The Palpable Prostate

Prostate cancer topics, links and more. Now at 100+ 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

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

Sulak et al

An interview with Joshua Schiffman, an author of the first paper, appears here:

In a New York Times article
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: 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

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 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.

Friday, August 14, 2015

Nutritional Supplements and Prostate Cancer

[Updated August 17, 2015]

Literature Review

A 2015 survey of nutritional approaches to prostate cancer published in BMC Medicine contains a table of approaches for which the authors found research. See table 1 in [Full Free Text of paper].


A 2014 six month randomized placebo-controlled double blind UK study published in Prostate Cancer and Prostatic Diseases of a mixture of polyphenols (pomegranate, green tea, turmeric and brocolli) with 199 prostate cancer patients on Active Surveillance or Watchful Waiting found that the treatment arm had an increase in PSA of 14% vs. 79% for the control arm (lesser increase is more favorable). The paper notes that the study received no funding from the manufacturer of the supplement. [Full Free Text of Paper] [Cancernet UK Charity info] [video interview with researcher Robert Thomas] [Manufacturer's FAQ].

PSA Doubling Time. Note that a 14% increase in PSA over a 6 month period (as found in the treatment arm) represents a doubling time of 6 / log2(1.14) = 31.74 months whereas an increase of 79% over 6 months (as found in the control arm) represents a doubling time of 6 / log2(1.79) = 7.14 months. Thus the doubling time was 31.74 / 7.14 = 4.4x times longer in the treatment arm (higher is more favorable).

Disease Progression. MRI scans were not part of the protocol but many of the patients had them anyways as part of their routine medical visits and these scans were consistent with lesser disease progression in the treatment arm (as opposed to just a matter of just modifying the PSA kinetics).

Group Composition. The treatment and control groups were assigned randomly subject to assigning 2 patients in the treatment group for every patient in the control group. By chance the average age in the treatment group was 5 years less than the average age in the control group so statistical methods were used to adjust the results to correct for this difference. On other measured variables the two groups were statistically similar.

A 12 month US study on effects of pomegranate extract on rising PSA levels

A randomized double blind trial of pomegranate extract on 183 men with rising PSA after primary therapy published in Prostate Cancer and Prostatic Disease 2015 found no effect on PSA doubling time. It did find some indications that patients with the MnSOD AA genotype might benefit but this would require a further study to confirm. Some of the study authors received funding from the manufacturer of the extract. See [PMID: 26169045] [Full Free Text].

Key differences between this study and the UK NCRN POMI-T study are that:
  • this study was performed after primary therapy whereas the UK study was performed on patients undergoing Active Surveillance and Watchful waiting.
  • this study examined only pomegranate extract whereas the prior study examined pomegranate extract in combination with 3 other polyphenols.
  • this study followed men for one year and the UK study for 6 months

Saturday, August 1, 2015

Blog updates for July 2015

August 1, 2015.  In PSADT Part 1 we add: PSA Doubling Time (PSADT) was found to be the most consistent of the top prognostic factors for a variety of endpoints (prostate cancer-specific survival, metastases-free survival, overall or all cause survival) in a 2015 literature review of relevant studies so we focus this 5 part series of posts specifically on it. [PMID: 26180662] [Full Free Text]. (The other consistent key factors were Gleason Score and Time to Biochemical Failure.)

Wednesday, July 1, 2015

Demographic Factors Affecting Prostate Cancer Mortality

In a June 25, 2015 PLoS One paper [full text] Yao et al perform a regression of prostate cancer mortality (one point per county) using the following explanatory variables:

Significant at 0.1% level:

- more urologists per 100,000 people decreases prostate cancer mortality
- being in a metropolitan country decreases prostate cancer mortality
- greater percentage of population being non-white increases prostate cancer mortality
- greater percentage of population with high school diploma decreases prostate cancer mortality

Significant at 1% level:
- greater prostate cancer incidence per 100,000 men increases prostate cancer mortality

Significant at 5% level:
- if county is a designated Health Professional Shortage Area it increases prostate cancer mortality
- if per capita income is higher then it reduces prostate cancer mortality

Factors that were not significant were:
- radiation oncologists per 100,000 people
- beds per 100,000 people
- percent of population over 65

Monday, June 1, 2015

Less lethal prostate cancer among those diagnosed with asthma

In a review of the Health Professionals Follow Up study (47,000 men) researchers found the proportion of subjects with lethal prostate cancer was 29% less among those who had been diagnosed with asthma vs. those who had not.   For those had been disagosed with hayfever the risk was 10% higher.  

The finding for asthma is odd because both prostate cancer and asthma are thought to be related to inflammation so that if there were a correlation the risk of lethal prostate cancer would be expected to be higher, not lower.
See [PMID:] and [Science Daily]

Thursday, April 30, 2015


A study of prostate cancer in a mouse model published this month [PMID: 25868577] concludes that "4-MU is an effective nontoxic, oral chemopreventive, and therapeutic agent that targets PCa development, growth, and metastasis by abrogating HA signaling." 4-MU (short for 4-Methylumbelliferone). It is also known as Hymecromone. It works by inhibiting hyaluronic acid.

Regarding the animal studies the researchers said:
"We found that when treatment started early, at eight or 12 weeks it completely inhibited prostate cancer development and growth ...  At 22 weeks, we found small cancers that had stopped growing and even regressed in some cases. Also to our amazement, while 60 percent of the animals in the control group experienced metastasis to distant organs, none in the treatment group developed metastasis. 4-MU did all of this without causing any toxicity to the host." Quoted in this News article

Although success in mice models is far from success in humans if 4-MU were effective for prostate cancer in humans as well, it would have the advantages that:
  1. it is already an approved for use in Europe and Asia (in Italy it goes by the name Cantabilin® for biliary applications and is called Cantabiline® in France and Belgium and in other countries by other names).
  2. Numerous human trials of 4-MU have been carried out.  See Table; however, these trials were for use in non-cancer applications and safety in cancer applications does not necessarily follow.  For example, if higher doses were required for cancer application at those higher doses there could be additional safety concerns; nevertheless, this is better from the viewpoint of unknown risks than a completely new drug.
A March, 2015 review of 4-MU appears here: [PMID: 25852691]