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Patient survival from head and neck squamous cell carcinoma (HNSCC), the seventh most common cause of cancer, has not markedly improved in recent years despite the approval of targeted therapies and immunotherapy agents. Precision medicine approaches that seek to individualise therapy through the use of predictive biomarkers and stratification strategies offer opportunities to improve therapeutic success in HNSCC. To enable precision medicine of HNSCC, an understanding of the microenvironment that influences tumour growth and response to therapy is required alongside research tools that recapitulate the features of human tumours. In this review, we highlight the importance of the tumour microenvironment in HNSCC, with a focus on tumour hypoxia, and discuss the fidelity of patient-derived xenograft and organoids for modelling human HNSCC and response to therapy. We describe the benefits of patient-derived models over alternative preclinical models and their limitations in clinical relevance and how these impact their utility in precision medicine in HNSCC for the discovery of new therapeutic agents, as well as predictive biomarkers to identify patients' most likely to respond to therapy.
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http://dx.doi.org/10.3390/cancers12123743 | DOI Listing |
Genome Biol
September 2025
National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.
Background: Soil salinization represents a critical global challenge to agricultural productivity, profoundly impacting crop yields and threatening food security. Plant salt-responsive is complex and dynamic, making it challenging to fully elucidate salt tolerance mechanism and leading to gaps in our understanding of how plants adapt to and mitigate salt stress.
Results: Here, we conduct high-resolution time-series transcriptomic and metabolomic profiling of the extremely salt-tolerant maize inbred line, HLZY, and the salt-sensitive elite line, JI853.
Geroscience
September 2025
Department of Urology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
This study aims to investigate the predictive value of combined phenotypic age and phenotypic age acceleration (PhenoAgeAccel) for benign prostatic hyperplasia (BPH) and develop a machine learning-based risk prediction model to inform precision prevention and clinical management strategies. The study analyzed data from 784 male participants in the US National Health and Nutrition Examination Survey (NHANES, 2001-2008). Phenotypic age was derived from chronological age and nine serum biomarkers.
View Article and Find Full Text PDFClin Transl Oncol
September 2025
Department of Radiation Oncology, Vithas La Milagrosa University Hospital, Madrid, 28010, Spain.
This narrative review analyzes current evidence comparing single-session and two-session approaches in Stereotactic Body Radiation Therapy (SBRT) and high-dose-rate (HDR) brachytherapy for localized prostate cancer. These ultra-hypofractionated strategies deliver high-precision ablative doses while minimizing exposure to normal tissues. SBRT regimens with fewer than five fractions show tumor control comparable to conventional treatments, offering reduced treatment burden and increased convenience.
View Article and Find Full Text PDFBariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence.
View Article and Find Full Text PDFAesthetic Plast Surg
September 2025
Department of Plastic and Cosmetic Surgery, Tongji Hospital, School of Medicine, Tongji University, No.389 Xincun Road, Shanghai, 200092, China.
Background: The integration of digital tools in aesthetic medicine has enhanced the precision of facial feature analysis. Using concepts like the Golden Ratio, these technologies enable more objective assessments of facial proportions and symmetry. The beauty scanner-face analyzer (BS-FA) app offers a digital approach to evaluate geometric proportions and facial alignment, providing valuable data for preoperative planning in plastic surgery and aesthetic treatments.
View Article and Find Full Text PDF