The Palpable Prostate

Prostate cancer topics, links and more. Now at 200+ posts!

News: Health Day, Medical News Today, ScienceDaily, Urol Times, Urotoday, Zero Cancer Papers: Pubmed (all), Pubmed (Free only), Amedeo
Journals: Eur Urol, J Urol, JCO, The Prostate Others Pubmed Central Journals (Free): Adv Urol, BMC Urol, J Endourol, Kor J Urol, Rev Urol, Ther Adv Urol, Urol Ann
Reviews: Cochrane Summaries, PC Infolink Newsletters: PCRI, US Too General Medical Reviews: f1000, Health News Review
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Saturday, April 30, 2016

Blog Updates for April 2016

Note to readers. The Palpable Prostate Blog has now published over 200 blog posts -- this post is number 201.

April 30, 2016 in Metformin and protate cancer we added: A number of investigations have concluded that metformin acts by blocking the glucose cancer cells need and in the absence of glucose they will turn to glutamanine and leucine. They hypothesize that interfering with glutamine and leucine uptake might synergistically work with metformin. Note that glutamine is a non-essential amino acid (i.e. the body can produce it itself) so simply lowering the intake of glutamine-containing foods might not be effective. [PMID: 23687346] [Free full text] [PMID: 26550231] [Full free text] [PMID: 24052625] [Full free text]

Thursday, March 31, 2016

Blog Updates for March 2016

March 31. In Choosing a Surgeon - Part I. Considerations, Choosing a Surgeon - Part I we added: Incidentally it has also been found that it is also true that radiation at high volume centers have better outcomes. See [PMID: 26972640] .

Thursday, February 25, 2016

Blog Updates for Feburary 2016

Feb 25, 2016. In Prostate Cancer Calculators we added this calculator: Probability of Recurrence, Potency and Continence after Laprascopic (LRP) Surgery Based on 500 LRP surgery patients of Christopher Eden this calculator accepts PSA and stage and displays the percentage of patients who were cancer-free, the percentage who regained potency and the percentage who regained continence after surgery. It also displays a table of data for all patients fitting the input parameters. The data is based on a follow up of 12 - 36 months with an average follow up of 13.5 months. The site links to a paper that provides more background detail. See theprostateclinic .

Feb 25, 2016. In Prostate Cancer Calculators we added this calculator in the Memorial Sloan Kettering section: Life Expectancy:As described and linked to in this prostatecancerinfo review "to use the tool, you will first be asked a number of questions about your health, your age, and your diagnosis with prostate cancer, and then those data are used to project your risk of death from prostate cancer and from other causes at 10 and 15 years after diagnosis.

Tuesday, January 5, 2016

Metformin and prostate cancer

[Updated April 30, 2016]

A 2014 article in the Journal of the National Cancer Institute by Azvolinksy [PMID: 24511112] [Full Free Text] and a 2014 article by Fleshner in the Canadian Urological Association Journal [PMID: 25243043] [Full Free Text] discuss observational studies on diabetic prostate cancer patients which have shown reduced risk of death from prostate cancer as well as reduced all cause mortality among those taking the widely used inexpensive diabetes drug, metformin.

An undated overview by Peter Wehrwein speculates that the biological mechanism may be the lowering of insulin, lowering of blood sugar output of the liver or via interruption of signalling pathways. A number of investigations have concluded that metformin acts by blocking the glucose cancer cells need and in the absence of glucose they will turn to glutamanine and leucine. They hypothesize that interfering with glutamine and leucine might synergistically work with metformin. Note that glutamine is a non-essential amino acid (i.e. the body can produce it itself) so simply lowering the intake of glutamine-containing foods might not be effective. [PMID: 23687346] [Free full text] [PMID: 26550231] [Full free text] [PMID: 24052625] [Full free text].

A 2015 meta-analysis by Wu et al found that the risk of developing prostate cancer (as opposed to the risk of death for those who have prostate cancer) is unaffected by metformin.

Confirmation of these results in diabetics and non-diabetics through randomized clinical trails is underway. See: [ClincialTrials.gov]

Monday, November 30, 2015

From Pilot to System Solution

It seems that so much is known in medicine and health care that is not widely enough applied. The video below of the keynote talk by Dr. Danielle Martin at the Health Quality Transformation 2015 conference focused on health care in Ontario notes that "less than 40% of health improvement projects successfully expand beyond the early group of adopters who first bring them to life" and discusses how innovation can move from pilot to system-wide application.

It discusses the concepts of spread and scale:

- Spread is about innovations diffusing to other teams or organizations, one at a time, as successive teams learn of the successful innovation and individually decide to adopt it.

- Scale is about large scale structural change involving policies that are implemented all at once across an entire region. It requires significant resources and political capital.

She discusses the application of these concepts and many associated issues and examples.




Sunday, November 1, 2015

Peto's Paradox

The larger an animal is the more cells it has and the longer lived an animal has the more time cells have to mutate so one would think that larger and longer lived animals would have more cancer; however, that is not the case.   Science World Report quotes researchers as saying that "less than 5 percent of elephants develop cancer compared to 25 percent of humans". That larger animals do not have higher rates of cancer is called Peto's paradox. [Wikipedia] [PMID: 21296451] [Full text] While it may be that larger animals do not get more cancer larger, or at least taller, humans have higher rates of cancer than shorter humans so this observation does seem to hold on the scale of an individual species. Evidently methods of cancer prevention have evolved in larger animals; however, taller humans may not have evolved over a sufficiently long period to elicit an evolutionary response.

We can get a bit more insight by reviewing the simple probability model of cancer developed by Calabrese and Shibata. [PMID: 20051132] [Full text] [Excel model] [Powerpoint slides] [Also see Box 2 of this paper] Assume that mutations must occur in k critical genes for cancer to occur. Assume each gene divides into d copies in its cell lineage and that there are M cells at risk in a particular organ such as the prostate -- all cells in an organ are not necessarily at risk so M is, in general, less than the number of cells in an organ.  Let u be the prob of a mutation in one critical gene. Then as shown by Calabrese and Shibata (also see proof at end of this post) the probability of cancer, p, is:

       p = 1 - (1 - (1 - (1 - u)^d)^k)^M

Larger animals have more cells, M, and longer lived animals undergo more cell divisions d.  The number of mutations needed for cancer, k, could vary among animals and the even by the type of cancer within a species.  Thus a number of other factors may be at play as well as size and life expectancy.

In the case of elephants two independent papers have concluded that they have multiple copies of the p53 tumor suppressor gene (which kills cancer cells) whereas humans only have a single set.  This had been previously hypothesized; however, these two 2015 papers seem to have independently determined this to be the case.

Abegglen et al
http://jama.jamanetwork.com/article.aspx?articleid=2456041

Sulak et al
http://biorxiv.org/content/early/2015/10/06/028522

An interview with Joshua Schiffman, an author of the first paper, appears here:
http://medicalxpress.com/news/2015-10-elephants-rarely-cancer-potential-mechanism.html

In a New York Times article
http://www.nytimes.com/2015/10/13/science/why-elephants-get-less-cancer.html
Dr. Patricia Muller mentions that this research does not establish the mechanism of action so further work needs to be done even before attempting to replicate this in humans.  Furthermore, the following paper: http://www.impactaging.com/papers/v2/n7/full/100178.html indicates that in
some contexts p53 accelerates aging in mice whereas in other contexts it promotes longevity so there is some question as to whether it would be feasible to apply p53 at all to humans.

Other large or long lived animals with low cancer rates might have evolved different mechanisms of combating cancer.  Discovering the various mechanisms that evolved over millions of years might lead to cancer treatments in humans.  Schiffman is quoted in the same New York Times article as speculating "that parrots, tortoises and whales may all have special longevity tactics of their
own".  http://www.nytimes.com/2015/10/13/science/why-elephants-get-less-cancer.html

Note:
The formula given above can be derived as follows:

p = 1 - Prob of no cancer in any of the M cells at risk)
       = 1 - (Prob of no cancer in one cell at risk)^M
       = 1 - (1 - Prob of cancer in one cell at risk)^M
       = 1 = (1 - Prob of one cell accumulating k mutations)^M
       = 1 - (1 - (Prob of one mutation)^k)^M
       = 1 - (1 - (Prob of mutation in 1 critical gene)^k)^M
       = 1 - (1 - (1 - Prob of no mutation in one cell lineage)^k))^M
       = 1 - (1 - (1 - (1 - Prob of no mutation in one of d divisions)^d)^k)^M
       = 1 - (1 - (1 - (1 - u)^d)^k)^M

Tuesday, September 29, 2015

Blog Updates for September 2015

Sep 27, 2015. In Prostate Cancer Calculators we added:
  • Date of Death The population.io web site asks for your birthday, country and gender and based on this input estimates what percentage of people in your country and on earth are younger than you and your date of death.
  • Mortality Simulator The flowingdata web site shows a chart with a blue curve part way down the page. The curve represents the probability of living for at least another year given your age. The probability is on the vertical axis and age is on the horizontal axis. Moving dots traverse the blue curve representing lifetimes of a single person. They drop off the curve at death and accumulate in piles below the curve. These piles represent the distribution of life spans.