This study examined whether metformin use predicts prostate cancer diagnosis and prognosis. 1034 men underwent transperineal template-guided mapping biopsy and were divided into 3 groups: nondiabetic, diabetic not taking metformin, diabetic taking metformin. Metformin did not predict cancer diagnosis or severity. Univariate and multivariate analyses found only age predicted cancer diagnosis, and age, PSA velocity, and BMI predicted higher Gleason scores (≥7). While metformin may reduce cancer risk in other types based on biochemical pathways, prostate cancer cells' fast doubling time may limit metformin's effects. Larger studies in more diverse populations are needed to better understand metformin's role in prostate cancer.

1. Metformin as a Predictor
for Prostate Cancer
Diagnosis and Prognosis
Travis Couture

2. Introduction
● Metformin is used to treat patients diagnosed with type 2 diabetes
● Type 2 diabetes is when the body cannot properly use insulin (Type 2,
2014)
○ Metformin works by increasing insulin sensitivity via insulin receptors
and tyrosine kinase activity (Type 2, 2014)
■ By doing this metformin helps limit gluconeogenesis (Violett, et
al., 2012)
■ Metformin lowers insulin levels (Violett, et al., 2012)
● Studies have been published that suggest metformin lowers cancer
mortality rates in pancreatic and hepatocellular cancers (DeCensi, et al.,
2010)

3. Introduction
Insulin is closely related to the activity of IGF-1 (Gallagher, et al., 2014)
Insulin increases activity and expression of growth hormone receptors
(Gallagher, et al., 2014)
IGF-1 is released based on growth hormone receptor signals (Gallagher, et
al., 2014)
Hyperinsulinemia would mean hyperexpression of growth hormone receptors and
an increase in IGF-1
IGF-1 causes cells to grow
Already fast growing tumor cells would grow even faster increasing
mortality rates and severity
Metformin biochemistry inhibits the mTOR pathway (Martin-Castillo, et al., 2010)

4. Figure 1: Shows the direct and
indirect effects that metformin
can have on tumor and
cancerous cell proliferation.
(Martin-Castillo 2010)
Biochemical Pathways of Metformin

5. Methods
1034 men underwent transperineal template-guided mapping biopsy (TTMB)
based on prostate specific antigen (PSA) levels and other criteria
787 of these men underwent transrectal ultrasound (TRUS) guided needle
biopsies before receiving a TTMB
Multiple data points were recorded for the 1034 men
PSA level prior to TTMB, body mass index (BMI), hypertension, age,
prostate volume, etc..
The sample group was divided into 3 subgroups

6. Figure 2: Shows coring sites for TTMB. (Tairia, et al., 2013)
TTMB Coring Sites Map

7. Methods
The subgroups were further categorized based on the presence of cancer
Nondiabetic patients diagnosed cancer (n=493)
Type 2 diabetic men not prescribed metformin and diagnosed with
cancer (n=44)
Type 2 diabetic men prescribed metformin and diagnosed with cancer
(n=47)
Allows for analysis of metformin as cancer predictor (diagnosis)
The distinction of cancer with Gleason score (GS) ≥7 was also made
Allows for analysis of metformin as a predictor for cancer severity
(prognosis)

8. Methods (Statistics)
Mean, median, and standard deviation calculated
1-way ANOVA test was used for continuous variables (BMI, PSA levels, age,
etc…)
Pearson χ² test was used for categorical variables (tobacco use,
hypertension, cancer symmetry, etc…)
Univariate and multivariate analysis used for cancer predictors

9. Results
Metformin use affected BMI, tobacco consumption, and hypertension
Diabetics not prescribed metformin were more likely to use tobacco
(P=0.015), have a higher BMI (P<0.001), and be hypertensive
(P<0.001)
Metformin did not predict for cancer diagnosis or severity
Cancer diagnosis (P=0.153)
GS distribution (P=0.960)
Number of positive biopsy cores (P=0.764)
Risk Group Stratification (P=0.877)

10. Results
Univariate and multivariate analysis of cancer diagnosis
Only age (P=0.003, RR=0.006) predicted for cancer diagnosis
Univariate and multivariate analysis of cancer severity (GS ≥ 7)
Multiple predictors found in univariate analysis
Narrowed to only 3 predictors using multivariate analysis
Age (P<0.001, RR=0.009)
PSA velocity (P=0.025, RR=0.008)
BMI (P=0.010, RR=0.011)

11. Table 1: Shows calculated continuous variable data for the
study population.
Non-Diabetic
Patients
(n=881)
Diabetics Prescribed
Metformin
(n=65)
Diabetics Not
Prescribed
Metformin
(n=88)
All Patients
(n=1034)
Median Mean Median Mean Median Mean Median Mean p
Age (yr) 68.0 68.4 70.0 69.0 72.0 70.5 69.0 68.6 0.059
PSA
(ng/mL) 6.1 7.6 5.2 6.3 6.4 7.9 6.1 7.5 0.334
Volumetric
prostate
(cm3) 52.8 61.3 54.9 58.6 62.7 70.1 53.3 61.9 0.059
Ellipsoid
prostate
(cm3) 46.4 54.5 48.5 52.4 57.2 62.9 47.3 55.1 0.055
Ellipsoid
TZ (cm3) 18.7 26.7 19.9 24.9 26.6 32.3 19.4 27.1 0.083
Continuous Variable Data of the Study Population

12. Table 1: Shows continued calculated continuous variable data
for the study population.
Non-Diabetic
Patients
(n=881)
Diabetics Prescribed
Metformin
(n=65)
Diabetics Not
Prescribed
Metformin
(n=88)
All Patients
(n=1034)
Median Mean Median Mean Median Mean Median Mean p
PSAD 0.17 0.13 0.11 0.15 0.12 0.15 0.13 0.16 0.577
PSADT (yr) 5.2 7.3 4.8 4.5 5.3 6.6 5.2 7.3 0.771
PSAV
(ng/mL/yr) 0.43 0.81 0.36 0.22 0.48 0.94 0.43 0.82 0.782
BMI (kg/m²) 27.8 28.5 30.5 31.1 29.9 33.4 28.1 29.1 <0.001
# TRUS
biopsies 1 1.2 1 1 1 1.1 1 1.2 0.429
Continuous Variable Data of the Study Population Continued

13. Table 3: Shows calculated categorical variable data for the
study population.
Nondiabetic Patients
(n=881)
Diabetics Prescribed
Metformin (n=65)
Diabetics Not
Prescribed
Metformin (n=88)
All Patients
(n=1034)
Count Percent Count Percent Count Percent Count Percent p
Tobacco 0.015
Never 407 46.8 29 44.6 27 30.7 463 45.3
Former 341 39.3 29 44.6 51 58 421 41.2
Current 121 13.9 7 10.8 10 11.4 138 13.5
Categorical Variable Data of the Study Population

14. Table 4: Shows continued calculated categorical variable data
for the study population.
Nondiabetic
Patients (n=881)
Diabetics Prescribed
Metformin (n=65)
Diabetics Not
Prescribed
Metformin (n=88)
All Patients
(n=1034)
Count Percent Count Percent Count Percent Count Percent p
Hypertension <0.001
Yes 42 47.9 46 70.8 66 75 536 51.8
No 462 52.1 19 29.2 22 25 498 48.2
TURP 0.471
Yes 20 2.3 0 0 2 2.3 22 2.1
No 861 97.7 65 100 86 97.7 1012 97.9
Categorical Variable Data of the Study Population Continued

15. Table 5: Shows calculated continuous variable data for cancer
detected.
Nondiabetic
Patients (n=493)
Diabetics Prescribed
Metformin (n=44)
Diabetics Not
Prescribed
Metformin (n=47) All Patients (n=584)
Median Mean Median Mean Median Mean Median Mean p
# TTMB cores 56 55.4 57 56.1 58 57.3 56 55.6 0.319
# Of positive
TTMB cores 7 9.2 7 9.7 5 8.1 7 9.2 0.238
% Positive
biopsy cores 13 17 12 19 10 15 13 17 0.162
%
Malignancy
involvement 8.1 10.6 7.8 12.1 8.5 9.8 8.1 10.7 0.412
Continuous Variable Data For Cancer Detected

16. Table 6: Shows calculated categorical variable data for cancer
detected.
Nondiabetic
Patients (n=493)
Diabetics Prescribed
Metformin (n=44)
Diabetics Not
Prescribed
Metformin (n=47)
All Patients
(n=584)
Count Percent Count Percent Count Percent Count Percent p
Prostate
cancer
Yes 493 56 44 67.7 47 53.4 584 56.5 0.153
No 388 44 21 32.3 41 46.6 240 41.1
Gleason
score 0.96
1 to 6 203 41.2 17 38.6 19 40.4 239 40.9
7 201 40.8 18 40.9 21 44.7 240 41.1
8 to 9 89 18.1 9 20.5 7 14.9 152 26
Categorical Variable Data For Cancer Detected

17. Table 7: Shows continued calculated continuous variable data
for cancer detected.
Nondiabetic
Patients (n=493)
Diabetics Prescribed
Metformin (n=44)
Diabetics Not
Prescribed
Metformin (n=47)
All Patients
(n=584)
Count Percent Count Percent Count Percent Count Percent p
# Of positive
cores 0.764
1 to 4 188 38.1 14 31.8 18 38.3 220 37.7
5 to 12 174 35.3 19 43.2 19 44.7 212 36.3
> 12 131 26.6 11 25 10 14.9 152 26
Cancer
Symmetry 0.124
Bilateral 173 35.1 22 50 19 40.4 214 36.6
Unilateral 320 64.9 22 50 28 59.6 370 63.4
Categorical Variable Data For Cancer Detected Continued

18. Table 8: Shows continued calculated continuous variable data
for cancer detected.
Nondiabetic
Patients (n=493)
Diabetics Prescribed
Metformin (n=44)
Diabetics Not
Prescribed
Metformin (n=47)
All Patients
(n=584)
Count Percent Count Percent Count Percent Count Percent p
Risk Group 0.877
Very Low 67 13.6 8 18.2 8 17 83 14.2
Low 136 27.6 9 20.5 11 23.4 156 26.7
Intermediate 201 40.8 18 40.9 21 44.7 240 41.1
High 89 18.1 9 20.5 7 14.9 105 18
Categorical Variable Data For Cancer Detected Continued

19. Table 9: Shows univariate and multivariate analysis for
predictors of cancer.
Univariate Multivariate
p RR p RR
Diabetes 0.418
Metformin 0.06
Metformin
duration (yr) 0.725
Age (yr) 0.003 0.006 0.003 0.006
PSA (ng/mL) 0.552
PSADT (yr) 0.732
Predictors of Cancer

20. Table 10: Shows univariate and multivariate analysis for
predictors of cancer continued.
Univariate Multivariate
p RR p RR
PSAV
(ng/mL/yr) 0.385
BMI (kg/m²) 0.262
Hypertension 0.055
Tobacco 0.183
Predictors of Cancer Continued

21. Table 11: Shows univariate and multivariate analysis for
predictors of cancer with a GS ≥7.
Univariate Multivariate
p RR p RR
Diabetes 0.464
Metformin 0.304
Metformin
duration (yr) 0.174
Age (yr) <0.001 0.009 <0.001 0.009
PSA (ng/mL) <0.001 0.01 0.118
Predictors of Gleason Score ≥7

22. Table 12: Shows univariate and multivariate analysis for
predictors of cancer with a GS ≥7 continued.
Univariate Multivariate
p RR p RR
PSADT (yr) 0.21
PSAV
(ng/mL/yr) 0.016 0.009 0.025 0.008
BMI (kg/m²) 0.007 0.004 0.01 0.011
Hypertensi
on 0.023 0.066 0.262
Tobacco 0.093
Predictors of Gleason Score ≥7 Continued

23. In this study metformin did not play a role in prostate cancer diagnosis or
severity
Metformin may reduce cancer occurrence and severity in other types of
cancers by interfering with mTOR pathway (Zakikhani M, et al.)
Prostate cancer cells have a doubling time between 0.6 and 3.6 months
which is 2-25 times faster than normal prostate cells (Werahera, et al.)
Other types of cancer have much faster doubling times
Discussion

24. Table 13: Shows doubling times of certain cancer cell lines.
Where proliferation is doubling time. (Deer, et al.)
Doubling Times of Cancer Cell Lines

25. Strengths of this study include:
Use of TTMB
Allows access to whole prostate gland an more accurate
measurement of cancer development and severity (Taria AV, et
al.)
All biopsies and pathological techniques were administered by only one
individual respectively
Weaknesses of this study include:
Small diabetic patient group
Only white males in sample population
Discussion

26. Discussion
This study conflicts with other studies while coinciding with others
This means there is not a definitive answer on if metformin impacts
prostate cancer
Future directions for more definitive conclusions
Larger sample size with patients of different ethnicities and geographical
locations
Well designed experiment with randomized trial

27. Resources
DeCensi, Andrea, Matteo Puntoni, and Pamela Goodwin. "Metformin and Cancer Risk in Diabetic Patients: A
Systematic Review and Meta-analysis." Metformin and Cancer Risk in Diabetic Patients: A Systematic Review
and Meta-analysis. N.p., 12 Oct. 2010. Web. 11 Sept. 2014.
<http://cancerpreventionresearch.aacrjournals.org/content/3/11/1451.full.pdf+html>.
Deer, Emily L., Jessica González-Hernández, Jill D. Coursen, Jill E. Shea, Josephat Ngatia, Courtney L. Scaife, Matthew A.
Firpo, and Sean J. Mulvihill. "Phenotype And Genotype Of Pancreatic Cancer Cell Lines." Pancreas: 425-35. Web. 20
Mar. 2015.
Gallagher , Emily, Yvonne Fierz, Rosalyn Ferguson, and Derek LeRoith. "Medscape ." Medscape . N.p., n.d. Web. 11
Sept. 2014. <http://www.medscape.com/viewarticle/732476_3>.
Martin-Castillo, Begoña, Alejandro Vazquez-Martin, Cristina Oliveras-Ferraros, and Javier A. Menendez. "Metformin
and cancer: Doses, mechanisms and the dandelion and hormetic phenomena." Cell Cycle 9.6 (2010): 1057-1064.
Print.
Pendick , Daniel. "Harvard Health Publications." Harvard Medical School. N.p., n.d. Web. 11 Sept. 2014.
<http://www.health.harvard.edu/blog/prostate-cancer-lives-as-it-is-born-slow-growing-and-benign-or-fast-growing-and-
dangerous-201308146604>.

28. Resources
"Type 2." American Diabetes Association. N.p., n.d. Web. 11 Sept. 2014.
<http://www.diabetes.org/diabetes-basics/type-2/>.
Violett , Benoit, Bruno Guigas, and Nieves Garcia . "Cellular and molecular mechanisms of metformin: an overview." PMC.
PMC, 18 July 2012. Web. 11 Sept. 2014. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398862/>.
Werahera, Priya N., L. Michael Glode, Francisco G. La Rosa, M. Scott Lucia, E. David Crawford, Kenneth Easterday, Holly T.
Sullivan, Rameshwar S. Sidhu, Elizabeth Genova, and Tammy Hedlund. "Proliferative Tumor Doubling Times of
Prostatic Carcinoma."Prostate Cancer: 1-7. Web. 20 Mar. 2015.
Zakikhani, M., R. Dowling, I. G. Fantus, N. Sonenberg, and M. Pollak. "Metformin Is an AMP Kinase-Dependent
Growth Inhibitor for Breast Cancer Cells." CANCER RESEARCH(2006): 10269-0273. Print.