NF1 -omics

Allergenome

Les pathologies salivaires

Antibodyome

In vitro modeling of hyperpigmentation associated to neurofibromatosis type 1 using melanocytes derived from human embryonic stem cells

Bibliome

Haplotype structure enables prioritization of common markers and candidate genes in autism spectrum disorder

Chaperome

Rethinking HSF1 in Stress, Development, and Organismal Health

Connectome

Resting state functional MRI reveals abnormal network connectivity in Neurofibromatosis 1

Cytome

Neurofibromin is a Novel Regulator of Ras-induced Reactive Oxygen Species Production in Mice and Humans

Dynome

NF1 loss disrupts Schwann cell–axonal interactions: a novel role for semaphorin 4F

Editome

Tissue-specific modification of gld-2 mRNA in C. elegans: Likely C-to-U editing

Embryome

Congenital tumours and tumour‐like lesions in domestic animals. 1. Cattle A review

Envirome

Neurofibromas in NF1: Schwann cell origin and role of tumor environment

Epigenome

Epigenetic mechanisms drive the progression of neurofibromas to malignant peripheral nerve sheath tumors

Exome

Exome sequencing identifies recurrent mutations in NF1 and RASopathy genes in sun-exposed melanomas

Exposome

Ten novel mutations in the human neurofibromatosis type 1 (NF1) gene in Italian patients

Fluxome

The space of enzyme regulation in HeLa cells can be inferred from its intracellular metabolome

Foodome

Nutrient intake in neurofibromatosis type 1: A cross-sectional study

Genome

A porcine model of neurofibromatosis type 1 that mimics the human disease

NF1 Genome Project

Glycome

Glioblastoma extracellular vesicles: reservoirs of potential biomarkers

Hologenome

Identification of de novo deletions at the NF1 gene: no preferential paternal origin and phenotypic analysis of patients

Interactome

Clustered, Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9-coupled Affinity Purification/Mass Spectrometry Analysis Revealed a Novel Role of Neurofibromin in mTOR Signaling

Interferome

An inflammatory gene signature distinguishes neurofibroma Schwann cells and macrophages from cells in the normal peripheral nervous system

Ionome

A systematic assessment of chemical, genetic, and epigenetic factors influencing the activity of anticancer drug KP1019 (FFC14A)

Kinome

Targeting the Kinome in Neurofibromatosis type 1 

Lipidome

Evaluating modified diets and dietary supplement therapies for reducing muscle lipid and improving muscle function in neurofibromatosis type 1 (NF1)

Mechanome

Mechanical Signaling in NF1 Osteoblast Cells

Membranome

SPD – A web-based secreted protein database

Metabolome

Metabolome Profiling by HRMAS NMR Spectroscopy of Pheochromocytomas and Paragangliomas Detects SDH Deficiency: Clinical and Pathophysiological Implications

Metagenome

Gene Expression and Molecular Characterization of a Xylanase from Chicken Cecum Metagenome

Metallome
Methylome

The DNA methylome

Microbiome
Moleculome
ORFeome
Obesidome
Organome
Pharmacogenome
Phenome
Physiome
Phytochemome
Proteome
Regulome
Researchsome
Secretome
Sociome
Speechome
Synaptome
Synthetome
Toponome
Toxome
Transcriptome
Trialome
Variome
Volatilome

A drug to cure cutaneous neurofibroma could be worth $3B

800px-neurofibroma02

According to the NY Times and NPR, drugs for orphan diseases have become big business, partly due to side-effects of a law intended to promote development.  The Times discusses two recent sales:

  1. $3.3 billion for rights to the drug Kalydeco for cystic fibrosis, which has a frequency of 1:3500 births.
  2. $2.85 billion for rights to the drug Tysabri for multiple sclerosis, which has a frequency of 1:750.

Cutaneous neurofibroma is a kind of benign skin tumor suffered by most people with NF1, which means that there is a mutation in the gene which codes for neurofibromin 1, which is a tumor suppressing protein.  NF1 has a frequency of 1:3000 which makes it more frequent than CF and less frequent than MS.  By the numbers above, a drug which prevents or eliminates cutaneous neurofibroma would be worth $3billion.

The drug selumetinib was discovered by Array BioPharma and licensed to  AstroZeneca.  The agreement has had some difficulties.  Selumetinib was approved to treat neurofibroma.  An early phase trial shows tumor reduction but not elimination.   Selumetinib is an MEK inhibitor.

NF1 biomarkers and etc.

CTF has a biobank: http://www.ctf.org/understanding-nf/ctf-biobank  Mt. Sinai is the prime contractor for sample collection, so if you are Med School professor there, this is easy:https://www.synapse.org/#!Synapse:syn4984604/wiki/247965

There are also 43 tissue banks in Europe.

In search of biobanks I found this wonderful summary of pathogenesis clues for NF1, which expands on Korf’s summary:

Diagnostic biomarkers

Predictive and pharmacodynamic biomarkers

Higher melanoma inhibitory activity (MIA)

Candidate genes: SOX5NOL1MLF2FOXM1FKBP1CDK4TSPAN31ERBB2MYC and TP53

Higher adrenomedullin (ADM)

Aurora kinase A

Higher serum fetal antigen 1

Survivin (BIRC5), thymidine kinase 1 (TK1) and topoisomerase 2-a (TOP2A) immunohistochemical staining of malignant peripheral nerve sheath tumors to split patients into high and low risk

Higher serum soluble growth factor receptor Axl (sAxl)

Lower blood circulating levels of hepatocyte growth factor

Significant differences in interleukin-6, interferon-γ, epidermal growth factor receptor, tumor necrosis factor–α, insulin-like growth factor binding protein 1 and RANTES

Survival in NF1 patients with methylated or unmethylated RASSF1A at five years

miR-204 downregulation in patients with NF1 with malignant peripheral nerve sheath tumors

 There are 42 or 43 omics, depending on your count:

Allergenome

Interactome

Phenome

Bibliome

Interferome

Physiome

Connectome

Ionome

Phytochemome

Cytome

Kinome

Proteome

Editome

Lipidome

Regulome

Embryome

Mechanome

Researchsome

Envirome

Metabolome

Secretome

Epigenome

Metagenome

Speechome

Exome

Metallome

Synthetome

Exposome (2005)

Microbiome

Toponome

Exposome (2009)

Obesidome

Transcriptome

Foodome

ORFeome

Trialome

Genome

Organome

Volatilome

Glycome

Pharmacogenetics

Hologenome

Pharmacogenome

For any of these topics, we could ask, “has anybody done something on NF1 xxxics?”  Randomly selecting “proteomics”, I get immediate hits:

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3650346/

https://www.ncbi.nlm.nih.gov/pubmed/15805275

https://www.nature.com/articles/mp201548

Let’s do a blog post inventorying articles under each omic for NF1, on a rainy day.

Also here’s a rather dense but topical article to save for a rainy day:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4573439/

 

Pathogenesis of NF1

Bruce Korf wrote this summary of the pathogenesis of NF1 which I will unpack here a little bit.

“NF1 is due to mutations in the NF1 gene, located at chromosome 17q11.2″

“Neurofibromin, the protein product encoded by the gene, is expressed in many tissues, including brain, kidney, spleen, and thymus.”

“It belongs to a family of guanosine triphosphate hydrolase (GTPase)-activating proteins (GAPs)”

“that stimulate intrinsic GTPase activity in the ras p21 family (21 kD rat sarcoma viral oncogene homologs)”

“Ras activates a number of signaling pathways”

“that includes the stem cell factor (SCF)/”

“c-kit signaling, ”

“mechanistic target of rapamycin (mTOR), and ”

“mitogen-activated protein kinase (MAPK) pathways.”

“Mutations in the NF1 gene result in loss of production or reduced function of protein,”

“causing the wide spectrum of clinical findings, including NF1-associated tumors.  ”

“Penetrance, or the likelihood that the individual carrying the mutation will manifest the disorder, is complete.”

“NF1 is highly variable in its expression, however (ie, the severity of and specific manifestations of the disorder vary among affected individuals within the same family and from one family to another) . ”

“Somatic mutation or loss of heterozygosity at the NF1 locus,”

“in combination with a germline NF1 mutation,”

“leads to complete loss of neurofibromin expression that is seen in NF1 lesions such as pseudoarthrosis and neurofibromas.”

” NF1 therefore functions as a tumor suppressor gene.”

How complex is a cell?

I asked a biologist recently how many parts there were to a cell.  I hazily remember pictures of an outside and an inside.  She said “more than 10,000”.  Let’s quantify that:

How many atoms? How about 100 trillion.

How many molecules? Between 5 million and 2 trillion?

How many proteins? About 10 billion?

Why ask?  The real question is: How hard is it to simulate a cell.  At a brute force level, the answer is: hard.  Obviously there is a lot of structure to a cell that I can’t begin to imagine.  It’s something I should study up a bit more.

Tweaking ACH for FARC

bokeh_plot

[Cross post]

ACH is a methodology which scores Inconsistency but doesn’t score Consistency. At most it says that evidence is really not consistent with the outcome, without opining on whether it is consistent.https://en.wikipedia.org/wiki/Analysis_of_competing_hypotheses http://competinghypotheses.org/docs/ACH,_Step_By_Step has Credibility and Relevance scores

The Xerox ACH implementation http://www.pherson.org/PDFFiles/ACHTechnicalDescription.pdf
has Credibility and Relevance scores of Low=1/sqrt(2), Medium = 1 and High = sqrt(2). The Consistency score is Very Inconsistent = -2, Inconsistent=-1, and Neutral, Consistent and Very Consistent are 0. The Weighted Inconsistency Score is Credbility * Relevance * Consistency. So any evidence item which is not inconsistent gets a weight of 0.

For my ACH-ish model, as applied to rationales with comments supplied for forecasts, I will weight as follows. Let the forecast be F. Assign Credibility and Relevance scores of Low=1/(2sqrt(2)), Medium = 1/sqrt(2), and High = 1. Let the Consistency score C be -1,-1/2,0,1/2,1. Let W = Credibility * Relevance. Then my ACH-ish-model weighted forecast will be W100*(C+1)/2 and ignore the original forecast in the formula, just looking at it as a shorthand for the text and how to view the import of the text.

So far I see 74 forecasts for FARC of which 32 have rationales. My model for FARC is ACH-ish as above. The Consensus has been towards 0 on FARC except it just picked up a little. The early comments on FARC anticipated that pick-up.