Stellar Iron Abundances at the Galactic Center

We present measurements of [Fe/H] for six M supergiant stars and three giant stars within 0.5 pc of the Galactic Center (GC) and one M supergiant star within 30 pc of the GC. The results are based on high-resolution (lambda / Delta lambda =40,000) K-band spectra, taken with CSHELL at the NASA Infrared Telescope Facility.We determine the iron abundance by detailed abundance analysis,performed with the spectral synthesis program MOOG.The mean [Fe/H] of the GC stars is determined to be near solar,[Fe/H] = +0.12 $\pm$ 0.22. Our analysis is a differential analysis, as we have observed and applied the same analysis technique to eleven cool, luminous stars in the solar neighborhood with similar temperatures and luminosities as the GC stars. The mean [Fe/H] of the solar neighborhood comparison stars, [Fe/H] = +0.03 $\pm$ 0.16, is similar to that of the GC stars. The width of the GC [Fe/H] distribution is found to be narrower than the width of the [Fe/H] distribution of Baade's Window in the bulge but consistent with the width of the [Fe/H] distribution of giant and supergiant stars in the solar neighborhood.Comment: 41 pages, 9 figures, ApJ, in pres

Dedicated 3D photoacoustic breast imaging

Purpose: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE).

PURPOSE: Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features. EXPERIMENTAL DESIGN: Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting. RESULTS: Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations. CONCLUSIONS: We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.Core funding for this project was provided by the National Institutes of Health (R01-CA172404, PI: S.J. Ramus; and R01-CA168758, PIs: J.A. Doherty and M.A.Rossing), the Canadian Institutes for Health Research (Proof-of-Principle I program, PIs: D.G.Huntsman and M.S. Anglesio), the United States Department of Defense Ovarian Cancer Research Program (OC110433, PI: D.D. Bowtell). A. Talhouk is funded through a Michael Smith Foundation for Health Research Scholar Award. M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. J. George was partially supported by the NIH/National Cancer Institute award number P30CA034196. C. Wang was a Career Enhancement Awardee of the Mayo Clinic SPORE in Ovarian Cancer (P50 CA136393). D.G. Huntsman receives support from the Dr. Chew Wei Memorial Professorship in Gynecologic Oncology, and the Canada Research Chairs program (Research Chair in Molecular and Genomic Pathology). M. Widschwendter receives funding from the European Union’s Horizon 2020 European Research Council Programme, H2020 BRCA-ERC under Grant Agreement No. 742432 as well as the charity, The Eve Appeal (https://eveappeal.org.uk/), and support of the National Institute for Health Research (NIHR) and the University College London Hospitals (UCLH) Biomedical Research Centre. G.E. Konecny is supported by the Miriam and Sheldon Adelson Medical Research Foundation. B.Y. Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124. H.R. Harris is 20 supported by the NIH/National Cancer Institute award number K22 CA193860. OVCARE (including the VAN study) receives support through the BC Cancer Foundation and The VGH+UBC Hospital Foundation (authors AT, BG, DGH, and MSA). The AOV study is supported by the Canadian Institutes of Health Research (MOP86727). The Gynaecological Oncology Biobank at Westmead, a member of the Australasian Biospecimen Network-Oncology group, was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID199600; ID400413 and ID400281). BriTROC-1 was funded by Ovarian Cancer Action (to IAM and JDB, grant number 006) and supported by Cancer Research UK (grant numbers A15973, A15601, A18072, A17197, A19274 and A19694) and the National Institute for Health Research Cambridge and Imperial Biomedical Research Centres. Samples from the Mayo Clinic were collected and provided with support of P50 CA136393 (E.L.G., G.L.K, S.H.K, M.E.S.)

Propagule Pressure: A Null Model for Biological Invasions

null model, propagule pressure Invasion ecology has been criticised for its lack of general principles. To explore this criticism, we con-ducted a meta-analysis that examined characteristics of invasiveness (i.e. the ability of species to establish in, spread to, or become abundant in novel communities) and invasibility (i.e. the susceptibility of habitats to the establishment or proliferation of invaders). There were few consistencies among invasiveness char-acteristics (3 of 13): established and abundant invaders generally occupy similar habitats as native species, while abundant species tend to be less affected by enemies; germination success and reproductive output were significantly positively associated with invasiveness when results from both stages (establishment/ spread and abundance/impact) were combined. Two of six invasibility characteristics were also significant: communities experiencing more disturbance and with higher resource availability sustained greater establishment and proliferation of invaders. We also found that even though ‘propagule pressure ’ was considered in only 29 % of studies, it was a significant predictor of both invasiveness and invasibility (55 of 64 total cases). Given that nonindigenous species are likely introduced non-randomly, we contend that ‘propagule biases ’ may confound current paradigms in invasion ecology. Examples of patterns that could be confounded by propagule biases include characteristics of good invaders and susceptible habitats, release from enemies, evolution of ‘invasiveness’, and invasional meltdown. We conclude that propagule pressure should serve as the basis of a null model for studies of biological invasions when inferring process from patterns of invasion

MyD88 and TLR4 Expression in Epithelial Ovarian Cancer.

OBJECTIVE: To evaluate myeloid differentiation primary response gene 88 (MyD88) and Toll-like receptor 4 (TLR4) expression in relation to clinical features of epithelial ovarian cancer, histologic subtypes, and overall survival. PATIENTS AND METHODS: We conducted centralized immunohistochemical staining, semi-quantitative scoring, and survival analysis in 5263 patients participating in the Ovarian Tumor Tissue Analysis consortium. Patients were diagnosed between January 1, 1978, and December 31, 2014, including 2865 high-grade serous ovarian carcinomas (HGSOCs), with more than 12,000 person-years of follow-up time. Tissue microarrays were stained for MyD88 and TLR4, and staining intensity was classified using a 2-tiered system for each marker (weak vs strong). RESULTS: Expression of MyD88 and TLR4 was similar in all histotypes except clear cell ovarian cancer, which showed reduced expression compared with other histotypes (P<.001 for both). In HGSOC, strong MyD88 expression was modestly associated with shortened overall survival (hazard ratio [HR], 1.13; 95% CI, 1.01-1.26; P=.04) but was also associated with advanced stage (P<.001). The expression of TLR4 was not associated with survival. In low-grade serous ovarian cancer (LGSOC), strong expression of both MyD88 and TLR4 was associated with favorable survival (HR [95% CI], 0.49 [0.29-0.84] and 0.44 [0.21-0.89], respectively; P=.009 and P=.02, respectively). CONCLUSION: Results are consistent with an association between strong MyD88 staining and advanced stage and poorer survival in HGSOC and demonstrate correlation between strong MyD88 and TLR4 staining and improved survival in LGSOC, highlighting the biological differences between the 2 serous histotypes

Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium

Abstract: Background: PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study. Methods: Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran–Mantel–Haenszel tests. Results: Downregulation of cytoplasmic PTEN expression was most frequent in ENOC (most frequently in younger patients; p value = 0.0001) and CCOC and was associated with longer overall survival in HGSOC (hazard ratio: 0.78, 95% CI: 0.65–0.94, p value = 0.022). PTEN expression was associated with ER, PR and AR expression (p values: 0.0008, 0.062 and 0.0002, respectively) in HGSOC and with lower CD8 counts in CCOC (p value < 0.0001). Heterogeneous expression of PTEN was more prevalent in advanced HGSOC (p value = 0.019) and associated with higher CD8 counts (p value = 0.0016). Conclusions: PTEN loss is a frequent driver in ovarian carcinoma associating distinctly with expression of hormonal receptors and CD8+ TIL counts in HGSOC and CCOC histotypes

Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium

Abstract: Background: PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study. Methods: Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran–Mantel–Haenszel tests. Results: Downregulation of cytoplasmic PTEN expression was most frequent in ENOC (most frequently in younger patients; p value = 0.0001) and CCOC and was associated with longer overall survival in HGSOC (hazard ratio: 0.78, 95% CI: 0.65–0.94, p value = 0.022). PTEN expression was associated with ER, PR and AR expression (p values: 0.0008, 0.062 and 0.0002, respectively) in HGSOC and with lower CD8 counts in CCOC (p value < 0.0001). Heterogeneous expression of PTEN was more prevalent in advanced HGSOC (p value = 0.019) and associated with higher CD8 counts (p value = 0.0016). Conclusions: PTEN loss is a frequent driver in ovarian carcinoma associating distinctly with expression of hormonal receptors and CD8+ TIL counts in HGSOC and CCOC histotypes