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  • Oracle Industry Connect Presents Their 2015 Life Sciences and Healthcare Program

 

Reporter: Stephen J. Williams, Ph.D. and Aviva Lev-Ari, Ph.D., R.N.

oraclehealthcare

Copyright photo Oracle Inc. (TM)

 

Transforming Clinical Research and Clinical Care with Data-Driven Intelligence

March 25-26 Washington, DC

For more information click on the following LINK:

https://www.oracle.com/oracleindustryconnect/life-sciences-healthcare.html

oracle-healthcare-solutions-br-1526409

https://www.oracle.com/industries/health-sciences/index.html  

Oracle Health Sciences: Life Sciences & HealthCare — the Solutions for Big Data

Healthcare and life sciences organizations are facing unprecedented challenges to improve drug development and efficacy while driving toward more targeted and personalized drugs, devices, therapies, and care. Organizations are facing an urgent need to meet the unique demands of patients, regulators, and payers, necessitating a move toward a more patient-centric, value-driven, and personalized healthcare ecosystem.

Meeting these challenges requires redesigning clinical R&D processes, drug therapies, and care delivery through innovative software solutions, IT systems, data analysis, and bench-to-bedside knowledge. The core mission is to improve the health, well-being, and lives of people globally by:

  • Optimizing clinical research and development, speeding time to market, reducing costs, and mitigating risk
  • Accelerating efficiency by using business analytics, costing, and performance management technologies

 

  • Establishing a global infrastructure for collaborative clinical discovery and care delivery models
  • Scaling innovations with world-class, transformative technology solutions
  • Harnessing the power of big data to improve patient experience and outcomes

The Oracle Industry Connect health sciences program features 15 sessions showcasing innovation and transformation of clinical R&D, value-based healthcare, and personalized medicine.

The health sciences program is an invitation-only event for senior-level life sciences and healthcare business and IT executives.

Complete your registration and book your hotel reservation prior to February 27, 2015 in order to secure the Oracle discounted hotel rate.

Learn more about Oracle Healthcare.

General Welcome and Joint Program Agenda

Wednesday, March 25

10:30 a.m.–12:00 p.m.

Oracle Industry Connect Opening Keynote

Mark Hurd, Chief Executive Officer, Oracle

Bob Weiler, Executive Vice President, Global Business Units, Oracle

Warren Berger, Author of “A More Beautiful Question: The Power of Inquiry to Spark Breakthrough Ideas.”

12:00 p.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:45 p.m.

Oracle Industry Connect Keynote

Bob Weiler, Executive Vice President, Global Business Units, Oracle

2:45 p.m.–3:45 p.m.

Networking Break

3:45 p.m.–5:45 p.m.

Life Sciences and Healthcare General Session

Robert Robbins, President, Chief Executive Officer, Texas Medical Center

Steve Rosenberg, Senior Vice President and General Manager Health Sciences Global Business Unit, Oracle

7:00 p.m.–10:00 p.m.

Life Sciences and Healthcare Networking Reception

National Museum of American History
14th Street and Constitution Avenue, NW
Washington DC 20001

Life Sciences Agenda

Thursday, March 26

7:00 a.m.–8:00 a.m.

Networking Breakfast

8:00 a.m.–9:15 a.m.

Digital Trials and Research Models of the Future 

Markus Christen, Senior Vice President and Head of Global Development, Proteus

Praveen Raja, Senior Director of Medical Affairs, Proteus Digital Health

Michael Stapleton, Vice President and Chief Information Officer, R&D IT, Merck

9:15 a.m.–10:30 a.m.

Driving Patient Engagement and the Internet of Things 

Howard Golub, Vice President of Clinical Research, Walgreens

Jean-Remy Behaeghel, Senior Director, Client Account Management, Product Development Solutions, Vertex Pharmaceuticals

10:30 a.m.–10:45 a.m.

Break

10:45 a.m.–12:00 p.m.

Leveraging Data and Advanced Analytics to Enable True Pharmacovigilance and Risk Management 

Leonard Reyno, Senior Vice President, Chief Medical Officer, Agensys

 

Accelerating Therapeutic Development Through New Technologies 

Andrew Rut, Chief Executive Officer, Co-Founder and Director, MyMeds&Me

12:45 a.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:30 p.m.

Oracle Industry Connect Keynote

2:30 p.m.–2:45 p.m.

Break

2:45 p.m.–3:15 p.m.

Harnessing Big Data to Increase R&D Innovation, Efficiency, and Collaboration 

Sandy Tremps, Executive Director, Global Clinical Development IT, Merck

3:15 p.m.–3:30 p.m.

Break

3:30 p.m.–4:45 p.m.

Transforming Clinical Research from Planning to Postmarketing 

Kenneth Getz, Director of Sponsored Research Programs and Research Associate Professor, Tufts University

Jason Raines, Head, Global Data Operations, Alcon Laboratories

4:45 p.m.–6:00 p.m.

Increasing Efficiency and Pipeline Performance Through Sponsor/CRO Data Transparency and Cloud Collaboration 

Thomas Grundstrom, Vice President, ICONIK, Cross Functional IT Strategies and Innovation, ICON

Margaret Keegan, Senior Vice President, Global Head Data Sciences and Strategy, Quintiles

6:00 p.m.–9:00 p.m.

Oracle Customer Networking Event

Healthcare Agenda

Thursday, March 26

7:00 a.m.–8:15 a.m.

Networking Breakfast

8:30 a.m.–9:15 a.m.

Population Health: A Core Competency for Providers in a Post Fee-for-Service Model 

Margaret Anderson, Executive Director, FasterCures

Balaji Apparsamy, Director, Business Intellegence, Baycare

Leslie Kelly Hall, Senior Vice President, Policy, Healthwise

Peter Pronovost, Senior Vice President, Patient Safety & Quality, Johns Hopkins

Sanjay Udoshi, Healthcare Product Strategy, Oracle

9:15 a.m.–9:30 a.m.

Break

9:30 a.m.–10:15 a.m.

Population Health: A Core Competency for Providers in a Post Fee-for-Service Model (Continued)

10:15 a.m.–10:45 a.m.

Networking Break

10:45 a.m.–11:30 a.m.

Managing Cost of Care in the Era of Healthcare Reform 

Chris Bruerton, Director, Budgeting, Intermountain Healthcare

Tony Byram, Vice President Business Integration, Ascension

Kerri-Lynn Morris, Executive Director, Finance Operations and Strategic Projects, Kaiser Permanente

Kavita Patel, Managing Director, Clinical Transformation, Brookings Institute

Christine Santos, Chief of Strategic Business Analytics, Providence Health & Services

Prashanth Kini, Senior Director, Healthcare Product Strategy, Oracle

11:30 a.m.–11:45 a.m.

Break

11:45 a.m.–12:45 p.m.

Managing Cost of Care in the Era of Healthcare Reform (Continued)

12:45 p.m.–1:45 p.m.

Networking Lunch

1:45 p.m.–2:30 p.m.

Oracle Industry Connect Keynote

2:30 p.m.–2:45 p.m.

Break

2:45 p.m.–3:30 p.m.

Precision Medicine 

Annerose Berndt, Vice President, Analytics and Information, UPMC

James Buntrock, Vice Chair, Information Management and Analytics, Mayo Clinic

Dan Ford, Vice Dean for Clinical Investigation, Johns Hopkins Medicine

Jan Hazelzet, Chief Medical Information Officer, Erasmus MC

Stan Huff, Chief Medical Information Officer, Intermountain Healthcare

Vineesh Khanna, Director, Biomedical Informatics, SIDRA

Brian Wells, Vice President, Health Technology, Penn Medicine

Wanmei Ou, Senior Product Strategist, Healthcare, Oracle

3:30 p.m.–3:45 p.m.

Networking Break

3:45 p.m.–4:30 p.m.

Precision Medicine (Continued)

4:30 p.m.–4:45 p.m.

Break

6:00 p.m.–9:00 p.m.

Oracle Customer Networking Event

Additional Links to Oracle Pharma, Life Sciences and HealthCare

 
Life Sciences | Industry | Oracle <http://www.oracle.com/us/industries/life-sciences/overview/>

http://www.oracle.com/us/industries/life-sciences/overview/

 
Oracle Corporation

 
Oracle Applications for Life Sciences deliver a powerful combination of technology and preintegrated applications.

  • Clinical

<http://www.oracle.com/us/industries/life-sciences/clinical/overview/index.html>

  • Medical Devices

<http://www.oracle.com/us/industries/life-sciences/medical/overview/index.html>

  • Pharmaceuticals

<http://www.oracle.com/us/industries/life-sciences/pharmaceuticals/overview/index.html>

 
Life Sciences Solutions | Pharmaceuticals and … – Oracle <http://www.oracle.com/us/industries/life-sciences/solutions/index.html>

http://www.oracle.com  Industries  Life Sciences

 
Oracle Corporation

 
Life Sciences Pharmaceuticals and Biotechnology.

 
Oracle Life Sciences Data Hub – Overview | Oracle <http://www.oracle.com/us/products/applications/health-sciences/e-clinical/data-hub/index.html>

http://www.oracle.com  …  E-Clinical Solutions

 
Oracle Corporation

 
Oracle Life Sciences Data Hub. Better Insights, More Informed Decision-Making. Provides an integrated environment for clinical data, improving regulatory …

 
Pharmaceuticals and Biotechnology | Oracle Life Sciences <http://www.oracle.com/us/industries/life-sciences/pharmaceuticals/overview/index.html>

http://www.oracle.com/us/…/life-sciences/…/index.html

 
Oracle Corporation

 
Oracle Applications for Pharmaceuticals and Biotechnology deliver a powerful combination of technology and preintegrated applications.

 
Oracle Health Sciences – Healthcare and Life Sciences … <https://www.oracle.com/industries/health-sciences/>

https://www.oracle.com/industries/health-sciences/

 
Oracle Corporation

 
Oracle Health Sciences leverages industry-shaping technologies that optimize clinical R&D, mitigate risk, advance healthcare, and improve patient outcomes.

 
Clinical | Oracle Life Sciences | Oracle <http://www.oracle.com/us/industries/life-sciences/clinical/overview/index.html>

http://www.oracle.com  Industries  Life Sciences  Clinical

 
Oracle Corporation

 
Oracle for Clinical Applications provides an integrated remote data collection facility for site-based entry.

 
Oracle Life Sciences | Knowledge Zone | Oracle … <http://www.oracle.com/partners/en/products/industries/life-sciences/get-started/index.html>

http://www.oracle.com/partners/…/life-sciences/…/index.ht&#8230;

 
Oracle Corporation

 
This Knowledge Zone was specifically developed for partners interested in reselling or specializing in Oracle Life Sciences solutions. To become a specialized …

 
[PDF]Brochure: Oracle Health Sciences Suite of Life Sciences … <http://www.oracle.com/us/industries/life-sciences/oracle-life-sciences-solutions-br-414127.pdf>

http://www.oracle.com/…/life-sciences/oracle-life-sciences-s&#8230;

 
Oracle Corporation

 
Oracle Health Sciences Suite of. Life Sciences Solutions. Integrated Solutions for Global Clinical Trials. Oracle Health Sciences provides the world’s broadest set …

 

 

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Biomarker Guided Therapy

Writer and Curator: Larry H. Bernstein, MD, FCAP

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

Liping Chung, K Moore, L Phillips, FM Boyle, DJ Marsh and RC Baxter
Breast Cancer Research 2014, 16:R63
http://breast-cancer-research.com/content/16/3/R63

Introduction: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed  proteins in sera from BC and healthy volunteers (HV), with the
goal  of developing a new prognostic biomarker panel.
Methods: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.
Results: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.
Conclusions: Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

Variants of uncertain significance in BRCA: a harbinger of ethical and policy issues to come?

Jae Yeon Cheon, Jessica Mozersky and Robert Cook-Deegan
Genome Medicine 2014, 6:121
http://genomemedicine.com/content/6/12/121

After two decades of genetic testing and research, the BRCA1 and BRCA2 genes are two of the most well-characterized genes in the human genome. As a result, variants of uncertain significance (VUS; also called variants of unknown significance) are reported less frequently than for genes that have been less thoroughly studied. However, VUS continue to be uncovered, even for BRCA1/2. The increasing use of multi-gene panels and whole-genome and whole-exome sequencing will lead to higher rates of VUS detection because more genes are being tested, and most genomic loci have been far less intensively characterized than BRCA1/2. In this article, we draw attention to ethical and policy-related issues that will emerge. Experience garnered from BRCA1/2 testing is a useful introduction to the challenges of detecting VUS in other genetic testing contexts, while features unique to BRCA1/2 suggest key differences between the BRCA experience and the current challenges of multi-gene panels in clinical care. We propose lines of research and policy development, emphasizing the importance of pooling data into a centralized open-access database for the storage of gene variants to improve VUS interpretation. In addition, establishing ethical norms and regulated practices for sharing and curating data, analytical algorithms, interpretive frameworks and patient re-contact are important policy areas.

The Significance of Normal Pretreatment Levels of CA125 (<35 U/mL) in Epithelial Ovarian Carcinoma

Joseph Menczer,  Erez Ben-Shem,  Abraham Golan, and Tally Levy
Rambam Maimonides Med J 2015;6 (1):e0005. http://dx.doi.org:/10.5041/RMMJ.10180

Objective: To assess the association between normal CA125 levels at diagnosis of epithelial ovarian carcinoma (EOC) with prognostic factors and with outcome.
Methods: The study group consisted of histologically confirmed EOC patients with normal pretreatment CA125 levels, and the controls consisted of EOC patients with elevated (≥35 U/mL) pretreatment CA125 levels, diagnosed and treated between 1995 and 2112. Study and control group patients fulfilled the following criteria: 1) their pretreatment CA125 levels were assessed; 2) they had full standard primary treatment, i.e. cytoreductive surgery and cisplatin-based chemotherapy; and 3) they were followed every 2–4 months during the first two years and every 4–6 months thereafter.
Results: Of 114 EOC patients who fulfilled the inclusion criteria, 22 (19.3%) had normal pretreatment CA125 levels. The control group consisted of the remaining 92 patients with ≥35 U/mL serum CA125 levels pretreatment. The proportion of patients with early-stage and low-grade disease, with optimal cytoreduction, and with platin-sensitive tumors was significantly higher in the study group than in the control group. The progression-free survival (PFS) and overall survival (OS) were significantly higher in the study group than in the control group on univariate analysis but not on multivariate analysis.

Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia

Simone Ecker, Vera Pancaldi, Daniel Rico and Alfonso Valencia
Genome Medicine (2015) 7:8 http://dx.doi.org:/10.1186/s13073-014-0125-z

Background: Chronic lymphocytic leukemia (CLL) presents two subtypes which have drastically different clinical outcomes, IgVH mutated (M-CLL) and IgVH unmutated (U-CLL). So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.
Methods: We analyzed gene expression data of two large cohorts of CLL patients and quantified expression variability across individuals to investigate differences between the two subtypes using different measures and statistical tests. Functional significance was explored by pathway enrichment and network analyses. Furthermore, we implemented a random forest approach based on expression variability to classify patients into disease subtypes.
Results: We found that U-CLL, the more aggressive type of the disease, shows significantly increased variability of gene expression across patients and that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication. These functions indicate a potential relation between gene expression variability and the faster progression of this CLL subtype. Finally, a classifier based on gene expression variability was able to correctly predict the disease subtype of CLL patients.
Conclusions: There are strong relations between gene expression variability and disease subtype linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

The Emerging Roles of Thyroglobulin

Yuqian Luo, Yuko Ishido, Naoki Hiroi, Norihisa Ishii, and Koichi Suzuki
Advances in Endocrinology 2014, Article ID 189194, 7 pages http://dx.doi.org/10.1155/2014/189194

Thyroglobulin (Tg), the most important and abundant protein in thyroid follicles, is well known for its essential role in thyroid hormone synthesis. In addition to its conventional role as the precursor of thyroid hormones, we have uncovered a novel function of Tg as an endogenous regulator of follicular function over the past decade. The newly discovered negative feedback effect of Tg on follicular function observed in the rat and human thyroid provides an alternative explanation for the observation of follicle heterogeneity. Given the essential role of the regulatory effects of Tg, we consider that dysregulation of normal Tg function is associated with multiple human thyroid diseases including autoimmune thyroid disease and thyroid cancer. Additionally, extrathyroid Tg may serve a regulatory function in other organs. Further exploration of Tg action, especially at the molecular level, is needed to obtain a better understanding of both the physiological and pathological roles of Tg.

The GUIDE-IT trial will help doctors find a new standard of care for heart failure.

Heart failure affects more than 25 million people worldwide, including 5.8 million in the United States and 6.9 million in Europe. About one to two percent of adults in developed countries have been diagnosed with heart failure; this increases to more than 10 percent in people over age 70. Moreover, heart failure accounts for more than 17 percent of Medicare spending and about 5 percent of total US healthcare spending. The cost to society in the US is about 30 billion dollars a year—and rising.

For people hospitalized due to heart failure, the outlook isn’t encouraging. Following discharge, one in four patients is likely to be back in the hospital in less than a month. With every acute heart failure event that requires readmission, the chances of dying from the disease increase.

Heart failure occurs when the heart is unable to fill with or pump sufficient blood to meet the needs of the body. Some heart failure symptoms—shortness of breath, fatigue and fluid buildup—which are present in other health problems. Heart failure may develop from coronary artery disease, high blood pressure, cardiomyopathy, heart valve disease, arrhythmias, viral or bacterial infections, and congenital heart defects. As a consequence, these patients often have additional diseases (comorbidities) and managing heart failure can be extremely challenging.

There have been no new drugs for heart failure in more than a decade. The last breakthrough was cardiac resynchronization therapy, a device and not a drug. The goals of therapy are to treat heart failure’s underlying causes, reduce symptoms, improve the patient’s quality of life and keep the disease from getting worse.

More than a pump

The heart isn’t just a muscle pumping blood through the body. It is also an endocrine gland that secretes peptides and hormones. When the heart is failing, its stressed cells release larger amounts of substances known as natriuretic peptides, including N-terminal prohormone brain natriuretic peptide, or NT-proBNP.

Roche’s NT-proBNP test measures the levels of this peptide and helps doctors to determine whether patients are suffering from heart failure and to assess their prognosis. Most recently, NT-proBNP has also been shown to help physicians guide and adjust the patient’s drug therapy. The objective of the pivotal GUIDE-IT trial is to demonstrate the efficacy and safety of NT-proBNP guided heart failure therapy.

Sponsored by the National Institutes of Health (NIH), the GUIDE-IT trial will help doctors answer important questions about NT-proBNP’s impact on medical care. About 1100 patients are enrolled in this robustly powered, randomized controlled trial comparing NT-proBNP guided therapy on top of standard care versus standard care alone in high-risk heart failure patients. Its primary endpoint is time to cardiovascular death or first heart failure hospitalization.

With the NT-proBNP biomarker, doctors can create personalized treatment plans for patients to substantially reduce mortality and morbidity. It can be viewed as a companion diagnostic that works with all the drugs recommended by the major guidelines.

Finding new answers

GUIDE-IT will last five years and involve approximately 45 trial sites in the United States. The first group of patients will be enrolled by the end of 2012.

“We need to take a more strategic approach if we are going to meet the AHA/ASA’s 2020 goal of reducing heart failure hospitalizations by 20 percent,” Dr. O’Connor, Chief of the Division of Cardiovascular Medicine at Duke Heart Center in Durham, North Carolina, said at a media briefing held in October at Roche Diagnostics International in Rotkreuz, Switzerland.
The relative and combined ability of: high-sensitivity cardiac troponin T, and N-terminal pro-B-type natriuretic Peptide – to predict cardiovascular events and death in patients with type 2 diabetes.

Hillis GS; Welsh P; Chalmers J; Perkovic V; Chow CK; Li Q; Jun M; Neal B; et al.
http://reference.medscape.com/medline/abstract/24089534?src=wnl_ref_prac_diab

OBJECTIVE Current methods of risk stratification in patients with type 2 diabetes are suboptimal. The current study assesses the ability of N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) to improve the prediction of cardiovascular events and death in patients with type 2 diabetes.
RESEARCH DESIGN AND METHODS A nested case-cohort study was performed in 3,862 patients who participated in the Action in Diabetes and Vascular Disease: Preterax and Diamicron Modified Release Controlled Evaluation (ADVANCE) trial. RESULTS Seven hundred nine (18%) patients experienced a major cardiovascular event (composite of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke) and 706 (18%) died during a median of 5 years of follow-up. In Cox regression models, adjusting for all established risk predictors, the hazard ratio for cardiovascular events for NT-proBNP was 1.95 per 1 SD increase (95% CI 1.72, 2.20) and the hazard ratio for hs-cTnT was 1.50 per 1 SD increase (95% CI 1.36, 1.65). The hazard ratios for death were 1.97 (95% CI 1.73, 2.24) and 1.52 (95% CI 1.37, 1.67), respectively. The addition of either marker improved 5-year risk classification for cardiovascular events (net reclassification index in continuous model, 39% for NT-proBNP and 46% for hs-cTnT). Likewise, both markers greatly improved the accuracy with which the 5-year risk of death was predicted. The combination of both markers provided optimal risk discrimination.
CONCLUSIONS NT-proBNP and hs-cTnT appear to greatly improve the accuracy with which the risk of cardiovascular events or death can be estimated in patients with type 2 diabetes.

Genetics and Heart Failure: A Concise Guide for the Clinician

Cécile Skrzynia, Jonathan S. Berg, Monte S. Willis and Brian C. Jensen
Current Cardiology Reviews, 2013; 9.

Abstract: The pathogenesis of heart failure involves a complex interaction between genetic and environmental factors. Genetic factors may influence the susceptibility to the underlying etiology of heart failure, the rapidity of disease progression, or the response to pharmacologic therapy. The genetic contribution to heart failure is relatively minor in most multifactorial cases, but more direct and profound in the case of familial dilated cardiomyopathy. Early studies of genetic risk for heart failure focused on polymorphisms in genes integral to the adrenergic and renin-angiotensin-aldosterone system. Some of these variants were found to increase the risk of developing heart failure, and others appeared to affect the therapeutic response to neurohormonal antagonists. Regardless, each variant individually confers a relatively modest increase in risk and likely requires complex interaction with other variants and the environment for heart failure to develop. Dilated cardiomyopathy frequently leads to heart failure, and a genetic etiology increasingly has been recognized in cases previously considered to be “idiopathic”. Up to 50% of dilated cardiomyopathy cases without other cause likely are due to a heritable genetic mutation. Such mutations typically are found in genes encoding sarcomeric proteins and are inherited in an autosomal dominant fashion. In recent years, rapid advances in sequencing technology have improved our ability to diagnose familial dilated cardiomyopathy and those diagnostic tests are available widely. Optimal care for the expanding population of patients with heritable heart failure involves counselors and physicians with specialized training in genetics, but numerous online genetics resources are available to practicing clinicians.

Cardiac Troponin Testing Is Overused after the Rule-In or Rule-Out of Myocardial Infarction

Olaia Rodriguez Fraga, Y Sandoval, SA Love, ZJ McKinney, MAM Murakami, SW Smith, FS Apple
Clinical Chemistry 2015; 61:2 http://dx.doi.org:/10.1373/clinchem.2014.232694

No good studies have systematically evaluated appropriate clinical utilization of cardiac troponin testing in the clinical setting of the rule-in and rule-out of myocardial infarction (MI). Our collective 100-plus years of clinical and laboratory experience suggested that provider test ordering and use of cardiac troponin has been excessive after a diagnosis of MI or no MI has been determined. There is no evidence that supports continuation of cardiac troponin testing after a diagnosis is made.

Number of cTnI results demonstrating excessive orders by diagnosis

Number of cTnI results demonstrating excessive orders by diagnosis

Time and Frequency Domain Analysis of Heart Rate Variability and their orrelations in Diabetes Mellitus
T. Ahamed Seyd, V. I. Thajudin Ahamed, Jeevamma Jacob, Paul Joseph K
Intl J Biolog and Life Sciences 2008; 4(1)

Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS
activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Power Spectral Density of the RR interval of a 55 year old healthy volunteer

Power Spectral Density of the RR interval of a 55 year old healthy volunteer

Power Spectral Density of the RR interval of a 55 year old healthy volunteer

Power Spectral Density of the RR interval of a 62 year old woman suffering

Power Spectral Density of the RR interval of a 62 year old woman suffering

Power Spectral Density of the RR interval of a 62 year old woman suffering
from diabetes for the last 15 years

HRV analysis has gained much importance in recent years, as a technique employed to explore the activity of ANS, and as an important early marker for identifying different pathological conditions. DM is a disease in which the cardiac autonomic activity is progressively compromised. Our investigation indicates that different time domain and frequency domain measures of HRV would be able to provide valuable information regarding the autonomic dysfunction to DM.

Time domain and frequency domain analysis of the RR interval variability of diabetic and normal subjects shows that there is significant difference in these measures for DM patients with respect to normal subjects. Variation of the HRV parameters indicates changes in ANS activity of DM patients. This can provide valid information regarding autonomic neuropathy in people with diabetes. It may be noted that these methods can detect changes before clinical signs appear. So we can expect that these measures enable early detection and treatment/subsequent management of patients and thus can avoid acute and chronic complications.

Multiparametric diagnostics of cardiomyopathies by microRNA signatures

Christine S. Siegismund & Maria Rohde & Uwe Kühl & Dirk Lassner
Microchim Acta 2014   http://dx.doi.org:/10.1007/s00604-014-1249-y

The diagnosis of cardiomyopathies by endomyocardial biopsy analysis is the gold standard for confirmation of causative reasons but is failing if a sample does not contain the area of interest due to focal pathology. Biopsies are revealing an extract of the current situation of the heart muscle only, and the need for global organ-specific or systemic markers is obvious in order to minimize sampling errors. Global markers like specific gene expression signatures in myocardial tissue may therefore reflect the focal situation or condition of the whole myocardium. Besides gene expression profiles, microRNAs (miRNAs) represent a new group of stable biomarkers that are detectable both in tissue and body fluids. Such miRNAs may serve as cardiological biomarkers to characterize inflammatory processes, to confirm viral infections, and to differentiate various forms of infection.
The predictive power of single miRNAs for diagnosis of complex diseases may be further increased if several distinctly deregulated candidates are combined to form a specific miRNA signature. Diagnostic systems that generate disease related miRNA profiles are based on microarrays, bead-based oligo sorbent assays, or on assays based on real-time polymerase chain reactions and placed on microfluidic cards or nanowell plates. Multiparametric diagnostic systems that can measure differentially expressed miRNAs may become the diagnostic tool of the future due to their predictive value with respect to clinical course, therapeutic decisions, and therapy monitoring. We discuss here specific merits, limitations and the potential of currently available analytical platforms for diagnostics of heart muscle diseases based on miRNA profiling.

Predictive value of plasma galectin-3 levels in heart failure with reduced and preserved ejection fraction

Rudolf A. de Boer, DJA Lok, T Jaarsma, P van der Meer, AA Voors, et al.
Annals Med, 2011; 43: 60–68 http://dx.doi.org:/10.3109/07853890.2010.538080

We studied the prognostic value of base-line galectin-3 in a large HF cohort, with preserved and reduced left ventricular ejection fraction (LVEF), and compared this to other biomarkers.
Methods. We studied 592 HF patients who had been hospitalized for HF and were followed for 18 months. The primary end-point was a composite of all-cause mortality and HF hospitalization.
Results. A doubling of galectin-3 levels was associated with a hazard ratio (HR) of 1.97 (1.62–2.42) for the primary outcome (P= 0.001). After correction for age, gender, BNP, eGFR, and diabetes the HR was 1.38 (1.07–1.78; P= 0.015). Galectin-3 levels were correlated with higher IL -6 and CRP levels (P= 0.002). Changes of galectin-3 levels after 6 months did not add prognostic information to the base-line value (n= 291); however, combining plasma galectin-3 and BNP levels increased prognostic value over either biomarker alone (ROC analysis, P = 0.05). The predictive value of galectin-3 was stronger in patients with preserved LVEF (n= 114) compared to patients with reduced LVEF (P= 0.001).
Conclusions. Galectin-3 is an independent marker for outcome in HF and appears to be particularly useful in HF patients with preserved LVEF.

Criteria for the use of omics-based predictors in clinical trials

Lisa M. McShane, MM Cavenagh, TG Lively, DA Eberhard, et al.
Nature  17 Oct 2013; 502: 317-320. http://dx.doi.org:/10.1038/nature12564

The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to ‘omics’-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength. The checklist will be used to evaluate proposals for NCI-sponsored clinical
trials in which omics tests will be used to guide therapy.

M-Atrial Natriuretic Peptide and Nitroglycerin in a Canine Model of Experimental Acute Hypertensive Heart Failure: Differential Actions of 2 cGMP Activating Therapeutics.

Paul M McKie, Alessandro Cataliotti, Tomoko Ichiki, S Jeson Sangaralingham, Horng H Chen, John C Burnett
J Am Heart Assoc 01/2014; 3(1):e000206. http://dx.doi.org:/10.1161/JAHA.113.000206

Systemic hypertension is a common characteristic in acute heart failure (HF). This increasingly recognized phenotype is commonly associated with renal dysfunction and there is an unmet need for renal enhancing therapies. In a canine model of HF and acute vasoconstrictive hypertension we characterized and compared the cardiorenal actions of M-atrial natriuretic peptide (M-ANP), a novel particulate guanylyl cyclase (pGC) activator, and nitroglycerin, a soluble guanylyl cyclase (sGC) activator.
HF was induced by rapid RV pacing (180 beats per minute) for 10 days. On day 11, hypertension was induced by continuous angiotensin II infusion. We characterized the cardiorenal and humoral actions prior to, during, and following intravenous M-ANP (n=7), nitroglycerin (n=7), and vehicle (n=7) infusion. Mean arterial pressure (MAP) was reduced by M-ANP (139±4 to 118±3 mm Hg, P<0.05) and nitroglycerin (137±3 to 116±4 mm Hg, P<0.05); similar findings were recorded for pulmonary wedge pressure (PCWP) with M-ANP (12±2 to 6±2 mm Hg, P<0.05) and nitroglycerin (12±1 to 6±1 mm Hg, P<0.05). M-ANP enhanced renal function with significant increases (P<0.05) in glomerular filtration rate (38±4 to 53±5 mL/min), renal blood flow (132±18 to 236±23 mL/min), and natriuresis (11±4 to 689±37 mEq/min) and also inhibited aldosterone activation (32±3 to 23±2 ng/dL, P<0.05), whereas nitroglycerin had no significant (P>0.05) effects on these renal parameters or aldosterone activation.
Our results advance the differential cardiorenal actions of pGC (M-ANP) and sGC (nitroglycerin) mediated cGMP activation. These distinct renal and aldosterone modulating actions make M-ANP an attractive therapeutic for HF with concomitant hypertension, where renal protection is a key therapeutic goal.

Genome-Wide Association Study of a Heart Failure Related Metabolomic Profile Among African Americans in the Atherosclerosis Risk in Communities (ARIC) Study

Bing Yu, Y Zheng, D Alexander, TA Manolio, A Alonso, JA Nettleton, & E Boerwinkle
Genet Epidemiol 2013; 00:1–6, http://dx.doi.org:/10.1002/gepi.21752

Both the prevalence and incidence of heart failure (HF) are increasing, especially among African Americans, but no large-scale, genome-wide association study (GWAS) of HF-related metabolites has been reported. We sought to identify novel genetic variants that are associated with metabolites previously reported to relate to HF incidence. GWASs of three metabolites identified previously as risk factors for incident HF (pyroglutamine, dihydroxy docosatrienoic acid, and X-11787, being either hydroxy-leucine or hydroxy-isoleucine) were performed in 1,260 African Americans free of HF at the baseline examination of the Atherosclerosis Risk in Communities (ARIC) study. A significant association on chromosome 5q33 (rs10463316, MAF = 0.358, P-value = 1.92 × 10−10) was identified for pyroglutamine. One region on chromosome 2p13 contained a nonsynonymous substitution in N-acetyltransferase 8 (NAT8) was associated with X-11787 (rs13538, MAF = 0.481, P-value = 1.71 × 10−23). The smallest P-value for dihydroxy docosatrienoic acid was rs4006531 on chromosome 8q24 (MAF = 0.400, P-value = 6.98 × 10−7). None of the above SNPs were individually associated with incident HF, but a genetic risk score (GRS) created by summing the most significant risk alleles from each metabolite detected 11% greater risk of HF per allele. In summary, we identified three loci associated with previously reported HF-related metabolites. Further use of metabolomics technology will facilitate replication of these findings in independent samples.

Global Left Atrial Strain Correlates with CHADS2 Risk Score in Patients with Atrial Fibrillation

SK Saha, PL Anderson, G Caracciolo, A Kiotsekoglou, S Wilansky, S Govind, et al.
J Am Soc Echocardiogr 2011; 24(5): 506-512.
http://dx.doi.org:/10.1016/j.echo.2011.02.012

Background: The aim of this cross-sectional study was to explore the association between echocardiographic parameters and CHADS2 score in patients with nonvalvular atrial fibrillation (AF).
Methods: Seventy-seven subjects (36 patients with AF, 41 control subjects) underwent standard twodimensional, Doppler, and speckle-tracking echocardiography to compute regional and global left atrial (LA) strain.
Results: Global longitudinal LA strain was reduced in patients with AF compared with controls (P < .001) and was a predictor of high risk for thromboembolism (CHADS2 score $ 2; odds ratio, 0.86; P = .02). LA strain indexes showed good interobserver and intraobserver variability. In sequential Cox models, the prediction of hospitalization and/or death was improved by addition of global LA strain and indexed LA volume to CHADS2 score (P = .003).
Conclusions: LA strain is a reproducible marker of dynamic LA function and a predictor of stroke risk and cardiovascular outcomes in patients with AF.

Gene Expression and Genetic Variation in Human Atria

Honghuang Lin, EV Dolmatova, MP Morley, KL Lunetta, et al.
Heart Rhythm, HRTHM5533. PII: S1547-5271(13)01226-5
http://dx.doi.org/10.1016/j.hrthm.2013.10.051

Background— The human left and right atria have different susceptibilities to develop atrial fibrillation (AF). However, the molecular events related to structural and functional changes that enhance AF susceptibility are still poorly understood.
Objective— To characterize gene expression and genetic variation in human atria.
Methods— We studied the gene expression profiles and genetic variations in 53 left atrial and 52 right atrial tissue samples collected from the Myocardial Applied Genomics Network (MAGNet) repository. The tissues were collected from heart failure patients undergoing transplantation and from unused organ donor hearts with normal ventricular function. Gene expression was profiled using the Affymetrix GeneChip Human Genome U133A Array. Genetic variation was profiled using the Affymetrix Genome-Wide Human SNP Array 6.0.
Results— We found that 109 genes were differentially expressed between left and right atrial tissues. A total of 187 and 259 significant cis-associations between transcript levels and genetic variants were identified in left and right atrial tissues, respectively. We also found that a SNP at a known AF locus, rs3740293, was associated with the expression of MYOZ1 in both left and right atrial tissues. Conclusion— We found a distinct transcriptional profile between the right and left atrium, and extensive cis-associations between atrial transcripts and common genetic variants. Our results implicate MYOZ1 as the causative gene at the chromosome 10q22 locus for AF.

Atrial Natriuretic Peptide Single Nucleotide Polymorphisms in Patients with Nonfamilial Structural Atrial Fibrillation

Pietro Francia, A Ricotta, A Frattari, R Stanzione, A Modestino, et al.
Clinical Medicine Insights: Cardiology 2013:7 153–159
http://dx.doi.org:/10.4137/CMC.S12239

Background: Atrial natriuretic peptide (ANP) has antihypertrophic and antifibrotic properties that are relevant to AF substrates. The −G664C and rs5065 ANP single nucleotide polymorphisms (SNP) have been described in association with clinical phenotypes, including hypertension and left ventricular hypertrophy. A recent study assessed the association of early AF and rs5065 SNPs in low-risk subjects. In a Caucasian population with moderate-to-high cardiovascular risk profile and structural AF, we conducted a case-control study to assess whether the ANP −G664C and rs5065 SNP associate with nonfamilial structural AF.
Methods: 168 patients with nonfamilial structural AF and 168 age- and sex-matched controls were recruited. The rs5065 and −G664C ANP SNPs were genotyped.
Results: The study population had a moderate-to-high cardiovascular risk profile with 86% having hypertension, 23% diabetes, 26% previous myocardial infarction, and 23% left ventricular systolic dysfunction. Patients with AF had greater left atrial diameter (44 ± 7
vs. 39 ± 5 mm; P , 0.001) and higher plasma NTproANP levels (6240 ± 5317 vs. 3649 ± 2946 pmol/mL; P , 0.01). Odds ratios (ORs)
for rs5065 and −G664C gene variants were 1.1 (95% confidence interval [CI], 0.7–1.8; P = 0.71) and 1.2 (95% CI, 0.3–3.2; P = 0.79), respectively, indicating no association with AF. There were no differences in baseline clinical characteristics among carriers and noncarriers of the −664C and rs5065 minor allele variants.
Conclusions: We report lack of association between the rs5065 and −G664C ANP gene SNPs and AF in a Caucasian population of patients with structural AF. Further studies will clarify whether these or other ANP gene variants affect the risk of different subphenotypes of AF driven by distinct pathophysiological mechanisms.

N-terminal proBNP and mortality in hospitalized patients with heart failure and preserved vs. reduced systolic function: data from the prospective Copenhagen Hospital Heart Failure Study (CHHF)

Kirk, M. Bay, J. Parnerc, K. Krogsgaard, T.M. Herzog, S. Boesgaard, et al.
Eur Journal Heart Failure 6 (2004) 335–341
http://dx.doi.org:/10.1016/j.ejheart.2004.01.002

Preserved systolic function among heart failure patients is a common finding, a fact that has only recently been fully appreciated. The aim of the present study was to examine the value of NT-proBNP to predict mortality in relation to established risk factors among consecutively hospitalised heart failure patients and secondly to characterise patients in relation to preserved and reduced systolic function. Material: At the time of admission 2230 consecutively hospitalised patients had their cardiac status evaluated through determinations of NT-proBNP, echocardiography, clinical examination and medical history. Follow-up was performed 1 year later in all patients. Results: 161 patients fulfilled strict diagnostic criteria for heart failure (HF). In this subgroup of patients 1-year mortality was approximately 30% and significantly higher as compared to the remaining non-heart failure population (approx. 16%). Using univariate analysis left ventricular ejection fraction (LVEF), New York Heart Association classification (NYHA) and plasma levels of NT-proBNP all predicted mortality independently. However, regardless of systolic function, age and NYHA class, risk-stratification was provided by measurements of NT-proBNP. Having measured plasma levels of NT-proBNP, LVEF did not provide any additional prognostic information on mortality among heart failure patients (multivariate analysis).
Conclusion: The results show that independent of LVEF, measurements of NT-proBNP add additional prognostic information. It is concluded that NT-proBNP is a strong predictor of 1-year mortality in consecutively hospitalised patients with heart failure with preserved as well as reduced systolic function.

N-terminal pro-B-type natriuretic peptide and the prediction of primary cardiovascular events: results from 15-year follow-up of WOSCOPS

Paul Welsh, Orla Doolin, Peter Willeit, Chris Packard, Peter Macfarlane, et al.
Eur Heart Journal 2014. http://eurheartj.oxfordjournals.org/

Aims: To test whether N-terminal pro-B-type natriuretic peptide (NT-proBNP) was independently associated with, and improved the prediction of, cardiovascular disease (CVD) in a primary prevention cohort.
Methods and results:  In the West of Scotland Coronary Prevention Study (WOSCOPS), a cohort of middle-aged men with hypercholesterolemia at a moderate risk of CVD, we related the baseline NT-proBNP (geometric mean 28 pg/mL) in 4801 men to the risk of CVD over 15 years during which 1690 experienced CVD events. Taking into account the competing risk of non-CVD death, NT-proBNP was associated with an increased risk of all CVD [HR: 1.17 (95% CI: 1.11–1.23) per standard deviation increase in log NT-proBNP] after adjustment for classical and clinical cardiovascular risk factors plus C-reactive protein. N-terminal pro-B-type natriuretic peptide was more strongly related to the risk of fatal [HR: 1.34 (95% CI: 1.19–1.52)] than non-fatal CVD [HR: 1.17 (95% CI: 1.10–1.24)] (P ¼ 0.022). The addition of NT-proBNP to traditional risk factors improved the C-index (+0.013; P , 0.001). The continuous net reclassification index improved with the addition of NT-proBNP by 19.8% (95% CI: 13.6–25.9%) compared with 9.8% (95% CI: 4.2–15.6%) with the addition of C-reactive protein. N-terminal pro-B-type natriuretic peptide correctly reclassified 14.7% of events, whereas C-reactive protein correctly reclassified 3.4% of events. Results were similar in the 4128 men without evidence of angina, nitrate prescription, minor ECG abnormalities, or prior cerebrovascular disease.
Conclusion: N-terminal pro-B-type natriuretic peptide predicts CVD events in men without clinical evidence of CHD, angina, or history of stroke, and appears related more strongly to the risk for fatal events. N-terminal pro-B-type natriuretic peptide also provides moderate risk discrimination, in excess of that provided by the measurement of C-reactive protein.

Effect of B-type natriuretic peptide-guided treatment of chronic heart failure on total mortality and hospitalization: an individual patient meta-analysis

Richard W. Troughton, Christopher M. Frampton, Hans-Peter Brunner-La Rocca,
Matthias Pfisterer, Luc W.M. Eurlings, Hans Erntell, Hans Persson, et al.
Eur Heart J 2014; 35: 1559–1567 http://dx.doi.org:/10.1093/eurheartj/ehu090

Aims Natriuretic peptide-guided (NP-guided) treatment of heart failure has been tested against standard clinically guided care in multiple studies, but findings have been limited by study size. We sought to perform an individual patient data metaanalysis to evaluate the effect of NP-guided treatment of heart failure on all-cause mortality.
Methods and results
Eligible randomized clinical trials were identified from searches of Medline andEMBASEdatabases and the Cochrane Clinical
Trials Register. The primary pre-specified outcome, all-cause mortality was tested using a Cox proportional hazards regression model that included study of origin, age (< 75 or ≥75 years), and left ventricular ejection fraction (LVEF, ≤45 or .45%) as covariates. Secondary endpoints included heart failure or cardiovascular hospitalization. Of 11 eligible studies, 9 provided individual patient data and 2 aggregate data. For the primary endpoint individual data from 2000 patients were included, 994 randomized to clinically guided care and 1006 to NP-guided care. All-cause mortality was significantly reduced by NP-guided treatment [hazard ratio = 0.62 (0.45–0.86);
P = 0.004] with no heterogeneity between studies or interaction with LVEF. The survival benefit from NP-guided therapy was seen in younger ( <75 years) patients [0.62 (0.45–0.85); P = 0.004] but not older (≥75 years) patients [0.98 (0.75–1.27); P = 0.96]. Hospitalization due to heart failure [0.80 (0.67–0.94); P = 0.009] or cardiovascular disease [0.82 (0.67–0.99); P = 0.048]was significantly lower in NP-guided patients with no heterogeneity between studies and no interaction with age or LVEF.
Conclusion: Natriuretic peptide-guided treatment of heart failure reduces all-cause mortality in patients aged < 75 years and overall reduces heart failure and cardiovascular hospitalization.

Diagnostic and prognostic evaluation of left ventricular systolic heart failure by plasma N-terminal pro-brain natriuretic peptide concentrations in a large sample of the general population

B A Groenning, I Raymond, P R Hildebrandt, J C Nilsson, M Baumann, F Pedersen
Heart 2004;90:297–303. http://dx.doi.org:/10.1136/hrt.2003.026021

Objective: To evaluate N-terminal pro-brain natriuretic peptide (NT-proBNP) as a diagnostic and prognostic marker for systolic heart failure in the general population.
Design: Study participants, randomly selected to be representative of the background population, filled in a heart failure questionnaire and underwent pulse and blood pressure measurements, electrocardiography, echocardiography, and blood sampling and were followed up for a median (range) period of 805 (6021171) days.
Setting: Participants were recruited from four randomly selected general practitioners and were examined in a Copenhagen university hospital.
Patients: 382 women and 290 men in four age groups (50259 (n = 174); 60269 (n = 204); 70279 (n = 174); > 80 years (n = 120)).
Main outcome measures: Value of NT-proBNP in evaluating patients with symptoms of heart failure and impaired left ventricular (LV) systolic function; prognostic value of NT-proBNP for mortality and hospital admissions.
Results: In 38 (5.6%) participants LV ejection fraction (LVEF) was (40%. NT-proBNP identified patients with symptoms of heart failure and LVEF (40% with a sensitivity of 0.92, a specificity of 0.86, positive and negative predictive values of 0.11 and 1.00, and area under the curve of 0.94. NT-proBNP was the strongest independent predictor of mortality (hazard ratio (HR) = 5.70, p = 0.0001), hospital admissions for heart failure (HR = 13.83, p = 0.0001), and other cardiac admissions (HR = 3.69, p = 0.0001). Mortality (26 v 6, p = 0.0003), heart failure admissions (18 v 2, p = 0.0002), and admissions for other cardiac causes (44 v 13, p = 0.0001) were significantly higher in patients with NTproBNP above the study median (32.5 pmol/l). Conclusions: Measurement of NT-proBNP may be useful as a screening tool for systolic heart failure in the general population.

Copeptin—Marker of Acute Myocardial Infarction

Martin Möckel & Julia Searle
Curr Atheroscler Rep 2014; 16:421 http://dx.doi.org:/10.1007/s11883-014-0421-5

The concentration of copeptin, the C-terminal part of pro-arginine vasopressin, has been shown to increase early after acute and severe events. Owing to complementary pathophysiology and kinetics, the unspecific marker copeptin, in combination with highly cardio-specific troponin, has been evaluated as an early-rule-out strategy for acute myocardial infarction in patients presenting with signs and symptoms of acute coronary syndrome. Overall, most studies have reported a negative predictive value between 97 and 100 % for the diagnosis of acute myocardial infarction in low- to intermediate-risk patients with suspected acute coronary syndrome. Additionally, a recent multicenter, randomized process study, where patients who tested negative for copeptin and troponin were discharged from the emergency department, showed that the safety of the new process was comparable to that of the current standard process. Further interventional trials and data from registries are needed to ensure the effectiveness and patient benefit of the new strategy.

The role of copeptin as a diagnostic and prognostic biomarker for risk stratification in the emergency department

Christian H Nickel1, Roland Bingisser and Nils G Morgenthaler
BMC Medicine 2012, 10:7 http://www.biomedcentral.com/1741-7015/10/7

The hypothalamic-pituitary-adrenal axis is activated in response to stress. One of the activated hypothalamic hormones is arginine vasopressin, a hormone involved in hemodynamics and osmoregulation. Copeptin, the C-terminal part of the arginine vasopressin precursor peptide, is a sensitive and stable surrogate marker for arginine vasopressin release. Measurement of copeptin levels has been shown to be useful in a variety of clinical scenarios, particularly as a prognostic marker in patients with acute diseases such as lower respiratory tract infection, heart disease and stroke. The measurement of copeptin levels may provide crucial information for risk stratification in a variety of clinical situations. As such, the emergency department appears to be the ideal setting for its potential use. This review summarizes the recent progress towards determining the prognostic and diagnostic value of copeptin in the emergency department.

Variability of the Transferrin Receptor 2 Gene in AMD

Daniel Wysokinski, Janusz Blasiak, Mariola Dorecka, Marta Kowalska, et al.
Disease Markers 2014, Article ID 507356, 8 pages http://dx.doi.org/10.1155/2014/507356

Oxidative stress is a major factor in the pathogenesis of age-related macular degeneration (AMD). Iron may catalyze the Fenton reaction resulting in overproduction of reactive oxygen species. Transferrin receptor 2 plays a critical role in iron homeostasis and variability in its gene may influence oxidative stress and AMD occurrence. To verify this hypothesis we assessed the association between  polymorphisms of the TFR2 gene and AMD. A total of 493AMDpatients and 171matched controls were genotyped for the two polymorphisms of the TFR2 gene: c.1892C>T (rs2075674) and c.−258+123T>C (rs4434553). We also assessed the modulation of some AMD risk factors by these polymorphisms.The CC and TT genotypes of the c.1892C>T were associated with AMD occurrence but the latter only in obese patients. The other polymorphism was not associated with AMD occurrence, but the CC genotype was correlated with an increasing AMD frequency in subjects with BMI < 26. The TT genotype and the T allele of this polymorphism decreased AMD occurrence in subjects above 72 years, whereas the TC genotype and the C allele increased occurrence of AMD in this group.The c.1892C>T and c.−258+123T>C polymorphisms of the TRF2 gene may be associated with AMD occurrence, either directly or by modulation of risk factors.

Urinary N-Acetyl-beta-D-glucosaminidase as an Early Marker for Acute Kidney Injury in Full-Term Newborns with Neonatal Hyperbilirubinemia

Bangning Cheng, Y Jin, G Liu, Z Chen, H Dai, and M Liu
Disease Markers 2014, Article ID 315843, 6 pages http://dx.doi.org/10.1155/2014/315843

Purpose. To investigate renal function estimated by markers in full-term newborns with hyperbilirubinemia.
Methods. A total of 332 full-term newborns with hyperbilirubinemia and 60 healthy full-term newborns were enrolled. Total serum bilirubin, serum creatinine (Cr), serum blood urea nitrogen (BUN), serum cystatin C (Cys-C), urinary beta-2-microglobulin (𝛽2MG) index, and urinary N-acetyl-beta-D-glucosaminidase (NAG) index were measured before and after treatment. All newborns were divided into three groups according to total serum bilirubin levels: group 1 (221-256), group 2 (256-342), and group 3 (>342). Results. The control group and group 1 did not differ significantly in regard to serum Cr, serum BUN, serum Cys-C, urinary 𝛽2MG index, and urinary NAG index. Urinary NAG index in group 2 was significantly higher than that in control group (𝑃 < 0.001). Between control group and group 3, serum Cys-C, urinary 𝛽2MG index, and urinary NAG index differed significantly. The significant positive correlation between total serum bilirubin and urinary NAG index was found in newborns when total serum bilirubin level was more than 272 𝜇mol/L.
Conclusions. High unconjugated bilirubin could result in acute kidney injury in full-term newborns. Urinary NAG might be the suitable marker for predicting acute kidney injury in full-term newborns with hyperbilirubinemia.

Urinary C-peptide creatinine ratio detects absolute insulin deficiency in Type 2 diabetes.

S V Hope, A G Jones, E Goodchild, M Shepherd, R E J Besser, B Shields, T McDonald, B A Knight, A Hattersley

Department of Geriatrics, Royal Devon and Exeter NHS Foundation Trust; NIHR Exeter Clinical Research Facility, University of Exeter.

Diabetic Medicine (impact factor: 2.9). 05/2013; http://dx.doi.org:/10.1111/dme.12222

Source: PubMed

ABSTRACT AIMS: To determine the prevalence and clinical characteristics of absolute insulin deficiency in long-standing Type 2 diabetes, using a strategy based on home urinary C-peptide creatinine ratio measurement.
METHODS: We assessed the urinary C-peptide creatinine ratios, from urine samples taken at home 2 h after the largest meal of the day, in 191 insulin-treated subjects with Type 2 diabetes (diagnosis age ≥45 years, no insulin in the first year). If the initial urinary C-peptide creatinine ratio was ≤0.2 nmol/mmol (representing absolute insulin deficiency), the assessment was repeated. A standardized mixed-meal tolerance test with 90-min stimulated serum C-peptide measurement was performed in nine subjects with a urinary C-peptide creatinine ratio ≤ 0.2 nmol/mmol (and in nine controls with a urinary C-peptide creatinine ratio >0.2 nmol/mmol) to confirm absolute insulin deficiency.
RESULTS: A total of 2.7% of participants had absolute insulin deficiency confirmed by a mixed-meal tolerance test. They were identified initially using urinary C-peptide creatinine ratio: 11/191 subjects (5.8%) had two consistent urinary C-peptide creatinine ratios ≤ 0.2 nmol/mmol; 9/11 subjects completed a mixed-meal tolerance test and had a median stimulated serum C-peptide of 0.18nmol/l. Five out of nine subjects had stimulated serum C-peptide <0.2 nmol/l and 9/9 subjects with urinary C-peptide creatinine ratio >0.2 had endogenous insulin secretion confirmed by the mixed-meal tolerance test. Compared with subjects with a urinary C-peptide creatinine ratio >0.2 nmol/mmol, those with confirmed absolute insulin deficiency had a shorter time to insulin treatment (median 2.5 vs. 6 years, P=0.005) and lower BMI (25.1 vs. 29.1kg/m(2) , P=0.04). Two out of five patients were glutamic acid decarboxylase autoantibody-positive.
CONCLUSIONS: Absolute insulin deficiency may occur in long-standing Type 2 diabetes, and cannot be reliably predicted by clinical features or autoantibodies. Its recognition should help guide treatment, education and management. The urinary C-peptide creatinine ratio is a practical non-invasive method to aid detection of absolute insulin deficiency, with a urinary C-peptide creatinine ratio > 0.2 nmol/mmol being a reliable indicator of retained endogenous insulin secretion.

Unlocking Biomarkers’ Full Potential

David Daniels, Ph.D.     genengnews  Feb 1, 2013 (Vol. 33, No. 3)

http://www.genengnews.com/gen-articles/unlocking-biomarkers-full-potential/4700/

Biomarker research and development has evolved over the past years from looking for a single marker (e.g., PSA) linked to a disease state to looking for a panel of markers that can capture the heterogeneity inherent in both the disease and the impacted patient population.

That is one of the key messages to be delivered at GTC’s “Biomarkers Summit” next month. Across the board, resources are being focused on the delivery of more precise, quantifiable biomarkers with predictive value in therapeutic decisions and for the prognosis of illness.

“Our focus on biomarker development is the recognition that the new products need to provide cost savings for the already strapped healthcare systems rather than just be cost effective,” shares Paul Billings, M.D., Ph.D., CMO at Life Technologies.

“We have built a new medical sciences group to address the needs of the multiple delivery systems in the world—from the sophisticated medical clinics in the developed world to the nurse-run shanty clinic in the third world. Providing tools for equitable access to quality diagnosis, on assay platforms that can provide care for all patients, is our goal.”

Life Tech’s medical sciences division has been built by acquisition of Pinpoint Genomics, Navigenics, and Compendia, and collaborations with partners such as Ingenuity Systems and CollabRx. The division is focused on taking the tools that have been used in the life science laboratories and providing molecular diagnostic data to the clinic. The intent is to deliver data in a valuable format that can be used by the molecular pathologist or the treating physician.

The division is developing the Pervenio™ Lung RS assay, a 14-gene expression profile that serves as a risk stratifier that uses a weighted algorithm for the expressed biomarkers within the tumor biopsy, a first-of-its-kind prognostic test for lung cancer, the firm reports.

Initially, tests will be offered as a service through Life Tech’s CLIA laboratory. Then, from the performance lessons learned, Life Tech’s will develop a simpler assay platform, with FDA approval, that can be dispersed globally without reduction of the essential content in the biomarker panel. The focus is on the workflow—screening for known mutations using established easy-to-use assay platforms, like RT-PCR. Should the screen not produce useful results, clinicians can search for new mutations via discovery platforms like next-gen sequencing (NGS).

http://www.genengnews.com/Media/images/Article/thumb_Sequenom_LungCartaPanel1722631391.jpg

Sequenom’s LungCarta panel of 214 somatic mutations in 26 tumor suppressors and oncogenes covers highly mutated pathways in lung adenocarcinomas.

At Sequenom, the company provides both the tools (DNA mass spectrometry and reagents) for confirmatory biomarker development as well as serving on the front lines as a diagnostic service provider (CLIA lab). The beauty of DNA mass spec is that it can process multiplexed PCR samples (10–60 loci) in a method that is quantitative when used for profiling tumor biopsies that are either archival or fresh tissue.

Given a tumor sample with multiple somatic mutations, the instrument enables the determination of the homogeneity of the cells, in which case the mutations will have the same allele frequency. Accuracy, as measured by coefficient of variance, is less than 2%. Despite this level of sensitivity, the mass spec can only be used as a confirmatory tool looking for known mutations. Discovery is best done using DNA sequencing. DNA mass spec can also be used to study methylation in tumor samples.

“In the not-too-distant future, we will be looking for mutations in plasma samples rather than biopsies,” predicts Charles Cantor, Ph.D., CSO at Sequenom.

“The key is to look noninvasively for mutations within plasma samples such that we can potentially catch the disease state earlier, rather than after tumor formation. Regardless of the tumor type, this approach will enable us to monitor therapeutic response and metastatic potential noninvasively. DNA mass spec is an ultrasensitive detection product that can detect somatic mutations at levels of 1 per 1,000. This level of sensitivity is critical for the future of plasma screening. NGS technology is not that sensitive.”

Sequenom’s CLIA lab is using automated DNA mass spec to provide three different test protocols: (1) carrier screening for cystic fibrosis looking at more than 100 different mutations, (2) adult macular degeneration progression using an SNP test with 13 loci, and (3) a noninvasive test for Rh compatibility between a mother and her unborn fetus.

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Scientists are using Illumina’s HiSeq system to discover molecular biomarkers that may provide opportunities for early detection of a range of diseases.

Sequenom has also set up an NGS facility within a CLIA lab in San Diego using Illumina’s HiSEQ platform. The NGS platform has been set up for noninvasive aneuploidy detection of maternal plasma (10 cc sample) looking at chromosomes 13, 18, and 21. The lab says it has analyzed more than 40,000 samples this year and is planning to increase that volume up to 100,000 samples per year. Most of these samples come from the U.S., but given the development of a new blood collection tube that allows for 72-hour ambient shipping, the lab is looking to increase the number of samples from outside the U.S.

Drug Development

During drug development, biomarkers function as pharmacodynamic markers to help assess the mechanism of action of a drug candidate, to define the downstream biological pathway, and to determine whether the drug is engaging the target with the anticipated biological effect. Later, biomarkers help determine whether a drug is effective using the tested regime (route of delivery, dosage level, and length of exposure time).

Following early development, the second stage is to use biomarkers to help segment patients for clinical trials. Part of the consideration here is how heterogeneous the disease is; are there homogeneous subsets of patients that will respond differentially to the drug based on different mechanisms of the disease?

“Biomarker research is focused on on- target effects,” says Nick Dracopoli, Ph.D., vp, head of oncology biomarkers at Janssen Research and Development, a J&J company.

“We look at indications and at patients with those indications that are most likely to respond to the drug candidates we’re developing. For oncology biomarkers, germ-line effects are weaker indicators than somatic changes in the tumor. As a consequence, SNP-based, genome-wide association studies are not very useful. It is better to focus on molecular changes within the tumor and define gene expression profiles and epigenetic modifications that correlate with the tumor phenotype. We are increasingly tracking patient immune response, particularly as more immuno-oncology products are moving into the drug development pipeline.”

The number of biomarkers being developed varies from project to project. But it is very clear that to be successful in the clinic, the biomarkers and the assays need to be of low complexity. Of the 10 to 12 companion diagnostics that have been approved by the FDA to date, all measure the status of the drug target (on-target markers). For example, EGFR measures the level of receptor expression; Braf and Kras markers measure the presence of the mutation and translocation in the ALK gene measures gene knockout.

It is important to realize that molecular profiles for first-in-class drugs are not optimal because they are based on only a few patients. Consequently they have weak predictive value overall.

“Aside from that rule of thumb, if you have a greater than 50% response rate for your drug, it is unlikely that you need a biomarker to predict response. Biomarker utility is best for drugs that would have a difficult road to approval, where it is critical to enrich for the subpopulation of responders. For example, Pfizer’s crizontinib was approved for non-small-cell lung patients but is only effective for 5% of all patients. If Pfizer was unable to demonstrate the relationship between activation of the ALK gene and disease, this inhibitor would not have been approved,” says Dr. Dracopoli.

“Drugs that are more broadly active can come to market without a companion diagnostic test. There is always a balance between the predictive values of the biomarker test and the response rates to treatment. That is, we should not treat if the chance of response is only 3–5%, rather than if it were 50% where the patient would want to take the chance if the drug were safe.”

An important take-home message is that mutations are not unique to an indication. So if you find a driver mutation in indications for which the drug has not been approved, you could discover new indications for the drug.

“At the end of the day, this is what cancer is—heterogeneous,” says Dr. Dracopoli. “We’d all love to treat one cancer with one drug and at one dose, but the story is more complex. The future of oncology is around understanding the molecular heterogeneity or underlying molecular pathology of the disease and the diversity of it, and then treat each patient accordingly.”

Clinical Considerations

“Given the complexity of biology,” says Achim Plum, Ph.D., principal consultant, Siemens, “whether is it cancer, metabolic disease, or any other disease state, we have been forced to move away from the idea that a single biomarker can capture the entire ‘story’ or mechanistic view of any disease. Hence newly developed biomarkers will be made up of a panel of markers that serve as a profile. In addition, with the sheer volume of DNA and protein analytics data, the clinic will need to employ software tools and algorithms to help the decision making.”

The task of getting broad profiling technologies that are analytical into a clinical setting and making them routine is difficult but not insurmontable. This will take a collaborative effort, something that Siemens among others are looking to develop. The key is to avoid technology hype and to establish good reliable software to process the data for decision making. “Data is not knowledge, and knowledge is not automatically decision making.”

As an academic, Daniel Chan, Ph.D., has a view of the whole value chain for biomarkers from discovery to development to use in the clinic. Dr. Chan holds the titles of professor in pathology, oncology, radiology, and urology, and is the director of the clinical chemistry division lab at Johns Hopkins Hospital.

Given his perspective from discovery to clinical use, Dr. Chan indicated that from the clinical point of view, “we need more markers.” He oversees the discovery of new biomarkers in his research lab, their validation in his translational research lab, and finally their utility in practice in his clinical chemistry lab. He is a strong advocate for collaboration of biomarker development from discovery to verification and validation to incorporation within the clinical practice.

Beyond the use of biomarkers for patient stratification and correlation between marker and therapeutic choice, as is the focus of the biopharma industry, for the clinic the use of biomarkers is for prevention and early detection. The earlier the detection, the better the outcome. That is, provide the “cure” before you need to initiate treatment.

To be successful in the future of biomarkers, we need to look beyond the biopharma focus and expand the horizon for early detection and monitor therapy later, says Dr. Chan. He describes a roadmap of developing bridges (to bridge the knowledge gaps), gates (decision gates for go/no go decisions as to whether a development path is viable), and partnerships (to collaborate with different points of view) for efficient new biomarker development.

According to Dr. Chan, we must define the intended use of the biomarker, which identifies the specific application and sets up the clinical study and study population to meet the clinical needs. We need to define specific assays to monitor biomarkers that will work within a clinical setting, not a research lab setting that uses disease models (tissue culture cells or small animals) and not real patient samples.

“The days when single markers are sufficient (PSA for prostate cancer or troponin for cardiovascular disease) are behind us. We need to develop a panel of markers or a profile pattern to address patient population heterogeneity and disease complexity that will guide our decision-making process,” remarks Dr. Chan. “Molecular biomarkers are giving way to protein biomarkers,” he adds.

Prevention and early detection will require the use of whole-body scans, so the sampling technology and analytical tools to be developed are critical to realize this goal. Assay ease of use, automation, and analytical performance that is suitable for the clinical lab are fundamental.

“An important future goal for biomarkers,” says Dr. Billings, “is to sample circulating tumor cells or circulating DNA in blood or plasma samples as a noninvasive measure of patient status. A decline in tumor biomarkers during chemotherapy, for example, could reflect the efficacy of the therapy. In contrast, an increase in tumor biomarkers, in a patient who had previously undergone surgery and therapy, might indicate disease recurrence, and is likely to do so before a tumor mass is detectable by imaging methods.”

STAT4 Gene Polymorphisms Are Associated with Susceptibility and ANA Status in Primary Biliary Cirrhosis

Satoru Joshita, T Umemura, M Nakamura, Y Katsuyama, S Shibata, et al.
Disease Markers  2014, Article ID 727393, 8 pages http://dx.doi.org/10.1155/2014/727393

Recent genome-wide association studies suggest that genetic factors contribute to primary biliary cirrhosis (PBC) susceptibility. Although several reports have demonstrated that the interleukin (IL) 12 signaling pathway is involved in PBC pathogenesis, its precise genetic factors have not been fully clarified. Here, we performed an association analysis between IL12A, IL12RB, and signal transducer and activator of transcription 4 (STAT4) genetic variations and susceptibility to PBC. Single nucleotide polymorphisms (SNPs) were genotyped in 395 PBC patients and 458 healthy subjects of Japanese ethnicity and evaluated for associations with PBC susceptibility, anti-nuclear antibody (ANA) status, and anti-mitochondrial antibody (AMA) status. We detected significant associations with PBC susceptibility for several STAT4 SNPs (rs10168266; p = 9.4 × 10−3, rs11889341; p = 1.2 × 10−3, rs7574865; p = 4.0 × 10−4, rs8179673; p = 2.0 × 10−4, and rs10181656; p = 4.2 × 10−5). Three risk alleles (rs7574865; p = 0.040, rs8179673; p = 0.032, and rs10181656; p = 0.031) were associated with ANA status, but not with AMA positivity. Our findings confirm that STAT4 is involved in PBC susceptibility and may play a role in ANA status in the Japanese population.

Serum Omentin-1 as a Disease Activity Marker for Crohn’s Disease

Yan Lu, Li Zhou, L Liu, Yan Feng, Li Lu, X Ren, X Dong, & W Sang
Disease Markers  2014, Article ID 162517, 5 pages   http://dx.doi.org/10.1155/2014/162517

Background and Aim. It remains challenging to determine the inflammatory activity in Crohn’s disease (CD) for lack of specific laboratory markers. Recent studies suggest that serum omentin-1 is associated with inflammatory response. We aimed to assess the potential of serum omentin-1 as a marker of disease activity in CD patients.
Methods. Serum omentin-1 concentrations were determined by enzyme-linked immunosorbent assay (ELISA) in patients with CD (n = 240), functional gastrointestinal disorders (FGDs, n = 120), and healthy controls (HC, n = 60) and evaluated for correlation with disease activity. Expression of omentin-1 in colonic tissues from patients with CD was also analyzed by real-time PCR and Western blotting. Serum omentin-1 levels as an activity index were evaluated using a receiver operating characteristic (ROC) curve.
Results. Serum omentin-1 concentrations were significantly decreased in active CD patients compared with patients in remission, FGDs, and HC (all p < 0.001). Expression of omentin-1 was decreased at mRNA and protein levels in inflamed colonic tissues in active CD than that in noninflamed colonic tissues. Serum omentin-1 levels were negatively correlated with disease activity in CD, better than C-reactive protein (CRP).
Conclusion. Our results indicate that serum and colonic omentin-1 expressions are decreased in active CD patients. The correlation of serum omentin-1 with disease activity in CD is superior to that of CRP. Serum omentin-1 is a potential marker for CD disease activity.
Serum Levels of Resistin, Adiponectin, and Apelin in Gastroesophageal Cancer Patients

Dorota Diakowska, K Markocka-Mdczka, P Szelachowski, and K Grabowski
Disease Markers 2014, Article ID 619649, 8 pages   http://dx.doi.org/10.1155/2014/619649

The aim of the study was the investigation of relationship between cachexia syndrome and serum resistin, adiponectin, and apelin in patients with gastroesophageal cancer (GEC).
Material and Methods. Adipocytokines concentrations were measured in sera of 85 GEC patients and 60 healthy controls. They were also evaluated in tumor tissue and appropriate normal mucosa of 38 operated cancer patients.
Results. Resistin and apelin concentrations were significantly higher in GEC patients than in the controls. The highest resistin levels were found in cachectic patients and in patients with distant metastasis. Serum adiponectin significantly decreased in GEC patients with regional and distant metastasis. Serum apelin was significantly higher in cachectic patients than in the controls. Apelin was positively correlated with hsCRP level. Resistin and apelin levels increased significantly in tumor tissues. Weak positive correlations between adipocytokines levels in serum and in tumor tissue were observed.
Conclusions. Resistin is associated with cachexia and metastasis processes of GEC. Reduction of serum adiponectin reflects adipose tissue wasting in relation to GEC progression. Correlation of apelin with hsCRP can reflect a presumable role of apelin in systemic inflammatory response in esophageal and gastric cancer.

Serum Level of HER-2 Extracellular Domain in Iranian Patients with Breast Cancer: A Follow-up Study

Mehrnoosh Doroudchi, Abdolrasoul Talei, Helmout Modjtahedi, et al.
IJI 2005; 2(4): 191-200

Background: A soluble form of HER-2/neu extracellular domain (sHER-2) is reported to be released in the sera of metastatic breast cancer patients.
Objective: To measure the level of sHER-2 in sera of 115 breast cancer patients. Methods: Serial samples of 27 patients with metastasis, 18 non-metastatic patients, 15 patients in stage 0/I and 14 patients with accompanying benign breast disease were also included in this study.
Results: No significant difference was observed between sHER-2 level in the pre-operative sera of breast cancer patients and that of healthy individuals. Only 8 out of 27 patients whom later developed metastasis showed elevated levels of sHER-2 in their first serum sample. However, a trend of increase in the level of sHER-2 was observed in 14 (51.8%) of 27 metastatic sera before clinical diagnosis of the metastasis. A significant association between sHER-2 positive status and vascular invasion of the tumor was observed (P = 0.02). In addition, significant correlation of sHER-2 level with CEA (highest r = 0.74) and CA 15.3 (highest r = 0.74) tumor marker levels in the serial sera were observed. The mean time from sHER-2 positivity to tumor metastasis was calculated to be 98 days (range = 29-174).  Conclusion: Our results indicate that a relatively high percentage of Iranian patients with breast cancer show an elevated level of sHER-2 in their sera before clinical diagnosis of the tumor metastasis. Therefore, measuring the level of this oncoprotein, not only helps physicians in monitoring the patients during HERCEPTIN therapy, but also can be helpful in choosing more aggressive treatments at the early satges of tumor metastasis.
B-type natriuretic peptide is a biomarker for pulmonary hypertension in preterm infants with bronchopulmonary dysplasia

Alain Cuna, Jegen Kandasamy, Naomi Fineberg, Brian Sims
Research and Reports in Neonatology 2013:3 33–36
http://dx.doi.org/10.2147/RRN.S42236

Background: B-type natriuretic peptide (BNP) is a cardiac biomarker useful in screening for pulmonary hypertension (PH) in adults. It is possible that BNP may also be useful in detecting PH among preterm infants with bronchopulmonary dysplasia (BPD).
Objective: To determine the utility of BNP for identification of PH among preterm infants with BPD.
Methods: We retrospectively identified preterm infants with BPD who underwent screening echocardiography for suspected PH and had serum BNP levels measured within 10 days before or after echocardiography. Eligible infants were classified based on echocardiographic diagnosis of either PH or no PH. Median and interquartile ranges (IQR) of BNP values were compared, and area under the curve (AUC) of receiver operator characteristic (ROC) analysis was used to determine the optimum threshold value for detection of PH.
Results: Twenty-five preterm infants with BPD (mean gestational age 26.5 ± 1.7 weeks, mean birth weight 747 ± 248 g) were identified. The median difference in days between echocardiography and BNP measurement was 1 day (IQR 0–3, range 0–10 days). Based on echocardiography, 16 were diagnosed with PH and nine without PH. No significant difference in terms of gestational age, birth weight, sex, race, or respiratory support was found between the two groups. Median (IQR) BNP values of those with PH were higher than those without PH (413 [212–1178] pg/mL versus 55 [21–84] pg/mL, P , 0.001). AUC of ROC analysis showed that a BNP value of 117 pg/mL had 93.8% sensitivity and 100% specificity for detecting PH.
Conclusion: BNP estimation may be useful for screening of PH in infants with BPD.

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Genomics and Metabolomics Advances in Cancer

Writer and Curator: Larry H. Bernstein, MD, FCAP

UPDATED 6/01/2019 

UPDATED 9/26/2021

Genomics

Unraveling the clonal hierarchy of somatic genomic aberrations

D Prandi, SC Baca, A Romanel, CE Barbieri, Juan-Miguel Mosquera, et al.
Genome Biology 2014, 15:439
http://genomebiology.com/2014/15/8/439

Defining the chronology of molecular alterations may identify milestones in carcinogenesis. To unravel the temporal evolution of aberrations from clinical tumors, we developed CLONET, which upon estimation of tumor admixture and ploidy infers the clonal hierarchy of genomic aberrations. Comparative analysis across 100 sequenced genomes from prostate, melanoma, and lung cancers established diverse evolutionary hierarchies, demonstrating the early disruption of tumor-specific pathways. The analyses highlight the diversity of clonal evolution within and across tumor types that might be informative for risk stratification and patient selection for targeted therapies. CLONET addresses heterogeneous clinical samples seen in the setting of precision medicine.

The Transcription Factor Titration Effect Dictates Level of Gene Expression

RC Brewster, FM Weinert, HG Garcia, D Song, M Rydenfelt, and R Phillips
Cell,  Mar 13, 2014;156: 1312–1323
http://dx.doi.org/10.1016/j.cell.2014.02.022

Models of transcription are often built around a picture of RNA polymerase and transcription factors (TFs) acting on a single copy of a promoter. However, most TFs are shared between multiple genes with varying binding affinities. Beyond that, genes often exist at high copy number—in multiple identical copies on the chromosome or on plasmids or viral vectors with copy numbers in the hundreds. Using a thermodynamic model, we characterize the interplay between TF copy number and the demand for that TF. We demonstrate the parameter-free predictive power of this model as a function of the copy number of the TF and the number and affinities of the available specific binding sites; such predictive control is important for the understanding of transcription and the desire to quantitatively design the output of genetic circuits. Finally, we use these experiments to dynamically measure plasmid copy number through the cell cycle.

Telomere dynamics in human mesenchymal stem cells after exposure to acute oxidative stress

M Harbo, S Koelvraa, N Serakinci, L Bendixa
DNA Repair 2012.  http://dx.doi.org/10.1016/j.dnarep.2012.06.003

A gradual shortening of telomeres due to replication can be measured using the standard telomere restriction fragments (TRF) assay and other methods by measuring the mean length of all the telomeres in a cell. In contrast, stress-induced telomere shortening, which is believed to be just as important for causing cellular senescence, cannot be measured properly using these methods. Stress-induced telomere shortening caused by, e.g. oxidative damage happens in a stochastic manner leaving just a few single telomeres critically short. It is now possible to visualize these few ultra-short telomeres due to the advantages of the newly developed Universal single telomere length assay (STELA), and we therefore believe that this method should be considered the method of choice when measuring the length of telomeres after exposure to oxidative stress. In order to test our hypothesis, cultured human mesenchymal stem cells, either primary or hTERT immortalized, were exposed to sub-lethal doses of hydrogen peroxide, and the short term effect on telomere dynamics was monitored by Universal STELA and TRF measurements. Both telomere measures were then correlated with the percentage of senescent cells estimated by senescence-associated β-galactosidase staining. The exposure to acute oxidative stress resulted in an increased number of ultra-short telomeres, which correlated strongly with the percentage of senescent cells, whereas a correlation between mean telomere length and the percentage of senescent cells was absent. Based on the findings in the present study, it seems reasonable to conclude that Universal STELA is superior to TRF in detecting telomere damage caused by exposure to oxidative stress. The choice of method should therefore be considered carefully in studies examining stress-related telomere shortening as well as in the emerging field of lifestyle studies involving telomere length measurements.

tDNA insulators and the emerging role of TFIIIC in genome organization

Kevin Van Bortle and Victor G. Corces
Transcription Dec 12, 2012; 3(6): 1-8. www.landesbioscience.com

Recent findings provide evidence that tDNAs function as chromatin insulators from yeast to humans. TFIIIC, a transcription factor that interacts with the B-box in tDNAs as well as thousands of ETC sites in the genome, is responsible for insulator function. Though tDNAs are capable of enhancer-blocking and barrier activities for which insulators are defined, new insights into the relationship between insulators and chromatin structure suggest that TFIIIC serves a complex role in genome organization. We review the role of tRNA genes and TFIIIC as chromatin insulators, and highlight recent findings that have broadened our understanding of insulators in genome biology.

Structure and organization of insulators in eukaryotes. (A) From yeast to mammals, in organisms in which it has been studied, the TFIIIC protein interacts with the B-box sequence in tRNA genes or sites in the genome named ETC sites.

Synthetic CpG islands reveal DNA sequence determinants of chromatin structure

E Wachter, T Quante, C Merusi, A Arczewska, F Stewart, S Webb, A Bird
eLife 2014;3:e03397. http://dx.doi.org:/10.7554/eLife.03397.001

The mammalian genome is punctuated by CpG islands (CGIs), which differ sharply from the bulk genome by being rich in G + C and the dinucleotide CpG. CGIs often include transcription initiation sites and display ‘active’ histone marks, notably histone H3 lysine 4 methylation. In embryonic stem cells (ESCs) some CGIs adopt a ‘bivalent’ chromatin state bearing simultaneous ‘active’ and ‘inactive’ chromatin marks. To determine whether CGI chromatin is developmentally programmed at specific genes or is imposed by shared features of CGI DNA, we integrated artificial CGI-like DNA sequences into the ESC genome. We found that bivalency is the default chromatin structure for CpG-rich, G + C-rich DNA. A high CpG density alone is not sufficient for this effect, as A + T-rich sequence settings invariably provoke de novo DNA methylation leading to loss of CGI signature chromatin. We conclude that both CpG-richness and G + C-richness are required for induction of signature chromatin structures at CGIs.

Locus-specific mutation databases: pitfalls and good practice based on the p53 experience

Thierry Soussi, Chikashi Ishioka, Mireille Claustres and Christophe Béroud
NATURE REVIEWS | CANCER JAN 2006; 6: 83-90.

Between 50,000 and 60,000 mutations have been described in various genes that are associated with a wide variety of diseases. Reporting, storing and analysing these data is an important challenge as such data provide invaluable information for both clinical medicine and basic science.

The practical value of mutation analysis All studies performed to date show that mutations are, in general, not randomly distributed. Hot-spot regions have been demonstrated, corresponding to a region of DNA that is susceptible to mutations (such as CpG dinucleotides), a codon encoding a key residue in the biological function of the protein, or both (BOX 1). Identification of these hot-spot regions and natural mutants is essential to define crucial regions in an unknown protein.

Locus-specific databases have been developed to exploit this huge volume of data. The p53 mutation database is a paradigm, as it constitutes the largest collection of somatic mutations (22,000). However, there are several biases in this database that can lead to serious erroneous interpretations. We describe several rules for mutation database management that could benefit the entire scientific community.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

A Subramaniana, P Tamayo, VK  Mootha, S Mukherjee, BL Ebert, et al.
PNAS  Oct 25, 2005; 102(43): 15545–15550
http://pnas.org/cgi/doi/10.1073/pnas.0506580102

Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Mutational landscape and significance across 12 major cancer types

C Kandoth, MD McLellan, F Vandin, Kai Ye, B Niu, C Lu, et al.
NATURE  OCT 2013; 502: 333-337. http://dx.doi.org:/10.1038/nature12634

The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/ carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known(for example, mitogen-activated protein kinase, phosphatidylinositol-3-OH kinase,Wnt/b-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the numberof driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment.

Molecular insights into RNA and DNA helicase evolution from the determinants of  specificity for a DEAD-box RNA helicase

Anna L. Mallam, David J. Sidote and Alan M. Lambowitz
eLife 2014; http://dx.doi.org:/10.7554/eLife.04630

How different helicase families with a conserved catalytic ‘helicase core’ evolved to function on varied RNA and DNA substrates by diverse mechanisms remains unclear. Here, we used Mss116, a yeast DEAD-box protein that utilizes ATP to locally unwind dsRNA, to investigate helicase specificity and mechanism. Our results define the molecular basis for the substrate specificity of a DEAD-box protein. Additionally, they show that Mss116 has ambiguous substrate-binding properties and interacts with all four NTPs and both RNA and DNA. The efficiency of unwinding correlates with the stability of the ‘closed-state’ helicase core, a complex with nucleotide and nucleic acid that forms as duplexes are unwound. Crystal structures reveal that core stability is modulated by family-specific interactions that favor certain substrates. This suggests how present-day  helicases diversified from an ancestral core with broad specificity by retaining core closure as a common catalytic mechanism while optimizing substrate-binding interactions for different cellular functions.

Identification of human TERT elements necessary for telomerase recruitment to telomeres

Jens C Schmidt, Andrew B Dalby, Thomas R Cech
eLife 2014; http://dx.doi.org/10.7554/eLife.03563

Human chromosomes terminate in telomeres, repetitive DNA sequences bound by the shelterin complex. Shelterin protects chromosome ends, prevents recognition by the DNA damage machinery, and recruits telomerase. A patch of  amino acids, termed the TEL-patch, on the OB-fold domain of the shelterin  component TPP1 is essential to recruit telomerase to telomeres. In contrast, the site on telomerase that interacts with the TPP1 OB-fold is not well defined. Here we identify separation-of-function mutations in the TEN-domain of human telomerase reverse transcriptase (hTERT) that disrupt the interaction of telomerase with TPP1 in vivo and in vitro but have very little effect on the catalytic activity of telomerase. Suppression of a TEN-domain mutation with a compensatory charge-swap mutation in the TEL-patch indicates that their association is direct. Our findings define the interaction interface required for telomerase recruitment to telomeres, an important step towards developing modulators of this interaction as therapeutics for human disease.

Metabolomics

Single Cell Profiling of Circulating Tumor Cells: Transcriptional Heterogeneity and Diversity from Breast Cancer Cell Lines

MN Mindrinos, G Bhanot, SH Dairkee, RW Davis, SS Jeffrey
PLoS ONE 7(5): e33788. http://dx.doi.org:/doi:10.1371/journal.pone.0033788

Background: To improve cancer therapy, it is critical to target metastasizing cells. Circulating tumor cells (CTCs) are rare cells found in the blood of patients with solid tumors and may play a key role in cancer dissemination. Uncovering CTC phenotypes offers a potential avenue to inform treatment. However, CTC transcriptional profiling is limited by leukocyte contamination; an approach to surmount this problem is single cell analysis. Here we demonstrate feasibility of performing high dimensional single CTC profiling, providing early insight into CTC heterogeneity and allowing comparisons to breast cancer cell lines widely used for drug discovery.
Methodology/Principal Findings: We purified CTCs using the MagSweeper, an immunomagnetic enrichment device that isolates live tumor cells from unfractionated blood. CTCs that met stringent criteria for further analysis were obtained from 70% (14/20) of primary and 70% (21/30) of metastatic breast cancer patients; none were captured from patients with nonepithelial cancer (n = 20) or healthy subjects (n = 25). Microfluidic-based single cell transcriptional profiling of 87 cancer associated and reference genes showed heterogeneity among individual CTCs, separating them into two major subgroups, based on 31 highly expressed genes. In contrast, single cells from seven breast cancer cell lines were tightly clustered together by sample ID and ER status. CTC profiles were distinct from those of cancer cell lines, questioning the suitability of such lines for drug discovery efforts for late stage cancer therapy.
Conclusions/Significance: For the first time, we directly measured high dimensional gene expression in individual CTCs without the common practice of pooling such cells. Elevated transcript levels of genes associated with metastasis NPTN, S100A4, S100A9, and with epithelial mesenchymal transition: VIM, TGFß1, ZEB2, FOXC1, CXCR4, were striking compared to cell lines. Our findings demonstrate that profiling CTCs on a cell-by-cell basis is possible and may facilitate the application of ‘liquid biopsies’ to better model drug discovery

Simplifying Disease Complexity part 6 – Bringing Metabolomics into Practice
Dr. Kirk Beebe, Director of Application Science, Metabolon, Inc.

n the previous editions of this 6-part series, we’ve explored numerous example of how metabolomics is bringing success to areas such as cancer, metabolic disease, cardiovascular, and rare disease research. Although we did not devote attention to every area of biology or therapeutic area, the intent of this broad series was not only to convey how metabolomics can be used in a specific area of research (e.g. cancer), but actually, how metabolomics is a central science for interrogating any biological question. So, although it may seem like an oversimplification, to understand whether metabolomics could be used in a research setting one need only ask themselves, “Do I have a biological question that would benefit from a hypothesis-free approach?, am I interested in exploring my system for potential new discoveries? Or do I need a biomarker/better biomarker?

As described in our first part, metabolites have been and continue to be a staple for clinical and in vivo decision making (e.g. cholesterol, glucose, bilirubin, creatinine, thyroid hormone, newborn screening for inborn errors of metabolism (IEMs)). In short, this utility is fundamental to the foundations of biology since metabolism is central to all kingdoms of life and contemporary biology is driven to maintain metabolic homeostasis to maintain the phenotype. An unappreciated point that we leave this series with is that this fundamental nature (the connection of metabolism to the phenotype) confers an important advantage of metabolism for deriving biomarkers and understanding the underlying physiology.

Metabolites are a diagnostic data stream.

Whether a phenotype is driven by a single mutation or a combination of genetic differences, environmental influences or the microbiota, metabolism provides a systems-level diagnostic.

That is, no matter the source of the physiological or phenotypic change (i.e. genes, microbiota, environmental), the change will almost invariably register within metabolism. Thus, modern metabolomic approaches offer the opportunity to more deeply interrogate the “metabolome” to discover more sensitive and specific biomarkers and understand the basis of disease and drug response.

As such, metabolomics has the potential to be able to integrate systems on a number of levels. It is useful through its ability to enrich genomics, transcriptomics and proteomics, thus integrating a number of data streams that provide knowledge and contribute to informed decision-making and patient management1. Using metabolomics, individual tissues can be queried but less invasive sample types (e.g., blood, urine, feces, and/or saliva) can also yield biomarkers and mechanistic insight. The integration of the individual tissues at the level of these more accessible samples can offer an overview of the entire system and inform on important biological pathways. Finally, although the focus of this series was on what metabolomics can bring to biomarker and other related research areas, it should be noted that a combination of metabolomics with other scientific approaches will undoubtedly broaden insight and produce verifiable, validatable biomarkers that track with efficacy and therapy.

As we close this series, we hope that we have conveyed 4 critical points – 1) metabolism is central to biology and hence, key in research and biomarker discovery, 2) the reason for this is due to the fundamental nature of metabolism being central to the development of all life and being the focal point of contemporary biology’s drive to maintain homeostasis, 3) metabolomic is the most powerful way to survey metabolism by offering a simultaneous read-out if hundreds of reactions and pathways, and 4) metabolomics as a practical tool has only recently emerged.

And it is on this last point that we leave the reader with some final considerations. We imagine that, after careful review of the information outlined in this series, many readers will be motivated to explore the use of metabolomics in their research. However, as outlined throughout this series, mature technologies have only recently arisen. Nevertheless, there are many laboratories that perform some version of “metabolomics”. Although the experimental goal often dictates the precise approach, there are 5 critical features  that a metabolomic technology must harbor in order for it to achieve a similar purpose as mature omic technologies (e.g. DNA sequencers) in terms of depth of coverage and data quality. These minimally include:

  1. Must be based on an authenticated chemical library
    2. Must have procedures for eliminated noise from the data
    5. Must have a mechanism to identify novel metabolites
    6. Must have robust QC process from sample preparation through statistical analysis
    4. Must provide a mechanism to abstract information/interpret the data

References

  1. Eckhart, A.D., Beebe, K. & Milburn, M. Metabolomics as a key integrator for “omic” advancement of personalized medicine and future therapies. Clin Transl Sci 5, 285-288

(2012).

  1. Evans, A., Mitchell, M., Dai, H. & DeHaven, C.D. Categorizing Ion –Features in Liquid Chromatography/Mass Spectrometry Metobolomics Data. Metabolomics 2 (2012).
  2. DeHaven, C.D., Evans, A., Dai, H. & Lawton, K.A. in Metabolomics. (ed. U. Roessner) (InTech, 2012).
  3. Dehaven, C.D., Evans, A.M., Dai, H. & Lawton, K.A. Organization of GC/MS and LC/MS metabolomics data into chemical libraries. J Cheminform 2, 9 (2010).
  4. Evans, A.M., DeHaven, C.D., Barrett, T., Mitchell, M. & Milgram, E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal Chem 81, 6656-6667 (2009).

Prediction of intracellular metabolic states from extracellular metabolomic data

MK Aurich, G Paglia, Ottar Rolfsson, S Hrafnsdottir, M  Magnusdottir, MM, et al.

Metabolomics Aug 14, 2014;  http://dx.doi.org:/10.1007/s11306-014-0721-3
http://link.springer.com/article/10.1007/s11306-014-0721-3/fulltext.html#Sec1

intra- extracellular metabolites

intra- extracellular metabolites

http://link.springer.com/static-content/images/404/
art%253A10.1007%252Fs11306-014-0721-3/MediaObjects/11306_2014_721_Fig1_HTML.gif

Metabolic models can provide a mechanistic framework to analyze information-rich omics data sets, and are increasingly being used to investigate metabolic alternations in human diseases. An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data. Herein, we describe a workflow for such an integrative analysis emphasizing on extracellular metabolomics data. We demonstrate, using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM, how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting a more glycolytic phenotype for the CCRF-CEM model and a more oxidative phenotype for the Molt-4 model, which was supported by our experimental data. Gene expression analysis revealed altered expression of gene products at key regulatory steps in those central metabolic pathways, and literature query emphasized the role of these genes in cancer metabolism. Moreover, in silico gene knock-outs identified unique control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model. Thus, our workflow is well suited to the characterization of cellular metabolic traits based on extracellular metabolomic data, and it allows the integration of multiple omics data sets into a cohesive picture based on a defined model context.

Metabolome Informatics Research

Metabolome Informatics Research

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer MOC vs EOC

Identification of Metabolites in the Normal Ovary and Their Transformation in Primary and Metastatic Ovarian Cancer MOC vs EOC

Genomics and Cancer

Identification of Gene Networks Associated with Acute Myeloid Leukemia by Comparative Molecular Methylation and Expression Profiling

M Dellett, KA O’Hagan, HA Alexandra Colyer and KI Mills
Biomarkers in Cancer 2010:2 43–55  http://www.la-press.com.

Around 80% of acute myeloid leukemia (AML) patients achieve a complete remission, however many will relapse and ultimately die of their disease. The association between karyotype and prognosis has been studied extensively and identified patient cohorts as having favourable [e.g. t(8; 21), inv (16)/t(16; 16), t(15; 17)], intermediate [e.g. cytogenetically normal (NK-AML)] or adverse risk [e.g. complex karyotypes]. Previous studies have shown that gene expression profiling signatures can classify the sub-types of AML, although few reports have shown a similar feature by using methylation markers. The global methylation patterns in 19 diagnostic AML samples were investigated using the Methylated CpG Island Amplification Microarray (MCAM) method and CpG island microarrays containing 12,000 CpG sites. The first analysis, comparing favourable and intermediate cytogenetic risk groups, revealed significantly differentially methylated CpG sites (594 CpG islands) between the two subgroups. Mutations in the NPM1 gene occur at a high frequency (40%) within the NK-AML subgroup and are associated with a more favourable prognosis in these patients. A second analysis comparing the NPM1 mutant and wild-type research study subjects again identified distinct methylation profiles between these two subgroups. Network and pathway analysis revealed possible molecular mechanisms associated with the different risk and/or mutation sub-groups. This may result in a better classification of the risk groups, improved monitoring targets, or the identification of novel molecular therapies.

Molecular Imaging of Proteases in Cancer

Yunan Yang, Hao Hong, Yin Zhang and Weibo Cai
Cancer Growth and Metastasis 2009:2 13–27. http://www.la-press.com

Proteases play important roles during tumor angiogenesis, invasion, and metastasis. Various molecular imaging techniques have been employed for protease imaging: optical (both fluorescence and bioluminescence), magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). In this review, we will summarize the current status of imaging proteases in cancer with these techniques. Optical imaging of proteases, in particular with fluorescence, is the most intensively validated and many of the imaging probes are already commercially available. It is generally agreed that the use of activatable probes is the most accurate and appropriate means for measuring protease activity. Molecular imaging of proteases with other techniques (i.e. MRI, SPECT, and PET) has not been well-documented in the literature which certainly deserves much future effort. Optical imaging and molecular MRI of protease activity has very limited potential for clinical investigation. PET/SPECT imaging is suitable for clinical investigation; however the optimal probes for PET/SPECT imaging of proteases in cancer have yet to be developed. Successful development of protease imaging probes with optimal in vivo stability, tumor targeting efficacy, and desirable pharmacokinetics for clinical translation will eventually improve cancer patient management. Not limited to cancer, these protease-targeted imaging probes will also have broad applications in other diseases such as arthritis, atherosclerosis, and myocardial infarction.

Evolutionarily conserved genetic interactions with budding and fission yeast MutS identify orthologous relationships in mismatch repair-deficient cancer cells

E Tosti, JA Katakowski, S Schaetzlein, Hyun-Soo Kim, CJ Ryan, M Shales, et al.
Genome Medicine 2014, 6:68. http://genomemedicine.com/content/6/9/68

Background: The evolutionarily conserved DNA mismatch repair (MMR) system corrects base-substitution and insertion-deletion mutations generated during erroneous replication. The mutation or inactivation of many MMR factors strongly predisposes to cancer, where the resulting tumors often display resistance to standard chemotherapeutics. A new direction to develop targeted therapies is the harnessing of synthetic genetic interactions, where the simultaneous loss of two otherwise non-essential factors leads to reduced cell fitness or death. High-throughput screening in human cells to directly identify such interactors for disease-relevant genes is now widespread, but often requires extensive case-by-case optimization. Here we asked if conserved genetic interactors (CGIs) with MMR genes from two evolutionary distant yeast species (Saccharomyces cerevisiae and Schizosaccharomyzes pombe) can predict orthologous genetic relationships in higher eukaryotes.
Methods: High-throughput screening was used to identify genetic interaction profiles for the MutSα and MutSβ heterodimer subunits (msh2Δ, msh3Δ, msh6Δ) of fission yeast. Selected negative interactors with MutSβ (msh2Δ/msh3Δ) were directly analyzed in budding yeast, and the CGI with SUMO-protease Ulp2 further examined after RNA interference/drug treatment in MSH2-deficient and -proficient human cells.
Results: This study identified distinct genetic profiles for MutSα and MutSβ, and supports a role for the latter in recombinatorial DNA repair. Approximately 28% of orthologous genetic interactions with msh2Δ/msh3Δ are conserved in both yeasts, a degree consistent with global trends across these species. Further, the CGI between budding/fission yeast msh2 and SUMO-protease Ulp2 is maintained in human cells (MSH2/SENP6), and enhanced by Olaparib, a PARP inhibitor that induces the accumulation of single-strand DNA breaks. This identifies SENP6 as a promising new target for the treatment of MMR-deficient cancers.
Conclusion: Our findings demonstrate the utility of employing evolutionary distance in tractable lower eukaryotes to predict orthologous genetic relationships in higher eukaryotes. Moreover, we provide novel insights into the genome maintenance functions of a critical DNA repair complex and propose a promising targeted treatment for MMR deficient tumors.

Cancer Genome Landscapes

B Vogelstein, N Papadopoulos, VE Velculescu, S Zhou, LA Diaz Jr., KW Kinzler, et al.
Science 339, 1546 (2013); http://dx.doi.org:/10.1126/science.1235122

Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.

Approaches for establishing the function of regulatory genetic variants involved in disease

Julian Charles Knight
Genome Medicine 2014, 6:92.  http://genomemedicine.com/content/6/10/92

The diversity of regulatory genetic variants and their mechanisms of action reflect the complexity and context-specificity of gene regulation. Regulatory variants are important in human disease and defining such variants and establishing mechanism is crucial to the interpretation of disease-association studies. This review describes approaches for identifying and functionally characterizing regulatory variants, illustrated using examples from common diseases. Insights from recent advances in resolving the functional epigenomic regulatory landscape in which variants act are highlighted, showing how this has enabled functional annotation of variants and the generation of hypotheses about mechanism of action. The utility of quantitative trait mapping at the transcript, protein and metabolite level to define association of specific genes with particular variants and further inform disease associations are reviewed. Establishing mechanism of action is an essential step in resolving functional regulatory variants, and this review describes how this is being facilitated by new methods for analyzing allele-specific expression, mapping chromatin interactions and advances in genome editing. Finally, integrative approaches are discussed together with examples highlighting how defining the mechanism of action of regulatory variants and identifying specific modulated genes can maximize the translational utility of genome-wide association studies to understand the pathogenesis of diseases and discover new drug targets or opportunities to repurpose existing drugs to treat them.

Biomarkers

TRIM29 as a Novel Biomarker in Pancreatic Adenocarcinoma

Hongli Sun, Xianwei Dai, and Bing Han
Disease Markers 2014, Article ID 317817, 7 pages
http://dx.doi.org/10.1155/2014/317817

Background and Aim. Tripartite motif-containing 29 (TRIM29) is structurally a member of the tripartite motif family of proteins and is involved in diverse human cancers. However, its role in pancreatic cancer remains unclear.
Methods. The expression pattern of TRIM29 in pancreatic ductal adenocarcinoma was assessed by immunocytochemistry. Multivariate logistic regression analysis was used to investigate the association between TRIM29 and clinical characteristics. In vitro analyses by scratch wound healing assay and invasion assays were performed using the pancreatic cancer cell lines.
Results. Immunohistochemical analysis showed TRIM29 expression in pancreatic cancer tissues was significantly higher (𝑛 = 186) than that in matched adjacent nontumor tissues. TRIM29 protein expression was significantly correlated with lymph node metastasis (𝑃 = 0.019). Patients with positive TRIM29 expression showed both shorter overall survival and shorter recurrence-free survival than those with negative TRIM29 expression. Multivariate analysis revealed that TRIM29 was an independent factor for pancreatic cancer over survival (HR = 2.180, 95% CI: 1.324–4.198, 𝑃 = 0.011). In vitro, TRIM29 knockdown resulted in inhibition of pancreatic cancer cell proliferation, migration, and invasion.
Conclusions. Our results indicate that TRIM29 promotes tumor progression and may be a novel prognostic marker for pancreatic ductal adenocarcinoma.

Bioinformatic identification of proteins with tissue-specific expression for biomarker discovery

I Prassas, CC Chrystoja, S Makawita1, and EP Diamandis
BMC Medicine 2012, 10:39. http://www.biomedcentral.com/1741-7015/10/39

Background: There is an important need for the identification of novel serological biomarkers for the early detection of cancer. Current biomarkers suffer from a lack of tissue specificity, rendering them vulnerable to nondisease-specific increases. The present study details a strategy to rapidly identify tissue-specific proteins using bioinformatics.
Methods: Previous studies have focused on either gene or protein expression databases for the identification of candidates. We developed a strategy that mines six publicly available gene and protein databases for tissue-specific proteins, selects proteins likely to enter the circulation, and integrates proteomic datasets enriched for the cancer secretome to prioritize candidates for further verification and validation studies.
Results: Using colon, lung, pancreatic and prostate cancer as case examples, we identified 48 candidate tissuespecific biomarkers, of which 14 have been previously studied as biomarkers of cancer or benign disease. Twenty six candidate biomarkers for these four cancer types are proposed.
Conclusions: We present a novel strategy using bioinformatics to identify tissue-specific proteins that are potential cancer serum biomarkers. Investigation of the 26 candidates in disease states of the organs is warranted

The Serum Glycome to Discriminate between Early-Stage Epithelial Ovarian Cancer and Benign Ovarian Diseases

K Biskup, E Iona Braicu, J Sehouli, R Tauber, and V Blanchard
Disease Markers 2014, Article ID 238197, 10 pages
http://dx.doi.org/10.1155/2014/238197

Epithelial ovarian cancer (EOC) is the sixth most common cause of cancer deaths in women because the diagnosis occurs mostly when the disease is in its late-stage. Current diagnostic methods of EOC show only a moderate sensitivity, especially at an early-stage of the disease; hence, novel biomarkers are needed to improve the diagnosis. We recently reported that serum glycome modifications observed in late-stage EOC patients by MALDI-TOF-MS could be combined as a glycan score named GLYCOV that was calculated from the relative areas of the 11 N-glycan structures that were significantly modulated. Here, we evaluated the ability of GLYCOV to recognize early-stage EOC in a cohort of 73 individuals comprised of 20 early-stage primary serous EOC, 20 benign ovarian diseases (BOD), and 33 age-matched healthy controls. GLYCOV was able to recognize stage I EOC whereas CA125 values were statistically significant only for stage II EOC patients. In addition, GLYCOV was more sensitive and specific compared to CA125 in distinguishing early-stage EOC from BOD patients, which is of high relevance to clinicians as it is difficult for them to diagnose malignancy prior to operation.

The Clinicopathological Significance of miR-133a in Colorectal Cancer

Timothy Ming-Hun Wan, Colin Siu-Chi Lam, Lui Ng, Ariel Ka-Man Chow, et al.
Disease Markers  2014, Article ID 919283, 8 pages http://dx.doi.org/10.1155/2014/919283

This study determined the expression of microRNA-133a (MiR-133a) in colorectal cancer (CRC) and adjacent normal mucosa samples and evaluated its clinicopathological role in CRC. The expression of miR-133a in 125 pairs of tissue samples was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) and correlated with patient’s clinicopathological data by statistical analysis. Endogenous expression levels of several potential target genes were determined by qRT-PCR and correlated using Pearson’s method. MiR-133a was downregulated in 83.2% of tumors compared to normal mucosal tissue. Higher miR-133a expression in tumor tissues was associated with development of distant metastasis, advanced Dukes and TNM staging, and poor survival. The unfavorable prognosis of higher miR-133a expression was accompanied by dysregulation of potential miR-133a target genes, LIM and SH3 domain protein 1 (LASP1), Caveolin-1 (CAV1), and Fascin-1 (FSCN1). LASP1 was found to possess a negative correlation (𝛾 = −0.23), whereas CAV1 exhibited a significant positive correlation (𝛾 = 0.27), and a stronger correlation was found in patients who developed distant metastases (𝛾 = 0.42). In addition, a negative correlation of FSCN1 was only found in nonmetastatic patients. In conclusion, miR-133a was downregulated in CRC tissues, but its higher expression correlated with adverse clinical characteristics and poor prognosis.

The Clinical Significance of PR, ER, NF-𝜅B, and TNF-𝛼 in Breast Cancer

Xian-Long Zhou, Wei Fan, Gui Yang, and Ming-Xia Yu
Disease Markers 2014, Article ID 494581, 7 pages http://dx.doi.org/10.1155/2014/494581

Objectives. To investigate the expression of estrogen (ER), progesterone receptors (PR), nuclear factor-𝜅B (NF-𝜅B), and tumor necrosis factor-𝛼 (TNF-𝛼) in human breast cancer (BC), and the correlation of these four parameters with clinicopathological features of BC.
Methods and Results. We performed an immunohistochemical SABC method for the identification of ER, PR, NF-𝜅B, and TNF-𝛼 expression in 112 patients with primary BC.The total positive expression rate of ER, PR, NF-𝜅B, and TNF-𝛼 was 67%, 76%, 84%, and 94%, respectively. The expressions of ER and PR were correlated with tumor grade, TNM stage, and lymph node metastasis (𝑃 < 0.01, resp.), but not with age, tumor size, histological subtype, age at menarche, menopause status, number of pregnancies, number of deliveries, and family history of cancer. Expressions of ER and PR were both correlated with NF-𝜅B and TNF-𝛼 expression (𝑃 < 0.05, resp.). Moreover, there was significant correlation between ER and PR (𝑃 < 0.0001) as well as between NF-𝜅B and TNF-𝛼 expression (𝑃 < 0.05).
Conclusion. PR and ER are highly expressed, with significant correlation with NF-𝜅B and TNF-𝛼 expression in breast cancer. The important roles of ER and PR in invasion and metastasis of breast cancer are probably associated with NF-𝜅B and TNF-𝛼 expression.

Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

J Wang, A Sharma, SA Ghamande, S Bush, D Ferris, W Zhi, et la.
PLoS ONE 8(11): e78393. http://dx.doi.org:/10.1371/journal.pone.0078393

Background: Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC) has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer. Experimental Design: Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC) and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD), remission (RM) and recurrence (RC). The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis.
Results: Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC) have individually good area-under-the-curve (AUC) values (AUC = 0.69–0.86) and more than 10 three-marker combinations have excellent AUC values (0.91–0.93) in distinguishing active cancer samples (PD & RC) from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC). Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1) measured at remission  can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p,1023).
Conclusion: We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.

Serum Clusterin as a Tumor Marker and Prognostic Factor for Patients with Esophageal Cancer

Wei Guo, Xiao Ma, Christine Xue, Jianfeng Luo, Xiaoli Zhu, et al.
Disease Markers 2014, Article ID 168960, 7 pages http://dx.doi.org/10.1155/2014/168960

Background. Recent studies have revealed that clusterin is implicated in many physiological and pathological processes, including tumorigenesis. However, the relationship between serum clusterin expression and esophageal squamous cell carcinoma (ESCC) is unclear.
Methods. The serum clusterin concentrations of 87 ESCC patients and 136 healthy individuals were examined. An independent-samples Mann-Whitney 𝑈 test was used to compare serum clusterin concentrations of ESCC patients to those of healthy controls. Univariate analysis was conducted using the log-rank test and multivariate analyses were performed using the Cox proportional hazards model. Results. In healthy controls, the mean clusterin concentration was 288.8 ± 75.1 𝜇g/mL, while in the ESCC patients, the mean clusterin concentration was higher at 412.3±159.4 𝜇g/mL (𝑃 < 0.0001). The 1-, 2-, and 4-year survival rates for the 87 ESCC patients were 89.70%, 80.00%, and 54.50%. Serum clusterin had an optimal diagnostic cut-off point (serum clusterin concentration = 335.5 𝜇g/mL) for esophageal squamous cell carcinoma with sensitivity of 71.26% and specificity of 77.94%. And higher serum clusterin concentration (>500 𝜇g/mL) indicated better prognosis (𝑃 = 0.030).
Conclusions. Clusterin may play a key role during tumorigenesis and tumor progression of ESCC and it could be applied in clinical work as a tumor marker and prognostic factor.

Septin 9 methylated DNA is a sensitive and specific blood test for colorectal cancer

JD Warren, Wei Xiong, AM Bunker, CP Vaughn, LV Furtado, et al.
BMC Medicine 2011, 9:133. http://www.biomedcentral.com/1741-7015/9/133

Background: About half of Americans 50 to 75 years old do not follow recommended colorectal cancer (CRC) screening guidelines, leaving 40 million individuals unscreened. A simple blood test would increase screening compliance, promoting early detection and better patient outcomes. The objective of this study is to demonstrate the performance of an improved sensitivity blood-based Septin 9 (SEPT9) methylated DNA test for colorectal cancer. Study variables include clinical stage, tumor location and histologic grade.
Methods: Plasma samples were collected from 50 untreated CRC patients at 3 institutions; 94 control samples were collected at 4 US institutions; samples were collected from 300 colonoscopy patients at 1 US clinic prior to endoscopy. SEPT9 methylated DNA concentration was tested in analytical specimens, plasma of known CRC cases, healthy control subjects, and plasma collected from colonoscopy patients.
Results: The improved SEPT9 methylated DNA test was more sensitive than previously described methods; the test had an overall sensitivity for CRC of 90% (95% CI, 77.4% to 96.3%) and specificity of 88% (95% CI, 79.6% to 93.7%), detecting CRC in patients of all stages. For early stage cancer (I and II) the test was 87% (95% CI, 71.1% to 95.1%) sensitive. The test identified CRC from all regions, including proximal colon (for example, the cecum) and had a 12% false-positive rate. In a small prospective study, the SEPT9 test detected 12% of adenomas with a false-positive rate of 3%.
Conclusions: A sensitive blood-based CRC screening test using the SEPT9 biomarker specifically detects a majority of CRCs of all stages and colorectal locations. The test could be offered to individuals of average risk for CRC who are unwilling or unable to undergo colonoscopy.

Matrix Metalloproteinases in Cancer: Prognostic Markers and Therapeutic Targets

Pia Vihinen And Veli-Matti K¨Ah¨Ari
Int. J. Cancer 2002; 99: 157–166 http://dx.doi.org:/10.1002/ijc.10329

Degradation of extracellular matrix is crucial for malignant tumour growth, invasion, metastasis and angiogenesis. Matrix metalloproteinases (MMPs) are a family of zinc-dependent neutral endopeptidases collectively capable of degrading essentially all matrix components. Elevated levels of distinct MMPs can be detected in tumour tissue or serumof patients with advanced cancer and their role as prognostic indicators in cancer is studied. In addition, therapeutic intervention of tumour growth and invasion based on inhibition of MMP activity is under intensive investigation and several MMP inhibitors are in clinical trials in cancer. In this review, we discuss the current view on the feasibility of MMPs as prognostic markers and as targets for therapeutic intervention in cancer.

Mass Spectrometric Screening of Ovarian Cancer with Serum Glycans

Jae-Han Kim, Chang Won Park, Dalho Um, Ki Hwang Baek, Yohahn Jo, et al.
Disease Markers  2014, Article ID 634289, 9 pages
http://dx.doi.org/10.1155/2014/634289

development of novel biomarkers based on the glycomic analysis. In this study, N-linked glycans from human serum were quantitatively profiled by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and compared between healthy controls and ovarian cancer patients. A training set consisting of 40 healthy controls and 40 ovarian cancer cases demonstrated an inverse correlation between 𝑃 value of ANOVA and area under the curve (AUC) of each candidate biomarker peak from MALDI-TOF MS, providing standards for the classification. A multi-biomarker panel composed of 15 MALDI-TOF MS peaks resulted in AUC of 0.89, 80∼90% sensitivity, and 70∼83% specificity in the training set. The performance of the biomarker panel was validated in a separate blind test set composed of 23 healthy controls and 37 ovarian cancer patients, leading to 81∼84% sensitivity and 83% specificity with cut-off values determined by the training set. Sensitivity of CA-125, the most widely used ovarian cancer marker, was 74%in the training set and 78% in the test set, respectively. These results indicate that MALDI-TOF MS-mediated serum N-glycan analysis could provide critical information for the screening of ovarian cancer.

Large, Collaborative Lung Cancer Trial Goes for Precision Medicine Goal

News | June 30, 2014 | Lung Cancer Targets

By Anna Azvolinsky, PhD

In a new biomarker-focused clinical trial, five therapies will be tested to develop new, precision medicine approaches to treat squamous cell lung cancer. The Lung Cancer Master Protocol (Lung-MAP)/SWOG S1400 phase 2/3 clinical trial, brings together the National Cancer Institute (NCI), the Foundation for the National Institutes of Health (FNIH), SWOG Cancer Research, five pharmaceutical companies (Amgen, AstraZeneca, Genentech, MedImmune, and Pfizer), Foundation Medicine (a molecular informatics company), and Friends of Cancer Research, a non-profit foundation.

The trial aims to enroll about 10,000 patients total and will cost about $160 million, of which the NCI is contributing $25 million.

Lung-MAP is unique as this is the first public-private partnership in drug development that includes the NCI, the Food and Drug Administration (FDA), U.S. oncology cooperative groups, and a number of patient advocacy groups according to one of the study investigators, David Gandara, MD, chair of the SWOG lung committee, and thoracic oncologist at the UC Davis Cancer Center. “Funds are made available for every aspect of the trial,” said Gandara. “There is nothing in the history of oncology or drug development like it.”

The clinical trial seeks to identify molecular aberrations in patients with advanced squamous cell lung cancer that can be targeted either by existing therapies or through the development of new ones. The innovation of this trial is a master protocol that will rely on the strength of numbers—up to 1000 patients per year at more than 200 sites throughout the U.S. for more than 200 cancer-related genetic alterations. Testing results will then dictate which experimental trial arm is most appropriate for which patient. Unlike a trial that seeks to enroll patients harboring just one mutation, which limits the access for many patients, the Lung-MAP design better ensures that a patient who is screened will be eligible for a targeted therapy trial arm.

This type of umbrella trial design is particularly suitable for squamous cell lung cancer. Thus far, has not been defined by one or several driver mutations. Instead, these tumors are made of a spectrum of genetic aberrations that are each relatively rare within the squamous lung cancer patient population, making enrollment into targeted therapy clinical trials difficult. According to the NCI, Lung-MAP “aims to establish a model of clinical testing that more efficiently meets the needs of both patients and drug developers,” facilitating more efficient matching of a patient to an investigational targeted therapy trial.

Lung-MAP was specifically designed for squamous cell lung cancer because this lung cancer subtype represents the greatest unmet need for new treatment, Gandara told OncoTherapy Network:

“All of the dramatic advances that have been made in the treatment of lung cancer over the last ten years have occurred in adenocarcinoma, a lung cancer subtype with several recently recognized and ‘druggable oncogenes’ such as EGFR mutations or ALK translocations. However, there have been essentially no advances in squamous cell lung cancer.”

But, recent genome-wide studies have identified several gene alterations in squamous cell lung cancer that are also druggable, including PI3K, FGFR, and CDK mutations, said Gandara. The trial is initially testing four targeted therapies: Genentech’s GDC-0032 (a PI3 kinase inhibitor), Pfizer’s palbociclib (an oral cyclin-dependent-kinase 4/6 inhibitor, AZD4547), an oral fibroblast growth factor receptor inhibitor from AstraZeneca, and rilotumumab, Amgen’s antibody against the human hepatocyte growth factor.

The fifth agent is, MEDI4736, an immune checkpoint inhibitor antibody targeting PD-L1. Patients whose tumors do not harbor a mutation suitable for targeting with one of the four targeted therapies will be enrolled in the MED4736 sub-study.

Once a patient is matched to a specific trial sub-study, randomization will determine whether the patient receives the experimental therapy or standard of care chemotherapy. The planned trial endpoints for each sub-study are overall survival and progression-free survival.

“I cannot overemphasize the importance of the FDA’s participation in this project, since each of these sub-studies is designed to result in approval of a paired biomarker and new drug if that sub-study meets the requirements for improved effectiveness,” said Gandara.

– See more at: http://www.oncotherapynetwork.com/lung-cancer-targets/large-collaborative-lung-cancer-trial-goes-precision-medicine-goal

The BATTLE Trial: Personalizing Therapy for Lung Cancer

Kim, RS. Herbst, II. Wistuba, JJ Lee, GR. Blumenschein Jr., A Tsao, DJ. Stewart, et al.

Authors’ Affiliations: 1Departments of Thoracic/Head and Neck Medical Oncology, 2Pathology, 3Biostatistics, and 4Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Texas; 5Winship Cancer Center, Emory University, Atlanta, Georgia; 6Dana-Farber Cancer Institute, Boston, Massachusetts; and 7University of Maryland, Baltimore, Maryland.

Corresponding Author:

Waun K. Hong, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030. Phone: 713-794-1441; Fax: 1-713-792-4654; E-mail:whong@mdanderson.org

The Biomarker-integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial represents the first completed prospective, biopsy-mandated, biomarker-based, adaptively randomized study in 255 pretreated lung cancer patients. Following an initial equal randomization period, chemorefractory non–small cell lung cancer (NSCLC) patients were adaptively randomized to erlotinib, vandetanib, erlotinib plus bexarotene, or sorafenib, based on relevant molecular biomarkers analyzed in fresh core needle biopsy specimens. Overall results include a 46% 8-week disease control rate (primary end point), confirm prespecified hypotheses, and show an impressive benefit from sorafenib among mutant-KRAS patients. BATTLE establishes the feasibility of a new paradigm for a personalized approach to lung cancer clinical trials.

(ClinicalTrials.gov numbers:NCT00409968, NCT00411671, NCT00411632, NCT00410059, and   NCT00410189.

Significance: The BATTLE study is the first completed prospective, adaptively randomized study in heavily pretreated NSCLC patients that mandated tumor profiling with “real-time” biopsies, taking a substantial step toward realizing personalized lung cancer therapy by integrating real-time molecular laboratory findings in delineating specific patient populations for individualized treatment. Cancer Discovery; 1(1); 44–53. © 2011 AACR.

Read the Commentary on this article by Sequist et al., p. 14
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Pharmacometabolomics in Drug Discovery & Development: Applications and Challenges

Yang and F. Marotta
Metabolomics 2012, 2:5 http://dx.doi.org/10.4172/2153-0769.1000e122

Recently, the concept of pharmaco-metabolomics is mentioned more frequently as an emerging discipline to study the effect of drugs on the whole pattern of small endogenous molecules and in applying the profiles of metabolomics for drug development. For the latter part, metabolomics is majorly used to differentiate patients into responder or non-responder groups in an effort to decrease large inter-individual variation in clinical trials. It is a novel approach that combines metabolite profile and chemo-metrics to model and predict drug targets, efficacy, pharmacokinetics and toxicity on both individual and population basis. It attracts many scientists’ attention because of its intrinsic advantages and promising potentials in drug discovery and development. Considering personalized drug treatment is the desired goal for current drug development, pharmaco-metabolomics provide an effective and inexpensive strategy to evaluate drug efficacy and toxicology, which may make personalized medicine realistic both from scientific and financial perspectives. Furthermore, the FDA also realized that metabolomics coupling with other “Omics” approaches could be a valuable tool in evaluating general toxicology and could eventually replace the use of animals after addressing certain challenges.

Networking metabolites and diseases

Pascal Braun, Edward Rietman, and Marc Vidal
PNAS  July 22, 2008; 105(29): 9849–9850

Diseasome and Drug-Target Network

Recently, Goh et al. constructed a ‘‘diseasome’’ network in which two diseases are linked to each other if they share at least one gene, in which mutations are associated with both diseases. In the resulting network, related disease families cluster tightly together, thus phenotypically defining functional modules. Importantly, for the first time this study applied concepts from network biology to human diseases, thus opening the door for discovering causal relationships between  disregulated networks and resulting ailments.

Subsequently Yilderim et al. linked drugs to protein targets in a drug–target network, which could then be overlaid with the diseasome network. One notable finding was the recent trend toward the development of new compounds directly targeted at disease gene products, whereas previous drugs, often found by trial and error, appear to target proteins only indirectly related to the actual disease molecular mechanisms. An important question that remains in this emerging field of network analysis consists of investigating the extent to which directly targeting the product of mutated genes is an efficient approach or whether targeting network properties instead, and thereby accounting for indirect nonlinear effects of system perturbations by drugs, may prove more fruitful. However, to answer such questions it is important to have a good understanding of the various influences that can lead to diseases.

UPDATED 6/01/2019

Combined hereditary and somatic mutations of replication error repair genes result in rapid onset of ultra-hypermutated cancers

from  2015 Mar;47(3):257-62. doi: 10.1038/ng.3202. Epub 2015 Feb 2.

Shlien A1Campbell BB2de Borja R3Alexandrov LB4Merico D5Wedge D4Van Loo P6Tarpey PS4Coupland P7Behjati S4Pollett A8Lipman T9Heidari A9Deshmukh S9Avitzur N9Meier B10Gerstung M4Hong Y10Merino DM3Ramakrishna M4Remke M11Arnold R3Panigrahi GB3Thakkar NP12Hodel KP13Henninger EE13Göksenin AY13Bakry D14Charames GS15Druker H16Lerner-Ellis J17Mistry M2Dvir R18Grant R14Elhasid R18Farah R19Taylor GP20Nathan PC14Alexander S14Ben-Shachar S21Ling SC22Gallinger S23Constantini S24Dirks P25Huang A26Scherer SW27Grundy RG28Durno C29Aronson M30Gartner A10Meyn MS31Taylor MD25Pursell ZF13Pearson CE12Malkin D32Futreal PA4Stratton MR4Bouffet E26Hawkins C33Campbell PJ34Tabori U35Biallelic Mismatch Repair Deficiency Consortium.

Abstract: DNA replication-associated mutations are repaired by two components: polymerase proofreading and mismatch repair. The mutation/consequences of disruption to both repair components in humans are not well studied. We sequenced cancer genomes from children with inherited biallelic mismatch repair deficiency (bMMRD). High-grade bMMRD brain tumors exhibited massive numbers of substitution mutations (>250/Mb), which was greater than all childhood and most cancers (>7,000 analyzed). All ultra-hypermutated bMMRD cancers acquired early somatic driver mutations in DNA polymerase ɛ or δ. The ensuing mutation signatures and numbers are unique and diagnostic of childhood germ-line bMMRD (P < 10(-13)). Sequential tumor biopsy analysis revealed that bMMRD/polymerase-mutant cancers rapidly amass an excess of simultaneous mutations (∼600 mutations/cell division), reaching but not exceeding ∼20,000 exonic mutations in <6 months. This implies a threshold compatible with cancer-cell survival. We suggest a new mechanism of cancer progression in which mutations develop in a rapid burst after ablation of replication repair.

Genetic changes which occur in spontaneous arising somatic cancers include point mutations, copy number alterations and rearrangements and in general result from a defective DNA repair mechanisms during proliferation/replication over many years however as most somatic cancers are heterogeneous it is difficult to pinpoint the exact repair defects which may be ultimately responsible for such genetic aberrations.

However, early-onset cancers (e.g. pediatric cancers) in patients with hereditary DNA repair defects offer a good view of the mutation types and secondary pathways that drive oncogenesis. bMMRD is a childhood cancer syndrome characterized by early-onset cancers in various organs and caused by biallelic mutations.  In this study, genomes from 17 inherited cancers, by exomic sequencing and microarrays, were analyzed and compared to non-neoplastic tissue genomes from matched patients.  Brain cancers from these patients had an extremely high number of point mutations compared to other childhood cancers and adult cancers.

Mismatch repair was defective in all these cancers therefore it appeared that secondary mutations are required to cause the ultrahypermutated state.  The most frequently mutated gene was POLE (polymerase epsilon), affecting the proofreading ability of this DNA polymerase.  The genomes of tumors with mutant POLE had signature mutational spectrum and the signature occurred early but these signatures had been found in endometrial and colorectal cancers.  The authors concluded, based on serial analysis of other brain cancers with bMMRD and the observation that recurrent brain cancers accumulated mutations over a relatively short period, once the proofreading capability of pol epsilon is compromised in MMR deficient cells there is no defense against rapid and catastrophic accumulations of mutations.  This rapid accumulation of mutations apparently do not lead to apoptosis but rather rapid tumor initiation, and generating multiple subclones of tumor cells.

UPDATED 9/26/2021

Metabolic Profiling Reveals a Dependency of Human Metastatic Breast Cancer on Mitochondrial Serine and One-Carbon Unit Metabolism

Source: https://pubmed.ncbi.nlm.nih.gov/31941752/

Abstract

Breast cancer is the most common cancer among American women and a major cause of mortality. To identify metabolic pathways as potential targets to treat metastatic breast cancer, we performed metabolomics profiling on the breast cancer cell line MDA-MB-231 and its tissue-tropic metastatic subclones. Here, we report that these subclones with increased metastatic potential display an altered metabolic profile compared with the parental population. In particular, the mitochondrial serine and one-carbon (1C) unit pathway is upregulated in metastatic subclones. Mechanistically, the mitochondrial serine and 1C unit pathway drives the faster proliferation of subclones through enhanced de novo purine biosynthesis. Inhibition of the first rate-limiting enzyme of the mitochondrial serine and 1C unit pathway, serine hydroxymethyltransferase (SHMT2), potently suppresses proliferation of metastatic subclones in culture and impairs growth of lung metastatic subclones at both primary and metastatic sites in mice. Some human breast cancers exhibit a significant association between the expression of genes in the mitochondrial serine and 1C unit pathway with disease outcome and higher expression of SHMT2 in metastatic tumor tissue compared with primary tumors. In addition to breast cancer, a few other cancer types, such as adrenocortical carcinoma and kidney chromophobe cell carcinoma, also display increased SHMT2 expression during disease progression. Together, these results suggest that mitochondrial serine and 1C unit metabolism plays an important role in promoting cancer progression, particularly in late-stage cancer. IMPLICATIONS: This study identifies mitochondrial serine and 1C unit metabolism as an important pathway during the progression of a subset of human breast cancers.

ntroduction

The majority of breast cancer patients die from metastatic disease. The process of cancer metastasis involves local invasion into surrounding tissue, dissemination into the bloodstream, extravasation, and eventual colonization of a new tissue. Following a period of dormancy, small numbers of micrometastases eventually proliferate into large macrometastases, or secondary tumors.

Previous studies have illuminated several themes of metabolic reprogramming that occur during metastasis (). However, the majority of these reported site-specific metabolic features of metastatic cancer cells. We reason that breast cancer cells that leave the primary tumor and successfully establish new lesions at distal sites would encounter similar metabolic stresses during metastasis. By performing comparative metabolomics on the MDA-MB-231 human breast cancer cell line and its tissue-tropic metastatic subclones, we uncovered that the catabolism of the non-essential amino acid serine through the mitochondrial one-carbon (1C) unit pathway is an important driver of proliferation in a subset of metastatic breast cancers that closely resembles the molecular features of MDA-MB-231 cells. Emerging evidence shows that the non-essential amino acid serine is essential for cancer cell survival and proliferation. The genomic regions containing PHGDH are amplified in breast cancer and melanoma, diverting 3PG to serine synthesis (,). We also reported that PHGDH is upregulated upon amino acid starvation by the transcription factor ATF4 (). On one hand, serine serves as a precursor for the synthesis of protein, lipids, nucleotides and other amino acids, which are necessary for cell division and growth. On the other hand, serine catabolism through the mitochondrial 1C unit pathway is critical for maintaining cellular redox control under stress conditions (,). In mitochondria, serine catabolism is initiated by serine hydroxymethyltransferase 2 (SHMT2). SHMT2 catalyzes a reversible reaction converting serine to glycine, with concurrent generation of the 1C unit donor methylene-THF, which is further oxidized by downstream enzymes MTHFD2 and MTHFD1L to produce NAD(P)H and formate. Subsequent export of formate from the mitochondria can then be re-assimilated into the cytosolic folate pool to support anabolic reactions. All three mitochondrial serine and 1C unit pathway enzymes (SHMT2, MTHFD2 and MTHFD1L) are upregulated in breast tumor samples compared to normal tissues (,). However, due to lack of functional investigations targeting this pathway in in vitro and in vivo breast cancer models, it remains unclear whether the mitochondrial 1C unit pathway represents a good target for treating metastatic breast cancer.

In this study, we report that enzymes in the mitochondrial serine and 1C unit pathway are even further upregulated specifically in subclones of the aggressive breast cancer cell line MDA-MB-231 that have been selected in vivo for the ability to preferentially metastasize to specific organs. We demonstrate that SHMT2 inhibition suppresses proliferation more strongly in these highly metastatic subclones compared to the parental population in vitro. Knockdown of SHMT2 also impairs breast cancer growth in vivo at both the primary and metastatic sites. In addition, we find that the expression of mitochondrial 1C unit pathway enzymes significantly associates with poor disease outcome in a subset of human breast cancer patients, potentiating its role as a therapeutic target or biomarker in advanced cancer. Finally, SHMT2 expression increases in breast invasive carcinoma, adrenocortical carcinoma, chromophobe renal cell carcinoma and papillary renal cell carcinoma during tumor progression, particularly in late stage tumors, suggesting that inhibitors targeting SHMT2 may hold promise for treating these late stage cancers when other therapeutic options become limited.

Materials and Methods

Cell lines

All of the paired parental and metastatic subclones were generated in Dr. Joan Massagué’s laboratory (Memorial Sloan-Kettering Cancer Center) (). Cells were cultured in DMEM/F12 with 10% fetal bovine serum (Sigma) with 1% penicillin/streptomycin. All cells lines were tested every three to six months and found negative for mycoplasma (MycoAlert Mycoplasma Detection Kit; Lonza). These cell lines were not authenticated by the authors. All cell lines used in experiments were passaged no more than ten times from time of thawing.

RNAi

Stable 831-BrM,1833-BoM, and 4175-LM cell lines expressing shRNA against SHMT2, MTHFD2, and c-Myc were generated through infection with lentivirus and 1 μg/mL puromycin selection. shRNA-expressing virus was obtained using a previously published method (). Pooled populations were tested for on-target knockdown by immunoblot.

Immunoblot

The following antibodies were used: SHMT1, SHMT2 (Sigma), MTHFD2, MTHFD1L, c-Myc, Actin (Cell Signaling Technologies).

RNA Isolation, Reverse Transcription, and Real-Time PCR

Total RNA was isolated from tissue culture plates according to the TRIzol Reagant (Invitrogen) protocol. 3 μg of total RNA was used in the reverse transcription reaction using the SuperScript III (Invitrogen) protocol. Quantitative PCR amplification was performed on the Prism 7900 Sequence Detection System (Applied Biosystems) using Taqman Gene Expression Assays (Applied Biosystems). Gene expression data were normalized to 18S rRNA.

In vivo Tumor Growth Assays

All procedures involving animals and their care were approved by the Institutional Animal Care and Use Committee of Stanford University in accordance with institutional and National Institutes of Health guidelines. For orthotopic growth studies, 4175-LM shNT and 4175-LM shSHMT2 cells (1 × 106 cells in 0.1 mL of PBS, n = 8 per group) were injected into the flanks of NU/J 10-week-old female mice (The Jackson Laboratory). Tumors were measured with calipers over a 50-day time course. Volumes were calculated using the formula width2 × length × 0.5.

For lung metastasis assays, 4175-LM shNT and 4175-LM shSHMT2 cells (0.2 × 105 cells, n = 8 per group) were injected via tail vein into 6–8 week-old female NOD SCID mice. Mice were imaged weekly using the Xenogen IVIS 200 (PerkinElmer, Waltham, MA). Briefly, mice were injected intraperitoneally with 100 μg/g of D-luciferin (potassium salt; PerkinElmer) on the day of imaging. 8 min later, mice were anesthetized in an anesthesia-induction chamber using a mixture of 3% isoflurane (Fluriso, VetOne) in O2. Anesthesia was maintained with a mixture of 2% isoflurane in O2 inside the imaging chamber. Using Living Image (PerkinElmer, Waltham, MA), images were acquired (Exposure time, auto; F stop. 1.2; Binning, medium) from both dorsal and ventral sides of mice and a total photon flux (p/sec/cm2/sr) per animal was calculated by averaging the signal acquired from the dorsal and ventral side. After 4 weeks, surviving mice were sacrificed and lungs snap frozen in liquid N2 prior to homogenization in TRIzol for RNA extraction.

Metabolite Profiling and Mass Spectrometry

For total metabolite analysis, parental and metastatic cell lines were seeded in 60mm culture dishes in DMEM/F12 supplemented with 10% dialyzed fetal bovine serum. Media was refreshed 2 hours prior to harvesting by washing 3x with PBS before quenching with 800mL of −80 C 80:20 methanol:water. Extracts were spun down, supernatants collected, dried and resuspended in water before LC-MS analysis. Samples were analyzed by reversed-phase ion-pairing chromatography coupled with negative-mode electrospray-ionization high-resolution MS on a stand-alone ThermoElectron Exactive orbitrap mass spectrometer (). Peak picking and quantification were conducted using MAVEN analysis software. Heatmap was generated in R. Multiple testing correction and q-value generation were performed in PRISM software (GraphPad).

For [2,3,3-2H]serine labeling experiments, parental and metastatic cells were cultured in RPMI medium lacking glucose, serine, and glycine (TEKnova) supplemented with 2 g/L glucose and 0.03 g/L [2,3,3-2H]serine (Cambridge Isotope Laboratories) for up to 24 hours before harvesting. Cells were washed twice with ice-cold PBS prior to extraction with 400 μL of 80:20 acetonitrile:water over ice for 15 min. Cells were scraped off plates to be collected with supernatants, sonicated for 30s, then spun down at 1.5 × 104 RPM for 10 min. 200 μL of supernatant was taken out for LC-MS/MS analysis immediately.

Quantitative LC-ESI-MS/MS analysis of [2,3,3-2H]serine-labeled cell extracts was performed using an Agilent 1290 UHPLC system equipped with an Agilent 6545 Q-TOF mass spectrometer (Santa Clara, CA, US). A hydrophilic interaction chromatography method (HILIC) with an BEH amide column (100 × 2.1 mm i.d., 1.7 μm; Waters) was used for compound separation at 35 °C with a flow rate of 0.3ml/min. The mobile phase A consisted of 25 mM ammonium acetate and 25mM ammonium hydroxide in water and mobile phase B was acetonitrile. The gradient elution was 0–1 min, 85 % B; 1–12 min, 85 % B → 65 % B; 12– 12.2 min, 65 % B-40%B; 12.2–15 min, 40%B. After the gradient, the column was re-equilibrated at 85%B for 5min. The overall runtime was 20 min and the injection volume was 5 μL. Agilent Q-TOF was operated in negative mode and the relevant parameters were as listed: ion spray voltage, 3500 V; nozzle voltage, 1000 V; fragmentor voltage, 125 V; drying gas flow, 11 L/min; capillary temperature, 325 °C, drying gas temperature, 350 °C; and nebulizer pressure, 40 psi. A full scan range was set at 50 to 1600 (m/z). The reference masses were 119.0363 and 980.0164. The acquisition rate was 2 spectra/s. Isotopologues extraction was performed in Agilent Profinder B.08.00 (Agilent Technologies). Retention time (RT) of each metabolite was determined by authentic standards (Supplementary Table S1). The mass tolerance was set to +/−15 ppm and RT tolerance was +/− 0.2 min. Natural isotope abundance was corrected using Agilent Profinder software (Agilent Technologies).

Cell Line Classification

Cell line expression and copy number data were downloaded from the COSMIC cell line dataset (https://cancer.sanger.ac.uk/cell_lines), and all cell lines were classified using different cell line classifiers, including PAM50 and scmod2 using the package genefu from Bioconductor; and iC10 using package iC10 (). The MDA-MB-231 parental and metastatic subclones were classified as Basal (posterior probability of 0.516), ER-Her2- (posterior probability of 0.997), IC4 (posterior probability of 0.999).

Outcome Analysis

METABRIC clinical and expression data was downloaded from EGA (EGAS00000000083) (). Outcome analysis was performed in IC4 samples only (N=342) in order to mimic the phenotype of the MDA-MB-231 breast cancer cell line. Survival analysis was performed over disease specific survival (DSS) censored to 20 years. Gene high/low categorization was performed using the maxstat algorithm, which determines the optimal threshold for separating high and low expression (from the surv cutpoint function of package survminer). Cox Proportional Hazard multivariate models use continuous expression adjusted by age, grade, size, number of lymph nodes, ER, PR and Her2 status. Kaplan-Meier plots were generated using the package survcomp, and Cox Proportional Hazards were generated using the package rms.

Immunohistochemical Staining and Quantification for SHMT2

Human primary breast cancer tissue and paired lymph node metastases were obtained from Biomax.us. Tumors were graded by Biomax.us pathologists according to the Nottingham grading system with respect to degree of glandular duct formation, nuclear pleomorphism, and nuclear fission counting. Each feature was scored from 1–3, and the total score was used to determine the following grades: Grade 1 (total score 3–5; low grade or well differentiated), Grade 2 (total score 6–7; intermediate grade or moderately differentiated), Grade 3 (total score 8–9; high grade or poorly differentiated). Standard immunohistochemical methods were performed as previously described (). The primary anti-human SHMT2 antibody (Sigma) was used at a concentration of 1:3000. Images were acquired on a Leica DMi8 system (Leica Microsystems) and quantified for positive SHMT2 signal intensity by ImageJ software.

SHMT2 Expression Analysis by Individual Cancer Stage

SHMT2 expression data across every annotated TCGA cancer data set was queried and downloaded from the UALCAN database (http://ualcan.path.uab.edu/index.html) ().

Statistical Analyses

All statistical tests were performed using the paired or unpaired Student’s t test by PRISM software. Values with a p value of < 0.05 were considered significant.

Results

Metastatic breast cancer cells exhibit altered metabolic profiles

To identify common metabolic pathways reprogrammed in metastatic breast cancer cells during cancer progression, we performed metabolomic profiling of the human triple negative breast cancer cell line MDA-MB-231 and its metastatic subpopulations (Fig. 1A and andB).B). This cell line was derived from the pleural effusion of a patient with widespread metastatic disease years after primary tumor removal (), and the subclones of this cell line with higher metastasis rate and preference to the bone, lung, or brain were previously isolated by in vivo selection () (831-BrM: brain metastasis. 1833-BoM: bone metastasis. 4175-LM: lung metastasis).

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Metastatic breast cancer subclones display an altered metabolic profile. (A) Schematic of targeted metabolomics workflow. Brain (831-BrM), bone (1833-BoM), and lung (4175-LM) metastatic subclones from tissue-tropic subpopulations were generated following IV injection of a parental population of MDA-MB-231 (231-Parental) cells into the tail vein or heart. Stable cell lines were passaged in culture prior to metabolite extraction for LC-MS/MS. (B) LC-MS profile of the 231-Parental, 831-BrM, and 1833-BoM cell lines. Cell lines were plated in biological triplicates prior to metabolite extraction. Signals were normalized to the mean signal of each metabolite across all samples, log2 transformed, and clustered.

At the time of initial metabolomics comparison, the lung metastatic subclone 4175-LM did not recover well in culture, so we profiled the 831-BrM and 1833-BoM metastatic subclones along with the parental population. We observed multiple metabolites involved in a plethora of metabolic pathways that were differentially enriched or depleted in the metastatic 831-BrM and 1833-BoM subclones compared to the parental population of MDA-MB-231 (231-Parental) cells (Fig. 1B). Following correction for false discovery rate, the levels of twenty-four metabolites were significantly altered in both 831-BrM and 1833-BoM cells compared to 231-Parental cells (Supplementary Table S2). Metabolites significantly enriched in metastatic subclones included the glycolytic intermediate dihydroxyacetone-phosphate (which is reversibly isomerized to glyceraldehyde-3-phosphate), the tricarboxylic acid (TCA) cycle intermediate succinate, amino acids such as proline and asparagine, and the pentose-phosphate pathway product 5-phosphoribosyl-1-pyrophosphate. These observations are consistent with prior observations of perturbations in lower glycolysis and the TCA cycle observed in other cell line models (notably murine 4T1 cells), suggesting common metabolic developments during metastasis of breast cancers in both mice and humans (,,). Additionally, enrichment of asparagine has been reported to promote metastatic cancer cell phenotypes by epithelial-to-mesenchymal transition (). Nonetheless, the most significantly depleted class of metabolites in 831-BrM and 1833-BoM cells compared to 231-Parental cells were free purine nucleotides, suggesting alterations in purine metabolism in metastatic cells (Fig. 1B).

c-Myc is important for breast cancer cell proliferation

We wondered whether reduced levels of purines reflected decreased synthesis or higher consumption in the metastatic subclones. Because it was previously reported that the oncogenic transcription factor c-Myc induces the expression of nucleotide biosynthesis genes and that c-Myc amplification and overexpression is a common event in triple-negative breast cancer (), we wondered if the relative differences in purine abundance could be explained by altered c-Myc protein levels in our cell line system. Indeed, 831-BrM, 1833-BoM, and 4175-LM cells overexpressed c-Myc compared to 231-Parental cells (Fig. 2A). Since sufficiency of free nucleotides can act as an important checkpoint for cell division (), we then compared the proliferation rates of parental and metastatic subclones. Accordingly, 831-BrM, 1833-BoM, and 4175-LM cells proliferated faster than 231-Parental cells in vitro (Fig. 2B), suggesting that the higher consumption rate is the cause of lower purine levels in the metastatic subclones.

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c-Myc drives proliferation in metastatic breast cancer cell subclones. (A) IB for c-Myc from whole-cell extracts of parental and metastatic subclones. (B) Proliferation of parental cells and metastatic subclones over 3 days (mean ± SD, n = 3). (C) 3 day proliferation of 231-Parental, 831-BrM, 1833-BoM, and 4175-LM cells expressing either a nontargeting (shNT) or c-Myc targeting (shMyc) vectors. (mean ± SD, n = 3).

Because the role of c-Myc in metastasis is still unclear, with evidence suggesting it plays both pro-metastatic and anti-metastatic functions in breast cancer depending on the genetic context (,), we tested the sensitivity of parental and metastatic subclones to c-Myc inhibition. Small hairpin RNA (shRNA)–mediated knockdown of c-Myc reduced cell proliferation in all four cell lines, although the degree of inhibition was stronger in 831-BrM and 1833-BoM cells (Fig. 2CSupplementary Fig. S1). Parental cells expressing a non-targeting shRNA showed elevated c-Myc expression, possibly due to puromycin selection. These data suggest that c-Myc is an important mediator of cell proliferation, and c-Myc overexpression provided a proliferative advantage at least in brain and bone-metastatic subclones.

Identification of serine and one-carbon unit pathway elevation in metastatic subclones

The products of several metabolic pathways feed into nucleotide synthesis, including ribulose-5-phosphate from the pentose phosphate pathway, and one-carbon (1C) units and glycine from the serine and 1C unit pathway. It is also known that c-Myc can promote the expression of serine and glycine metabolism genes in cancer cells (,). We performed expression analyses of the metastatic subclones and found elevated levels of the key mitochondrial enzymes serine hydroxymethyltransferase 2 (SHMT2), methylenetetrahydrofolate dehydrogenase 2 (MTHFD2), and methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L), in contrast to the downregulated expression of the cytosolic isoenzyme serine hydroxymethyltransferase 1 (SHMT1) (Fig. 3AC). Consistent with previous reports in other cell types, knockdown of c-Myc in parental and metastatic breast cancer subclones diminished MTHFD2 and MTHFD1L protein expression, suggesting these enzymes are c-Myc-regulated (Supplementary Fig. S1). SHMT2 expression did not reduce upon c-Myc knockdown, suggesting that SHMT2 expression was regulated by other transcription factors. To determine whether c-Myc and mitochondrial 1C unit pathway enzyme overexpression was a common co-occurrence in other cancer metastasis models, we checked protein expression levels in the parental and metastatic subpopulations of other human cell line systems derived from lung adenocarcinoma or ER+ breast carcinoma patients (,). There was a clear correlation of SHMT2, MTHFD2, and MTHFD1L expression with c-Myc expression among all the cell lines tested. The brain metastatic subclones of lung adnocacinoma cell lines PC9 and H2030 had increased MTHFD2 expression, though we could not find another system that also displayed overexpression of c-Myc and all the three mitochondrial 1C unit pathway enzymes in metastatic subclones relative to their corresponding parental cells (Supplementary Fig. S2). Taken together with the observations of higher serine and glycine levels in 831-BrM and 1833-BoM cells compared to 231-Parental cells (Fig. 1B), these data suggest that the role of c-Myc in regulating mitochondrial serine and 1C unit metabolism in metastatic cancer may be tissue-specific.

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The mitochondrial serine and one-carbon unit pathway is upregulated in metastatic breast cancer subclones. (A) Schematic of the cytosolic and mitochondrial serine and one-carbon unit pathway. (B) qPCR for serine and one-carbon unit pathway genes (mean ± SD, n = 3, *P < 0.05 **P < 0.01 ***P < 0.001 ****P < 0.0001 by two-tailed Student’s t test, compared to expression in parental cells). (C) IB for serine and one-carbon unit pathway enzymes from whole-cell extracts of parental cells and metastatic subclones. (D) Schematic diagram of incorporation of 2H (D) from [2,3,3-2H]serine onto glycine, one-carbon units, and purines. (E) SHMT flux estimated by relative abundance of labeled glycine from serine (mean ± SD, n = 3, **P < 0.01 by two-tailed Student’s t test). (F) Fractional labeling of [2,3,3-2H]serine onto GTP and ATP (mean ± SD, n = 3, *P < 0.05 **P < 0.01 ***P < 0.001 by two-tailed Student’s t test).

Metastatic subclones display increased mitochondrial serine and one-carbon unit pathway activity

We next asked if higher expression of mitochondrial serine and 1C unit pathway enzymes might indeed reflect higher pathway activity. Serine can be catabolized in both the mitochondrial and cytosolic branch of the 1C unit pathway. Since cancer cells predominately express the mitochondrial serine catabolic enzymes over the cytosolic enzymes, serine is generally catabolized in the mitochondria in cancer cells (,,). Serine hydroxyl-methyltransferase 2 (SHMT2) initiates this reaction by converting serine to glycine while donating a carbon group to tetrahydrafolate (THF) to generate methylene-THF. Subsequent oxidation of methylene-THF by MTHFD2 and MTHFD1L generates NAD(P)H and formate. Formate can cross the mitochondrial membrane to provide 1C units for anabolic reactions such as nucleotide synthesis ().

We hypothesized that the reason metastatic cells upregulate the serine and 1C unit pathway is to enhance nucleotide synthesis to fuel cell proliferation. Indeed, most cancer cells have been reported to utilize serine as the predominant source of 1C units for biosynthesis (). We performed [2,3,3-2H]serine tracing to examine 1C unit pathway flux to glycine and purine nucleotides. In cells grown in media containing [2,3,3-2H]serine, the cytosolic pathway generates methylene-THF (me-THF) mass heavy by 2 (M+2) and 10-formyl-THF mass heavy by 1 (M+1), while 10-formyl-THF derived from mitochondrial formate exchange to the cytosol is strictly M+1. [2,3,3-2H]serine labeling onto the metabolites glycine and purine nucleotide triphosphates produced from the mitochondrial pathway thereby produces glycine M+1 and purines either M+1 or M+2 (Fig. 3D). Time course experiments were performed in 4175-LM cells to determine the optimal steady state labeling conditions for glycine and ATP from serine: 2 hours and 24 hours respectively (Supplementary Fig. S3). We observed higher SHMT flux in metastatic subclones, as the relative abundance of M+1 glycine was approximately 1.5-fold higher in 4175-LM cells compared to 231-Parental cells, indicating that higher purine turnover in metastatic cells was fueled by higher SHMT flux (Fig. 3E). Importantly, while robust fractions of ATP and GTP were labeled in parental cells, the metastatic subclones displayed even higher labeling fractions from serine (Fig. 3F). These results demonstrate that upregulation of serine catabolism through the mitochondrial 1C unit pathway promotes de novo purine synthesis in metastatic breast cancer cells.

Serine catabolism is necessary for metastatic cancer cell proliferation in vitro

To address the extent to which mitochondrial serine catabolism is necessary for cell proliferation, 231-Parental, 831-BrM, 1833-BoM, and 4175-LM cells were infected with lentivirus expressing shRNAs against SHMT2 (shSHMT2) or a nontargeting control (shNT). Intriguingly, knockdown of SHMT2 protein expression with two different shRNAs drastically suppressed proliferation of the metastatic subclones significantly, with a reduced effect in 231-Parental cells (Fig. 4A and andB).B). In contrast, knockdown of the downstream enzyme of the mitochondrial serine and 1C unit pathway, MTHFD2, suppressed proliferation to a lesser extent (Supplementary Fig. S4A and B). To evaluate the therapeutic potential of targeting 1C unit metabolism to block metastatic growth, we treated cells with a small-molecule inhibitor of SHMT called SHIN1 (). In vitro, metastatic subclones were sensitive to SHIN1 with an EC50 in the 100–500 nM range (Supplementary Fig. S5). There was no obvious enhancement of SHIN1 sensitivity in 831-BrM, 1833-BoM, and 4175-LM cells compared to 231-Parental cells, possibly because SHIN1 inhibits both SHMT2 and SHMT1 (Fig. 4C). Importantly, inhibition of cell proliferation in the presence of SHIN1 could be rescued by the supplementation of formate (2 mM), a source of cellular 1C units (Fig. 4C). These results indicate that the major role of elevated mitochondrial serine catabolism is to generate 1C units for cytosolic purine biosynthesis in the metastatic subclones. Thus, targeting SHMT activity may be a promising way to restrict nucleotide availability to block metastatic breast cancer cell proliferation.

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Metastatic subclones are particularly sensitive to SHMT2 inhibition. (A) 3 day proliferation of 231-Parental, 831-BrM,1833-BoM, and 4175-LM cells expressing either a nontargeting (shNT) or SHMT2 targeting (shSHMT2) vectors. Relative proliferation was calculated relative to average proliferation of shNT cells (mean ± SD, n = 3). (B) IB for SHMT2 in parental and metastatic subclones. (C) 3 day proliferation of parental and metastatic cells with 2 μM SHIN1, in RPMI with or without 2 mM formate and dialyzed FBS (mean ± SD, n = 3, ***P < 0.001 ****P < 0.0001 by two-tailed Student’s t test). Counts were normalized to the proliferation of 231-Parental cells in media without SHIN1 and formate treatment. (D) Growth of 4175-LM shNT and shSHMT2 tumors in the mammary fat pad of nude mice (mean ± SEM, n = 8, **P < 0.01 by two-tailed Student’s t test). (E) Quantification of luminescence signal in the lungs of mice 3 weeks post injection of either 4175-LM shNT or shSHMT2 cells (mean ± SEM, **P < 0.01 by two-tailed Student’s t test, shNT;n = 8 shSHMT2;n = 7). (F) qPCR analysis of hGAPDH expression in the lungs of mice 4 weeks post injection of either 4175-LM shNT or shSHMT2 cells (mean ± SEM, *P < 0.05 by two-tailed Student’s t test, shNT;n = 6 shSHMT2;n = 7).

SHMT2 knockdown impairs primary and metastatic growth in vivo

We then interrogated the effect of reducing mitochondrial 1C unit pathway activity in two different models of cancer growth in vivo. 4175-LM cells were chosen due to the relative ease of monitoring, measuring, and collecting tissue from lung metastasis compared to brain and bone metastasis. For the first model, we monitored breast cancer growth at the primary tumor site. SHMT2 knockdown significantly impaired the growth of 4175-LM cells in the mammary fat pads of immunodeficient mice (Fig. 4DSupplementary Fig. S6). For the second model, we induced breast cancer metastasis to the lung by intravenous tail vein injection. Because 4175-LM cells express firefly luciferase (), we tracked tumor growth in the lung by bioluminescence imaging (BLI). Both BLI and quantification of human GAPDH (hGAPDH) expression from resected mouse lungs revealed a roughly two-fold reduction of lung tumor burden in mice injected with shSHMT2 cells compared to shNT cells (Fig. 4E and andF,FSupplementary Fig. S7A). While on average, shSHMT2 tumors had reduced human SHMT2 (hSHMT2) expression compared to shNT tumors, some shSHMT2 tumors appeared to have reacquired hSHMT2 expression (Supplementary Fig. S7B and C). These data suggest that SHMT2 is necessary for metastatic growth in vivo.

Mitochondrial serine and 1C unit pathway genes are associated with more aggressive metastatic disease in some human breast cancer patients

To further explore the relevancy of mitochondrial one-carbon unit metabolism in human breast cancer metastasis, we examined the expression of SHMT1, SHMT2, MTHFD2, and MTHFD1L in the METABRIC dataset of human breast cancer patients (). We retrospectively inferred metastatic recurrence in patients by examining the frequency of disease-specific survival (DSS) up to 20 years. Patients were separated into two groups based on the maxstat algorithm (see Materials and Methods). Patients with high SHMT2 expression were significantly more likely to succumb to metastatic recurrent disease, while patients with high expression of the cytosolic isozyme SHMT1 were significantly protected from metastatic relapse (Fig. 5ASupplementary Fig. S8). Using three different breast cancer subtype clustering analyses based on gene expression (PAM50, IC10, SCMOD2), we classified the MDA-MB-231 cell line as basal, IC4 (copy number flat), and ERHer2 (,). We have previously described IC4 as consisting of a mixture of ER tumors with lymphocytic infiltration and ER+ tumors with abundant stroma. Accordingly, further analysis of the IC4 patient subgroup following adjustment for covariates of age, grade, size, number of lymph nodes, ER, PR and Her2 status revealed a significant association of MTHFD1, MTHFD1L, MTHFD2, and SHMT2 expression with worse survival and SHMT1 expression with better survival (Fig. 5B). Finally, we stained a tissue microarray panel of human breast invasive ductal carcinoma and matched lymph node metastases and found significantly higher expression of SHMT2 in metastatic cancer cells comparing to the primary tumors (Fig. 5C and andD).D). Together, these data suggest that SHMT2 and other mitochondrial 1C unit pathway enzymes may be used as prognostic markers that indicate worse patient outcome, while cytosolic SHMT1 expression may indicate better survival rate in the IC4 patient subgroup.

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Mitochondrial serine and one-carbon unit pathway enzyme expression correlates with poor survival in human breast cancer. (A) Kaplan-Meier plot for SHMT1 (left) and SHMT2 (right) expression associated with disease-specific survival (DSS) in the human IC4 patient subgroup (METABRIC). (B) Forest plot for the hazard of individual 1C unit pathway genes adjusted for covariates (age, grade, size, number of lymph nodes, ER, PR and Her2 status) in the IC4 subgroup (n=343). (C) Representative SHMT2 staining (at 40x) of human breast invasive ductal carcinoma and matched metastatic carcinoma tissue samples (LN = lymph node). (D) Quantification of SHMT2 intensity by IHC in metastatic lesions compared to primary tumors (mean ± SD, n = 33 per group, *P < 0.05 by two-tailed Student’s t test).

Relevance of SHMT2 expression in the progression and aggressiveness of other cancer types

To evaluate the contribution of mitochondrial 1C unit metabolism to the progression of other cancer types, we queried SHMT2 expression in TCGA datasets through the UALCAN portal (). In addition to breast invasive carcinoma (BRCA), we identified adrenocortical carcinoma (ACC), head and neck squamous cell carcinoma (HNSC), kidney chromophobe cell carcinoma (KICH), and kidney renal papillary cell carcinoma (KIRP) as cancer types in which SHMT2 expression progressively increased as a function of stage (Fig. 6). Notably, gain of SHMT2 expression in BRCA and HNSC tended to occur early on in cancer progression, whereas in KICH, SHMT2 upregulation may occur only during the very late stage. A few cancer types such as mesothelioma (MESO) and ovarian serous cystadenocarcinoma (OV) showed the opposite trend: a progressive loss of SHMT2 expression with increasing cancer stage (Supplementary Fig. 9). Collectively, these data present the possibility that there exist additional cancer types in which mitochondrial 1C unit metabolism promotes progression and aggressiveness.

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SHMT2 expression increases with stage in various cancers.

Box plots depicting the average expression level (transcripts per million) of SHMT2 in normal tissue (N) and as a function of cancer stage (stage 1 = S1; stage 2 = S2; stage 3 = S4; stage 4 = S4). Statistically significant differences between pairwise comparisons are highlighted in red. Abbreviations for cancer types are explained as follows: ACC (adrenocortical carcinoma), BRCA (breast invasive carcinoma), HNSCC (head and neck squamous cell carcinoma), KICH (kidney chromophobe carcinoma), KIRP (kidney renal papillary cell carcinoma).

Discussion

For breast cancer, common metastatic sites include the brain, bone, liver, and lung. At the cellular level, the original heterogeneous population of cancer cells from the primary tumor undergo a selection process whereby those clones with alterations (carrying both genetic lesions and epigenetic modifications) favoring fitness and plasticity are enriched. These adaptations, in turn, equip cells with the ability to withstand standard treatments such as chemotherapy and radiation therapy, ultimately leading to cancer progression and metastatic recurrence (). While many previous studies have elucidated a role for molecular processes such as epithelial to mesenchymal transition and invasion and migration of cancer cells, our understanding of how metabolic pathway alterations shape metastatic growth is still limited. It is important to note that the MDA-MB-231 cells we studied were isolated from a pleural population that already metastasizes well in vivo. Our metabolomics profiling of the even more highly metastatic triple-negative breast cancer subclones suggested alterations in both glycolysis and the TCA cycle during the late stages of cancer progression, consistent with findings from other groups of heightened mitochondrial metabolism in metastatic cells (,,,). We further discovered elevated catabolism of serine in the mitochondria of our metastatic subclones. A previous study in isogenic murine 4T1 breast cancer cell lines found that transformed cells showed higher levels of nucleotides than nontransformed cells, and that “more metastatic” lines had even more nucleotides than “less metastatic” ones (). In contrast, we found lower levels of free purines in metastatic variants of human MDA-MB-231 cell lines compared to the parental population (Fig. 1B). This discrepancy may be attributed to different oncogenic contexts in 4T1 cells versus MDA-MB-231 cells or inherent differences in purine metabolism between murine and human cells. Due to the difficulty of obtaining pure metastatic tumor tissue from in vivo studies, the metabolomic analysis were performed using established cell lines in vitro. Microenvironmental factors from metastatic niche, such as hypoxia and nutrient starvation, also regulate cancer cell metabolism. Since mitochondrial 1C unit metabolism can utilize both NAD+ and NADP+, cancer cells with upregulation of mitochondrial 1C unit metabolism may gain metabolic flexibility to sustain proliferation under stress conditions. When cells engage active respiration, the mitochondrial 1C unit pathway can utilize NAD+ to generate 1C units; under hypoxia or starvation conditions, when the NAD+/NADH ratio decreases, elevated mitochondrial ROS leads to an increased NADP+/NADPH ratio, which can also drive the 1C unit pathway and purine synthesis. Further investigations comparing the metabolic profile changes under these stress conditions may provide more insight into potential links between metabolic stresses and the evolution of metastatic cancer cells.

The role of serine in cancer growth has drawn increasing interest over the years ever since the identification of PHGDH amplifications in melanoma and breast cancer (,). A variety of mechanisms have been proposed to explain why increased serine synthesis and serine catabolism could promote tumorigenesis, including rerouting glucose carbon flux, maintenance of compartment-specific NAD(P)+/NAD(P)H ratios, and the control of metabolites such as acetyl-coA, α-ketoglutarate, or 2-hydroxyglutarate (,,). Moreover, a previous study had implicated SHMT2 and a neutral amino acid importer of serine and glycine (ASCT2) as prognostic biomarkers for breast cancer (). Our study is the first to directly evaluate the therapeutic potential of targeting SHMT2 in metastatic breast cancer using both genetic and pharmaceutical approaches. Intriguingly, genetic knockdown of SHMT2 strongly inhibited the proliferation of metastatic cells, while treatment with a dual SHMT1/SHMT2 inhibitor suppressed proliferation of both parental and metastatic subclones. This discrepancy may be explained by prior observations that while MDA-MB-231 cells preferentially utilize the mitochondrial pathway for 1C unit production, inhibition of individual mitochondrial enzymes can lead to a switch to the cytosolic pathway (). We thus speculate that 231-Parental cells may be more adept at switching to cytosolic serine catabolism, and for reasons still unclear, the metastatic subclones are less flexible. Consistent with observations in colon cancer xenografts (), SHMT2 knockdown in the lung metastatic subclone slowed, but not completely suppressed, tumor growth in the mammary fat pad and lung. In addition, we found that in the IC4 subset of human breast cancer patients, the expression of mitochondrial one-carbon unit enzymes is positively associated with more aggressive disease. Thus, interrogating the expression status of mitochondrial one-carbon unit enzymes through transcriptional or proteomic methods holds prognostic value in the metastatic setting, and warrants the need for further development of drugs that selectively inhibit serine catabolism for treating the metastasis of triple-negative breast cancer.

What causes the upregulation of mitochondrial serine catabolic flux in highly metastatic cancer cells? We provide evidence that a crucial oncogenic event promotes the ability of metastatic breast cancer subclones to catabolize serine faster than parental cells: c-Myc activation. c-Myc overexpression is known to be associated with up to 40% of breast cancers, with hyperactive c-Myc enriched particularly in the basal-like subtype (,). These observations are consistent with our findings of the MDA-MB-231 cell line as basal-like and its metastatic subclones expressing even higher levels of c-Myc than the parental population (Fig. 2A). We found that c-Myc was required for the maintenance of the mitochondrial serine and 1C unit pathway genes MTHFD2 and MTHFD1L, consistent with previous reports that c-Myc supports serine/glycine metabolism at the transcriptional level in other cell types (,). These results suggest a model for breast cancer metastasis in which a small fraction of c-Mychigh expressing cells from the primary tumor acquire the ability to upregulate serine catabolism to fuel growth in metastatic tissue sites. Alternatively, high c-Myc expression and the linked ability to upregulate serine catabolism may be intrinsic properties of stem-like metastasis-initiating cells that are enriched in breast cancer cell populations selected for high metastatic activity in mice. As one of the key oncogenic transcription factors, there is increasing evidence that c-Myc plays multiple roles during the metastatic process. c-Myc knockdown reduces invasion and migration of MDA-MB-231 cells (). Moreover, a recent study corroborated our findings of elevated c-Myc levels in brain-metastatic derivatives of human breast cancer cells and demonstrated its necessity for the invasive growth of brain metastases (). Our study highlights the role of c-Myc in enhancing 1C unit pathway activity and proliferation, which is also important for metastatic growth. Since SHMT2 expression was not reduced by c-Myc shRNA, it is likely that other tumor-promoting factors, such as ATF4 and NRF2, also play important roles in late stage cancer progression by modulating 1C unit metabolism. Intriguingly, a recent report showed that TGF-β signaling induces the expression of SHMT2 (). Given the critical role of TGF-β in promoting metastasis (,), it may be interesting to further investigate whether serine and 1C unit pathway metabolic reprogramming is controlled by TGF-ß signaling in metastatic subpopulations of human breast cancer cells.

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1:00PM 11/13/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

1:00 p.m. Panel Discussion Genomics in Prenatal and Childhood Disorders

Genomics in Prenatal and Childhood Disorders

     Moderator:

David Sweetser, M.D., Ph.D.
Unit Chief, Division of Medical Genetics; Attending Physician in Pediatric Hematology/Oncology,
Massachusetts General Hospital for Children

Genomics revolutionized medicine and genetic variation in a larger scale

Cases one on Causing Autism – mutations in a gene of synapse formation, clinical trials

Treatment: IGF1

Genetics: embryo – implant only the healthy embryo – newborn comprehensive genetics testing in the medical record integrated – Standard language of GENE-DRUG interaction not only drug-drug interaction

Potential Harms: May or may not happen disease – stigma issues

Explaining to parents the conditions is very difficult for MDs

Panelists:

3. Diana Bianchi, M.D.
Executive Director, Mother Infant Research Institute;
Vice Chair for Research and Academic Affairs,
Department of Pediatrics; Attending Geneticists and Neonatologist;
Natalie V. Zucker Professor, Tufts University School of Medicine

Medical Geneticist – Pediatrics

  • Prenatal screening and diagnosis – chromosomal abnormality – Down Syndrome, testing is more precise 70% fewer procedures to correct defects due to screening prenatally.
  • Prenatal diagnostics — patient is not in front of us, ultrasound examination, options to terminate pregnancies, genetic counseling — changed due to Genomics
  • Prenatal treatment to down syndrome before the birth – Transcriptomic approach, treat the fetus prebirth
  • Standard of care – all pregnant women – must receive from MD the option for screening for down syndrome, it is a test positive or negative
  • NOW – DNA allows to test for  fetal sex, chromosome in maternal circulation fetal and maternal genetics — Mother may have chromosomal variation
  • high false positive – DNA for Down Syndrome, 97% effective Micro duplication only 5%
  • genetics information protection act – sue prospective employer using Genome, life insurance issues
  • most data available is on Down Syndrome, of all parents informed of a fetus with Down Syndrome – 40% continues the pregnancy
  • accuracy in testing, offering choice and treatment are LEADING principles NOT elimination of a disease (i.e. down syndromes)
  • in ten years — GENOME OF EVERY FETUS TO BE SEQUENCE

for reference see Prenatal Treatment of Down’s Syndrome: a Reality?

and ref list by Dr. Bianchi

2. Holmes Morton, M.D. @ClinicSpecChild
Medical Director, Clinic for Special Children

Small population in Lancaster, PA – risk for untreatable disease 52,000 screens 4.2 millions in US are screened Target mutation analysis, diagnosis very effectively. Harrisburg, PA – small scale natural history studies

Carrier testing offered in 70s. Discourages  from marriage, culture reaction is different. Working in the community, clinical practice using exon sequencing, combine population genetics and molecular biology.Translate Genomics to Clinical, small number of risk factors

History of genetics in population important to establish treatment

Upon birth, affected newborns get matching bone marrow transplant, thus, bypass stem cells – Gene therapy is another thing

1. Benjamin Solomon, Ph.D., M.D.
Chief, Division of Medical Genomics,
Inova Translational Medicine Institute

Longer term, statistical model in asthma research,  rigorous process on patient consent, life insurance, mutation that parents also have. Consequences: actionable findings are communicated
135 Genes – sequencing for some conditions
100,000 deliveries 10% ENTER THE STUDY, CASE BY CASE BASIS O PARTICIPATE, WHO SHOULD BE TESTED

Questions from the Podium

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4:00PM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

 

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

4:00 p.m. Panel Discussion Novel Approaches to Personalized Medicine

Novel Approaches to Personalized Medicine

Genetic and genomic knowledge is helping the development of new drugs, therapies and prognostic tests. As a result, there are new approaches, new partnerships and new business models that are emerging. In some cases, diseases that were considered incurable not too long ago are now being tackled with highly targeted therapies. In other cases the uncertainties associated with assessing potential aggressiveness of disease are being eliminated. This panel will provide examples of new business paradigms that are emerging from the application of personalized medicine.

Novel Approaches to Personalized Medicine

Moderator:

Meghan FitzGerald, Ph.D. @cardinalhealth
President, Cardinal Health Specialty Solutions

Chief Genome Officer – next steps in companies, Genomics Index will replace the Biotech Index

Most Interesting person in Genomics: Marc Levin,

Panelists:

2. Chris Garabedian @Sarepta
President and CEO, Sarepta

  • Applications of genomics to Infectious diseases, therapeutics – design of drugs, Duchenne Muscular Dystrophy (DMD)
  • technology safe working, one drug very effective, 60 alternative drugs, not enough patients to power clinical trials

 

4. Shawn Marcell
President & CEO, Metamark Genetics

  • Prostatic Cancer – Use of genomics tools to diagnose and treat Prostate cancer
  • US market is the best for Genomics innovations because venture capital Market is mature, FDA is negotiable, CMP well established
  • Business model: platform, good test big market, commercialize, clinical data — PM has a different Business model: Delivery of Test results need to be different
  • IPO 2016

 

1. Scott Schell, M.D., Ph.D. – surgical oncology @KEWGroup
President and CEO, KEW Group

  • Large scale platform, strategic partnerships with Oncology Practices,
  • Immuno oncologists, repository of data
  • 80% of cancers are treated in the community 20% at Academic centers. Integration of knowledge, patients wish to stay in the community
  • phase I approval at record high levels

3. Gabriel Bien-Willner, M.D., Ph.D. @MolecularHealth
Medical Director, MolecularHealth, Inc.

  • Diagnostics Tools in Analytics. Clinicians do not have the training in Genomics – position firm to create Lab reports and consulting MDs using Analytics for Clinicians

 

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

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3:15PM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

 

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

 

3:15 p.m. Discussion Complex Disorders

Complex Disorders

During the past 30-40 years, it has become well established that most human disorders affecting large groups of individuals have a genetic basis. Based upon this information there are several efforts to conduct genetic analysis on very large populations of individuals to identify genetic factors that cause susceptibility to complex disorders. In this session, two examples where such studies are bearing fruit will be discussed.

Complex Disorders

Discussion Leader:

Anna Barker, Ph.D.
Director, Transformative Healthcare Knowledge Networks;
Co-Director, Complex Adaptive Systems Initiative:
Professor, School of Life Sciences, Arizona State University

World of Biomarkers following NIH Career – Molecular based Medicine

get all the facts right straight then distort them

Speakers:

Roy Perlis, MGH, Bipolar Specialty, Prof of Psychiatry

Specialist in Schizophrenia, Autism

  • Complexity – overlapping diseases, genomics discovery
  • Psychiatry Genomics – Susceptibility, variance explained by common variation, intervention studies for susceptibility
  • depression is hereditary
  • 2000 schizophrenics genome,
  • phenotype models is only partially indicative of help if you are on Klonopin, is this enough for the diagnosis
  • CRISPR — HOW to use it — not discovered yet for psychiatry disorder — it may be the solution, though

Joe Vockley

COO, Inova Health System

CSO, Inova Translational Medicine Institute

  • Preeclempsia – preterm Birth is a complex disease many factor can cause it, 12% of birth are Preterm birth
  • 10,000 genome vs full term birth, clinical phenotypes,
  • model 81% predictive — triage screening based on markers – genomics to follow phenotyping.
  • Genomics — indicative — not fully used from diagnostics to therapy
  • ancestor data (familial info) of the 10,000 in the cohort was done filter variant
  • whole genome sequencing, reimbursement does not support  to path to therapy based on genomics

Robert Plenge, M.D., Ph.D.   @rplenge
Vice President and Worldwide Head Genetics and Pharmacogenomics
Merck Research Laboratories – Specialist RA

ex- Pharmacogenetics at MGH

  • sample size 100,000 genomes completely sequenced  – PM is at present in Oncology – use Genetics to discover diagnostics markers, clinical diagnosis, protocols – worst in cancer
  • genetic effect are important component requires big cohort to identify large effect
  • dysfunctional variant
  • Proteomic predictors, in drug discovery not sufficient, marker of disease  it is helpful

 

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

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1:45PM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

 

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

 

1:45 p.m. Panel Discussion – Oncology

Oncology

There has been a remarkable transformation in our understanding of the molecular genetic basis of cancer and its treatment during the past decade or so. In depth genetic and genomic analysis of cancers has revealed that each cancer type can be sub-classified into many groups based on the genetic profiles and this information can be used to develop new targeted therapies and treatment options for cancer patients. This panel will explore the technologies that are facilitating our understanding of cancer, and how this information is being used in novel approaches for clinical development and treatment.

Oncology

Opening Speaker & Moderator:

Lynda Chin, M.D.
Department Chair, Department of Genomic Medicine
MD Anderson Cancer Center     @MDAnderson   #endcancer

  • Who pays for personalized medicine?
  • potential of Big data, analytics, Expert systems, so not each MD needs to see all cases, Profile disease to get same treatment
  • business model: IP, Discovery, sharing, ownership — yet accelerate therapy
  • security of healthcare data
  • segmentation of patient population
  • management of data and tracking innovations
  • platforms to be shared for innovations
  • study to be longitudinal,
  • How do we reconcile course of disease with personalized therapy
  • phenotyping the disease vs a Patient in wait for cure/treatment

Panelists:

Roy Herbst, M.D., Ph.D.    @DrRoyHerbstYale

Ensign Professor of Medicine and Professor of Pharmacology;
Chief of Medical Oncology, Yale Cancer Center and Smilow Cancer Hospital     @YaleCancer

Development new drugs to match patient, disease and drug – finding the right patient for the right Clinical Trial

  • match patient to drugs
  • partnerships: out of 100 screened patients, 10 had the gene, 5 were able to attend the trial — without the biomarker — all 100 patients would participate for the WRONG drug for them (except the 5)
  • patients wants to participate in trials next to home NOT to have to travel — now it is in the protocol
  • Annotated Databases – clinical Trial informed consent – adaptive design of Clinical Trial vs protocol
  • even Academic MD can’t read the reports on Genomics
  • patients are treated in the community — more training to MDs
  • Five companies collaborating – comparison of 6 drugs in the same class
  • if drug exist and you have the patient — you must apply personalized therapy

 

Lincoln Nadauld, M.D., Ph.D.
Director, Cancer Genomics, Huntsman Intermountain Cancer Clinic @lnadauld @intermountain

  • @Stanford, all patients get Tumor profiles Genomic results, interpretation – deliver personalized therapy
  • Outcomes from Genomics based therapies
  • Is survival superior
  • Targeted treatment – Health economic impact is cost lower or not for same outcome???
  • genomic profiling of tumors: Genomic information changes outcome – adverse events lower
  • Path ways and personalized medicine based on Genomics — integration not yet been worked out

Question by Moderator: Data Management

  • Platform development, clinical knowledge system,
  • build consortium of institutions to share big data – identify all patients with same profile

 

 

 

 

See more at  http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

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11:30AM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

 

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

11:30 Personalized Medicine Coalition Award &  Award Recipient Speech

Presentation of Personalized Medicine Coalition’s 10th Annual Award for Leadership in Personalized Medicine.

Personalized Medicine Coalition Award Recipient

Mark J. Levin
Co-Founder and Partner
Third Rock Ventures, LLC

Presenter:

Brian Munroe
PMC Founder and Senior Vice President, Government Affairs
Endo

 Award in Science, Business Policy to individual to lead PM – Mark Levin

 

 

  • was at Ely Lilly in the 70s leading supplier of Insulin in the 20s and antibiotics in the 30s,Factor 8, pain drugs, chemotherapy
  • was at Genentech – Human growth Hormone and Human Insulin — both are PM, Interferon,
  • was at Mayfield Ventures
  • was at Millenium, CEO, early 90s, monoclonal antibodies
  • 2000 discussion on the need for PMC
  • Founder of Foundation Medicine – molecular informatics – expands therapeutics and PM
  • NOW — with Third Rock Ventures, LLC

 

Mark Levin – award acceptance speech – Team accomplishments most important

We need to thank the patients participating in Clinical Trials

  1. How I got involved in personalized medicine (PM): High School – Human Biology
  2. Genetics – drive
  3. PM – All diseases – genetic disorders — combination with extreme phenotyping, Muscular Dystrophy – splicing a gene for treatment
  4. Drugability and PM – gene therapy, replace factor, deliver a gene to the brain and the drug. inside CSF
  5. Gene editing – deliver to the Brain correct the gene in the Brain – therapy for ALS, Schizophrenia – understanding the genes involved in this disease, same
  6. Cancer cure – treatment of combination therapies several at the same time vs present time treat one other emerges
  7. cancer vaccine
  8. Sample of blood – proteomics — in Annual Exams at MDs Annual physical
  9. Convergent — comparison of Mutation across to 1000 patient’s mutations
  10. Future is MOST exciting
  11. Challenges of the Future: Biology and Technology, cells in microbiome, 10 million genes, SYSTEM BIOLOGY — will lead the way,
  12. FUNDING SCIENCE via NIH Scientist is the most important National task
  13. Preventative and Prognostics Medicine -need be part of DRUG development
  14. Justification – maximize value for patient vs $$ spent – maximum value – waste and no leadership
  15. Concern — Affordability of Healthcare to All, access to care vs economic Inequality
  16. Leadership and Management: We truly need NATIONAL CONVERSATION — with a Leader with set of goals to solve a problem in certain time
  17. Insurance, Pharma, HMO — budget challenge — attendees inn the room, need to provide leadership at the National Level

 

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

 

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11:00AM 11/12/2014 – 10th Annual Personalized Medicine Conference at the Harvard Medical School, Boston

Reporter: Aviva Lev-Ari, PhD, RN

 

REAL TIME Coverage of this Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

11:00 Keynote Speaker – Past, Present and Future of Personalized Medicine

Past, Present and Future of Personalized Medicine

Keynote Speaker

Mirella Marlow, M.A., M.B.A.
Programme Director, Centre for Health Technology Evaluation,
National Institute for Health and Clinical Excellence (NICE) @NICEcomms

PM in the UK

Clinical evidence and cost effectiveness needed for PM

UK Government life sciences policy

Scale of PM:

2013 – 10 million pound

2020 – 60 million pound

Innovative healthcare to promote economic growth

  • Genomics England 100,000  – new scientific discovery and kick start the UK genomics industry
  • BIS – accelerate Skills & Training for the Genomics Industries
  • UK Precision Medicine Catapult development of tests and commercialization of innovation in diagnostics

1 Billion Pound NIHR in UK

  • tissue banks – Biobank
  • Farr Institute – “big data”
  • develop methodologies for starter research

National Institute Care Excellence

– standards for NP

Benefits of PM

  • right treatment
  • responding subgroups
  • earlier treatments
  • dosing
  • reduce side effects

Companion Diagnostics in NICE – Technology Appraisals

  • elevate a test like evaluate a drug ad part of Diagnostics
  • Treatment: GIST — >>Biomarker: KitCD117

Diagnostics assessment Program

  • 9 EGFR-TK – mutation testing –
  • Mutation Analysis Services

NICE support to Companies – Company engagement

  • discuss product pipeline and value proposition
  • orientation to the process
  • Scientific Advice on Clinical Trial Design
  • workshops for Pharma and for Diagnostics — are different
  • online tool being developed – standardize the Advise for Fee — get Accredited Advisors in the Fields of Genomics, Diagnostics
  • Post guidance – evidence gaps, clinical utility and economic evidence
  • Update guidance – research questions guiding Guidance for the industry
  • Indirect Research facilitation: protocol external funding identify clinical context ethics +GCP leading to Publication within 2 years

UK and Genetics: Kirk and Watson on DNA

UK – 60 million patients under one National Universal Health Care System

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

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8:00 AM – Welcome & Opening Remarks

Reporter: Aviva Lev-Ari, PhD, RN

REAL TIME Coverage of the Conference by Dr. Aviva Lev-Ari, PhD, RN – Director and Founder of LEADERS in PHARMACEUTICAL BUSINESS INTELLIGENCE, Boston http://pharmaceuticalintelligence.com

Speakers

Raju Kucherlapati, Ph.D.
Paul C. Cabot Professor of Genetics, Professor of Medicine, Harvard Medical School

Welcome all attendees, discussing Personalized Medicine, what happened and looking forward — the potential of this approach to Medicine. Event organized with Partner, National Council Cancer Research. Organizing committee and Sponsors made the event possible.

AND

Scott Weiss, M.D., M.S.
Scientific Director, Partners Personalized Medicine;
Associate Director, Channing Laboratory, Professor of Medicine.

Greetings

Greetings from the Institute of Medicine

Victor Dzau, M.D. — ABSENT — By Voice addressing the Audience
President, Institute of Medicine

Advisor on Genomics – In 1996 returned from Stanford to Harvard. What role Genetics and Genomics will play in Medicine.

Boston is a very special place for that endeavor. Harvard allocated $100 Million to study this topic. 10th year of the Conference. I am 100 days at IOM, Genomics and personalized medicine (PM) and Translation Medicine are the center. Spin off in Software development to solicit application in PM. Scientists, payers, technologists — the economics of PM navigate the regulatory. Looking forward for the next 10 years in PM

“10 Years in 10 Minutes: 10 Facts”

Edward Abrahams, Ph.D. (@newsfrompmc)
President, Personalized Medicine Coalition

Review the Progress made in PM – it has change, treating the patient not changing the disease. Friendlier  between Science and the Medicine.

  • 2004 Harvard graduate started Facebook, Viox was recalled,
  • Personalized Medicine – drugs increase form 13 in 2003 to 113 in 2013.
  • Diagnostics evolution by revolution
  • It took 4 years to develop new drug in 2013
  • In 20 years 45% of drug approvals – revolution in 155 Pharmacogenomics drugs approved at $12 Billion sales
  • FDA encouraged PM – 2017 Diagnostics
  • FDA molecular diagnostics test
  1. Regulatory of tests
  2. Payers and Manufacturer do not agree on practices
  3. Education of MDs in PM, 10% had sufficient knowledge in Genomics to incorporate it in Delivery of Care
Margaret Hamburg, MD
Commissioner of FDA

– See more at: http://personalizedmedicine.partners.org/Education/Personalized-Medicine-Conference/Program.aspx#sthash.qGbGZXXf.dpuf

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