · 2026Article
- Crossing paths: historical and philosophical perspectives on cancer and diabetes classifications.History and philosophy of the life sciences · 2026Article
- Research advances in aptamers in the diagnosis and treatment of breast cancer (Review).International journal of oncology · 2026Review
- Conserved mRNA expression patterns of the Klotho family in canine mammary tumors and human breast cancer.Scientific reports · 2026Article
- Artificial intelligence in cancer diagnosis and therapy using sex and gender as precision biomarkers.Discover oncology · 2026Review
- Discovery and Evaluation of Biomarkers for Triple-Negative Breast Cancer Subtypes Uncovers Patient Stratification and Targeted Therapeutic Strategies.Cancer research · 2026Article
- Higher Levels ofMedical sciences (Basel, Switzerland) · 2026Article
- Multimodal machine learning integrates clinical and comorbidity data to predict breast cancer prognosis and treatment outcomes.Scientific reports · 2026Article
- The Selective Estrogen Receptor Degrader ZN-c5 Has Broad Antitumor Activity in Wild-Type and Mutant ER-Positive Breast Cancer Models.Molecular cancer therapeutics · 2026Article
- Natural Killer Cell Phenotype and Function as a Predictive Factor for Treatment Response to Neoadjuvant Therapy in Breast Cancer Patients.International journal of molecular sciences · 2026Article
- The effect of the number of negative lymph nodes removed during surgery on the survival and recurrence rates of patients with breast cancer after surgery.BMC surgery · 2026Article
- Integration of tumor microenvironment and metabolic signatures reveals TMPI-defined prognostic and immunotherapy-relevant phenotypes in breast cancer.Frontiers in pharmacology · 2026Article
- Engineering Complexity: Advances in 3D Breast Cancer Models for Precision Oncology.Advanced healthcare materials · 2026Review
- Cell-cell junction gene signatures as subtype-specific prognostic biomarkers in breast cancer.PloS one · 2026Article
273 more citing papers are in PubMed but not listed here.
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
Breast cancer is a heterogeneous disease and differs greatly among different patients (intertumor heterogeneity) and even within each individual tumor (intratumor heterogeneity). Clinical and morphologic intertumor heterogeneity is reflected by staging systems and histopathologic classification of breast cancer. Heterogeneity in the expression of established prognostic and predictive biomarkers, hormone receptors, and human epidermal growth factor receptor 2 oncoprotein is the basis for targeted treatment. Molecular classifications are indicators of genetic tumor heterogeneity, which is probed with multigene assays and can lead to improved stratification into low- and high-risk groups for personalized therapy. Intratumor heterogeneity occurs at the morphologic, genomic, transcriptomic, and proteomic levels, creating diagnostic and therapeutic challenges. Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Despite the improved knowledge of the complex genetic and phenotypic features underpinning tumor heterogeneity, there has been only limited advancement in diagnostic, prognostic, or predictive strategies for breast cancer. The current guidelines for reporting of biomarkers aim to maximize patient eligibility for targeted therapy, but do not take into account intratumor heterogeneity. The molecular classification of breast cancer is not implemented in routine clinical practice. Additional studies and in-depth analysis are required to understand the clinical significance of rapidly accumulating data. This review highlights inter- and intratumor heterogeneity of breast carcinoma with special emphasis on pathologic findings, and provides insights into the clinical significance of molecular and cellular mechanisms of heterogeneity.
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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.