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Gene engineering and editing specifically are becoming more attractive. There are many applications derived from microbial origins to correct genomes in many organisms including human to find solutions in health.
There are four customizable DNA specific binding protein applications to edit the gene expression in translational genomics. The targeted DNA double-strand breaks (DSBs) could greatly stimulate genome editing through HR-mediated recombination events. We can mainly name these site-specific DNA DSBs:
meganucleases derived from microbial mobile genetic elements (Smith et al., 2006),
most recently the RNA-guided DNA endonuclease Cas9 from the type II bacterial adaptive immune system CRISPR (Cong et al., 2013;Mali et al., 2013a).
There is a new ground breaking study published in Science by Valentino Gantz and Ethan Bier of the University of California, San Diego, described an approach called mutagenic chain reaction (MCR).
This group developed a new technology for editing genes that can be transferable change to the next generation by combining microbial immune defense mechanism, CRISPR/Cas9 that is the latest ground breaking technology for translational genomics with gene therapy-like approach.
In short, this so-called “mutagenic chain reaction” (MCR) introduces a recessive mutation defined by CRISPR/Cas9 that lead into a high rate of transferable information to the next generation. They reported that when they crossed the female MCR offspring to wild type flies, the yellow phenotype observed more than 95 percent efficiency.
Structural and Metagenomic Diversity of Cas9 Orthologs
(A) Crystal structure of Streptococcus pyogenes Cas9 in complex with guide RNA and target DNA.
(B) Canonical CRISPR locus organization from type II CRISPR systems, which can be classified into IIA-IIC based on their cas gene clusters. Whereas type IIC CRISPR loci contain the minimal set of cas9, cas1, andcas2, IIA and IIB retain their signature csn2 and cas4 genes, respectively.
(C) Histogram displaying length distribution of known Cas9 orthologs as described in UniProt, HAMAP protein family profile MF_01480.
(D) Phylogenetic tree displaying the microbial origin of Cas9 nucleases from the type II CRISPR immune system. Taxonomic information was derived from greengenes 16S rRNA gene sequence alignment, and the tree was visualized using the Interactive Tree of Life tool (iTol).
(E) Four Cas9 orthologs from families IIA, IIB, and IIC were aligned by ClustalW (BLOSUM). Domain alignment is based on the Streptococcus pyogenes Cas9, whereas residues highlighted in red indicate highly conserved catalytic residues within the RuvC I and HNH nuclease domains.
There is a big difference between the new type of mutation and traditional mutation is expressivity of the character since previously mutations were passive and non-transferable at 100% rate. However, in classical Mendelian Genetics, only one fourth f the recessive traits can be presented in new generation. Yet, in this case this can be achieve about 97% plus transferred to new generation.
MCR alterations is active that is they convert matching sequences at the same target site so mutated sites took over the wild type character without degenerating by wild type alleles segregating independently during the breeding process
Therefore, the altered sequences routinely replace the wild type (original) sequences at that site. The data demonstrated that among 92 flies, only one female became wild type but remaining 41 females had yellow eyes yet all 50 males showed wild type eye coloring at the second generation.
The genetic engineering of the genome occurred in a single generation with high efficiency.
Their technique developed by Gantz and Bier had three basic parts:
Both somatic and germline cells expressed a Cas9 gene,
A guide RNA (gRNA) targeted to a genomic sequence of interest,
The Cas9/gRNA cassettes have the flanking homolog arms that matches the two genomic sequences immediately adjacent to either side of the target cut site
There are many applications in translational genomics that requires multiple steps to make it perfect for complicated organisms, such as plants, mosquitoes and human diseases.
Short Walk from Past to the Future of CRISPR/Cas9
The RNA-guided Cas9 nuclease from the microbial clustered regularly interspaced short palindromic repeats(CRISPR)adaptive immune system can be used to facilitate efficient genome engineering in eukaryotic cells by simply specifying a 20-nt targeting sequence within its guide RNA.
CRISPR/Cas systems are part of the adaptive immune system of bacteria and archaea, protecting them against invading nucleic acids such as viruses by cleaving the foreign DNA in a sequence-dependent manner.
The latest ground-breaking technology for genome editing is based on RNA-guided engineered nucleases, which already hold great promise due to their:
simplicity,
efficiency and
versality
Although CRISPR arrays were first identified in the Escherichia coli genome in 1987 (Ishino et al., 1987),
their biological function was not understood until 2005, when it was shown that the spacers were homologous to viral and plasmid sequences suggesting a role in adaptive immunity (Bolotin et al., 2005; Mojica et al., 2005; Pourcel et al., 2005).
Two years later, CRISPR arrays were confirmed to provide protection against invading viruses when combined with Cas genes (Barrangou et al., 2007).
The mechanism of this immune system based on RNA-mediated DNA targeting was demonstrated shortly thereafter (Brounset al., 2008; Deltcheva et al., 2011; Garneau et al., 2010; Marraffini and Sontheimer, 2008).
The most widely used system is the type II clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 (CRISPR-associated) system from Streptococcus pyogenes (Jinek et al., 2012).
Then, five independent groups demonstrated that the two-component system was functional in eukaryotes (human, mouse and zebrafish), indicating that the other functions of the CRISPR locus genes were supported by endogenous eukaryotic enzymes (Cho et al., 2013, Cong et al., 2013, Hwang et al., 2013, Jinek et al., 2013 and Mali et al., 2013).
Beginning with target design, gene modifications can be achieved within as little as 1-2 weeks, and modified colonial cell lines can be derived within 2-3 weeks
Genome editing with site-specific nucleases.
Double-strand breaks induced by a nuclease at a specific site can be repaired either by non-homologous end joining (NHEJ) or homologous recombination (HR). In most cases, NHEJ causes random insertions or deletions (indels), which can result in frameshift mutations if they occur in the coding region of a gene, effectively creating a gene knockout.
Alternatively, when the DSB generates overhangs, NHEJ can mediate the targeted introduction of a double-stranded DNA template with compatible overhangs
Even though the generation of breaks in both DNA strands induces recombination at specific genomic loci, NHEJ is by far the most common DSB repair mechanism in most organisms, including higher plants, and the frequency of targeted integration by HR remains much lower than random integration.
Unlike its predecessors, the CRISPR/Cas9 system does not require any protein engineering steps, making it much more straightforward to test multiple gRNAs for each target gene
Unlike ZFNs and TALENs, the CRISPR/Cas9 system can cleave methylated DNA in human cells (Hsu et al., 2013), allowing genomic modifications that are beyond the reach of the other nucleases (Ding et al., 2013).
The main practical advantage of CRISPR/Cas9 compared to ZFNs and TALENs is the ease of multiplexing. The simultaneous introduction of DSBs at multiple sites can be used to edit several genes at the same time (Li et al., 2013; Mao et al., 2013) and can be particularly useful to knock out redundant genes or parallel pathways.
Finally, the open access policy of the CRISPR research community has promoted the widespread uptake and use of this technology in contrast, for example, to the proprietary nature of the ZFN platform.
The community provides access to plasmids (e.g., via the non-profit repository Addgene), web tools for selecting gRNA sequences and predicting specificity:
hosts active discussion groups (e.g.: https://groups.google. com/forum/#!forum/crispr).
Downside:
One area that will likely need to be addressed when moving to more complex genomes, for instance, is off-target CRISPR/Cas9 activity since fruit fly has only four chromosomes and less likely to have off-target effects. However, this study provided proof of principle.
Yet, this critics is not new since one of the few criticisms of the CRISPR/Cas9 technology is the relatively high frequency of off-target mutations reported in some of the earlier studies (Cong et al., 2013; Fu et al., 2013; Hsu et al., 2013; Jiang et al., 2013a; Mali et al., 2013; Pattanayak et al., 2013).
Several strategies have been developed to reduce off-target genome editing, the most important of which is the considered design of the gRNA.
fusions of catalytically inactive Cas9 and FokI nuclease have been generated, and these show comparable efficiency to the nickases but substantially higher (N140-fold) specificity than the wild-type enzyme (Guilinger et al., 2014; Tsai et al., 2014)
Altering the length of the gRNA can also minimize non-target modifications. Guide RNAs with two additional guanidine residues at the 5′ end were able to avoid off-target sites more efficiently than normal gRNAs but were also slightly less active at on-target sites (Cho et al., 2014)
What more:
The CRISPR/Cas9 system can be used for several purposes in addition to genome editing:
The ectopic regulation of gene expression, which can provide useful information about gene functions and can also be used to engineer novel genetic regulatory circuits for synthetic biology applications.
The external control of gene expression typically relies on the use of inducible or repressible promoters, requiring the introduction of a new promoter and a particular treatment (physical or chemical) for promoter activation or repression.
Disabled nucleases can be used to regulate gene expression because they can still bind to their target DNA sequence. This is the case with the catalytically inactive version of Cas9 which is known as dead Cas9 (dCas9).
Preparing the host for an immunotherapy is possible if it is combined with TLR mechanism:
On the other hand, the host mechanism needs to be review carefully for the design of an effective outcome.
The mechanism of microbial response and infectious tolerance are complex.
During microbial responses, Toll-like receptors (TLRs) play a role to differentiate and determine the microbial structures as a ligand to initiate production of cytokines and pro-inflammatory agents to activate specific T helper cells.
Uniqueness of TLR comes from four major characteristics of each individual TLR :
ligand specificity,
signal transduction pathways,
expression profiles and
cellular localization.
Thus, TLRs are important part of the immune response signaling mechanism to initiate and design adoptive responses from innate (naïve) immune system to defend the host.
TLRs are expressed cell type specific patterns and present themselves on APCs (DCs, MQs, monocytes) with a rich expression levels Specific TLR stimulat ion links innate and acquired responses through simple recognition of pathogen-associated molecular patterns (PAMPs) or co-stimulation of PAMPs with other TLR or non-TLR receptors, or even better with proinflammatory cytokines.
Some examples of ligand – TLR specificity shown in Table1, which are bacterial lipopeptides, Pam3Cys through TLR2, double stranded (ds) RNAs through TLR3, lipopolysaccharide (LPS) through TLR4, bacterial flagellin through TLR5, single stranded RNAs through TLR7/8, synthetic anti-viral compounds imiquinod through TLR 7 and resiquimod through TLR8, unmethylated CpG DNA motifs through TLR9.
The specificity is established by correct pairing of a TLR with its proinflammatory cytokine(s), so that these permutations influence creation and maintenance of cell differentiat ion.
Immunotherapy: The immune cells can be used as a sensor to scavenger the circulating malformed cells in vivo diagnostics or attack and remember them, for instance, relapse of cancer, re-infection with a same or similar agent (bacteria or virus) etc.
Not only using unique microbial and other model organism properties but also using the human host defense mechanism during innate immune responses may bring a new combat to create a new method of precision medicine. This can be a new type of immunotherapy, immune cell mediated gene therapy or vaccine even a step for an in vivo diagnostics.
Molecular Genetics took a long road from discovery of restriction enzymes, developing PCR assays, cloning were the beginning. Now, having technology to sequence and compare the sequences between organisms also help to design more sophisticated methods.
Generating mutant lines in Drosophila with the classical genetics methods relies on P elements, a type of transposon and balancers after crossing selected flies with specific markers. This fly pushing is a very tedious work but powerful to identify primary pathways, mechanisms and gene interactions in system and translational genomics.
Thus, Microbial Immunomodulation is an important factor not only using the microorganisms or their mechanisms but also modulating the immune cells based on the host interaction may generate new types of diagnostics and targeted therapy tools.
Microbial immunomodulation. Microbes from the environment, and from the various microbiota, modulate the immune system. Some of this is due to direct effects of defined microbial products on elements of the immune system. But modulation of the immune system also secondarily alters the host–microbiota relationship and leads to changes in the composition of the microbiota, and so to further changes in immunoregulation (shown as indirect pathways). At the end of the day balance is the key for survival.
CRISPR-Cas9 mediated NHEJ in transient transfection experiments.
Table 1.
Species
Transformation method
Cas9 codon optimization
Promoters (Cas9, gRNA)
Target
Mutation frequency
Detection method
Off-target (no. of sites analyzed)
Detection method
Multiplex (deletion)
Reference
Arabidopsis thaliana
PEG-protoplast transfection
Arabidopsis (with intron)
CaMV35SPDK, AtU6
PDS3<comma> FLS2
1.1–5.6%
PCR + sequencing
Li et al. (2013)
A. thaliana
Leaf agroinfiltration
Arabidopsis (with intron)
CaMV35SPDK, AtU6
PDS3
2.70%
PCR + sequencing
Yes (48 bp)
Li et al. (2013)
A. thaliana
PEG-protoplast transfection
Arabidopsis (with intron)
CaMV35SPDK, AtU6
RACK1b<comma> RACK1c
2.5–2.7%
PCR + sequencing
No (1 site)
PCR + sequencing
Li et al. (2013)
A. thaliana
Leaf agroinfiltration
C. reinhardtii
CaMV35S, AtU6
Co-transfected GFP
n.a.
Pre-digested PCR + RE
Jiang et al. 2013a and Jiang et al. 2013b
Nicotiana benthamiana
PEG-protoplast transfection
Arabidopsis (with intron)
CaMV35SPDK, AtU6
PDS3
37.7–38.5%
PCR + sequencing
Li et al. (2013)
N. benthamiana
Leaf agroinfiltration
Arabidopsis (with intron)
CaMV35SPDK, AtU6
PDS3
4.80%
PCR + sequencing
Li et al. (2013)
N. benthamiana
Leaf agroinfiltration
Human
CaMV35S, AtU6
PDS
1.8–2.4%
PCR + RE
No (18 sites)
PCR + RE
Nekrasov et al. (2013)
N. benthamiana
Leaf agroinfiltration
C. reinhardtii
CaMV35S, AtU6
Co-transfected GFP
n.a.
pre-digested PCR + RE
Jiang et al. 2013a and Jiang et al. 2013b
N. benthamiana
Leaf agroinfiltration
Human
CaMV35S, CaMV35S
PDS
12.7–13.8%
Upadhyay et al. (2013)
Nicotiana tabacum
PEG-protoplast transfection
Tobacco
2xCaMV35S, AtU6
PDS<comma> PDR6
16.27–20.3%
PCR + RE
Yes (1.8 kb)
Gao et al. (2014)
Oryza sativa
PEG-protoplast transfection
Rice
2xCaMV35S, OsU3
PDS<comma> BADH2<comma> MPK2<comma> Os02g23823
14.5–38.0%
PCR + RE
Noa (3 sites)
PCR + RE
Shan et al. (2013)
O. sativa
PEG-protoplast transfection
Human
CaMV35S, OsU3 or OsU6
MPK5
3–8%
RE + qPCR and T7E1 assay
No (2 sites) Yes (1 site with a mismatch at position 12)
RE + PCR
Xie and Yang (2013)
O. sativa
PEG-protoplast transfection
Rice
CaMV35S, OsU6
SWEET14
n.a.
pre-digested PCR + RE
Jiang et al. 2013a and Jiang et al. 2013b
O. sativa
PEG-protoplast transfection
Rice
ZmUbi, OsU6
KO1 KOL5; CPS4 CYP99A2; CYP76M5 CYP76M6
n.a.
PCR + sequencing
Yes (115<comma> 170<comma> 245 kb)
Zhou et al. (2014)
Triticum aestivum
PEG-protoplast transfection
Rice
2xCaMV35S, TaU6
MLO
28.50%
PCR + RE
Shan et al. (2013)
T. aestivum
PEG-protoplast transfection
Plant
ZmUbi, TaU6
MLO-A1
36%
T7E1
Wang et al. 2014a and Wang et al. 2014b
T. aestivum
Agrotransfection of cells from immature embryos
Human
CaMV35S, CaMV35S
PDS<comma> INOX
18–22%
PCR + sequencing
Upadhyay et al. (2013)
T. aestivum
Agrotransfection of cells from immature embryos
Human
CaMV35S, CaMV35S
INOX
PCR + sequencing
No*
PCR + RE
Yes (53 bp)
Upadhyay et al. (2013)
Zea mays
PEG-protoplast transfection
Rice
2xCaMV35S, ZmU3
IPK
16.4–19.1%
PCR + RE
Liang et al. (2014)
Citrus sinensis
Leaf agroinfiltration
Human
CaMv35S, CaMV35S
PDS
3.2–3.9%
PCR + RE
No (8 sites)
PCR + RE
Jia et al. (2014)
References:
A brief overview of CRISPR-mediated immunity and explain how the emerging new properties of this defense system are being repurposed for genome engineering in bacteria, yeast, human cells, insects, fish, worms, plants, frogs, pigs, and rodents.
Cho SW, Kim S, Kim JM, Kim J. Targeted genome engineering in human cells with the Cas9 RNA-guided endonuclease. Nat Biotechnol. 2013;31:230–2. doi: 10.1038/nbt.2507.
Cradick TJ, Fine EJ, Antico CJ, Bao G. CRISPR/Cas9 systems targeting β-globin and CCR5 genes have substantial off-target activity. Nucleic Acids Res.2013;41:9584–92. doi: 10.1093/nar/gkt714.
Bassett AR, Tibbit C, Ponting CP, Liu J. Highly efficient targeted mutagenesis of Drosophila with the CRISPR/Cas9 system. Cell Rep. 2013;4:220–8. doi: 10.1016/j.celrep.2013.06.020.
Cho SW, Lee J, Carroll D, Kim J, Lee J. Heritable Gene Knockout in Caenorhabditis elegans by Direct Injection of Cas9-sgRNA Ribonucleoproteins.Genetics. 2013;195:1177–80. doi: 10.1534/genetics.113.155853.
Katic I, Großhans H. Targeted Heritable Mutation and Gene Conversion by Cas9-CRISPR in Caenorhabditis elegans. Genetics. 2013;195:1173–6. doi: 10.1534/genetics.113.155754.
Jiang W, Zhou H, Bi H, Fromm M, Yang B, Weeks DP. Demonstration of CRISPR/Cas9/sgRNA-mediated targeted gene modification in Arabidopsis, tobacco, sorghum and rice. Nucleic Acids Res. 2013;41:e188. doi: 10.1093/nar/gkt780.
Li W, Teng F, Li T, Zhou Q. Simultaneous generation and germline transmission of multiple gene mutations in rat using CRISPR-Cas systems. Nat Biotechnol.2013;31:684–6. doi: 10.1038/nbt.2652.
CRISPR-Cas9 Discovery and Development of Programmable Genome Engineering – Gabbay Award Lectures in Biotechnology and Medicine – Hosted by Rosenstiel Basic Medical Sciences Research Center, 10/27/14 3:30PM Brandeis University, Gerstenzang 121
Annual Margaret Pittman Lecture, honors the NIH’s first female lab chief, March 11, 2015, 3:00:00 PM by Jennifer Doudna, Ph.D., University of California, Berkeley
attn #1: Investors in HealthCare — Platforms in the Ecosystem of Regulatory & Reimbursement – Integrated Informational Platforms in Medical Devices, Global Oncology Drugs Market and Peer-Reviewed Curations: Cancer, Genomics and Cardiovascular – Draft
attn #2: Investors in HealthCare — Cardiovascular Medical Devices: Platforms in the Ecosystem of Regulatory & Reimbursement with Integrated Informational Platforms of Peer-Reviewed Global Scientific Curations on Medical Devices and Cardiac Surgery, Interventional Cardiology and Cardiovascular Imaging – Draft
attn #3: Investors in HealthCare — Platforms in the Ecosystem of Regulatory & Reimbursement – Integrated Informational Platforms in Orthopedic Medical Devices, and Global Peer-Reviewed Scientific Curations: Bone Disease and Orthopedic Medicine – Draft
attn #7: Investors in HealthCare — Platforms in the Ecosystem of Regulatory & Reimbursement – Integrated Informational Platforms in Medical Devices, Global Oncology Drugs Market and Peer-Reviewed Curations: Cancer, Genomics and Cardiovascular – Draft
attn #6: Investors in HealthCare — Platforms in the Ecosystem of Regulatory & Reimbursement – Integrated Informational Platforms in Medical Devices, Global Oncology Drugs Market and Peer-Reviewed Curations: Cancer, Genomics and Cardiovascular – Draft
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New Frontiers in Gene Editing — Cambridge Healthtech Institute’s Inaugural, February 19-20, 2015 | The Inter Continental San Francisco | San Francisco, CA
Lecture Contents delivered at Koch Institute for Integrative Cancer Research, Summer Symposium 2014: RNA Biology, Cancer and Therapeutic Implications, June 13, 2014 @MIT
9:10 – 9:30, 6/13/2014, Phillip Sharp “Why RNA Biology?” Phillip Sharp, PhD Institute Professor, Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology
Koch Institute for Integrative Cancer Research @MIT – Summer Symposium 2014: RNA Biology, Cancer and Therapeutic Implications, June 13, 2014 8:30AM – 4:30PM, Kresge Auditorium @MIT
Dr Sag has a Bachelor’s degree in Basic and Industrial Microbiology as a Sum cum Laude among 450 graduating class of Science faculty, an MSc in Microbial Engineering and Biotechnology (Bioprocessing improvement) and PhD in Molecular and Developmental Genetics (Functional Genome and Stem Cell Biology).
She is an translational functional genomic scientist to develop diagnostics and targeted therapies by non-invasive methods for personalized medicine from bench to bedside and engineering tools through clinical trials and regulatory affairs.
You may contact with her at 858-729-4942 or by demet.sag@gmail.com if you have questions.
Our body works a s a system even during complex diseases that is sometimes forgotten. From nutrition to basic immune responses since we are born we start to change how we respond and push the envelope to keep hemostasis in our body.
During this time additional factors also increase or decrease the rate of changes such as life style, environment, inherited as well acquired genetic make-up, types of infections, weight and stress only some of them. As a result we customized our body so deserve a personalized medicine for a treatment. Customized approach is its hype with developing technology to analyze data and compare functional genomics of individuals.
However, still we need the basic cell differentiation to solve the puzzle to respond well and connect the dots for physiological problems. At the stem of the changes there is a cell that respond and amplify its reaction to gain a support to defend at its best . Thus, in this review I like to make a possible connection for pancreatic cancer, obesity-diabetes and innate immune response through natural killer cells.
Pancreatic cancer is one of the most lethal malignancies. Pancreatic cancer is one of the most difficult cancers to treat. Fewer than 5% of patients survive more than 5 years after diagnosis. The 5-year survival rate is despite therapeutic improvements still only 6%. More than 80% of the pancreatic tumors are classified as pancreatic ductal adenocarcinoma (PDA).
When cells in the pancreas that secrete digestive enzymes (acinar cells) turn into duct-like structures, pancreatic cancer can develop. Oncogenic signaling – that which causes the development of tumors – can influence these duct-like cells to form lesions that are a cancer risk.
Crossing roads
The recent publication brought up the necessity to understand how pancreatic cancer and IL17 are connected.
Schematic diagram showing the central role of IL-17B–IL-17RB signaling in pancreatic cancer metastasis.
Adapted from an illustration by Heng-Hsiung Wu and colleagues
Simply, obesity and diabetes increases the risks of cancers, cardiovascular disease, hypertension, and type-2 DM. There is a very big public health concern as obesity epidemic, the incidence of diabetes is increasing globally, with an estimated 285 million people, or 6.6% of the population from 20 to 79 years of age, affected this is especially more alarming as child obesity is on the rise.
According to a World Health Organization (WHO) report showing that 400 million people are obese in the world, with a predicted increase to 700 million by 2015 and in the US, 30–35 percent of adults are obese. In addition, high BMI and increased risk of many common cancers, such as liver, endometrium, breast, pancreas, and colorectal cancers have a linear increasing relationship.
The BMI is calculated by dividing body weight in kilograms by height squared in meters kg/m2). The current standard categories of BMI are as follows: underweight, <18.5; normal weight, 18.5–24.9; overweight, 25.0–29.9; obese, 30.0–34.9; and severely obese, > or = 35.0).
Furthermore, natural killer cells not only control innate immune responses but have function in other immune responses that was not recognized well before.
Recently, there have been reports regarding Natural Killer cells on was about the function of IL17 that is produced by iNKT, a subtype of NK, for a possible drug target. In addition, regulation of receptors that are up or downregulated by NK cells for a precise determination between compromised cells and healthy cells.
Therefore, instead of sole reliance on SNPs, or GWAS for early diagnostics or only organ system base pathology, compiling the overall health of the system is necessary for a proper molecular diagnostics and targeted therapies.
What is Pancreas cancer
SNAP SHOT:
Incidence
It is a rare type of cancer.
20K to 200K US cases per year
Medically manageable
Treatment can help
Requires a medical diagnosis
lab tests or imaging
spreads rapidly and has a poor prognosis.
treatments may include: removing the pancreas, radiation, and chemotherapy.
Ages affected; even though person may develop this cancer from age 0 to 60+ there is a high rate of incidence after age 40.
People may experience:
Pain: in the abdomen or middle back
Whole body: nausea, fatigue, or loss of appetite
Also common: yellow skin and eyes, fluid in the abdomen, weight loss, or dark urine
The pancreas secretes enzymes that aid digestion and hormones that help regulate the metabolism of sugars.
Prescription
Chemotherapy regimen by injection: Irinotecan, Gemcitabine (Gemzar), Oxaliplatin (Eloxatin)
Other treatments: Leucovorin by injection, Fluorouracil by injection (Adrucil)
Procedures: Radiation therapy, Pancreatectomy, surgery to remove pancreatic tumors
Specialists
Radiologist: Uses images to diagnose and treat disease within the body.
Oncologist: Specializes in cancer.
Palliative medicine: Focuses on improving quality of life for terminally ill patients.
General surgeon: Performs a range of surgeries on the abdomen, skin, breast, and soft tissue.
Gastroenterologist: Focuses on the digestive system and its disorders.
What are the current and possible applications for treatment and early diagnosis
Diagnostics
Several imaging techniques are employed in order to see if cancer exists and to find out how far it has spread. Common imaging tests include:
Ultrasound – to visualize tumor
Endoscopic ultrasound (EUS) – thin tube with a camera and light on one end
Abdominal computerized tomography (CT) scans – to visualize tumor
Endoscopic retrograde cholangiopancreatography (ERCP) – to x-ray the common bile duct
Angiogram – to x-ray blood vessels
Barium swallows to x-ray the upper gastrointestinal tract
Magnetic resonance imaging (MRI) – to visualize tumor
Positron emission tomography (PET) scans – useful to detect if disease has spread
New solutions in Diagnostics;
The study, published in Nature Communications, suggests that targeting the gene in question – protein kinase D1 (PKD1) – could lead to new ways of halting the development of one of the most difficult tumors to treat.
“As soon as pancreatic cancer develops, it begins to spread, and PKD1 is key to both processes. Given this finding, we are busy developing a PKD1 inhibitor that we can test further,” says the study’s co-lead investigator, Dr. Peter Storz.
Do we have new markers?
Is it possible check the cancer along with glucose levels or insulin at the point of care or companion diagnostics?
Therapy
New Solutions in Therapies
ABRAXANE (paclitaxel formulated as albumin bound nanoparticles; nab-paclitaxel), in combination with gemcitabine, has been recommended for use within NHS Scotland by the Scottish Medicines Consortium (SMC) for the treatment of metastatic adenocarcinoma of the pancreas.
The SMC decision is based on results from the MPACT (Metastatic Pancreatic Adenocarcinoma Clinical Trial) study, published in the October 2013 edition of the New England Journal of Medicine, which demonstrated an increase in median overall survival of 1.8 months when compared to gemcitabine alone [(8.5 months vs. 6.7 months respectively) (HR 0.72; 95% CI 0.62 to 0.83 P<0.001)].
Updated results from post-hoc analysis of the MPACT trial based on an extended data cut-off (8 months) at the time the trial was closed demonstrated an increase in the median overall survival benefit of 2.1 months when compared to gemcitabine alone [(8.7 months vs. 6.6 months respectively) (HR 0.72,95% CI = 0.62 to 0.83, P<.001)].
Targeting stroma is another approached that is followed by TGen to potentially extend patient survival in all cases including advanced cases based on a report at Clinical Cancer Research, published online by the American Association for Cancer Research. Thus this eliminates one of the limiting factor to reach tumor cells and destroying the accumulation of stroma — the supporting connective tissue that includes hyaluronan and few other collagen types.
One of the study leaders, Andrew Biankin, a Cancer Research UK scientist at the University of Glasgow in the UK said that “Being able to identify which patients would benefit from platinum-based treatments would be a game-changing moment for treating pancreatic cancer, potentially improving survival for a group of patients.”
In the journal Nature, the international team- including scientists from Cancer Research UK showed the evidence of large chunks of DNA being shuffled around, which they were able to classify according to the type of disruption they created in chromosomes.
The study concludes there are four subtypes of pancreatic cancer, depending on the frequency, location and types of DNA rearrangement. It terms the subtypes: stable, locally rearranged, scattered and unstable.
Can we develop an immunotherapy?
Genetics of Pancreatic Cancer
There are many ongoing studies to develop diagnostics technologies and treatments. However, the etiology of PC is not well understood. Pancreas has dual functions that include 2% of endocrine hormone secretion and 98% exocrine secretion, enzymes, to help digestion. As a result, pancreatic cancer is related to obesity, overweight, diabetes.
First, eliminating the risk factors can be the simplest path. Next approach is dropping the obesity and diabetes to prevent the occurrence of cancers since in the U.S. population, 50 percent are overweight, 30 percent are medically obese and 10 percent have diabetes mellitus (DM). Tobacco smoking, alcohol consumptions, chronic pancreatitis, and genetic risk factors, have been recognized as potential risk factors for the development and progression of PC.
Many studies showed that the administration of anti-diabetic drugs such as metformin and thiazolidinediones (TZD) class of PPAR-γ agonists decreases the risk of cancers. Thus, these agents are thought to be the target to diagnose or cure PC.
Type 2 diabetes mellitus has been associated with an increased risk of several human cancers, such as liver, pancreatic, endometrial, colorectal, breast, and bladder cancer. The majority of the data show that metformin therapy decreases, while insulin secretagog drugs slightly increase the risk of certain types of cancers in type 2 diabetes.
Metformin can decrease cell proliferation and induce apoptosis in certain cancer cell lines. Endogenous and exogenous (therapy induced) hyperinsulinemia may be mitogenic and may increase the risk of cancer in type 2 diabetes. Type 2 diabetes mellitus accounts for more than 95% of the cases.
In PDA these cells have been reported to express specific genes such as Aldh1 or CD133. To date, more than 20 case-control studies and cohort and nested case-control studies with information on the association between diabetes and pancreatic cancer, BMI and cancer, and obesity and cancer have been reported.
Meta analysis and cohort studies:
Meta studies for Diabetes and PC
Most of the diabetes and PC studies were included in two meta-analyses, in 1995 and in 2005, investigating the risk of pancreatic cancer in relation to diabetes.
The first meta-analysis, conducted in 1995, included 20 of these 40 published case-control and cohort studies and reported an overall estimated relative risk (RR) of pancreatic cancer of 2.1 with a 95% confidence interval (CI) of 1.6-2.8. These values were relatively unchanged when the analyses were restricted to patients who had diabetes for at least 5 years (RR, 2.0 [95% CI, 1.2-3.2]).
The second meta-analysis, which was conducted in 2005, included 17 case-control and 19 cohort and nested case-control studies published from 1996 to 2005 and demonstrated an overall odds ratio (OR) for pancreatic cancer of 1.8 and 95% CI of 1.7-1.9 . Individuals diagnosed with diabetes within 4 years before their pancreatic cancer diagnosis had a 50% greater risk of pancreatic cancer than did those diagnosed with diabetes more than 5 years before their cancer diagnosis (OR, 2.1 [95% CI, 1.9-2.3] versus OR, 1.5 [95% CI, 1.3-1.8]; P = 0.005).
In a recent pooled analysis of 2192 patients with pancreatic cancer and 5113 cancer-free controls in three large case-control studies conducted in the United States (results of two of the three studies were published after 2005),
Risk estimates decreased as the number of years with diabetes increased.
Individuals with diabetes for 2 or fewer, 3-5, 6-10, 11-15, or more than 15 years had ORs (95% CIs) of 2.9 (2.1-3.9), 1.9 (1.3-2.6), 1.6 (1.2-2.3), 1.3 (0.9-2.0), and 1.4 (1.0-2.0), respectively (P < 0.0001 for trend).
Meta Studies between BMI and PC
Meta studies in 2003 and 2008 showed a week positive association between BMI and PC. In 2003, a meta-analysis of six case-control and eight prospective studies including 6,391 PC cases 2% increase in risk per 1 kg/m2 increase in BMI. In 2008, 221 datasets, including 282,137 incidence of cancer cases with 3,338,001 subjects the results were similar RR, 1.12; CI, 1.02–1.22.
In 2007, 21 prospective studies handled , 10 were from the United States, 9 were from Europe, and 2 were from Asia and studies was conducted including 3,495,981 individuals and 8,062 PC cases. There was no significant difference between men and women and the estimated summary risk ratio (RR) per 5 kg/m2 increase in BMI was 1.12 (95% CI, 1.06–1.17) in men and women combined.
This study concluded that concluded that there was a positive association between BMI and risk of PC, per a 5 kg/m2 increase in BMI may be equal to a 12% increased risk of PC.
The location and type of the obesity may also signal for a higher risk. The recent Women’s Health Initiative study in the United States among 138,503 postmenopausal showed that women central obesity in relation to PC (n=251) after average of 7.7 years of follow-up duration demonstrated that central adiposity is related to developing PC at a higher risk. Based on their result “women in the highest quintile of waist-to-hip ratio have a 70 percent (95% CI, 10–160%) greater risk of PC compared with women in the lowest quintile”
Age of obesity or being overweight versus risk of developing PC was also examined.
Regardless of their DM status they were at risk and decreased their survival even more so among men than women between age of 14-59.
overweight 14 to 39 years (highest odds ratio [OR], 1.67; 95% CI, 1.20–2.34) or
obese 20 to 49 years (highest OR, 2.58; 95% CI, 1.70–3.90) , independent of DM status.
This association was different between men and women from the ages of 14 to 59:
stronger in men (adjusted OR, 1.80; 95% CI, 1.45–2.23)
weaker in women (adjusted OR, 1.32; 95% CI, 1.02–1.70).
The effect of BMI , obesity and overweight had reduced overall survival of PC regardless of disease stage and tumor resection status
high BMI (= or > 25) 20 to 49 years , an earlier onset of PC by 2 to 6 years.
Being overweight or obese during early adulthood was associated with a greater risk of PC and a younger age of disease onset, whereas obesity at an older age was associated with a lower overall survival in patients diagnosed with PC.
More recently, several large prospective cohort studies with a long duration of follow-up has been conducted in the U.S. showing a positive association between high BMI and the risk of PC (adjusted RR 1.13–1.54), suggesting the role of obesity and overweight with higher risk in the development and eventual death due to PC.
Although the role of smoking and gender in the association of obesity and PC is not clear, the new evidence strongly supports a positive association of high BMI with increased risk of PC, consistent with the majority of early findings; however, all recent studies strongly suggest that obesity and overweight are independent risk factor of PC.
Diabetes was associated with a 1.8-fold increase in risk of pancreatic cancer (95% CI, 1.5-2.1).
How pancreatic cancer is related to obesity, overweight, BMI, diabetes
Connections in Physiology and Pathology:
Altogether cumulative data suggest that DM has a three-fold increased risk for the development of PC and a two-fold risk for biliary cancer insulin resistance and abnormal glucose metabolism, even in the absence of diabetes, is associated with increased risk for the development of PC. Obesity alters the metabolism towards insulin resistance through affecting gene expression of inflammatory cytokines, adipose hormones such as adipokines, and PPAR-γ.
Furthermore, adiponectin also pointed out to be a negative link factor for cancers such as colon, breast, and PC. Therefore, insulin resistance is one of the earliest negative effects of obesity, early altered glucose metabolism, chronic inflammation, oxidative stress and decreased levels of adipose hormone adiponectin and PPAR-γ, key regulators for adipogenesis.
Potential pathways directly linking obesity and diabetes to pancreatic cancer. Obesity and diabetes cause mutiple alterations in glucose and lipid hemastasis, microenvironments, and immune responses, which result in the activation of several oncogenic signaling pathways.
These deregulations increase cell survival and proliferation, eventually leading to the development and progression of pancreatic cancer. ROS, reactive oxygen species; IGF-1, insulin-like growth factor-1; IR, insulin receptors; IGF-1R, insulin-like growth factor-1 receptors; TNFR, tumor necrosis factor receptors; TLR, Toll-like receptors; HIF-1α, hypoxia-inducible factor-α1; AMPK, AMP kinase; IKK, IκB kinase; PPAR-γ, peroxisome proliferator-activated receptor-γ; VEGF, vascular endothelial growth factor; MAPK, MAP kinase; mTOR, mammalian target of rapamycin; TSC, tuberous sclerosis complex; Akt, protein kinase B. PI3K, phosphoinositide-3-kinase; STAT3, activator of transcription-3; JNK, c-Jun NH2-terminal kinase.
Top six pathways interacting with obesity or diabetes in modifying the risk of pancreatic cancer are Chemokine Signaling, Pathways in cancer, Cytokine-cytokine receptor interaction, Calcium signaling pathway. MAPK signaling pathway.
This analysis showed
GNGT2,
RELA,
TIAM1,
CBLC,
IFNA13,
IL22RA1,
IL2RA
GNAS,
MAP2K7,
DAPK3,
EPAS1 and
FOS as contributor genes.
Furthermore, top overrepresented canonical pathways, including
Role of RIG1-like Receptors in Antiviral Innate Immunity,
Role of PI3K/AKT Signaling in the Pathogenesis of Influenza, and
Molecular Mechanisms of Cancer
in genes interacting with risk factors (P < 10−8) are
aNumber of genes making up the pathway/ number of genes survived the PCA-LRT (P ≤ 0.10).
bNumber of SNPs in the “reconstructed” pathways/number of principal components for LRT.
cP value was estimated by LRT in logistic regression model with adjustment of age, sex, study site, pack years(continuous), obesity or diabetes as appropriate, and five principal components for population structure.
dGenes with PG x E ≤ 0.05 in logistic regression and P ≤ 0.10 in PCA-LRT.
ePathways remained significant after Bonferroni correction (P < 1.45 × 10−4)
Top overrepresented canonical pathways in genes interacting with risk factors (P < 10−8)
aCalculated using Fisher’s exact test (right-tailed).
bNumber of genes interacting with a risk factor of interest (P ≤ 0.05) in a given pathway divided by total number of genes making up that pathway.
Pancreatic Cancer and Diabetes:
We conclude that diabetes type II has a fundamental influence on pancreatic ductal adenocarcinoma by stimulating cancer cell proliferation, while metformin inhibits cancer cell proliferation. Chronic inflammation had only a minor effect on the pathophysiology of an established adenocarcinoma.
Diabetes increases tumor size and proliferation of carcinoma cells
Diabetes does not decrease cell death in carcinomas
Diabetes II like syndrome reduces the number of Aldh1+cells within the tumor
Metformin decreases tumor size and proliferation of carcinoma cells
Much is known about factors increasing the likelihood to develop PDA. Identified risk factors include among others chronic pancreatitis, long lasting diabetes, and obesity. Patients with chronic and especially hereditary pancreatitis have a very high relative risk of developing pancreatic cancer of 13.3 and 69.0, respectively. Patients with diabetes and obesity have a moderately increased relative risk of 1.8 and 1.3. These studies indicate that a substantial number of patients with PDA also suffer from local inflammation or diabetes.
Type 2 diabetes mellitus is likely the third modifiable risk factor for pancreatic cancer after cigarette smoking and obesity. The relationship between diabetes and pancreatic cancer is complex. Diabetes or impaired glucose tolerance is present in more than 2/3rd of pancreatic cancer patients.
Epidemiological investigations have found that long-term type 2 diabetes mellitus is associated with a 1.5-fold to 2.0-fold increase in the risk of pancreatic cancer. A causal relationship between diabetes and pancreatic cancer is also supported by findings from prediagnostic evaluations of glucose and insulin levels in prospective studies.
Insulin resistance and associated hyperglycemia, hyperinsulinemia, and inflammation have been suggested to be the underlying mechanisms contributing to development of diabetes-associated pancreatic cancer.
“A study by Permert et al.using glucose tolerance tests in patients with newly diagnosed pancreatic cancer showed that 75% of patients met criteria for diabetes. Pannala et al. used fasting blood glucose values or previous use of antidiabetic medications to define diabetes in patients with pancreatic cancer (N.=512) and age-matched control non-cancer subjects attending primary care clinics (N.=933) “
Distribution of fasting blood glucose among pancreatic cancer cases and controls. From Pannala et al.
“ They reported a nearly seven-fold higher prevalence of diabetes in pancreatic cancer patients compared to controls (47% vs. 7%). In a retrospective study using similar criteria, Chari et al. found the prevalence of diabetes in pancreatic cancer patients to be 40%. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3932318/”
Relationship between type 2 diabetes and risk of pancreatic cancer in case-control and nested case control studies. “Diamond: point estimate representing study-specific relative risks or summary relative risks with 95% CIs. Horizontal lines: represent 95% confidence intervals (CIs). Test for heterogeneity among studies: P<0.001, I2=93.6%. 1, cohort studies (N.=27) use incidence or mortality rate as the measurements of relative risk; 2, cohort studies (N.=8) use standardized incidence/mortality rate as the measurement of relative risk. From Benet al.”
PART II: Targets for Immunomodulation to develop a therapy
Natural Killer Cells:
Natural Killer cells usually placed under non-specific immune response as a first defend mechanism during innate immunity. NKs responses to innate immune reactions but not only viruses but also bacteria and parasitic infections develop a new line of defense. These reactions involve amplification of many cytokines based on the specific infection or condition. Thus, these activities help NKs to evolve.
However, their functions proven to be more than innate immune response since from keeping the pregnancy term to prevent recurrent abortions to complex diseases such as cancer, diabetes and cardiovascular conditions they have roles thorough awakening chemokines and engaging them specifically with their receptors to activate other immune cells. For example, there is a signaling mechanism connection between NKs and DCs to respond attacks. Furthermore, there are interactions between various types of immune cells and they are specific for example between NK and Tregs.
During pregnancy there is a special kind of interaction between NK cells and Tregs.
There can be several reasons such as to protect pregnancy from the immunosuppressive environment so then the successful implantation of the embryo and tolerance of the mother to the embryo can be established. In normal pregnancy, these cells are not killers, but rather provide a microenvironment that is pregnancy compatible and supports healthy placentation.
During cancer development tumors want to build a microenvironment through an array of highly orchestrated immune elements to generate a new environment against the host. In normal pregnancy, decidua, the uterine endometrium, is critical for the development of placental vasculature.
This is the region gets thicks and thin during female cycles to prevent or accept pregnancies. As a result, mother nature created that 70% of all human decidual lymphocytes are NK cells, defined as uterine or decidual NK (dNK) cells.
The NK cell of decidua (dNK) and peripheral blood NK cells are different since dNK cells are characterized as CD56brightCD16−CD3−, express killer cell immunoglobulin-like receptors and exhibit low killing capacity despite the presence of cytolytic granules, and a higher frequency of CD4+CD25bright
The lesson learn here is that pregnancy and mammary tissue are great examples of controlling cellular differentiation and growth since after pregnancy all these cells go back to normal state.
Understanding these minute differences and relations to manipulate gene expression may help to:
Develop better biomaterials to design long lasting medical devices and to deliver vaccines without side effects.
Generate safer vaccines as NKcells are the secret weapons in DC vaccination and studying their behavior together with T-cell activation in vaccinated individuals might predict clinical outcome.
Establish immunotherapies based on interactions between NK cells and Tregs for complex diseases not only cancer, but also many more such as autoimmune disorder, transplants, cardiovascular, diabetes.
Trascription factors are the silence players of the gene expression that matches input to output as a cellular response either good or bad but this can be monitored and corrected with a proper meical device or diagnostics tool to provide successful treatment regimen.
Therefore, the effects of Tregs on NK during gene regulation analyzed and compared among other living organisms for concerved as well as signature sequence targets even though the study is on human.
Unfortunatelly we can’t mutate the human for experimental purposes so comparative developmental studies now its widely called stem cell biology with a system biology approach may help to establish the pathway.
NK and T reg regulation share a common interest called T box proteins. These proteins are conserved and also play role in development of heart at very early development, embryology. What is shared among all T-box is simply lie behind the capacity for DNA binding through the T-box domain and transcriptional regulatory activity, which plays a role in controlling the expression of developmental gene in all animal species.
The Special T box protein: T-bet
The first identified T-box protein was Brachyury (T). in a nut shell
The T-box domain is made up of about 180 amino-acid residues that includes a specific sequence of DNA
called T-box domain, TCACACCT between residues 135 and 326 in mouse.
However, T-bet which is the T-box protein expressed in T cells and also called as TBX21 is quite conserved in 18 members of the T-box protein (TBX) family
since it has a crucial dual role during development and for coordination of both innate and adaptive immune responses.
T-Bet was originally cloned for its role in Th1 lineage, it has a role in Th2 development, too.
The whole mechanism based on direct activation and modulation mechanisms in that T-Bet directly activates IFN-γ gene transcription and enhances development of Th1 cells at the same time modulates IL-2 and Th2 cytokines in an IFN-γ-independent manner that creates an attenuation of Th2 cell development.
Thus, certain lipids ligands or markers can be utilized during vaccine design to steer the responses for immune therapies against autoimmune diseases. As a result, tumors can be removed and defeated by manipulating NKs action.
INKT:
NKT has functions in diabetes, asthma. One cell type that has been proposed to contribute immensely to the development of asthma is NKT cells, which constitute a small population of lymphocytes that express markers of both T cells (T-cell receptor, TCR) and NK cells (e.g., NK1.1, NKG2D). NKT cells can be subdivided into at least three subtypes, based on their TCR. Type I NKT cells or invariant NKT (iNKT) cells express invariant TCR chains (V14–J18 in mice and V24–J18 in humans) coupled with a limited repertoire of V chains (V8, V7 and V2 in mice and V11 in humans).
The studies in the past decade showed the protective mechanism of NKT cells during the development of Type 1 diabetes can be complex.
First, NKT cells can impair the differentiation of anti-islet reactive T cells into Th1 effector cells in a cell–cell contact dependent manner, which did not require Th2 cytokine production or CD1d recognition.
Second, NKT cells accumulating in the pancreas can indirectly suppress diabetogenic CD4+T cells via IFN-γ production.
Last, anergic iNKT cells induced by protracted αGalCer stimulation can induce the production of noninflammatory DCs, which inhibit diabetes development in an Ag-specific fashion.
These findings point to an important protective role for NKT cells during autoimmune pathogenesis in the pancreas.
A crucial role has been suggested for invariant natural killer T cells (iNKT) in regulating the development of asthma, a complex and heterogeneous disease characterized by airway inflammation and airway hyperreactivity (AHR).
iNKT cells constitute a unique subset of T cells responding to endogenous and exogenous lipid antigens, rapidly secreting a large amount of cytokines, which amplify both innate and adaptive immunity.
IL17:
Terashima A et al (2008) identified a novel subset of natural killer T (NKT) cells that expresses the interleukin 17 receptor B (IL-17RB) for IL-25 (also known as IL-17E) and is essential for the induction of Airway hypersensitive reaction (AHR). IL-17RB is preferentially expressed on a fraction of CD4(+) NKT cells but not on other splenic leukocyte populations tested.
They strongly suggested that IL-17RB(+) CD4(+) NKT cells play a crucial role in the pathogenesis of asthma.
NKT connection can be established between through targeting IL17 and IL17RB. There is a functional specialization of interleukin-17 family members. Interleukin-17A (IL-17A) is the signature cytokine of the recently identified T helper 17 (Th17) cell subset. IL-17 has six family members (IL-17A to IL-17F).
Although IL-17A and IL-17F share the highest amino acid sequence homology, they perform distinct functions; IL-17A is involved in the development of autoimmunity, inflammation, and tumors, and also plays important roles in the host defenses against bacterial and fungal infections, whereas IL-17F is mainly involved in mucosal host defense mechanisms. IL-17E (IL-25) is an amplifier of Th2 immune responses.
There is no one easy answer for the role of IL-17 in pancreatic cancer as there are a number of unresolved issues and but it can be only suggested that pro-tumorigenic IL-17 activity is confined to specific subsets of patients with pancreatic cancer since there is a increased expression of IL-17RB in these patients about ∼40% of pancreatic cancers presented on their histochemical staining (IHC- immunohistochemistry.
IL17 and breast cancer:
In addition, during breast cancer there is an increased signaling of interleukin-17 receptor B (IL-17RB) and IL-17B. They promoted tumor formation in breast cancer cells in vivo and even created acinus formation in immortalized normal mammary epithelial cells in vitro cell culture assays.
Furthermore, the elevated expression of IL-17RB not only present itself stronger than HER2 for a better prognosis but also brings the shortest survival rate if patients have increased IL-17RB and HER2 levels.
However, decreased level of IL-17RB in trastuzumab-resistant breast cancer cells significantly reduced their tumor growth. This may prompt a different independent role for IL-17RB and HER2 in breast cancer development.
In addition, treatment with antibodies specifically against IL-17RB or IL-17B effectively attenuated tumorigenicity of breast cancer cells.
These results suggest that the amplified IL-17RB/IL-17B signaling pathways may serve as a therapeutic target for developing treatment to manage IL-17RB-associated breast cancer.
IL 17 and Asthma:
A requirement for iNKT cells has also been shown in a model of asthma induced with air pollution, ozone and induced with respiratory viruses chronic asthma studied in detail. In these studies specific types of NKT cells found to that specific types of NK and receptors trigger of asthma symptoms. Taken together, these studies indicate that both Th2 cells (necessary for allergen-specific responses) and iNKT cells producing IL-4 and IL-13 are required for the development of allergen-induced AHR.
Although CD4+ IL-4/IL-13-producing iNKT cells (in concert with antigen-specific Th2 cells) are crucial in allergen-induced AHR, NK1.1–IL-17-producing iNKT cells have a major role in ozone-induced AHR.
A main question in iNKT cell biology involves the identification of lipid antigens that can activate iNKT cells since this allow to identify which microorganisms to attack as a result, the list of microorganisms that produce lipids that activate iNKT cells is rapidly growing.
Invariant natural killer T cells (iNKT) cell function in airway hyperreactivity (AHR). iNKT cells secrete various cytokines, including Th2 cytokines, which have direct effects on hematopoietic cells, airway smooth muscle cells, and goblet cells. Alternatively, iNKT cells could regulate other cell types that are known to be involved in asthma pathogenesis, e.g., neutrophils and alveolar macrophages.
Chemokines have a crucial role in organogenesis of various organs including lymph nodes, arising from their key roles in stem cell migration. Moreover, most homeostatic chemokines can control the movement of lymphocytes and dendritic cells and eventually adaptive immunity. Chemokines are heparin-binding proteins with 4 cysteine residues in the conserved positions.
The human chemokine system has about 48 chemokines. They are subgrouped based on:
Number of cysteines
Number of amino acid separating cysteines
Presence or absence of ELR motif includes, 3-amino acid sequence, glutamic acid-leucine-arginine
functionally classified as inflammatory, homeostatic, or both, based on their expression patterns
Chemokines are structurally divided into 4 subgroups :CXC, CC, CX3C, and C. X represent an aminoacid so the first 2 cysteines are separated by 1 is grouped as CXC and 3 amino acids is called CX3C chemokines but in CC the first 2 cysteines are adjacent. In the C chemokines there is no second and fourth cysteines.
Various types of inflammatory stimuli induce abundantly the expression of inflammatory chemokines to induce the infiltration of inflammatory cells such as granulocytes and monocytes/macrophages.
inflammatory chemokines are CXC chemokines with ELR motif and CCL2.
homeostatic chemokines are expressed constitutively in specific tissues or cells.
Chemokines exert their biological activities by binding their corresponding receptors, which belong to G-protein coupled receptor (GPCR) with 7-span transmembrane portions. Thus, the target cell specificity of each chemokine is determined by the expression pattern of its cognate receptor .
Moreover, chemokines can bind to proteoglycans and glycosaminoglycans with a high avidity, because the carboxyl-terminal region is capable of binding heparin.
Consequently, most chemokines are produced as secretory proteins, but upon their secretion, they are immobilized on endothelium cells and/or in extracellular matrix by interacting with proteoglycans and glycosaminoglycans. The immobilization facilitates the generation of a concentration gradient, which is important for inducing the target cells to migrate in a directed way.
The human chemokine system.
Chemokine receptor
Chemokines
Receptor expression in
Leukocytes
Epithelium
Endothelium
CXCR1
CXCL6, 8
PMN
+
−
CXCR2
CXCL1, 2, 3, 5, 6, 7, 8
PMN
+
+
CXCR3
CXCL4, 9, 10, 11
Th1, NK
−
+
CXCR4
CXCL12
Widespread
+
+
CXCR5
CXCL13
B
−
−
CXCR6
CXCL16
Activated T
+
−
CXCR7 (ACKR3)
CXCL12, CXCL11
Widespread
+
+
Unknown
CXCL14 (acts on monocytes)
CCR1
CCL3, 4, 5, 7, 14, 15, 16, 23
Mo, Mϕ, iDC, NK
+
+
CCR2
CCL2, 7, 8, 12, 13
Mo, Mϕ, iDC, NK
activated T, B
+
+
CCR3
CCL5, 7, 11, 13, 15, 24, 26, 28
Eo, Ba, Th2
−
+
CCR4
CCL2, 3, 5, 17, 22
iDC, Th2, NK, T, Mϕ
−
−
CCR5
CCL3, 4, 5, 8
Mo, Mϕ, NK, Th1
activated T
+
−
CCR6
CCL20
iDC, activated T, B
+
−
CCR7
CCL19, 21
mDC, Mϕ, naïve T
activated T
+
−
CCR8
CCL1, 4, 17
Mo, iDC, Th2, Treg
−
−
CCR9
CCL25
T
+
−
CCR10
CCL27, 28
Activated T, Treg
+
−
Unknown
CCL18 (acts on mDC and naïve T)
CX3CR1
CX3CL1
Mo, iDC, NK, Th1
+
−
XCR1
XCL1, 2
T, NK
−
−
Miscellaneous
Scavenger receptors for chemokines
Duffy antigen (ACKR1)
CCL2, 5, 11, 13, 14
CXCL1, 2, 3, 7, 8
D6 (ACKR2)
CCL2, 3, 4, 5, 7, 8, 12
CCL13, 14, 17, 22
CCRRL1 (ACKR4)
CCL19, CCL21, CCL25
Leukocyte anonyms are as follows. Ba: basophil, Eo: eosinophil, iDC: immature dendritic cell, mDC: mature dendritic cell, Mo: monocyte, Mϕ: macrophage, NK: natural killer cell, Th1: type I helper T cell, Th2: type II helper T cell, and Treg: regulatory T cell.
There are differences between human liver and peripheral NK cells. Regulation of NK cell functions by CD226, CD96 and TIGIT.close. CD226 binding to CD155 or CD112 at the cell surface of transformed or infected cells triggers cytotoxic granule exocytosis and target cell lysis by natural killer (NK) cells. TIGIT, CD226, CD96 and CRTAM ligand specificity and signalling.close.
Regulation of NK cell-mediated cancer immunosurveillance through CD155 expression.close. CD155 is frequently overexpressed by cancer cells.
In conclusion, having to develop precise early diagnostics is about determining the overlapping genes as key among diabetes, obesity, overweight and pancreas functions even pregnancy can be suggested.
It seems feasible to develop an immunotherapy for pancreatic cancer with the focus on chemokines and primary signaling between iNKT and Tregs such as one of the recent plausable target IL-17 and IL17 RB.
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Key Papers:
These papers, Gilfian et all and Iguchi-Manaka et al, were the first to show the role of CD226 in NK cell- and CD8+ T cell-mediated tumour immunosurveillance using Cd226−/− mice.
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Fang, M. et al. CD94 is essential for NK cell-mediated resistance to a lethal viral disease.Immunity34, 579–589 (2011). This study using CD94-deficient mice shows that the activating receptor formed by CD94 and NKG2E is essential for the resistance of C57BL/6 mice to mousepox.
Pradeu, T., Jaeger, S. & Vivier, E. The speed of change: towards a discontinuity theory of immunity? Nature Rev. Immunol.13, 764–769 (2013). This is an outstanding review on the formulation of a new immune paradigm ‘the discontinuity theory’
Synchronous Triple Cancers of the Pancreas, Stomach, and Cecum Treated with S-1 Followed by Pancrelipase Treatment of Pancreatic Exocrine Insufficiency
Synchronous Triple Cancers of the Pancreas, Stomach, and Cecum Treated with S-1 Followed by Pancrelipase Treatment of Pancreatic Exocrine Insufficiency
Anti-pancreatic cancer antibodies: David M. Goldenberg, Mendham, NJ (US); Hans J. Hansen, Picayune, MS (US); Chien-Hsing Chang, Downingtown, PA (US); …
Yamaue, Hiroki; to Onco Therapy Science, Inc. Combination therapy for pancreatic cancer using an antigenic peptide and chemotherapeutic agent 08703713 …
Thymoquinone, an extract of nigella sativa seed oil, blocked pancreatic cancer cell growth and killed the cells by enhancing the process of programmed cell death.
Consortium of European Research Institutions and Private Partners will develop a microfluidics-based lab-on-a-chip device to identify Pancreatic Cancer Circulating Tumor Cells (CTC) in blood
Pancreatic Cancer Diagnosis: Four Novel Histo-pathologies Screening Characteristics offers more Reliable Identification of Cellular Features associated with Cancer
Synchronous Triple Cancers of the Pancreas, Stomach, and Cecum Treated with S-1 Followed by Pancrelipase Treatment of Pancreatic Exocrine Insufficiency
Synchronous Triple Cancers of the Pancreas, Stomach, and Cecum Treated with S-1 Followed by Pancrelipase Treatment of Pancreatic Exocrine Insufficiency
Natural Drug Target Discovery and Translational Medicine in Human Microbiome
Author and Curator: Demet Sag, PhD
Remember Ecology 101, simple description of ecosystem includes both living, biotic, and non-living, abiotic, that response to differentiation based on external and internal factors. Hence, biodiversity changes since living systems are open systems and always try to reach stability. Both soil and human body are rich in microbial life against ever changing conditions. Previously, discovery of marine microorganisms for treatment of complex diseases especially cancer and drug discovery for pharmaceutical applications was discussed. (http://pharmaceuticalintelligence.com/2014/03/20/without-the-past-no-future-but-learn-and-move-genomics-of-microorganisms-to-translational-medicine/)
Here, the focus will be given to clinical drug discovery based on how lactose intolerance and human microbiome related to treat cancer patients or other diseases. In sum, creating clinical relevance with human microbiome require knowledge of both of the worlds to make best of it to solve complex diseases naturally.
The huge undertake as a roadmap to biomedical research originated by NIH under The Human Microbiome Project (HMP) (http://nihroadmap.nih.gov) with 250 healthy individuals as a starting point. Recent developments opened the doors to pursue us to understand how human microbiome reflects on metabolism, drug interactions and numerous diseases. Finally, association between clinical states and microbiome are improving with advanced algorithms, bioinformatics and genomics. In classical reading tests questions finding the simile between two groups of words can well relate how microbiome- human and soil-earth relates. Both are rich in microbial life with quite changing characters to survive through commensal living.
Thus, it is also good to talk about how we can synthesize existing info on interactions between soil microorganisms and decomposers for human diseases and human microbiome. Epidemiology of living organisms is diverse but they all share common interest. In soil, for example, radioactively contaminated soil can’t support plant growth well so Nitrosomonas may support to bring the life to soil through supplying nitrogen. And others can be added to bring a favorable enriched soil.
In human microbiome nutrition-diseases interacts in such a harmony with genetic make up (the information received at time of birth germline- or acquired later in life due to mutations by various reasons). For example, the simplest example is lactose intolerance and the other is development of diabetes. Generally, it is described as If person is missing a gene to metabolize lactose (sugar) this person become Lactose intolerant yet this can be gained before birth or after. The fix is easy since avoiding certain food groups i.e. milk products.
Yet, this is not that simple!
In human microbiome, the rich gastrointestinal (GI) tract contains many organisms and one of the most important ones is Enterococci that are often simply described as lactic-acid–producing bacteria—by under- appreciation of their power of microbial physiology and outcomes as well as their ubiquitous nature of enterococci. Schleifer & Kilpper-Bälz, 1984 also reported that the Group D streptococci, such as Streptococcus faecalis and Streptococcus faecium, were included in the new genus called Enterococcus.
The importance of this genius, consists of 37 species, coming from their spectrum of habitats that include the gastrointestinal microbiota of nearly every animal phylum and flexibility with ability to widely colonize, intrinsic resistance to many inhabitable conditions even though they don’t have spores but they can survive against desiccation and can persist for months on dried surfaces. Furthermore, they can tolerate extreme conditions such as pH changes, ionizing radiation, osmotic and oxidative stresses, high heavy metal concentrations, and antibiotics.
There is a double sword application as these organisms used as probiotics to improve immune system of the host. If it is human to prevent contaminated food related diseases or in animals prevent transmitting them to the consumers. Thus, E. faecium and E. faecalis strains are used as probiotics and are ingested in high numbers, generally in the form of pharmaceutical preparations to treat diarrhea, antibiotic-associated diarrhea or irritable bowel syndrome, to lower cholesterol levels or to improve host immunity.
When it comes to human body within each system specific organs may create distinct values. For example the pH values of GI tract vary and during diseases since pH levels are not at at correct levels. As a result, due to mal-absorption of nutrients and elements such as food, vitamins and minerals body can’t heal itself. This changing microbial genomics on the surface of GI reflects on general health. Entrococcus family among the other GI’s natural flora has the microbial physiology adopt these various pH conditions well.
Our body has its own standards to function, such as pH, temperature, oxygen etc these are basics so that enzymatic reactions may happen to metabolize,synthesizing (making) or catalyzing (breaking) what we eat. The pH is the measure of hydrogen-ion concentration in solution. For example, human blood has a narrow pH (7.35 – 7.45 ) and below or above this range means symptoms and disease yet if blood pH moves to much below 6.8 or above 7.8, cells stop functioning and the patient dies since the ideal pH for blood is 7.4. This value is unified. On the other hand, the pH in the human digestive tract or GI changes tremendously to adopt and carry on its function, the pH of saliva (6.5 – 7.5), upper portion of the stomach (4.0 – 6.5) where “predigestion” occurs, the lower portion of the stomach is secreting hydrochloric acid (HCI) and pepsin until it reaches a pH between 1.5 – 4.0; duodenum, small intestine, (7.0 – 8.5) where 90% of the absorption of nutrients is taken in by the body while the waste products are passed out through the colon (pH 4.0 – 7.0).
Why is pH important and how related to anything?
Development and presence of cancer always require an acid pH and lack of oxygen. Thus, prevention of these two factors may be the key for treatment of cancer as it progress the acidity increases such that the level raises even up to 1000 more than normal levels.
Mainly, due to Warburg effect body opt to get its energy from fermentation of glucose and produce lactic acid that decreases the body pH from 7.3 down to 7 then to 6.5 in advanced stages of cancer. Furthermore, during metastases this level even reaches to 6.0 and even 5.7 where body can’t fight back with the disease. (Warburg effect is well explained previously by Dr. Larry Berstein (www.linkedin.com/pub/larry-bernstein/38/94b/3aa).
How to bypass the lack of oxygen naturally?
One of the many solution can be a natural solution. The nature made the hemoglobin carrying bacteria, Vitreoscilla hemoglobin (VHb), which is first described by Dale Webster in 1966. The gram negative and obligate aerobic bacterium, Vitreoscillasynthesizes elevated quantities of a homodimeric hemoglobin (VHb) under hypoxic growth conditions. The main role is likely the binding of oxygen at low concentrations and its direct delivery to the terminal respiratory oxidase(s) such as cytochrome o. Then, after 1986 with detailed description of the molecule other hemoglobins and flavohemoglobins were identified in a variety of microbes, indicating the widespread occurrence of Hb-like proteins. Currently, it is the most studied bacterial hemoglobin with application potentials in biotechnology.
It is a plausible solution to integrate Vitroscilla and Enterobacter powers for cancer detection and treatment naturally with body’s own microbiome.
However, there are many microbial organisms and differ person to person based on gender, age, background, genetic make-up, food intake, habits, location etc. The huge undertake as a roadmap to biomedical research originated by NIH under The Human Microbiome Project (HMP) (http://nihroadmap.nih.gov) with 250 healthy individuals as a starting point.
There were three goals in the agenda of The Human Microbiome Project (HMP) simply:
1. Utilize advanced high throughput technology,
2. Identify any association between microbiome and disease/health stages,
3. Initiate scientific studies to collect more data.
In sum, creating clinical relevance with human microbiome require knowledge of both of the worlds to make best of it to solve complex diseases naturally.
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Graham
A. W. Rook,*,1 Christopher A. Lowry,2 and Charles L. Raison3 Microbial ‘Old Friends’, immunoregulation and stress resilience Evol Med Public Health. 2013; 2013(1): 46–64. Published online 2013 Apr 9. doi: 10.1093/emph/eot004 PMCID: PMC3868387
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