Growth of PdCoO2 films with controlled termination by molecular-beam epitaxy and determination of their electronic structure by angle-resolved photoemission spectroscopy

Utilizing the powerful combination of molecular-beam epitaxy (MBE) and angle-resolved photoemission spectroscopy (ARPES), we produce and study the effect of different terminating layers on the electronic structure of the metallic delafossite PdCoO2. Attempts to introduce unpaired electrons and synthesize new antiferromagnetic metals akin to the isostructural compound PdCrO2 have been made by replacing cobalt with iron in PdCoO2 films grown by MBE. Using ARPES, we observe similar bulk bands in these PdCoO2 films with Pd-, CoO2-, and FeO2-termination. Nevertheless, Pd- and CoO2-terminated films show a reduced intensity of surface states. Additionally, we are able to epitaxially stabilize PdFexCo1-xO2 films that show an anomaly in the derivative of the electrical resistance with respect to temperature at 20 K, but do not display pronounced magnetic order

Survival prediction from clinico-genomic models - a comparative study

<p>Abstract</p> <p>Background</p> <p>Survival prediction from high-dimensional genomic data is an active field in today's medical research. Most of the proposed prediction methods make use of genomic data alone without considering established clinical covariates that often are available and known to have predictive value. Recent studies suggest that combining clinical and genomic information may improve predictions, but there is a lack of systematic studies on the topic. Also, for the widely used Cox regression model, it is not obvious how to handle such combined models.</p> <p>Results</p> <p>We propose a way to combine classical clinical covariates with genomic data in a clinico-genomic prediction model based on the Cox regression model. The prediction model is obtained by a simultaneous use of both types of covariates, but applying dimension reduction only to the high-dimensional genomic variables. We describe how this can be done for seven well-known prediction methods: variable selection, unsupervised and supervised principal components regression and partial least squares regression, ridge regression, and the lasso. We further perform a systematic comparison of the performance of prediction models using clinical covariates only, genomic data only, or a combination of the two. The comparison is done using three survival data sets containing both clinical information and microarray gene expression data. Matlab code for the clinico-genomic prediction methods is available at <url>http://www.med.uio.no/imb/stat/bmms/software/clinico-genomic/</url>.</p> <p>Conclusions</p> <p>Based on our three data sets, the comparison shows that established clinical covariates will often lead to better predictions than what can be obtained from genomic data alone. In the cases where the genomic models are better than the clinical, ridge regression is used for dimension reduction. We also find that the clinico-genomic models tend to outperform the models based on only genomic data. Further, clinico-genomic models and the use of ridge regression gives for all three data sets better predictions than models based on the clinical covariates alone.</p

Use of ER/PR/HER2 subtypes in conjunction with the 2007 St Gallen Consensus Statement for early breast cancer

<p>Abstract</p> <p>Background</p> <p>The 2007 St Gallen international expert consensus statement describes three risk categories and provides recommendations for treatment of early breast cancer. The set of recommendations on how to best treat primary breast cancer is recognized and used by clinicians worldwide. We now examine the variability of five-year survival of the 2007 St Gallen Risk Classifications utilizing the ER/PR/HER2 subtypes.</p> <p>Methods</p> <p>Using the population-based California Cancer Registry, 114,786 incident cases of Stages 1-3 invasive breast cancer diagnosed between 2000 and 2006 were identified. Cases were assigned to Low, Intermediate, or High Risk categories. Five-year-relative survival was computed for the three St Gallen risk categories and for the ER/PR/HER2 subtypes for further differentiation.</p> <p>Results and Discussion</p> <p>There were 9,124 (13%) cases classified as Low Risk, 44,234 (65%) cases as Intermediate Risk, and 14,340 (21%) as High Risk. Within the Intermediate Risk group, 33,735 (76%) were node-negative (Intermediate Risk 2) and 10,499 (24%) were node-positive (Intermediate Risk 3). For the High Risk group, 6,149 (43%) had 1 to 3 positive axillary lymph nodes (High Risk 4) and 8,191 (57%) had four or more positive lymph nodes (High Risk 5).</p> <p>Using five-year relative survival as the principal criterion, we found the following: a) There was very little difference between the Low Risk and Intermediate Risk categories; b) Use of the ER/PR/HER2 subtypes within the Intermediate and High Risk categories separated each into a group with better five-year survival (ER-positive) and a group with worse survival (ER-negative), irrespective of HER2-status; c) The heterogeneity of the High Risk category was most evident when one examined the ER/PR/HER2 subtypes with four or more positive axillary lymph nodes; (d) HER2-positivity did not always translate to worse survival, as noted when one compared the triple positive subtype (ER+/PR+/HER2+) to the triple negative subtype (ER-/PR-/HER2-); and (e) ER-negativity appeared to be a stronger predictor of poor survival than HER2-positivity.</p> <p>Conclusion</p> <p>The use of ER/PR/HER2 subtype highlights the marked heterogeneity of the Intermediate and High Risk categories of the 2007 St Gallen statements. The use of ER/PR/HER2 subtypes and correlation with molecular classification of breast cancer is recommended.</p

A variant of green fluorescent protein exclusively deposited to active intracellular inclusion bodies

Background: Inclusion bodies (IBs) were generally considered to be inactive protein deposits and did not hold any attractive values in biotechnological applications. Recently, some IBs of recombinant proteins were confirmed to show their functional properties such as enzyme activities, fluorescence, etc. Such biologically active IBs are not commonly formed, but they have great potentials in the fields of biocatalysis, material science and nanotechnology. Results: In this study, we characterized the IBs of DL4, a deletion variant of green fluorescent protein which forms active intracellular aggregates. The DL4 proteins expressed in Escherichia coli were exclusively deposited to IBs, and the IBs were estimated to be mostly composed of active proteins. The spectral properties and quantum yield of the DL4 variant in the active IBs were almost same with those of its native protein. Refolding and stability studies revealed that the deletion mutation in DL4 didn&apos;t affect the folding efficiency of the protein, but destabilized its structure. Analyses specific for amyloid-like structures informed that the inner architecture of DL4 IBs might be amorphous rather than well-organized. The diameter of fluorescent DL4 IBs could be decreased up to 100-200 nm by reducing the expression time of the protein in vivo. Conclusions: To our knowledge, DL4 is the first GFP variant that folds correctly but aggregates exclusively in vivo without any self-aggregating/assembling tags. The fluorescent DL4 IBs have potentials to be used as fluorescent biomaterials. This study also suggests that biologically active IBs can be achieved through engineering a target protein itself.open0

dSETDB1 and SU(VAR)3–9 Sequentially Function during Germline-Stem Cell Differentiation in Drosophila melanogaster

Germline-stem cells (GSCs) produce gametes and are thus true “immortal stem cells”. In Drosophila ovaries, GSCs divide asymmetrically to produce daughter GSCs and cystoblasts, and the latter differentiate into germline cysts. Here we show that the histone-lysine methyltransferase dSETDB1, located in pericentric heterochromatin, catalyzes H3-K9 trimethylation in GSCs and their immediate descendants. As germline cysts differentiate into egg chambers, the dSETDB1 function is gradually taken over by another H3-K9-specific methyltransferase, SU(VAR)3–9. Loss-of-function mutations in dsetdb1 or Su(var)3–9 abolish both H3K9me3 and heterochromatin protein-1 (HP1) signals from the anterior germarium and the developing egg chambers, respectively, and cause localization of H3K9me3 away from DNA-dense regions in most posterior germarium cells. These results indicate that dSETDB1 and SU(VAR)3–9 act together with distinct roles during oogenesis, with dsetdb1 being of particular importance due to its GSC-specific function and more severe mutant phenotype

The Antidiabetic Effect of MSCs Is Not Impaired by Insulin Prophylaxis and Is Not Improved by a Second Dose of Cells

Type 1 diabetes mellitus (T1D) is due to autoimmune destruction of pancreatic beta-cells. Previously, we have shown that intravenously administered bone marrow-derived multipotent mesenchymal stromal cells (MSCs) allows pancreatic islet recovery, improves insulin secretion and reverts hyperglycemia in low doses streptozotocin (STZ)-induced diabetic mice. Here we evaluate whether insulin prophylaxis and the administration of a second dose of cells affect the antidiabetic therapeutic effect of MSC transplantation. Insulitis and subsequent elimination of pancreatic beta-cells was promoted in C57BL/6 mice by the injection of 40 mg/kg/day STZ for five days. Twenty-four days later, diabetic mice were distributed into experimental groups according to if they received or not insulin and/or one or two doses of healthy donor-derived MSCs. Three and half months later: glycemia, pancreatic islets number, insulinemia, glycated hemoglobin level and glucose tolerance were determined in animals that did not received exogenous insulin for the last 1.5 months. Also, we characterized MSCs isolated from mice healthy or diabetic. The therapeutic effect of MSC transplantation was observed in diabetic mice that received or not insulin prophylaxis. Improvements were similar irrespective if they received one or two doses of cells. Compared to MSCs from healthy mice, MSCs from diabetic mice had the same proliferation and adipogenic potentials, but were less abundant, with altered immunophenotype and no osteogenic potential

Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer

Introduction: Human epidermal growth factor receptor 2 (HER2)-amplified breast cancer represents a clinically well-defined subgroup due to availability of targeted treatment. However, HER2-amplified tumors have been shown to be heterogeneous at the genomic level by genome-wide microarray analyses, pointing towards a need of further investigations for identification of recurrent copy number alterations and delineation of patterns of allelic imbalance. Methods: High-density whole genome array-based comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) array data from 260 HER2-amplified breast tumors or cell lines, and 346 HER2-negative breast cancers with molecular subtype information were assembled from different repositories. Copy number alteration (CNA), loss-of-heterozygosity (LOH), copy number neutral allelic imbalance (CNN-AI), subclonal CNA and patterns of tumor DNA ploidy were analyzed using bioinformatical methods such as genomic identification of significant targets in cancer (GISTIC) and genome alteration print (GAP). The patterns of tumor ploidy were confirmed in 338 unrelated breast cancers analyzed by DNA flow cytometry with concurrent BAC aCGH and gene expression data. Results: A core set of 36 genomic regions commonly affected by copy number gain or loss was identified by integrating results with a previous study, together comprising > 400 HER2-amplified tumors. While CNN-AI frequency appeared evenly distributed over chromosomes in HER2-amplified tumors, not targeting specific regions and often < 20% in frequency, the occurrence of LOH was strongly associated with regions of copy number loss. HER2-amplified and HER2-negative tumors stratified by molecular subtypes displayed different patterns of LOH and CNN-AI, with basal-like tumors showing highest frequencies followed by HER2-amplified and luminal B cases. Tumor aneuploidy was strongly associated with increasing levels of LOH, CNN-AI, CNAs and occurrence of subclonal copy number events, irrespective of subtype. Finally, SNP data from individual tumors indicated that genomic amplification in general appears as monoallelic, that is, it preferentially targets one parental chromosome in HER2-amplified tumors. Conclusions: We have delineated the genomic landscape of CNAs, amplifications, LOH, and CNN-AI in HER2-amplified breast cancer, but also demonstrated a strong association between different types of genomic aberrations and tumor aneuploidy irrespective of molecular subtype

Identification of Enriched Driver Gene Alterations in Subgroups of Non-Small Cell Lung Cancer Patients Based on Histology and Smoking Status

BACKGROUND: Appropriate patient selection is needed for targeted therapies that are efficacious only in patients with specific genetic alterations. We aimed to define subgroups of patients with candidate driver genes in patients with non-small cell lung cancer. METHODS: Patients with primary lung cancer who underwent clinical genetic tests at Guangdong General Hospital were enrolled. Driver genes were detected by sequencing, high-resolution melt analysis, qPCR, or multiple PCR and RACE methods. RESULTS: 524 patients were enrolled in this study, and the differences in driver gene alterations among subgroups were analyzed based on histology and smoking status. In a subgroup of non-smokers with adenocarcinoma, EGFR was the most frequently altered gene, with a mutation rate of 49.8%, followed by EML4-ALK (9.3%), PTEN (9.1%), PIK3CA (5.2%), c-Met (4.8%), KRAS (4.5%), STK11 (2.7%), and BRAF (1.9%). The three most frequently altered genes in a subgroup of smokers with adenocarcinoma were EGFR (22.0%), STK11 (19.0%), and KRAS (12.0%). We only found EGFR (8.0%), c-Met (2.8%), and PIK3CA (2.6%) alterations in the non-smoker with squamous cell carcinoma (SCC) subgroup. PTEN (16.1%), STK11 (8.3%), and PIK3CA (7.2%) were the three most frequently enriched genes in smokers with SCC. DDR2 and FGFR2 only presented in smokers with SCC (4.4% and 2.2%, respectively). Among these four subgroups, the differences in EGFR, KRAS, and PTEN mutations were statistically significant. CONCLUSION: The distinct features of driver gene alterations in different subgroups based on histology and smoking status were helpful in defining patients for future clinical trials that target these genes. This study also suggests that we may consider patients with infrequent alterations of driver genes as having rare or orphan diseases that should be managed with special molecularly targeted therapies

Tumour expression of leptin is associated with chemotherapy resistance and therapy-independent prognosis in gastro-oesophageal adenocarcinomas

Background: Cytotoxic chemotherapy remains the main systemic therapy for gastro-oesophageal adenocarcinoma, but resistance to chemotherapy is common, resulting in ineffective and often toxic treatment for patients. Predictive biomarkers for chemotherapy response would increase the probability of successful therapy, but none are currently recommended for clinical use. We used global gene expression profiling of tumour biopsies to identify novel predictive biomarkers for cytotoxic chemotherapy. Methods: Tumour biopsies from patients (n=14) with TNM stage IB–IV gastro-oesophageal adenocarcinomas receiving platinum-based combination chemotherapy were used as a discovery cohort and profiled with Affymetrix ST1.0 Exon Genechips. An independent cohort of patients (n=154) treated with surgery with or without neoadjuvant platinum combination chemotherapy and gastric adenocarcinoma cell lines (n=22) were used for qualification of gene expression profiling results by immunohistochemistry. A cisplatin-resistant gastric cancer cell line, AGS Cis5, and the oesophageal adenocarcinoma cell line, OE33, were used for in vitro validation investigations. Results: We identified 520 genes with differential expression (Mann–Whitney U, P<0.020) between radiological responding and nonresponding patients. Gene enrichment analysis (DAVID v6.7) was used on this list of 520 genes to identify pathways associated with response and identified the adipocytokine signalling pathway, with higher leptin mRNA associated with lack of radiological response (P=0.011). Similarly, in the independent cohort (n=154), higher leptin protein expression by immunohistochemistry in the tumour cells was associated with lack of histopathological response (P=0.007). Higher leptin protein expression by immunohistochemistry was also associated with improved survival in the absence of neoadjuvant chemotherapy, and patients with low leptin protein-expressing tumours had improved survival when treated by neoadjuvant chemotherapy (P for interaction=0.038). In the gastric adenocarcinoma cell lines, higher leptin protein expression was associated with resistance to cisplatin (P=0.008), but not to oxaliplatin (P=0.988) or 5fluorouracil (P=0.636). The leptin receptor antagonist SHLA increased the sensitivity of AGS Cis5 and OE33 cell lines to cisplatin. Conclusions: In gastro-oesophageal adenocarcinomas, tumour leptin expression is associated with chemoresistance but a better therapy-independent prognosis. Tumour leptin expression determined by immunohistochemistry has potential utility as a predictive marker of resistance to cytotoxic chemotherapy, and a prognostic marker independent of therapy in gastro-oesophageal adenocarcinoma. Leptin antagonists have been developed for clinical use and leptin and its associated pathways may also provide much needed novel therapeutic targets for gastro-oesophageal adenocarcinoma