ReviewFrontiers in molecular biosciences2022
'Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics'.
Review in Frontiers in molecular biosciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Decoding breast cancer: insights into molecular pathways & therapeutic approaches.Discover oncology · 2025Review
- Review
- Oxygen deprivation in breast cancer: mechanisms, pathways, and implications.Annals of medicine and surgery (2012) · 2025Review
- Targeting the MAPK signaling pathway: implications and prospects of flavonoids in 3P medicine as modulators of cancer cell plasticity and therapeutic resistance in breast cancer patients.The EPMA journal · 2025Article
- Radiogenomic Landscape of Metastatic Endocrine-Positive Breast Cancer Resistant to Aromatase Inhibitors.Cancers · 2025Review
- Genetic advancements in breast cancer treatment: a review.Discover oncology · 2025Review
- Autophagy stimulation influenced the angiogenesis and metastasis behavior of human triple-negative breast cancer cells.BioImpacts : BI · 2025Article
- Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.Clinical Medicine Insights. Oncology · 2025Review
- Precision medicine in breast cancer (Review).Molecular and clinical oncology · 2024Review
- Implications of Agile Values in Software Engineering for Agility in Breast Cancer Treatment: Protocol for a Comparative Study.JMIR research protocols · 2023Article
- Omics Technologies Improving Breast Cancer Research and Diagnostics.International journal of molecular sciences · 2023Review
- Molecular mechanisms of multi-omic regulation in breast cancer.Frontiers in oncology · 2023Review
- Morphological Dependence of Breast Cancer Cell Responses to Doxorubicin on Micropatterned Surfaces.Polymers · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.
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.