Posts Tagged ‘DNA’

Immunoediting can be a constant defense in the cancer landscape

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


There are many considerations in the cancer immunoediting landscape of defense and regulation in the cancer hallmark biology. The cancer hallmark biology in concert with key controls of the HLA compatibility affinity mechanisms are pivotal in architecting a unique patient-centric therapeutic application. Selection of random immune products including neoantigens, antigens, antibodies and other vital immune elements creates a high level of uncertainty and risk of undesirable immune reactions. Immunoediting is a constant process. The human innate and adaptive forces can either trigger favorable or unfavorable immunoediting features. Cancer is a multi-disease entity. There are multi-factorial initiators in a certain disease process. Namely, environmental exposures, viral and / or microbiome exposure disequilibrium, direct harm to DNA, poor immune adaptability, inherent risk and an individual’s own vibration rhythm in life.


When a human single cell is crippled (Deranged DNA) with mixed up molecular behavior that is the initiator of the problem. A once normal cell now transitioned into full threatening molecular time bomb. In the modeling and creation of a tumor it all begins with the singular molecular crisis and crippling of a normal human cell. At this point it is either chop suey (mixed bit responses) or a productive defensive and regulation response and posture of the immune system. Mixed bits of normal DNA, cancer-laden DNA, circulating tumor DNA, circulating normal cells, circulating tumor cells, circulating immune defense cells, circulating immune inflammatory cells forming a moiety of normal and a moiety of mess. The challenge is to scavenge the mess and amplify the normal.


Immunoediting is a primary push-button feature that is definitely required to be hit when it comes to initiating immune defenses against cancer and an adaptation in favor of regression. As mentioned before that the tumor microenvironment is a “mixed bit” moiety, which includes elements of the immune system that can defend against circulating cancer cells and tumor growth. Personalized (Precision-Based) cancer vaccines must become the primary form of treatment in this case. Current treatment regimens in conventional therapy destroy immune defenses and regulation and create more serious complications observed in tumor progression, metastasis and survival. Commonly resistance to chemotherapeutic agents is observed. These personalized treatments will be developed in concert with cancer hallmark analytics and immunocentrics affinity and selection mapping. This mapping will demonstrate molecular pathway interface and HLA compatibility and adaptation with patientcentricity.




Read Full Post »

Lesson 1 & 2 Cell Signaling & Motility: Lessons, Curations and Articles of reference as supplemental information: #TUBiol3373

Curator: Stephen J. Williams, Ph.D.

UPDATED 2/05/2019

Syllabus for Cell Signaling & Motility for 2019




Monday 5:00 PM – 8:00 PM

Biology Life Sciences, Room 342


Antonio Giordano, M.D., Ph.D.

Office hours: Biology Life Sciences Building, Room 431.

Friday: 12:00 noon – 2:00 PM. By appointment

(Phone: 215-2049520, or email:


BIO 3096, Cell Structure and Function (Minimum Grade of C- | May not be taken concurrently). 


The communication among cells is essential for the regulation of the development of an organism and for the control of its physiology and homeostasis. Aberrant cellular signaling events are often associated with human pathological conditions, such as cancer, neurological disorders, cardiovascular diseases and so on. The full characterization of cell signaling systems may provide useful insights into the pathogenesis of several human maladies.


Molecular Biology of the Cell 6th Edition, Alberts et al. Garland Science. This textbook is available at the Temple Bookstore.


The final grade will be based on the score of four examinations that include both group and individuals assignment. Each exam accounts for 25% of the final grade. There will be no make-up tests during the course. If you have a documented medical excuse and you contact me as soon as possible after the emergency, I will arrange a make-up exam. Complaints regarding the grading will not be considered later than two weeks after the test is returned.


Announcements will be readily posted on Blackboard. It is your responsibility to check Blackboard periodically.

Attendance: Lecture attendance is mandatory. In addition, punctuality is expected.

Disabilities: Students with documented disabilities who need particular accommodation should contact me privately as soon as possible.

Honesty and Civility:

Students must follow the Temple’s Code of Conduct (see This Code of Conduct prohibits: 1. Academic dishonesty and impropriety, including plagiarism and cheating. 2. Interfering or attempting to interfere with or disrupting the conduct of classes or any other activity of the University.”

Academic Rights and Responsibilities:

The policy of the University that regulates Student and Faculty Academic Rights and Responsibilities (Policy # 03.70.02) is available at the following web link:

This policy sets the parameters for freedom to learn and freedom to teach, which constitute the pillars of academia.



This schedule is a general outline, which may be eventually modified. Changes will be announced in advance. Please, always check Blackboard and your email.

Date Topic
Jan 14 Introduction (course overview  and discussion of syllabus). General concepts: Eukaryotic and prokaryotic cell; DNA, RNA  and proteins: Protein synthesis
Jan 21 Martin Luther King, Jr. Day (no classes held)
Jan 28 DNA analysis, RNA analysis; Proteins analysis; Microscopy.
Feb 4 Signaling: general concepts; Introduction to G-proteins; signaling via G-proteins (1)
Feb 11 Exam 1: In class presentation (group assignment)
Feb 18 Signaling via G-proteins (2); tyrosine kinase receptors signaling; Ras-MAPK pathway.
Feb 25 Exam 2: In class presentation (group assignment)
March 4- 10 Spring break
Mar 11


Cytoskeleton:  Intermediate filaments; actin
Mar 18 Cytoskeleton: actin binding proteins; microtubules
Mar 25


Cytoskeleton: microtubules
April 1


Exam 3: in class Multiple choice questions (individual assignment)
Apr 8 Extracellular matrix; cell adhesion; coordinated polarization.
Apr  15 Cell motility and Wnt Signal Signaling. 
Apr  22 Medical consequences of aberrant signaling pathways; production of small molecules for protein kinases In cancer therapy.
Study days
May 6 Exam 4: In class presentation (group assignment)


Below is Powerpoint presentations for Lesson 1 and Lesson 2.  Please check for UPDATES on this page for additional supplemental information for these Lessons including articles from this Online Access Journal


cell signaling and motility 1 lesson


cell signaling and motility 2 lesson

The following articles and curations discuss about the new paradigm how we now envision DNA, in particular how we now understand that the important parts of the genome are not just the exons which code for proteins but also the intronic DNA, which contains all the regulatory elements such as promoters, lnDNA, miRNA sequences etc.  These are good reads for your presentations.

The Search for the Genetic Code

Junk DNA codes for valuable miRNAs


And on How the Cell Creates Diversity post the Genetic Code by Use of Post Translational Modifications to Bring Diversity to Protein Structure/Function

Expanding the Genetic Alphabet and Linking the Genome to the Metabolome

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

Also there is a link to a Blood article using FISH to detect gene amplifications after Gleevec resistance onset here

Novel Mechanisms of Resistance to Novel Agents

Other Articles related to the #TUBiol3373 course include:

Lesson 9 Cell Signaling: Curations and Articles of reference as supplemental information for lecture section on WNTs: #TUBioll3373

Curation of selected topics and articles on Role of G-Protein Coupled Receptors in Chronic Disease as supplemental information for #TUBiol3373


Read Full Post »

Bioinformatics Tool Review: Genome Variant Analysis Tools

Curator: Stephen J. Williams, Ph.D.

Updated 11/15/2018

The following post will be an ongoing curation of reviews of gene variant bioinformatic software.


The Ensembl Variant Effect Predictor.

McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F.

Genome Biol. 2016 Jun 6;17(1):122. doi: 10.1186/s13059-016-0974-4.

Author information


European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.


European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.


European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.


The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.


Rare diseases can be difficult to diagnose due to low incidence and incomplete penetrance of implicated alleles however variant analysis of whole genome sequencing can identify underlying genetic events responsible for the disease (Nature, 2015).  However, a large cohort is required for many WGS association studies in order to produce enough statistical power for interpretation (see post and here).  To this effect major sequencing projects have been initiated worldwide including:

A more thorough curation of sequencing projects can be seen in the following post:

Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies


And although sequencing costs have dramatically been reduced over the years, the costs to determine the functional consequences of such variants remains high, as thorough basic research studies must be conducted to validate the interpretation of variant data with respect to the underlying disease, as only a small fraction of variants from a genome sequencing project will encode for a functional protein.  Correct annotation of sequences and variants, identification of correct corresponding reference genes or transcripts in GENCODE or RefSeq respectively offer compelling challenges to the proper identification of sequenced variants as potential functional variants.

To this effect, the authors developed the Ensembl Variant Effect Predictor (VEP), which is a software suite that performs annotations and analysis of most types of genomic variation in coding and non-coding regions of the genome.

Summary of Features

  • Annotation: VEP can annotate two broad categories of genomic variants
    • Sequence variants with specific and defined changes: indels, base substitutions, SNVs, tandem repeats
    • Larger structural variants > 50 nucleotides
  • Species and assembly/genomic database support: VEP can analyze data from any species with assembled genome sequence and annotated gene set. VEP supports chromosome assemblies such as the latest GRCh38, FASTA, as well as transcripts from RefSeq as well as user-derived sequences
  • Transcript Annotation: VEP includes a wide variety of gene and transcript related information including NCBI Gene ID, Gene Symbol, Transcript ID, NCBI RefSeq ID, exon/intron information, and cross reference to other databases such as UniProt
  • Protein Annotation: Protein-related fields include Protein ID, RefSeq ID, SwissProt, UniParc ID, reference codons and amino acids, SIFT pathogenicity score, protein domains
  • Noncoding Annotation: VEP reports variants in noncoding regions including genomic regulatory regions, intronic regions, transcription binding motifs. Data from ENCODE, BLUEPRINT, and NIH Epigenetics RoadMap are used for primary annotation.  Plugins to the Perl coding are also available to link other databases which annotate noncoding sequence features.
  • Frequency, phenotype, and citation annotation: VEP searches Ensembl databases containing a large amount of germline variant information and checks variants against the dbSNP single nucleotide polymorphism database. VEP integrates with mutational databases such as COSMIC, the Human Gene Mutation Database, and structural and copy number variants from Database of Genomic Variants.  Allele Frequencies are reported from 1000 Genomes and NHLBI and integrates with PubMed for literature annotation.  Phenotype information is from OMIM, Orphanet, GWAS and clinical information of variants from ClinVar.
  • Flexible Input and Output Formats: VEP supports input data format called “variant call format” or VCP, a standard in next-gen sequencing. VEP has the ability to process variant identifiers from other database formats.  Output formats are tab deliminated and give the user choices in presentation of results (HTML or text based)
  • Choice of user interface
    • Online tool (VEP Web): simple point and click; incorporates Instant VEP Functionality and copy and paste features. Results can be stored online in cloud storage on Ensembl.
    • VEP script: VEP is available as a downloadable PERL script (see below for link) and can process large amounts of data rapidly. This interface is powerfully flexible with the ability to integrate multiple plugins available from Ensembl and GitHub.  The ability to alter the PERL code and add plugins and code functions allows the flexibility to modify any feature of VEP.
    • VEP REST API: provides robust computational access to any programming language and returns basic variant annotation. Can make use of external plugins.



Watch Video on VES Instructional Webinar:

Watch Video on VES Web Version training on How to Analyze Your Sequence in VEP



Availability of data and materials

The dataset supporting the conclusions of this article is available from Illumina’s Platinum Genomes [93] and using the Ensembl release 75 gene set. Pre-built data sets are available for all Ensembl and Ensembl Genomes species [94]. They can also be downloaded automatically during set up whilst installing the VEP.



Large-scale discovery of novel genetic causes of developmental disorders.

Deciphering Developmental Disorders Study.

Nature2015 Mar 12;519(7542):223-8. doi: 10.1038/nature14135. PMID:25533962

Updated 11/15/2018


Research Points to Caution in Use of Variant Effect Prediction Bioinformatic Tools

Although we have the ability to use high throughput sequencing to identify allelic variants occurring in rare disease, correlation of these variants with the underlying disease is often difficult due to a few concerns:

  • For rare sporadic diseases, classical gene/variant association studies have proven difficult to perform (Meyts et al. 2016)
  • As Whole Exome Sequencing (WES) returns a considerable number of variants, how to differentiate the normal allelic variation found in the human population from disease-causing pathogenic alleles
  • For rare diseases, pathogenic allele frequencies are generally low

Therefore, for these rare pathogenic alleles, the use of bioinformatics tools in order to predict the resulting changes in gene function may provide insight into disease etiology when validation of these allelic changes might be experimentally difficult.

In a 2017 Genes & Immunity paper, Line Lykke Andersen and Rune Hartmann tested the reliability of various bioinformatic software to predict the functional consequence of variants of six different genes involved in interferon induction and sixteen allelic variants of the IFNLR1 gene.  These variants were found in cohorts of patients presenting with herpes simplex encephalitis (HSE). Most of the adult population is seropositive for Herpes Simplex Virus (HSV) however a minor fraction (1 in 250,000 individuals per year) of HSV infected individuals will develop HSE (Hjalmarsson et al., 2007).  It has been suggested that HSE occurs in individuals with rare primary immunodeficiencies caused by gene defects affecting innate immunity through reduced production of interferons (IFN) (Zhang et al., Lim et al.).



Meyts I, Bosch B, Bolze A, Boisson B, Itan Y, Belkadi A, et al. Exome and genome sequencing for inborn errors of immunity. J Allergy Clin Immunol. 2016;138:957–69.

Hjalmarsson A, Blomqvist P, Skoldenberg B. Herpes simplex encephalitis in Sweden, 1990-2001: incidence, morbidity, and mortality. Clin Infect Dis. 2007;45:875–80.

Zhang SY, Jouanguy E, Ugolini S, Smahi A, Elain G, Romero P, et al. TLR3 deficiency in patients with herpes simplex encephalitis. Science. 2007;317:1522–7.

Lim HK, Seppanen M, Hautala T, Ciancanelli MJ, Itan Y, Lafaille FG, et al. TLR3 deficiency in herpes simplex encephalitis: high allelic heterogeneity and recurrence risk. Neurology. 2014;83:1888–97.


Genes Immun. 2017 Dec 4. doi: 10.1038/s41435-017-0002-z.

Frequently used bioinformatics tools overestimate the damaging effect of allelic variants.

Andersen LL1Terczyńska-Dyla E1Mørk N2Scavenius C1Enghild JJ1Höning K3Hornung V3,4Christiansen M5,6Mogensen TH2,6Hartmann R7.



We selected two sets of naturally occurring human missense allelic variants within innate immune genes. The first set represented eleven non-synonymous variants in six different genes involved in interferon (IFN) induction, present in a cohort of patients suffering from herpes simplex encephalitis (HSE) and the second set represented sixteen allelic variants of the IFNLR1 gene. We recreated the variants in vitro and tested their effect on protein function in a HEK293T cell based assay. We then used an array of 14 available bioinformatics tools to predict the effect of these variants upon protein function. To our surprise two of the most commonly used tools, CADD and SIFT, produced a high rate of false positives, whereas SNPs&GO exhibited the lowest rate of false positives in our test. As the problem in our test in general was false positive variants, inclusion of mutation significance cutoff (MSC) did not improve accuracy.


  1. Identification of rare variants
  2. Genomes of nineteen Dutch patients with a history of HSE sequenced by WES and identification of novel HSE causing variants determined by filtering the single nucleotide polymorphisms (SNPs) that had a frequency below 1% in the NHBLI Exome Sequencing Project Exome Variant Server and the 1000 Genomes Project and were present within 204 genes involved in the immune response to HSV.
  3. Identified variants (204) manually evaluated for involvement of IFN induction based on IDBase and KEGG pathway database analysis.
  4. In-silico predictions: Variants classified by the in silico variant pathogenicity prediction programs: SIFT, Mutation Assessor, FATHMM, PROVEAN, SNAP2, PolyPhen2, PhD-SNP, SNP&GO, FATHMM-MKL, MutationTaster2, PredictSNP, Condel, MetaSNP, and CADD. Each program returned prediction scores measuring likelihood of a variant either being ‘deleterious’ or ‘neutral’. Prediction accuracy measured as

ACC = (true positive+true negative)/(true positive+true negative+false positive+false negative)


  1. Validation of prediction software/tools

In order to validate the predictive value of the software, HEK293T cells, deficient in IRF3, MAVS, and IKKe/TBK1, were cotransfected with the nine variants of the aforementioned genes and a luciferase reporter under control of the IFN-b promoter and luciferase activity measured as an indicator of IFN signaling function.  Western blot was performed to confirm the expression of the constructs.



Table 2 Summary of the
bioinformatic predictions
HSE variants IFNLR1 variants Overall ACC
Uniform cutoff
SIFT 4 1 0 4 9 0.56 8 1 0 7 16 0.56 0.56
Mutation assessor 6 1 0 2 9 0.78 9 1 0 6 16 0.63 0.68
FATHMM 7 1 0 1 9 0.89 0.89
PROVEAN 8 1 0 0 9 1.00 11 1 0 4 16 0.75 0.84
SNAP2 5 1 0 3 9 0.67 8 0 1 7 16 0.50 0.56
PolyPhen2 6 1 0 2 9 0.78 12 1 0 3 16 0.81 0.80
PhD-SNP 7 1 0 1 9 0.89 11 1 0 4 16 0.75 0.80
SNPs&GO 8 1 0 0 9 1.00 14 1 0 1 16 0.94 0.96
FATHMM MKL 4 1 0 4 9 0.56 13 0 1 2 16 0.81 0.72
MutationTaster2 4 0 1 4 9 0.44 14 0 1 1 16 0.88 0.72
PredictSNP 6 1 0 2 9 0.78 11 1 0 4 16 0.75 0.76
Condel 6 1 0 2 9 0.78 0.78
Meta-SNP 8 1 0 0 9 1.00 11 1 0 4 16 0.75 0.84
CADD 2 1 0 6 9 0.33 8 0 1 7 16 0.50 0.44
MSC 95% cutoff
SIFT 5 1 0 3 9 0.67 8 1 0 8 16 0.50 0.56
PolyPhen2 6 1 0 2 9 0.78 13 1 0 3 16 0.81 0.80
CADD 4 1 0 4 9 0.56 7 0 1 9 16 0.44 0.48


Note: TN: true negative, TP: true positive, FN: false negative, FP: false positive, ACC: accuracy

Functional testing (data obtained from reporter construct experiments) were considered as the correct outcome.

Three prediction tools (PROVEAN, SNP&GO, and MetaSNP correctly predicted the effect of all nine variants tested.


Other articles related to Genomics and Bioinformatics on this online Open Access Journal Include:

Finding the Genetic Links in Common Disease: Caveats of Whole Genome Sequencing Studies


Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes


US Personalized Cancer Genome Sequencing Market Outlook 2018 –


Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies



Read Full Post »

The Role of Exosomes in Metabolic Regulation

Author: Larry H. Bernstein, MD, FCAP


On 9/25/2017, Aviva Lev-Ari, PhD, RN commissioned Dr. Larry H. Bernstein to write a short article on the following topic reported on 9/22/2017 in


We are publishing, below the new article created by Larry H. Bernstein, MD, FCAP.



During the period between 9/2015  and 6/2017 the Team at Leaders in Pharmaceutical Business Intelligence (LPBI)  has launched an R&D effort lead by Aviva Lev-Ari, PhD, RN in conjunction with SBH Sciences, Inc. headed by Dr. Raphael Nir.

This effort, also known as, “DrugDiscovery @LPBI Group”  has yielded several publications on EXOSOMES on this Open Access Online Scientific Journal. Among them are included the following:


QIAGEN – International Leader in NGS and RNA Sequencing, 10/08/2017

Reporter: Aviva Lev-Ari, PhD, RN


cell-free DNA (cfDNA) tests could become the ultimate “Molecular Stethoscope” that opens up a whole new way of practicing Medicine, 09/08/2017

Reporter: Aviva Lev-Ari, PhD, RN


Detecting Multiple Types of Cancer With a Single Blood Test (Human Exomes Galore), 07/02/2017

Reporter and Curator: Irina Robu, PhD


Exosomes: Natural Carriers for siRNA Delivery, 04/24/2017

Reporter: Aviva Lev-Ari, PhD, RN


One blood sample can be tested for a comprehensive array of cancer cell biomarkers: R&D at WPI, 01/05/2017

Curator: Marzan Khan, B.Sc


SBI’s Exosome Research Technologies, 12/29/2016

Reporter: Aviva Lev-Ari, PhD, RN


A novel 5-gene pancreatic adenocarcinoma classifier: Meta-analysis of transcriptome data – Clinical Genomics Research @BIDMC, 12/28/2016

Curator: Tilda Barliya, PhD


Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood – R&D @Worcester Polytechnic Institute, Micro and Nanotechnology Lab, 12/28/2016

Reporters: Tilda Barliya, PhD and Aviva Lev-Ari, PhD, RN


Exosomes – History and Promise, 04/28/2016

Reporter: Aviva Lev-Ari, PhD, RN


Exosomes, 11/17/2015

Curator: Larry H. Bernstein, MD, FCAP


Liquid Biopsy Assay May Predict Drug Resistance, 11/16/2015

Curator: Larry H. Bernstein, MD, FCAP


Glypican-1 identifies cancer exosomes, 10/31/2015

Curator: Larry H. Bernstein, MD, FCAP


Circulating Biomarkers World Congress, March 23-24, 2015, Boston: Exosomes, Microvesicles, Circulating DNA, Circulating RNA, Circulating Tumor Cells, Sample Preparation, 03/24/2015

Reporter: Aviva Lev-Ari, PhD, RN


Cambridge Healthtech Institute’s Second Annual Exosomes and Microvesicles as Biomarkers and Diagnostics Conference, March 16-17, 2015 in Cambridge, MA, 03/17, 2015

Reporter: Aviva Lev-Ari, PhD, RN


The newly created think-piece on the relationship between regulatory functions of Exosomes and Metabolic processes is developed conceptually, below.


The Role of Exosomes in Metabolic Regulation

Author: Larry H. Bernstein, MD, FCAP

We have had more than a half century of research into the genetic code and transcription leading to abundant work on RNA and proteomics. However, more recent work in the last two decades has identified RNA interference in siRNA. These molecules may be found in the circulation, but it has been a challenge to find their use in therapeutics. Exosomes were first discovered in the 1980s, but only recently there has been a huge amount of research into their origin, structure and function. Exosomes are 30–120 nm endocytic membrane-bound extracellular vesicles (EVs)(1-23) , and more specifically multiple vesicle bodies (MVBs) by a budding process from invagination of the outer cell membrane that carry microRNA (miRNA), and have structures composed of protein and lipids (1,23-27 ). EVs are the membrane vesicles secreted by eukaryotic cells for intracellular communication by transferring the proteins, lipids, and RNA under various physiologic conditions as well as during the disease stage. EVs also act as a signalosomes in many biological processes. Inward budding of the plasma membrane forms small vesicles that fuse. Intraluminal vesicles (ILVs) are formed by invagination of the limiting endosomal membrane during the maturation process of early endosome.

EVs are the MVBs secreted that serve in intracellular communication by transferring a cargo consisting of proteins, lipids, and RNA under various physiologic conditions (4, 23). Exosome-mediated miRNA transfer between cells is considered to be necessary for intercellular signaling and exosome-associated miRNAs in biofluids (23). Exosomes carry various molecular constituents of their cell of origin, including proteins, lipids, mRNAs, and microRNAs (miRNAs) (. They are released from many cell types, such as dendritic cells (DCs), lymphocytes, platelets, mast cells, epithelial cells, endothelial cells, and neurons, and can be found in most bodily fluids including blood, urine, saliva, amniotic fluid, breast milk, hydrothoracic fluid, and ascitic fluid, as well as in culture medium of most cell types.Exosomes have also been shown to be involved in noncoding RNA surveillance machinery in generating antibody diversity (24). There are also a vast number of long non-coding RNAs (lncRNAs) and enhancer RNAs (eRNAs) that accumulate R-loop structures upon RNA exosome ablation, thereby, resolving deleterious DNA/RNA hybrids arising from active enhancers and distal divergent eRNA-expressing elements (lncRNA-CSR) engaged in long-range DNA interactions (25). RNA exosomes are large multimeric 3′-5′ exo- and endonucleases representing the central RNA 3′-end processing factor and are implicated in processing, quality control, and turnover of both coding and noncoding RNAs. They are large macromolecular cages that channel RNA to the ribonuclease sites (29). A major interest has been developed to characterize of exosomal cargo, which includes numerous non-randomly packed proteins and nucleic acids (1). Moreover, exosomes play an active role in tumorigenesis, metastasis, and response to therapy through the transfer of oncogenes and onco-miRNAs between cancer cells and the tumor stroma. Blood cells and the vascular endothelium is also exosomal shedding, which has significance for cardiovascular,   neurologicological disorders, stroke, and antiphospholipid syndrome (1). Dysregulation of microRNAs and the affected pathways is seen in numerous pathologies their expression can reflect molecular processes of tumor onset and progression qualifying microRNAs as potential diagnostic and prognostic biomarkers (30).

Exosomes are secreted by many cells like B lymphocytes and dendritic cells of hematopoietic and non-hematopoietic origin viz. platelets, Schwann cells, neurons, mast cells, cytotoxic T cells, oligodendrocytes, intestinal epithelial cells were also found to be releasing exosomes (4). They are engaged in complex functions like persuading immune response as the exosomes secreted by antigen presenting cells activate T cells (4). They all have a common set of proteins e.g. Rab family of GTPases, Alix and ESCRT (required for transport) protein and they maintain their cytoskeleton dynamics and participate in membrane fusion. However, they are involved in retrovirus disease pathology as a result of recruitment of the host`s endosomal compartments in order to generate viral vesicles, and they can either spread or limit an infection based on the type of pathogen and its target cells (5).

Upon further consideration, it is understandable how this growing biological work on exosomes has enormous significance for laboratory diagnostics (1, 3, 5, 6, 11, 14, 15, 17-20, 23,30-41) . They are released from many cell types, such as dendritic cells (DCs), lymphocytes, platelets, mast cells, epithelial cells, endothelial cells, and neurons, and can be found in most bodily fluids including blood, urine, saliva, amniotic fluid, breast milk, thoracic and abdominal effusions, and ascitic fluid (1). The involvement of exosomes in disease is broad, and includes: cancer, autoimmune and infectious disease, hematologic disorders, neurodegenerative diseases, and cardiovascular disease. Proteins frequently identified in exosomes include membrane transporters and fusion proteins (e.g., GTPases, annexins, and flotillin), heat shock proteins (e.g., HSC70), tetraspanins (e.g., CD9, CD63, and CD81), MVB biogenesis proteins (e.g., alix and TSG101), and lipid-related proteins and phospholipases. The exosomal lipid composition has been thoroughly analyzed in exosomes secreted from several cell types including DCs and mast cells, reticulocytes, and B-lymphocytes (1). Dysregulation of microRNAs of pathways observed in numerous pathologies (5, 10, 12, 21, 27, 35, 37) including cancers (30), particularly, colon, pancreas, breast, liver, brain, lung (2, 6, 17-20, 30, 33-36, 38, 39). Following these considerations, it is important that we characterize the content of exosomal cargo to gain clues to their biogenesis, targeting, and cellular effects which may lead to identification of biomarkers for disease diagnosis, prognosis and response to treatment (42).

We might continue in pursuit of a particular noteworthy exosome, the NLRP3 inflammasome, which is activated by a variety of external or host-derived stimuli, thereby, initiating an inflammatory response through caspase-1 activation, resulting in inflammatory cytokine IL-1b maturation and secretion (43).
Inflammasomes are multi-protein signaling complexes that activate the inflammatory caspases and the maturation of interleukin-1b. The NLRP3 inflammasome is linked with human autoinflammatory and autoimmune diseases (44). This makes the NLRP3 inflammasome a promising target for anti-inflammatory therapies. The NLRP3 inflammasome is activated in response to a variety of signals that indicate tissue damage, metabolic stress, and infection (45). Upon activation, the NLRP3 inflammasome serves as a platform for activation of the cysteine protease caspase-1, which leads to the processing and secretion of the proinflammatory cytokines interleukin-1β (IL-1β) and IL-18. Heritable and acquired inflammatory diseases are both characterized by dysregulation of NLRP3 inflammasome activation (45).
Receptors of innate immunity recognize conserved moieties associated with either cellular damage [danger-associated molecular patterns (DAMPs)] or invading organisms [pathogen-associated molecular patterns (PAMPs)](45). Either chronic stimulation or overwhelming tissue damage is injurious and responsible for the pathology seen in a number of autoinflammatory and autoimmune disorders, such as arthritis and diabetes. The nucleotide-binding domain leucine-rich repeat (LRR)-containing receptors (NLRs) are PRRs are found intracellularly and they share a unique domain architecture. It consists of a central nucleotide binding and oligomerization domain called the NACHT domain that is located between an N-terminal effector domain and a C-terminal LRR domain (45). The NLR family members NLRP1, NLRP3, and NLRC4 are capable of forming multiprotein complexes called inflammasomes when activated.

The (NLRP3) inflammasome is important in chronic airway diseases such as asthma and chronic obstructive pulmonary disease because the activation results, in pro-IL-1β processing and the secretion of the proinflammatory cytokine IL-1β (46). It has been proposed that Activation of the NLRP3 inflammasome by invading pathogens may prove cell type-specific in exacerbations of airway inflammation in asthma (46). First, NLRP3 interacts with the adaptor protein ASC by sensing microbial pathogens and self-danger signals. Then pro-caspase-1 is recruited and the large protein complex called the NLRP3 inflammasome is formed. This is followed by autocleavage and activation of caspase-1, after which pro-IL-1β and pro-IL-18 are converted into their mature forms. Ion fluxes disrupt membrane integrity, and also mitochondrial damage both play key roles in NLRP3 inflammasome activation (47). Depletion of mitochondria as well as inhibitors that block mitochondrial respiration and ROS production prevented NLRP3 inflammasome activation. Futhermore, genetic ablation of VDAC channels (namely VDAC1 and VDAC3) that are located on the mitochondrial outer membrane and that are responsible for exchanging ions and metabolites with the cytoplasm, leads to diminished mitochondrial (mt) ROS production and inhibition of NLRP3 inflammasome activation (47). Inflammasome activation not only occurs in immune cells, primarily macrophages and dendritic cells, but also in kidney cells, specifically the renal tubular epithelium. The NLRP3 inflammasome is probably involved in the pathogenesis of acute kidney injury, chronic kidney disease, diabetic nephropathy and crystal-related nephropathy (48). The inflammasome also plays a role in autoimmune kidney disease. IL-1 blockade and two recently identified specific NLRP3 inflammasome blockers, MCC950 and β-hydroxybutyrate, may prove to have value in the treatment of inflammasome-mediated conditions.

Autophagosomes derived from tumor cells are referred to as defective ribosomal products in blebs (DRibbles). DRibbles mediate tumor regression by stimulating potent T-cell responses and, thus, have been used as therapeutic cancer vaccines in multiple preclinical cancer models (49). It has been found that DRibbles could induce a rapid differentiation of monocytes and DC precursor (pre-DC) cells into functional APCs (49). Consequently, DRibbles could potentially induce strong innate immune responses via multiple pattern recognition receptors. This explains why DRibbles might be excellent antigen carriers to induce adaptive immune responses to both tumor cells and viruses. This suggests that isolated autophagosomes (DRibbles) from antigen donor cells activate inflammasomes by providing the necessary signals required for IL-1β production.

The Hsp90 system is characterized by a cohort of co-chaperones that bind to Hsp90 and affect its function (50). The co-chaperones enable Hsp90 to chaperone structurally and functionally diverse client proteins. Sahasrabudhe et al. (50) show that the nature of the client protein dictates the contribution of a co-chaperone to its maturation. The study reveals the general importance of the cochaperone Sgt1 (50). In addition to Hsp90, we have to consider Hsp60. Adult cardiac myocytes release heat shock protein (HSP)60 in exosomes. Extracellular HSP60, when not in exosomes, causes cardiac myocyte apoptosis via the activation of Toll-like receptor 4. the protein content of cardiac exosomes differed significantly from other types of exosomes in the literature and contained cytosolic, sarcomeric, and mitochondrial proteins (21).

A new Protein Organic Solvent Precipitation (PROSPR) method efficiently isolates the EV repertoire from human biological samples. Proteomic profiling of PROSPR-enriched CNS EVs indicated that > 75 % of the proteins identified matched previously reported exosomal and microvesicle cargoes. In addition lipidomic characterization of enriched CNS vesicles identified previously reported EV-specific lipid families and novel lipid isoforms not previously detected in human EVs. The characterization of these structures from central nervous system (CNS) tissues is relevant to current neuroscience, especially to advance the understanding of neurodegeneration in amyotrophic lateral sclerosis (ALS), Parkinson’s disease (PD) and Alzheimer’s disease (AD)(15). In addition, study of EVs in brain will enable characterization of the degenerative posttranslational modifications (DPMs) occurring in those proteins.
Neurodegenerative disease is characterized by dysregulation because of NLRP3 inflammasome activation. Alzheimer’s disease (AD) and Parkinson’s disease (PD), both neurodegenerative diseases are associated with the NLRP3 inflammasome. PD is characterized by accumulation of Lewy bodies (LB) formed by a-synuclein (aSyn) aggregation. A recent study revealed that aSyn induces synthesis of pro-IL-1b by an interaction with TLR2 and activates NLRP3 inflammasome resulting in caspase-1 activation and IL-1b maturation in human primary monocytes (43). In addition mitophagy downregulates NLRP3 inflammasome activation by eliminating damaged mitochondria, blocking NLRP3 inflammasome activating signals. It is notable that in this aberrant activation mitophagy downregulates NLRP3 inflammasome activation by eliminating damaged mitochondria, blocking NLRP3 inflammasome activating signals (43).


  1. Lin J, Li J, Huang B, Liu J, Chen X. Exosomes: Novel Biomarkers for Clinical Diagnosis. Scie World J 2015; Article ID 657086, 8 pages
  2. Kahlert C, Melo SA, Protopopov A, Tang J, Seth S, et al. Identification of Double-stranded Genomic DNA Spanning All Chromosomes with Mutated KRAS and p53 DNA in the Serum Exosomes of Patients with Pancreatic Cancer. J Biol Chem 2014; 289: 3869-3875. doi: 10.1074/jbc.C113.532267.
  3. Lässer C, Eldh M, Lötvall J. Isolation and Characterization of RNA-Containing Exosomes. J. Vis. Exp. 2012; 59, e3037. doi:10.3791/3037(2012).
  4. Kaur A, Leishangthem GD, Bhat P, et al. Role of Exosomes in Pathology – A Review. Journal of Pathology and Toxicology 2014; 1: 07-11
  5. Hosseini HM, Fooladi AAI, Nourani MR and Ghanezadeh F. The Role of Exosomes in Infectious Diseases. Inflammation & Allergy – Drug Targets 2013; 12:29-37.
  6. Ciregia F, Urbani A and Palmisano G. Extracellular Vesicles in Brain Tumors and Neurodegenerative Diseases. Front. Mol. Neurosci. 2017;10:276. doi: 10.3389/fnmol.2017.00276
  7. Zhang B, Yin Y, Lai RC, Lim SK. Immunotherapeutic potential of extracellular vesicles. Front Immunol (2014)
  8. Kowal J, Tkach M, Théry C. Biogenesis and secretion of exosomes. Current Opin in Cell Biol 2014 Aug; 29: 116-125.
  9. McKelvey KJ, Powell KL, Ashton AW, Morris JM and McCracken SA. Exosomes: Mechanisms of Uptake. J Circ Biomark, 2015; 4:7   DOI: 10.5772/61186
  10. Xiao T, Zhang W, Jiao B, Pan C-Z, Liu X and Shen L. The role of exosomes in the pathogenesis of Alzheimer’ disease. Translational Neurodegen 2017; 6:3. DOI 10.1186/s40035-017-0072-x
  11. Gonzales PA, Pisitkun T, Hoffert JD, et al. Large-Scale Proteomics and Phosphoproteomics of Urinary Exosomes. J Am Soc Nephrol 2009; 20: 363–379. doi: 10.1681/ASN.2008040406
  12. Waldenström A, Ronquist G. Role of Exosomes in Myocardial Remodeling. Circ Res. 2014; 114:315-324.
  13. Xin H, Li Y and Chopp M. Exosomes/miRNAs as mediating cell-based therapy of stroke. Front. Cell. Neurosci. 10 Nov, 2014; 8(377) doi: 10.3389/fncel.2014.00377
  14. Wang S, Zhang L, Wan S, Cansiz S, Cui C, et al. Aptasensor with Expanded Nucleotide Using DNA Nanotetrahedra for Electrochemical Detection of Cancerous Exosomes. ACS Nano, 2017; 11(4):3943–3949 DOI: 10.1021/acsnano.7b00373
  15. Gallart-Palau X, Serra A, Sze SK. (2016) Enrichment of extracellular vesicles from tissues of the central nervous system by PROSPR. Mol Neurodegener 11(1):41.
  16. Simpson RJ, Jensen SS, Lim JW. Proteomic profiling of exosomes: current perspectives. Proteomics. 2008 Oct; 8(19):4083-99. doi: 10.1002/pmic.200800109.
  17. Sandfeld-Paulsen R, Aggerholm-Pedersen N, Bæk R, Jakobs KR, et al. Exosomal proteins as prognostic biomarkers in non-small cell lung cancer. Mol Onc 2016 Dec; 10(10):1595-1602.
  18. Li W, Li C, Zhou T, et al. Role of exosomal proteins in cancer diagnosis. Molecular Cancer 2017; 16:145 DOI 10.1186/s12943-017-0706-8
  19. Zhang W, Xia W, Lv Z, Xin Y, Ni C, Yang L. Liquid Biopsy for Cancer: Circulating Tumor Cells, Circulating Free DNA or Exosomes? Cell Physiol Biochem 2017; 41:755-768. DOI: 10.1159/00045873
  20. Thakur BK ,…, Williams C, Rodriguez-Barrueco R, Silva JM, Zhang W, et al. Double-stranded DNA in exosomes: a novel biomarker in cancer detection. Cell Research 2014 June; 24(6):766-769. doi:10.1038/cr.2014.44.
  21. Malik ZA, Kott KS, Poe AJ, Kuo T, Chen L, Ferrara KW, Knowlton AA. Cardiac myocyte exosomes: stability, HSP60, and proteomics. Am J Physiol Heart Circ Physiol 304: H954–H965, 2013. doi:10.1152/ajpheart.00835.2012.
  22. De Toro J, Herschlik L, Waldner C and Mongini C. Emerging roles of exosomes in normal and pathological conditions: new insights for diagnosis and therapeutic applications. Front. Immunol. 2015; 6:203. doi: 10.3389/fimmu.2015.00203
  23. Chevilleta JR, Kanga Q, Rufa IK, Briggs HA, et al. Quantitative and stoichiometric analysis of the microRNA content of exosomes. PNAS 2014 Oct 14; 111(41): 14888–14893.
  24. Basu U, Meng F-L, Keim C, Grinstein V, Pefanis E, et al. The RNA Exosome Targets the AID Cytidine Deaminase to Both Strands of Transcribed Duplex DNA Substrates. Cell 2011; 144: 353–363, DOI 10.1016/j.cell.2011.01.001
  25. Pefanis E, Wang J, …, Rabadan R, Basu U. RNA Exosome-Regulated Long Non-Coding RNA Transcription Controls Super-Enhancer Activity. Cell 2015; 161: 774–789.
  26. Kilchert C,Wittmann S & Vasiljeva L. The regulation and functions of the nuclear RNA exosome complex. In RNA processing and modifications. Nature Reviews Molecular Cell Biology 17, 227–239 (2016) doi:10.1038/nrm.2015.15
  27. Guay C, Regazzi R. Exosomes as new players in metabolic organ cross-talk. Diabetes Obes Metab. 2017;19(Suppl. 1):137–146. DOI: 10.1111/dom.13027.
  28. Abramowicz A, Widlak P, Pietrowska M. Proteomic analysis of exosomal cargo: the challenge of high purity vesicle isolation. Molecular BioSystems MB-REV-02-2016-000082.R1
  29. Hopfner K-P, Hartung S. The RNA Exosomes. In Nucleic Acids and Molecular Biology. 2011. Ribonucleases pp 223-244.
  30. Fuessel S, Lohse-Fischer A, Vu Van D, Salomo K, Erdmann K, Wirth MP. (2017) Quantification of MicroRNAs in Urine-Derived Specimens. In Urothelial Carcinoma, Methods Mol Biol 1655:201-226.
  31. Street JM, Barran PE, Mackay CL, Weidt S, et al. Identification and proteomic profiling of exosomes in human cerebrospinal fluid. Journal of Translational Medicine 2012; 10:5.
  32. Pisitkun T, Shen R-F, and Knepper MA. Identification and proteomic profiling of exosomes in human urine. PNAS 2004, Sept 7; 101(36): 13368–13373.
  33. Duijvesz D, Burnum-Johnson KE, Gritsenko MA, Hoogland AM, Vredenbregt-van den Berg MS, et al. Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer. PLoS ONE 2013; 8(12): e82589. doi:10.1371/journal.pone.0082589
  34. Welton JL, Khanna S, Giles PJ, Brennan P, et al. Proteomics Analysis of Bladder Cancer Exosomes. Molecular & Cellular Proteomics 2010; 9:1324–1338. DOI 10.1074/mcp.M000063-MCP201
  35. Lee S, Suh G-Y, Ryter SW, and Choi AMK. Regulation and Function of the Nucleotide Binding Domain Leucine-Rich Repeat-Containing Receptor, PyrinDomain-Containing-3 Inflammasome in Lung Disease. Am J Respir Cell Mol Biol 2016 Feb; 54(2):151–160. DOI: 10.1165/rcmb.2015-0231TR.
  36. Zhang X, Yuan X, Shi H, Wu L, Qian H, Xu W. Exosomes in cancer: small particle, big player. J Hematol Oncol (2015)
  37. Zhao X, Wu Y, Duan J, Ma Y, Shen Z, et al. Quantitative Proteomic Analysis of Exosome Protein Content Changes Induced by Hepatitis B Virus in Huh-7 Cells Using SILAC Labeling and LC–MS/MS. J. Proteome Res.; 2014, 13 (12):5391–5402. DOI: 10.1021/pr5008703
  38. Liang B, Peng P, et al. Characterization and proteomic analysis of ovarian cancer-derived exosomes. J Proteomics. 2013 Mar; 80:171-182.
  39. Beckler MD, Higginbotham JN, Franklin JL,…, Li M, Liebler DC, Coffey RJ. Proteomic analysis of exosomes from mutant KRAS colon cancer cells identifies intercellular transfer of mutant KRAS. Mol. Cell Proteomics. 2013 Feb 12; (2).
  40. Alvarez-Llamas G, Díaz J, Zubiri I. Proteome of Human Urinary Exosomes in Diabetic Nephropathy. In Biomarkers in Kidney Disease. Vinood B. Patel, Ed. Springer Science 2015; pp 1-21. DOI 10.1007/978-94-007-7743-9_22-1
  41. Simpson RJ, Jensen SS, Lim JW. Proteomic profiling of exosomes: current perspectives. Proteomics. 2008 Oct; 8(19):4083-99. doi: 10.1002/pmic.200800109.
  42. Scheya JKL, Luther M, Rose KL. Proteomics characterization of exosome cargo. Methods 2015 Oct; 87(1): 75-82.
  43. Kim M-J, Yoon J-H & Ryu J-H. Mitophagy: a balance regulator of NLRP3 inflammasome Activation. BMB Rep. 2016; 49(10): 529-535.
  44. Eun-Kyeong Jo, Kim JK, Shin D-M and C Sasakawa. Molecular mechanisms regulating NLRP3 inflammasome activation. Cell Molec Immunol 2016; 13: 148–159. doi:10.1038/cmi.2015.95
  45. Leemans JC, Cassel SL, and Sutterwala FS. Sensing damage by the NLRP3 inflammasome. Immunol Rev. 2011 Sept; 243(1): 152–162. doi:10.1111/j.1600-065X.2011.01043.x.
  46. Hirota JA, Im H, Rahman MM, Rumzhum NN, Manetsch M, Pascoe CD, Bunge K, Alkhouri H, Oliver BG, Ammit AJ. The nucleotide-binding domain and leucine-rich repeat protein-3 inflammasome is not activated in airway smooth muscle upon toll-like receptor-2 ligation. Am J Respir Cell Mol Biol. 2013 Oct; 49(4):517-24. doi: 10.1165/rcmb.2013-0047OC.
  47. Zhong Z, Sanchez-Lopez E, Karin M. Autophagy, NLRP3 inflammasome and auto-inflammatory immune diseases. Clin Exp Rheumatol. 2016 Jul-Aug; 34(4 Suppl 98):12-6. Epub 2016 Jul 21.
  48. Hutton HL, Ooi JD, Holdsworth SR, Kitching AR. The NLRP3 inflammasome in kidney disease and autoimmunity. Nephrology (Carlton). 2016 Sep; 21(9):736-44. doi: 10.1111/nep.12785
  49. Xing Y, Cao R and Hu H-M. TLR and NLRP3 inflammasome-dependent innate immune responses to tumor-derived autophagosomes (DRibbles). Cell Death and Disease (2016) 7, e2322; doi:10.1038/cddis.2016.206
  50. Sahasrabudhe P, Rohrberg J, Biebl MM, Rutz DA, Buchner J. The Plasticity of the Hsp90 Co-chaperone System. Molecular Cell 2017 Sept; 67:947–961.


Read Full Post »

How the ACLU Won the Fight Against Patenting Genes: Article and video on  the History of the Issue of Gene Patents

Curator: Stephen J. Williams, PhD


please see the TED talk below on how ACLU took on the Gene Patenting Industry:

Tania Simoncelli – How I took on the gene patent industry — and won – Ted Talks 2016

This fight started with the patenting of the BRCA1/2 gene mutants, which increase the risk of breast/ovarian cancer in women who harbor these mutation as well as their offspring, which would be the basis for genetic testing services offered by Myriad Genetics.

However, as seen below, these patent fights and the patenting of DNA has been around since the mid 1970’s, with the advent of cloning and other molecular biology techniques.


Robert Cook-Deegan and Christopher Heaney in Annu Rev Genomics Hum Genet. 2010 Sep 22; 11: 383–425.

In April 2009, the U.S. Patent and Trademark Office (USPTO) granted the 50,000th U.S. patent that entered the DNA Patent Database at Georgetown University. That database includes patents that make claims mentioning terms specific to nucleic acids (e.g., DNA, RNA, nucleotide, plasmid, etc.) (64). The specificity of many terms unique to nucleic acid structures makes it possible to monitor patents that correspond to and arise largely from research in genetics and genomics. Patents have been a part of the story of the rise of genetics and genomics since the 1970s, and not just because they can be counted but also because science and commerce have been deeply intertwined, one chapter in the story of modern biotechnology in medicine, agriculture, energy, environment, and other economic sectors. The first DNA patents were granted in the 1970s, but numbers surged in the mid-1990s as molecular genetic techniques began to produce patentable inventions.

This database (Delphion Patent Database) can be reached at (

From Cook-Deegan, R. and C. Heany. Annu Rev Genomics Hum Genet. 2010 Sep 22; 11: 383–425.

An external file that holds a picture, illustration, etc. Object name is nihms218000f1.jpg

U.S. Patents: DNA Patents and Patent Applications by Year, 1984–2008. The DNA Patent Database contains patents obtained by searching the Delphion Patent Database ( with an algorithm posted on the DNA Patent Database website that searches for granted U.S. patents (since 1971) and published applications (since 2001) in U.S. patent classes related to genetics and genomics as well as claims that include words specific to nucleic acids, genetics, and genomics. The year 1984 is the first for which more than 100 granted patents are in the DNA Patent Database. Data from Reference 64.

The authors make several points concerning obtaining patents in the genomics field including:

  • Differences in patent practice can be important to scientists working in genetics and genomics. In the United States, a patent goes to the first inventor. If patents or patent applications overlap and the first person to invent is in dispute, then the patent office initiates what’s called an interference proceeding, with intricate rules about deciding priority of invention.
  • Interferences are more than twice as common in biotechnology patents than in any other patent class, six times higher than patents on average (140).
  • The United States also allows a year’s grace period from publication of information pertinent to a patent claim, whereas any public disclosure becomes “prior art” that can defeat patent claims in other jurisdictions.


International harmonization of DNA patents exist including:

  1. 1973 European Patent Convention created the European Patent Office (EPO). EPO can issue a patent valid in signatory countries
  2. 1995 Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement committed signatory countries to adopt patent standards mainly modeled on the developed-country model of strong patent protection
  3. 1998 Biotechnology Directive: the Directive became an important element of European patent law that binds national governments to comply with it
  4. Both the United States House and Senate of the 111th Congress are considering bills similar to one passed by the House of Representatives (but not the Senate) in the 110th Congress (2007–2008). Two provisions particularly relevant to genetic and genomic inventions are (a) shifting from the current “first to invent” U.S. standard to “first inventor to file,” as in the rest of the world; and (b) establishing a mechanism to challenge patent claims closer to the European opposition process.

top 30 institutions holding patents in the DNA Patent Database. Among them are

  1. Agribusiness and chemical companies (Monsanto and DuPont)
  2. U.S. Government (largely attributable to the large intramural research program at the National Institutes of Health)
  3. Public and private universities (Universities of California and Texas, Johns Hopkins, Harvard, Stanford, MIT, etc.)
  4. Pharmaceutical firms (Novartis, Glaxo SmithKline, Pfizer, Merck, SanofiAventis, Takeda, Bayer, Novo Nordisk, Lilly, etc.)
  5. Established biotechnology firms (Genentech, Amgen, Genzyme, ISIS, etc.)
  6. Firms created to exploit genomic technologies (Incyte, Human Genome Sciences, etc.)
  7. Instrumentation and DNA chip firms (LifeTechnologies, Affymetrix, Becton, Dickinson, etc.)
  8. Academic research institutes (Institut Pasteur, Salk, Scripps, and Ludwig Institutes, Cold Spring Harbor Laboratories, etc.)
  9. Hospitals with research units (e.g., Massachusetts General Hospital)







Top U.S. DNA patent holders. The authors compiled a list of assignees with at least 100 patents, combined different names for the same assignee, and updated names to reflect corporate mergers and acquisitions. Patent counts are from the Delphion Patent Database for U.S. patents granted as of October 26, 2009, using the DNA Patent Database algorithm (64). Data from Reference 64. From Cook-Deegan, R. and C. Heany. Annu Rev Genomics Hum Genet. 2010 Sep 22; 11: 383–425.

And an opinion article by Harvard Law School arguing against the patent-ability of natural products such as DNA:

DNA Sequences as Unpatentable Subject Matter

by  Victor Song & Prof. Peter Hutt

How Merck’s attempt to patent Vitamin B12 may have started a precedent:

In addition to Kuehmsted, the case most frequently cited to support the patentability of “purified and isolated” substances is Merck & Company v. Olin Mathieson Chemical Corporation [44] . In 1958, the United States Court of Appeals for the Fourth Circuit addressed the metes and bounds of the product of nature exception in Merck . The invention at the center of Merck was entitled, “Vitamin B(12)-Active Composition and Process of Preparing Same”.

Prior to the discovery claimed by the patent, vitamin B(12) was unknown to man. What had been known was that patients who had pernicious anemia could mitigate the effects of their condition by consuming cow liver. For years the scientific community analyzed cow liver to determine what in cow liver was the therapeutically active compound. For lack of a better term, scientists named this unknown therapeutic agent the “anti-pernicious anemia” compound.

After a considerable amount of chemical analysis, scientists at Merck isolated the “anti-pernicious anemia” compound in cow liver. They also discovered an alternate source of the “anti-pernicious anemia” compound. Merck scientists were able to harvest the “anti-pernicious anemia” compound from the fermenting eluent of certain microorganisms. After isolating and characterizing the structure of the newly found “anti-pernicious anemia” compound, the scientist renamed it vitamin B(12) for its chemical similarities to the vitamin B family.

Having discovered vitamin B(12), Merck filed for and obtained U.S. patent 2,703,302 (‘the ‘302 patent”) covering both the process of making vitamin B(12) and the actual chemical compound for vitamin B(12). Only the product claims were at issue in Merck [45] . A representative product claim reads:

A vitamin B(12)-active composition comprising recovered elaboration products of the fermentation of a vitamin B(12)-activity producing strain of Fungi selected from the class consisting of Schizomycetes, Torula, and Eremothecium, the L.L.D. activity of said composition being at least 440 L.L.D. units per milligram and less than 11 million L.L.D. units per milligram.[46]

Prior to the appeal, the district court had determined that the product claims were invalid as products of nature. The Court of Appeals for the Fourth Circuit reversed. In reversing the District Court, the Fourth Circuit followed a line of reasoning similar to Kuehmsted.The Court of Appeals reasoned that the product of nature was the unpurified fermenting eluent which had no therapeutic value. However, Merck’s purified fermenting eluent had therapeutic value. Thus, the court believed Merck’s purified product, which was essentially vitamin B(12), was a different from unpurified fermenting eluent. Since Merck’s purified product was different from the product of nature, the court reasoned that it could not be a product of nature.

The main weakness in the Merck decision is similar to weakness of the Kuehmsted decision. Can vitamin B(12) be considered “new” if it always existed in cow liver? In addition, is it necessary to grant Merck both product and process claims? Even without the product claims, Merck will still be able to profit handsomely from the process claims alone. In addition, Merck could have applied for a vitamin B(12) use patent. Merck could have patented the therapeutic use of their vitamin B(12) for treating pernicious anemia.

There are two interesting aspects of the courts decision in Merck . First, in coming to its conclusion that the purified fermentate was not a product of nature the court turned to the phrase “new and useful” contained in section 101. This was an appropriate focus of analysis for the court because it is from this phrase that the product of nature exception is derived. However, in interpreting the phrase “new and useful” the court substituted the patent terms “novelty and utility”.[47]

The threshold for meeting the utility requirement for patentability is very low. Nearly all inventions meet the utility requirement. It is the Fourth Circuit’s reliance on the patent requirement of novelty for the term “new” which is more interesting. The court’s reliance of the novelty standard presents an interesting interpretation because the product of nature exception is not premised solely on the novelty requirement.[48] The product of nature doctrine simply states that products of nature are not patentable because they are made by nature, not by man. Furthermore, since products of nature existed in nature prior to man’s discovery of them, they are not new and thus excluded from patentability.

The novelty standard requires a different analysis. Although the issue of novelty also addresses the question as to whether or not an invention is new, the question of novelty is answered by looking at the prior art. Roughly speaking, the prior art exemplifies man’s entire body of scientific knowledge at the time of invention. In order to be novel, an invention must not be recited in one piece of prior art. For example, to demonstrate a lack of novelty, a single scientific journal article must describe how to extract vitamin B(12) from a fungal fermenting eluent.

The problem with using the novelty requirement to interpret “new” with regard to product of nature purposes is that no product of nature would be found in the prior art before it was discovered. In effect, using the novelty standard eviscerates the product of nature exception. The novelty standard also circumvents the purpose of the product of nature doctrine which is to prevent man from claiming “manifestations of [the] laws of nature”.[49]

For illustrative purposes we can use vitamin B(12) as an example. According to the Fourth Circuit, in order for vitamin B(12) to be considered a product of nature it must lack novelty. To lack novelty, vitamin B(12) must be recited in a single prior art source. Before its discovery by Merck, vitamin B(12) was unknown and hence could not be found in any prior art source. However, vitamin B(12) has always existed as a naturally occurring substance in cow liver (i.e. a product of nature). Despite clear evidence that vitamin B(12) is a product of nature, the Fourth Circuit would permit a patent on vitamin B(12).

This approach nullifies the purpose of the product of nature doctrine. By using the novelty standard, the court never asks the question whether or not vitamin B(12) was made by man. The purpose of the product of nature doctrine is to prevent man from patenting what is made by nature and should thus be accessible to everyone. The Fourth Circuit’s novelty analysis does not consider this.

The second interesting point about Merck is the product claim itself. In claim 1 recited above, vitamin B(12) is claimed only as a product of fermentation. Merck did not claim the vitamin B(12)chemical formula. This is a significant distinction because competitors could design around Merck’s product claim if they could manufacture vitamin B(12) without utilizing the fermenting eluent of fungi. For example, a manufacturer who processed cow livers to obtain vitamin B(12) could sell its version of vitamin B(12) product without infringing Merck’s product claims[50] . With cases such as Kuehmsted and Merck on one side of the product of nature debate, there are several cases which fall on the other side of the debate[51] . In addition to Funk Brothers, General Electric Co. v. De Forest Radio Co. [52] is representative of a court decision upholding the product of nature exception. The invention at the center of General Electric was the chemical element tungsten (W). General Electric was assigned U.S. Patent 1,082,933 (the ‘933 patent) for tungsten.

Is DNA Patentable Subject Matter?

As the cases discussed indicate, it is not entirely clear whether or not DNA sequences are patentable subject matter. What is clear is that processes for isolating DNA sequences are permissible as are product claims that use DNA sequences (such as Chakrabarty’s genetically modified micro-organism). In addition, inventors could get patents for the therapeutic uses of their DNA sequence products.

The Supreme Court’s decision in Chakrabarty indicates an intention by the court to expand the scope of patentable subject matter, but the product of nature doctrine still remains. Whether or not the product of nature exception will apply to DNA sequences depends upon how the courts view DNA sequences. If the courts analogize isolated and purified DNA sequences to aspirin or vitamin B(12), then DNA sequences would be moved outside the product of nature exception and into the scope of patentable subject matter. On the other hand, if DNA sequences are comparable to tungsten or “manifestation of laws of nature” then the product of nature exception would apply.

As the law is currently interpreted by patent practitioners, the product of nature exception to patentable subject matter is considered a technical problem related to drafting DNA sequence product claims. For the patent attorney, all that is necessary to get around the product of nature exception is to not claim a DNA in its naturally occurring form. In order to resolve this technical problem, a patent attorney will claim DNA sequences in an “isolated and purified” form. For example, Amgen’s DNA sequence claim to EPO in United States Patent 4,703,008 reads, “A purified and isolated DNA sequence consisting essentially of a DNA sequence encoding human erythropoietin.”[57]

DNA sequences have been described as molecular strands of genetic information.[59] Information which is so fundamental that it is akin to the natural laws of science. This fundamental information, in the words of Funk Brothers , is “part of the storehouse of knowledge of all men. They are manifestations of laws of nature, free to all men and reserved exclusively to none.”[60] As manifestations of the laws of nature, DNA sequences should be free to all men. By unlocking the hidden secrets of the genetic code, scientists will be able to produce new medical therapies to treat a wide range of illnesses. It is these new therapeutic inventions, their uses, and the processes for making them which should be patented, not the DNA sequences used to implement these inventions.

Although DNA sequences have been analogized to long polymer chains[65] and as a result should be treated similarly to synthesized polymers, this is not entirely correct. The analogy fails because an inventor’s ingenuity plays a part in designing a polymer chain. A chemist will manipulate reaction conditions to produce a polymer with certain characteristics such as strength, durability, and flexibility. This is not the case with DNA. The inventor’s ingenuity, once again, plays no part in designing the DNA sequence as this was the work of nature over thousands of years of evolution.

So the Harvard Law School article concludes:

  1. Patentable subject matter is statutorily defined in 35 U.S.C. Section 101 to include new and useful products (machines, manufactures, and compositions of matter) and processes. However, subject matter which fall outside the scope of Section 101 are products of nature.
  2. There are two general arguments for excluding products of nature from patentable subject matter. First, is that products of nature are the “manifestations of laws of nature”. As the building blocks of science, to grant ownership to these fundamental products would do more harm than good to scientific innovation. Second, is the patent system’s purpose in encouraging inventorship. An inherent aspect of inventorship is interaction of human ingenuity with the natural world. Products of nature are excluded from patentability because they would grant ownership rights to the natural world without any element of human ingenuity. These product of nature patents would reward inventors for nature’s work.

Man has played no part in creating DNA. What required man’s ingenuity was isolating, purifying, and sequencing the DNA. These inventions deserve patent protection.

Other articles on this Open Access Journal on Patents, Patent Fights and Intellectual Property include:

Top Twenty Universities on a list of the top 100 worldwide universities that received the most U.S. utility patents in 2014

The Patents for CRISPR, the DNA editing technology as the Biggest Biotech Discovery of the Century

Innovators can exit with an idea: How to Monetizing Patents and ideas: launches Idea Lab

RNA related IP Patents Awards

Linus Pauling: On Lipoprotein(a) Patents and On Vitamin C

Recent Patents on Biomarkers

Litigation on the Way: Broad Institute Gets Patent on Revolutionary Gene-Editing Method





Read Full Post »

Insulin, Heat from Sugar, and Research on Diabetes for a Cure

Author: Danut Dragoi, PhD


Insulin is a complex molecule, discovered in early 1916 by Paulescu. It is a relative large molecule that has a molecular mass of 5807.57 amu, that corresponds to the following chemical formula C257H383N65O77S6 .

Beyond its well known role in human being, insulin have many interesting structural features.

The picture below shows the structure of the molecule of the insulin. The colored spheres represent the atoms C, H, N, O, and S. This arrangements of atoms results from x-ray proteins crystallography of single crystals obtained from pure insulin.

Insulin molec structure


The yellow spheres in the picture correspond to sulfur atoms that somehow are getting in the structure from a certain source, probably from foods like eggs. It is important to mention that if one component atom is missing in our body, for example Sulfur, the pancreas will not produce the insulin molecule we needed.

Next picture below shows single crystals grown in the lab on Earths as well as in outer space.

Insulin crystals NASA


As we see high quality crystals were obtained in low gravity conditions by NASA. The preferred instrument for producing high quality x-ray diffraction measurements is the synchrotron diffractometer, see link in here.

Heat source from sugar

Metabolic processes require an optimal temperature. . At temperatures higher or lower than 37 °C, enzymes will not function optimally. Too high – they denature opens in a new window, too low – they will slow down the rate at which metabolic processes proceed. A rise of just 2 °C will cause disruption to the internal functioning of a human and should the temperature rise between 43 °C and 45 °C, death may occur. Our tolerance to lower temperatures is much greater. The temperature needs to fall below 23 °C to cause death. So it is important to know about the thermal source generator in our body and its estimated environmental temperature.

The idea of calculating the temperature of human body impose serious computational barriers, but measuring it is not a problem. A simplified approach on this topic can be an approximation with reasonable assumptions. Complex biochemical reactions occur every second in our body. An exact consideration of all chemical reactions in human body is a complicated task, but a simplification can be done using the oxidation of sugar reaction.

Assuming an average body of 70 kg and all sugar from the blood, to be about 5 grams in 5 liters of blood, and considering the density of all blood close to 1g/cubic cm, we can consider the reaction of glucose, Equation (1):

342 g ———————–    2870 kJ

C6H12O6 + 6O2 –> 6CO2 + 6H2O + 2870 kJ ————— (1)

70 g ————————       q=?

The numbers above the chemical reaction of sugar (1) are the molecular mass in grams and the energy released in kJ. Below are the actual amount of sugar in a 70 kg human body and the q, the actual heat generated. Knowing the total amount of sugar in our body, which is approximated as 5 g/5kg (in blood)*5 kg (blood) + 5 g/5 kg *65 kg=70 g sugar and the molecular mass of sugar as 342.2965 g/mol, we have the amount of heat reduced from 2870 kJ* 70/342= 587.4 kJ which represents the heat q in Equation (1). An equation for variable q is shown in Equation (2):

q=mc(T-T’) —————————————–(2)

where we describe the thermal energy needed to raise the body temperature from T’ to T (T'<T). For body temperature T=37 C deg, normal temperature of human body,  m=70 kg-0.15*70 kg-0.15*70 kg=49 kg (where the first factor 0.15 represents the bones and second 0.15 is for the fat in which sugar is assumed not to react with Oxygen as in equation (1) and c= 2624 J/kg/C deg is the minimum specific heat of muscles . Since T’, could be the temperature of the environment in which the human body dissipates the thermal energy, is the only unknown in Equation (1), we can solve for T’, and find T’= 32.4 C deg. The value obtained is in a safe range, above room temperature with some C degrees. The modeling captures well the effect of sugar as an important source of energy for human body.

A study on diabetes indicates that heat treatment improves glucose tolerance. The structure of insulin as a protein suggests the link between our DNA programmed to producing specific proteins needed in our body including insulin. This is a promising avenue for future solutions for a cure of diabetes.

Genetics for a Cure

A recent research on converting fatty tissue into mature beta cells, shows that insulin can be produced by newly created beta like cells raising new expectations for cure of the diabetes.

An interesting posting, discusses in detail the findings of scientists at the Swiss Federal Institute of Technology (ETH) in Zurich, where the investigators added a highly complex synthetic network of genes to the stem cells to recreate precisely the key growth factors involved in this maturation process.





Read Full Post »

DNA change with seeding asbestos molecules in living cells

Author: Danut Dragoi, PhD

As a fact, it is well known that some substances are producing DNA changes in human body. One of those substances is asbestos, see link in here, in which debatable reasons are revisited with less convincing arguments. One important aspect of the interaction of asbestos with living cells is its symmetry which is reflected in its physical and chemical properties. One important feature of substances interacting with DNA structure is to have element symmetry in common. DNA macromolecule is a low symmetry molecule and is expected that DNA’s elements of symmetry to be found in asbestos group symmetry. Looking for crystal structure of asbestos we find the powder diffraction file PDF-21-543 that contains that information, see link in here.

From symmetry point of view, we can distinguish the chirality symmetry of asbestos, which requires an axis “2” of symmetry or a mirror plan “m” that both cross the center of the unit cell, see link in here.

A schematic of chemical make up of asbestos can be seen below, see link in here

Asbestos chemical make up


At first glance we see that the chemical formula in the picture above, H4Mg3O9Si2, corresponds to that of chrysotile, one distinguished form of asbestos. We notice the ionic bond between the Silicon tetrahedrons SiO4 using Mg++ ion between two O- ions. Since the ionic bonds are not too strong, we can imagine that a SiO4 tetrahedron can replace a PO4 tetrahedron in DNA back bone with important consequences on DNA functionality in human body. As a fact, not all asbestos structures produce cancers in human body, therefore the chirality symmetry must play an important role. From this point of view we can state, with some degree of certainty, that asbestos of D-form chirality, that fits the DNA chirality, is the culprit in the asbestos induced cancers.

Looking at the rate of cancers over 50 years we can find that the rate of cancers increased, see link in here. How we explain this? Some reasons are linked with aging, see link in here. However, other factors exists such as silicosis and its role on lung cancer, see link in here.

In the studies considered by IARC (NB-International Agency for Research on Cancer), they reported that lung cancer risk tended to increase with cumulative exposure to RCS (NB- respirable crystalline silica), duration of exposure, peak intensity of exposure, the presence of silicosis and length of follow-up time from diagnosis of silicosis. However, the findings were not consistent, i.e. those that observed a relationship with cumulative exposure did not always observe one with duration of exposure and vice versa. Again, here is the symmetry play, where not all silica is in D-form chirality to produce cancers.

As we have seen before, the presence of silicon tetrahedrons in the asbestos structure suggests that Silica is a major player in producing cancers. The main source of dangerous silica is not only in asbestos, it is in any mining and silicate processing industry, in which cement industry uses large quantities of powdered quartz, sometimes in very fine grain size that could be in the nano-size range. The roads development in the last 100 years, based on cement, is suggesting a correlation with cancers development.


Read Full Post »

Older Posts »