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Archive for the ‘Clinical Genomics’ Category


Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

A mutated gene called RAS gives rise to a signalling protein Ral which is involved in tumour growth in the bladder. Many researchers tried and failed to target and stop this wayward gene. Signalling proteins such as Ral usually shift between active and inactive states.

 

So, researchers next tried to stop Ral to get into active state. In inacvtive state Ral exposes a pocket which gets closed when active. After five years, the researchers found a small molecule dubbed BQU57 that can wedge itself into the pocket to prevent Ral from closing and becoming active. Now, BQU57 has been licensed for further development.

 

Researchers have a growing genetic data on bladder cancer, some of which threaten to overturn the supposed causes of bladder cancer. Genetics has also allowed bladder cancer to be reclassified from two categories into five distinct subtypes, each with different characteristics and weak spots. All these advances bode well for drug development and for improved diagnosis and prognosis.

 

Among the groups studying the genetics of bladder cancer are two large international teams: Uromol (named for urology and molecular biology), which is based at Aarhus University Hospital in Denmark, and The Cancer Genome Atlas (TCGA), based at institutions in Texas and Boston. Each team tackled a different type of cancer, based on the traditional classification of whether or not a tumour has grown into the muscle wall of the bladder. Uromol worked on the more common, earlier form, non-muscle-invasive bladder cancer, whereas TCGA is looking at muscle-invasive bladder cancer, which has a lower survival rate.

 

The Uromol team sought to identify people whose non-invasive tumours might return after treatment, becoming invasive or even metastatic. Bladder cancer has a high risk of recurrence, so people whose non-invasive cancer has been treated need to be monitored for many years, undergoing cystoscopy every few months. They looked for predictive genetic footprints in the transcriptome of the cancer, which contains all of a cell’s RNA and can tell researchers which genes are turned on or off.

 

They found three subgroups with distinct basal and luminal features, as proposed by other groups, each with different clinical outcomes in early-stage bladder cancer. These features sort bladder cancer into genetic categories that can help predict whether the cancer will return. The researchers also identified mutations that are linked to tumour progression. Mutations in the so-called APOBEC genes, which code for enzymes that modify RNA or DNA molecules. This effect could lead to cancer and cause it to be aggressive.

 

The second major research group, TCGA, led by the National Cancer Institute and the National Human Genome Research Institute, that involves thousands of researchers across USA. The project has already mapped genomic changes in 33 cancer types, including breast, skin and lung cancers. The TCGA researchers, who study muscle-invasive bladder cancer, have looked at tumours that were already identified as fast-growing and invasive.

 

The work by Uromol, TCGA and other labs has provided a clearer view of the genetic landscape of early- and late-stage bladder cancer. There are five subtypes for the muscle-invasive form: luminal, luminal–papillary, luminal–infiltrated, basal–squamous, and neuronal, each of which is genetically distinct and might require different therapeutic approaches.

 

Bladder cancer has the third-highest mutation rate of any cancer, behind only lung cancer and melanoma. The TCGA team has confirmed Uromol research showing that most bladder-cancer mutations occur in the APOBEC genes. It is not yet clear why APOBEC mutations are so common in bladder cancer, but studies of the mutations have yielded one startling implication. The APOBEC enzyme causes mutations early during the development of bladder cancer, and independent of cigarette smoke or other known exposures.

 

The TCGA researchers found a subset of bladder-cancer patients, those with the greatest number of APOBEC mutations, had an extremely high five-year survival rate of about 75%. Other patients with fewer APOBEC mutations fared less well which is pretty surprising.

 

This detailed knowledge of bladder-cancer genetics may help to pinpoint the specific vulnerabilities of cancer cells in different people. Over the past decade, Broad Institute researchers have identified more than 760 genes that cancer needs to grow and survive. Their genetic map might take another ten years to finish, but it will list every genetic vulnerability that can be exploited. The goal of cancer precision medicine is to take the patient’s tumour and decode the genetics, so the clinician can make a decision based on that information.

 

References:

 

https://www.ncbi.nlm.nih.gov/pubmed/29117162

 

https://www.ncbi.nlm.nih.gov/pubmed/27321955

 

https://www.ncbi.nlm.nih.gov/pubmed/28583312

 

https://www.ncbi.nlm.nih.gov/pubmed/24476821

 

https://www.ncbi.nlm.nih.gov/pubmed/28988769

 

https://www.ncbi.nlm.nih.gov/pubmed/28753430

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Scientists think excessive population growth is a cause of scarcity and environmental degradation. A male pill could reduce the number of unintended pregnancies, which accounts for 40 percent of all pregnancies worldwide.

 

But, big drug companies long ago dropped out of the search for a male contraceptive pill which is able to chemically intercept millions of sperm before they reach a woman’s egg. Right now the chemical burden for contraception relies solely on the female. There’s not much activity in the male contraception field because an effective solution is available on the female side.

 

Presently, male contraception means a condom or a vasectomy. But researchers from Center for Drug Discovery at Baylor College of Medicine, USA are renewing the search for a better option—an easy-to-take pill that’s safe, fast-acting, and reversible.

 

The scientists began with lists of genes active in the testes for sperm production and motility and then created knockout mice that lack those genes. Using the gene-editing technology called CRISPR, in collaboration with Japanese scientists, they have so far made more than 75 of these “knockout” mice.

 

They allowed these mice to mate with normal (wild type) female mice, and if their female partners don’t get pregnant after three to six months, it means the gene might be a target for a contraceptive. Out of 2300 genes that are particularly active in the testes of mice, the researchers have identified 30 genes whose deletion makes the male infertile. Next the scientists are planning a novel screening approach to test whether any of about two billion chemicals can disable these genes in a test tube. Promising chemicals could then be fed to male mice to see if they cause infertility.

 

Female birth control pills use hormones to inhibit a woman’s ovaries from releasing eggs. But hormones have side effects like weight gain, mood changes, and headaches. A trial of one male contraceptive hormone was stopped early in 2011 after one participant committed suicide and others reported depression. Moreover, some drug candidates have made animals permanently sterile which is not the goal of the research. The challenge is to prevent sperm being made without permanently sterilizing the individual.

 

As a better way to test drugs, Scientists at University of Georgia, USA are investigating yet another high-tech approach. They are turning human skin cells into stem cells that look and act like the spermatogonial cells in the testes. Testing drugs on such cells might provide more accurate leads than tests on mice.

 

The male pill would also have to start working quickly, a lot sooner than the female pill, which takes about a week to function. Scientists from University of Dundee, U.K. admitted that there are lots of challenges. Because, a women’s ovary usually release one mature egg each month, while a man makes millions of sperm every day. So, the male pill has to be made 100 percent effective and act instantaneously.

 

References:

 

https://www.technologyreview.com/s/603676/the-search-for-a-perfect-male-birth-control-pill/

 

https://futurism.com/videos/the-perfect-male-birth-control-pill-is-coming-soon/?utm_source=Digest&utm_campaign=c42fc7b9b6-EMAIL_CAMPAIGN_2017_03_20&utm_medium=email&utm_term=0_03cd0a26cd-c42fc7b9b6-246845533

 

http://www.telegraph.co.uk/women/sex/the-male-pill-is-coming—and-its-going-to-change-everything/

 

http://www.mensfitness.com/women/sex-tips/male-birth-control-pill-making

 

http://health.howstuffworks.com/sexual-health/contraception/male-bc-pill.htm

 

http://europe.newsweek.com/male-contraception-side-effects-study-pill-injection-518237?rm=eu

 

http://edition.cnn.com/2016/01/07/health/male-birth-control-pill/index.html

 

http://www.nhs.uk/Conditions/contraception-guide/Pages/male-pill.aspx

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Translation of whole human genome sequencing to clinical practice: The Joint Initiative for Metrology in Biology (JIMB) is a collaboration between the National Institute of Standards & Technology (NIST) and Stanford University.

Reporter: Aviva Lev-Ari, PhD, RN

 

JIMB’s mission is to advance the science of measuring biology (biometrology). JIMB is pursuing fundamental research, standards development, and the translation of products that support confidence in biological measurements and reliable reuse of materials and results. JIMB is particularly focused on measurements and technologies that impact, are related to, or enabled by ongoing advances in and associated with the reading and writing of DNA.

Stanford innovators and industry entrepreneurs have joined forces with the measurement experts from NIST to create a new engine powering the bioeconomy. It’s called JIMB — “Jim Bee” — the Joint Initiative for Metrology in Biology. JIMB unites people, platforms, and projects to underpin standards-based research and innovation in biometrology.

Genome in a Bottle
Authoritative Characterization of
Benchmark Human Genomes


The Genome in a Bottle Consortium is a public-private-academic consortium hosted by NIST to develop the technical infrastructure (reference standards, reference methods, and reference data) to enable translation of whole human genome sequencing to clinical practice. The priority of GIAB is authoritative characterization of human genomes for use in analytical validation and technology development, optimization, and demonstration. In 2015, NIST released the pilot genome Reference Material 8398, which is genomic DNA (NA12878) derived from a large batch of the Coriell cell line GM12878, characterized for high-confidence SNPs, indel, and homozygous reference regions (Zook, et al., Nature Biotechnology 2014).

There are four new GIAB reference materials available.  With the addition of these new reference materials (RMs) to a growing collection of “measuring sticks” for gene sequencing, we can now provide laboratories with even more capability to accurately “map” DNA for genetic testing, medical diagnoses and future customized drug therapies. The new tools feature sequenced genes from individuals in two genetically diverse groups, Asians and Ashkenazic Jews; a father-mother-child trio set from Ashkenazic Jews; and four microbes commonly used in research. For more information click here.  To purchase them, visit:

Data and analyses are publicly available (GIAB GitHub). A description of data generated by GIAB is published here. To standardize best practices for using GIAB genomes for benchmarking, we are working with the Global Alliance for Genomics and Health Benchmarking Team (benchmarking tools).

High-confidence small variant and homozygous reference calls are available for NA12878, the Ashkenazim trio, and the Chinese son with respect to GRCh37.  Preliminary high-confidence calls with respect to GRCh38 are also available for NA12878.   The latest version of these calls is under the latest directory for each genome on the GIAB FTP.

The consortium was initiated in a set of meetings in 2011 and 2012, and the consortium holds open, public workshops in January at Stanford University in Palo Alto, CA and in August/September at NIST in Gaithersburg, MD. Slides from workshops and conferences are available online. The consortium is open and welcomes new participants.

SOURCE

Stanford innovators and industry entrepreneurs have joined forces with the measurement experts from NIST to create a new engine powering the bioeconomy. It’s called JIMB — “Jim Bee” — the Joint Initiative for Metrology in Biology. JIMB unites people, platforms, and projects to underpin standards-based research and innovation in biometrology.

JIMB World Metrology Day Symposium

JIMB’s mission is to motivate standards-based measurement innovation to facilitate translation of basic science and technology development breakthroughs in genomics and synthetic biology.

By advancing biometrology, JIMB will push the boundaries of discovery science, accelerate technology development and dissemination, and generate reusable resources.

 SOURCE

VIEW VIDEO

https://player.vimeo.com/video/184956195?wmode=opaque&api=1″,”url”:”https://vimeo.com/184956195″,”width”:640,”height”:360,”providerName”:”Vimeo”,”thumbnailUrl”:”https://i.vimeocdn.com/video/594555038_640.jpg”,”resolvedBy”:”vimeo”}” data-block-type=”32″>

Other related articles published in this Open Access Online Scientific Journal include the following:

“Genome in a Bottle”: NIST’s new metrics for Clinical Human Genome Sequencing

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2012/09/06/genome-in-a-bottle-nists-new-metrics-for-clinical-human-genome-sequencing/

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

MicroRNAs (miRNAs) are a group of small non-coding RNA molecules that play a major role in posttranscriptional regulation of gene expression and are expressed in an organ-specific manner. One miRNA can potentially regulate the expression of several genes, depending on cell type and differentiation stage. They control every cellular process and their altered regulation is involved in human diseases. miRNAs are differentially expressed in the male and female gonads and have an organ-specific reproductive function. Exerting their affect through germ cells and gonadal somatic cells, miRNAs regulate key proteins necessary for gonad development. The role of miRNAs in the testes is only starting to emerge though they have been shown to be required for adequate spermatogenesis. In the ovary, miRNAs play a fundamental role in follicles’ assembly, growth, differentiation, and ovulation.

 

Deciphering the underlying causes of idiopathic male infertility is one of the main challenges in reproductive medicine. This is especially relevant in infertile patients displaying normal seminal parameters and no urogenital or genetic abnormalities. In these cases, the search for additional sperm biomarkers is of high interest. This study was aimed to determine the implications of the sperm miRNA expression profiles in the reproductive capacity of normozoospermic infertile individuals. The expression levels of 736 miRNAs were evaluated in spermatozoa from normozoospermic infertile males and normozoospermic fertile males analyzed under the same conditions. 57 miRNAs were differentially expressed between populations; 20 of them was regulated by a host gene promoter that in three cases comprised genes involved in fertility. The predicted targets of the differentially expressed miRNAs unveiled a significant enrichment of biological processes related to embryonic morphogenesis and chromatin modification. Normozoospermic infertile individuals exhibit a specific sperm miRNA expression profile clearly differentiated from normozoospermic fertile individuals. This miRNA cargo has potential implications in the individuals’ reproductive competence.

 

Circulating or “extracellular” miRNAs detected in biological fluids, could be used as potential diagnostic and prognostic biomarkers of several disease, such as cancer, gynecological and pregnancy disorders. However, their contributions in female infertility and in vitro fertilization (IVF) remain unknown. Polycystic ovary syndrome (PCOS) is a frequent endocrine disorder in women. PCOS is associated with altered features of androgen metabolism, increased insulin resistance and impaired fertility. Furthermore, PCOS, being a syndrome diagnosis, is heterogeneous and characterized by polycystic ovaries, chronic anovulation and evidence of hyperandrogenism, as well as being associated with chronic low-grade inflammation and an increased life time risk of type 2 diabetes. Altered miRNA levels have been associated with diabetes, insulin resistance, inflammation and various cancers. Studies have shown that circulating miRNAs are present in whole blood, serum, plasma and the follicular fluid of PCOS patients and that these might serve as potential biomarkers and a new approach for the diagnosis of PCOS. Presence of miRNA in mammalian follicular fluid has been demonstrated to be enclosed within microvesicles and exosomes or they can also be associated to protein complexes. The presence of microvesicles and exosomes carrying microRNAs in follicular fluid could represent an alternative mechanism of autocrine and paracrine communication inside the ovarian follicle. The investigation of the expression profiles of five circulating miRNAs (let-7b, miR-29a, miR-30a, miR-140 and miR-320a) in human follicular fluid from women with normal ovarian reserve and with polycystic ovary syndrome (PCOS) and their ability to predict IVF outcomes showed that these miRNAs could provide new helpful biomarkers to facilitate personalized medical care for oocyte quality in ART (Assisted Reproductive Treatment) and during IVF (In Vitro Fertilization).

 

References:

 

http://link.springer.com/chapter/10.1007%2F978-3-319-31973-5_12

 

http://onlinelibrary.wiley.com/doi/10.1111/andr.12276/abstract;jsessionid=F805A89DCC94BDBD42D6D60C40AD4AB0.f03t03

 

http://www.sciencedirect.com/science/article/pii/S0009279716302241

 

http://link.springer.com/article/10.1007%2Fs10815-016-0657-9

 

http://www.nature.com/articles/srep24976

 

 

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LIVE 9/21 8AM to 10:55 AM Expoloring the Versatility of CRISPR/Cas9 at CHI’s 14th Discovery On Target, 9/19 – 9/22/2016, Westin Boston Waterfront, Boston

http://www.discoveryontarget.com/

http://www.discoveryontarget.com/crispr-therapies/

Leaders in Pharmaceutical Business Intelligence (LPBI) Group is a

Media Partner of CHI for CHI’s 14th Annual Discovery on Targettaking place September 19 – 22, 2016 in Boston.

In Attendance, streaming LIVE using Social Media

Aviva Lev-Ari, PhD, RN

Editor-in-Chief

http://pharmaceuticalintelligence.com

#BostonDOT16

@BostonDOT

 

COMMENTS BY Stephen J Williams, PhD

EXPLORING THE VERSATILITY OF CRISPR/Cas9

 

8:00 Chairperson’s Opening Remarks

TJ Cradick , Ph.D., Head of Genome Editing, CRISPR Therapeutics

 

@CRISPRTX

 

8:10 Functional Genomics Using CRISPR-Cas9: Technology and Applications

Neville Sanjana, Ph.D., Core Faculty Member, New York Genome Center and Assistant Professor, Department of Biology & Center for Genomics and Systems Biology, New York University

 

CRISPR Cas9 is easier to target to multiple genomic loci; RNA specifies DNA targeting; with zinc finger nucleases or TALEEN in the protein specifies DNA targeting

 

  • This feature of crisper allows you to make a quick big and cheap array of a GENOME SCALE Crisper Knock out (GeCKO) screening library
  • How do you scale up the sgRNA for whole genome?; for all genes in RefSeq, identify consitutive exons using RNA-sequencing data from 16 primary human tissue (alot of genes end with ‘gg’) changing the bases on 3’ side negates crisper system but changing on 5’ then crisper works fine
  • Rank sequences to be specific for target
  • Cloned array into lentiviral and put in selectable markers
  • GeCKO displays high consistency betweens reagents for the same gene versus siRNA; GeCKO has high screening sensitivity
  • 98% of genome is noncoding so what about making a library for intronic regions (miRNA, promoter regions?)
  • So you design the sgRNA library by taking 100kb of gene-adjacent regions
  • They looked at CUL3; (data will soon be published in Science)
  • Do a transcription CHIP to verify the lack of binding of transcription factor of interest
  • Can also target histone marks on promoter and enhancer elements
  • NYU wants to explore this noncoding screens
  • sanjanalab.org

 

@nyuniversity

 

8:40 Therapeutic Gene Editing With CRISPR/Cas9

TJ Cradick , Ph.D., Head of Genome Editing, CRISPR Therapeutics

 

NEHJ is down and dirty repair of single nonhomologous end but when have two breaks the NEHJ repair can introduce the inversions or deletions

 

    • High-throughput screens are fine but can limit your view of genomic context; genome searches pick unique sites so use bioinformatic programs  to design specific guide Rna
    • Bioinformatic directed, genome wide, functional screens
    • Compared COSMID and CCTOP; 320 COSMID off-target sites, 333 CCtop off target
    • Young lab GUIDESeq program genome wide assay useful to design guides
    • If shorten guide may improve specificity; also sometime better sensitivity if lengthen guide

 

  • Manufacturing of autologous gene corrected product ex vivo gene correction (Vertex, Bayer, are partners in this)

 

 

They need to use a clones from multiple microarrays before using the GUidESeq but GUIDEseq is better for REMOVING the off targets than actually producing the sgRNA library you want (seems the methods for library development are not fully advanced to do this)

 

The score sometimes for the sgRNA design programs do not always give the best result because some sgRNAs are genome context dependent

9:10 Towards Combinatorial Drug Discovery: Mining Heterogeneous Phenotypes from Large Scale RNAi/Drug Perturbations

Arvind Rao, Ph.D., Assistant Professor, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center

 

Bioinformatics in CRISPR screens:  they looked at image analysis of light microscopy of breast cancer cells and looked for phenotypic changes

 

  • Then they modeled in a small pilot and then used the algorithm for 20,000 images (made morphometric measurements)
  • Can formulate training statistical algorithms to make a decision tree how you classify data points
  • Although their algorithms worked well there was also human input from scientists

Aggregate ranking of hits programs available on web like LINKS

 

@MDAndersonNews

 

10:25 CRISPR in Stem Cell Models of Eye Disease

Alexander Bassuk, M.D., Ph.D., Associate Professor of Pediatrics, Department of Molecular and Cellular Biology, University of Iowa

 

Blind athlete Michael Stone, biathlete, had eye disease since teenager helped fund and start the clinical trial for Starbardt disease; had one bad copy of ABCA4, heterozygous (inheritable in Ahkenazi Jewish) – a recessive inheritable mutation with juvenile macular degeneration

  • Also had another male in family with disease but he had another mutation in the RPGR gene
  • December 2015 paper Precision Medicine: Genetic Repair of retinitis pigmentosa in patient derived stem cells
  • They were able to correct the iPSCs in the RPGR gene derived from patient however low efficiency of repair, scarless repair, leaves changes in DNA, need clinical grade iPSCs, and need a humanized model of RPGR

@uiowa

10:55 CRISPR in Mouse Models of Eye Disease

Vinit Mahajan, M.D., Ph.D., Assistant Professor of Ophthalmology and Visual Sciences, University of Iowa College of Medicine

  • degeneration of the retina will see brown spots, the macula will often be preserved but retinal cells damaged but with RPGR have problems with peripheral vision, retinitis pigmentosa get tunnel vision with no peripheral vision (a mouse model of PDE6 Knockout recapitulates this phenotype)
  • the PDE6 is linked to the rhodopsin GTP pathway
  • rd1 -/- mouse has something that looks like retinal pigmentosa; has mutant PDE6; is actually a nonsense mutation in rd1 so they tried a crisper to fix in mice
  • with crisper fix of rd1 nonsense mutation the optic nerve looked comparible to normal and the retina structure restored
  • photoreceptors layers- some recovery but not complete
  • sequence results show the DNA is a mosaic so not correcting 100% but only 35% but stil leads to a phenotypic recovery; NHEJ was about 12% to 25% with large deletions
  • histology is restored in crspr repaired mice
  • CRSPR off target effects: WGS and analyze for variants SNV/indels, also looked at on target and off target regions; there were no off target SNVs indels while variants that did not pass quality control screening not a single SNV
  • Rhodopsin mutation accounts for a large % of patients (RhoD190N)
  • injection of gene therapy vectors: AAV vector carrying CRSPR and cas9 repair templates

CAPN mouse models

  • family in Iowa have dominant mutation in CAPN5; retinal degenerates
  • used CRSPR to generate mouse model with mutation in CAPN5 similar to family mutation
  • compared to other transgenic methods CRSPR is faster to produce a mouse model

To Follow LIVE CONFERENCE COVERAGE PLEASE FOLLOW ON TWITTER USING

Meeting #: #BostonDOT16

Meeting @: @BostonDOT

 

Overall good meeting #s:

#personalizedmedicine

#innovation

#cancer

#immunology

#immunooncology

#pharmanews

#CRSPR

#geneediting

#crisper

#biotech

 

AND FOLLOW these @

@pharma_BI

@AVIVA_1950

@BiotechNews

@CHI

@FierceBiotech

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Milestones in Physiology & Discoveries in Medicine and Genomics: Request for Book Review Writing on Amazon.com


physiology-cover-seriese-vol-3individualsaddlebrown-page2

Milestones in Physiology

Discoveries in Medicine, Genomics and Therapeutics

Patient-centric Perspective 

http://www.amazon.com/dp/B019VH97LU 

2015

 

 

Author, Curator and Editor

Larry H Bernstein, MD, FCAP

Chief Scientific Officer

Leaders in Pharmaceutical Business Intelligence

Larry.bernstein@gmail.com

Preface

Introduction 

Chapter 1: Evolution of the Foundation for Diagnostics and Pharmaceuticals Industries

1.1  Outline of Medical Discoveries between 1880 and 1980

1.2 The History of Infectious Diseases and Epidemiology in the late 19th and 20th Century

1.3 The Classification of Microbiota

1.4 Selected Contributions to Chemistry from 1880 to 1980

1.5 The Evolution of Clinical Chemistry in the 20th Century

1.6 Milestones in the Evolution of Diagnostics in the US HealthCare System: 1920s to Pre-Genomics

 

Chapter 2. The search for the evolution of function of proteins, enzymes and metal catalysts in life processes

2.1 The life and work of Allan Wilson
2.2  The  evolution of myoglobin and hemoglobin
2.3  More complexity in proteins evolution
2.4  Life on earth is traced to oxygen binding
2.5  The colors of life function
2.6  The colors of respiration and electron transport
2.7  Highlights of a green evolution

 

Chapter 3. Evolution of New Relationships in Neuroendocrine States
3.1 Pituitary endocrine axis
3.2 Thyroid function
3.3 Sex hormones
3.4 Adrenal Cortex
3.5 Pancreatic Islets
3.6 Parathyroids
3.7 Gastointestinal hormones
3.8 Endocrine action on midbrain
3.9 Neural activity regulating endocrine response

3.10 Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

 

Chapter 4.  Problems of the Circulation, Altitude, and Immunity

4.1 Innervation of Heart and Heart Rate
4.2 Action of hormones on the circulation
4.3 Allogeneic Transfusion Reactions
4.4 Graft-versus Host reaction
4.5 Unique problems of perinatal period
4.6. High altitude sickness
4.7 Deep water adaptation
4.8 Heart-Lung-and Kidney
4.9 Acute Lung Injury

4.10 Reconstruction of Life Processes requires both Genomics and Metabolomics to explain Phenotypes and Phylogenetics

 

Chapter 5. Problems of Diets and Lifestyle Changes

5.1 Anorexia nervosa
5.2 Voluntary and Involuntary S-insufficiency
5.3 Diarrheas – bacterial and nonbacterial
5.4 Gluten-free diets
5.5 Diet and cholesterol
5.6 Diet and Type 2 diabetes mellitus
5.7 Diet and exercise
5.8 Anxiety and quality of Life
5.9 Nutritional Supplements

 

Chapter 6. Advances in Genomics, Therapeutics and Pharmacogenomics

6.1 Natural Products Chemistry

6.2 The Challenge of Antimicrobial Resistance

6.3 Viruses, Vaccines and immunotherapy

6.4 Genomics and Metabolomics Advances in Cancer

6.5 Proteomics – Protein Interaction

6.6 Pharmacogenomics

6.7 Biomarker Guided Therapy

6.8 The Emergence of a Pharmaceutical Industry in the 20th Century: Diagnostics Industry and Drug Development in the Genomics Era: Mid 80s to Present

6.09 The Union of Biomarkers and Drug Development

6.10 Proteomics and Biomarker Discovery

6.11 Epigenomics and Companion Diagnostics

 

Chapter  7

Integration of Physiology, Genomics and Pharmacotherapy

7.1 Richard Lifton, MD, PhD of Yale University and Howard Hughes Medical Institute: Recipient of 2014 Breakthrough Prizes Awarded in Life Sciences for the Discovery of Genes and Biochemical Mechanisms that cause Hypertension

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

7.3 Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

7.4 Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

7.5 Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

7.6 Imaging Biomarker for Arterial Stiffness: Pathways in Pharmacotherapy for Hypertension and Hypercholesterolemia Management

7.7 Neuroprotective Therapies: Pharmacogenomics vs Psychotropic drugs and Cholinesterase Inhibitors

7.8 Metabolite Identification Combining Genetic and Metabolic Information: Genetic association links unknown metabolites to functionally related genes

7.9 Preserved vs Reduced Ejection Fraction: Available and Needed Therapies

7.10 Biosimilars: Intellectual Property Creation and Protection by Pioneer and by

7.11 Demonstrate Biosimilarity: New FDA Biosimilar Guidelines

 

Chapter 7.  Biopharma Today

8.1 A Great University engaged in Drug Discovery: University of Pittsburgh

8.2 Introduction – The Evolution of Cancer Therapy and Cancer Research: How We Got Here?

8.3 Predicting Tumor Response, Progression, and Time to Recurrence

8.4 Targeting Untargetable Proto-Oncogenes

8.5 Innovation: Drug Discovery, Medical Devices and Digital Health

8.6 Cardiotoxicity and Cardiomyopathy Related to Drugs Adverse Effects

8.7 Nanotechnology and Ocular Drug Delivery: Part I

8.8 Transdermal drug delivery (TDD) system and nanotechnology: Part II

8.9 The Delicate Connection: IDO (Indolamine 2, 3 dehydrogenase) and Cancer Immunology

8.10 Natural Drug Target Discovery and Translational Medicine in Human Microbiome

8.11 From Genomics of Microorganisms to Translational Medicine

8.12 Confined Indolamine 2, 3 dioxygenase (IDO) Controls the Homeostasis of Immune Responses for Good and Bad

 

Chapter 9. BioPharma – Future Trends

9.1 Artificial Intelligence Versus the Scientist: Who Will Win?

9.2 The Vibrant Philly Biotech Scene: Focus on KannaLife Sciences and the Discipline and Potential of Pharmacognosy

9.3 The Vibrant Philly Biotech Scene: Focus on Computer-Aided Drug Design and Gfree Bio, LLC

9.4 Heroes in Medical Research: The Postdoctoral Fellow

9.5 NIH Considers Guidelines for CAR-T therapy: Report from Recombinant DNA Advisory Committee

9.6 1st Pitch Life Science- Philadelphia- What VCs Really Think of your Pitch

9.7 Multiple Lung Cancer Genomic Projects Suggest New Targets, Research Directions for Non-Small Cell Lung Cancer

9.8 Heroes in Medical Research: Green Fluorescent Protein and the Rough Road in Science

9.9 Issues in Personalized Medicine in Cancer: Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing

9.10 The SCID Pig II: Researchers Develop Another SCID Pig, And Another Great Model For Cancer Research

Epilogue

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metabolomics-seriesdindividualred-page2

Metabolic Genomics & Pharmaceutics

2015

http://www.amazon.com/dp/B012BB0ZF0

 

Author, Curator and Editor

Larry H Bernstein, MD, FCAP

Chief Scientific Officer

Leaders in Pharmaceutical Business Intelligence

Larry.bernstein@gmail.com

Chapter 1: Metabolic Pathways

1.1            Carbohydrate Metabolism

1.2            Studies of Respiration Lead to Acetyl CoA

1.3            Pentose Shunt, Electron Transfer, Galactose, more Lipids in brief

1.4            The Multi-step Transfer of Phosphate Bond and Hydrogen Exchange Energy

1.5            Diabetes Mellitus

1.6            Glycosaminoglycans, Mucopolysaccharides, L-iduronidase, Enzyme Therapy

Chapter 2: Lipid Metabolism

2.1            Lipid Classification System

2.2            Essential Fatty Acids

2.3            Lipid Oxidation and Synthesis of Fatty Acids

2.4            Cholesterol and Regulation of Liver Synthetic Pathways

2.5            Sex hormones, Adrenal cortisol, Prostaglandins

2.6            Cytoskeleton and Cell Membrane Physiology

2.7            Pharmacological Action of Steroid hormone

Chapter 3: Cell Signaling

3.1            Signaling and Signaling Pathways

3.2            Signaling Transduction Tutorial

3.3            Selected References to Signaling and Metabolic Pathways in Leaders in Pharmaceutical Intelligence

3.4            Integrins, Cadherins, Signaling and the Cytoskeleton

3.5            Complex Models of Signaling: Therapeutic Implications

3.6            Functional Correlates of Signaling Pathways

Chapter 4: Protein Synthesis and Degradation

4.1            The Role and Importance of Transcription Factors

4.2            RNA and the Transcription of the Genetic Code

4.3            9:30 – 10:00, 6/13/2014, David Bartel “MicroRNAs, Poly(A) tails and Post-transcriptional Gene Regulation

4.4            Transcriptional Silencing and Longevity Protein Sir2

4.5            Ca2+ Signaling: Transcriptional Control

4.6            Long Noncoding RNA Network regulates PTEN Transcription

4.7            Zinc-Finger Nucleases (ZFNs) and Transcription Activator–Like Effector Nucleases (TALENs)

4.8            Cardiac Ca2+ Signaling: Transcriptional Control

4.9            Transcription Factor Lyl-1 Critical in Producing Early T-Cell Progenitors

4.10            Human Frontal Lobe Brain: Specific Transcriptional Networks

4.11            Somatic, Germ-cell, and Whole Sequence DNA in Cell Lineage and Disease

Chapter 5:  Sub-cellular Structure

5.1            Mitochondria: Origin from Oxygen free environment, Role in Aerobic Glycolysis and Metabolic Adaptation

5.2            Mitochondrial Metabolism and Cardiac Function

5.3            Mitochondria: More than just the “Powerhouse of the Cell”

5.4            Mitochondrial Fission and Fusion: Potential Therapeutic Targets?

5.5            Mitochondrial Mutation Analysis might be “1-step” Away

5.6            Autophagy-Modulating Proteins and Small Molecules Candidate Targets for Cancer Therapy: Commentary of Bioinformatics Approaches

5.7            Chromatophagy, A New Cancer Therapy: Starve The Diseased Cell Until It Eats Its Own DNA

5.8           A Curated Census of Autophagy-Modulating Proteins and Small Molecules Candidate Targets for Cancer Therapy

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

Chapter 6: Proteomics

6.1            Proteomics, Metabolomics, Signaling Pathways, and Cell Regulation: a Compilation of Articles in the Journal http://pharmaceuticalintelligence.com

6.2            A Brief Curation of Proteomics, Metabolomics, and Metabolism

6.3            Using RNA-seq and Targeted Nucleases to Identify Mechanisms of Drug Resistance in Acute Myeloid Leukemia, SK Rathe in Nature, 2014

6.4            Proteomics – The Pathway to Understanding and Decision-making in Medicine

6.5            Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

6.6           Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

6.7            Genomics, Proteomics and Standards

6.8            Proteins and Cellular Adaptation to Stress

6.9            Genes, Proteomes, and their Interaction

6.10           Regulation of Somatic Stem Cell Function

6.11           Scientists discover that Pluripotency factor NANOG is also active in Adult Organism

Chapter 7: Metabolomics

7.1            Extracellular Evaluation of Intracellular Flux in Yeast Cells

7.2            Metabolomic Analysis of Two Leukemia Cell Lines Part I

7.3            Metabolomic Analysis of Two Leukemia Cell Lines Part II

7.4            Buffering of Genetic Modules involved in Tricarboxylic Acid Cycle Metabolism provides Homeomeostatic Regulation

7.5            Metabolomics, Metabonomics and Functional Nutrition: The Next Step in Nutritional Metabolism and Biotherapeutics

7.6            Isoenzymes in Cell Metabolic Pathways

7.7            A Brief Curation of Proteomics, Metabolomics, and Metabolism

7.8            Metabolomics is about Metabolic Systems Integration

7.9             Mechanisms of Drug Resistance

7.10           Development Of Super-Resolved Fluorescence Microscopy

7.11            Metabolic Reactions Need Just Enough

Chapter 8.  Impairments in Pathological States: Endocrine Disorders; Stress Hypermetabolism and CAncer

8.1           Omega3 Fatty Acids, Depleting the Source, and Protein Insufficiency in Renal Disease

8.2             Liver Endoplasmic Reticulum Stress and Hepatosteatosis

8.3            How Methionine Imbalance with Sulfur Insufficiency Leads to Hyperhomocysteinemia

8.4            AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth InVivo

8.5           A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

8.6            Mitochondrial Damage and Repair under Oxidative Stress

8.7            Metformin, Thyroid Pituitary Axis, Diabetes Mellitus, and Metabolism

8.8            Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

8.9            Social Behavior Traits Embedded in Gene Expression

8.10          A Future for Plasma Metabolomics in Cardiovascular Disease Assessment

Chapter 9: Genomic Expression in Health and Disease 

9.1            Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

9.2            BRCA1 a Tumour Suppressor in Breast and Ovarian Cancer – Functions in Transcription, Ubiquitination and DNA Repair

9.3            Metabolic Drivers in Aggressive Brain Tumors

9.4            Modified Yeast Produces a Range of Opiates for the First time

9.5            Parasitic Plant Strangleweed Injects Host With Over 9,000 RNA Transcripts

9.6            Plant-based Nutrition, Neutraceuticals and Alternative Medicine: Article Compilation the Journal

9.7            Reference Genes in the Human Gut Microbiome: The BGI Catalogue

9.8            Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

9.9            HDL-C: Target of Therapy – Steven E. Nissen, MD, MACC, Cleveland Clinic vs Peter Libby, MD, BWH

Summary 

Epilogue


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