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https://www.selleckchem.com/products/zebularine.html Background REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning.Lung metastasis is one of the leading causes of death in patients with breast cancer. The mechanism of tumor metastasis remains controversial. Recently, the formation of a pre-metastatic niche has been considered a key factor contributing to breast cancer metastasis, which might also explain the tendency of organ metastasis. Our study initially re-examined the critical time of the niche formation and simultaneously detected a novel subset of neutrophils, CD62Ldim neutrophils, which had not previously been reported in tumor metastasis; the number of these cells progressively increased during breast cancer progression and was closely related to the formation of the pre-metastatic niche. Furthermore, we explored the mechanism of their aggregation in the pre-metastati

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