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Leukemia is one of the most common cancers in prepubertal girls and adolescents, with advances improving survival rates. However, treatments like chemotherapy and radiation are highly gonadotoxic, often causing ovarian insufficiency, early menopause, infertility, and endocrine disorders. Fertility preservation for young female cancer patients, especially prepubertal girls without mature germ cells, relies heavily on ovarian tissue cryopreservation.

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Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.

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In 2025, it will be 30 years since the initial clinical approval of pegylated liposomal doxorubicin (PLD) by the Food and Drug Administration. PLD predated the field of nanomedicine and became a model nanomedicine setting key pharmacological principles (prolonged circulation, slow drug release and the enhanced permeability and retention (EPR) effect) for clinical application of other nano-drugs in cancer therapy. The impressive reduction of cardiotoxicity conferred by PLD is the most valuable clinical asset.

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Background: The homologous recombination deficiency (HRD) test is an important tool for identifying patients with epithelial ovarian cancer (EOC) benefit from the treatment with poly(adenosine diphosphate-ribose) polymerase inhibitor (PARPi). Using whole exome sequencing (WES)-based platform can provide information of gene mutations and HRD score; however, the clinical value of WES-based HRD test was less validated in EOC.

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Identifying Safeguards Disabled by Epstein-Barr Virus Infections in Genomes From Patients With Breast Cancer: Chromosomal Bioinformatics Analysis.

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Department of Biochemistry and Medical Genetics, Cancer Center, University of Illinois Chicago, 900 s Ashland, Chicago, IL, 60617, United States, 1 8479124216.

Background: The causes of breast cancer are poorly understood. A potential risk factor is Epstein-Barr virus (EBV), a lifelong infection nearly everyone acquires. EBV-transformed human mammary cells accelerate breast cancer when transplanted into immunosuppressed mice, but the virus can disappear as malignant cells reproduce.

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