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CDC Findings: Due to Aging Population, Actual Number of Cancer Deaths is Rising while Risk of Dying From Cancer is Falling in the US

 

Reporter: Aviva Lev-Ari, PhD, RN

 

SOURCES: Mary White, Sc.D., M.P.H., scientist, division of cancer prevention and control, U.S. Centers for Disease Control and Prevention; David Katz, M.D., M.P.H., director, Yale University Prevention Research Center, New Haven, Conn.; Rich Wender, M.D., chief, cancer control officer, American Cancer Society; July 2015, Preventing Chronic Disease

Last Updated: Jul 2, 2015

THURSDAY, July 2, 2015 (HealthDay News) — The risk that any one American will die from cancer — the cancer death rate — is going down, regardless of sex or race, a new government study reports.

However, because the United States has a growing aging population, the overall number of people dying from cancer is on the rise, officials from the U.S. Centers for Disease Control and Prevention reported.

“While we are making progress in reducing cancer death rates, we still have real work to do to reduce cancer deaths among our aging population,” said lead researcher Mary White, a scientist in the CDC’s division of cancer prevention and control.

Between 2007 and 2020, cancer deaths are expected to rise more than 10 percent among men and black women, the report found. Among white women, the number of cancer deaths will start to stabilize, increasing less than 5 percent during this period, according to the CDC researchers.

“Further declines in cancer deaths might be achieved if we can reach other national targets for addressing risk factors,” White said.

These include cutting exposure to tobacco and UV radiation, increasing cancer screening for early detection, and improving access to health care to increase early treatment and survival, she said.

White said that a decline in cancer death rates — even as the actual number of cancer deaths rises — is not a paradox.

“Death rates are calculated by dividing the number of cancer deaths by the number of people in the population,” she explained.

The number of older adults continues to grow, White explained. “Because death rates for many cancers increase with age, the number of people who die from cancer is also predicted to grow, even while death rates decline,” she said.

Dr. David Katz, director of the Yale University Prevention Research Center in New Haven, Conn., agreed that reducing cancer deaths and reducing cancer are not the same.

“Cancer death rates are declining markedly, which is excellent news and testimony to the power of early detection and improving treatments,” said Katz, who was not involved with the study.

And Dr. Rich Wender, the chief cancer control officer at the American Cancer Society, said, “We have made substantial progress for many of the common adult cancers. The key to that progress is applying research about how to prevent cancer, how to detect it early and treat it effectively.”

The report is published in the July issue of the journal Preventing Chronic Disease.

According to the study findings, between 1975 and 2009, the number of cancer deaths increased 45.5 percent among white men, 56 percent among white women, 53 percent among black men and 98 percent among black women.

These increases are primarily attributed to an aging white population and an increasing black population, White said. This pattern is likely to continue, she added.

The government’s Healthy People 2020 initiative set a goal of reducing the rate of cancer deaths by 10 to 15 percent for some cancers by 2020. This target was met for prostate cancer in 2010, the study authors said.

Researchers expect to meet the goal for breast, cervix, colon and rectum, lung and bronchus cancers in 2015. The death rates for cancers of the oral cavity and pharynx seem to be stabilizing, the report said.

However, the goal for melanoma is not expected to be achieved. “It’s discouraging to find out that we aren’t reducing deaths from melanoma, the most deadly form of skin cancer,” White said.

“We know that most cases of melanoma are preventable,” she said. “To lower your skin cancer risk, protect your skin from the sun and avoid indoor tanning.”

White suggested the people can lower their own risk of dying from cancer by learning about screening tests and other steps they can take to prevent cancer.

“While we have seen improvements to lower cancer deaths, everyone can learn about screening tests and the cancer prevention steps that are right for them,” she said.

Katz pointed out that “back in 1981, researchers first highlighted the substantial preventability of cancer by changing one’s lifestyle. Most authorities remain convinced that 30 to 60 percent of cancers could be prevented by avoiding tobacco, having a healthy diet, routine activity and weight control.”

SOURCE

http://www.nlm.nih.gov/medlineplus/news/fullstory_153389.html

Mary White, Sc.D., M.P.H., scientist, division of cancer prevention and control, U.S. Centers for Disease Control and Prevention; David Katz, M.D., M.P.H., director, Yale University Prevention Research Center, New Haven, Conn.; Rich Wender, M.D., chief, cancer control officer, American Cancer Society; July 2015, Preventing Chronic Disease

 


Originally posted on Beyond the Dish:

A study published online by the journal Science Translational Medicine discusses a new experimental treatment for a rare, deadly leukemia (blood cancer) that can send the disease into remission even in those patients for whom the standard therapy has failed. Such a treatment can buy patients more time to have a stem cell transplant that could save their lives. This study was only a small pilot study, but these findings are potentially revolutionary.

“It was unbelievable, really, seeing a patient who had already failed Campath [the drug typically used to treat the disease] literally going back into remission,” said Thomas P. Loughran Jr., MD, the director of the University of Virginia Cancer Center, who also served as one of the lead researchers of this study. “We were able to get every single patient back into remission.”

This new approach for battling T-cell prolymphocytic leukemia combines immunotherapy, which boosts the body’s…

View original 494 more words


Atherosclerosis: What is New in Biomarker Discovery

Reporter: Aviva Lev-Ari, PhD, RN
Eur Heart J. 2015 Jun 5. pii: ehv236. [Epub ahead of print]

Novel methodologies for biomarker discovery in atherosclerosis.

Abstract

Identification of subjects at increased risk for cardiovascular events plays a central role in the worldwide efforts to improve prevention, prediction, diagnosis, and prognosis of cardiovascular disease and to decrease the related costs. Despite their high predictive value on population level, traditional risk factors fail to fully predict individual risk. This position paper provides a summary of current vascular biomarkers other than the traditional risk factors with a special focus on the emerging -omics technologies. The definition of biomarkers and the identification and use of classical biomarkers are introduced, and we discuss the limitations of current biomarkers such as high sensitivity C-reactive protein (hsCRP) or N-terminal pro-brain natriuretic peptide (NT-proBNP). This is complemented by circulating plasma biomarkers, including high-density lipoprotein (HDL), and the conceptual shift from HDL cholesterol levels to HDL composition/function for cardiovascular risk assessment.

Novel sources for plasma-derived markers include

  • microparticles,
  • microvesicles, and
  • exosomes and their use for current omics-based analytics.

Measurement of

  • circulating micro-RNAs,
  • short RNA sequences regulating gene expression,

has attracted major interest in the search for novel biomarkers. Also,

  • mass spectrometry and
  • nuclear magnetic resonance spectroscopy

have become key complementary technologies in the search for new biomarkers, such as

  • proteomic searches or
  • identification and quantification of small metabolites including lipids (metabolomics and lipidomics). In particular,
  • pro-inflammatory lipid metabolites

have gained much interest in the cardiovascular field. Our consensus statement concludes on leads and needs in biomarker research for the near future to improve individual cardiovascular risk prediction.

Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

KEYWORDS:

Atherosclerosis; Clinical biomarker; HDL; Mass spectrometry; Micro-RNA; Risk prediction; Systems biology

PMID:
26049157
[PubMed – as supplied by publisher]

SOURCE

http://www.ncbi.nlm.nih.gov/pubmed/26049157


Human Microbiome: Recent Advances and New Treatments

Reporter: Aviva Lev-Ari, PhD, RN

Recent Advances and New Treatments in Understanding the Human Microbiome

 

Cambridge Health Tech Institute

End Pre-Header Preview Main Content

Dear Colleague,

While the microbiome R&D is an emerging area of science that is starting to prove its importance, much advancement has been made in using the microbiome as a tool for therapeutic development.

Over 15 leading researchers and thought leaders assemble at Drug Discovery on Target’s Targeting the Microbiome Track this September 22-23, 2015 in Boston, MA to share best practices and applications of these important advancements.

These particular presentations in the Track discuss advancements, new concepts in treatment of disease, computational approaches, ecological perspectives, and more:

Keynote Presentation: Recent Advances in Understanding the Human Microbiome 

Karen E. Nelson, Ph.D., President, J. Craig Venter Institute (JCVI)

Our recent studies on the human microbiome highlight a higher degree of microbial diversity within and across individuals than was previously appreciated as well as new microbial species whose roles remain unexplored. Studying healthy and diseased human populations, their microbiomes and circulating metabolites present new opportunities for defining novel diagnostics and therapeutic approaches for several human diseases. It is clear that the advent of metagenomics holds significant promise for increasing our understanding of many microbial diseases associated with the human body, inclusive of those that are yet to be characterized.

Computational and Synthetic Biology Approaches for Discovering Microbiome Interactions and Functions

Georg K. Gerber, M.D., Ph.D., MPH, Assistant Professor of Pathology, Harvard Medical School; Co-Director, Center for Clinical and Translation Metagenomics, Director, Computational Unit, Associate Pathologist, Department of Pathology, Brigham and Women’s Hospital

I will describe: (1) a new computational approach for accurately predicting microbiota dynamics, with applications to finding networks of bacteria that protect against a human enteric pathogen, and (2) a synthetic biology platform to functionally mine bacterial genomes for genes that contribute to fitness, with applications to finding genes important for colonizing the mammalian gut over time.

Studying the Microbiome Community Networks Across Different Body Sites

Corrado Priami, Ph.D., Professor, Computer Science, The University of Trento; President and CEO, The Microsoft Research – University of Trento Centre for Computational and Systems Biology (COSBI)

The study aims to get an ecological view of microbiota from systems perspective across different body sites. Microbiome community networks were computed for samples from two different body sources, based on maximal information content. The patterns were compared and enriched with functional annotation to discover strong relationships between biological processes and microbes.

Keynote Presentation: Exploring the Medical Microbiome 

George M. Weinstock, Ph.D. Professor and Associate Director, Jackson Laboratory for Genomic Medicine, Farmington CT

The Human Microbiome, the collection of microbes colonizing the human body, is coming under increasingly sophisticated scrutiny as genomic technologies and analytic tools advance. Microbiome research continues to find correlations between the microbial ecology of the human body and diseases, lifestyles, and other factors. The most recent projects bring together studies of the host with that of the microbes and involve large multidisciplinary datasets that present complex profiles to be mined for diagnostic and mechanistic clues to health and disease. The fruits of this research are leading to new concepts in treatment of disease.

Hear the above and more first-hand experiences and case studies at the Targeting the Microbiome Track taking place at the 12th Annual Discovery on Target, September 22-23, 2015 in Boston, MA.

For more details on the program agenda and speaker line-up, please visit:

www.discoveryontarget.com/targeting-microbiome

I hope you’ll join us this September in Boston to learn about microbial targeted therapies and tools to improve disease treatment and health maintenance.

Sincerely,

Cindy Crowninshield, RDN, LDN, HHC
Senior Conference Director/Team Lead
Cambridge Healthtech Institute
ccrowninshield@healthtech.com End Main Content Start Footer

Cambridge Healthtech Institute

250 First Avenue, Suite 300 | Needham, MA 02494 | P: 781.972.5400 | E: chi@healthtech.com

www.healthtech.com

SOURCE

From: “Cindy Crowninshield” <kerris@discoveryontarget.com>

Date: July 1, 2015 at 9:59:00 AM EDT

To: avivalev-ari@alum.berkeley.edu

Subject: Recent Advances and New Treatments in Understanding the Human Microbiome


Novel Modeling Methods for Genomic Data Analysis & Evolutionary Systems Biology to Design Dosing Regimens to Minimize Resistance

Reporter: Aviva Lev-Ari, PhD, RN

Dana-Farber’s Franziska Michor to Present Novel Modeling Methods for Genomic Data Analysis

As part of Discovery on Target’s new Quantitative Systems Pharmacology conference, Dr. Franziska Michor, will provide her team’s experiences in employing state-of the-art modeling methods to address treatment response and the evolution of resistance. The event will be held September 23-24 in Boston and will bring together experts in QSP and the researchers interested in using this methodology.

Featured Presentation: Applying Evolutionary Systems Biology to Design Dosing Regimens to Minimize Resistance

Franziska Michor, Ph.D., Professor, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute,Department of Biostatistics, Harvard School of Public Health

 

Final Agenda

APPLICATIONS OF QSP TO DRUG DISCOVERY AND DEVELOPMENT

Right Target, Right Dose, Right Trial with Limited Animal Use: QSP Doubles the 3R Benefits
Valeriu Damian-Iordcahe, Ph.D., Head, Modelling and Translational Biology, GSK

The QSP Extensibility Concept: A Physiology-Based Multi-Scale Model as a Platform to Address Wide-Ranging Clinical Questions
Mark C. Peterson, Ph.D., Director, Global Pharmacometrics, GIPB Clinical Pharmacology, Pfizer, Inc.

Creating and Performing Research with PhysioPD™ Research Platforms: Overview and Case Study

Ananth Kadambi, Ph.D., Senior Vice President, PhysioPD™, Rosa & Co.

Diverse Application with a Common Underlying Workflow
Saroja Ramanujan, Ph.D., Senior Scientist, Group Lead, Translational & Systems Pharmacology, Genentech

Building Translational Quantitative Pharmacology: The Merck Experience
Prajakti Kothare, Ph.D., Scientific Lead, Early Phase Quantitative Pharmacology & Pharmacometrics, Pharmacokinetics, Pharmacodynamics & Drug Metabolism, Merck

INTERACTIVE BREAKOUT DISCUSSIONS

Partnerships between Academia, Government and Industry to Implement QSP as A New Paradigm for Drug Discovery

Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation, Professor of Computational and Systems Biology, University of Pittsburgh

Preclinical-to-Clinical Translation in Oncology: Principles and Best Practices

Arijit Chakravarty, Ph.D., Director, Modeling and Simulation (DMPK), Takeda Pharmaceuticals International Co.

SYSTEMS DISEASE MODELS

A Quantitative Systems Pharmacology (QSP) Framework for Oncology Translational and Early Clinical Development
Arijit Chakravarty, Ph.D., Director, Modeling and Simulation (DMPK), Takeda Pharmaceuticals International Co.

Applying Evolutionary Systems Biology To Design Dosing Regimens To Minimize Resistance
Franziska Michor, Ph.D., Professor, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Department of Biostatistics, Harvard School of Public Health

Development and Application of the Coagulation Systems Model
Fei Hua, Ph.D., Clinical Pharmacology Lead, PharmaTx Clinical Research & Development, Pfizer, Inc.

Applications of Quantitative Systems Pharmacology (QSP) in Crohn’s Disease Drug Discovery and Development
Oliver Ghobrial, Ph.D., Senior Research Scientist III, Translational Modeling and Simulation, AbbVie

Adaptive Resistance and Fractional Response of Cancer Cells to Therapy
Mohammad Fallahi-Sichani, Ph.D., Merck Fellow of the Life Sciences Research Foundation, Department of Systems Biology, Harvard Medical School

QSP FOR BIOMARKERS IDENTIFICATION AND DEVELOPMENT

Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery in Academia

Lansing Taylor, Ph.D., Director, University of Pittsburgh Drug Discovery Institute & Allegheny Foundation, Professor of Computational and Systems Biology, University of Pittsburgh

Systems Pharmacology Insights for Patient Selection for Liposomal Anti-Cancer Therapy: From Idea to Clinical Evaluation
Bart Hendriks, Ph.D., Director, Research & Development, Merrimack Pharmaceuticals

TECHNOLOGIES FOR QUANTITATIVE PHARMACOLOGY

Engineering Targeted Growth Factors to Repair Heart Tissue Following Ischemic Injury
Matthew Onsum, Ph.D., President and CEO, Silver Creek Pharmaceuticals

Kriging – An Emerging Technology with the Potential of Improving the Precision of in silico Predictions and Eliminating the Need for Creating Local Models
Istvan Enyedy, Ph.D., Senior Scientist, Chemistry and Molecular Therapeutics, Biogen

A Massively Orthogonal Pharmacology Search Engine: Can All of Our Models and Data Be “GoogledTM”?
Douglas Selinger, Ph.D., Manager, Bioinformatics, Preclinical Safety, Novartis Institutes for BioMedical Research

Also Available at Discovery on Target:

Short Course: Using Mechanistic Physiological Models in Drug Development: A Proven Quantitative Systems Pharmacology (QSP) Approach (Separate Registration Required)

SOURCE

From: “Quantitative Systems Pharmacology” <jaimeh@healthtech.com>

Date: July 1, 2015 at 9:20:00 AM EDT

To: avivalev-ari@alum.berkeley.edu

Subject: Dana-Farber’s Franziska Michor Presents Novel Modeling for Genomic Data


Archives of Medicine (AOM) to Publish from “Leaders in Pharmaceutical Business Intelligence (LPBI)” Open Access On-Line Scientific Journal http://pharmaceuticalintelligence.com

Reporter: Aviva Lev-Ari, PhD, RN

From our series on Calcium and Cardiovascular Diseases: A Series of Twelve Articles in Advanced Cardiology

AOM Editor-in Chief’s Article Selection and Assignment of manuscript number: iMedPub Journals includes the following and is updated as soon as additional selections are made

Part I:

Identification of Biomarkers that are Related to the Actin Cytoskeleton

Larry H Bernstein, MD, FCAP

  

Part II: has been been assigned the following manuscript number: iMedPub Journals-15-472

Role of Calcium, the Actin Skeleton, and Lipid Structures in Signaling and Cell Motility

Larry H. Bernstein, MD, FCAP, Stephen Williams, PhD and Aviva Lev-Ari, PhD, RN

 

Part III:

Renal Distal Tubular Ca2+ Exchange Mechanism in Health and Disease

Larry H. Bernstein, MD, FCAP, Stephen J. Williams, PhD
 and Aviva Lev-Ari, PhD, RN

  

Part IV: has been been assigned the following manuscript number: iMedPub Journals-15-471

The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, ArterialSmooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets

Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN

 

Part V: has been been assigned the following manuscript number: iMedPub Journals-15-516

Heart, Vascular Smooth Muscle, Excitation-Contraction Coupling (E-CC), Cytoskeleton, Cellular Dynamics and Ca2 Signaling

Larry H Bernstein, MD, FCAP, Justin Pearlman, MD, PhD, FACC and Aviva Lev-Ari, PhD, RN

 

Part VI:

Calcium Cycling (ATPase Pump) in Cardiac Gene Therapy: Inhalable Gene Therapy for Pulmonary Arterial Hypertension and Percutaneous Intra-coronary Artery Infusion for Heart Failure: Contributions by Roger J. Hajjar, MD

Aviva Lev-Ari, PhD, RN

 

Part VII:

Cardiac Contractility & Myocardium Performance: Ventricular Arrhythmias and Non-ischemic Heart Failure – Therapeutic Implications for Cardiomyocyte Ryanopathy (Calcium Release-related Contractile Dysfunction) and Catecholamine Responses

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

  

Part VIII

Disruption of Calcium Homeostasis: Cardiomyocytes and Vascular Smooth Muscle Cells: The Cardiac and Cardiovascular Calcium Signaling Mechanism – Part VIII

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

 

Part IX

Calcium-Channel Blockers, Calcium Release-related Contractile Dysfunction (Ryanopathy) and Calcium as Neurotransmitter Sensor – Part IX

Justin Pearlman, MD, PhD, FACC, Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

 

Part X – has been been assigned the following manuscript number: iMedPub Journals-15-517

Synaptotagmin functions as a Calcium Sensor: How Calcium Ions Regulate the fusion of vesicles with cell membranes during Neurotransmission – Part X

Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

 

Part XI

Sensors and Signaling in Oxidative Stress – Part XI

Larry H. Bernstein, MD, FCAP

 

Part XII

Atherosclerosis Independence: Genetic Polymorphisms of Ion Channels Role in the Pathogenesis of Coronary Microvascular Dysfunction and Myocardial Ischemia (Coronary Artery Disease (CAD)) – Part XII

Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

Part XIII has been been assigned the following manuscript number: iMedPub Journals-15-471

Ca2+-Stimulated Exocytosis:  The Role of Calmodulin and Protein Kinase C in Ca2+ Regulation of Hormone and Neurotransmitter

Larry H Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN


Methyltransferases are enzymes that facilitate the transfer of a methyl (-CH3) group to specific nucleophilic sites on proteins, nucleic acids or other biomolecules. They share a reaction mechanism in which the nucleophilic acceptor site attacks the electrophilic carbon of S-adenosyl-L-methionine (SAM) in an SN2 displacement reaction that produces a methylated biomolecule and S-adenosyl-L-homocysteine (SAH) as a byproduct. Methylation reactions are essential transformations in small-molecule metabolism, and methylation is a common modification of DNA and RNA. The recent discovery of dynamic and reversible methylation of amino acid side chains of chromatin proteins, particularly within the N-terminal tail of histone proteins, has revealed the importance of methyl ‘marks’ as regulators of gene expression. Human protein methyltransferases (PMTs) fall into two major families – protein lysine methyltransferases (PKMTs) and protein arginine methyltransferases (PRMTs) – that are distinguishable by the amino acid that accepts the methyl group and by the conserved sequences of their respective catalytic domains. Given their involvement in many cellular processes, PMTs have attracted attention as potential drug targets, spurring the search for small-molecule PMT inhibitors. Several classes of inhibitors have been identified, but new specific chemical probes that are active in cells will be required to elucidate the biological roles of PMTs and serve as potent leads for PMT-focused drug development.

Protein lysine methyltransferases (PKMTs)

The phylogenetic tree shows 51 genes predicted to encode PKMTs, which are positioned in the tree on the basis of the similarities of their amino acid sequences. This tree excludes one validated PKMT, DOT1L, which lacks a SET domain – the catalytic domain conserved in this family – and clusters more closely with the PRMTs. The tree has four major branches, and each branch contains enzymes with validated methyltransferase activity (highlighted in red). Some PKMTs add a single methyl group, resulting in a mono-methylated product (Kme), whereas others produce di-(Kme2) or tri-methylated (Kme3) lysine modifications. Many of the validated PKMTs methylate lysines on histones, though nonhistone substrates have also been identified.

Protein arginine methyltransferases (PRMTs)

The human PRMT phylogenetic tree comprises 45 predicted enzymes including the PKMT DOT1L. There are two major types of PRMTs; both catalyze the formation of mono-methylarginine (Rme1) but distinct reaction mechanisms yield symmetric (Rme2s) or asymmetric (Rme2a) dimethylarginine. A small number of predicted PRMTs have validated activity (highlighted in blue). In addition to PRMTs, this tree includes validated RNA methyltransferases (highlighted in green) and biosynthetic enzymes (highlighted in violet). It remains uncertain whether these latter enzymes have PRMT activity, despite their shared structural features. Substrates for the enzymes shown include RNA, metabolites, histones and RNA-binding and spiceosomal proteins.

More info: http://www.epizyme.com/epigenetics/about-epigenetics/chromatin-modifying-enzymes/

Sourced through Scoop.it from: www.genautica.com

See on Scoop.itCardiovascular and vascular imaging

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