The role of the tetraspanin CD9 in metastasis – A double edged sword?

The current consensus is that CD9 is a metastasis suppressor. CD9 expression has been inversely associated with the metastasis of cancers. That is low CD9 protein expression is associated with tumour samples taken from secondary metastatic sites compared to the primary tumour site. Furthermore in a number of cancer cell lines and primary cells, CD9 expression has been shown to decrease cell motility. A number of studies however conversely demonstrate that CD9 can increase the motility of cancer and “normal” cells. This does not fit with the metastasis suppressor hypothesis and has not been adequately explained by current models of CD9 function during metastasis.

These apparently contradictory observations may stem from the large number of functionally distinct steps that the term metastasis covers. … Furthermore recent evidence suggests that contrary to the traditional view that metastasis occurs late in cancer progression, metastasis may occur early in relatively normal cells. This has serious implications for the role of CD9 and many other proteins in metastasis. CD9 is widely expressed in many normal cells. If metastasis occurs early this suggests that CD9 expression does not inhibit metastasis.

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Does Colombia hold the solution to the antibiotic crisis?

Antibiotic resistance is an immediate serious problem. There is a limited pipeline of new antibiotics largely due to the lack of financial incentive for pharma to develop them:

https://longitudeprize.org/blog-post/antibiotic-resistance-why-fuss-and-what-simple-actions-can-everyone-take

There is an urgent need for new antibiotic discovery. There is good reason to think that Colombia is in a strong position to supply this need:

  1. Colombia represents about 0.7% of the land surface worldwide and this area contains 10% of the world’s biodiversity, making Colombia a “megadiverse country” [1].
  2. New simple and cheap methods have been developed for culturing previously unculturable bacteria:

    http://www.statnews.com/2015/12/03/antibiotics-bacteria-research/

    It is likely that Colombia’s unique megadiversity is also reflected in the as yet undiscovered bacteria in her soil. This could prove a major untapped source for novel antibiotic discovery.

  3. Antibiotics represent a relatively straightforward entry point for Colombian startup pharma companies to establish themselves and create high skilled employment opportunities. Big Pharma has largely abandoned antibiotic development in favour of more lucrative sectors such as cancer therapeutics.

Refs

  1. Bueno, Juan, Ericsson David Coy, and Elena Stashenko. ‘Antimycobacterial Natural Products–an Opportunity for the Colombian Biodiversity’. Revista Española De Quimioterapia: Publicación Oficial De La Sociedad Española De Quimioterapia 24, no. 4 (December 2011): 175–83. [PMID: 22173186]

Paradigm shift

You have probably come across the term “paradigm shift” before. But who invented it and what does it really mean?

The term was elaborated in Thomas S. Kuhn’s book – The Structure of Scientific Revolutions.

Paradigm:

“Achievements that share these two characteristics I shall henceforth refer to as ‘paradigms’”:

“(1) Their achievement was sufficiently unprecedented to attract an enduring group of adherents away from competing modes of scientific activity. (2) Simultaneously, it was sufficiently open-ended to leave all sorts of problems for the redefined group of practitioners to resolve”.

Extraordinary science:

“History of science indicates that, particularly in the early developmental stages of a new paradigm, it is not even very difficult to invent such alternates. But that invention of alternates is just what scientists seldom undertake except during the pre-paradigm stage of their science’s development and at very special occasions during its subsequent evolution”.

“The proliferation of competing articulations, the willingness to try anything, the expression of explicit discontent, the recourse to philosophy and debate over fundamentals, all these are symptoms of a transition from normal to extraordinary research”.

Revolution leading to paradigm shift is characterised by questions that cannot be answered by normal science:

“Like the issue of competing standards, that question of values can be answered only in terms of criteria that lie outside of normal science altogether, and it is that recourse to external criteria that most obviously makes paradigm debates revolutionary”.

Revolution is likely to be settled by someone from a different field who uses a different paradigm routinely.

Three oncolytic virotherapies approved for cancer patient treatment

Oncolytic virotherapy (drugs based on viruses which trigger cancer cell death and an immune response) have been approved for doctors to prescribe to patients for longer than most realise.

Back in 2003 Gendicine was approved by the State Food and Drug Administration of China (SFDA) for head and neck squamous cell carcinoma (HNSCC) [1].  It is a replication-incompetent, recombinant, serotype 5 human adenovirus (Ad5) engineered to contain the human wild-type p53 tumor-suppressor gene. It could be argued that Gendicine is not in fact a “true” oncolytic virus as it is replication incompetent, however I include it here because in recent years it has been recognised that oncolytic virotherapies generate an immune reaction against the tumour. This can lead to tumour lysis indirectly and may be more important than direct viral lysis. Indeed Gendicine leads to tumour cell lysis.

In 2005 the SFDA of China approved a classic (replication competent) oncolytic virotherapy called Oncorine for HNSCC [2]. Oncorine is an Ad5 with an E1B and E3 gene deletion. The development in the USA of a very similar virus called Onyx-15 was halted at the outset of a phase III trial due to a funding crisis. This funding crisis has resulted in a ten year lag behind China in the approval of an oncolytic virus.

In October 2015, the US food and drug administration (FDA) approved Imlygic, for the treatment of melanoma in patients with inoperable tumors [3]. In Jan 2016 it was approved in Europe for some inoperable melanoma [4]. Imlygic is a herpes simplex virus 1 (HSV-1) based oncolytic vector delivered via injection. It was generated from a fresh isolation of HSV-1 virus (JS1) and has a GM-CSF replacement of the two copies of the ICP34.5 gene which normally reverses the interferon induced phosphorylation of the α subunit of the eukaryotic initiation factor 2 (EIF2S1) [5]. The interferon pathway is usually disrupted in cancer thus lending the vector specificity to cancer cells.

Although the first FDA approval has been a long time coming there are many oncolytic viruses now in the clinical pipeline with more approvals likely.

 

  1. Pearson, Sue, Hepeng Jia, and Keiko Kandachi. ‘China Approves First Gene Therapy’. Nature Biotechnology 22, no. 1 (January 2004): 3–4. doi:10.1038/nbt0104-3.
  2. Garber, Ken. ‘China Approves World’s First Oncolytic Virus Therapy For Cancer Treatment’. Journal of the National Cancer Institute 98, no. 5 (3 January 2006): 298–300. doi:10.1093/jnci/djj111.
  3. ‘FDA Approves Amgen’s Injected Immunotherapy for Melanoma’. Reuters, 27 October 2015. http://www.reuters.com/article/us-amgen-fda-idUSKCN0SL2YH20151027.
  4. Semedo, Daniela, and PhD. ‘Metastatic Melanoma Therapy, Imlygic, Now Available in EU’. Immuno-Oncology News, 7 January 2016. http://immuno-oncologynews.com/2016/01/07/metastatic-melanoma-therapy-imlygic-now-available-eu/.
  5. Liu BL, Robinson M, Han Z-Q, Branston RH, English C, Reay P, et al. ICP34.5 deleted herpes simplex virus with enhanced oncolytic, immune stimulating, and anti-tumour properties. Gene Ther 2003; 10:292–303. [PMID: 12595888]

New candidate biomarkers for early detection of pancreatic cancer

One of the reasons the prognosis of pancreatic cancer patients is so poor is due to its late diagnosis as symptoms do not present until an advanced stage. Until recently there have not been effective candidate markers for screening of early stage pancreatic cancer.

Recently the situation has improved. There are now candidates for blood and urine tests.

The protein Glypican-1 shed into blood from tumours as exosomes (lipid droplets) can be  detected in the blood of pancreatic cancer patients but not healthy volunteers [1].

A three protein urine test has been developed which can detect early-stage pancreatic cancer [2].

With further development these markers could form the basis of tests that make screening for pancreatic cancer a routine procedure. If the majority of pancreatic cancer cases could be diagnosed early this would dramatically improve the prognosis of patients.

  1. Melo, Sonia A., Linda B. Luecke, Christoph Kahlert, Agustin F. Fernandez, Seth T. Gammon, Judith Kaye, Valerie S. LeBleu, et al. ‘Glypican-1 Identifies Cancer Exosomes and Detects Early Pancreatic Cancer’. Nature 523, no. 7559 (9 July 2015): 177–82. doi:10.1038/nature14581.
  2. Radon, Tomasz P., Nathalie J. Massat, Richard Jones, Wasfi Alrawashdeh, Laurent Dumartin, Darren Ennis, Stephen W. Duffy, et al. ‘Identification of a Three-Biomarker Panel in Urine for Early Detection of Pancreatic Adenocarcinoma’. Clinical Cancer Research 21, no. 15 (8 January 2015): 3512–21. doi:10.1158/1078-0432.CCR-14-2467.

Some interesting facts about the phylogeny of CUB domains

The Complement subcomponents C1r/ C1s, sea urchin epidermal growth factor (Uegf), Bone morphogenetic protein 1 (Bmp1) domain (CUB domain) is a structural fold named after the first proteins in which it was identified [1].

The CUB domain is predominantly found in multicellular eukaryotes excluding fungi. However they are found in some unicellular plants and protozoa. The genomes of single celled alga and plankton as well as multicellular moss and poplar tree contain CUB proteins. There are few known CUB proteins from protozoa, however the parabasalid human parasite Trichomonas vaginalis expresses three proteins that contain a CUB domain and the slime mold Polysphondylium pallidum expresses a CUB protein. CUB domains appear to have been present in some of the earliest unicellular marine eukaryotes such as alga and plankton and have become established in multicellular eukaroytes.

There are examples of CUB domains in bacteria such as Clostridium perfringens [2] and archaea. The Clostridium perfringens and archaea CUB domain gene was probably obtained by horizontal gene transfer from a eukaryote [2].

Interestingly CUB domains have structural similarity to a number of viral capsid proteins including the small protein subunit of the bean-pod mottle virus (BPMV) capsid [3,4]. CUB domains and these capsid proteins may have evolved similar structures through convergent evolution [4].

  1. Bork, P. and G. Beckmann, The CUB Domain : A Widespread Module in Developmentally Regulated Proteins. Journal of Molecular Biology, 1993. 231(2): p. 539-545.

  2. Briggs, D.C. and A.J. Day, A bug in CUB’s clothing: similarity between clostridial CBMs and complement CUBs. Trends in Microbiology, 2008. 16(9): p. 407-408.
  3. Varela, P.F., et al., The 2.4 Å resolution crystal structure of boar seminal plasma PSP-I/PSP-II: a zona pellucida-binding glycoprotein heterodimer of the spermadhesin family built by a CUB domain architecture. Journal of Molecular Biology, 1997. 274(4): p. 635-649.
  4. Romero, A., et al., The crystal structures of two spermadhesins reveal the CUB domain fold. Nat Struct Biol, 1997. 4(10): p. 783-8.

R script, microarray data, and the interesting outliers

I previously mentioned that outliers in microarray data are what you should be interested in. But what did I mean by that?

Let’s take a look. The following is an excerpt of simple R script which can be used to examine microarray data outputted from the CARMAweb service:

> gene.normal <- normal.df[“LAMP3”, ]

> t.gene.normal <- as.data.frame(t(gene.normal))

> gene.cancer <- cancer.df[“LAMP3”, ]

> t.gene.cancer <- as.data.frame(t(gene.cancer))

> boxplot(t.gene.normal$LAMP3, t.gene.cancer$LAMP3, names = c(“Normal”, “Cancer”), ylab = “RMA”, main = “LAMP3”)

> mean.normal <- mean(t.gene.normal$LAMP3)

> mean.cancer <- mean(t.gene.cancer$LAMP3)

> fold.change <- mean.cancer/ mean.normal

> mean.normal

[1] 5.377307

> mean.cancer

[1] 5.634959

> fold.change

[1] 1.047915

In this example LAMP3 is being examined. Judging from the average fold change there is no difference between normal tissue and cancer. However if you look at the box plot:
LAMP3

You see that there are three tumours in which the robust multiarray average (RMA) is much higher than in normal tissue. These could represent a small subpopulation of tumours. Although it is difficult to tell from this dataset alone which contains only 45 tumours.

These tumours are potentially important and this would be missed by only looking at the fold change. You could imagine a drug that targets LAMP3 being effective only in this subset. This is much better than no drug being developed because on average there appears to be no fold change.