Effects of cardiovascular lifestyle change on lipoprotein subclass profiles defined by nuclear magnetic resonance spectroscopy.

BACKGROUND: Low-density lipoprotein (LDL) cholesterol lowering is a primary goal in clinical management of patients with cardiovascular disease, but traditional cholesterol levels may not accurately reflect the true atherogenicity of plasma lipid profiles. The size and concentration of lipoprotein particles, which transport cholesterol and triglycerides, may provide additional information for accurately assessing cardiovascular risk. This study evaluated changes in plasma lipoprotein profiles determined by nuclear magnetic resonance (NMR) spectroscopy in patients participating in a prospective, nonrandomized lifestyle modification program designed to reverse or stabilize progression of coronary artery disease (CAD) to improve our understanding of lipoprotein management in cardiac patients. RESULTS: The lifestyle intervention was effective in producing significant changes in lipoprotein subclasses that contribute to CAD risk. There was a clear beneficial effect on the total number of LDL particles (-8.3%, p < 0.05 compared to matched controls), small dense LDL particles (-9.5%, p < 0.05), and LDL particle size (+0.8%; p < 0.05). Likewise, participants showed significant improvement in traditional CAD risk factors such as body mass index (-9.9%, p < 0.01 compared to controls), total cholesterol (-5.5%, p < 0.05), physical fitness (+37.2%, p < 0.01), and future risk for CAD (-7.9%, p < 0.01). Men and women responded differently to the program for all clinically-relevant variables, with men deriving greater benefit in terms of lipoprotein atherogenicity. Plasma lipid and lipoprotein responses to the lifestyle change program were not confounded by lipid-lowering medications. CONCLUSION: In at risk patients motivated to participate, an intensive lifestyle change program can effectively alter traditional CAD risk factors and plasma lipoprotein subclasses and may reduce risk for cardiovascular events. Improvements in lipoprotein subclasses are more evident in men compared to women.

Amplification of HER2 is a marker for global genomic instability.

BACKGROUND: Genomic alterations of the proto-oncogene c-erbB-2 (HER-2/neu) are associated with aggressive behavior and poor prognosis in patients with breast cancer. The variable clinical outcomes seen in patients with similar HER2 status, given similar treatments, suggests that the effects of amplification of HER2 can be influenced by other genetic changes. To assess the broader genomic implications of structural changes at the HER2 locus, we investigated relationships between genomic instability and HER2 status in patients with invasive breast cancer. METHODS: HER2 status was determined using the PathVysion assay. DNA was extracted after laser microdissection from the 181 paraffin-embedded HER2 amplified (n=39) or HER2 negative (n=142) tumor specimens with sufficient tumor available to perform molecular analysis. Allelic imbalance (AI) was assessed using a panel of microsatellite markers representing 26 chromosomal regions commonly altered in breast cancer. Student t-tests and partial correlations were used to investigate relationships between genomic instability and HER2 status. RESULTS: The frequency of AI was significantly higher (P<0.005) in HER2 amplified (27%) compared to HER2 negative tumors (19%). Samples with HER2 amplification showed significantly higher levels of AI (P<0.05) at chromosomes 11q23, 16q22-q24 and 18q21. Partial correlations including ER status and tumor grade supported associations between HER2 status and alterations at 11q13.1, 16q22-q24 and 18q21. CONCLUSION: The poor prognosis associated with HER2 amplification may be attributed to global genomic instability as cells with high frequencies of chromosomal alterations have been associated with increased cellular proliferation and aggressive behavior. In addition, high levels of DNA damage may render tumor cells refractory to treatment. In addition, specific alterations at chromosomes 11q13, 16q22-q24, and 18q21, all of which have been associated with aggressive tumor behavior, may serve as genetic modifiers to HER2 amplification. These data not only improve our understanding of HER in breast pathogenesis but may allow more accurate risk profiles and better treatment options to be developed.

Performance of whole-genome amplified DNA isolated from serum and plasma on high-density single nucleotide polymorphism arrays.

Defining genetic variation associated with complex human diseases requires standards based on high-quality DNA from well-characterized patients. With the development of robust technologies for whole-genome amplification, sample repositories such as serum banks now represent a potentially valuable source of DNA for both genomic studies and clinical diagnostics. We assessed the performance of whole-genome amplified DNA (wgaDNA) derived from stored serum/plasma on high-density single nucleotide polymorphism arrays. Neither storage time nor usage history affected either DNA extraction or whole-genome amplification yields; however, samples that were thawed and refrozen showed significantly lower call rates (73.9 +/- 7.8%) than samples that were never thawed (92.0 +/- 3.3%) (P < 0.001). Genotype call rates did not differ significantly (P = 0.13) between wgaDNA from never-thawed serum/plasma (92.9 +/- 2.6%) and genomic DNA (97.5 +/- 0.3%) isolated from whole blood. Approximately 400,000 genotypes were consistent between wgaDNA and genomic DNA, but the overall discordance rate of 4.4 +/- 3.8% reflected an average of 11,110 +/- 9502 genotyping errors per sample. No distinct patterns of chromosomal clustering were observed for single nucleotide polymorphisms showing discordant genotypes or homozygote conversion. Because the effects of genotyping errors on whole-genome studies are not well defined, we recommend caution when applying wgaDNA from serum/plasma to high-density single nucleotide polymorphism arrays in addition to the use of stringent quality control requirements for the resulting genotype data.

Genomic alterations associated with early stages of breast tumor metastasis.

BACKGROUND: Molecular studies suggest that acquisition of metastatic potential occurs early in the development of breast cancer; mechanisms by which cells disseminate from the primary carcinomas and successfully colonize foreign tissues are, however, largely unknown. Thus, we examined levels and patterns of chromosomal alterations in primary breast tumors from node-negative (n = 114) and node-positive (n = 115) patients to determine whether specific genomic changes are associated with tumor metastasis. METHODS: Fifty-two genetic markers representing 26 chromosomal regions commonly altered in breast cancer were examined in laser microdissected tumor samples to assess levels and patterns of allelic imbalance (AI). Real time-PCR (RT-PCR) was performed to determine expression levels of candidate genes. Data was analyzed using exact unconditional and Student's t-tests with significance values of P < 0.05 and P < 0.002 used for the clinicopathological and genomic analyses, respectively. RESULTS: Overall levels of AI in primary breast tumors from node-negative (20.8%) and node-positive (21.9%) patients did not differ significantly (P = 0.291). When data were examined by chromosomal region, only chromosome 8q24 showed significantly higher levels (P < 0.0005) of AI in node-positive primary tumors (23%) versus node-negative samples (6%). c-MYC showed significantly higher levels of gene expression in primary breast tumors from patients with lymph node metastasis. CONCLUSIONS: Higher frequencies of AI at chromosome 8q24 in patients with positive lymph nodes suggest that genetic changes in this region are important to the process of metastasis. Because overexpression of c-MYC has been associated with cellular dissemination as well as development of the premetastatic niche, alterations of the 8q24 region, including c-MYC, may be key determinants in the development of lymph node metastasis.

The genomic heritage of lymph node metastases: implications for clinical management of patients with breast cancer.

BACKGROUND: Metastatic breast cancer is an aggressive disease associated with recurrence and decreased survival. To improve outcomes and develop more effective treatment strategies for patients with breast cancer, it is important to understand the molecular mechanisms underlying metastasis. METHODS: We used allelic imbalance (AI) to determine the molecular heritage of primary breast tumors and corresponding metastases to the axillary lymph nodes. Paraffin-embedded samples from primary breast tumors and matched metastases (n = 146) were collected from 26 patients with node-positive breast cancer involving multiple axillary nodes. Hierarchical clustering was used to assess overall differences in the patterns of AI, and phylogenetic analysis inferred the molecular heritage of axillary lymph node metastases. RESULTS: Overall frequencies of AI were significantly higher (P < 0.01) in primary breast tumors (23%) than in lymph node metastases (15%), and there was a high degree of discordance in patterns of AI between primary breast carcinomas and the metastases. Metastatic tumors in the axillary nodes showed different patterns of chromosomal changes, suggesting that multiple molecular mechanisms may govern the process of metastasis in individual patients. Some metastases progressed with few genomic alterations, while others harbored many chromosomal alterations present in the primary tumor. CONCLUSIONS: The extent of genomic heterogeneity in axillary lymph node metastases differs markedly among individual patients. Genomic diversity may be associated with response to adjuvant therapy, recurrence, and survival, and thus may be important in improving clinical management of breast cancer patients.

Correlation of levels and patterns of genomic instability with histological grading of invasive breast tumors.

Pathological grade is a useful prognostic factor for stratifying breast cancer patients into favorable (well-differentiated tumors) and less favorable (poorly-differentiated tumors) outcome groups. The current system of tumor grading, however, is subjective and a large proportion of tumors are characterized as intermediate-grade tumors, making determination of optimal treatments difficult. To determine whether molecular profiles can discriminate breast disease by grade, patterns and levels of allelic imbalance (AI) at 26 chromosomal regions frequently altered in breast disease were examined in 185 laser microdissected specimens representing well-differentiated (grade 1; n = 55), moderately-differentiated (grade 2; n = 71), and poorly-differentiated (grade 3; n = 59) stage I-IV breast tumors. Overall levels of AI were significantly higher in grade 3 compared to grade 1 tumors (P < 0.05). Grades 1 and 3 showed distinct genetic profiles--grade 1 tumors were associated with large deletions of chromosome 16q22, while alterations at 9p21, 11q23, 13q14, 17p13.1 and 17q12 were characteristics of grade 3 carcinomas. In general, levels and patterns of AI in grade 2 carcinomas were intermediate between grade 1 and grade 3 tumors. Patterns of AI accurately categorized approximately 70% of samples into high- or low-grade disease groups, suggesting that the majority of breast tumors have genetic profiles consistent with high- or low-grade, and that molecular signatures of breast tumors can be useful for more accurate characterization of invasive breast cancer.

Correlation of levels and patterns of genomic instability with histological grading of DCIS.

BACKGROUND: Histological grading of ductal carcinoma-in-situ (DCIS) lesions separates DCIS into three subgroups (well-, moderately, or poorly differentiated). It is unclear, however, whether breast disease progresses along a histological continuum or whether each grade represents a separate disease. In this study, levels and patterns of allelic imbalance (AI) were examined in DCIS lesions to develop molecular models that can distinguish pathological classifications of DCIS. METHODS: Laser microdissected DNA samples were collected from DCIS lesions characterized by a single pathologist including well- (n = 18), moderately (n = 35), and poorly differentiated (n = 47) lesions. A panel of 52 microsatellite markers representing 26 chromosomal regions commonly altered in breast cancer was used to assess patterns of AI. RESULTS: The overall frequency of AI increased significantly (P < .001) with increasing grade (well differentiated, 12%; moderately differentiated, 17%; poorly differentiated, 26%). Levels of AI were not significantly different between well- and moderately differentiated grades of disease but were significantly higher (P < .0001) in poorly differentiated compared with well- or moderately differentiated disease. No statistically significant differences in patterns of AI were detected between well- and moderately differentiated disease; however, AI occurred significantly more frequently (P < .05) in high-grade lesions at chromosomes 6q25-q27, 8q24, 9p21, 13q14, and 17p13.1, and significantly more frequently in low-grade lesions at chromosome 16q22.3-q24.3. CONCLUSIONS: The inability to discriminate DCIS at the genetic level suggests that grades 1 and 2 DCIS may represent a single, non-high-grade form of DCIS, whereas poorly differentiated DCIS seems to be a genetically more advanced disease that may represent a discrete disease entity, characterized by a unique spectrum of genetic alterations.