Evangelical Visitor- October 2, 1911. Vol. XXV. No. 20.

Evangelical Visitor published in Harrisburg, Pa., for the exposition of true, practical piety and devoted to the spread of evangelical truths and the unity of the church. Published in the interest of the church of the Brethren in Christ on October 2, 1911. Vol. XXV. No. 20

SEOM clinical guidelines in early stage breast cancer (2018)

Breast cancer is the most common cancer in women in our country and it is usually diagnosed in the early and potentially curable stages. Nevertheless, around 20–30% of patients will relapse despite appropriate locoregional and systemic therapies. A better knowledge of this disease is improving our ability to select the most appropriate therapy for each patient with a recent diagnosis of an early stage breast cancer, minimizing unnecessary toxicities and improving long-term efficacy

Famosa: Evaluation of a multigene panel in patients with suspected HBOC

Background: Objectives: Characterize 1) the frequency of mutations in patients with clinical criteria for HBOC using a 25-gene panel in a Spanish population (FAMOSA study). 2) The psychological impact of these tests and patient''s counseling preferences. Methods: Patients with breast or ovarian cancer who met the NCCN criteria for genetic testing with a) prior testing for BRCA genes with NO mutation identified; or b) recently diagnosed (<6 months) and not genetically tested, were enrolled for multiplex cancer testing (MyRisk 25-gene panel). Participants completed self-questionnaires regarding geneting counseling preferences and three psychological scales (MICRA, CWS, R-IES) at base-line, one week, three and twelve months after results disclosure. Results: From November 14 to February 15, 210 patients were included in the FAMOSA study (109 HBOC). 61 (56%) patients were previously tested for BRCA1/2 gene mutations with conventional techniques; median age: 44y (22-77); gender: 3 males / 106 females; cancer types: breast 95 (87%); ovary 14 (13%). Overall 22 pathogenic variants were identified in 21 patients (19, 3%): 10 BRCA1, 2 BRCA2, 2 PALB2, 3 MUYTH, 1 CDKN2A; 2 ATM, 1 BRAD1, 1 BRIP1. One patient had an unexpected mutation in CDKN2A gene (gluteus sarcoma age 20; bilateral breast ca; ages 45 and 50; father lung ca, age 70; brother melanoma, age 35). Three patients had a significant mutation of a recessive condition in MUYTH. Of 61 patients previously tested negative for HBOC, 1 had a pathogenic variant in BRCA1 and 17/ 19 patients with VUS were classified negative in BRCA genes with MyRisk.Patients are willing to be disclosed all available information from panel testing. Differences were observed among type of results at short and mid-term. Cancer worry was higher in moderate-penetrance carriers than high penetrance carriers. Longer follow up is ongoing. Conclusions: Panel testing in patients with HBOC yielded a 19, 3% mutation rate, increasing the yield of genetic mutations beyond BRCA. Patients are willing to be disclosed all available information from panel testing

ACE and CXCL10 as predictive biomarkers in the LEA study

Background: LEA Study (GEICAM/2006-11/GBG51), is a randomized clinical trial comparing bevacizumab in combination with endocrine therapy (ET + B) with endocrine therapy (ET) in postmenopausal women with advanced or metastatic HR-positive/HER2-negative breast cancer (BC) with indication of hormonotherapy as first-line treatment. Patients with secondary hypertension had better progression-free survival (PFS) and overall survival (OS). We have evaluated the role of two hypertension-related biomarkers, Angiotensin-Converting Enzyme (ACE) and Small-Inducible Cytokine B10 (CXCL10) as prognostic and/or predictive biomarkers of benefit to bevacizumab in the first line metastatic disease. Methods: From 380 patients, 266 were included in 33 Spanish sites. Median age was 64 years, 63.5% had measurable disease, 97.4% were metastatic at randomization, 51.5% had visceral disease and 52.6% received previous chemotherapy. PFS was 14.3 months (range 0.8-61.1), OS was 34 months (range 0.8-71.6) and 93 patients had Objective Response (OR). We analyzed 124 plasma samples collected before treatment (52 from ET and 72 from ET + B arms). Circulating levels of ACE and CXCL10 were determined by ELISA. ACE levels of 115ng/ml and 135ng/ml were pre-defined as cutoff values. CXCL10 was explored as a quantitative variable. Results: PFS was 15.1 months (range 1.4-61.1), OS was 31.1 months (range 2.8-61.1) and 40.3% had OR. OR was significantly different between treatment arms (p < 0.001) but not PFS or OS. Median ACE concentration was 130.9ng/ml (range 35.3-315.4). Low ACE (<135ng/ml) had better PFS in the whole population (p = 0.048) and in the ET + B arm (p = 0.041). ACE cutoff of 115 ng/ml was not able to identify any subgroup with better prognosis. Median CXCL10 concentration was 230.3pg/ml (range 15.1-4129.6). A higher expression of CXCL10 was significantly associated with worse OS in the whole population (p < 0.0001) and each treatment arm (p = 0.002 and p = 0.001 in ET and ET + B, respectively). No association with OR were identified neither for ACE nor for CXCL10. Conclusions: ACE levels could be considered a prognostic and a bevacizumab predictive biomarker of PFS. CXCL10 could be prognostic of OS. Confirmatory studies are warranted

EuroDia: a beta-cell gene expression resource

Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms

Health-related quality of life with palbociclib plus endocrine therapy versus capecitabine in postmenopausal patients with hormone receptor–positive metastatic breast cancer: Patient-reported outcomes in the PEARL study

Background: The PEARL study showed that palbociclib plus endocrine therapy (palbociclib/ET) was not superior to capecitabine in improving progression-free survival in postmenopausal patients with metastatic breast cancer resistant to aromatase inhibitors, but was better tolerated. This analysis compared patient-reported outcomes. Patients and methods: The PEARL quality of life (QoL) population comprised 537 patients, 268 randomised to palbociclib/ET (exemestane or fulvestrant) and 269 to capecitabine. Patients completed the European Organisation for Research and Treatment of Cancer QLQ-C30 and QLQ-BR23 and EQ-5D-3L questionnaires. Changes from the baseline and time to deterioration (TTD) were analysed using linear mixed-effect and stratified Cox regression models, respectively. Results: Questionnaire completion rate was high and similar between treatment arms. Significant differences were observed in the mean change in global health status (GHS)/QoL scores from the baseline to cycle 3 (2.9 for palbociclib/ET vs. -2.1 for capecitabine (95% confidence interval [CI], 1.4–8.6; P = 0.007). The median TTD in GHS/QoL was 8.3 months for palbociclib/ET versus 5.3 months for capecitabine (adjusted hazard ratio, 0.70; 95% CI, 0.55–0.89; P = 0.003). Similar improvements for palbociclib/ET were also seen for other scales as physical, role, cognitive, social functioning, fatigue, nausea/vomiting and appetite loss. No differences were observed between the treatment arms in change from the baseline in any item of the EQ-5D-L3 questionnaire as per the overall index score and visual analogue scale. Conclusion: Patients receiving palbociclib/ET experienced a significant delay in deterioration of GHS/QoL and several functional and symptom scales compared with capecitabine, providing additional evidence that palbociclib/ET is better tolerated. Trial registration number: NCT02028507 (ClinTrials.gov). EudraCT study number: 2013-003170-27. © 2021 The Author(s

Anomalous Features of EMT during Keratinocyte Transformation

During the evolution of epithelial cancers, cells often lose their characteristic features and acquire a mesenchymal phenotype, in a process known as epithelial-mesenchymal transition (EMT). In the present study we followed early stages of keratinocyte transformation by HPV16, and observed diverse cellular changes, associated with EMT. We compared primary keratinocytes with early and late passages of HF1 cells, a cell line of HPV16-transformed keratinocytes. We have previously shown that during the progression from the normal cells to early HF1 cells, immortalization is acquired, while in the progression to late HF1, cells become anchorage independent. We show here that during the transition from the normal state to late HF1 cells, there is a progressive reduction in cytokeratin expression, desmosome formation, adherens junctions and focal adhesions, ultimately leading to poorly adhesive phenotype, which is associated with anchorage-independence. Surprisingly, unlike “conventional EMT”, these changes are associated with reduced Rac1-dependent cell migration. We monitored reduced Rac1-dependent migration also in the cervical cancer cell line SiHa. Therefore we can conclude that up to the stage of tumor formation migratory activity is eliminated

Predicting Pancreas Cell Fate Decisions and Reprogramming with a Hierarchical Multi-Attractor Model

Cell fate reprogramming, such as the generation of insulin-producing β cells from other pancreas cells, can be achieved by external modulation of key transcription factors. However, the known gene regulatory interactions that form a complex network with multiple feedback loops make it increasingly difficult to design the cell reprogramming scheme because the linear regulatory pathways as schemes of causal influences upon cell lineages are inadequate for predicting the effect of transcriptional perturbation. However, sufficient information on regulatory networks is usually not available for detailed formal models. Here we demonstrate that by using the qualitatively described regulatory interactions as the basis for a coarse-grained dynamical ODE (ordinary differential equation) based model, it is possible to recapitulate the observed attractors of the exocrine and β, δ, α endocrine cells and to predict which gene perturbation can result in desired lineage reprogramming. Our model indicates that the constraints imposed by the incompletely elucidated regulatory network architecture suffice to build a predictive model for making informed decisions in choosing the set of transcription factors that need to be modulated for fate reprogramming

Immunohistochemical assessment of Pax8 expression during pancreatic islet development and in human neuroendocrine tumors

The paired box transcription factor Pax8 is critical for development of the eye, thyroid gland as well as the urinary and reproductive organs. In adult, Pax8 overexpression is associated with kidney, ovarian and thyroid tumors and has emerged as a specific marker for these cancers. Recently, Pax8 expression was also reported in human pancreatic islets and in neuroendocrine tumors, identifying Pax8 as a novel member of the Pax family expressed in the pancreas. Herein, we sought to provide a comprehensive analysis of Pax8 expression during pancreogenesis and in adult islets. Immunohistochemical analysis using the most employed Pax8 polyclonal antibody revealed strong nuclear staining in the developing mouse pancreas and in mature human and mouse islets. Astonishingly, Pax8 mRNA in mouse islets was undetectable while human islets exhibited low levels. These discrepancies raised the possibility of antibody cross-reactivity. This premise was confirmed by demonstrating that the polyclonal Pax8 antibody also recognized the islet-enriched Pax6 protein both by Western blotting and immunohistochemistry. Thus, in islets polyclonal Pax8 staining corresponds mainly to Pax6. In order to circumvent this caveat, a novel Pax8 monoclonal antibody was used to re-evaluate whether Pax8 was indeed expressed in islets. Surprisingly, Pax8 was not detected in neither the developing pancreas or in mature islets. Reappraisal of pancreatic neuroendocrine tumors using this Pax8 monoclonal antibody exhibited no immunostaining as compared to the Pax8 polyclonal antibody. In conclusion, Pax8 is not expressed in the pancreas and cast doubts on the value of Pax8 as a pancreatic neuroendocrine tumor marker

Quantitative utilization of prior biological knowledge in the Bayesian network modeling of gene expression data

<p>Abstract</p> <p>Background</p> <p>Bayesian Network (BN) is a powerful approach to reconstructing genetic regulatory networks from gene expression data. However, expression data by itself suffers from high noise and lack of power. Incorporating prior biological knowledge can improve the performance. As each type of prior knowledge on its own may be incomplete or limited by quality issues, integrating multiple sources of prior knowledge to utilize their consensus is desirable.</p> <p>Results</p> <p>We introduce a new method to incorporate the quantitative information from multiple sources of prior knowledge. It first uses the Naïve Bayesian classifier to assess the likelihood of functional linkage between gene pairs based on prior knowledge. In this study we included cocitation in PubMed and schematic similarity in Gene Ontology annotation. A candidate network edge reservoir is then created in which the copy number of each edge is proportional to the estimated likelihood of linkage between the two corresponding genes. In network simulation the Markov Chain Monte Carlo sampling algorithm is adopted, and samples from this reservoir at each iteration to generate new candidate networks. We evaluated the new algorithm using both simulated and real gene expression data including that from a yeast cell cycle and a mouse pancreas development/growth study. Incorporating prior knowledge led to a ~2 fold increase in the number of known transcription regulations recovered, without significant change in false positive rate. In contrast, without the prior knowledge BN modeling is not always better than a random selection, demonstrating the necessity in network modeling to supplement the gene expression data with additional information.</p> <p>Conclusion</p> <p>our new development provides a statistical means to utilize the quantitative information in prior biological knowledge in the BN modeling of gene expression data, which significantly improves the performance.</p