Fulvestrant plus anastrozole or placebo versus exemestane alone after progression on non-steroidal aromatase inhibitors in postmenopausal patients with hormone-receptor-positive locally advanced or metastatic breast cancer (SoFEA): a composite, multicentre, phase 3 randomised trial

SummaryBackgroundThe optimum endocrine treatment for postmenopausal women with advanced hormone-receptor-positive breast cancer that has progressed on non-steroidal aromatase inhibitors (NSAIs) is unclear. The aim of the SoFEA trial was to assess a maximum double endocrine targeting approach with the steroidal anti-oestrogen fulvestrant in combination with continued oestrogen deprivation.MethodsIn a composite, multicentre, phase 3 randomised controlled trial done in the UK and South Korea, postmenopausal women with hormone-receptor-positive breast cancer (oestrogen receptor [ER] positive, progesterone receptor [PR] positive, or both) were eligible if they had relapsed or progressed with locally advanced or metastatic disease on an NSAI (given as adjuvant for at least 12 months or as first-line treatment for at least 6 months). Additionally, patients had to have adequate organ function and a WHO performance status of 0–2. Participants were randomly assigned (1:1:1) to receive fulvestrant (500 mg intramuscular injection on day 1, followed by 250 mg doses on days 15 and 29, and then every 28 days) plus daily oral anastrozole (1 mg); fulvestrant plus anastrozole-matched placebo; or daily oral exemestane (25 mg). Randomisation was done with computer-generated permuted blocks, and stratification was by centre and previous use of an NSAI as adjuvant treatment or for locally advanced or metastatic disease. Participants and investigators were aware of assignment to fulvestrant or exemestane, but not of assignment to anastrozole or placebo. The primary endpoint was progression-free survival (PFS). Analyses were by intention to treat. This trial is registered with ClinicalTrials.gov, numbers NCT00253422 (UK) and NCT00944918 (South Korea).FindingsBetween March 26, 2004, and Aug 6, 2010, 723 patients underwent randomisation: 243 were assigned to receive fulvestrant plus anastrozole, 231 to fulvestrant plus placebo, and 249 to exemestane. Median PFS was 4·4 months (95% CI 3·4–5·4) in patients assigned to fulvestrant plus anastrozole, 4·8 months (3·6–5·5) in those assigned to fulvestrant plus placebo, and 3·4 months (3·0–4·6) in those assigned to exemestane. No difference was recorded between the patients assigned to fulvestrant plus anastrozole and fulvestrant plus placebo (hazard ratio 1·00, 95% CI 0·83–1·21; log-rank p=0·98), or between those assigned to fulvestrant plus placebo and exemestane (0·95, 0·79–1·14; log-rank p=0·56). 87 serious adverse events were reported: 36 in patients assigned to fulvestrant plus anastrozole, 22 in those assigned to fulvestrant plus placebo, and 29 in those assigned to exemestane. Grade 3–4 adverse events were rare; the most frequent were arthralgia (three in the group assigned to fulvestrant plus anastrozole; seven in that assigned to fulvestrant plus placebo; eight in that assigned to exemestane), lethargy (three; 11; 11), and nausea or vomiting (five; two; eight).InterpretationAfter loss of response to NSAIs in postmenopausal women with hormone-receptor-positive advanced breast cancer, maximum double endocrine treatment with 250 mg fulvestrant combined with oestrogen deprivation is no better than either fulvestrant alone or exemestane.FundingCancer Research UK and AstraZeneca

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file 32: Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.Peer reviewedPublisher PD

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Funding Information: GMP, PN, and CW are supported by NHLBI R01HL127564. GMP and PN are supported by R01HL142711. AG acknowledge support from the Wellcome Trust (201543/B/16/Z), European Union Seventh Framework Programme FP7/2007–2013 under grant agreement no. HEALTH-F2-2013–601456 (CVGenes@Target) & the TriPartite Immunometabolism Consortium [TrIC]-Novo Nordisk Foundation’s Grant number NNF15CC0018486. JMM is supported by American Diabetes Association Innovative and Clinical Translational Award 1–19-ICTS-068. SR was supported by the Academy of Finland Center of Excellence in Complex Disease Genetics (Grant No 312062), the Finnish Foundation for Cardiovascular Research, the Sigrid Juselius Foundation, and University of Helsinki HiLIFE Fellow and Grand Challenge grants. EW was supported by the Finnish innovation fund Sitra (EW) and Finska Läkaresällskapet. CNS was supported by American Heart Association Postdoctoral Fellowships 15POST24470131 and 17POST33650016. Charles N Rotimi is supported by Z01HG200362. Zhe Wang, Michael H Preuss, and Ruth JF Loos are supported by R01HL142302. NJT is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 217065/Z/19/Z), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC-1215–2001) and the MRC Integrative Epidemiology Unit (MC_UU_00011), and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). Ruth E Mitchell is a member of the MRC Integrative Epidemiology Unit at the University of Bristol funded by the MRC (MC_UU_00011/1). Simon Haworth is supported by the UK National Institute for Health Research Academic Clinical Fellowship. Paul S. de Vries was supported by American Heart Association grant number 18CDA34110116. Julia Ramierz acknowledges support by the People Programme of the European Union’s Seventh Framework Programme grant n° 608765 and Marie Sklodowska-Curie grant n° 786833. Maria Sabater-Lleal is supported by a Miguel Servet contract from the ISCIII Spanish Health Institute (CP17/00142) and co-financed by the European Social Fund. Jian Yang is funded by the Westlake Education Foundation. Olga Giannakopoulou has received funding from the British Heart Foundation (BHF) (FS/14/66/3129). CHARGE Consortium cohorts were supported by R01HL105756. Study-specific acknowledgements are available in the Additional file : Supplementary Note. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

The inhibitory effect of Gremlin-2 on adipogenesis suppresses breast cancer cell growth and metastasis

Abstract Background Gremlin-1 (GREM1) and Gremlin-2 (GREM2) are bone morphogenetic protein antagonists that play important roles in organogenesis, tissue differentiation, and tissue homeostasis. Although GREM1 has been reported to be involved in promoting various cancers, little has been reported about effects of GREM2 on cancer. Recently, it has been reported that GREM2 can inhibit adipogenesis in adipose-derived stromal/stem cells. However, as an inhibitor of adipogenesis, the role of GREM2 in cancer progression is not well understood yet. Methods Pre-adipocyte 3T3-L1 cells overexpressing mock or Grem2 were established using a lentiviral transduction system and differentiated into adipocytes-mock and adipocytes-Grem2, respectively. To investigate the effect of adipocyte-Grem2 on breast cancer cells, we analyzed the proliferative and invasion abilities of spheroids using a 3D co-culture system of breast cancer cells and adipocytes or conditioned medium (CM) of adipocytes. An orthotopic breast cancer mouse model was used to examine the role of adipocytes-Grem2 in breast cancer progression. Results Grem2 overexpression suppressed adipogenesis of 3T3-L1 cells. Proliferative and invasion abilities of spheroids formed by co-culturing MTV/TM-011 breast cancer cells and adipocytes-Grem2 were significantly reduced compared to those of spheroids formed by co-culturing MTV/TM-011 cells and adipocytes-mock. Compared to adipocytes-mock, adipocytes-Grem2 showed decreased mRNA expression of several adipokines, notably IL-6. The concentration of IL-6 in the CM of these cells was also decreased. Proliferative and invasive abilities of breast cancer cells reduced by adipocytes-Grem2 were restored by IL-6 treatment. Expression levels of vimentin, slug, and twist1 in breast cancer cells were decreased by treatment with CM of adipocytes-Grem2 but increased by IL-6 treatment. In orthotopic breast cancer mouse model, mice injected with both MTV/TM-011 cells and adipocytes-Grem2 showed smaller primary tumors and lower lung metastasis than controls. However, IL-6 administration increased both the size of primary tumor and the number of metastatic lung lesions, which were reduced by adipocytes-Grem2. Conclusions Our study suggests that GREM2 overexpression in adipocytes can inhibit adipogenesis, reduce the expression and secretion of several adipokines, including IL-6, and ultimately inhibit breast cancer progression

Outcomes With a Mobile Digital Health Platform for Patients Undergoing Spine Surgery: Retrospective Analysis

BackgroundDigital health solutions have been shown to enhance outcomes for individuals with chronic medical illnesses, but few have been validated for surgical patients. The digital health platform ManageMySurgery (MMS) has been validated for spine surgery as a feasible method for patients along their surgical journey through in-app education and completion of patient-reported outcomes surveys. ObjectiveThe aim of this study is to determine the rates of 90-day emergency room (ER) visits, readmissions, and complications in patients undergoing spine surgery using MMS compared to patients using traditional perioperative care alone. MethodsPatients undergoing spine surgery at a US-based academic hospital were invited to use MMS perioperatively between December 2017 and September 2021. All patients received standard perioperative care and were classified as MMS users if they logged into the app. Demographic information and 90-day outcomes were acquired via electronic health record review. The odds ratios of having 90-day ER visits, readmissions, mild complications, and severe complications between the MMS and non-MMS groups were estimated using logistic regression models. ResultsA total of 1015 patients were invited, with 679 using MMS. MMS users and nonusers had similar demographics: the average ages were 57.9 (SD 12.5) years and 61.5 (SD 12.7) years, 54.1% (367/679) and 47.3% (159/336) were male, and 90.1% (612/679) and 88.7% (298/336) had commercial or Medicare insurance, respectively. Cervical fusions (559/1015, 55.07%) and single-approach lumbar fusions (231/1015, 22.76%) were the most common procedures for all patients. MMS users had a lower 90-day readmission rate (55/679, 8.1%) than did nonusers (30/336, 8.9%). Mild complications (MMS: 56/679, 8.3%; non-MMS: 32/336, 9.5%) and severe complications (MMS: 66/679, 9.7%; non-MMS: 43/336, 12.8%) were also lower in MMS users. MMS users had a lower 90-day ER visit rate (MMS: 62/679, 9.1%; non-MMS: 45/336, 13.4%). After adjustments were made for age and sex, the odds of having 90-day ER visits for MMS users were 32% lower than those for nonusers, but this difference was not statistically significant (odds ratio 0.68, 95% CI 0.45-1.02; P=.06). ConclusionsThis is one of the first studies to show differences in acute outcomes for people undergoing spine surgery who use a digital health app. This study found a correlation between MMS use and fewer postsurgical ER visits in a large group of spine surgery patients. A planned randomized controlled trial will provide additional evidence of whether this digital health tool can be used as an intervention to improve patient outcomes