Annual Meeting Proceedings Part 1 - American Society of Clinical ...

88s Cancer Prevention/Epidemiology
1508 Oral Abstract Session, Mon, 8:00 AM-11:00 AM
Use of PTEN protein dosage to predict for underlying germ-line PTEN
mutations among patients presenting with thyroid cancer and Cowden-like
phenotypes. Presenting Author: Joanne Y. Y. Ngeow, Genomic Medicine
Institute, Cleveland Clinic, Cleveland, OH
Background: Thyroid cancer is a major component of Cowden Syndrome
(CS), a heritable syndrome characterized also by breast, uterine and kidney
cancers. CS patients with an underlying germline PTEN mutation have a
70-fold increased risk of developing epithelial thyroid cancer. In contrast,
�1% of sporadic epithelial thyroid cancer harbor a germline PTEN
mutation. Thus, cost-efficient markers capable of shortlisting thyroid
cancers for CS genetic testing would be clinically useful. Here, we analyzed
the relationship of patient PTEN protein levels in predicting the presence of
germline PTEN mutations. Methods: We conducted a 5-year, multi-center
prospective study of 2792 CS and CS-like patients, all of whom had
comprehensive PTEN analysis done. Analysis of PTEN and downstream
proteins by immunoblotting was performed on total protein lysates from
patient-derived lymphoblast lines. We compared PTEN protein expression
levels between patients with pathogenic PTEN mutations (PTENmut� ), and
those with variants of unknown significance (VUS) or wildtype PTEN. PTEN
immunohistochemistry (IHC) was performed on available thyroid samples.
Results: Of 2792 CS/CS-like patients, 722 had thyroid cancer. PTEN
germline pathogenic mutations were present in 36/722 (5%) patients.
PTEN mut�
cases presented at an earlier age (35 vs 42 years; p�0.02). PTEN
frameshift and truncation mutations accounted for 55% of mutations. 95%
(19/20) of PTENmut� patients had blood-PTEN protein levels in the lowest
quartile as compared to 27% (90/330) of PTEN wildtype/PTEN VUS
patients (p�0.001). Low blood-PTEN levels predicted for PTENmut� cases
with a 99.6 % NPV (95%CI 97.7- 99.9) and a positive test likelihood ratio
of 3.5 (95%CI 2.8-4.3). Affected thyroid tissues (n�22) from PTENmut� cases showed loss of PTEN protein by IHC, correlating with patient blood
PTEN levels (r2�0.30, p�0.016). Conclusions: Our study shows that
PTEN protein dosage could serve as a molecular correlate predicting for
germline PTEN mutation in CS and CS-like presentations of thyroid cancer.
The clinical utility of PTEN IHC in identifying thyroid cancer patients for
germline PTEN testing should be further explored.
1510 Clinical Science Symposium, Sat, 8:00 AM-9:30 AM
Meta-analysis of cancer risk among users of insulin glargine. Presenting
Author: Alice Koechlin, International Prevention Research Institute, Lyon,
France
Background: The association between diabetes, its risk factors and treatments,
and cancer risk and death is now high on the clinical and research
agenda. Methods: All data regarding cancer risk and use of insulin glargine
has been assembled and meta-analyses performed using state-of-the-art
statistical methodology. Glargine is the most studied insulin in this regard.
A random effects model was employed with tests for heterogeneity (I2 ) and
publication bias. These meta-analyses are based on reports from epidemiological
studies involving a total of 907,008 diabetic subjects and 2,597,602
person-years of observation. Results: Based on independent estimates from
14 studies, the Summary Relative Risk (SRR) for all forms of cancer was
(SRR�0.90, 95% CI (0.82, 0.98)) and for breast cancer SRR�1.14 (95%
CI (1.00, 1.29)). For new users of glargine, from 7 studies, the SRR for
breast cancer was SRR�1.20 (95% CI (0.90, 1.58)). Based on independent
estimates for 9 studies, for colorectal cancer the SRR was 0.73 (95%
CI (0.59, 0.91)) and for prostate cancer SRR�1.16 (95% CI (1.03,
1.30)). Overall, the risk of developing cancer among users of insulin
glargine is reduced compared to the risk of users of other insulins.
Similarly, the risk of colorectal cancer is reduced among users of glargine.
While above unity, the risks of breast cancer and prostate cancer are
increased marginally. Potential limitations to this meta-analysis include
that the comparison group was not the same in all studies but this could
also be seen as a strength. This is not likely to invalidate the findings of this
analysis nor would the fact that different adjustments were made in the
individual studies. Conclusions: The current evidence gives no support to
the hypothesis that insulin glargine is associated with an increased risk of
cancer as compared to other insulins and should give reassurance to
physicians and their patients. Given the short exposure time possible to
glargine (less than 5 years maximum), it is not biologically plausible to have
a causal link to common forms of cancer.
1509 Clinical Science Symposium, Sat, 8:00 AM-9:30 AM
Diabetes, related factors, and breast cancer risk. Presenting Author: Peter
Boyle, International Prevention Research Institute, Lyon, France
Background: Diabetes and breast cancer are both common conditions in
women and may share common risk factors. Methods: To shed clarification
on the potential association between diabetes, related factors and breast
cancer risk, a comprehensive literature review and formal meta-analysis
was carried out, planned, conducted and reported following PRISMA
guidelines regarding meta-analysis of observational studies. Variables
studies in relation to breast cancer risk were adiposity, physical activity,
glycaemic load, glycaemic index, diabetes, IGF-1, fasting glucose, fasting
insulin and C-peptide, adiponectin, metformin and glargine use. The
Summary Relative Risk (SRR) and the corresponding 95% Confidence
Interval (CI) was calculated. Results: For breast cancer at all ages, the
calculated risks were as follows: diabetes (SRR�1.23 95% CI (1.12,
1.34); physical activity (SRR�0.88, 95% CI (0.85, 0.92)); glycaemic load
(SRR�1.05, 95% CI (1.00, 1.10)); glycaemic index (SRR�1.05, 95% CI
(1.00, 1.09)); fasting glucose (SRR�1.14, 95% CI (0.94, 1.37)); serum
insulin (SRR�1.26, 95% CI (0.86, 1.84)); c-peptide (SRR�1.29, 95% CI
(0.91, 1.82)); adiponectin (SRR�1.16, 95% CI (0.93, 1.46)); metformin
(SRR�0.97, 95% CI (0.82, 1.16)); and glargine (SRR�1.10, 95% CI
(0.94, 1.30)). An increase of 5 units in Body Mass Index (a weight increase
if 14.5 kg in a person 1.70 metres tall) was associated in post-menopausal
breast cancer (SRR�1.12, 95% CI (1.08, 1.16)) but not at premenopausal
ages (SRR�0.83, 95% CI (0.72, 0.95)). Serum insulin was
associated with breast cancer at post-menopausal ages but not at premenopausal
ages whereas with c-peptide there was a significant association
at pre-menopausal ages but not post-menopausal. For IGF-1, Hodge’s
Standardised Mean Difference (HSMD) was calculated and there was no
significant association with breast cancer at all ages (HSMD�-0.026, 95%
CI (-0.031, 0.084)), at post-menopausal ages (HSMD�0.007, 95% CI
(-0.068, 0.082)) or at pre-menopausal ages (HSMD�-0.065, 95% CI
(-0.009, 0.140)). Conclusions: Key risk factors for breast cancer appear to
be adiposity and physical activity which are both related to the risk of
developing diabetes.
1511 Clinical Science Symposium, Sat, 8:00 AM-9:30 AM
Changes in glucose, insulin, and insulin resistance from presurgery to post
adjuvant treatment for breast cancer. Presenting Author: Emer M. Guinan,
Trinity College Dublin, Dublin, Ireland
Background: Elevated fasting insulin levels at breast cancer diagnosis are
associated with increased risk of recurrence and reduced survival. (Goodwin
PJ, et al. JCO. 2012;30:164-171) Weight gain related to adjuvant
treatment coupled with sedentary activity habits may further alter insulinrelated
measures for breast cancer survivors. We present results from a
prospective longitudinal study examining changes in insulin-related markers
from pre breast cancer surgery to post adjuvant treatment. Methods:
Subjects were recruited from St. James’s hospital, Dublin, Ireland at the
time of breast cancer diagnosis (stage I-III). Fasting pre-surgery blood
samples were drawn to measure insulin, glucose and glycosylated haemoglobin
A1c (HBA1C). Insulin resistance was calculated using the homeostatic
model assessment (HOMA). Subjects with no evidence of active
cancer completed the same measurements 2-5 years later. Paired sample
t-tests were used to measure changes from pre-surgery to post-adjuvant
treatment. Statistical significance was set at P � .05. Results: Forty-four
subjects (n � 22 postmenopausal) completed both measurements (mean
� SD age 54.1�8.6 years). Mean time since diagnosis to follow-up
measures was 3.4�0.8 years. Adjuvant therapy included chemotherapy
(n�37), radiotherapy (n�36), biological therapy (n�8) and concurrent
hormonal therapy (n�37). There was a statistically significant increase in
insulin (mean � SD change 2.8�4.1mU/L, P�.000), insulin resistance
(0.54�1.0, P�.001) and HBA1C (0.1�0.2 %, P� .003). Fasting glucose
levels did not change (P � .06). Conclusions: Results indicate that patients
with breast cancer experience significant increases in insulin, insulin
resistance and HBA1C from pre-surgery to post adjuvant treatment.
Elevated post-treatment insulin levels may further contribute to risk of
breast cancer recurrence and mortality, while also predisposing to the
development of cardiovascular disease and type 2 diabetes mellitus.
Exercise and diet interventions are warranted in this population to improve
markers of insulin resistance as a surrogate for improving breast cancer and
overall health outcomes.
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