ReviewCancer management and research2018
Predicting the response to neoadjuvant therapy for early-stage breast cancer: tumor-, blood-, and imaging-related biomarkers.
Review in Cancer management and research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04770272 (An Adaptive Randomized Neoadjuvant Two Arm Trial in Triple-negative Breast Cancer Comparing a Mono Atezolizumab Window Followed by a Atezolizumab - CTX Therapy With Atezolizumab - CTX Therapy), which is not on this map. Cited by 34 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.
An Adaptive Randomized Neoadjuvant Two Arm Trial in Triple-negative Breast Cancer Comparing a Mono Atezolizumab Window Followed by a Atezolizumab - CTX Therapy With Atezolizumab - CTX Therapy (neoMono)
Who cites it
34 citing papers in PubMed.
- Article
- Multimodal Imaging-Based Prediction of Pathological Complete Response After Neoadjuvant Chemotherapy for Breast Cancer.Journal of imaging informatics in medicine · 2026Article
- Ensemble Machine Learning on Bulk RNA-Seq Identifies 17-Gene Signature Predicting Neoadjuvant Chemotherapy Response in Breast Cancer.Current issues in molecular biology · 2026Article
- Dynamics of the intratumoural microbiome across malignant transformation and treatment in breast cancer.Clinical and translational medicine · 2025Article
- Markers of Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer: New in Molecular Oncology.Asian Pacific journal of cancer prevention : APJCP · 2024Review
- Development of a clinical nomogram for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer.World journal of gastrointestinal surgery · 2024Article
- Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer.NPJ breast cancer · 2024Article
- The cellular composition of the tumor microenvironment is an important marker for predicting therapeutic efficacy in breast cancer.Frontiers in immunology · 2024Review
- Inter-reader agreement of breast magnetic resonance imaging and contrast-enhanced mammography in breast cancer diagnosis: a multi-reader retrospective study.Breast cancer research and treatment · 2023Article
- Predictive significance of HIF-1α, Snail, and PD-L1 expression in breast cancer.Clinical and experimental medicine · 2023Article
- Tumor immune microenvironment components and the other markers can predict the efficacy of neoadjuvant chemotherapy for breast cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Review
- How Radiomics Can Improve Breast Cancer Diagnosis and Treatment.Journal of clinical medicine · 2023Review
- Risk model and factors for prediction of response to neoadjuvant chemotherapy in patients with advanced gastric cancer-a two-center cohort study.BMC cancer · 2023Article
- Diagnostic performance of image-guided vacuum-assisted breast biopsy after neoadjuvant therapy for breast cancer: prospective pilot study.The British journal of surgery · 2023Article
- Precision Medicine in Breast Cancer: Do MRI Biomarkers Identify Patients Who Truly Benefit from the Oncotype DX Recurrence ScoreDiagnostics (Basel, Switzerland) · 2022Article
- Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study.BMC medical imaging · 2022Article
- Review
- Tumor-stroma ratio is associated with Miller-Payne score and pathological response to neoadjuvant chemotherapy in HER2-negative early breast cancer.International journal of cancer · 2021Article
- Article
- Recent Radiomics Advancements in Breast Cancer: Lessons and Pitfalls for the Next Future.Current oncology (Toronto, Ont.) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.
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