Genetic Analysis Workshop 15: gene expression analysis and approaches to detecting multiple functional loci

National Institutes of Health (AR44422, N01-AR-7-2232, 5R01-HL049609-14, IR01-AG021917-01A1); Genome Canada and Associations AFP; Polyarctique-Groupe Taitbout; Rhumatisme et Travail; Arthritis Research Campaign; Unversity of Minnesota; Minnesota Supercomputing Institute; National Institute of General Medical Sciences (R01 GM31575

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p((adjusted))=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p((adjusted))=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p((interaction))=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.Peer reviewe

Inherited variation in immune genes and pathways and glioblastoma risk

To determine whether inherited variations in immune function single-nucleotide polymorphisms (SNPs), genes or pathways affect glioblastoma risk, we analyzed data from recent genome-wide association studies in conjunction with predefined immune function genes and pathways. Gene and pathway analyses were conducted on two independent data sets using 6629 SNPs in 911 genes on 17 immune pathways from 525 glioblastoma cases and 602 controls from the University of California, San Francisco (UCSF) and a subset of 6029 SNPs in 893 genes from 531 cases and 1782 controls from MD Anderson (MDA). To further assess consistency of SNP-level associations, we also compared data from the UK (266 cases and 2482 controls) and the Mayo Clinic (114 cases and 111 controls). Although three correlated epidermal growth factor receptor (EGFR) SNPs were consistently associated with glioblastoma in all four data sets (Mantel–Haenzel P values = 1 × 10−5 to 4 × 10−3), independent replication is required as genome-wide significance was not attained. In gene-level analyses, eight immune function genes were significantly (minP < 0.05) associated with glioblastoma; the IL-2RA (CD25) cytokine gene had the smallest minP values in both UCSF (minP = 0.01) and MDA (minP = 0.001) data sets. The IL-2RA receptor is found on the surface of regulatory T cells potentially contributing to immunosuppression characteristic of the glioblastoma microenvironment. In pathway correlation analyses, cytokine signaling and adhesion–extravasation–migration pathways showed similar associations with glioblastoma risk in both MDA and UCSF data sets. Our findings represent the first systematic description of immune genes and pathways that characterize glioblastoma risk

Keeping the herds healthy and alert: implications of predator control for infectious disease

Predator control programmes are generally implemented in an attempt to increase prey population sizes. However, predator removal could prove harmful to prey populations that are regulated primarily by parasitic infections rather than by predation. We develop models for microparasitic and macroparasitic infection that specify the conditions where predator removal will (a) increase the incidence of parasitic infection, (b) reduce the number of healthy individuals in the prey population and (c) decrease the overall size of the prey population. In general, predator removal is more likely to be harmful when the parasite is highly virulent, macroparasites are highly aggregated in their prey, hosts are long-lived and the predators select infected prey

Sustainable Urban Systems: Co-design and Framing for Transformation

Rapid urbanisation generates risks and opportunities for sustainable development. Urban policy and decision makers are challenged by the complexity of cities as social–ecological–technical systems. Consequently there is an increasing need for collaborative knowledge development that supports a whole-of-system view, and transformational change at multiple scales. Such holistic urban approaches are rare in practice. A co-design process involving researchers, practitioners and other stakeholders, has progressed such an approach in the Australian context, aiming to also contribute to international knowledge development and sharing. This process has generated three outputs: (1) a shared framework to support more systematic knowledge development and use, (2) identification of barriers that create a gap between stated urban goals and actual practice, and (3) identification of strategic focal areas to address this gap. Developing integrated strategies at broader urban scales is seen as the most pressing need. The knowledge framework adopts a systems perspective that incorporates the many urban trade-offs and synergies revealed by a systems view. Broader implications are drawn for policy and decision makers, for researchers and for a shared forward agenda

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Background: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).Method: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.Results: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0. 902 for patients with ER-positive tumours (p = 2.3 x 10(-6)) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.Conclusion: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe