Pankratz, V. Shane

BackgroundThe six domain standard Clinical Dementia Rating Scale (CDRstd) has been successful for staging patients with the clinical syndrome of probable Alzheimer's disease (AD). The CDRstd does not specifically address language dysfunction or alteration in personality and social behaviors which are prominent in behavioral variant frontotemporal dementia (bvFTD) and primary progressive aphasia (PPA).ObjectiveTo determine the value of adding domains of Language (LANG), and Behavior, Comportment, and Personality (BEHAV) to the CDRstd for the evaluation of patients with bvFTD and PPA.MethodsTwo new domains, LANG and BEHAV, were constructed to parallel the six domains sampled in the CDRstd. Clinical and neuropsychological test data were obtained from the National Alzheimer's Coordinating Center. The dataset contained information on 2550 probable AD, 88 vascular dementia, 281 dementia with Lewy body, 234 bvFTD, and 137 PPA patients.ResultsThere were 76.5% of bvFTD and 99.3% of PPA patients with abnormal ratings (>0) on the LANG domain; 90.2% of bvFTD and 63.5% of PPA had abnormal ratings on the BEHAV domain. In patients with a CDRstd sum of boxes score of <4, 53.7% of bvFTD had BEHAV domain and 78.6% of PPA patients had LANG domain scores >1. Among probable AD patients, 3.7% had LANG ratings that were ≥1 and 3.8% had BEHAV ratings that were ≥1. Logistic regression analyses showed that adding either the LANG or BEHAV domains to the CDRstd sum of boxes score significantly improved the discrimination between probable AD, bvFTD, and PPA.ConclusionsThe new LANG and BEHAV domains add value to the CDRstd for the characterization of the nonamnestic symptoms that are prominent in patients with bvFTD and PPA but that also occur in those with probable AD.

Abstract Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-186.

Abstract INTRODUCTION: The centrosome is the primary microtubule organizing center of the cell. Numerical or functional defects of the centrosome can result in improper chromosome segregation, leading to aneuploidy and polyploidy. Because many cancer cells have aberrant numbers of chromosomes, many have suggested a link between centrosomes and cancer. We conducted an association study to determine whether common genetic variations in 100 genes involved in maintaining and regulating centrosome structure and function account in part for the contribution of the pathway to breast cancer risk. METHODS: Incident cases of BC were identified at the Mayo Clinic in Rochester, MN from 2001 through 2005. Controls (N=843) were frequency matched to cases (N=798) on age and region of residence. Seven hundred-eighty-two tagging and candidate functional SNPs were selected from 100 genes involved in the structure and/or function of the centrosome. Genotyping was performed on an Illumina BeadLab using the Illumina GoldenGate genotyping assay. Logistic regression was used to calculate odds ratios and 95% confidence intervals for BC. Women having two copies of the most common allele were defined as the referent category. Linear regression was used to estimate mean and 95% CI for PD for each additional copy of the variant allele. All models were adjusted for age, residence, and confounding factors. RESULTS: Forty-eight SNPs from 29 genes (out of 782 SNPs examined) showed evidence of significant associations with breast cancer risk in our population in the log-additive (1 degree of freedom (d.f.)) model (Ptrend&lt; 0.05). One SNP, rs1374468 SNP in TACC3, displayed the most significant association with risk in the overall analyses (Ptrend = 0.001). Two SNPs from each of seven genes (AJUBA, CHUK, MCPH1, NEK7, PAK1, PIK3CB, and PINS) were significantly associated with risk of breast cancer (Ptrend &lt; 0.05). Three genes, AXIN2, NIN, NUMA1, had four or more SNPs that were significantly associated with breast cancer risk (Ptrend &lt; 0.05). All of the SNPs in these four genes were in strong linkage disequilibrium (r2&gt;0.6). No single SNP association was significant after adjustment for multiple comparisons via permutation testing. Haplotype analyses showed 20 genes for which global haplotypes were significantly associated with breast cancer risk. Of these, haplotype blocks in six genes (14-3-3 Epsilon, CDC16, CD-TOG, KIF2, NEK9, NPM2) were significantly associated with risk (global P&lt;0.05), although none of the individual SNPs in these six genes displayed significant associations. This suggests that the associations of these specific combinations of alleles with risk were not due to the effects of individual SNPs. CONCLUSION: These analyses provide some evidence to support an association between genetic variation in centrosomal genes and risk of breast cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2852.

Abstract Introduction: Mammographic breast density is one of the strongest risk factors for breast cancer and appears to be modifiable. However, whether longitudinal changes in density are associated with breast cancer risk is unknown. We hypothesize that decreases in breast density are associated with reduced breast cancer risk. Methods: The Mayo Mammography Health Study cohort enrolled 19,924 women having a screening mammogram (mgm) at the Mayo Clinic, Rochester, between 2003 and 2006. Participants were 35 years and older, had no prior breast cancer and lived in the tri-state area (MN, IA and WI). Risk factor data were collected through self-administered questionnaire and clinic databases. Incident breast cancers were identified through tumor registries (Mayo Clinic, MN, IA, WI). The BI-RADS, 4-category clinical density measure (fatty, scattered density, heterogeneous density and extreme density) was available on all mgms performed after 1996. A case-cohort design consisting of incident cases (n=241) and a random selection of the cohort (n=2300, 28 developed cancer) was used to examine the association between change in BI-RADS density and breast cancer. BI-RADS densities measured from the earliest available, and enrollment mgms (average 6 years apart) were used to assess density change. Proportional hazards regression was performed to estimate the hazard ratio (HR) associated with a change in one or more BI-RADS density categories over time, relative to staying within the same category. Age was used as the time scale, and the subcohort was weighted by the inverse of the sampling proportion. Analyses were adjusted for age, years between mgms, BI-RADS density at earliest mgm, and changes in BMI, postmenopausal hormone use, and menopausal status. Results: Longitudinal analyses were conducted on the 219 cases and 1900 non-cases in the subcohort with at least one mgm available prior to enrollment mgm. Compared to the subcohort, cases were older (56.8 vs. 52.9 years), more likely postmenopausal (73.4% vs. 61.6%), had higher BMI (29.0 vs 28.1) and were more frequently screened (8.0 vs. 6.9 pre-enrollment mgms). As expected, cases were more likely to have extreme density (BI-RADS=4) at earliest mgm than non-cases (16.2% vs 14.3%). Cases were less likely than non-cases to experience a reduction of one density category or more (37.0% vs 38.6%) following earliest mgm. Adjusting for potential confounders, women who decreased one BI-RADS category or more over an average 6 years were at reduced risk of breast cancer (HR=0.72, 95%CI: 0.50-0.99) compared to those whose density was unchanged. However, women who increased one or more BI-RADS categories had suggestion of increased risk (HR=1.52, 95%CI: 0.97-2.4). Conclusion: Women with a decrease in BI-RADS density category over 6 years may have decreased breast cancer risk relative to women whose breast density category remains stable. Two measures of breast density may inform women's risk beyond a measure at one point in time. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4828.

Abstract Background: Epithelial proliferation in benign breast disease (BBD) is a well-established biomarker of breast cancer risk, and BBD tissues can be used as a platform to assess other biomarkers for breast cancer risk. Lobular involution (the degree of age-related atrophy in lobules) is a new biomarker, with greater degrees of involution associated with lower breast cancer risk. Successful application of tissue biomarkers of risk to breast tissues from normal women would be valuable for risk prediction in the general population. We hypothesized that normal breast tissue samples would differ from BBD tissues in these histologic features of breast cancer risk, with less epithelial proliferation but a similar degree of involution compared to BBD tissues. Methods: Core biopsy samples from the Mayo Benign Breast Disease Cohort Study were compared to core biopsy samples of normal breast tissue obtained from the Susan G. Komen for the Cure Tissue Bank at IU Simon Cancer Center (KTB), a unique resource of breast tissue from donor women without any known breast abnormalities. All core biopsies were assessed histologically by a single breast pathologist for degree of epithelial proliferation (classified as non-proliferative, proliferative without atypia, or atypical hyperplasia) and extent of lobular involution (classified as none, 1-24%, 25-74%, or &gt;75% of lobules). Data were analyzed using chi-square tests and logistic regression. Results: Overall, 318 Mayo BBD and 303 normal (KTB) core breast biopsy samples were evaluated. As anticipated, significantly less epithelial proliferation was present in normal samples compared to BBD samples. Proliferative disease occurred in 9/303 (3%) of normals versus 79/318 (25%) of BBD, and atypical hyperplasia was seen in 2/303 (0.7%) of normal samples versus 24/318 (8%) of BBD core biopsies, p &lt; 0.0001. This difference remained significant after adjusting for age (which was greater overall in the BBD samples). Complete involution was more frequent in normal compared to BBD tissues, although the difference did not reach statistical significance. The age-adjusted odds ratio of complete involution in normal versus BBD tissues was 1.46 (95% CI 0.98-2.17, p = 0.06), suggesting a possible delay or failure of involution in women with BBD. Conclusions: Histologic features of normal breast tissues are different from those of BBD tissues, with less epithelial proliferation and more lobular involution, consistent with a lower risk of breast cancer expected for women with normal breast tissue compared to those with benign breast disease. Normal breast tissues are a valuable and distinct resource that should be considered for biomarker validation studies. Citation Information: Cancer Prev Res 2010;3(12 Suppl):B23.

Abstract Background: Risk prediction models are important clinical tools for counseling and decision making for women with an elevated risk of breast cancer, such as women with atypical lobular or ductal hyperplasia (atypia). The Gail model has been shown to underestimate the risk of breast cancer in women with atypia. We sought to evaluate the performance of the Tyrer-Cuzick model in a well-defined cohort of women with atypia.Methods: The Mayo Benign Breast Disease (BBD) Cohort includes 9,376 women aged 18 to 85 who had an open breast biopsy with benign pathological findings between 1967 and 1991. The subset of women with atypia was identified by our study pathologists. Risk factor data required by the Tyrer-Cuzick model were collated for each woman, and the model was used to predict each woman's risk of developing invasive breast cancer within ten years. The predicted numbers of breast cancers were compared to the observed numbers to assess overall model calibration, and the concordance between breast cancer outcomes and predicted probabilities was used to measure the accuracy of the model on the individual level. Subset analysis of women with strong family history was performed. Strong family history was defined as: at least one first-degree relative with breast cancer before the age of 50 years or two or more relatives with breast cancer, at least one being a first degree relative.Results: Three hundred and thirty one women with atypia were identified. Over a mean follow up of 13.7 years, 62 (19%) women have developed invasive breast cancer. Thirty one women developed invasive cancer in the first ten years after biopsy. The Tyrer-Cuzick model predicted that 64.6 invasive breast cancers would occur in the first ten years after biopsy. Thus, the predicted to observed ratio was 2.08 [95% CI: 1.47 – 2.96], p &lt; 0.001).The concordance statistic was 0.51, revealing that the Tyrer-Cuzick model did not accurately distinguish, on an individual level, between women who were diagnosed with invasive breast cancer within ten years of biopsy and those who were not.Performance was somewhat better in the subset of 68 women with a strong family history of breast cancer. The model predicted 12.3 invasive breast cancers, and 7 were observed, for a predicted to observed ratio of 1.76 [95% CI: 0.84 – 3.70]. The concordance statistic was 0.57.Conclusion: The Tyrer-Cuzick model significantly overestimated the risk of breast cancer in the first ten years after biopsy for this group of women with atypia. Individual risk estimates showed poor concordance. Performance was slightly improved in women with a strong family history of breast cancer. Physicians should be cautious when using the Tyrer-Cuzick model to predict ten-year risk in patients with atypia. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6063.