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Reporter: Gail S. Thornton, M.A.

LPBI Update

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Newsletter #1 – February 2020

Welcome to the premier issue of LPBI Group News, where readers can find relevant news and updates about science, business and medical innovation. This newsletter is distributed as a service for our readers.

The Conference Forum Highlights Immuno-Oncology 360° in New York

The Conference Forum is hosting Immuno-Oncology 360°, which reports on current data and developments of immuno-oncology in the science and business communities. The summit takes place on February 26-28 at the Crowne Plaza Times Square in New York.

Please visit www.io360summit.com to register and use code LPBI20 for a 20% discount. 

Ahead of the conference, Immuno-Oncology 360° has created a series celebrating their women speakers in the work they are doing to fight cancer. To read the series, visit: https://theconferenceforum.org/conferences/immuno-oncology-360/io360%cb%9a-leadership-interviews/

This information is published in conjunction with the Immuno-Oncology 360° Summit.

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Venture Summit Attracts Top Innovators in Silicon Valley

Leaders in Pharmaceutical Business Intelligence (LPBI) Group is one of the sponsors of Venture Summit | West, “Where Innovation Meets Capital.”

The meeting will be held on March 23-24 at the Santa Clara Convention Center, Silicon Valley.

 

Special offer:  Register Now & Save $450 off (Use discount code “LPBI-VIP”)

For more information, please visit: https://pharmaceuticalintelligence.com/2019/12/17/venture-summit-west-where-innovation-meets-capital-march-23rd-24th-2020-santa-clara-convention-center-silicon-valley/

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e-Proceedings of 15th Annual Personalized Medicine Conference at Harvard Medical School

The 15th Annual Personalized Medicine Conference at Harvard Medical School, Boston last year [November 13-14, 2019], entitled  The Paradigm Evolves, explored the science, business and policy issues facing personalized medicine. In today’s world, scientists need to understand how molecular diagnostics augmented by artificial intelligence, data analytics and digital health empowers physicians and patients in their health care decisions.

Please visit for LPBI Group coverage of the meeting, including social media activities at the conference:

https://pharmaceuticalintelligence.com/2019/07/19/15th-annual-personalized-medicine-conference-at-harvard-medical-school-the-paradigm-evolves-november-13-14-2019-%e2%80%a2-harvard-medical-school-boston-ma/

https://pharmaceuticalintelligence.com/2019/11/15/tweets-and-retweets-by-aviva1950-and-by-pharma_bi-for-15th-annual-personalized-medicine-conference-at-harvard-medical-school-the-paradigm-evolves-november-13-14-2019-%e2%80%a2/

  •   3D Medical BioPrinting Technology Featured in Podcast

LPBI Group leaders, Aviva Lev-Ari, Ph.D., R.N., Stephen Williams, Ph.D., and Irina Robu, Ph.D., spoke with Partners in Health and Biz, a half-hour audio podcast that reaches 40,000 listeners, about the topic of 3D Medical BioPrinting Technology: A Revolution in Medicine.

Please click on this link to hear the podcast. https://www.youtube.com/watch?v=laozyrfi29c.

The topic is also the title of a recently offered e-book by the LPBI Group on 3D BioPrinting, available on Amazon/Kindle Direct [https://www.amazon.com/Medical-BioPrinting-Technologies-Patient-centered-Patient-Centered-ebook/dp/B078QVDV2W]. 

The 3D BioPrinting technology is being used to develop advanced medical practices that will help with previously difficult processes, such as delivering drugs via micro-robots, targeting specific cancer cells and even assisting in difficult eye operations.

The table of contents in this book includes: Chapter 1: 3D Bioprinting: Latest Innovations in a Forty year-old Technology. Chapter 2: LPBI Initiative on 3D BioPrinting, Chapter 3: Cardiovascular BioPrinting, Chapter 4: Medical and Surgical Repairs – Advances in R&D Research, Chapter 5: Organ on a Chip, Chapter 6: FDA Regulatory Technology Issues, Chapter 7: DNA Origami, Chapter 8: Aptamers and 3D Scaffold Binding, Chapter 9: Advances and Future Prospects, Chapter 10: BioInks and MEMS, Chapter 11: BioMedical MEMS, Chapter 12: 3D Solid Organ Printing and Chapter 13: Medical 3D Printing: Sources and Trade Groups – List of Secondary Material. 

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New e-Book: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology

LPBI Group’s latest e-book entitled, Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS & BioInformatics, Simulations and the Genome Ontology, offers the reader content curation with embedded videos and audio podcasts, real-time conference e-Proceedings by LPBI’s scientists and professors and archived tweets of quotes from speakers at leading biotechnology conferences.

Please click on this link on Amazon/Kindle Direct: https://www.amazon.com/dp/B08385KF87

 

The book integrates in a single volume four distinct perspectives: basic science, technologies and methodologies, clinical aspects and business and legal aspects of genomics research. “The materials in this book represents the scientific frontier in Biological Sciences and Medicine related to the genomics aspects of disease onset,” said Aviva Lev-Ari, Ph.D., R.N., and founder of LPBI Group.

The book addresses:

  • aspects of life: the Cell, the Organ, the Human Body and Human Populations;
  • methodologies of genomic data analysis: Next Generation Sequencing, Gene Editing, AI, Single Cell Genomics, Evolution Biology Genomics, Simulation Modeling in Genomics, Genotypes and Phenotypes Modeling, measurement of Epigenomics effects on disease, and developments in Pharmaco-Genomics.

Additionally, artificial Intelligence in medicine is covered in Part 3 of the e-Book, which represents the frontier in this emerging field, with topics, such as the science, technologies and methodologies, clinical aspects, business and legal implications as well as the latest machine learning algorithms harnessed for medical diagnosis.

This e-book is significant because it:

  • contains 326 articles on topics, such as gene editing, bioinformatics and genome ontology;
  • incorporates 74 e-Proceedings created in real time by the Book’s authors and editors
  • includes four collections of Tweets representing quotes from speakers at global leading conferences on Genomics
  • has 13 locations of Videos and Audio Podcasts that serve to enrich the e-Reader’s experience.

We welcome your comments and suggestions. Please send them to Aviva Lev-Ari at avivalev-ari@alum.berkeley.edu.

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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

This email is being sent to sjwilliamspa@comcast.net. This email communication is for marketing purposes. If it is not of interest to you, please disregard and we apologize for any inconvenience this may have caused.
Visit www.chicorporate.com/corporate_unsubscribe.aspx to update usage.

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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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A Perspective on Personalized Medicine

Curator: Larry H. Bernstein, MD, FCAP

 

 

A book has recently been reviewed by Laura Fisher (Feb 19 2016) titled “Junk DNA: a journey through the dark matter of the genome” (Nessa Carey  Icon Books 2015 | 352pp  ISBN 9781848319158).  http://www.rsc.org/chemistryworld/2016/02/junk-dna-genome-nessa-carey-book-review  It is important in its focus on, ‘junk DNA’, a term coined in the 1960s that refers to regions of our DNA that don’t code for proteins.  It is now known that a large portion of the genome is noncoding. These non-coding areas of our DNA are far from being without function. Whether regulating gene expression and transcription, or providing protein attachment sites, this once-dismissed part of the genome is vital for all life, and this is the focus of Junk DNA.  However, in 1869 Friedrich Miescher discovered a new substance (Dahm, 2008) from the cell nuclei that had chemical properties unlike any protein, including a much higher phosphorous content and resistance to proteolysis (protein digestion).  He wrote, “It seems probable to me that a whole family of such slightly varying phosphorous-containing substances will appear, as a group of nucleins, equivalent to proteins” (Wolf, 2003). In 1971, Chargaff  noted that Miescher’s discovery of nucleic acids was unique among the discoveries of the four major cellular components (i.e., proteins, lipids, polysaccharides, and nucleic acids) in that it could be “dated precisely… [to] one man one place, one date.”  We now know that there are two basic categories of nitrogenous bases: the purines (adenine [A] and guanine [G]), each with two fused rings, and the pyrimidines (cytosine [C], thymine [T], and uracil [U]), each with a single ring. Furthermore, it is now widely accepted that RNA contains only A, G, C, and U (no T), whereas DNA contains only A, G, C, and T (no U).  Keeping this in mind, the Watson-Crick proposal, as important as it was, was a discovery out of historical proportion, and it set the path of molecular biology for the remainder of the 20th century. A consequence of this seminal event was that the direction of biochemistry and molecular biology became set for several generations into the 21st century, culminating in the Human Genome Project.

As important as this discovery and others related that followed, there were a number of unrelated discoveries that took on huge importance, immediately recognized, but not so soon integrated with the evolving body of knowledge.  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.  There was also a relevance of 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. This involves the effect of one ligand on the binding or catalysis of another with no direct interaction between the two ligands. This was 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 binding at a different, nonoverlapping (regulatory) site, the former could inhibit the enzyme without competing with the latter. Pauling (Pauling 1935) had earlier proposed a model for intramolecular control in hemoglobin to explain the positive cooperativity observed in the binding of oxygen molecules. But  Monod, Wyman, and Changeux  substantially updated the view of allostery in 1965 with their landmark paper.  Present day applications of computational methods to biomolecular systems, combined with structural, thermodynamic, and kinetic studies, make possible an approach to that question, so as to provide a deeper understanding of the requirements for allostery. The current view is that a variety of measurements (e.g., NMR, FRET, and single molecule studies) are providing additional data beyond that available previously from structural, thermodynamic, and kinetic results. These should serve to continue to improve our understanding of the molecular mechanism of allostery, particularly when supplemented by simulations and theoretical analyses. A ‘‘dynamic’’ proposal by Cooper and Dryden (1984) is that the distribution around the average structure changes in allostery; which in turn, affects the subsequent (binding) affinity at a distant site. Such a model focuses on the vibrational contribution to the entropy as the origin of cooperativity, as discussed for the CAPN dimer.  Why is this important?  It is because it brings a different focus into the conception of how living cells engage with their neighbors and external environment.  Moreover, this is not all that has to be considered.

What else do we have to consider?  Oxidative stress is essentially an imbalance between the production of free radicals and the ability of the body to counteract or detoxify their harmful effects through neutralization by antioxidants. 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. Common mechanisms involving the Fenton reaction, generation of the superoxide radical and the hydroxyl radical appear to be involved for iron, copper, chromium, vanadium and cobalt primarily associated with mitochondria, microsomes and peroxisomes. 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.

In addition to what I have identified, there is substantial work in the last decade to indicate a more complex model of cellular regulatory processes.  On the one hand, there is no uncertainty about the importance of “Junk DNA”.  Indeed, not only is “Junk DNA” not junk, but it has either a presence that is an evolutionary remnant, or it has a role in cell regulation, much of which has yet to be understood.  Moreover, the relationship between the oligonucleotide sequences to their histones are largely unknown.  Beyond the DNA sequences, the language of the gene, we now have a large output of research on noncoding RNA.  We now have siRNA, miRNA, and others with roles other than transcription. This is a very active field of investigation that requires major revision of our model of cell regulatory processes.  The classic model is solely transcriptional.  DNA-> RNA-> Amino Acid in a protein.  This would now have to be redrawn because DNA-> RNA-> DNA and DNA->RNA-> protein-> DNA.

I have provided a series of four mechanisms explanatory for transcription and for regulation of the cell. This is not adequate for a more full comprehension because there is a layer beyond the classic model of metabolic pathways associated with the cytoplasm, mitochondria, endoplasmic reticulum, and lysosome, there are critical paths beyond oxidative phosphorylation and glycolysis, such as the cell death pathways, expressed in a homeostasis between apoptosis and repair.  Nevertheless, there is still a missing part of this discussion. The missing piece gets at the time and space interactions of the cell, cellular cytoskeleton and extracellular and intracellular substrate interactions in the immediate environment.  This can’t be simply accounted for by genetics or epigenetics. There have been papers that call attention to heterogeneity among cancer cells of expected identical type, which would be consistent with differences in phenotypic expression, aligned with epigenetics.  There is now the recent publication of the finding that there is heterogeneity in the immediate interstices between cancer cells, which may seem surprising, but it should not be.  This refers to the complexity of the cells arranged as tissues and to their immediate environment, which I shall elaborate on. 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. I did introduce the word gene into this reference, and we are well aware of mutations that occur in cancer progression.  In the case of breast cancer, mention is not made of interaction with a hormone, as we refer to in androgen-unresponsive prostate cancer.  This is particularly relevant, but incomplete.

The fifth item for discussion is the interaction between enzyme and substrates that may be conditionally unidirectional in defining the activity within the cell.  When we speak of the genome, we are dealing with a code defined by an oligonucleotide sequence that has an element of stability, but that can conditionally be altered by a process termed mutagenesis.  The altered code can be expected to have a negative, positive, or no effect, depending. In any case, there is a substantial stability inherent in the code that is essential to all living creatures.  The activity of the cell is dynamically interacting and at high rates of activity.  There are many examples of this.  The first example is in a study of energy for reverse pyruvate kinase (PK) reaction.  This catalytic activity of the PK reaction was reversed to the thermodynamically unfavorable direction in a muscle preparation by a specific inhibitor. Using the same crude supernatant for the two opposite activities of this enzyme some of the results found in the regulatory assays indicated differences in the active form of pyruvate kinase that were clearly related to the environmental condition – glycolitic or glyconeogenetic – of the assay. The conformational changes indicated by differential regulatory response found in the conditions studied, together with the role of similar factors, for instance, substrates and pH, in the structural states proposed by others, were used together 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 according to its vibrational, translational and rotational components and the activating ions – 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 pyridine nucleotide-linked dehydrogenases.   The lactate dehydrogenase (LD) reaction is ordered so that NADH binds to the enzyme before pyruvate can bind. The H-type isoenzyme, but not the M-type, is characterized by substrate inhibition at high pyruvate concentrations. The inhibition of the H4 lactate dehydrogenase, but not the M4, by high concentrations of pyruvate is caused by the formation of an abortive complex consisting of the enzyme, pyruvate, and NADH. An investigation of the structural properties of the ternary complex revealed that the complex possesses an absorption maximum at 335 nm and that a covalent bond was formed between the nicotinamide ring of the NAD+ and the pyruvate moiety. The same study demonstrated that the enol form of pyruvate is responsible for the complex formation.  It was suggested that abortive complex formation is a significant metabolic control mechanism, and the different behavior of the H and M forms has been rationalized in terms of different functional roles for the two isoenzymes.  However, similar experiments carried out with the mitochondrial malate dehydrogenase suggested a similar inhibition, but in this case only the mitochondrial malate dehydrogenase is sensitive to inhibition by high concentrations of oxaloacetate. Further studies showed the inhibition is promoted by an abortive binary complex formed by the enzymes and the enol form of oxalacetate. Neither the oxidized coenzyme nor the reduced coenzyme appears to be involved in the formation of this complex. These results suggest that the mechanism of substrate inhibition that occurs with the pig heart malate dehydrogenases is different from that observed with the lactate dehydrogenases.

It was established years later that there is an isoenzyme of isocitrate dehydrogenase that is characteristic for cancer cells. IDH1 and IDH2 mutations occur frequently in some types of World Health Organization grades 2–4 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. To date, all IDH1 mutations have been identified at the Arg132 codon. Mutations in IDH2 have been identified at the Arg140 codon, as well as at Arg172, which is aligned with IDH1 Arg132. IDH1 and IDH2 mutations are heterozygous in cancer, and they catalyze the production of α-2-hydroxyglutarate. The study found human IDH1 transitions between an inactive open, an inactive semi-open, and a catalytically active closed conformation. In the inactive open conformation, Asp279 occupies the position where the isocitrate substrate normally forms hydrogen bonds with Ser94. This steric hindrance by Asp279 to isocitrate binding is relieved in the active closed conformation.

Finally, what does this have to do with personalized medicine? Personalized medicine has been largely view from a lens of genomics.  But genomics is only the reading frame, even taking into consideration the mutations that are found in transition.  The living activities of cell processes are dynamic and occur at rapid rates.  When we refer to homeostasis and to neoplasia, 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.

References

Cui Q& Karplus M. Allostery and cooperativity revisited. Protein Science 2008; 17:1295–1307. http://www.proteinscience.org/cgi/doi/10.1110/ps.03259908.

Changeux, J-P. 1961. The feedback control mechanisms of biosynthetic L-threonine deaminase by L-isoleucine. Cold Spring Harb. Symp. Quant. Biol. 26: 313–318.

Pauling, L. 1935. The oxygen equilibrium of hemoglobin and its structural interpretation. Proc. Natl. Acad. Sci. 21: 181–191.

Monod, J., Wyman, J., and Changeux, J.P. 1965. On the nature of allosteric transitions: A plausible model. J. Mol. Biol. 12: 88–118.

Cooper, A. and Dryden, D.T.F. 1984. Allostery without conformational change. Eur. Biophys. J. 11: 103–109.

Valko M, Morris H and Cronin TD. Toxicity and Oxidative Stress. Curr Med Chem 2005; 12(10):1161-208
http://dx.doi.org:/10.2174/0929867053764635

Natrajan R, Sailem H, Mardakheh FK, Arias Garcia M, Tape CJ, Dowsett M, etal.(2016) Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology–Genomic Integration Analysis. PLoS Med 13(2):e1001961. http://dx.doi.org:/10.1371/journal.pmed.1001961

Roselino JEDS, Xavier AR, Kettelhut IDC, Hélios Migliorini RH. Res Gate communication2015.
http://dx.doi.org:/10.13140/RG.2.1.5137.1686

O’Carra P, Barry S and Corcoran E. Affinity Chromatographic Differentiation of Lactate Dehydrogenase Isoenzymes on the Basis of Differential Abortive Complex Formation.  FEBS Letters 1974; 43(2):163-168.

Everse J, Berger RL, and Kaplan N0 (1972) in Structure and Function of Oxidation-Reduction Enzymes (Akeson A, and Ehrenberg A, eds) pp. 691-708, Pergamon Press, Oxford.

LH Bernstein LH, Grisham MB, Cole KD, and Everse J. Substrate Inhibition of the Mitochondrial and Cytoplasmic Malate Dehydrogenases. J Biol Chem 1978 Dec 25; 253(24):8697-8701.

Reitman ZJ & Yan H. Isocitrate Dehydrogenase 1 and 2 Mutations in Cancer: Alterations at a Crossroads of Cellular Metabolism. J Natl Cancer Inst 2010; 102: 1–10. http://dx.doi.org:/10.1093/jnci/djq187

 

 

 

 

 

 

 

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Novel Mechanisms of Resistance to Novel Agents

 

Curators: Larry H. Berstein, M.D. FACP & Stephen J. Williams, Ph.D.

For most of the history of chemotherapy drug development, predicting the possible mechanisms of drug resistance that ensued could be surmised from the drug’s pharmacologic mechanism of action. In other words, a tumor would develop resistance merely by altering the pathways/systems which the drug relied on for mechanism of action. For example, as elucidated in later chapters in this book, most cytotoxic chemotherapies like cisplatin and cyclophosphamide were developed to bind DNA and disrupt the cycling cell, thereby resulting in cell cycle arrest and eventually cell death or resulting in such a degree of genotoxicity which would result in great amount of DNA fragmentation. These DNA-damaging agents efficacy was shown to be reliant on their ability to form DNA adducts and lesions. Therefore increasing DNA repair could result in a tumor cell becoming resistant to these drugs. In addition, if drug concentration was merely decreased in these cells, by an enhanced drug efflux as seen with the ABC transporters, then there would be less drug available for these DNA adducts to be generated. A plethora of literature has been generated on this particular topic.

However in the era of chemotherapies developed against targets only expressed in tumor cells (such as Gleevec against the Bcr-Abl fusion protein in chronic myeloid leukemia), this paradigm had changed as clinical cases of resistance had rapidly developed soon after the advent of these compounds and new paradigms of resistance mechanisms were discovered.

speed of imitinib resistance

Imatinib resistance can be seen quickly after initiation of therapy

mellobcrablresistamplification

Speed of imatinib resistance a result of rapid gene amplification of BCR/ABL target, thereby decreasing imatinib efficacy

 

 

 

 

 

 

 

 

 

 

Although there are many other new mechanisms of resistance to personalized medicine agents (which are discussed later in the chapter) this post is a curation of cellular changes which are not commonly discussed in reviews of chemoresistance and separated in three main categories:

Cellular Diversity and Adaptation

Identifying Cancers and Resistance

Cancer Drug-Resistance Mechanism

p53 tumor drug resistance gene target

Variability of Gene Expression and Drug Resistance

 

Expression of microRNAs and alterations in RNA resulting in chemo-resistance

Drug-resistance Mechanism in Tumor Cells

Overexpression of miR-200c induces chemoresistance in esophageal cancers mediated through activation of the Akt signaling pathway

 

The miRNA–drug resistance connection: a new era of personalized medicine using noncoding RNA begins

 

Gene Duplication of Therapeutic Target

 

The advent of Gleevec (imatinib) had issued in a new era of chemotherapy, a personalized medicine approach by determining the and a lifesaver to chronic myeloid leukemia (CML) patients whose tumors displayed expression of the Bcr-Abl fusion gene. However it was not long before clinical resistance was seen to this therapy and, it was shown amplification of the drug target can lead to tumor outgrowth despite adequate drug exposure. le Coutre, Weisberg and Mahon23, 24, 25 all independently generated imatinib-resistant clones through serial passage of the cells in imatinib-containing media and demonstrated elevated Abl kinase activity due to a genetic amplification of the Bcr–Abl sequence. However, all of these samples were derived in vitro and may not represent a true mode of clinical resistance. Nevertheless, Gorre et al.26 obtained specimens, directly patients demonstrating imatinib resistance, and using fluorescence in situ hybridization analysis, genetic duplication of the Bcr–Abl gene was identified as one possible source of the resistance. Additional sporadic examples of amplification of the Bcr–Abl sequence have been clinically described, but the majority of patients presenting with either primary or secondary imatinib resistance fail to clinically demonstrate Abl amplification as a primary mode of treatment failure.

This is seen in the following papers:

Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification.Gorre ME, Mohammed M, Ellwood K, Hsu N, Paquette R, Rao PN, Sawyers CL. Science. 2001 Aug 3;293(5531):876-80. Epub 2001 Jun 21.

and in another original paper by le Coutre et. al.

Induction of resistance to the Abelson inhibitor STI571 in human leukemic cells through gene amplification. le Coutre P1, Tassi E, Varella-Garcia M, Barni R, Mologni L, Cabrita G, Marchesi E, Supino R, Gambacorti-Passerini C. Blood. 2000 Mar 1;95(5):1758-66

The 2-phenylaminopyrimidine derivative STI571 has been shown to selectively inhibit the tyrosine kinase domain of the oncogenic bcr/abl fusion protein. The activity of this inhibitor has been demonstrated so far both in vitro with bcr/abl expressing cells derived from leukemic patients, and in vivo on nude mice inoculated with bcr/abl positive cells. Yet, no information is available on whether leukemic cells can develop resistance to bcr/abl inhibition. The human bcr/abl expressing cell line LAMA84 was cultured with increasing concentrations of STI571. After approximately 6 months of culture, a new cell line was obtained and named LAMA84R. This newly selected cell line showed an IC50 for the STI571 (1.0 microM) 10-fold higher than the IC50 (0.1 microM) of the parental sensitive cell line. Treatment with STI571 was shown to increase both the early and late apoptotic fraction in LAMA84 but not in LAMA84R. The induction of apoptosis in LAMA84 was associated with the activation of caspase 3-like activity, which did not develop in the resistant LAMA84R cell line. LAMA84R cells showed increased levels of bcr/abl protein and mRNA when compared to LAMA84 cells. FISH analysis with BCR- and ABL-specific probes in LAMA84R cells revealed the presence of a marker chromosome containing approximately 13 to 14 copies of the BCR/ABL gene. Thus, overexpression of the Bcr/Abl protein mediated through gene amplification is associated with and probably determines resistance of human leukemic cells to STI571 in vitro. (Blood. 2000;95:1758-1766)

This is actually the opposite case with other personalized therapies like the EGFR inhibitor gefinitib where actually the AMPLIFICATION of the therapeutic target EGFR is correlated with better response to drug in

Molecular mechanisms of epidermal growth factor receptor (EGFR) activation and response to gefitinib and other EGFR-targeting drugs.Ono M, Kuwano M. Clin Cancer Res. 2006 Dec 15;12(24):7242-51. Review.

Abstract

The epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases, including EGFR, HER2/erbB2, and HER3/erbB3, is an attractive target for antitumor strategies. Aberrant EGFR signaling is correlated with progression of various malignancies, and somatic tyrosine kinase domain mutations in the EGFR gene have been discovered in patients with non-small cell lung cancer responding to EGFR-targeting small molecular agents, such as gefitinib and erlotinib. EGFR overexpression is thought to be the principal mechanism of activation in various malignant tumors. Moreover, an increased EGFR copy number is associated with improved survival in non-small cell lung cancer patients, suggesting that increased expression of mutant and/or wild-type EGFR molecules could be molecular determinants of responses to gefitinib. However, as EGFR mutations and/or gene gains are not observed in all patients who respond partially to treatment, alternative mechanisms might confer sensitivity to EGFR-targeting agents. Preclinical studies showed that sensitivity to EGFR tyrosine kinase inhibitors depends on how closely cell survival and growth signalings are coupled with EGFR, and also with HER2 and HER3, in each cancer. This review also describes a possible association between EGFR phosphorylation and drug sensitivity in cancer cells, as well as discussing the antiangiogenic effect of gefitinib in association with EGFR activation and phosphatidylinositol 3-kinase/Akt activation in vascular endothelial cells.

 

Mutant Variants of Therapeutic Target

 

resistant subclones in tissue samples and Tyrosine Kinase tumor activity

 

Mitochondrial Isocitrate Dehydrogenase and Variants

Mutational Landscape of Rare Childhood Brain Cancer: Analysis of 60 Intercranial Germ Cell Tumor Cases using NGS, SNP and Expression Array Analysis – Signaling Pathways KIT/RAS are affected by mutations in IGCTs

 

AND seen with the ALK inhibitors as well (as seen in the following papers

Acquisition of cancer stem cell-like properties in non-small cell lung cancer with acquired resistance to afatinib.

Hashida S, Yamamoto H, Shien K, Miyoshi Y, Ohtsuka T, Suzawa K, Watanabe M, Maki Y, Soh J, Asano H, Tsukuda K, Miyoshi S, Toyooka S. Cancer Sci. 2015 Oct;106(10):1377-84. doi: 10.1111/cas.12749. Epub 2015 Sep 30.

In vivo imaging models of bone and brain metastases and pleural carcinomatosis with a novel human EML4-ALK lung cancer cell line.

Nanjo S, Nakagawa T, Takeuchi S, Kita K, Fukuda K, Nakada M, Uehara H, Nishihara H, Hara E, Uramoto H, Tanaka F, Yano S. Cancer Sci. 2015 Mar;106(3):244-52. doi: 10.1111/cas.12600. Epub 2015 Feb 17.

Identification of a novel HIP1-ALK fusion variant in Non-Small-Cell Lung Cancer (NSCLC) and discovery of ALK I1171 (I1171N/S) mutations in two ALK-rearranged NSCLC patients with resistance to Alectinib. Ou SH, Klempner SJ, Greenbowe JR, Azada M, Schrock AB, Ali SM, Ross JS, Stephens PJ, Miller VA.J Thorac Oncol. 2014 Dec;9(12):1821-5

Reports of chemoresistance due to variants have also been seen with the BRAF inhibitors like vemurafenib and dabrafenib:

The RAC1 P29S hotspot mutation in melanoma confers resistance to pharmacological inhibition of RAF.

Watson IR, Li L, Cabeceiras PK, Mahdavi M, Gutschner T, Genovese G, Wang G, Fang Z, Tepper JM, Stemke-Hale K, Tsai KY, Davies MA, Mills GB, Chin L.Cancer Res. 2014 Sep 1;74(17):4845-52. doi: 10.1158/0008-5472.CAN-14-1232-T. Epub 2014 Jul 23

 

 

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