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Real Time Coverage @BIOConvention #BIO2019: Precision Medicine Beyond Oncology June 5 Philadelphia PA

Reporter: Stephen J Williams PhD @StephenJWillia2

Precision Medicine has helped transform cancer care from one-size-fits-all chemotherapy to a new era, where patients’ tumors can be analyzed and therapy selected based on their genetic makeup. Until now, however, precision medicine’s impact has been far less in other therapeutic areas, many of which are ripe for transformation. Efforts are underway to bring the successes of precision medicine to neurology, immunology, ophthalmology, and other areas. This move raises key questions of how the lessons learned in oncology can be used to advance precision medicine in other fields, what types of data and tools will be important to personalizing treatment in these areas, and what sorts of partnerships and payer initiatives will be needed to support these approaches and their ultimate commercialization and use. The panel will also provide an in depth look at precision medicine approaches aimed at better understanding and improving patient care in highly complex disease areas like neurology.
Speaker panel:  The big issue now with precision medicine is there is so much data and hard to put experimental design and controls around randomly collected data.
  • The frontier is how to CURATE randomly collected data to make some sense of it
  • One speaker was at a cancer meeting and the oncologist had no idea what to make of genomic reports they were given.  Then there is a lack of action or worse a misdiagnosis.
  • So for e.g. with Artificial Intelligence algorithms to analyze image data you can see things you can’t see with naked eye but if data quality not good the algorithms are useless – if data not curated properly data is wasted
Data needs to be organized and curated. 
If relying of AI for big data analysis the big question still is: what are the rates of false negative and false positives?  Have to make sure so no misdiagnosis.

Please follow LIVE on TWITTER using the following @ handles and # hashtags:

@Handles

@pharma_BI

@AVIVA1950

@BIOConvention

# Hashtags

#BIO2019 (official meeting hashtag)

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Personalized Immunotherapy: The Immuno-Oncology Summit August 30-31 2016 Boston MA

Reporter: Stephen J Williams, PhD

 

ANNOUNCEMENT

 

Leaders in Pharmaceutical Business intelligence (LPBI) Group will cover in Real Time using Social Media

The CHI’S 4TH ANNUAL IMMUNO-ONCOLOGY SUMMIT – Personalized Immunotherapy

Personalized Oncology in the Genomic Era: Expanding the Druggable Space

Aviva Lev-Ari, PhD, RN

will be streaming LIVE from the Marriott Long Wharf Hotel in Boston, MA

REGISTRATION

https://chidb.com/reg/imx/reg.asp

PROGRAM

http://www.immuno-oncologysummit.com/uploadedFiles/Immuno_Oncology_Summit/Agenda/16/2016-The-Immuno-Oncology-Summit-Brochure.pdf

 

 

Plenary Keynotes

TUESDAY | AUGUST 30

Matthew Goldstein

4:00 A New Era of Personalized Therapy: Using Tumor Neoantigens to Unlock the Immune System

Matthew J. Goldstein, M.D., Ph.D., Director, Translational Medicine, Neon Therapeutics, Inc.

Neon Therapeutics, Inc. launched in 2015 to focus on advancing neoantigen biology to improve cancer patient care. A neoantigen-based product engine will allow Neon to develop further treatment modalities including next-generation vaccines and T cell therapies targeting both personalized as well as shared neoantigens. The company’s first trial will launch later this year investigating the combination of a personalized, vaccine with nivolumab in advanced Melanoma, NSCLC, and Bladder Cancer.

Michael Rosenzweig

4:30 Emerging Innate Immune Targets for Enhancing Adaptive Anti-Tumor Responses

Michael Rosenzweig, Ph.D., Executive Director, Biology-Discovery, IMR Early Discovery, Merck Research Laboratories

Novel cancer immunotherapies targeting T cell checkpoint proteins have emerged as powerful tools to induce profound, durable regression and remission of many types of cancer. Despite these advances, multiple studies have demonstrated that not all patients respond to these therapies, and the ability to predict which patients may respond is limited. Harnessing the innate immune system to augment the adaptive anti-tumor response represents an attractive target for therapy, which has the potential to enhance both the percentage and rate of response to checkpoint blockade.

 

Morganna Freeman

5:00 Reading Tea Leaves:
The Dilemma of Prediction and Prognosis in Immunotherapy

Morganna Freeman, D.O., Associate Director, Melanoma & Cutaneous Oncology Program, The Angeles Clinic and Research Institute

With the rapid expansion of immunotherapeutics in oncology, scientifically significant advances have been made with both the depth and duration of antitumor responses. However, not all patients benefit, or quickly relapse, thus much scientific inquiry has been devoted to appropriate patient selection and how such obstacles might be overcome. While more is known about potential biomarkers, accurate prognostication persists as a knowledge gap, and efforts to bridge it will be discussed here.

Personalized Immunotherapy | The Immuno-Oncology Summit
August 30-31, 2016 | Marriott Long Wharf Hotel – Boston, MA

Personalized Immunotherapy
Personalized Oncology in the Genomic Era: Expanding the Druggable Space
August 30-31, 2016 | Learn More | Sponsorship & Exhibit Opportunities | Register by July 29 & SAVE up to $200!

Fueled with advances in genomic technologies, personalized oncology promises to innovate cancer therapy and target the previously undruggable space. Developments in immune checkpoint inhibitors, cancer vaccines, and adoptive T-cell therapies, as well as biomarker-driven immuno-oncology clinical trials, are enabling the next generation of cancer therapy. Cambridge Healthtech Institute’s Inaugural Personalized Immunotherapy meeting brings together clinical immuno-oncologists and thought leaders from pharmaceutical and biotech companies, and leading academic teams to share research and case studies in implementing patient-centric approaches to using the immune system to beat cancer.

TUMOR NEOANTIGENS FOR PERSONALIZED IMMUNOTHERAPY

Basics of Personalized Immunotherapy: What Is a Good Antigen?
Pramod K. Srivastava, M.D., Ph.D., Professor, Immunology and Medicine, Director, Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut School of Medicine

Novel Antibodies against Immunogenic Neoantigens
Philip M. Arlen, M.D., President & CEO, Precision Biologics, Inc.

PD-1 Blockade in Tumors with Mismatch-Repair Deficiency
Luis Alberto Diaz, M.D., Associate Professor, Oncology, Johns Hopkins Sidney Kimmel Comprehensive Cancer Center

PERSONALIZED IMMUNOTHERAPY WITH CANCER VACCINES

Cancer Vaccines in the Era of Checkpoint Inhibitors
Keith L. Knutson, Ph.D., Professor, Immunology, Mayo Clinic

Developing Therapeutic Cancer Vaccine Strategies for Prostate Cancer
Ravi Madan, M.D., Clinical Director, Genitourinary Malignancies Branch, National Cancer Institute, National Institutes of Health

Getting Very Personal: Fully Individualized Tumor Neoantigen-Based Vaccine Approaches to Cancer Therapy
Karin Jooss, Ph.D., CSO, Gritstone Oncology

Approaches to Assess Tumor Mutation Load for Selecting Patients for Cancer Immunotherapy
John Simmons, Ph.D., Manager, Research Services, Personal Genome Diagnostics

In situ Vaccination for Lymphoma
Joshua Brody, M.D., Director, Lymphoma Immunotherapy Program, Icahn School of Medicine at Mount Sinai

Immunotherapy Using Ad5 [E1-, E2b-] Vector Vaccines in the Cancer MoonShot 2020 Program
Frank R. Jones, Ph.D., Chairman & CEO, Etubics Corporation

PERSONALIZED CELL THERAPY

Integration of Natural Killer-Based Therapy into the Treatment of Lymphoma
Andrew M. Evens, D.O., Professor and Chief, Hematology/Oncology, Tufts University School of Medicine; Director, Tufts Cancer Center

Dendritic Cells: Personalized Cancer Vaccines and Inducers of Multi-Epitope-Specific T Cells for Adoptive Cell Therapy
Pawel Kalinski, M.D., Ph.D., Professor, Surgery, Immunology, and Bioengineering, University of Pittsburgh School of Medicine, University of Pittsburgh Cancer Institute

Mesothelin-Targeted CAR T-Cell Therapy for Solid Tumors
Prasad S. Adusumilli, M.D., FACS, Deputy Chief of Translational & Clinical Research, Thoracic Surgery, Memorial Sloan-Kettering Cancer Center

Synthetic Regulation of T Cell Therapies Adds Safety and Enhanced Efficacy to Previously Unpredicted Therapies
David M. Spencer, Ph.D., CSO, Bellicum Pharmaceuticals

Long-Term Relapse-Free Survival of Patients with Acute Myeloid Leukemia (AML) Receiving a Telomerase- Engineered Dendritic Cell Immunotherapy
Jane Lebkowski, Ph.D., President & CSO, Research and Development, Asterias Biotherapeutics

Activated and Exhausted Tumor Infiltrating B Cells in Non-Small Cell Lung Cancer Patients Present Antigen and Influence the Phenotype of CD4 Tumor Infiltrating T Cells
Tullia Bruno, Ph.D., Research Assistant Professor, Immunology, University of Pittsburgh

About the Immuno-Oncology Summit

CHI’s 4th Annual Immuno-Oncology Summit has been designed to support a coordinated effort by industry players to bring commercial immunotherapies and immunotherapy combinations through clinical development and into the market. This weeklong, nine-meeting set will include topics ranging from early discovery through clinical development as well as emerging areas such as oncolytic virotherapy. Overall, this event will provide a focused look at how researchers are applying new science and technology in the development of the next generation of effective and safe immunotherapies.

Monday, August 29 –
Tuesday, August 30
Tuesday, August 30 –
Wednesday, August 31
Thursday, September 1 –
Friday, September 2
Immunomodulatory Antibodies Combination Immunotherapy Adoptive T Cell Therapy
Oncolytic Virotherapy Personalized Immunotherapy Biomarkers for Immuno-Oncology
Training Seminar: Immunology for Drug Discovery Scientists Preclinical & Translational Immuno-Oncology Clinical Trials for Cancer Immunotherapy

For more info about sponsorship opportunities, including podium presentations and 1-2-1 meetings, please contact:

Companies A-K
Ilana Quigley
Sr Business Development Manager
781-972-5457
iquigley@healthtech.com
Companies L-Z:
Joe Vacca
Associate Director, Business Development
781-972-5431
jvacca@healthtech.com

For conference updates please visit
Immuno-OncologySummit.com/Personalized-Immunotherapy

Cambridge Healthtech Institute, 250 First Avenue, Suite 300, Needham, MA 02494 healthtech.com
Tel: 781-972-5400 | Fax: 781-972-5425

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Recent Research On SMAD4 In Pancreatic Cancer

Curator: David Orchard-Webb, PhD

 

Deleted in Pancreatic Cancer, locus 4 (DPC4) officially known as SMAD4 is a component of the Transforming Growth Factor Beta (TGFß) pathway with tumour suppressive properties. As its name suggests it is frequently lost in pancreatic cancer, although through a variety of mechanisms in addition to gene deletion. The loss of SMAD4 is important in the progression of pancreatic intraepithelial neoplasia (PanIN) towards pancreatic ductal adenocarcinoma (PDAC). The expression of SMAD4 can suppress metastasis, angiogenesis, and cancer stem-like cell generation. SMAD4 can promote cancer cell apoptosis through a recently described mechanism involving a lethal epithelial to mesenchymal transition (EMT). SMAD4 status has a predictive role in pancreatic cancer personalised medicine. This curation categorises recent publications of note regarding SMAD4.

 

Role of SMAD4 in neoplastic progression towards PDAC

 

Garcia-Carracedo, Dario, Chih-Chieh Yu, Nathan Akhavan, Stuart A. Fine, Frank Schönleben, Naoki Maehara, Dillon C. Karg, et al. ‘Smad4 Loss Synergizes with TGFα Overexpression in Promoting Pancreatic Metaplasia, PanIN Development, and Fibrosis’. Edited by Ilse Rooman. PLOS ONE 10, no. 3 (24 March 2015): e0120851. doi:10.1371/journal.pone.0120851.

 

Norris, A M, A Gore, A Balboni, A Young, D S Longnecker, and M Korc. ‘AGR2 Is a SMAD4-Suppressible Gene That Modulates MUC1 Levels and Promotes the Initiation and Progression of Pancreatic Intraepithelial Neoplasia’. Oncogene 32, no. 33 (15 August 2013): 3867–76. doi:10.1038/onc.2012.394.

 

Leung, Lisa, Nikolina Radulovich, Chang-Qi Zhu, Dennis Wang, Christine To, Emin Ibrahimov, and Ming-Sound Tsao. ‘Loss of Canonical Smad4 Signaling Promotes KRAS Driven Malignant Transformation of Human Pancreatic Duct Epithelial Cells and Metastasis’. Edited by Hidayatullah G Munshi. PLoS ONE 8, no. 12 (27 December 2013): e84366. doi:10.1371/journal.pone.0084366.

 

Mechanism of SMAD4 deactivation

 

Xia, Xiang, Kundong Zhang, Gang Cen, Tao Jiang, Jun Cao, Kejian Huang, Chen Huang, Qian Zhao, and Zhengjun Qiu. ‘MicroRNA-301a-3p Promotes Pancreatic Cancer Progression via Negative Regulation of SMAD4’. Oncotarget 6, no. 25 (28 August 2015): 21046–63. doi:10.18632/oncotarget.4124.

 

Murphy, Stephen J., Steven N. Hart, Geoffrey C. Halling, Sarah H. Johnson, James B. Smadbeck, Travis Drucker, Joema Felipe Lima, et al. ‘Integrated Genomic Analysis of Pancreatic Ductal Adenocarcinomas Reveals Genomic Rearrangement Events as Significant Drivers of Disease’. Cancer Research 76, no. 3 (1 February 2016): 749–61. doi:10.1158/0008-5472.CAN-15-2198.

 

Sawai, Yugo, Yuzo Kodama, Takahiro Shimizu, Yuji Ota, Takahisa Maruno, Yuji Eso, Akira Kurita, et al. ‘Activation-Induced Cytidine Deaminase Contributes to Pancreatic Tumorigenesis by Inducing Tumor-Related Gene Mutations’. Cancer Research 75, no. 16 (15 August 2015): 3292–3301. doi:10.1158/0008-5472.CAN-14-3028.

 

Demagny, Hadrien, and Edward M De Robertis. ‘Point Mutations in the Tumor Suppressor Smad4/DPC4 Enhance Its Phosphorylation by GSK3 and Reversibly Inactivate TGF-β Signaling’. Molecular & Cellular Oncology 3, no. 1 (2 January 2016): e1025181. doi:10.1080/23723556.2015.1025181.

 

Foster, David. ‘BxPC3 Pancreatic Cancer Cells Express a Truncated Smad4 Protein upon PI3K and mTOR Inhibition’. Oncology Letters, 28 January 2014. doi:10.3892/ol.2014.1833.

 

Hao, Jun, Shuyu Zhang, Yingqi Zhou, Cong Liu, Xiangui Hu, and Chenghao Shao. ‘MicroRNA 421 Suppresses DPC4/Smad4 in Pancreatic Cancer’. Biochemical and Biophysical Research Communications 406, no. 4 (25 March 2011): 552–57. doi:10.1016/j.bbrc.2011.02.086.

 

SMAD4 effects on cell motility

 

Zhang, Xueying, Junxia Cao, Yujun Pei, Jiyan Zhang, and Qingyang Wang. ‘Smad4 Inhibits Cell Migration via Suppression of JNK Activity in Human Pancreatic Carcinoma PANC‑1 Cells’. Oncology Letters, 7 April 2016. doi:10.3892/ol.2016.4427.

 

Kang, Ya ’an, Jianhua Ling, Rei Suzuki, David Roife, Xavier Chopin-Laly, Mark J. Truty, Deyali Chatterjee, et al. ‘SMAD4 Regulates Cell Motility through Transcription of N-Cadherin in Human Pancreatic Ductal Epithelium’. Edited by Neil A. Hotchin. PLoS ONE 9, no. 9 (29 September 2014): e107948. doi:10.1371/journal.pone.0107948.

 

Chen, Yu-Wen, Pi-Jung Hsiao, Ching-Chieh Weng, Kung-Kai Kuo, Tzu-Lei Kuo, Deng-Chyang Wu, Wen-Chun Hung, and Kuang-Hung Cheng. ‘SMAD4 Loss Triggers the Phenotypic Changes of Pancreatic Ductal Adenocarcinoma Cells’. BMC Cancer 14, no. 1 (2014): 1. https://bmccancer.biomedcentral.com/articles/10.1186/1471-2407-14-181.

 

SMAD4 effects on angiogenesis

 

Zhou, Zhichao, Juming Lu, Jingtao Dou, Zhaohui Lv, Xi Qin, and Jing Lin. ‘FHL1 and Smad4 Synergistically Inhibit Vascular Endothelial Growth Factor Expression’. Molecular Medicine Reports 7, no. 2 (February 2013): 649–53. doi:10.3892/mmr.2012.1202.

 

SMAD4 mediated repression of cancer stem-like cells

 

Hoshino, Yukari, Jun Nishida, Yoko Katsuno, Daizo Koinuma, Taku Aoki, Norihiro Kokudo, Kohei Miyazono, and Shogo Ehata. ‘Smad4 Decreases the Population of Pancreatic Cancer–Initiating Cells through Transcriptional Repression of ALDH1A1’. The American Journal of Pathology 185, no. 5 (2015): 1457–1470. http://www.sciencedirect.com/science/article/pii/S0002944015000802.

 

SMAD4 mediated growth inhibition/ apoptosis induction

 

David, Charles J., Yun-Han Huang, Mo Chen, Jie Su, Yilong Zou, Nabeel Bardeesy, Christine A. Iacobuzio-Donahue, and Joan Massagué. ‘TGF-β Tumor Suppression through a Lethal EMT’. Cell 164, no. 5 (February 2016): 1015–30. doi:10.1016/j.cell.2016.01.009.

 

Wang, Qi, Juanjuan Li, Wei Wu, Ruizhe Shen, He Jiang, Yuting Qian, Yanping Tang, et al. ‘Smad4-Dependent Suppressor Pituitary Homeobox 2 Promotes PPP2R2A-Mediated Inhibition of Akt Pathway in Pancreatic Cancer’. Oncotarget 7, no. 10 (8 March 2016): 11208–22. doi:10.18632/oncotarget.7158.

 

Poorly characterised targets of SMAD4

 

Fullerton, Paul T., Chad J. Creighton, and Martin M. Matzuk. ‘Insights Into SMAD4 Loss in Pancreatic Cancer From Inducible Restoration of TGF-β Signaling’. Molecular Endocrinology (Baltimore, Md.) 29, no. 10 (October 2015): 1440–53. doi:10.1210/me.2015-1102.

 

Li, Lei, Zhaoshen Li, Xiangyu Kong, Dacheng Xie, Zhiliang Jia, Weihua Jiang, Jiujie Cui, et al. ‘Down-Regulation of MicroRNA-494 via Loss of SMAD4 Increases FOXM1 and β-Catenin Signaling in Pancreatic Ductal Adenocarcinoma Cells’. Gastroenterology 147, no. 2 (August 2014): 485–497.e18. doi:10.1053/j.gastro.2014.04.048.

 

Drugs that restore SMAD4

 

Lin, Sheng-Zhang, Jin-Bo Xu, Xu Ji, Hui Chen, Hong-Tao Xu, Ping Hu, Liang Chen, et al. ‘Emodin Inhibits Angiogenesis in Pancreatic Cancer by Regulating the Transforming Growth Factor-Β/drosophila Mothers against Decapentaplegic Pathway and Angiogenesis-Associated microRNAs’. Molecular Medicine Reports 12, no. 4 (October 2015): 5865–71. doi:10.3892/mmr.2015.4158.

 

Predictive value of SMAD4 status in personalised medicine

 

Whittle, Martin C., Kamel Izeradjene, P. Geetha Rani, Libing Feng, Markus A. Carlson, Kathleen E. DelGiorno, Laura D. Wood, et al. ‘RUNX3 Controls a Metastatic Switch in Pancreatic Ductal Adenocarcinoma’. Cell 161, no. 6 (June 2015): 1345–60. doi:10.1016/j.cell.2015.04.048.

 

Boone, Brian A., Shirin Sabbaghian, Mazen Zenati, J. Wallis Marsh, A. James Moser, Amer H. Zureikat, Aatur D. Singhi, Herbert J. Zeh, and Alyssa M. Krasinskas. ‘Loss of SMAD4 Staining in Pre-Operative Cell Blocks Is Associated with Distant Metastases Following Pancreaticoduodenectomy with Venous Resection for Pancreatic Cancer’. Journal of Surgical Oncology 110, no. 2 (August 2014): 171–75. doi:10.1002/jso.23606.

 

Herman, Joseph M., Katherine Y. Fan, Aaron T. Wild, Laura D. Wood, Amanda L. Blackford, Ross C. Donehower, Manuel Hidalgo, et al. ‘Correlation of Smad4 Status With Outcomes in Patients Receiving Erlotinib Combined With Adjuvant Chemoradiation and Chemotherapy After Resection for Pancreatic Adenocarcinoma’. International Journal of Radiation Oncology*Biology*Physics 87, no. 3 (November 2013): 458–59. doi:10.1016/j.ijrobp.2013.06.2039.

 

Other Related Articles Published In This Open Access Online Journal Include The Following:

 

https://pharmaceuticalintelligence.com/2016/06/10/pancreatic-cancer-modeling-using-retrograde-viral-vector-delivery-and-in-vivo-crisprcas9-mediated-somatic-genome-editing/

https://pharmaceuticalintelligence.com/2015/04/10/wnt%CE%B2-catenin-signaling-7-10/

 

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Pharmacogenetics

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

The New Landscape of Pharmacogenetics  

Standardized Assays Are Driving Preemptive Genotyping and Personalized Drug Therapies

http://www.genengnews.com/gen-articles/pharmacogenetics-for-the-rest-of-us/5751/

  • For decades, genotyping has promised to serve as a practical means of relating genetic make-up and pharmacological efficiency—first at the level of patient groups and more recently at the level of individuals. Genotyping, however, still has a fairly limited role in determining which drug therapies, and which doses, should be used in specific circumstances.

    If genotyping is to find widespread adoption, it will have to overcome several barriers, most notably variation in assays and delay in reporting, difficulty in translating genotype into specific actions, and a perceived lack of economic and/or clinical value. Technological advances coupled with changes in the availability of genetic information will dramatically change the landscape of pharmacogenetics.

    The efficacy of any given drug therapy is dependent on a number of factors, most commonly described through the pharmacokinetic parameters of absorption, distribution, metabolism, and elimination (ADME). Together, these factors determine whether a patient will need increased or decreased dosages, or whether a given therapy will work at all in that patient. Additionally, these factors can determine drug-drug interactions for patients on polypharmacy.

  • Genotype Variants

    Although a detailed description of specific genotype variants is beyond the scope of this article, a brief survey of the diversity of genotypes is helpful to provide a sense of the complexity that is inherent in genotyping, which has, in some ways, slowed the adoption of pharmacogenetics. As an example, human leukocyte antigen (HLA) genes are among the most highly polymorphic genes; more than 3,600 HLA class II alleles have been described.

    More than 50 human cytochromes P450 (CYPs) have been identified, and most have at least several single nucleotide polymorphisms (SNPs), with CYP2D6 having over 100 identified SNPs. Specific combinations of polymorphisms are translated into star alleles, which are used to predict the impact on therapeutic response.

    As might be expected, any individual enzyme can metabolize multiple drugs, and most drugs can be metabolized by multiple enzymes. Drugs can also inhibit metabolizing enzymes, while metabolizing enzymes can activate drugs by converting prodrugs into active metabolites. Generally, changes in functional activity of the enzyme are translated clinically by categorizing patients as poor, intermediate, extensive, or ultrarapid metabolizers.

    The FDA has now included pharmacogenomics information in the labeling of 166 approved drugs, some of which include specific action to be taken based on biomarker information. Table 1summarizes the biomarkers and indications for the pharmacogenomics labels. The FDA labels rangefrom dosage and pharmacokinetics information to precautions and, in nine of the labels, boxed warnings to highlight potentially serious adverse reactions.

    Most pharmacogenetics assays are currently offered as laboratory-developed tests; therefore, there is a wide range in the specific variants that are reported for any given target. As noted above, CYP2D6 has over 100 identified SNPs, and laboratories report various numbers of star alleles. Historically, this is because most genotyping assays involve methods based on the multiplex polymerase chain reaction (PCR). Accordingly, in these assays, the cost or effort to perform the genotyping is approximately proportional to the size of the panel.

    Additionally, because some of the functional variants are copy number changes, multiple assays may be required (for example, quantitative PCR for copy number, plus PCR for genotyping). More recent advances in microarray technology make it possible to perform more complete genotyping and copy number analysis of known star alleles simultaneously across multiple genes, thus reducing the cost and increasing the efficiency of pharmacogenomics. For example, the Affymetrix DMET Axiom Assay can analyze over 4,000 genotypes across 900 genes along with copy number in a single assay.

    From a regulatory perspective, it is likely that the disparate technologies laboratories use to generate their pharmacogenetics results will coalesce into a few, defined FDA-cleared devices. Because arrays can reproducibly provide comprehensive genotyping and copy number information at low cost, analytical and clinical validity can be readily demonstrated in a regulatory submission.

    The translation of specific genotype combinations into actionable clinical utility is hampered by difficulties in interpretation. Part of this relates to the somewhat ambiguous notation of the impact of a given star allele; the designation “ultrametabolizer,” for example, does not obviously translate to a specific dose for a given individual.

    Additionally, parameters such as ethnicity, age, body mass index, and gender can influence the pharmacokinetics in any specific individual. The establishment of guidelines can assist the practitioner in utilizing pharmacogenetics information to make therapeutic selections. At the forefront of establishing guidelines is the Clinical Pharmacogenetics Implementation Consortium (CPIC), which provides guidelines centered around specific genes as well as for specific drugs.

  • Preemptive Genotyping

    Click Image To Enlarge +
    Physicians, who need to make therapeutic decisions quickly and cannot wait for genotype results, are increasingly looking at preemptive genotyping as a potential solution to improve treatment options. [iStock/D3Damon]

    In most cases, physicians need to make treatment decisions immediately and cannot wait for genotype results. The obvious solution to this is preemptive genotyping, which is being deployed at five academic medical institutions (Mayo Clinic, Mount Sinai, St. Jude Children’s Research Hospital, University of Florida and Shands Hospital, and Vanderbilt University Medical Center) as part of the Translational Pharmacogenetics Program.

    For preemptive genotyping to be widely deployed, the structure of electronic health records (EHRs) will need to evolve so that they enable the retrieval, storage, and reporting of complex genotyping data. Moreover, they will need to be able to provide the translation of star alleles with metabolizing status for specific drugs, dosing guidelines or suggestions for alternative drugs, and links to guidelines and other supporting information.

    The most sophisticated embodiments of EHRs will also take into account other information that can influence dosing contained within the EHR, such as the patient’s ethnicity, weight, sex, and other medications. Most EHRs lack such capabilities, but two trends will substantially alter this landscape.

    First, there is an increasing recognition of the role medical informatics plays in healthcare and an increased emphasis on this role at medical institutions, both academic and community-based. Second, the entry of high-tech giants such as Google and Apple into the medical informatics and large-scale genotyping/genetic analysis arena will accelerate the development of these tools.

    Third-party payers have generally been reluctant to pay for most pharmacogenetics tests. The paucity of prospective randomized clinical studies showing either clinical or economic utility remains a fundamental hurdle for widespread adoption of pharmacogenetics. A likely path for the generation of clinical data will be through large, publicly funded genotyping initiatives in combination with investigator-initiated studies that rely primarily on mining EHRs for dosing, adverse reaction, and outcome information.

    One such initiative is tied to the Million Veterans Program. It is mining data to explore the pharmacogenetics of metformin response in diabetics with renal disease.

    Another push may come from consumers who choose to proactively obtain their pharmacogenetics information. Such activity will heavily depend on the appropriate EHR and bioinformatics infrastructure at primary care centers as well as harmonization of analytical test methods. These requirements suggest that consumer-driven work will lag the efforts at academic medical centers.

  • Future Perspectives

    Future Perspectives

    The pace at which pharmacogenetics is incorporated into healthcare will increase due to factors such as the decreasing cost of genotyping, the installation of a medical informatics infrastructure, and increased consumer demand for personal genotyping information. Moreover, these factors will reinforce each other and help preemptive genotyping become the norm rather than the exception.

    As this trend gathers momentum, it will begin contributing to a virtuous cycle in which the increased availability of genotyping data associated with outcome information will permit the development of additional and more precise treatment algorithms. Technological advances in genotyping, most notably high-density genotyping at low cost with high reproducibility, and medical informatics will be key to making this a reality.

 

 

 

 

 

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A Revolutionary Approach in Brain Tumor Research

Author: Gail S. Thornton, M.A.

For the more than 680,000 Americans living with a brain tumor, there is a revolutionary research effort under way at the Cedars-Sinai Precision Medicine Initiative in Brain Cancer in Los Angeles to look at ways of using precision science to tailor personalized treatments for individuals with malignant brain tumors.

Brain Cancer Meets Precision Science

Brain cancer continues to be among the hardest of diseases to treat. Until now, most medical treatments for the most common, aggressive and lethal form of brain cancer, glioblastoma multiforme, which affects more than 138,000 Americans yearly, have been designed for the average patient. Given that every cancer is genetically unique, this “one-size-fits-all” drug treatment has not worked for brain cancer and for most solid cancers. Unfortunately, today’s standard-of-care, which includes surgical removal, radiation therapy, and chemotherapy, has only modest benefits with patients living on average 15 months after diagnosis.

“Precision Medicine, an innovative approach that takes into account individual differences in people’s genes, environments and lifestyles, only works when we apply ‘Precision Science’ to the effort,” notes Dr. Chirag Patil, M.D., Neurosurgeon & Program Director at Cedars-Sinai Medical Center. “If we want to treat cancer more effectively, we need a novel approach to cancer care. In our program, we use tumor genomics and precision science to build a holistic mathematical model of cancer that then can be used to develop new, personalized cancer treatments.  Right now, we’re focused on the most common type of brain cancer, but are developing a unique scientific process that could tackle ANY type of cancer.”

This past year, the White House launched the Precision Medicine Initiative to dramatically improve health and treatment through a $215 million investment in the President’s 2016 budget.  The Initiative will provide additional impetus to Precision Medicine’s approach to disease prevention and treatment that has already led to powerful new discoveries and several new treatment methods for critical diseases.

PMI photo.png

Caption: The Cedars-Sinai program uses precision science to build a mathematical virtual brain tumor for testing.

Image SOURCEhttp://www.drchiragpatil.com/main.html

Delivering Personalized Cancer Care Through Big Data And Virtual Simulations

Harnessing the power of big data, Dr. Patil’s program puts a patient’s brain tumor through next-generation genomic sequencing to establish a comprehensive profile of that specific brain cancer. Researchers, in collaboration with Cellworks Inc., a therapeutics design company, use this profile to build a mathematical “virtual“ tumor cell. The simulations are then compared to the real patient tumor cells that have been growing in Dr. Patil’s laboratory. The “real data” from experiments in the lab are used to confirm  the virtual tumor model – again, this is customized for each individual patient.

The next step is to run a virtual experiment where all FDA-approved targeted drug combinations are tried on the virtual tumor cell to identify the best drug combination that eradicates the cells for the specific brain tumor.  In the final step, researchers expose the patient’s real cancer cells to this unique and personalized drug combination to ensure that it effectively kills the patient’s cancer cells in the laboratory.

Spreading the Word

This effort is not someday in the future but is happening now, and has demonstrated remarkable progress in the last six months. Researchers expect to have data on 30 brain cancer patients from this precision medicine strategy by mid-2016. From this, they will develop an innovative randomized clinical trial, not simply to compare one drug to another, but rather compare this innovative Precision Medicine treatment algorithm to a current standard treatment regimen.

Learn More

For more information on this revolutionary approach, visit www.BrainTumorExpert.com, to learn more about Dr. Patil and his precision science approach to treating brain tumors.

REFERENCE

http://www.drchiragpatil.com/main.html

SOURCE

http://www.drchiragpatil.com/main.html

Other related articles:

http://www.rsc.org/chemistryworld/2016/02/junk-dna-genome-nessa-carey-book-review

http://www.genengnews.com/gen-news-highlights/advanced-immunotherapeutic-method-shows-promise-against-brain-cancer/81252433/

http://www.mdtmag.com/news/2015/11/blood-brain-barrier-opened-noninvasively-focused-ultrasound-first-time

http://www.biosciencetechnology.com/news/2015/11/protein-atlas-brain

 

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

2015

The 11th Annual Personalized Medicine Conference, November 18-19, 2015, Joseph B. Martin Conference Center of the Harvard New Research Building at Harvard Medical School

https://pharmaceuticalintelligence.com/2015/07/09/the-11th-annual-personalized-medicine-conference-november-18-19-2015-joseph-b-martin-conference-center-of-the-harvard-new-research-building-at-harvard-medical-school/

Silicon Valley 2015 Personalized Medicine World Conference, Mountain View, CA, January 26, 2015, 8:00AM to January 28, 2015, 3:30PM PST
https://pharmaceuticalintelligence.com/2015/01/08/silicon-valley-2015-personalized-medicine-world-conference-mountain-view-ca-january-26-2015-800am-to-january-28-2015-330pm-pst/

2014

10th Annual Personalized Medicine Conference at the Harvard Medical School, November 12-13, 2014, The Joseph B. Martin Conference Center at Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA
http://pharmaceuticalintelligence.com/2014/10/09/10th-annual-personalized-medicine-conference-at-the-harvard-medical-school-november-12-13-2014-hotel-commonwealth-boston-ma/

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RNA in synthetic biology

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

RNA May Surpass DNA in Precision Medicine

http://www.genengnews.com/gen-news-highlights/rna-may-surpass-dna-in-precision-medicine/81252507/

 

Scientists based at the Translational Genomics Research Institute have published a review heralding the promise of RNA sequencing (RNA-seq) for precision medicine. The scientists also note that progress will be needed on analytical, bioinformatics, and regulatory fronts, particularly in light of the transcriptome’s variety, dynamism, and wealth of detail. In this image, one aspect of RNA-seq is shown, the alignment with intron-split short reads. It reflects the alignment of mRNA sequence obtained via high-throughput sequencing and the expected behavior of the alignment to the reference genome when the read falls in an exon–exon junction. [Rgocs, Wikipedia]
http://www.genengnews.com/Media/images/GENHighlight/thumb_Mar22_2016_Rgocs_RNASeqAlignment1872484040.jpg

 

It’s not an either/or situation. Both DNA sequencing and RNA sequencing hold clinical promise—diagnostically, prognostically, and therapeutically. It must be said, however, that RNA sequencing reflects the dynamic nature of gene expression, shifting with the vagaries of health and disease. Also, RNA sequencing captures more biochemical complexity, in the sense that it allows for the detection of a wide variety of RNA species, including mRNA, noncoding RNA, pathogen RNA, chimeric gene fusions, transcript isoforms, and splice variants, and provides the capability to quantify known, predefined RNA species and rare RNA transcript variants within a sample.

All these potential advantages were cited in a paper that appeared March 21 in Nature Reviews Genetics, in an article entitled, “Translating RNA Sequencing into Clinical Diagnostics: Opportunities and Challenges.” The paper, contributed by scientists based at the Translational Genomics Research Institute (TGen), was definitely optimistic about the clinical utility of RNA sequencing, but it also highlighted the advances that would have to occur if RNA sequencing is to achieve its promise.

In general, the very things that make RNA sequencing so interesting are the same things that make it so challenging. RNA sequencing would take the measure of a world—the transcriptome—that is incredibly rich. To capture all the relevant subtleties of the transcriptome, scientists will have to develop sensitive, precise, and trustworthy analytical techniques. What’s more, scientists will need to find efficient and reliable means of processing and interpreting all of the transcriptome data they will collect. Finally, they will need to continue integrating RNA-based knowledge with DNA-based knowledge. That is, RNA sequencing results can be used to guide the interpretation of DNA sequencing results.

In their Nature Reviews Genetics paper, the TGen scientists review the state of RNA sequencing and offer specific recommendations to enhance its clinical utility. The TGen scientists make a special point about the promise held by extracellular RNA (exRNA). Because exRNA can be monitored by simply taking a blood sample, as opposed to taking a tumor biopsy, it could serve as a noninvasive diagnostic indicator of disease.

“Detection of gene fusions and differential expression of known disease-causing transcripts by RNA-seq represent some of the most immediate opportunities,” wrote the authors. “However, it is the diversity of RNA species detected through RNA-seq that holds new promise for the multi-faceted clinical applicability of RNA-based measures, including the potential of extracellular RNAs as non-invasive diagnostic indicators of disease.”

The first test measuring exRNA was released earlier this year, the paper said, for use measuring specific exRNAs in lung cancer patients. And, the potential for using RNA-seq in cancer is expanding rapidly. Commercial RNA-seq tests are now available, and they provide the opportunity for clinicians to profile cancer more comprehensively and use this information to guide treatment selection for their patients.

In addition, the authors reported on several recent applications for RNA-seq in the diagnosis and management of infectious diseases, such as monitoring for drug-resistant populations during therapy and tracking the origin and spread of the Ebola virus.

Despite these advances, the authors also sounded a few cautionary notes. “There are currently few agreed upon methods for isolation or quantitative measurements and a current lack of quality controls that can be used to test platform accuracy and sample preparation quality,” they wrote. “Analytical, bioinformatics, and regulatory challenges exist, and ongoing efforts toward the establishment of benchmark standards, assay optimization for clinical conditions and demonstration of assay reproducibility are required to expand the clinical utility of RNA-seq.”

Overall, the authors remain hopeful that precision medicine will embrace RNA sequencing. For example, lead author Sara Byron, research assistant professor in TGen’s Center for Translational Innovation, said, “RNA is a dynamic and diverse biomolecule with an essential role in numerous biological processes. From a molecular diagnostic standpoint, RNA-based measurements have the potential for broad application across diverse areas of human health, including disease diagnosis, prognosis, and therapeutic selection.”

 

RNA Bacteriophages May Open New Path to Fighting Antibiotic-Resistant Infections

http://www.genengnews.com/gen-news-highlights/rna-bacteriophages-may-open-new-path-to-fighting-antibiotic-resistant-infections/81252521/

http://www.genengnews.com/Media/images/GENHighlight/thumb_Mar25_2016_Wikimedia_RNABacteriophages2091791481.jpg

Micrograph image of RNA bacteriophages attached to part of the bacterium E. coli. A new study at Washington University School of Medicine in St. Louis suggests that bacteriophages made of RNA, a close chemical cousin of DNA, likely play a much larger role in shaping the bacterial makeup of worldwide habitats than previously recognized. [Graham Beards/Wikimedia]

Scientists at Washington University School of Medicine in St. Louis report that bacteriophages made of RNA likely play a much larger role in shaping the bacterial makeup of worldwide habitats than previously recognized. Their study (“Hyperexpansion of RNA Bacteriophage Diversity”), published in PLOS Biology, identified 122 new types of RNA bacteriophages in diverse ecological niches, providing an opportunity for scientists to define their contributions to ecology and potentially to exploit them as novel tools to fight bacterial infections, particularly those that are resistant to antibiotics.

“Lots of DNA bacteriophages have been identified, but there’s an incredible lack of understanding about RNA bacteriophages,” explained senior author David Wang, Ph.D., associate professor of molecular microbiology. “They have been largely ignored—relatively few were known to exist, and for the most part, scientists haven’t bothered to look for them. This study puts RNA bacteriophages on the map and opens many new avenues of exploration.”

Dr. Wang estimates that of the more than 1500 bacteriophages that have been identified, 99% of them have DNA genomes. The advent of large-scale genome sequencing has helped scientists identify DNA bacteriophages in the human gut, skin, and blood, as well as in the environment, but few researchers have looked for RNA bacteriophages in those samples (doing so requires that RNA be isolated from the samples and then converted back to DNA before sequencing).

As part of the new study, first author and graduate student Siddharth Krishnamurthy, and the team, including Dan Barouch, M.D., Ph.D., of Beth Israel Deaconess Medical Center and Harvard Medical School, identified RNA bacteriophages by analyzing data from samples taken from the environment, such as oceans, sewage, and soils, and from aquatic invertebrates including crabs, sponges, and barnacles, as well as insects, mice, and rhesus macaques.

RNA bacteriophages have been shown to infect Gram-negative bacteria, which have become increasingly resistant to antibiotics and are the source of many infections in health care settings. But the researchers also showed for the first time that these bacteriophages also may infect Gram-positive bacteria, which are responsible for strep and staph infections as well as MRSA (methicillin-resistant Staphylococcus aureus).

“What we know about RNA bacteriophages in any environment is limited,” Dr. Wang said. “But you can think of bacteriophages and bacteria as having a predator–prey relationship. We need to understand the dynamics of that relationship. Eventually, we’d like to manipulate that dynamic to use phages to selectively kill particular bacteria.”

 

Hyperexpansion of RNA Bacteriophage Diversity

Siddharth R. Krishnamurthy , Andrew B. Janowski , Guoyan Zhao , Dan Barouch
24 Mar 2016 | PLOS Biology   
   http://dx.doi.org:/10.1371/journal.pbio.1002409

Bacteriophage modulation of microbial populations impacts critical processes in ocean, soil, and animal ecosystems. However, the role of bacteriophages with RNA genomes (RNA bacteriophages) in these processes is poorly understood, in part because of the limited number of known RNA bacteriophage species. Here, we identify partial genome sequences of 122 RNA bacteriophage phylotypes that are highly divergent from each other and from previously described RNA bacteriophages. These novel RNA bacteriophage sequences were present in samples collected from a range of ecological niches worldwide, including invertebrates and extreme microbial sediment, demonstrating that they are more widely distributed than previously recognized. Genomic analyses of these novel bacteriophages yielded multiple novel genome organizations. Furthermore, one RNA bacteriophage was detected in the transcriptome of a pure culture of Streptomyces avermitilis, suggesting for the first time that the known tropism of RNA bacteriophages may include gram-positive bacteria. Finally, reverse transcription PCR (RT-PCR)-based screening for two specific RNA bacteriophages in stool samples from a longitudinal cohort of macaques suggested that they are generally acutely present rather than persistent.

Bacteriophages (viruses that infect bacteria) can alter biological processes in numerous ecosystems. While there are numerous studies describing the role of bacteriophages with DNA genomes in these processes, the role of bacteriophages with RNA genomes (RNA bacteriophages) is poorly understood. This gap in knowledge is in part because of the limited diversity of known RNA bacteriophages. Here, we begin to address the question by identifying 122 novel RNA bacteriophage partial genome sequences present in metagenomic datasets that are highly divergent from each other and previously described RNA bacteriophages. Additionally, many of these sequences contained novel properties, including novel genes, segmentation, and host range, expanding the frontiers of RNA bacteriophage genomics, evolution, and tropism. These novel RNA bacteriophage sequences were globally distributed from numerous ecological niches, including animal-associated and environmental habitats. These findings will facilitate our understanding of the role of the RNA bacteriophage in microbial communities. Furthermore, there are likely many more unrecognized RNA bacteriophages that remain to be discovered.

 

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A Reconstructed View of Personalized Medicine

Author: Larry H. Bernstein, MD, FCAP

 

There has always been Personalized Medicine if you consider the time a physician spends with a patient, which has dwindled. But the current recognition of personalized medicine refers to breakthrough advances in technological innovation in diagnostics and treatment that differentiates subclasses within diagnoses that are amenable to relapse eluding therapies.  There are just a few highlights to consider:

  1. We live in a world with other living beings that are adapting to a changing environmental stresses.
  2. Nutritional resources that have been available and made plentiful over generations are not abundant in some climates.
  3. Despite the huge impact that genomics has had on biological progress over the last century, there is a huge contribution not to be overlooked in epigenetics, metabolomics, and pathways analysis.

A Reconstructed View of Personalized Medicine

There has been much interest in ‘junk DNA’, non-coding areas of our DNA are far from being without function. DNA has two basic categories of nitrogenous bases: the purines (adenine [A] and guanine [G]), and the pyrimidines (cytosine [C], thymine [T], and  no uracil [U]),  while RNA contains only A, G, C, and U (no T).  The Watson-Crick proposal set the path of molecular biology for decades into the 21st century, culminating in the Human Genome Project.

There is no uncertainty about the importance of “Junk DNA”.  It is both an evolutionary remnant, and it has a role in cell regulation.  Further, the role of histones in their relationship the oligonucleotide sequences is not understood.  We now have a large output of research on noncoding RNA, including siRNA, miRNA, and others with roles other than transcription. This requires major revision of our model of cell regulatory processes.  The classic model is solely transcriptional.

  • DNA-> RNA-> Amino Acid in a protein.

Redrawn we have

  • DNA-> RNA-> DNA and
  • DNA->RNA-> protein-> DNA.

Neverthess, there were unrelated discoveries that took on huge importance.  For example, since the 1920s, the work of Warburg and Meyerhoff, followed by that of Krebs, Kaplan, Chance, and others built a solid foundation in the knowledge of enzymes, coenzymes, adenine and pyridine nucleotides, and metabolic pathways, not to mention the importance of Fe3+, Cu2+, Zn2+, and other metal cofactors.  Of huge importance was the work of Jacob, Monod and Changeux, and the effects of cooperativity in allosteric systems and of repulsion in tertiary structure of proteins related to hydrophobic and hydrophilic interactions, which involves the effect of one ligand on the binding or catalysis of another,  demonstrated by the end-product inhibition of the enzyme, L-threonine deaminase (Changeux 1961), L-isoleucine, which differs sterically from the reactant, L-threonine whereby the former could inhibit the enzyme without competing with the latter. The current view based on a variety of measurements (e.g., NMR, FRET, and single molecule studies) is a ‘‘dynamic’’ proposal by Cooper and Dryden (1984) that the distribution around the average structure changes in allostery affects the subsequent (binding) affinity at a distant site.

What else do we have to consider?  The measurement of free radicals has increased awareness of radical-induced impairment of the oxidative/antioxidative balance, essential for an understanding of disease progression.  Metal-mediated formation of free radicals causes various modifications to DNA bases, enhanced lipid peroxidation, and altered calcium and sulfhydryl homeostasis. Lipid peroxides, formed by the attack of radicals on polyunsaturated fatty acid residues of phospholipids, can further react with redox metals finally producing mutagenic and carcinogenic malondialdehyde, 4-hydroxynonenal and other exocyclic DNA adducts (etheno and/or propano adducts). The unifying factor in determining toxicity and carcinogenicity for all these metals is the generation of reactive oxygen and nitrogen species. Various studies have confirmed that metals activate signaling pathways and the carcinogenic effect of metals has been related to activation of mainly redox sensitive transcription factors, involving NF-kappaB, AP-1 and p53.

I have provided mechanisms explanatory for regulation of the cell that go beyond the classic model of metabolic pathways associated with the cytoplasm, mitochondria, endoplasmic reticulum, and lysosome, such as, the cell death pathways, expressed in apoptosis and repair.  Nevertheless, there is still a missing part of this discussion that considers the time and space interactions of the cell, cellular cytoskeleton and extracellular and intracellular substrate interactions in the immediate environment.

There is heterogeneity among cancer cells of expected identical type, which would be consistent with differences in phenotypic expression, aligned with epigenetics.  There is also heterogeneity in the immediate interstices between cancer cells.  Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. In the case of breast cancer, there is interaction with estrogen , and we refer to an androgen-unresponsive prostate cancer.

Finally,  the interaction between enzyme and substrates may be conditionally unidirectional in defining the activity within the cell.  The activity of the cell is dynamically interacting and at high rates of activity.  In a study of the pyruvate kinase (PK) reaction the catalytic activity of the PK reaction was reversed to the thermodynamically unfavorable direction in a muscle preparation by a specific inhibitor. Experiments found that in there were differences in the active form of pyruvate kinase that were clearly related to the environmental condition of the assay – glycolitic or glyconeogenic. The conformational changes indicated by differential regulatory response were used to present a dynamic conformational model functioning at the active site of the enzyme. In the model, the interaction of the enzyme active site with its substrates is described concluding that induced increase in the vibrational energy levels of the active site decreases the energetic barrier for substrate induced changes at the site. Another example is the inhibition of H4 lactate dehydrogenase, but not the M4, by high concentrations of pyruvate. An investigation of the inhibition revealed that a covalent bond was formed between the nicotinamide ring of the NAD+ and the enol form of pyruvate.  The isoenzymes of isocitrate dehydrogenase, IDH1 and IDH2 mutations occur in gliomas and in acute myeloid leukemias with normal karyotype. IDH1 and IDH2 mutations are remarkably specific to codons that encode conserved functionally important arginines in the active site of each enzyme. In this case, there is steric hindrance by Asp279 where the isocitrate substrate normally forms hydrogen bonds with Ser94.

Personalized medicine has been largely viewed from a lens of genomics.  But genomics is only the reading frame.  The living activities of cell processes are dynamic and occur at rapid rates.  We have to keep in mind that personalized in reference to genotype is not complete without reconciliation of phenotype, which is the reference to expressed differences in outcomes.

 

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