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With the advent of high‐throughput sequencing, an efficient computing strategy is required to deal with large genomic data sets. The challenge of estimating a large precision matrix has garnered substantial research attention for its direct application to discriminant analyses and graphical models. Most existing methods either use a lasso‐type penalty that may lead to biased estimators or are computationally intensive, which prevents their applications to very large graphs. We propose using an L0 penalty to estimate an ultra‐large precision matrix (scalnetL0). We apply scalnetL0 to RNA‐seq data from breast cancer patients represented in The Cancer Genome Atlas and find improved accuracy of classifications for survival times. The estimated precision matrix provides information about a large‐scale co‐expression network in breast cancer. Simulation studies demonstrate that scalnetL0 provides more accurate and efficient estimators, yielding shorter CPU time and less Frobenius loss on sparse learning for large‐scale precision matrix estimation. [ABSTRACT FROM AUTHOR]

The analysis of genomics alterations that may occur in nature when segments of chromosomes are copied (known as copy number alterations) has been a focus of research to identify genetic markers of cancer. One high throughput technique that has recently been adopted is the use of molecular inversion probes to measure probe copy number changes. The resulting data consist of high dimensional copy number profiles that can be used to ascertain probe-specific copy number alterations in correlative studies with patient outcomes to guide risk stratification and future treatment. We propose a novel Bayesian variable selection method, the hierarchical structured variable selection method, which accounts for the natural gene and probe-within-gene architecture to identify important genes and probes associated with clinically relevant outcomes. We propose the hierarchical structured variable selection model for grouped variable selection, where simultaneous selection of both groups and within-group variables is of interest. The hierarchical structured variable selection model utilizes a discrete mixture prior distribution for group selection and group-specific Bayesian lasso hierarchies for variable selection within groups. We provide methods for accounting for serial correlations within groups that incorporate Bayesian fused lasso methods for within-group selection. Through simulations we establish that our method results in lower model errors than other methods when a natural grouping structure exists. We apply our method to a molecular inversion probe study of breast cancer and show that it identifies genes and probes that are significantly associated with clinically relevant subtypes of breast cancer. [ABSTRACT FROM AUTHOR]

BACKGROUND: The current study was conducted to determine the frequency and association between recurrence-free survival (RFS) and MET and catalytic subunit of phosphoinositide-3-kinase ( PIK3CA) copy number elevations in patients with early stage breast cancer. METHODS: Tumor DNA was extracted from 971 formalin-fixed, paraffin-embedded early breast cancers for molecular inversion probes arrays. Data were segmented using the single-nucleotide polymorphism (SNP)-FASST2 segmentation algorithm. Copy number gains were called when the copy number of each segment was greater than 2.3 or 1.7, respectively. RFS was estimated by the Kaplan-Meier method. Cox proportional hazards models were fit to determine independent associations between copy number and RFS. RESULTS: Of the 971 tumors studied, 82 (8.44%) and 134 (13.8%) had an elevation of the MET or PIK3CA copy number, respectively, and 25.6% of tumors with a MET copy number elevation had a PIK3CA copy number elevation. Patients with either a MET or PI3KCA high copy number tended to have poorer prognostic features (larger tumor size, higher tumor grade, and hormone receptor negativity). Both MET and PIK3CA high copy numbers were more likely to occur in patients with triple receptor-negative disease ( P = .019 and P < .001, respectively). At a median follow-up of 7.4 years, there were 252 cases of disease recurrence. The 5-year RFS rates were 63.5% and 83.1% for MET high copy number and MET normal/low copy number, respectively ( P = .06) and 73.1%, and 82.3% for PIK3CA high copy number and PIK3CA normal/low copy number, respectively ( P = .15). A high copy number for either gene was not found to be an independent predictor of RFS. CONCLUSIONS: A high copy number of MET or PIK3CA was found to be associated with poorer prognostic features and triple receptor-negative disease. Coamplification was frequent. Patients with tumors with high MET copy numbers tended to have a worse RFS. Cancer 2013. © 2012 American Cancer Society. [ABSTRACT FROM AUTHOR]

A number of studies of copy number imbalances (CNIs) in breast tumors support associations between individual CNIs and patient outcomes. However, no pattern or signature of CNIs has emerged for clinical use. We determined copy number (CN) gains and losses using high-density molecular inversion probe (MIP) arrays for 971 stage I/II breast tumors and applied a boosting strategy to fit hazards models for CN and recurrence, treating chromosomal segments in a dose-specific fashion (-1 [loss], 0 [no change] and +1 [gain]). The concordance index (C-Index) was used to compare prognostic accuracy between a training (n = 728) and test (n = 243) set and across models. Twelve novel prognostic CNIs were identified: losses at 1p12, 12q13.13, 13q12.3, 22q11, and Xp21, and gains at 2p11.1, 3q13.12, 10p11.21, 10q23.1, 11p15, 14q13.2-q13.3, and 17q21.33. In addition, seven CNIs previously implicated as prognostic markers were selected: losses at 8p22 and 16p11.2 and gains at 10p13, 11q13.5, 12p13, 20q13, and Xq28. For all breast cancers combined, the final full model including 19 CNIs, clinical covariates, and tumor marker-approximated subtypes (estrogen receptor [ER], progesterone receptor, ERBB2 amplification, and Ki67) significantly outperformed a model containing only clinical covariates and tumor subtypes (C-Index full model, train[test] = 0.72[0.71] ±0.02 vs. C-Indexclinical + subtype model, train[test] = 0.62[0.62] ±0.02; p<10-6). In addition, the full model containing 19 CNIs significantly improved prognostication separately for ER-, HER2+, luminal B, and triple negative tumors over clinical variables alone. In summary, we show that a set of 19 CNIs discriminates risk of recurrence among earlystage breast tumors, independent of ER status. Further, our data suggest the presence of specific CNIs that promote and, in some cases, limit tumor spread. [ABSTRACT FROM AUTHOR]

Background: The PI3K/AKT pathway is activated through PIK3CA or AKT1 mutations and PTEN loss in breast cancer. We conducted a phase II trial with an allosteric AKT inhibitor MK-2206 in patients with advanced breast cancer who had tumors with PIK3CA/AKT1 mutations and/or PTEN loss/mutation.Methods: The primary endpoint was objective response rate (ORR). Secondary endpoints were 6-month progression-free survival (6 m PFS), predictive and pharmacodynamic markers, safety, and tolerability. Patients had pre-treatment and on-treatment biopsies as well as collection of peripheral blood mononuclear cells (PBMC) and platelet-rich plasma (PRP). Next-generation sequencing, immunohistochemistry, and reverse phase protein arrays (RPPA) were performed.Results: Twenty-seven patients received MK-2206. Eighteen patients were enrolled into the PIK3CA/AKT1 mutation arm (cohort A): 13 had PIK3CA mutations, four had AKT1 mutations, and one had a PIK3CA mutation as well as PTEN loss. ORR and 6 m PFS were both 5.6% (1/18), with one patient with HR+ breast cancer and a PIK3CA E542K mutation experiencing a partial response (on treatment for 36 weeks). Nine patients were enrolled on the PTEN loss/mutation arm (cohort B). ORR was 0% and 6 m PFS was 11% (1/9), observed in a patient with triple-negative breast cancer and PTEN loss. The study was stopped early due to futility. The most common adverse events were fatigue (48%) and rash (44%). On pre-treatment biopsy, PIK3CA and AKT1 mutation status was concordant with archival tissue testing. However, two patients with PTEN loss based on archival testing had PTEN expression on the pre-treatment biopsy. MK-2206 treatment was associated with a significant decline in pAKT S473 and pAKT T308 and PI3K activation score in PBMC and PRPs, but not in tumor biopsies. By IHC, there was no significant decrease in median pAKT S473 or Ki-67 staining, but a drop was observed in both responders.Conclusions: MK-2206 monotherapy had limited clinical activity in advanced breast cancer patients selected for PIK3CA/AKT1 or PTEN mutations or PTEN loss. This may, in part, be due to inadequate target inhibition at tolerable doses in heavily pre-treated patients with pathway activation, as well as tumor heterogeneity and evolution in markers such as PTEN conferring challenges in patient selection.Trial Registration: ClinicalTrials.gov, NCT01277757 . Registered 13 January 2011. [ABSTRACT FROM AUTHOR]

We conducted a study in Egypt to assess the determinants of organochlorine serum levels among premenopausal women and the risk of premenopausal breast cancer for women with high organochlorine serum levels. We included 69 breast cancer patients and 53 controls consisting of visitors to the hospitals of the cancer patients. We found low levels of dichlorodiphenyldichloroethylene (DDE), total dichlorodiphenyltrichloroethane, and β-hexacholorhexane (β-HCH) in most subjects. Mean DDE levels were 12.7±20.3 ppb for cases and 16.6±30.1 ppb for controls (P=0.60); β-HCH levels were 2.1±3.8 ppb for patients and 2.1±3.9 ppb for controls (P=0.71). Interestingly, subjects with low levels had breast fed their children for an average period of 18 months. Women with no lactation history had much higher organochlorine levels than women who breast fed (P=0.002 for DDE). Younger age, older age at first childbirth, and shorter duration of breast feeding were significant predictors of higher levels of serum DDE levels. Younger age, older age at first childbirth, and higher body mass index were significant predictors of higher β-HCH levels. This study suggests that organochlorine serum levels in Egyptian women are quite low, but indicates an effect of breast feeding in eliminating organochlorines, which would imply exposure to children. Organochlorine serum level was not a risk factor of breast cancer in this population. [Copyright &y& Elsevier]