35, 95% CI 1.15-1.58). Null findings for younger participants. Higher 1-year average PM exposures were associated with higher risks for acute myeloid and chronic lymphoblastic leukaemia. Among older adults, higher risk for leukaemia was associated with higher residential PM concentrations averaged over 1, 5 and 10 years prior to diagnosis. Among older adults, higher risk for leukaemia was associated with higher residential PM2.5 concentrations averaged over 1, 5 and 10 years prior to diagnosis. Anti-EGFR-based therapies have limited success in HNSCC patients. Predictive biomarkers are greatly needed to identify the patients likely to be benefited from these targeted therapies. Here, we present the prognostic and predictive association of biomarkers in HPV-negative locally advanced (LA) HNSCC patients. Treatment-naive tumour tissue samples of 404 patients, a subset of randomised Phase 3 trial comparing cisplatin radiation (CRT) versus nimotuzumab plus cisplatin radiation (NCRT) were analysed to evaluate the expression of HIF1α, EGFR and pEGFR by immunohistochemistry and EGFR gene copy change by FISH. Progression-free survival (PFS), locoregional control (LRC) and overall survival (OS) were estimated by Kaplan-Meier method. https://www.selleckchem.com/products/ziftomenib.html Hazard ratios were estimated by Cox proportional hazard models. Baseline characteristics of the patients were balanced between two treatment groups (CRT vs NCRT) and were representative of the trial cohort. The median follow-up was of 39.13 months. Low HIF1α was associated with better PFS [HR (95% CI) = 0.62 (0.42-0.93)], LRC [HR (95% CI) = 0.56 (0.37-0.86)] and OS [HR (95% CI) = 0.63 (0.43-0.93)] in the CRT group. Multivariable analysis revealed HIF1α as an independent negative prognostic biomarker. For patients with high HIF1α, NCRT significantly improved the outcomes [PFSHR (95% CI) = 0.55 (0.37-0.82), LRCHR (95% CI) = 0.55 (0.36-0.85) and OSHR (95% CI) = 0.54 (0.36-0.81)] compared to CRT. While in patients with low HIF1α, no difference in the clinical outcomes was observed between treatments. Interaction test suggested a predictive value of HIF1α for OS (P = 0.008). High HIF1α expression is a predictor of poor clinical response to CRT in HPV-negative LA-HNSCC patients. These patients with high HIF1α significantly benefited with the addition of nimotuzumab to CRT. Registered with the Clinical Trial Registry of India (Trial registration identifier-CTRI/2014/09/004980). Registered with the Clinical Trial Registry of India (Trial registration identifier-CTRI/2014/09/004980). The natural history of breast cancer among BRCA2 carriers has not been clearly established. In a previous study from Iceland, positive ER status was a negative prognostic factor. We sought to identify factors that predicted survival after invasive breast cancer in an expanded cohort of BRCA2 carriers. We studied 608 women with invasive breast cancer and a pathogenic BRCA2 mutation (variant) from four Nordic countries. Information on prognostic factors and treatment was retrieved from health records and by analysis of archived tissue specimens. Hazard ratios (HR) were estimated for breast cancer-specific survival using Cox regression. About 77% of cancers were ER-positive, with the highest proportion (83%) in patients under 40 years. ER-positive breast cancers were more likely to be node-positive (59%) than ER-negative cancers (34%) (P < 0.001). The survival analysis included 584 patients. Positive ER status was protective in the first 5 years from diagnosis (multivariate HR = 0.49; 95% CI 0.26-0.93, P = 0.03); thereafter, the effect was adverse (HR = 1.91; 95% CI 1.07-3.39, P = 0.03). The adverse effect of positive ER status was limited to women who did not undergo endocrine treatment (HR = 2.36; 95% CI 1.26-4.44, P = 0.01) and patients with intact ovaries (HR = 1.99; 95% CI 1.11-3.59, P = 0.02). The adverse effect of a positive ER status in BRCA2 carriers with breast cancer may be contingent on exposure to ovarian hormones. The adverse effect of a positive ER status in BRCA2 carriers with breast cancer may be contingent on exposure to ovarian hormones.An important need exists to better understand and stratify kidney disease according to its underlying pathophysiology in order to develop more precise and effective therapeutic agents. National collaborative efforts such as the Kidney Precision Medicine Project are working towards this goal through the collection and integration of large, disparate clinical, biological and imaging data from patients with kidney disease. Ontologies are powerful tools that facilitate these efforts by enabling researchers to organize and make sense of different data elements and the relationships between them. Ontologies are critical to support the types of big data analysis necessary for kidney precision medicine, where heterogeneous clinical, imaging and biopsy data from diverse sources must be combined to define a patient's phenotype. The development of two new ontologies - the Kidney Tissue Atlas Ontology and the Ontology of Precision Medicine and Investigation - will support the creation of the Kidney Tissue Atlas, which aims to provide a comprehensive molecular, cellular and anatomical map of the kidney. These ontologies will improve the annotation of kidney-relevant data, and eventually lead to new definitions of kidney disease in support of precision medicine.Drug repositioning and repurposing can enhance traditional drug development efforts and could accelerate the identification of new treatments for individuals with Alzheimer disease (AD) dementia and mild cognitive impairment. Transcriptional profiling offers a new and highly efficient approach to the identification of novel candidates for repositioning and repurposing. In the future, novel AD transcriptional signatures from cells isolated at early stages of disease, or from human neurons or microglia that carry mutations that increase the risk of AD, might be used as probes to identify additional candidate drugs. Phase II trials assessing repurposed agents must consider the best target population for a specific candidate therapy as well as the mechanism of action of the treatment. In this Review, we highlight promising compounds to prioritize for clinical trials in individuals with AD, and discuss the value of Delphi consensus methodology and evidence-based reviews to inform this prioritization process. We also describe emerging work, focusing on the potential value of transcript signatures as a cost-effective approach to the identification of novel candidates for repositioning.