The kSORT assay to detect renal transplant patients at high risk for acute rejection: results of the multicenter AART study

Abstract Background: Development of noninvasive molecular assays to improve disease diagnosis and patient monitoring is a critical need. In renal transplantation, acute rejection (AR) increases the risk for chronic graft injury and failure. Noninvasive diagnostic assays to improve current late and nonspecific diagnosis of rejection are needed. We sought to develop a test using a simple blood gene expression assay to detect patients at high risk for AR. Methods and Findings: We developed a novel correlation-based algorithm by step-wise analysis of gene expression data in 558 blood samples from 436 renal transplant patients collected across eight transplant centers in the US, Mexico, and Spain between 5 February 2005 and 15 December 2012 in the Assessment of Acute Rejection in Renal Transplantation (AART)study. Gene expression was assessed by quantitative real-time PCR (QPCR) in one center. A 17-gene set the Kidney Solid Organ Response Test (kSORT) was selected in 143 samples for AR classification using discriminant analysis (area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI 0.91-0.98), validated in 124 independent samples (AUC = 0.95; 95% CI 0.88-1.0) and evaluated for AR prediction in 191 serial samples, where it predicted AR up to 3 mo prior to detection by the current gold standard (biopsy). A novel reference-based algorithm (using 13 12-gene models) was developed in 100 independent samples to provide a numerical AR risk score, to classify patients as high risk versus low risk for AR. kSORT was able to detect AR in blood independent of age, time post-transplantation, and sample source without additional data normalization; AUC = 0.93 (95% CI 0.86-0.99). Further validation of kSORT is planned in prospective clinical observational and interventional trials. Conclusions: The kSORT blood QPCR assay is a noninvasive tool to detect high risk of AR of renal transplants

Ybp2 Associates with the Central Kinetochore of Saccharomyces cerevisiae and Mediates Proper Mitotic Progression

The spindle checkpoint ensures the accurate segregation of chromosomes by monitoring the status of kinetochore attachment to microtubules. Simultaneous mutations in one of several kinetochore and cohesion genes and a spindle checkpoint gene cause a synthetic-lethal or synthetic-sick phenotype. A synthetic genetic array (SGA) analysis using a mad2Δ query mutant strain of yeast identified YBP2, a gene whose product shares sequence similarity with the product of YBP1, which is required for H2O2-induced oxidation of the transcription factor Yap1. ybp2Δ was sensitive to benomyl and accumulated at the mitotic stage of the cell cycle. Ybp2 physically associates with proteins of the COMA complex (Ctf19, Okp1, Mcm21, and Ame1) and 3 components of the Ndc80 complex (Ndc80, Nuf2, and Spc25 but not Spc24) in the central kinetochore and with Cse4 (the centromeric histone and CENP-A homolog). Chromatin-immunoprecipitation analyses revealed that Ybp2 associates specifically with CEN DNA. Furthermore, ybp2Δ showed synthetic-sick interactions with mutants of the genes that encode the COMA complex components. Ybp2 seems to be part of a macromolecular kinetochore complex and appears to contribute to the proper associations among the central kinetochore subcomplexes and the kinetochore-specific nucleosome

SLC2A9 Is a High-Capacity Urate Transporter in Humans

Serum uric acid levels in humans are influenced by diet, cellular breakdown, and renal elimination, and correlate with blood pressure, metabolic syndrome, diabetes, gout, and cardiovascular disease. Recent genome-wide association scans have found common genetic variants of SLC2A9 to be associated with increased serum urate level and gout. The SLC2A9 gene encodes a facilitative glucose transporter, and it has two splice variants that are highly expressed in the proximal nephron, a key site for urate handling in the kidney. We investigated whether SLC2A9 is a functional urate transporter that contributes to the longstanding association between urate and blood pressure in man

Randomised, open-label, phase II study of Gemcitabine with and without IMM-101 for advanced pancreatic cancer

Background: Immune Modulation and Gemcitabine Evaluation-1, a randomised, open-label, phase II, first-line, proof of concept study (NCT01303172), explored safety and tolerability of IMM-101 (heat-killed Mycobacterium obuense; NCTC 13365) with gemcitabine (GEM) in advanced pancreatic ductal adenocarcinoma. Methods: Patients were randomised (2 : 1) to IMM-101 (10 mg ml−l intradermally)+GEM (1000 mg m−2 intravenously; n=75), or GEM alone (n=35). Safety was assessed on frequency and incidence of adverse events (AEs). Overall survival (OS), progression-free survival (PFS) and overall response rate (ORR) were collected. Results: IMM-101 was well tolerated with a similar rate of AE and serious adverse event reporting in both groups after allowance for exposure. Median OS in the intent-to-treat population was 6.7 months for IMM-101+GEM v 5.6 months for GEM; while not significant, the hazard ratio (HR) numerically favoured IMM-101+GEM (HR, 0.68 (95% CI, 0.44–1.04, P=0.074). In a pre-defined metastatic subgroup (84%), OS was significantly improved from 4.4 to 7.0 months in favour of IMM-101+GEM (HR, 0.54, 95% CI 0.33–0.87, P=0.01). Conclusions: IMM-101 with GEM was as safe and well tolerated as GEM alone, and there was a suggestion of a beneficial effect on survival in patients with metastatic disease. This warrants further evaluation in an adequately powered confirmatory study

Ovarian Real-World International Consortium (ORWIC): A multicentre, real-world analysis of epithelial ovarian cancer treatment and outcomes

IntroductionMuch drug development and published analysis for epithelial ovarian cancer (EOC) focuses on early-line treatment. Full sequences of treatment from diagnosis to death and the impact of later lines of therapy are rarely studied. We describe the establishment of an international network of cancer centers configured to compare real-world treatment pathways in UK, Portugal, Germany, South Korea, France and Romania (the Ovarian Real-World International Consortium; ORWIC).Methods3344 patients diagnosed with EOC (2012-2018) were analysed using a common data model and hub and spoke programming approach applied to existing electronic medical records. Consistent definition of line of therapy between sites and an efficient approach to analysis within the limitations of local information governance was achieved.ResultsMedian age of participants was 53-67 years old and 5-29% were ECOG >1. Between 62% and 84% of patients were diagnosed with late-stage disease (FIGO III-IV). Sites treating younger and fitter patients had higher rates of debulking surgery for those diagnosed at late stage than sites with older, more frail patients. At least 21% of patients treated with systemic anti-cancer therapy (SACT) had recurrent disease following second-line therapy (2L); up to 11 lines of SACT treatment were recorded for some patients. Platinum-based SACT was consistently used across sites at 1L, but choices at 2L varied, with hormone therapies commonly used in the UK and Portugal. The use (and type) of maintenance therapy following 1L also varied. Beyond 2L, there was little consensus between sites on treatment choice: trial compounds and unspecified combinations of other agents were common.DiscussionSpecific treatment sequences are reported up to 4L and the establishment of this network facilitates future analysis of comparative outcomes per line of treatment with the aim of optimizing available options for patients with recurrent EOC. In particular, this real-world network can be used to assess the growing use of PARP inhibitors. The real-world optimization of advanced line treatment will be especially important for patients not usually eligible for involvement with clinical trials. The resources to enable this analysis to be implemented elsewhere are supplied and the network will seek to grow in coverage of further sites

Peer mentoring : models and outcomes at QUT

Students entering university study often experience feelings of isolation and disconnection, both academically and socially. At Queensland University of Technology, like many universities, there is a commitment to the student experience, in relation to welfare, satisfaction, retention, and success. The first year experience is a priority for many universities. Kift and Nelson (2005) described the unique needs of students-in-transition: social, academic, and administrative support. Efforts to facilitate the transition to university for first-year students include transition programs targeted for specific faculties’ requirements (McInnis et al., 2000); academically oriented peer support programs (McInnis et al., 2000); reciprocal peer tutoring (Rittschof & Griffin, 2001); online support (O’Reagan et al., 2004); and mentoring programs (Drew et al., 2000). Peer mentors may be a valuable resource for institutions to use in increasing persistence rates and enhancing the first year experience (Kahn & Nauta, 2001). Some of the benefits for first-year students include preventing the negative effects of stress (Jacobi, 1991, cited in Glaser et al., 2006); enhancing the sense of belonging and identity with the university, school or faculty (Evans & Peel, 1999, cited in Glaser et al., 2006); early access to information about resources on campus (Clark & Crome, 2004, cited in Glaser et al., 2006); academic success (Rodger & Tremblay, 2003, cited in Glaser et al., 2006); social connections (Pope & Van Dyke, 1999, cited in Glaser et al., 2006); skill development (Treston, 1999, cited in Glaser et al., 2006); and improved retention (Jacobi, 1991, cited in Glaser et al., 2006). In implementing a mentoring program, research indicates several factors critical to the success of the mentoring relationship including: organisational support; clarifying goals and roles; matching mentor and mentees; training mentors; sufficient resources; and monitoring and evaluation (Lloyd & Bristol, 2006). The structure of mentoring programs may vary depending on the target faculty or discipline. Key characteristics associated with effective programs, correspond with characteristics that are critical to the success of mentoring programs. These include: the characteristics of the mentor; the size of the mentoring group; the sustainability of the program; the presence of a coordinator; ongoing monitoring and evaluation; and a multidimensional approach (Rolfe-Flett, 2000)

Assessment of bone-targeting agents use in patients with bone metastasis from breast, lung or prostate cancer using structured and unstructured electronic health records from a regional UK-based hospital

Design Retrospective cohort study.Setting Regional hospital-based oncology database of approximately 2 million patients in England.Participants Patients aged ≥18 years with a diagnosis of BC, NSCLC or PC as well as BM between 1 January 2007 and 31 December 2018, with follow-up to 30 June 2020 or death; BM diagnosis ascertained from recorded medical codes and unstructured data using natural language processing (NLP).Main outcomes measures Initiation or non-initiation of BTA following BM diagnosis, time from BM diagnosis to BTA initiation, time from first to last BTA, time from last BTA to death.Results This study included 559 BC, 894 NSCLC and 1013 PC with BM; median age (Q1–Q3) was 65 (52–76), 69 (62–77) and 75 (62–77) years, respectively. NLP identified BM diagnosis from unstructured data for 92% patients with BC, 92% patients with NSCLC and 95% patients with PC. Among patients with BC, NSCLC and PC with BM, 47%, 87% and 88% did not receive a BTA, and 53%, 13% and 12% received at least one BTA, starting a median 65 (27–167), 60 (28–162) and 610 (295–980) days after BM, respectively. Median (Q1–Q3) duration of BTA treatment was 481 (188–816), 89 (49–195) and 115 (53–193) days for patients with BC, NSCLC and PC. For those with a death record, median time from last BTA to death was 54 (26–109) for BC, 38 (17–98) for NSCLC and 112 (44–218) days for PC.Conclusion In this study identifying BM diagnosis from both structured and unstructured data, a high proportion of patients did not receive a BTA. Unstructured data provide new insights on the real-world use of BTA