A5014416150- Breast Cancer Treatment Studies
- Estrogen and related hormone effects
- Ultrasound Imaging and Elastography
- Cancer Risks and Factors
- Ubiquitin and proteasome pathways
- Ferroptosis and cancer prognosis
- Inflammatory mediators and NSAID effects
- HER2/EGFR in Cancer Research
- Breast Lesions and Carcinomas
- MRI in cancer diagnosis
- Receptor Mechanisms and Signaling
- Advanced Radiotherapy Techniques
- Protein Degradation and Inhibitors
- Cancer Immunotherapy and Biomarkers
Dalian Medical University
2022-2024
Second Affiliated Hospital of Dalian Medical University
2022-2024
First Affiliated Hospital of Xi'an Jiaotong University
2024
Dalian University
2021
While large-scale artificial intelligence (AI) models for protein structure prediction and design are advancing rapidly, the translation of deep learning practical macromolecular drug development remains limited. This investigation aims to bridge this gap by combining cutting-edge methodologies create a novel peptide-based PROTAC paradigm. Using ProteinMPNN RFdiffusion, we identified binding peptides androgen receptor (AR) Von Hippel-Lindau (VHL), followed computational modeling with...
To the Editor: De-escalating treatment of ductal carcinoma in situ (DCIS) breast has been investigated recent years. A 5-year adjuvant endocrine therapy (AET) regimen is recommended for hormone receptor-positive DCIS. Selective estrogen receptor modulators (such as commonly used tamoxifen and toremifene) aromatase inhibitors (AIs) are currently AET drugs. However, long-term accompanied by severe side effects such menopausal symptoms, endometrial carcinoma, cardiovascular events, venous...
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment early breast cancer (EBC). Therefore, this study aims noninvasively and predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, create a nomogram construct machine learning model. This retrospective included 304 EBC patients recruited from multiple centers. All enrollees had...
Tumor microenvironment (TME) status is closely related to breast cancer (BC) prognosis and systemic therapeutic effects. However, date studies have not considered the interactions of immune stromal cells at gene expression level in BC as a whole. Herein, we constructed predictive model, for adjuvant decision-making, by mining TME molecular information patient drug treatment sensitivity.Clinical profiles were extracted from The Cancer Genome Atlas (TCGA), with patients divided into high-...
To determine the feasibility of predicting rate an axillary lymph node pathological complete response (apCR) using nomogram and machine learning methods.A total 247 patients with early breast cancer (eBC), who underwent neoadjuvant therapy (NAT) were included retrospectively. We compared pre- post-NAT ultrasound information calculated maximum diameter change primary lesion (MDCPL): [(pre-NAT - preoperative lesion)/pre-NAT lesion] described score (LNS) (1): unclear border (2), irregular...
Background: De-escalating treatment of ductal carcinoma in situ (DCIS) the breast has been investigated recent years. A 5-year adjuvant endocrine therapy (AET) regimen is standard for hormone receptor-positive DCIS. In TAM-01 trial, low-dose tamoxifen (5 mg daily) 3 years was safe and effective preventing local contralateral recurrence compared to placebo. this multicenter real-world study we whether short-duration ET at a dosage as longer duration patients with DCIS breast.Methods: We...