9 research outputs found
The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data
This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys
Methylation of and function as possible biomarkers for the differential diagnosis of lung cancer
Lung cancer is the major cause of cancer-related deaths worldwide. Differential diagnosis can be difficult, especially when only small samples are available. Epigenetic changes are frequently tissue-specific events in carcinogenesis and hence may serve as diagnostic biomarkers.
138 representative formalin-fixed, paraffin-embedded (FFPE) tissues (116 lung cancer cases and 22 benign controls) were used for targeted DNA methylation analysis via pyrosequencing of ten literature-derived methylation markers and ). Methylation levels were analyzed with the Classification and Regression Tree Algorithm (CART), Conditional Interference Trees (ctree) and ROC. Validation was performed with additional 27 lung cancer cases and 38 benign controls. TCGA data for 282 lung cancer cases was included in the analysis.
CART and ctree analysis identified the combination of and as well as and as independent methylation markers with high discriminative power between tumor and benign tissue (for each combination, 91% specificity and 100% sensitivity). methylation associated significantly with tumor type and grade (p<0.001) with highest methylation in the control group. The opposite was found for (p<0.001). methylation increased with tumor type and grade (p<0.001) with strongest methylation in neuroendocrine tumors (NET).
Hypomethylation of is frequent in tumors compared to benign controls and associates with higher grade, whereas increasing methylation of is an independent marker for tumors and higher grade. hypermethylation was frequent in tumors and most prominent in NET making it an auxiliary marker for separation of NSCLC and NET. in combination with either or could function as biomarkers for separating lung cancer and non-cancerous tissue and could be useful for samples of limited size such as biopsies
Mutational analysis of pulmonary tumours with neuroendocrine features using targeted massive parallel sequencing: a comparison of a neglected tumour group
Background: Lung cancer is the leading cause of cancer-related deaths worldwide. The typical and atypical carcinoid (TC and AC), the large-cell neuroendocrine carcinoma (LCNEC) and the small-cell lung cancers (SCLC) are subgroups of pulmonary tumours that show neuroendocrine differentiations. With the rising impact of molecular pathology in routine diagnostics the interest for reliable biomarkers, which can help to differentiate these subgroups and may enable a more personalised treatment of patients, grows. Methods: A collective of 70 formalin-fixed, paraffin-embedded (FFPE) pulmonary neuroendocrine tumours (17 TCs, 17 ACs, 19 LCNECs and 17 SCLCs) was used to identify biomarkers by high-throughput sequencing. Using the Illumina TruSeq Amplicon-Cancer Panel on the MiSeq instrument, the samples were screened for alterations in 221 mutation hot spots of 48 tumour-relevant genes. Results: After filtering >26 000 detected variants by applying strict algorithms, a total of 130 mutations were found in 29 genes and 49 patients. Mutations in JAK3, NRAS, RB1 and VHL1 were exclusively found in SCLCs, whereas the FGFR2 mutation was detected in LCNEC only. KIT, PTEN, HNF1A and SMO were altered in ACs. The SMAD4 mutation corresponded to the TC subtype. We prove that the frequency of mutations increased with the malignancy of tumour type. Interestingly, four out of five ATM-mutated patients showed an additional alteration in TP53, which was by far the most frequently altered gene (28 out of 130; 22%). We found correlations between tumour type and IASLC grade for ATM-(P = 0.022; P = 0.008) and TP53-mutated patients (P<0.001). Both mutated genes were also associated with lymph node invasion and distant metastasis (P <= 0.005). Furthermore, PIK3CA-mutated patients with high-grade tumours showed a reduced overall survival (P = 0.040) and the mutation frequency of APC and ATM in high-grade neuroendocrine lung cancer patients was associated with progression-free survival (PFS) (P = 0.020). Conclusions: The implementation of high-throughput sequencing for the analysis of the neuroendocrine lung tumours has revealed that, even if these tumours encompass several subtypes with varying clinical aggressiveness, they share a number of molecular features. An improved understanding of the biology of neuroendocrine tumours will offer the opportunity for novel approaches in clinical management, resulting in a better prognosis and prediction of therapeutic response
Mutational analysis of pulmonary tumours with neuroendocrine features using targeted massive parallel sequencing: a comparison of a neglected tumour group
Apolipoprotein B, Residual Cardiovascular Risk After Acute Coronary Syndrome, and Effects of Alirocumab.
Background: Apolipoprotein B (apoB) provides an integrated measure of atherogenic risk. Whether apoB levels and apoB lowering hold incremental predictive information on residual risk after acute coronary syndrome beyond that provided by low-density lipoprotein cholesterol is uncertain. Methods: The ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) compared the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab with placebo in 18â924 patients with recent acute coronary syndrome and elevated atherogenic lipoproteins despite optimized statin therapy. Primary outcome was major adverse cardiovascular events (MACE; coronary heart disease death, nonfatal myocardial infarction, fatal/nonfatal ischemic stroke, hospitalization for unstable angina). Associations between baseline apoB or apoB at 4 months and MACE were assessed in adjusted Cox proportional hazards and propensity scoreâmatched models. Results: Median follow-up was 2.8 years. In proportional hazards analysis in the placebo group, MACE incidence increased across increasing baseline apoB strata (3.2 [95% CI, 2.9â3.6], 4.0 [95% CI, 3.6â4.5], and 5.5 [95% CI, 5.0â6.1] events per 100 patient-years in strata 35â<50, and â€35 mg/dL, respectively). Compared with propensity scoreâmatched patients from the placebo group, treatment hazard ratios for alirocumab also decreased monotonically across achieved apoB strata. Achieved apoB was predictive of MACE after adjustment for achieved low-density lipoprotein cholesterol or nonâhigh-density lipoprotein cholesterol but not vice versa. Conclusions: In patients with recent acute coronary syndrome and elevated atherogenic lipoproteins, MACE increased across baseline apoB strata. Alirocumab reduced MACE across all strata of baseline apoB, with larger absolute reductions in patients with higher baseline levels. Lower achieved apoB was associated with lower risk of MACE, even after accounting for achieved low-density lipoprotein cholesterol or nonâhigh-density lipoprotein cholesterol, indicating that apoB provides incremental information. Achievement of apoB levels as low as â€35 mg/dL may reduce lipoprotein-attributable residual risk after acute coronary syndrome. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01663402.gov; Unique identifier: NCT01663402.URL: https://www
The Seventeenth Data Release of the Sloan Digital Sky Surveys:complete release of MaNGA, MaStar and APOGEE-2 data
This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys