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Archive for the ‘Mutagenesis’ Category


Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

 

Curator: Aviva Lev-Ari, PhD, RN

 

Dana Pe’er, PhD, now chair of computational and systems biology at the Sloan Kettering Institute at the Memorial Sloan Kettering Cancer Center and a member of the Human Cell Atlas Organizing Committee,

what really sets Regev apart is the elegance of her work. Regev, says Pe’er, “has a rare, innate ability of seeing complex biology and simplifying it and formalizing it into beautiful, abstract, describable principles.”

Dr. Aviv Regev, an MIT biology professor who is also chair of the faculty of the Broad and director of its Klarman Cell Observatory and Cell Circuits Program, was reviewing a newly published white paper detailing how the Human Cell Atlas is expected to change the way we diagnose, monitor, and treat disease at a gathering of international scientists at Israel’s Weizmann Institute of Science, 10/2017.

For Regev, the importance of the Human Cell Atlas goes beyond its promise to revolutionize biology and medicine. As she once put it, without an atlas of our cells, “we don’t really know what we’re made of.”

Regev, turned to a technique known as RNA interference (she now uses CRISPR), which allowed her to systematically shut genes down. Then she looked at which genes were expressed to determine how the cells’ response changed in each case. Her team singled out 100 different genes that were involved in regulating the response to the pathogens—some of which weren’t previously known to be involved in immune function. The study, published in Science, generated headlines.

The project, the Human Cell Atlas, aims to create a reference map that categorizes all the approximately 37 trillion cells that make up a human. The Human Cell Atlas is often compared to the Human Genome Project, the monumental scientific collaboration that gave us a complete readout of human DNA, or what might be considered the unabridged cookbook for human life. In a sense, the atlas is a continuation of that project’s work. But while the same DNA cookbook is found in every cell, each cell type reads only some of the recipes—that is, it expresses only certain genes, following their DNA instructions to produce the proteins that carry out a cell’s activities. The promise of the Human Cell Atlas is to reveal which specific genes are expressed in every cell type, and where the cells expressing those genes can be found.

Regev says,

The final product, will amount to nothing less than a “periodic table of our cells,” a tool that is designed not to answer one specific question but to make countless new discoveries possible.

Sequencing the RNA of the cells she’s studying can tell her only so much. To understand how the circuits change under different circumstances, Regev subjects cells to different stimuli, such as hormones or pathogens, to see how the resulting protein signals change.

“the modeling step”—creating algorithms that try to decipher the most likely sequence of molecular events following a stimulus. And just as someone might study a computer by cutting out circuits and seeing how that changes the machine’s operation, Regev tests her model by seeing if it can predict what will happen when she silences specific genes and then exposes the cells to the same stimulus.

By sequencing the RNA of individual cancer cells in recent years—“Every cell is an experiment now,” she says—she has found remarkable differences between the cells of a single tumor, even when they have the same mutations. (Last year that work led to Memorial Sloan Kettering’s Paul Marks Prize for Cancer Research.) She found that while some cancers are thought to develop resistance to therapy, a subset of melanoma cells were resistant from the start. And she discovered that two types of brain cancer, oligodendroglioma and astrocytoma, harbor the same cancer stem cells, which could have important implications for how they’re treated.

As a 2017 overview of the Human Cell Atlas by the project’s organizing committee noted, an atlas “is a map that aims to show the relationships among its elements.” Just as corresponding coastlines seen in an atlas of Earth offer visual evidence of continental drift, compiling all the data about our cells in one place could reveal relationships among cells, tissues, and organs, including some that are entirely unexpected. And just as the periodic table made it possible to predict the existence of elements yet to be observed, the Human Cell Atlas, Regev says, could help us predict the existence of cells that haven’t been found.

This year alone it will fund 85 Human Cell Atlas grants. Early results are already pouring in.

  • In March, Swedish researchers working on cells related to human development announced they had sequenced 250,000 individual cells.
  • In May, a team at the Broad made a data set of more than 500,000 immune cells available on a preview site.

The goal, Regev says, is for researchers everywhere to be able to use the open-source platform of the Human Cell Atlas to perform joint analyses.

Eric Lander, PhDthe founding director and president of the Broad Institute and a member of the Human Cell Atlas Organizing Committee, likens it to genomics.

“People thought at the beginning they might use genomics for this application or that application,” he says. “Nothing has failed to be transformed by genomics, and nothing will fail to be transformed by having a cell atlas.”

“How did we ever imagine we were going to solve a problem without single-cell resolution?”

SOURCE

https://www.technologyreview.com/s/611786/the-cartographer-of-cells/?utm_source=MIT+Technology+Review&utm_campaign=Alumni-Newsletter_Sep-Oct-2018&utm_medium=email

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

 

University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/01/13/university-of-california-santa-cruzs-genomics-institute-will-create-a-map-of-human-genetic-variations/

 

Recognitions for Contributions in Genomics by Dan David Prize Awards

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/31/recognitions-for-contributions-in-genomics-by-dan-david-prize-awards/

 

ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/18/encode-encyclopedia-of-dna-elements-program-tragic-sequestration-impact-on-nhgri-programs/

 

Single-cell Sequencing

Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/04/genomic-diagnostics-three-techniques-to-perform-single-cell-gene-expression-and-genome-sequencing-single-molecule-dna-sequencing/

 

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT – See, Aviv Regev

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/03/13/16th-annual-cancer-research-symposium-koch-institute-friday-june-16-9am-5pm-kresge-auditorium-mit/

 

LIVE 11/3/2015 1:30PM @The 15th Annual EmTech MIT – MIT Media Lab: Top 10 Breakthrough Technologies & 2015 Innovators Under 35 – See, Gilead Evrony

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2015/11/03/live-1132015-130pm-the-15th-annual-emtech-mit-mit-media-lab-top-10-breakthrough-technologies-2015-innovators-under-35/

 

Cellular Guillotine Created for Studying Single-Cell Wound Repair

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2017/06/29/cellular-guillotine-created-for-studying-single-cell-wound-repair/

 

New subgroups of ILC immune cells discovered through single-cell RNA sequencing

Reporter: Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2016/02/17/new-subgroups-of-ilc-immune-cells-discovered-through-single-cell-rna-sequencing-from-karolinska-institute/

 

#JPM16: Illumina’s CEO on new genotyping array called Infinium XT and Bio-Rad Partnership for single-cell sequencing workflow

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/jpm16-illuminas-ceo-on-new-genotyping-array-called-infinium-xt-and-bio-rad-partnership-for-single-cell-sequencing-workflow/

 

Juno Acquires AbVitro for $125M: high-throughput and single-cell sequencing capabilities for Immune-Oncology Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/juno-acquires-abvitro-for-125m-high-throughput-and-single-cell-sequencing-capabilities-for-immune-oncology-drug-discovery/

 

NIH to Award Up to $12M to Fund DNA, RNA Sequencing Research: single-cell genomics,  sample preparation,  transcriptomics and epigenomics, and  genome-wide functional analysis.

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/10/27/nih-to-award-up-to-12m-to-fund-dna-rna-sequencing-research-single-cell-genomics-sample-preparation-transcriptomics-and-epigenomics-and-genome-wide-functional-analysis/

 

Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm

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

https://pharmaceuticalintelligence.com/2012/08/07/genome-wide-single-cell-analysis-of-recombination-activity-and-de-novo-mutation-rates-in-human-sperm/

REFERENCES to Original studies

In Science, 2018

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

 See all authors and affiliations

Science  21 Apr 2017:
Vol. 356, Issue 6335, eaah4573
DOI: 10.1126/science.aah4573
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

See all authors and affiliations

Science  26 Apr 2018:
eaar3131
DOI: 10.1126/science.aar3131

In Nature, 2018 and 2017

How to build a human cell atlas

Aviv Regev is a maven of hard-core biological analyses. Now she is part of an effort to map every cell in the human body.

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

References:

 

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

 

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

 

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

 

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

 

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

 

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

 

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Li -Fraumeni Syndrome and Pancreatic Cancer

Curator: Marzan Khan, B.Sc.

Li-Fraumeni syndrome (LFS) is a condition that makes individuals prone to developing a wide variety of cancers that occur early on in life, the most common types being- soft tissue sarcoma, osteosarcoma, breast cancer, brain tumors, adrenocortical carcinoma (ACC), and leukemia. (1) Pancreatic cancer is minimally associated with the condition. (2) A survey found the presence of pancreatic cancer in only 1% of 475 tumor samples collected from 91 families who were carriers of p53 mutations, with half of them having LFS. The incidence of breast cancer amongst them was the highest -24%. (2) Pancreatic carcinoma in LFS patients usually occurs in the later stages of life. (3)

The underlying cause of LFS is germline mutations in TP53 gene on chromosome 17p, that encodes the transcription factor p53, crucial in cell cycle regulation and the repair of damaged and/or abnormal cells. (4) In the majority of cases, this mutation is obtained by inheritance. (5) De-novo germline mutations in p53 occur in 7%-20% of the cases. (5)

A person showing symptoms of any type of cancer at an early age or having first or second-degree relatives with cancer are at risk of developing LFS. (5) That is why tracing family history is an important part of diagnosis in LFS patients. Genetic testing can confirm mutations present in the gene, however, there are controversial ethical issues regarding their use, particularly in children and fetuses.

In patients with LFS, it is important to control the manifestations of the disease. They should be monitored closely so that any new cancers that arise are diagnosed and treated during the early stages. (6) Patients are also at risk of developing radiation-induced second and third primary tumors. (6) Therefore, radiation and alkylating agents should be used minimally (6) People at risk can be cautioned to avoid exposure to carcinogens such as sunlight, cigarette smoke, and alcohol consumption. (5) Therapeutic approaches that are aimed at restoring wild-type p53 by gene therapy as well as reactivating non-functional p53 by the use of small-molecule drugs are currently being investigated in many cancers. (7) Unlike radiation therapy, these small-molecule drugs are non-toxic to healthy cells, thus eliminating the risk of forming new tumors.

So far, PRIMA-1 has proven to be quite effective at correcting non-functional p53. (8) PRIMA-1 is changed to its methylated form, PRIMA-1MET   that forms covalent adducts to thiol groups in the mutated protein and modifies them. (8) As a result, p53 regains its ability to destroy malignant cells. (8) A research study also found that PRIMA-1 induces apoptosis and increases the sensitivity of pancreatic cancer cells to various chemotherapeutic agents. (9)

  1. Magali Olivier, David E. Goldgar, Nayanta Sodha, Hiroko Ohgaki, Paul Kleihues, Pierre Hainaut and Rosalind A. Eeles. Li-Fraumeni and Related Syndromes. Cancer Res October 15 2003 63 (20) 6643-6650 http://cancerres.aacrjournals.org/content/63/20/6643.abstract
  2. Kleihues P, Schauble B, zur Hausen H, et al. Tumors associated with p53 germline mutations: a synopsis of 91 families. Am J Pathol 1997; 150:1-13 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1858532/
  3. John P. Neoptolemos, Raul Urrutia, James L. Abbruzzese, Markus W. Buchler. Pancreatic Cancer. 2010.1st ed, pp-6, 2010, Springer, Verlag, New York
  4. Mishra B and Patel RR. Gene Therapy for Treatment of Pancreatic Cancer. Austin Therapeutics. 2014;1(1): 10. https://books.google.ca/books?id=NmBB5ZoKkk4C&pg=PA6&lpg=PA6&dq=connection+between+li+fraumeni+and+Pancreatic+cancer&source=bl&ots=H0iCeaPP0N&sig=pqJT1tPMR6C-NIig3S_NkFKFsD0&hl=en&sa=X&ved=0ahUKEwi4nLrgzuPQAhUUIWMKHS3wBoc4ChDoAQhNMAg#v=onepage&q=connection%20between%20li%20fraumeni%20and%20Pancreatic%20cancer&f=false
  5. Schneider K, Zelley K, Nichols KE, et al. Li-Fraumeni Syndrome. 1999 Jan 19 [Updated 2013 Apr 11]. In: Pagon RA, Adam MP, Ardinger HH, et al., editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1993-2016. https://www.ncbi.nlm.nih.gov/pubmed/20301488
  6. Elisa Becze BA, ELS, 2011 Mar 1. An introduction to Li-Fraumeni Syndrome, Five-Minute-In-Service. http://connect.ons.org/columns/five-minute-in-service/an-introduction-to-li-fraumeni-syndrome
  7. Sorrell, A. D., Espenschied, C. R., Culver, J. O., & Weitzel, J. N. (2013).TP53Testing and Li-Fraumeni Syndrome: Current Status of Clinical Applications and Future Directions. Molecular Diagnosis & Therapy17(1), 31–47. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3627545/
  8. Emily J. Lewis. PRIMA-1 as a cancer therapy restoring mutant p53: a reviewBioscience Horizons (2015) 8: hzv006 http://biohorizons.oxfordjournals.org/content/8/hzv006.full
  9. Izetti, Patricia, Agnes Hautefeuille, Ana Lucia Abujamra, Caroline Brunetto de Farias, Juliana Giacomazzi, Bárbara Alemar, Guido Lenz, et al. ‘PRIMA-1, a Mutant p53 Reactivator, Induces Apoptosis and Enhances Chemotherapeutic Cytotoxicity in Pancreatic Cancer Cell Lines’. Investigational New Drugs 32, no. 5 (October 2014): 783–94. https://www.ncbi.nlm.nih.gov/pubmed/24838627

Izetti, Patricia, Agnes Hautefeuille, Ana Lucia Abujamra, Caroline Brunetto de Farias, Juliana Giacomazzi, Bárbara Alemar, Guido Lenz, et al. ‘PRIMA-1, a Mutant p53 Reactivator, Induces Apoptosis and Enhances Chemotherapeutic Cytotoxicity in Pancreatic Cancer Cell Lines’. Investigational New Drugs 32, no. 5 (October 2014): 783–94

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

p53 mutation – Li-Fraumeni Syndrome – Likelihood of Genetic or Hereditary conditions playing a role in Intergenerational incidence of Cancer

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/12/01/p53-mutation-li-fraumeni-syndrome-likelihood-of-genetic-or-hereditary-conditions-playing-a-role-in-intergenerational-incidence-of-cancer/

Pancreatic Cancer: Articles of Note @PharmaceuticalIntelligence.com

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/05/26/pancreatic-cancer-articles-of-note-pharmaceuticalintelligence-com/

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

http://www.discoveryontarget.com/

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

Leaders in Pharmaceutical Business Intelligence (LPBI) Group is a

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

In Attendance, streaming LIVE using Social Media

Aviva Lev-Ari, PhD, RN

Editor-in-Chief

http://pharmaceuticalintelligence.com

#BostonDOT16

@BostonDOT

 

COMMENTS BY Stephen J Williams, PhD

EXPLORING THE VERSATILITY OF CRISPR/Cas9

 

8:00 Chairperson’s Opening Remarks

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

 

@CRISPRTX

 

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

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

 

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

 

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

 

@nyuniversity

 

8:40 Therapeutic Gene Editing With CRISPR/Cas9

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

 

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

 

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

 

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

 

 

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

 

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

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

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

 

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

 

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

Aggregate ranking of hits programs available on web like LINKS

 

@MDAndersonNews

 

10:25 CRISPR in Stem Cell Models of Eye Disease

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

 

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

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

@uiowa

10:55 CRISPR in Mouse Models of Eye Disease

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

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

CAPN mouse models

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

To Follow LIVE CONFERENCE COVERAGE PLEASE FOLLOW ON TWITTER USING

Meeting #: #BostonDOT16

Meeting @: @BostonDOT

 

Overall good meeting #s:

#personalizedmedicine

#innovation

#cancer

#immunology

#immunooncology

#pharmanews

#CRSPR

#geneediting

#crisper

#biotech

 

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The Strategy of Precision Editing the Cancer Cell Glycocalyx using an “antibody–enzyme conjugate” for Cancer Immunotherapy: Research Beyond “augment the activator or remove inhibitor, or both”

Reporter: Aviva Lev-Ari, PhD, RN

Significance

Successful tumors are able to evade the immune system, which is otherwise capable of killing transformed cells. Therapies that prevent this evasion have become revolutionary treatments for incurable cancers. One mechanism of evasion is the presentation of sugars, called sialic acids, within the cell surface’s sugar coating, or glycocalyx. Here, we designed biotherapeutic molecules, termed “antibody–enzyme conjugates,” that selectively remove sialic acids from tumor cells. The antibody directs the enzyme to the cancer cells, the enzyme cleaves the sugars, and then the antibody directs immune cells to kill the desialylated cancer cells. The conjugate increased tumor cell killing compared with the antibody alone. Editing the cancer cell glycocalyx with an antibody–enzyme conjugate represents a promising approach to cancer immune therapy.

SOURCE 

 

AUGUST 22, 2016

Stanford chemists develop a new method of cancer immunotherapy

A team of Stanford ChEM-H scientists has discovered a novel form of cancer immunotherapy, which works by removing certain sugars from the surface of cancer cells and making those cells visible to the immune system.

“All of the world of immune therapy is now thinking about the immune system as calculating pluses and minuses. If you want to tilt the scale toward immune activation, you can either augment the activator or remove inhibitor, or both,” said Bertozzi, who is also an investigator with the Howard Hughes Medical Institute.

Current immunotherapies on the market work by blocking one of the inhibitory signals that are recognized by the adaptive immune system. Block those and the balance tilts in such a way that the immune system will attack the now recognizable cancer.

Bertozzi’s approach provides a second way of tiling the balance in favor of attack, this time for the innate immune system. She said this study shows just one example of how it could work, but her sugar-removing lawnmower could be used on a wide variety of cell types, not just those expressing HER2, and on different types of sugars.

“It’s almost always the case that you need a component of both the adaptive and innate immunity to get a robust reaction against infectious pathogens, such as during vaccination,” said Bertozzi. “The smart money suggests that the same will be true with tumors.”

Bertozzi said the approach also highlights the importance of paying attention to the much ignored glycocalyx.

SOURCE

Stanford chemists develop a new method of cancer immunotherapy

http://news.stanford.edu/2016/08/22/new-method-cancer-immunotherapy/

 

immobilization-ok

A symbolic representation of a glycocalyx chain attached to a cytoskeleton.

IMAGE SOURCE: google images

 

glycocalyx-145E1F0C801699F8CFE

image glycocalyx

IMAGE SOURCE: google images

Glycocalyx

Glycocalyx – www.futura-sciences.us576 × 284Search by image

The carbohydrates, glycoproteins and proteoglycans making up the glycocalyx

IMAGE SOURCE: google images

PNAS – Original Article

Precision glycocalyx editing as a strategy for cancer immunotherapy

  1. Han Xiaoa,b,1,
  2. Elliot C. Woodsa,b,1,
  3. Petar Vukojicica,b, and
  4. Carolyn R. Bertozzia,b,2
  1. Edited by Laura L. Kiessling, University of Wisconsin-Madison, Madison, WI, and approved July 11, 2016 (received for review May 24, 2016)

Abstract

Cell surface sialosides constitute a central axis of immune modulation that is exploited by tumors to evade both innate and adaptive immune destruction. Therapeutic strategies that target tumor-associated sialosides may therefore potentiate antitumor immunity. Here, we report the development of antibody–sialidase conjugates that enhance tumor cell susceptibility to antibody-dependent cell-mediated cytotoxicity (ADCC) by selective desialylation of the tumor cell glycocalyx. We chemically fused a recombinant sialidase to the human epidermal growth factor receptor 2 (HER2)-specific antibody trastuzumab through a C-terminal aldehyde tag. The antibody–sialidase conjugate desialylated tumor cells in a HER2-dependent manner, reduced binding by natural killer (NK) cell inhibitory sialic acid-binding Ig-like lectin (Siglec) receptors, and enhanced binding to the NK-activating receptor natural killer group 2D (NKG2D). Sialidase conjugation to trastuzumab enhanced ADCC against tumor cells expressing moderate levels of HER2, suggesting a therapeutic strategy for cancer patients with lower HER2 levels or inherent trastuzumab resistance. Precision glycocalyx editing with antibody–enzyme conjugates is therefore a promising avenue for cancer immune therapy.

SOURCE 

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DISCUSSION – Genomics-driven personalized medicine for Pancreatic Cancer

Reporter: Aviva Lev-Ari, PhD, RN

[bold face added, ALA]

Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer –>>> Personalized Tumor Models Could Help Identify Combination Therapies for Hard-to-Treat Cancers

 

Original article

Pancreatic Cancer – Genomics-driven personalized medicine

 

PDAC has a particularly poor prognosis, and even with new targeted therapies and chemotherapy, the survival is poor. Here, we show that patient-derived models can be developed and used to investigate therapeutic sensitivities determined by genetic features of the disease and to identify empirical therapeutic vulnerabilities. These data reveal several key points that are of prime relevance to pancreatic cancer and tumor biology in general.

The Challenges of Using Genetic Analysis to Inform Treatment in PDAC

Precision oncology is dependent on the existence of known vulnerabilities encoded by high-potency genetic events and drugs capable of exploiting these vulnerabilities. At present, the repertoire of actionable genetic events in PDAC is limited.

  • Rare BRAF V600E mutations are identified in PDAC and could represent the basis for targeted inhibition, as our group and others have previously published (Collisson et al., 2012; Witkiewicz et al., 2015).

Similarly,

  • germline BRCA deficiency is the basis for ongoing poly(ADP-ribose) polymerase (PARP) inhibitor clinical trials (Lowery et al., 2011).

As shown here, out of 28 cases, only one genetic event was identified that yielded sensitivity to a therapeutic strategy. In this case, existence of the matched model allowed us to confirm the biological relevance of the

  • STAG2 mutation by showing sensitivity of the model to a DNA cross-linking agent.

Therefore, annotated patient-derived models provide a substrate upon which to functionally dissect the significance of novel and potentially actionable genetic events that occur within a tumor.

Another challenge of genomics-driven personalized medicine is

  • assessing the effect of specific molecular aberrations on therapeutic response in the context of complex genetic changes present in individual tumors.
  • KRAS has been proposed to modify therapeutic dependency to EZH2 inhibitors (Kim et al., 2015), and in the models tested, responses to this class of drugs were not uniformly present in cases harboring mutations in chromatin-remodeling genes.

This finding suggests that, although tumors acquire genetic alterations in specific genes, the implicated pathway may not be functionally inactive or therapeutically actionable. Therefore, annotated patient derived models provide a unique test bed for interrogating specific therapeutic dependencies in a genetically tractable system.

Empirical Definition of Therapeutic Sensitivities and Clinical Relevance

Cell lines offer the advantage of the ability to conduct high throughput approaches to interrogate many therapeutic agents. A large number of failed clinical trials have demonstrated the difficulty in treating PDAC. Based on the data herein, the paucity of clinical success is, most probably, due to the diverse therapeutic sensitivity of individual PDAC cases, suggesting that, with an unselected patient population, it will be veritably impossible to demonstrate clinical benefit. Additionally,

  •  very few models exhibited an exceptional response to single agents across the breadth of a library encompassing 305 agents.
  • We could identify only one tumor that was particularly sensitive to MEK inhibition and another model that was sensitive to
  • EGFR and
  • tyrosine kinase inhibitors.

In contrast to the limited activity of single agents, combination screens yielded responses at low-dose concentrations in the majority of models. Specific combinations were effective across several models, indicating that, by potentially screening more models, therapeutic sensitivity clades of PDAC will emerge. In the pharmacological screens performed in this study,

  • MEK inhibition, coupled with MTOR, docetaxel, or tyrosine kinase inhibitors, was effective in _30% of models tested.
  • Resistance to MEK inhibitors occurs through several mechanisms, including
  • Upregulation of oncogenic bypass signaling pathways such as AKT, tyrosine kinase, or MTOR (mammalian target of rapamycin) signaling.

In the clinic, the MEK and MTOR inhibitors (e.g., NCT02583542) are being tested. An intriguing finding from the drug screen was

  • sensitivity of a subset of models to combined MEK and docetaxel inhibition. This combination has been observed to synergistically enhance apoptosis and inhibit tumor growth in human xenograft tumor models (Balko et al., 2012; McDaid et al., 2005) and is currently being tested in a phase III study in patients with KRAS-mutated, advanced non-small-cell lung adenocarcinoma (Ja¨ nne et al., 2016).

Interestingly, in the models tested herein, there was limited sensitivity imparted through

  •  the combination of gemcitabine and MEK inhibition.

This potentially explains why the combination of MEK inhibitor and gemcitabine tested in the clinic did not show improved efficacy over gemcitabine alone (Infante et al., 2014).

Another promising strategy that emerged from this study involves using

  • CHK or BCL2 inhibitors as agents that drive enhanced sensitivity to chemotherapy.

Together, the data suggest that the majority of PDAC tumors have intrinsic therapeutic sensitivities, but the challenge is to prospectively identify effective treatment.

Patient-Derived Model-Based Approach to Precision Medicine

This study supports a path for guiding patient treatment based on the integration of genetic and empirically determined sensitivities of the patient’s tumor (Figure S7). In reference to defined genetic susceptibilities, the models provide a means to interrogate the voracity of specific drug targets. Parallel unbiased screening enables the discovery of sensitivities that could be exploited in the clinic. The model-guided treatment must be optimized, allowing for the generation of data in a time frame compatible with clinical decision making and appropriate validation.

In the present study, the majority of models were developed, cell lines were drug screened, and select hits were validated in PDX models within a 10- to 12-month window (Figure S7). This chronology would allow time to inform frontline therapy for recurrent disease for most patients who were surgically resected and treated with a standard of care where the median time to recurrence is approximately 14 months (Saif, 2013).

Although most models were generated from surgically resected specimens, two of the models (EMC3226 and EMC62) were established from primary tumor biopsies, indicating that this approach could be used with only a limited amount of tumor tissue available.

In the context of inoperable pancreatic cancer, application of data from a cell-line screen without in vivo validation in PDX would permit the generation of sensitivity data in the time frame compatible with treatment.

[We] acknowledge that model-guided treatment is also not without significant logistical hurdles, including the availability of drugs for patient treatment, clinically relevant time frames, patient-performance status, toxicity of combination regiments, and quality metrics related to model development and therapeutic response evaluation.

Additionally, it will be very important to monitor ex vivo genetic and phenotypic divergence with passage and try to understand the features of tumor heterogeneity that could undermine the efficacy of using models to direct treatment. As shown here, drug sensitivities remained stable with passage in cell culture and, importantly, were confirmed in PDX models, suggesting that the dominant genetic drivers and related therapeutic sensitivities are conserved.

In spite of these challenges, progressively more effort is going into the development of patient-derived models for guidance of disease treatment (Aparicio et al., 2015; Boj et al., 2015; Crystal et al., 2014; van de Wetering et al., 2015).

Several ongoing trials use PDX models to direct a limited repertoire of agents (e.g., NCT02312245, NCT02720796, and ERCAVATAR2015). Given the experience here, PDAC cell lines would provide the opportunity to rapidly interrogate a larger portfolio of combinations that could be used to guide patient care and provide a novel approach to precision medicine.

Validation of this approach would require the establishment of challenging multi-arm or N-of-1 clinical trials. However, considering the dire outcome for PDAC patients and the long-lasting difficulty in developing effective treatments, this non-canonical approach might be particularly impactful in pancreatic cancer.

SOURCE

Witkiewicz et al., 2016, Cell Reports 16, 1–15

August 16, 2016 ª 2016 The Author(s).

http://dx.doi.org/10.1016/j.celrep.2016.07.023

Agnieszka K. WitkiewiczPress enter key for correspondence information
Uthra Balaji
Cody Eslinger
Elizabeth McMillan
William Conway
Bruce Posner
Gordon B. Mills
Eileen M. O’Reilly
Erik S. KnudsencorrespondencePress enter key for correspondence information
Publication stage: In Press Corrected Proof
Open Access

Resource Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer

Correspondence

awitki@email.arizona.edu (A.K.W.),

eknudsen@email.arizona.edu (E.S.K.)

Accession Numbers: GSE84023

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

Pancreatic Cancer: Articles of Note @PharmaceuticalIntelligence.com

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/05/26/pancreatic-cancer-articles-of-note-pharmaceuticalintelligence-com/

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Using Online Mendelian Inheritance in Man (OMIM) database and the Human Genome Mutation Database (HGMD) Pro 2015.2 for Quantification of the growth in gene-disease and variant-disease associations

Reporter: Aviva Lev-Ari, PhD, RN

 

Reanalysis of Clinical Exome Data Over Time Could Yield New Diagnoses

NEW YORK (GenomeWeb) – Clinical exomes that are re-evaluated in a systematic way could yield new diagnoses and prove useful to clinicians, according to a study published yesterday in Genetics in Medicine.

A team of researchers from Stanford University set out to examine whether nondiagnostic clinical exomes could provide new information for patients if they were re-examined with current bioinformatics software and knowledge of disease-related variants as presented in the literature.

Clinical exome sequencing yields no diagnosis for about 75 percent of patients evaluated for possible Mendelian disorders, wrote senior author Gill Bejerano and his colleagues. But a reanalysis of exome and phenotypic data from 40 such individuals using current methods identified a definitive diagnosis for four of them — 10 percent — the team said.

In these cases, the causative variant was de novo and found in a relevant autosomal-dominant disease gene. At the time these exomes were first sequenced, the researchers wrote, the existing literature on these causative genes was either “weak, nonexistent, or not readily located.” When the exomes were re-examined by his team, Bejerano noted, the supporting literature was more robust.

SOURCE

https://www.genomeweb.com/sequencing/reanalysis-clinical-exome-data-over-time-could-yield-new-diagnoses?utm_source=SilverpopMailing&utm_medium=email&utm_campaign=Daily%20News:%20Reanalysis%20of%20Clinical%20Exome%20Data%20Over%20Time%20Could%20Yield%20New%20Diagnoses%20-%2007/22/2016%2011:20:00%20AM

At ACMG, Researchers Report Data Re-Analysis, Matchmaking Boosts Solved Exome Cases

In addition to re-analyzing exome data, the researchers have been working on establishing causality for novel candidate disease genes through patient matches. For this, the team has been using the GeneMatcher website, which allows them to find other clinicians and researchers around the world who have patients, or animal models, with mutations in the same genes as their own patients. Through an API developed by the Matchmaker Exchange project, GeneMatcher submitters can also query the PhenomeCentral and Decipher databases. As of March, more than 4,000 genes had been submitted to GeneMatcher from more than 1,300 submitters in 48 countries, and 1,900 matches had been made, Sobreira reported.

Her team has so far submitted data from 104 families, involving 280 genes, and has had 314 matches so far, involving 113 genes. Several cases have been successes, meaning the researchers could establish that a candidate gene is indeed disease causing, and several others are pending, both from Hopkins and from other groups. The total number of solved cases tracing their success to GeneMatcher is currently unknown, Sobreira said, but the organizers are planning to survey submitters about their success rate in the near future.

SOURCE

https://www.genomeweb.com/molecular-diagnostics/acmg-researchers-report-data-re-analysis-matchmaking-boosts-solved-exome-cases

 

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