NOMENCLATURE (II) ON SOME GENES REPORTED IN PANCREATIC CANCER

SMAD4:  Co-factor of TGF Beta, involved in Juvenile Polyposis syndrome, mutations lead to a form of dwarfism and pulmonary hypertension

S100-P; important for cell differentiation and progression, through the EZRIN, it participates in lighting PI3K pathway.  It also participates in propagation of Osteosarcoma.

NFAT:  Uses calmodulin-calcineurin pathways to drive to specific transcription factors for growth and invasion particularly in breast cancer.  It the site of action of Cyclosporine as its disturbance mislocates immune modulating cyclins and growth factors. NFAT3 inhibits Lipocalin 2 expression to blunt the cell invasion.
 
PRKCG: reminds us that the pancreas is heavily full of nerves. Whether this is the origin of pains from the pancreatic cancer is a question, but through PICK1, it links this to mitochondrial function/membrane.
Remember the role of Mitochondria, pancreas and glycolysis,  this connection to the mitochondria raises questions in all kind of directions,  further investigation is needed here... " be involved in neuropathic pain development. Defects in this protein have been associated with neurodegenerative disorder spinocerebellar ataxia-14 (SCA14).^{[3]" (wikipedia)}
 
MLL3:  binds to the Core Binding factor like molecule  for blood and neuron differentiation.  T
his CBF contains Retinoblastoma protein 5 therefore interfere with a stop in cell division
but also involve THIS!

NCOA6

From Wikipedia, the free encyclopedia

Jump to: navigation, search

Nuclear receptor coactivator 6
Identifiers
Symbols	NCOA6; AIB3; ASC2; NRC; PRIP; RAP250; TRBP
External IDs	OMIM: 605299 MGI: 1929915 HomoloGene: 40920 GeneCards: NCOA6 Gene
[show]Gene Ontology
RNA expression pattern
More reference expression data
Orthologs
Species	Human	Mouse
Entrez	23054	56406
Ensembl	ENSG00000198646	ENSMUSG00000038369
UniProt	Q14686	A2AQM9
RefSeq (mRNA)	NM_001242539	NM_001242558
RefSeq (protein)	NP_001229468	NP_001229487
Location (UCSC)	Chr 20: 33.28 – 33.41 Mb	Chr 2: 155.39 – 155.47 Mb
PubMed search	[1]	[2]

Nuclear receptor coactivator 6 is a protein that in humans is encoded by the NCOA6 gene.^[1][2][3]
The protein encoded by this gene is a transcriptional coactivator that can interact with nuclear hormone receptors to enhance their transcriptional activator functions. The encoded protein has been shown to be involved in the hormone-dependent coactivation of several receptors, including prostanoid, retinoid, vitamin D₃, thyroid hormone, and steroid receptors. The encoded protein may also act as a general coactivator since it has been shown to interact with some basal transcription factors, histone acetyltransferases, and methyltransferases.<sup>[3]"

Making MLL3 a huge target! although disruptions here may have implication on all cells.</sup>

THE AURORA KINASES

ONCE AGAIN YOU SEE HOW THE CELL PLAYS, USING SIMPLE THINGS THAT GET COMPLICATED REALLY QUICKLY! 
Given our current understanding of the way they are suppressed by normal activity of P53, the aurora Kinase inhibitors should be used in cancers where P53  is clearly dys-regulated, and  probably in disease with positive Prostate Stem Cell Antigen.  This open the door to Sarcomas (chondrosarcoma being the most cited) and Pancreatic cancers  (as well as Bladder cancers). 

GADD45, a P53 dependent protein that inhibits Cdc2/Cyclin B1 could therefore be the best predictor of Aurora activity.
Quantification of CDCA8/Borealin, BIRC5/survivin, and INCENP may provide additional information on AURORA KINASE ACTIVITY.  Like the core Binding Factor, these 3 Molecules form  the Chromosomal Passenger Complex (CPC) which interact with POGZ, EVI5, and JTB.

Niehrs at al further define the role of GADD45 as "Gadd45 recruits nucleotide and/or base excision repair factors to gene-specific loci and acts as an adapter between repair factors and chromatin, thereby creating a nexus between epigenetics and DNA repair."  Therefore explaining how P53 induced arrest is followed by DNA repair through recruitment of GADD45.   When the cell is trying to repair itself with increase in GADD45, of course it wont want to die, therefore over-expression of GADD45 decrease the c-JUN, protecting therefore from TNF induced apoptosis.   GADD45 is not good theoretically when you use Cisplatin or radiation for that matter!

*POGZ explains Nuclear transposition of P53 effects as it impacts SP1, a transcription factor with inteaction of all major playors in the cell including E2F1, POU2F1.   YOU TARGET SP1 WITH WITH AFERIN FOR EXAMPLE, IT IS IMPOSSIBLE TO COME UP EMPTY HANDED.

*EVI5
"Identification of Rab11 as a small GTPase binding protein for the Evi5 oncogene"

Christopher J. Westlake,^* Jagath R. Junutula,^*† Glenn C. Simon,^‡ Manohar Pilli,^* Rytis Prekeris,^‡ Richard H. Scheller,^*§ Peter K. Jackson,^* and Adam G. Eldridge^*§

Author information ► Article notes ► Copyright and License information ►

This article has been cited by other articles in PMC.

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Abstract

The Evi5 oncogene has recently been shown to regulate the stability and accumulation of critical G₁ cell cycle factors including Emi1, an inhibitor of the anaphase-promoting complex/cyclosome, and cyclin A. Sequence analysis of the amino terminus of Evi5 reveals a Tre-2, Bub2, Cdc16 domain, which has been shown to be a binding partner and GTPase-activating protein domain for the Rab family of small Ras-like GTPases. Here we describe the identification of Evi5 as a candidate binding protein for Rab11, a GTPase that regulates intracellular transport and has specific roles in endosome recycling and cytokinesis. By yeast two-hybrid analysis, immunoprecipitation, and Biacore analysis, we demonstrate that Evi5 binds Rab11a and Rab11b in a GTP-dependent manner. However, Evi5 displays no activation of Rab11 GTPase activity in vitro. Evi5 colocalizes with Rab11 in vivo, and overexpression of Rab11 perturbs the localization of Evi5, redistributing it into Rab11-positive recycling endosomes. Interestingly, in vitro binding studies show that Rab11 effector proteins including FIP3 compete with Evi5 for binding to Rab11, suggesting a partitioning between Rab11–Evi5 and Rab11 effector complexes. Indeed, ablation of Evi5 by RNA interference causes a mislocalization of FIP3 at the abscission site during cytokinesis. These data demonstrate that Evi5 is a Rab11 binding protein and that Evi5 may cooperate with Rab11 to coordinate vesicular trafficking, cytokinesis, and cell cycle control independent of GTPase-activating protein function.

Keywords: cytokinesis, GTPase-activating protein, recycling endosome".

*JTB

JTB (gene)

From Wikipedia, the free encyclopedia

Jump to: navigation, search

Jumping translocation breakpoint
Available structures PDB Ortholog search: PDBe, RCSB [show]List of PDB id codes
Identifiers
Symbols	JTB; HJTB; HSPC222; PAR; hJT
External IDs	OMIM: 604671 MGI: 1346082 HomoloGene: 4870 GeneCards: JTB Gene
[show]Gene Ontology
RNA expression pattern
More reference expression data
Orthologs
Species	Human	Mouse
Entrez	10899	23922
Ensembl	ENSG00000143543	ENSMUSG00000027937
UniProt	O76095	O88824
RefSeq (mRNA)	NM_006694	NM_206924
RefSeq (protein)	NP_006685	NP_996807
Location (UCSC)	Chr 1: 153.95 – 153.95 Mb	Chr 3: 90.23 – 90.24 Mb
PubMed search	[1]	[2]
This box: view talk edit

Jumping translocation breakpoint protein (JTB)
Identifiers
Symbol	JTB
Pfam	PF05439
InterPro	IPR008657
[show]Available protein structures:

Protein JTB also known as the jumping translocation breakpoint protein or prostate androgen-regulated protein (PAR) is a protein that in humans is encoded by the JTB gene.^[1][2]
The JTB family of proteins contains several jumping translocation breakpoint proteins or JTBs. Jumping translocation (JT) is an unbalanced translocation that comprises amplified chromosomal segments jumping to various telomeres. JTB has been found to fuse with the telomeric repeats of acceptor telomeres in a case of JT. Homo sapiens JTB (hJTB) encodes a transmembrane protein that is highly conserved among divergent eukaryotic species. JT results in a hJTB truncation, which potentially produces an hJTB product devoid of the transmembrane domain. hJTB is located in a gene-rich region at 1q21, called EDC (Epidermal Differentiation Complex).^[1] JTB has also been implicated in prostatic carcinomas.<sup>[3]

KANOME ET AL SUGGESTED

"</sup>JTB-induced clustering of mitochondria around the nuclear periphery and swelling of each mitochondrion. In those mitochondria, membrane potential, as monitored with a JC-1 probe, was significantly reduced. Coinciding with these changes in mitochondria, JTB retarded the growth of the cells and conferred resistance to TGF-1-induced apoptosis. These activities were dependent on the N-terminal processing and induced by wild-type JTB but not by a mutant resistant to cleavage. These findings raised the possibility that aberration of JTB in structure or expression induced neoplastic changes in cells through dysfunction of mitochondria leading to deregulated cell growth and/or death."
==================================================================
ONCE AGAIN YOU SEE HOW THE CELL PLAYS, USING SIMPLE THINGS THAT GET COMPLICATED REALLY QUICK!

GENES MUTATED AT CHROMOSOME 8q IN PANCREATIC CANCER

1.CDH 17
The change in expression of this gene in advance pancreatic cancer does not come as a surprise
because by now we have become familiar with the fact that advance cancer is on the move and should metastasize, CDH belong to the Cadherin family, the family of adhesion molecule, cells need to detach and go. Takamura M et al. have shown that the Liver-intestine Cadherins reduction correlated with Colon cancer metastatic to lymph nodes.
CDH17 appears to be a gene of differentiation and could help determine the origin of of tissue in those ambivalent cases where we are dealing with an cancer of unknown primary.  It is a proton pump dependent cellular membrane structure.   What is fascinating is the fact that how quickly these structures are internalized or their stimulation effect is transmitted to the Nucleus at splicing center to be expressed as differentiation agents.
Zhu at al. have suggested that the hepatic Nuclear factor 1 and CDX2 participate in the regulation of CDH17 expression. (larger speculation Where is the p molecule counterpart? since this cadherin is on 8q) 

2. PSCA:  PROSTATE stem cell Antigen
When the prostate lends a hand to the pancreas you know this is bad news.  This antigen does not exist in the normal pancreas.  But when it appears in the Pancreas you know the disease is advanced.  Even in the Prostate the amplification of this antigen marks very high Gleason at presentation or bone Metastatasis.  It is not PSA we should be looking for, but PCR overexpression of PSCA.   By its name it says it all "Stem cell" meaning the cancer is now OMNIPOTENT and Incredibly resistant.  The presence of this antigen is not only predictive but also prognosis. The makers of SIPULEUCEL-T should be incubating patient dendritic cells  with with this antigen rather than PAP to be active in pancreatic cancers.

One interesting observation was made by Moore et al. while they were knocking down rats to further study this gene, they noted an over-expression of the AURORA kinases, these genes that regulate mitosis by controlling events at the Centrosomes.  It is interesting because it raises the possibility of using the PSCA as an indicator for use of Aurora inhibitors (Hesperadin, ZM447439,Tozasertib,VX680).  Also recent evidence of activity of Abraxane in Pancreatic cancer would open up the opportunity to use Abraxane in combination with Aurora kinase inhibitor in this disease.   Clearly if P53 is dysregulated, we can safely assume the Aurora kinase may have a role since they are more likely over-expressed.

SO: new target Therapy in Pancreatic cancer  ABRAXANE with an Aurora MutiKinase Inhibitor would be the next step if we want to introduce target therapy in Pancreatic cancers.

A recent TV documentary showed that a chemical compound that the EPA is investigating because it has contaminated the drinking waters in the USA caused cells to have Multiple Centrosomes in exposed cells, clearly is it affecting the AURORA and most likely AURORA A.  It raised the possibility that Metallic based chemical compound toxicity may have a larger weight on this pathways.  I wonder what Arsenic Trioxyde would add to this!   remember the anti-Aurora have a secondary anti-Histone (3) activity contributing to their effect in CML.

3. MYC:
*a GLOBAL AMPLIFIER OF ALL GENES INCLUDING PROLIFERATIVE GENES.
 *RECRUITER OF HISTONES DEACETYLASE PROTEIN
*OVERACTION OF CBF LIKE MOLECULES
*IT HAS IRES THE INTERNAL RIBOSOME ENTRY SITES WHICH IS THE KEY TO THE DOOR TO RIBOSOME FOR PROTEIN FORMATION (REGULATOR FOR MATION) AND HAS A THE ZIPPER TO ATTACH AND OPEN WIDE DNA FOR TRANSLATION.  OVER-EXPRESSION OF MYC DRIVES PROLIFERATION AT HIGH PACE!

WIKIPEDIA SAYS IT ALL
Myc protein is a transcription factor that activates expression of many genes through binding on consensus sequences (Enhancer Box sequences (E-boxes)) and recruiting histone acetyltransferases (HATs). It can also act as a transcriptional repressor. By binding Miz-1 transcription factor and displacing the p300 co-activator, it inhibits expression of Miz-1 target genes. In addition, myc has a direct role in the control of DNA replication.^[4]
Myc is activated upon various mitogenic signals such as Wnt, Shh and EGF (via the MAPK/ERK pathway). By modifying the expression of its target genes, Myc activation results in numerous biological effects. The first to be discovered was its capability to drive cell proliferation (upregulates cyclins, downregulates p21), but it also plays a very important role in regulating cell growth (upregulates ribosomal RNA and proteins), apoptosis (downregulates Bcl-2), differentiation and stem cell self-renewal. Myc is a very strong proto-oncogene and it is very often found to be upregulated in many types of cancers. Myc overexpression stimulates gene amplification,^[5] presumably through DNA over-replication."
"

PROOF OF CONCEPTS: THE CASE OF PANCREATIC CANCER

1.  "P" ARM VERSUS  "Q"
-----------------------------
As you look at the location of Genes, one will quickly notice that various genes have their family counterpart not close on the same chromosome. But instead on a different chromosome altogether.  In general we almost treat this  information in a profane manner in that we overlook the meaning of this.  Nature, however, has no place for randomness. Everything has deep meaning and NUANCES OR MINIMAL VARIATIONS can make a world of difference. Should you doubt this statement, ask the people with Sickle cell, they are not laughing about that nuance in Hemoglobins.  So when a family member has put in a different chromosome, there is no pun intended.

ERBB1 is on chromosome 7p12 (involved in Glioblastoma and Squamous cell head and neck cancers)
ERBB2 is on chromosome 17q11.2-q12 (involved in breast, Ovarian and cervical cancer)

Also however, we note that the family member is put on a "p" rather than "q" location.  This also has a profound meaning.   It just turn out that mutation on "q" location seems to have the worse prognosis and are more likely to be expressed  than those on "p" location.

The bad guy MYC is located 8q24 and is found on advanced forms of cancers (Ovarian, Breast, small cell, Esophageal and cervical but also in the Burkitt (ALL))
The nice MYCN, often a better prognosis indicator, is located on 2p24  but still can be involved in Neurobalstoma.

These are in fact speculation but check it out!

Another example
just go ahead and compare
breast cancer with FGFR1 located 8p11
and breast cancer with EGFR1 located 10q25
and call me if you find different!

PROOF OF CONCEPT NEEDED FOR PANCREATIC CANCER:

One of the complication or hurdle you encounter when you are dealing with abnormal genes
in pancreatic cancers is the the genes found in abnormal cancers are also found in benign conditions such as Adenoma or even pancreatitis.  Now if we assume that this is an Adenocarcinoma of the same origin embryonically as the colon (check that assumption out), we could apply the colon cancer model where
EARLY CANCER FOR ADENOCARCINOMA IS ANNOUNCED BY LOSS OR MUTATION IN CHROMOSOME 17:   IE GENES     (FOLLOWING THE COLON MODEL)
-----------------------------------
-KRT20
-TEM 7
-MAP2K4
BAT-26
ALOX 12
TP53
BIRC5
NME1
ERBB2
GAS
TM4SF5

LATE CANCER,  LOSS OF CHROMOSOME 8 (FOLLOWING THE COLON MODEL)

CDH4
PSCA
MYC
 (FGFR1 AND BAG4 ARE HAVE A "p" LOCATION ON THE CHROMOSOSME)

NOMENCLATURE ON SOME GENES REPORTED IN PANCREATIC CANCER

SMAD4:  Co-factor of TGF Beta, involved in Juvenile Polyposis syndrome, mutation lead to a form of dwarfism and pulmonary hypertension

S100-P; important for cell differentiation and progression, through the EZRIN, it participate in lighting PI3K pathway.  It also participate in propagation of Osteosarcoma

NFAT:  Uses calmodulin-calcineurin pathways to drive to specific transcription factors for growth and invasion particularly in breast cancer.  It the site of action of Cyclosporine as it disturbance mislocate immune modulating cyclins and growth factors. NFAT3 inhibits Lipocalin 2 expression to blunt the cell invasion.
 
PRKCG: remind us that the pancreas is heavily full of nerve. whether this is the origin of pains from the pancreatic cancer is a question, but through PICK1, it links this to mitochondrial function/membrane
remember the role of Mitochondria, pancreas and glucolysis,  this connection to the mitochondria raises questions in all kind of directions,  further investigation is needed here... " be involved in neuropathic pain development. Defects in this protein have been associated with neurodegenerative disorder spinocerebellar ataxia-14 (SCA14).^{[3]" (wikipedia)}
 
MLL3:  binds to the Core Binding factor like molecule  for blood and neuron differentiation.  T
his CBF contain Retinoblastoma protein 5 therefore interfere with a stop in cell division
but also involve THIS!

NCOA6

From Wikipedia, the free encyclopedia

Jump to: navigation, search

Nuclear receptor coactivator 6
Identifiers
Symbols	NCOA6; AIB3; ASC2; NRC; PRIP; RAP250; TRBP
External IDs	OMIM: 605299 MGI: 1929915 HomoloGene: 40920 GeneCards: NCOA6 Gene
[show]Gene Ontology
RNA expression pattern
More reference expression data
Orthologs
Species	Human	Mouse
Entrez	23054	56406
Ensembl	ENSG00000198646	ENSMUSG00000038369
UniProt	Q14686	A2AQM9
RefSeq (mRNA)	NM_001242539	NM_001242558
RefSeq (protein)	NP_001229468	NP_001229487
Location (UCSC)	Chr 20: 33.28 – 33.41 Mb	Chr 2: 155.39 – 155.47 Mb
PubMed search	[1]	[2]

Nuclear receptor coactivator 6 is a protein that in humans is encoded by the NCOA6 gene.^[1][2][3]
The protein encoded by this gene is a transcriptional coactivator that can interact with nuclear hormone receptors to enhance their transcriptional activator functions. The encoded protein has been shown to be involved in the hormone-dependent coactivation of several receptors, including prostanoid, retinoid, vitamin D₃, thyroid hormone, and steroid receptors. The encoded protein may also act as a general coactivator since it has been shown to interact with some basal transcription factors, histone acetyltransferases, and methyltransferases.<sup>[3]"

Making MLL3 a huge target! although disruptions here may have implication on all cells.</sup>



BETA 4 INTEGRIN: a gene that does more than being an adhesion molecules
it is the road to a poorly described and not well recognized pathway

The LysRS-Ap₄A-MITF signaling pathway

The LysRS-Ap₄A-MITF signaling pathway was first discovered in mast cells, in which , the MAPK pathway is activated upon allergen stimulation. Lysyl-tRNA synthetase (LysRS), which normally resides in the multisynthetase complex with other tRNA sythetases, is phosphorylated on Serine 207 in a MAPK-dependent manner.^[30] This phosphorylation causes LysRS to change its conformation, detach from the complex and translocate into the nucleus, where it associates with the MITF-HINT1 inhibitory complex. The conformational change switches LysRS activity from aminoacylation of Lysine tRNA to diadenosine tetraphosphate (Ap₄A) production. Ap₄A binds to HINT1, which releases MITF from the inhibitory complex, allowing it to transcribe its target genes.^[31] Activation of the LysRS-Ap₄A-MITF signaling pathway by isoproterenol has been confirmed in cardiomyocytes, where MITF is a major regulator of cardiac growth and hypertrophy.<sup>[32][33](wikipedia)

Not only it gives Hypertrophy but epidermolysis goes through this intergrin, it participates in the ERBB pathways.  Mark my word this is are critical pathways in pancreatic cancers.

MTIF GIVES YOU MOTIVES TO AFTER IT!
MAKING THE ERBIN A PLAUSIBLE TARGET.
MAKING ALSO A STRONGER CASE THAT MEMBRANE CYTOSKELETON SHOULD BE A GOOD TARGET BECAUSE OF THE WAY IT DRIVES ITS PATHWAY NOT THROUGH THE CYTOSOL( ALTHOUGH THERE IS A SECONDARY RAS/MAPK STIMULATION,) BUT THE PATHWAY HERE IS THROUGH THE RETICULUM ENDOTHELIUM DIRECTLY TO THE NUCLEUS!  CONCEPTUALLY, AN ANTIBODY TO LAMININ ATTACHED TO A SUBUNIT OF A LIPOLYTIC COMPOUND SHOULS HAVE AN THERAPEUTIC OR CHEMICAL EFFECT AT THIS LEVEL.  AN INTERESTING APPROACH.  CHANCES ARE IT MAY ALSO HAVE A STRONG IMPACT ON THE WNT-PATHWAY WHICH TRAVEL CLOSE BY AND IS IMPORTANT IN BREAST CANCER!</sup>

MTA-1: THIS IS A REAL OPPORTUNITY
Here the cell stopped fooling around trying to lie to you.  Here the cell says to you this is one of my way to metastatasize.  yes this is my gene to mestastasize and I will work like any CBF like molecule by attaching to DNA and make me protein that will have me spread like wild fire!   And by the way I will use a growth hormone like Estrogen.   no kidding around
 "MTA1 has been shown to interact with HDAC1,^[4][5] Histone deacetylase 2,^[4][6][5] MTA2,^[4] Estrogen receptor alpha^[7][5] and MNAT1.^[8] MTA1 has also been shown to inhibit SMAD7 at the transcriptional level[9]<sup>"  

IT DOES NEED TGF TO WORK, TGF IS FOR LOCAL GROWTH ANYWAY THAT WHY IT BLOCKS THE SMAD.</sup>

SPINT2
Mutation at SPINT2 leads to significant Malignant Ascites and peritoneal invasion, SPINT 2 is a suppressor of this phenomena. On the Intestinal membrane deficiency of SPINT2 leads to sodium induced/containing diarrhea.  This is also true in Ovarian cancer or peritoneal based tumors.  Targeting this is better then trying Avastin, a blind approach when it comes to effusions management.

MMP11

A metalloproteiase, aimed at breaking down extracellular matrix and be on the move.  Targeting MMP for cancer has proven futile.  The cell is not stupid, it does not put out things that is going to hunt it!  It build first a strong inhibitor to metalloproteiases.  In fact lack of inhibitors has been recognized as the main pathogenesis of TTP.   With the ADAMs being the integrins involved!  and next is that Inhibitor which is of course expressed in pancreatic cancer.

TIMP1

TIMP1

From Wikipedia, the free encyclopedia

Jump to: navigation, search

TIMP metallopeptidase inhibitor 1
PDB rendering based on 1d2b.
Available structures PDB Ortholog search: PDBe, RCSB [show]List of PDB id codes
Identifiers
Symbols	TIMP1; CLGI; EPA; EPO; HCI; TIMP
External IDs	OMIM: 305370 MGI: 98752 HomoloGene: 36321 GeneCards: TIMP1 Gene
[show]Gene Ontology
RNA expression pattern
More reference expression data
Orthologs
Species	Human	Mouse
Entrez	7076	21857
Ensembl	ENSG00000102265	ENSMUSG00000001131
UniProt	P01033	P12032
RefSeq (mRNA)	NM_003254	NM_001044384
RefSeq (protein)	NP_003245	NP_001037849
Location (UCSC)	Chr X: 47.44 – 47.45 Mb	Chr X: 20.87 – 20.87 Mb
PubMed search	[1]	[2]
This box: view talk edit

TIMP metallopeptidase inhibitor 1, also known as TIMP1, a tissue inhibitor of metalloproteinases, is a glycoprotein that is expressed from the several tissues of organisms.
This protein a member of the TIMP family. The glycoprotein is a natural inhibitor of the matrix metalloproteinases (MMPs), a group of peptidases involved in degradation of the extracellular matrix. In addition to its inhibitory role against most of the known MMPs, the encoded protein is able to promote cell proliferation in a wide range of cell types, and may also have an anti-apoptotic function.
==============
PRKCA  see PRKCG
Here Phorbol esters, diacylglycerol, and calcium become important for the cell performance of various functions.  Did I mention few targets, I truly believe I did!

CDH1  The Cadherin by excellence, not only important as adhesion molecule and role in metastasis.  Its role is amplified by what else anchors here such as Vinculin, and others molecules such as Plakoglobins, amplifying the role.  Remember even Cytochrome C is anchored at the mitochondrial membrane and its release leads to apoptosis!
The anchors are legitimate targets therefore, and brings to mind NACA1 in the anchoring to Histone deacetyl transferase (SEE OUR LEUKEMIA SECTION)  CDH13 THAT'S ANOTHER BALL GAME ALL TOGETHER.  THE CELL TWEACKS SOMETHING AND IT IS ANOTHER BALL GAME ALL TOGETHER!
==========================
ALOX5AP
ACVR1B
PCD1
IRS2
TJP1
MADH6

CPRIT: At its February 25, 2013 meeting, the CPRIT Oversight Committee approved proposed changes to existing agency rules and the addition of three new rules

so you know:

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At its February 25, 2013 meeting, the CPRIT Oversight Committee approved proposed changes to existing agency rules and the addition of three new rules.  The changes proposed are designed to implement many of the State Auditor’s recommendations concerning ethics, conflicts of interest, grant review and documentation of the agency’s grant processes. The proposed rule changes and new rules appear in the March 15, 2013 edition of the Texas Register.  Public comment is accepted for 30 days following publication and is due no later than 5:00 pm on April 15, 2013.  At its meeting in late April, the Oversight Committee expects to consider final rules reflecting the comments received. Individuals or organizations interested in providing input on the rule changes and new rules may do so by sending written comments to Ms. Kristen Pauling Doyle, General Counsel, Cancer Prevention and Research Institute of Texas, P. O. Box 12097, Austin, Texas 78711.  Comments may also be submitted electronically to kdoyle@cprit.state.tx.us or by facsimile transmission to 512/475-2563.  Comments must be received no later than 5:00 pm on April 15, 2013.

Maternal caffeine intake during pregnancy is associated with birth weight but not with gestational length: results from a large prospective observational cohort study

This has been an intriguing question for a long time. Here the Institute of Public Health of Norway looked at 59,123 women and found that ... but read on:

Verena Sengpiel, Elisabeth Elind, Jonas Bacelis, Staffan Nilsson, Jakob Grove, Ronny Myhre, Margaretha Haugen, Helle M Meltzer, Jan Alexander, Bo Jacobsson and Anne-Lise Brantsaeter

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BMC Medicine 2013, 11:42 doi:10.1186/1741-7015-11-42
Published: 19 February 2013

Abstract (provisional)

Background

Pregnant women consume caffeine daily. The aim of this study was to examine the association between maternal caffeine intake from different sources and (a) gestational length, particularly the risk for spontaneous preterm delivery (PTD), and (b) birth weight (BW) and the baby being small for gestational age (SGA).

Methods

This study is based on the Norwegian Mother and Child Cohort Study conducted by the Norwegian Institute of Public Health. A total of 59,123 women with uncomplicated pregnancies giving birth to a live singleton were identified. Caffeine intake from different sources was self-reported at gestational weeks 17, 22 and 30. Spontaneous PTD was defined as spontaneous onset of delivery between 22+0 and 36+6 weeks (n = 1,451). As there is no consensus, SGA was defined according to ultrasound-based (Marsal, n = 856), population-based (Skjaerven, n = 4,503) and customized (Gardosi, n = 4,733) growth curves.

Results

The main caffeine source was coffee, but tea and chocolate were the main sources in women with low caffeine intake. Median pre-pregnancy caffeine intake was 126 mg/day (IQR 40 to 254), 44 mg/day (13 to 104) at gestational week 17 and 62 mg/day (21 to 130) at gestational week 30. Coffee caffeine, but not caffeine from other sources, was associated with prolonged gestation (8 h/100 mg/day, P <10-7). Neither total nor coffee caffeine was associated with spontaneous PTD risk. Caffeine intake from different sources, measured repeatedly during pregnancy, was associated with lower BW (Marsal -28 g, Skjaerven -25 g, Gardosi -21 g per 100 mg/day additional total caffeine for a baby with expected BW 3,600 g, P <10-25). Caffeine intake of 200 to 300 mg/day increased the odds for SGA (OR Marsal 1.62, Skjaerven 1.44, Gardosi 1.27, P <0.05), compared to 0 to 50 mg/day.

Conclusions

Coffee, but not caffeine, consumption was associated with marginally increased gestational length but not with spontaneous PTD risk. Caffeine intake was consistently associated with decreased BW and increased odds of SGA. The association was strengthened by concordant results for caffeine sources, time of survey and different SGA definitions. This might have clinical implications as even caffeine consumption below the recommended maximum (200 mg/day in the Nordic countries and USA, 300 mg/day according to the World Health Organization (WHO)) was associated with increased risk for SGA.

The complete article is available as a provisional PDF. The fully formatted PDF and HTML versions are in production.

Crossing the Omic Chasm. A Time for Omic Ancillary Systems

Free ViewPoint
 

Justin Starren, MD, PhD; Marc S. Williams, MD; Erwin P. Bottinger, MD

[+] Author Affiliations

JAMA. 2013;():1-2. doi:10.1001/jama.2013.1579.

Text Size: A A A

Published online March 14, 2013

Article

Figures

References

• 

Figures in this Article

Despite the information gains from genome-wide association studies and next-generation sequencing (NGS), there remains a chasm between this scientific knowledge and daily clinical practice. Leveraging recent advances in genomics to improve patient care will require electronic health record (EHR) systems that incorporate genomic clinical decision support (CDS). The eMerge (Electronic Medical Records and Genomics)^1- 2 consortium is bridging this chasm by developing interoperable systems that can integrate large-scale genomic data with clinical workflows. According to a recent Institute of Medicine report,³ the current document-centric approach to omic (eg, genomic, epigenomic, proteomic, metabolomic) data will not scale, making storage of raw omic data in current-generation EHRs not feasible. Although commercial EHRs may eventually evolve to handle omic data efficiently, dedicated omic ancillary systems will be essential in the interim.

Historically, “EHR” has been taken to refer to the system used in day-to-day patient care, whereas systems that collect and manage specialized data, such as laboratory, pharmacy, and imaging, have been considered “ancillary” systems. Before discussing how an omic ancillary system would function, it is useful to consider how omic data differ from conventional health data. The simplest difference is the amount of data. Current EHRs are optimized to manage large numbers of discrete and actionable items to facilitate clinical care. They are not designed to store large blocks of data that do not require rapid access. When diagnostic tests create large data sets, ancillary systems are developed to manage the data, and only a subset of clinically relevant information is transferred to the EHR. The archetypal example is imaging. Radiologic images are stored in a picture archiving and communication system (PACS). Radiologists interpret the images to generate a report, and only the text report is stored in the EHR database. An EHR may interface with a PACS to display images, but it does not store them. This dichotomy is evident by comparing the amount of data stored in the EHR vs that stored in ancillary systems. For example, at Northwestern University, the EHR averages 375 kB per patient, whereas the PACS averages 104 MB per patient (a 277-fold difference). Typical NGS identifies 3 to 10 million variants per individual,⁴ requiring 5 to 10 GB of storage (50-fold greater than imaging). Compression may reduce the absolute storage requirement but will not reduce the number of variants to be considered.

One maxim taught to medical students is never to order any test unless the results of the test may affect a treatment decision. The implication of this maxim is that clinicians know how they will interpret each piece of information before that information is collected. Most clinical laboratory tests measure variable parameters (eg, serum sodium level) compared with set reference values, allowing interpretation using the relevant clinical context. It is unlikely that current understanding of sodium metabolism will change so radically that reinterpretation of historical sodium values is necessary.

Omic data are different. An individual's germline genetic sequence changes little over a lifetime, but understanding of that sequence is changing rapidly. For years the DNA between coding regions was called “junk,” but it is now known that this DNA plays an important role in gene regulation.^5- 6 The 1000 Genomes project has identified tens of millions of different genomic variants; the clinical significance of these variants is mostly unknown, but current understanding is rapidly changing. Unlike serum sodium levels, the clinical implications of NGS obtained today will keep changing for years as knowledge evolves. This necessitates systems that dynamically reanalyze and reinterpret stored static genomic results in the context of evolving knowledge.

The Figure shows the possible data paths that omic data may take from collection to use. Today, most genomic results are delivered as textual reports (route A). Small panels of genes can be reported as conventional laboratory results (route B).⁷ Although some results will likely continue to be stored this way, NGS will overwhelm both routes. Conventional human-centric approaches to genomic results do not support reinterpretation as new knowledge emerges and will be gradually replaced by computer-centric approaches.

Figure. Integration of Genomic Data With Electronic Health Records

Integration depends on the format and complexity of the data. Note that data paths convey high-level data flows and do not necessarily imply point-to-point connections. CLIA indicates Clinical Laboratory Improvement Amendments.

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Increasingly, NGS and other high-dimensionality omic testing will become routine, creating large, complex data sets and setting the stage for “omic” ancillary systems. This approach adds value by providing a location to store variants of unknown significance until enough knowledge emerges to move these variants into clinical practice. Three paths could facilitate transfer of actionable genomic information to the EHR: (1) results of the genomic analysis could be manually reviewed, converted to a textual report, and presented to the clinician (route C); (2) “computable observations” could be created and stored within the EHR, where the observations can be used to trigger conventional CDS rules (route D); or (3) an external CDS system could be incorporated that is queried by the EHR at appropriate points in the clinical workflow (route E). Although that CDS system is shown as part of the omic ancillary system, it is also possible that the CDS system could be external to the organization.

Large organizations will likely operate their own omics ancillary systems, in the same way that they maintain other ancillaries. For smaller practices, reference laboratories may add omic ancillary services to their existing services. The number of clinically significant variants is currently limited, but the availability of affordable NGS will greatly accelerate this flow. Omic ancillary systems are one way to bridge the omic chasm without waiting for an entirely new generation of EHRs to emerge.

AUTHOR INFORMATION

Corresponding Author: Justin Starren, MD, PhD, Division of Health and Biomedical Informatics, Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 750 N Lake Shore Dr, 11th Floor, Chicago, IL 60611 (justin.starren@northwestern.edu).

Published Online: March 14, 2013. doi:10.1001/jama.2013.1579

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Bottinger reported that he is named on a previous patent application for personalized clinical decision support.

Funding/Support:The eMERGE Network was initiated and funded by National Human Genome Research Institute through the following grants: U01HG006828 (Cincinnati Children's Hospital Medical Center/Harvard); U01HG006830 (Children's Hospital of Philadelphia); U01HG006389 (Essentia Institute of Rural Health); U01HG006382 (Geisinger Clinic); U01HG006375 (Group Health Cooperative); U01HG006379 (Mayo Clinic); U01HG006380 (Mount Sinai School of Medicine); U01HG006388 (Northwestern University); U01HG006378 (Vanderbilt University); and U01HG006385 (Vanderbilt University serving as the Coordinating Center).

Role of the Sponsors: The funders had no role in the preparation, review, or approval of the manuscript.

Additional Contributions: We thank all the members of the eMERGE EHR Integration workgroup for input on this article.

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