High Quality Genomic Copy Number Data from Archival Formalin-Fixed Paraffin-Embedded Leiomyosarcoma: Optimisation of Universal Linkage System Labelling

Most soft tissue sarcomas are characterized by genetic instability and frequent genomic copy number aberrations that are not subtype-specific. Oligonucleotide microarray-based Comparative Genomic Hybridisation (array CGH) is an important technique used to map genome-wide copy number aberrations, but the traditional requirement for high-quality DNA typically obtained from fresh tissue has limited its use in sarcomas. Although large archives of Formalin-fixed Paraffin-embedded (FFPE) tumour samples are available for research, the degradative effects of formalin on DNA from these tissues has made labelling and analysis by array CGH technically challenging. The Universal Linkage System (ULS) may be used for a one-step chemical labelling of such degraded DNA. We have optimised the ULS labelling protocol to perform aCGH on archived FFPE leiomyosarcoma tissues using the 180k Agilent platform. Preservation age of samples ranged from a few months to seventeen years and the DNA showed a wide range of degradation (when visualised on agarose gels). Consistently high DNA labelling efficiency and low microarray probe-to-probe variation (as measured by the derivative log ratio spread) was seen. Comparison of paired fresh and FFPE samples from identical tumours showed good correlation of CNAs detected. Furthermore, the ability to macro-dissect FFPE samples permitted the detection of CNAs that were masked in fresh tissue. Aberrations were visually confirmed using Fluorescence in situ Hybridisation. These results suggest that archival FFPE tissue, with its relative abundance and attendant clinical data may be used for effective mapping for genomic copy number aberrations in such rare tumours as leiomyosarcoma and potentially unravel clues to tumour origins, progression and ultimately, targeted treatment

Integrated genomic analyses of ovarian carcinoma

A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients’ lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.National Institutes of Health (U.S.) (Grant U54HG003067)National Institutes of Health (U.S.) (Grant U54HG003273)National Institutes of Health (U.S.) (Grant U54HG003079)National Institutes of Health (U.S.) (Grant U24CA126543)National Institutes of Health (U.S.) (Grant U24CA126544)National Institutes of Health (U.S.) (Grant U24CA126546)National Institutes of Health (U.S.) (Grant U24CA126551)National Institutes of Health (U.S.) (Grant U24CA126554)National Institutes of Health (U.S.) (Grant U24CA126561)National Institutes of Health (U.S.) (Grant U24CA126563)National Institutes of Health (U.S.) (Grant U24CA143882)National Institutes of Health (U.S.) (Grant U24CA143731)National Institutes of Health (U.S.) (Grant U24CA143835)National Institutes of Health (U.S.) (Grant U24CA143845)National Institutes of Health (U.S.) (Grant U24CA143858)National Institutes of Health (U.S.) (Grant U24CA144025)National Institutes of Health (U.S.) (Grant U24CA143866)National Institutes of Health (U.S.) (Grant U24CA143867)National Institutes of Health (U.S.) (Grant U24CA143848)National Institutes of Health (U.S.) (Grant U24CA143843)National Institutes of Health (U.S.) (Grant R21CA135877

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients

Identification and Characterization of a Mef2 Transcriptional Activator in Schistosome Parasites

Myocyte enhancer factor 2 protein (Mef2) is an evolutionarily conserved activator of transcription that is critical to induce and control complex processes in myogenesis and neurogenesis in vertebrates and insects, and osteogenesis in vertebrates. In Drosophila, Mef2 null mutants are unable to produce differentiated muscle cells, and in vertebrates, Mef2 mutants are embryonic lethal. Schistosome worms are responsible for over 200 million cases of schistosomiasis globally, but little is known about early development of schistosome parasites after infecting a vertebrate host. Understanding basic schistosome development could be crucial to delineating potential drug targets. Here, we identify and characterize Mef2 from the schistosome worm Schistosoma mansoni (SmMef2). We initially identified SmMef2 as a homolog to the yeast Mef2 homolog, Resistance to Lethality of MKK1P386 overexpression (Rlm1), and we show that SmMef2 is homologous to conserved Mef2 family proteins. Using a genetics approach, we demonstrate that SmMef2 is a transactivator that can induce transcription of four separate heterologous reporter genes by yeast one-hybrid analysis. We also show that Mef2 is expressed during several stages of schistosome development by quantitative PCR and that it can bind to conserved Mef2 DNA consensus binding sequences

Comparative Analyses by Sequencing of Transcriptomes during Skeletal Muscle Development between Pig Breeds Differing in Muscle Growth Rate and Fatness

Understanding the dynamics of muscle transcriptome during development and between breeds differing in muscle growth is necessary to uncover the complex mechanism underlying muscle development. Herein, we present the first transcriptome-wide longissimus dorsi muscle development research concerning Lantang (LT, obese) and Landrace (LR, lean) pig breeds during 10 time-points from 35 days-post-coitus (dpc) to 180 days-post-natum (dpn) using Solexa/Illumina's Genome Analyzer. The data demonstrated that myogenesis was almost completed before 77 dpc, but the muscle phenotypes were still changed from 77 dpc to 28 dpn. Comparative analysis of the two breeds suggested that myogenesis started earlier but progressed more slowly in LT than in LR, the stages ranging from 49 dpc to 77 dpc are critical for formation of different muscle phenotypes. 595 differentially expressed myogenesis genes were identified, and their roles in myogenesis were discussed. Furthermore, GSK3B, IKBKB, ACVR1, ITGA and STMN1 might contribute to later myogenesis and more muscle fibers in LR than LT. Some myogenesis inhibitors (ID1, ID2, CABIN1, MSTN, SMAD4, CTNNA1, NOTCH2, GPC3 and HMOX1) were higher expressed in LT than in LR, which might contribute to more slow muscle differentiation in LT than in LR. We also identified several genes which might contribute to intramuscular adipose differentiation. Most important, we further proposed a novel model in which MyoD and MEF2A controls the balance between intramuscular adipogenesis and myogenesis by regulating CEBP family; Myf5 and MEF2C are essential during the whole myogenesis process while MEF2D affects muscle growth and maturation. The MRFs and MEF2 families are also critical for the phenotypic differences between the two pig breeds. Overall, this study contributes to elucidating the mechanism underlying muscle development, which could provide valuable information for pig meat quality improvement

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society

Developmental regulation of MURF ubiquitin ligases and autophagy proteins nbr1, p62/SQSTM1 and LC3 during cardiac myofibril assembly and turnover

AbstractThe striated muscle-specific tripartite motif (TRIM) proteins TRIM63/MURF1, TRIM55/MURF2 and TRIM54/MURF3 can function as ubiquitin E3 ligases in ubiquitin-mediated muscle protein turnover. Despite their well-characterised roles in muscle atrophy, the dynamics of MURF expression in the development and early postnatal adaptation of striated muscle is largely unknown. Here, we show that MURF2 is expressed at the very onset of mouse cardiac differentiation at embryonic day 8.5, and represents a sensitive marker for differentiating myocardium. During cardiac development, expression shifts from the 50 kDa to the 60 kDa A-isoform, which dominates postnatally. In contrast, MURF1 shows strong postnatal upregulation and MURF3 is not significantly expressed before birth. MURF2 expression parallels that of the autophagy-associated proteins LC3, p62/SQSTM1 and nbr1. SiRNA knockdown of MURF2 in neonatal rat cardiomyocytes disrupts posttranslational microtubule modification and myofibril assembly, and is only partly compensated by upregulation of MURF3 but not MURF1. Knockdown of both MURF2 and MURF3 severely disrupts the formation of ordered Z- and M-bands, likely by perturbed tubulin dynamics. These results suggest that ubiquitin-mediated protein turnover and MURF2 in particular play an unrecognised role in the earliest steps of heart muscle differentiation, and that partial complementation of MURF2 deficiency is afforded by MURF3