High EMSY expression defines a BRCA‐like subgroup of high‐grade serous ovarian carcinoma with prolonged survival and hypersensitivity to platinum

Background Approximately half of high‐grade serous ovarian carcinomas (HGSOCs) demonstrate homologous recombination repair (HR) pathway defects, resulting in a distinct clinical phenotype comprising hypersensitivity to platinum, superior clinical outcome, and greater sensitivity to poly(adenosine diphosphate‐ribose) polymerase (PARP) inhibitors. EMSY, which is known to be amplified in breast and ovarian cancers, encodes a protein reported to bind and inactivate BRCA2. Thus, EMSY overexpression may mimic BRCA2 mutation, resulting in HR deficiency. However, to our knowledge, the phenotypic consequences of EMSY overexpression in HGSOC patients has not been explored. Methods Here we investigate the impact of EMSY expression on clinical outcome and sensitivity to platinum‐based chemotherapy using available data from transcriptomically characterized HGSOC cohorts. Results High EMSY expression was associated with better clinical outcome in a cohort of 265 patients with HGSOC from Edinburgh (overall survival multivariable hazard ratio, 0.58 [95% CI, 0.38‐0.88; P = .011] and progression‐free survival multivariable hazard ratio, 0.62 [95% CI, 0.40‐0.96; P = .030]). Superior outcome also was demonstrated in the Medical Research Council ICON7 clinical trial and multiple publicly available data sets. Patients within the Edinburgh cohort who had high EMSY expression were found to demonstrate greater rates of complete response to multiple platinum‐containing chemotherapy regimens (radiological complete response rate of 44.4% vs 12.5% at second exposure; P = .035) and corresponding prolonged time to disease progression (median, 151.5 days vs 60.5 days after third platinum exposure; P = .004). Conclusions Patients with HGSOCs demonstrating high EMSY expression appear to experience prolonged survival and greater platinum sensitivity, reminiscent of BRCA‐mutant cases. These data are consistent with the notion that EMSY overexpression may render HGSOCs HR deficient

Site-specific incorporation of phosphotyrosine using an expanded genetic code.

Access to phosphoproteins with stoichiometric and site-specific phosphorylation status is key to understanding the role of protein phosphorylation. Here we report an efficient method to generate pure, active phosphotyrosine-containing proteins by genetically encoding a stable phosphotyrosine analog that is convertible to native phosphotyrosine. We demonstrate its general compatibility with proteins of various sizes, phosphotyrosine sites and functions, and reveal a possible role of tyrosine phosphorylation in negative regulation of ubiquitination

Clinical research in ovarian cancer: consensus recommendations from the Gynecologic Cancer InterGroup

The Gynecologic Cancer InterGroup (GCIG) sixth Ovarian Cancer Conference on Clinical Research was held virtually in October, 2021, following published consensus guidelines. The goal of the consensus meeting was to achieve harmonisation on the design elements of upcoming trials in ovarian cancer, to select important questions for future study, and to identify unmet needs. All 33 GCIG member groups participated in the development, refinement, and adoption of 20 statements within four topic groups on clinical research in ovarian cancer including first line treatment, recurrent disease, disease subgroups, and future trials. Unanimous consensus was obtained for 14 of 20 statements, with greater than 90% concordance in the remaining six statements. The high acceptance rate following active deliberation among the GCIG groups confirmed that a consensus process could be applied in a virtual setting. Together with detailed categorisation of unmet needs, these consensus statements will promote the harmonisation of international clinical research in ovarian cancer

A cross-sectional investigation of regional patterns of diet and cardio-metabolic risk in India

<p>Abstract</p> <p>Background</p> <p>The role of diet in India's rapidly progressing chronic disease epidemic is unclear; moreover, diet may vary considerably across North-South regions.</p> <p>Methods</p> <p>The India Health Study was a multicenter study of men and women aged 35-69, who provided diet, lifestyle, and medical histories, as well as blood pressure, fasting blood, urine, and anthropometric measurements. In each region (Delhi, n = 824; Mumbai, n = 743; Trivandrum, n = 2,247), we identified two dietary patterns with factor analysis. In multiple logistic regression models adjusted for age, gender, education, income, marital status, religion, physical activity, tobacco, alcohol, and total energy intake, we investigated associations between regional dietary patterns and abdominal adiposity, hypertension, diabetes, and dyslipidemia.</p> <p>Results</p> <p>Across the regions, more than 80% of the participants met the criteria for abdominal adiposity and 10 to 28% of participants were considered diabetic. In Delhi, the "fruit and dairy" dietary pattern was positively associated with abdominal adiposity [highest versus lowest tertile, multivariate-adjusted OR and 95% CI: 2.32 (1.03-5.23); P_trend= 0.008] and hypertension [2.20 (1.47-3.31); P_trend< 0.0001]. In Trivandrum, the "pulses and rice" pattern was inversely related to diabetes [0.70 (0.51-0.95); P_trend= 0.03] and the "snacks and sweets" pattern was positively associated with abdominal adiposity [2.05 (1.34-3.14); P_trend= 0.03]. In Mumbai, the "fruit and vegetable" pattern was inversely associated with hypertension [0.63 (0.40-0.99); P_trend= 0.05] and the "snack and meat" pattern appeared to be positively associated with abdominal adiposity.</p> <p>Conclusions</p> <p>Cardio-metabolic risk factors were highly prevalent in this population. Across all regions, we found little evidence of a Westernized diet; however, dietary patterns characterized by animal products, fried snacks, or sweets appeared to be positively associated with abdominal adiposity. Conversely, more traditional diets in the Southern regions were inversely related to diabetes and hypertension. Continued investigation of diet, as well as other environmental and biological factors, will be needed to better understand the risk profile in this population and potential means of prevention.</p

Concept drift for big data

The term “concept drift” refers to a change in statistical distribution of the data. In machine learning and predictive analysis, a fundamental assumption exits which reasons that the data is a random variable which is being generated independently from an underlying stationary distribution. In this chapter we present discussions on concept drifts that are inherent in the context big data. We discuss different forms of concept drifts that are evident in streaming data and outline different techniques for handling them. Handling concept drift is important for big data where the data flow occurs continuously causing existing learned models to lose their predictive accuracy. This chapter will serve as a reference to academicians and industry practitioners who are interested in the niche area of handling concept drift for big data applications