Meta-analysis of breast cancer risk for individuals with PALB2 pathogenic variants.

Multigene panel testing now allows efficient testing of many cancer susceptibility genes leading to a larger number of mutation carriers being identified. They need to be counseled about their cancer risk conferred by the specific gene mutation. An important cancer susceptibility gene is PALB2. Multiple studies reported risk estimates for breast cancer (BC) conferred by pathogenic variants in PALB2. Due to the diverse modalities of reported risk estimates (age-specific risk, odds ratio, relative risk, and standardized incidence ratio) and effect sizes, a meta-analysis combining these estimates is necessary to accurately counsel patients with this mutation. However, this is not trivial due to heterogeneity of studies in terms of study design and risk measure. We utilized a recently proposed Bayesian random-effects meta-analysis method that can synthesize estimates from such heterogeneous studies. We applied this method to combine estimates from 12 studies on BC risk for carriers of pathogenic PALB2 mutations. The estimated overall (meta-analysis-based) risk of BC is 12.80% (6.11%-22.59%) by age 50 and 48.47% (36.05%-61.74%) by age 80. Pathogenic mutations in PALB2 makes women more susceptible to BC. Our risk estimates can help clinically manage patients carrying pathogenic variants in PALB2.

Rejoinder to the discussion on "Bayesian meta-analysis of penetrance for cancer risk".

The five discussions of our paper provide several modeling alternatives, extensions, and generalizations that can potentially guide future research in meta-analysis. In this rejoinder, we briefly summarize and comment on some of those points.

Bayesian meta-analysis of penetrance for cancer risk.

Multi-gene panel testing allows many cancer susceptibility genes to be tested quickly at a lower cost making such testing accessible to a broader population. Thus, more patients carrying pathogenic germline mutations in various cancer-susceptibility genes are being identified. This creates a great opportunity, as well as an urgent need, to counsel these patients about appropriate risk-reducing management strategies. Counseling hinges on accurate estimates of age-specific risks of developing various cancers associated with mutations in a specific gene, ie, penetrance estimation. We propose a meta-analysis approach based on a Bayesian hierarchical random-effects model to obtain penetrance estimates by integrating studies reporting different types of risk measures (eg, penetrance, relative risk, odds ratio) while accounting for the associated uncertainties. After estimating posterior distributions of the parameters via a Markov chain Monte Carlo algorithm, we estimate penetrance and credible intervals. We investigate the proposed method and compare with an existing approach via simulations based on studies reporting risks for two moderate-risk breast cancer susceptibility genes, ATM and PALB2. Our proposed method is far superior in terms of coverage probability of credible intervals and mean square error of estimates. Finally, we apply our method to estimate the penetrance of breast cancer among carriers of pathogenic mutations in the ATM gene.

Advances in the Delivery and Development of Epigenetic Therapeutics for the Treatment of Cancer.

Gene expression at the transcriptional level is altered by epigenetic modifications such as DNA methylation, histone methylation, and acetylation, which can upregulate, downregulate, or entirely silence genes. Pathological dysregulation of epigenetic processes can result in the development of cancer, neurological problems, metabolic disorders, and cardiovascular diseases. It is of promising therapeutic interest to find medications that target these epigenetic alterations. Despite the enormous amount of work that has been done in this area, very few molecules have been approved for clinical purposes. This article provides a comprehensive review of recent advances in epigenetic therapeutics for cancer, with a specific focus on emerging delivery and development strategies. Various delivery systems, including pro-drugs, conjugated molecules, nanoparticles (NPs), and liposomes, as well as remedial strategies such as combination therapies, and epigenetic editing, are being investigated to improve the efficacy and specificity of epigenetic drugs (epi-drugs). Furthermore, the challenges associated with available epi-drugs and the limitations of their translation into clinics have been discussed. Target selection, isoform selectivity, physiochemical properties of synthesized molecules, drug screening, and scalability of epi-drugs from preclinical to clinical fields are the major shortcomings that are addressed. This Review discusses novel strategies for the identification of new biomarkers, exploration of the medicinal chemistry of epigenetic modifiers, optimization of the dosage regimen, and design of proper clinical trials that will lead to better utilization of epigenetic modifiers over conventional therapies. The integration of these approaches holds great potential for improving the efficacy and precision of epigenetic treatments, ultimately benefiting cancer patients.

Dual-Drug-Loaded Topical Delivery of Photodynamically Active Lipid-Based Formulation for Combination Therapy of Cutaneous Melanoma.

Topical administration of anti-cancer drugs along with photodynamically active molecules is a non-invasive approach, which stands to be a promising modality for treating aggressive cutaneous melanomas with the added advantage of high patient compliance. However, the efficiency of delivering drugs topically is limited by several factors, such as penetration of the drug across skin layers at the tumor site and limited light penetrability. In this study, curcumin, an active anti-cancer agent, and chlorin e6, a photoactivable molecule, were encapsulated into lipidic nanoparticles that produced reactive oxygen species (ROS) when activated at 665 nm by near-infrared (NIR) light. The optimized lipidic nanoparticle containing curcumin and chlorin e6 exhibited a particle size of less than 100 nm. The entrapment efficiency for both molecules was found to be 81%. The therapeutic efficacy of the developed formulation was tested on B16F10 and A431 cell lines via cytotoxicity evaluation, combination index, cellular uptake, nuclear staining, DNA fragmentation, ROS generation, apoptosis, and cell cycle assays under NIR irradiation (665 nm). Co-delivering curcumin and chlorin e6 exhibited higher cellular uptake, better cancer growth inhibition, and pronounced apoptotic events compared to the formulation having the free drug alone. The study results depicted that topical application of this ROS-generating dual-drug-loaded lipidic nanoparticles incorporated in SEPINEO gel achieved better permeation (80 ± 2.45%) across the skin, and exhibited the improved skin retention and a synergistic effect as well. The present work introduces photo-triggered ROS-generating dual-drug-based lipidic nanoparticles, which are simple and efficient to develop and exhibit synergistic therapeutic effects against cutaneous melanoma.

Bivalent dopamine agonists with co-operative binding and functional activities at dopamine D2 receptors, modulate aggregation and toxicity of alpha synuclein protein.

To follow up on our previous report on bivalent compounds exhibiting potent co-operative binding at dopamine D2 receptors, we modified the structure of the linker in our earlier bivalent molecules (S)-6-((9-(((R)-5-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)(propyl)amino)nonyl)-(propyl)amino)-5,6,7,8-tetrahydronaphthalen-1-ol (Ia) and (S)-6-((10-(((R)-5-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)(propyl)amino)decyl)(propyl)amino)-5,6,7,8-tetrahydronaphthalen-1-ol (Ib) (Fig. 1) connecting the two pharmaophoric moieties to observe any tolerance in maintaining similar affinities and potencies. Specifically, we introduced aromatic and piperazine moieties in the linker to explore their effect. Overall, similar activities at D2 receptors as observed in our earlier study was maintained in the new molecules e.g. (6S,6'S)-6,6'-((1,4-phenylenebis(ethane-2,1-diyl))bis(propylazanediyl))bis(5,6,7,8-tetrahydronaphthalen-1-ol) (D-382) (Ki, D2 = 3.88 nM). The aromatic moiety in D-382 was next functionalized by introducing hydroxyl groups to mimic polyhydroxy natural products which are known to interact with amyloidogenic proteins. Such a transformation resulted in development of compounds like 2,5-bis(2-(((S)-5-hydroxy-1,2,3,4-tetrahydronaphthalen-2-yl)(propyl)amino)ethyl)benzene-1,4-diol (D-666) (Ki, D2 = 7.62 nM) which retained similar affinity and potency at D2 receptors. Such dihydroxyl compounds turned out to be potent inhibitors against aggregation and toxicity of recombinant alpha synuclein protein. The work reported here is in line with our overall goal to develop multifunctional dopamine agonist for symptomatic and disease modifying treatment of Parkinson's disease.

CBCRisk-Black: a personalized contralateral breast cancer risk prediction model for black women.

PURPOSE: Black breast cancer (BC) survivors have a higher risk of developing contralateral breast cancer (CBC) than Whites. Existing CBC risk prediction tools are developed based on mostly White women. To address this racial disparity, it is crucial to develop tools tailored for Black women to help them inform about their actual risk of CBC. METHODS: We propose an absolute risk prediction model, CBCRisk-Black, specifically for Black BC patients. It uses data on Black women from two sources: Breast Cancer Surveillance Consortium (BCSC) and Surveillance, Epidemiology, and End Results (SEER). First, a matched lasso logistic regression model for estimating relative risks (RR) is developed. Then, it is combined with relevant hazard rates and attributable risks to obtain absolute risks. Six-fold cross-validation is used to internally validate CBCRisk-Black. We also compare CBCRisk-Black with CBCRisk, an existing CBC risk prediction model. RESULTS: The RR model uses data from BCSC on 744 Black women (186 cases). CBCRisk-Black has four risk factors (RR compared to baseline): breast density (2.13 for heterogeneous/extremely dense), family history of BC (2.28 for yes), first BC tumor size (2.14 for T3/T4, 1.56 for TIS), and age at first diagnosis of BC (1.41 for < 40). The area under the receiver operating characteristic curve (AUC) for 3- and 5-year predictions are 0.72 and 0.65 for CBCRisk-Black while those are 0.65 and 0.60 for CBCRisk. CONCLUSION: CBCRisk-Black may serve as a useful tool to clinicians in counseling Black BC patients by providing a more accurate and personalized CBC risk estimate.

Comparison of haplotype-based tests for detecting gene-environment interactions with rare variants.

Dissecting the genetic mechanism underlying a complex disease hinges on discovering gene-environment interactions (GXE). However, detecting GXE is a challenging problem especially when the genetic variants under study are rare. Haplotype-based tests have several advantages over the so-called collapsing tests for detecting rare variants as highlighted in recent literature. Thus, it is of practical interest to compare haplotype-based tests for detecting GXE including the recent ones developed specifically for rare haplotypes. We compare the following methods: haplo.glm, hapassoc, HapReg, Bayesian hierarchical generalized linear model (BhGLM) and logistic Bayesian LASSO (LBL). We simulate data under different types of association scenarios and levels of gene-environment dependence. We find that when the type I error rates are controlled to be the same for all methods, LBL is the most powerful method for detecting GXE. We applied the methods to a lung cancer data set, in particular, in region 15q25.1 as it has been suggested in the literature that it interacts with smoking to affect the lung cancer susceptibility and that it is associated with smoking behavior. LBL and BhGLM were able to detect a rare haplotype-smoking interaction in this region. We also analyzed the sequence data from the Dallas Heart Study, a population-based multi-ethnic study. Specifically, we considered haplotype blocks in the gene ANGPTL4 for association with trait serum triglyceride and used ethnicity as a covariate. Only LBL found interactions of haplotypes with race (Hispanic). Thus, in general, LBL seems to be the best method for detecting GXE among the ones we studied here. Nonetheless, it requires the most computation time.

Antimicrobial peptide S100A12 (calgranulin C) inhibits growth, biofilm formation, pyoverdine secretion and suppresses type VI secretion system in Pseudomonas aeruginosa.

Pseudomonas aeruginosa is an opportunistic pathogen and is the major cause of corneal infections in India and worldwide. The increase in antimicrobial resistance among Pseudomonas has prompted rise in significant research to develop alternative therapeutics. Antimicrobial peptides (AMPs) are considered as potent alternatives to combat bacterial infections. In this study, we investigated the role of S100A12, a host defense peptide, against PAO1 and an ocular clinical isolate. Increased expression of S100A12 was observed in corneal tissues obtained from Pseudomonas keratitis patients by immunohistochemistry. S100A12 significantly inhibited growth of Pseudomonas in vitro as determined from colony forming units. Furthermore, recombinant S100A12 reduced the corneal opacity and the bacterial load in a mouse model of Pseudomonas keratitis. Transcriptome changes in PAO1 in response to S100A12 was investigated using RNA sequencing. The pathway analysis of transcriptome data revealed that S100A12 inhibits expression of genes involved in pyoverdine synthesis and biofilm formation. It also impedes several important pathways like redox, pyocyanin synthesis and type 6 secretion system (T6SS). The transcriptome data was further validated by checking the expression of several affected genes by quantitative PCR. Our study sheds light on how S100A12 impacts Pseudomonas and that it might have the potential to be used as therapeutic intervention in addition to antibiotics to combat infection in future.

HDAC6 as privileged target in drug discovery: A perspective.

HDAC6, a class IIB HDAC isoenzyme, stands unique in its structural and physiological functions. Besides histone modification, largely due to its cytoplasmic localization, HDAC6 also targets several non-histone proteins including Hsp90, α-tubulin, cortactin, HSF1, etc. Thus, it is one of the key regulators of different physiological and pathological disease conditions. HDAC6 is involved in different signaling pathways associated with several neurological disorders, various cancers at early and advanced stage, rare diseases and immunological conditions. Therefore, targeting HDAC6 has been found to be effective for various therapeutic purposes in recent years. Though several HDAC6 inhibitors (HDAC6is) have been developed till date, only two ACY-1215 (ricolinostat) and ACY-241 (citarinostat) are in the clinical trials. A lot of work is still needed to pinpoint strictly selective as well as potent HDAC6i. Considering the recent crystal structure of HDAC6, novel HDAC6is of significant therapeutic value can be designed. Notably, the canonical pharmacophore features of HDAC6is consist of a zinc binding group (ZBG), a linker function and a cap group. Significant modifications of cap function may lead to achieve better selectivity of the inhibitors. This review details the study about the structural biology of HDAC6, the physiological and pathological role of HDAC6 in several disease states and the detailed structure-activity relationships (SARs) of the known HDAC6is. This detailed review will provide key insights to design novel and highly effective HDAC6i in the future.

Detecting rare haplotype association with two correlated phenotypes of binary and continuous types.

Multiple correlated traits/phenotypes are often collected in genetic association studies and they may share a common genetic mechanism. Joint analysis of correlated phenotypes has well-known advantages over one-at-a-time analysis including gain in power and better understanding of genetic etiology. However, when the phenotypes are of discordant types such as binary and continuous, the joint modeling is more challenging. Another research area of current interest is discovery of rare genetic variants. Currently there is no method available for detecting association of rare (or common) haplotypes with multiple discordant phenotypes jointly. Our goal is to fill this gap specifically for two discordant phenotypes. We consider a rare haplotype association method for a binary phenotype, logistic Bayesian LASSO (univariate LBL) and its extension for two correlated binary phenotypes (bivariate LBL-2B). Under this framework, we propose a haplotype association test with binary and continuous phenotypes jointly (bivariate LBL-BC). Specifically, we use a latent variable to induce correlation between the two phenotypes. We carry out extensive simulations to investigate bivariate LBL-BC and compare it with univariate LBL and bivariate LBL-2B. In most settings, bivariate LBL-BC performs the best. In only two situations, bivariate LBL-BC has similar performance-when the two phenotypes are (1) weakly or not correlated and the target haplotype affects the binary phenotype only and (2) strongly positively correlated and the target haplotype affects both phenotypes in positive direction. Finally, we apply the method to a data set on lung cancer and nicotine dependence and detect several haplotypes including a rare one.

Design, synthesis and binding mode of interaction of novel small molecule o-hydroxy benzamides as HDAC3-selective inhibitors with promising antitumor effects in 4T1-Luc breast cancer xenograft model.

Histone deacetylase 3 (HDAC3) is one of the most promising targets to develop anticancer therapeutics. In continuation of our quest for selective HDAC3 inhibitors, a series of small molecules having o-hydroxy benzamide as the novel zinc binding group (ZBG) has been introduced for the first time that can be able to produce good HDAC3-selectivity over other HDACs. The most promising HDAC3 inhibitors, 11a and 12b, displayed promising in vitro anticancer activities with less toxicity to normal kidney cells. These compounds significantly upregulate histone acetylation and induce apoptosis with a G2/M phase arrest in B16F10 cells. Compound 11a exhibited potent antitumor efficacy in 4T1-Luc breast cancer xenograft mouse model in female Balb/c mice. It also showed significant tumor growth suppression with no general toxicity and extended survival rates post-tumor resection. It significantly induced higher ROS generation, leading to apoptosis. No considerable toxicity was noticed in major organs isolated from the compound 11a-treated mice. Compound 11a also induced the upregulation of acH3K9, acH4K12, caspase-3 and caspase-7 as analyzed by immunoblotting with treated tumor tissue. Overall, HDAC3 selective inhibitor 11a might be a potential lead for the clinical translation as an emerging drug candidate.

Synthesis, biological evaluation, and molecular docking analysis of novel linker-less benzamide based potent and selective HDAC3 inhibitors.

A series of novel linker-less benzamides with different aryl and heteroaryl cap groups have been designed, synthesized, and screened as potent histone deacetylase (HDAC) inhibitors with promising anticancer activity. Two lead compounds 5e and 5f were found as potent and highly selective HDAC3 inhibitors over other Class-I HDACs and HDAC6. Compound 5e bearing a 6-quinolinyl moiety as the cap group was found to be a highly potent HDAC3 inhibitor (IC50 = 560 nM) and displayed 46-fold selectivity for HDAC3 over HDAC2, and 33-fold selectivity for HDAC3 over HDAC1. The synthesized compounds possess antiproliferative activities against different cancer cell lines and significantly less cytotoxic to normal cells. Molecular Docking studies of compounds 5e and 5f reveal a similar binding mode of interactions as CI994 at the HDAC3 active site. These observations agreed with the in vitro HDAC3 inhibitory activities. Significant enhancement of the endogenous acetylation level on H3K9 and H4K12 was found when B16F10 cells were treated with compounds 5e and 5f in a dose-dependent manner. The compounds induced apoptotic cell death in Annexin-V/FITC-PI assay and caused cell cycle arrest at G2/M phase of cell cycle in B16F10 cells. These compounds may serve as potential HDAC3 inhibitory anticancer therapeutics.

Synergistic co-loading of vincristine improved chemotherapeutic potential of pegylated liposomal doxorubicin against triple negative breast cancer and non-small cell lung cancer.

The current work aims to explore the biological characteristics of vincristine synergistic co-loading into pegylated liposomal doxorubicin in non-indicated modalities of non-small cell lung cancer (NSCLC) and triple negative breast cancer (TNBC). The combinatorial liposome prepared by active co-loading of the drugs against modified ammonium ion gradient exhibited 95% encapsulation of both drugs. The cellular uptake studies using confocal microscopy and flow cytometry showed significantly increased uptake of dual drug formulation as against liposomal doxorubicin. The co-loaded liposome formulation had significantly increased cell cycle arrest in G2/M phase with subsequent apoptosis and reduced cell viability in both tumor cell lines than doxorubicin liposome. This carrier exhibited similar acute toxicity, pharmacokinetic and tissue distribution profiles with significant increase in tumor regression as compared to liposomal doxorubicin. These results indicate that co-encapsulation of vincristine into clinically used pegylated liposomal doxorubicin significantly improved in-vitro and in-vivo therapeutic efficacy against NSCLC and TNBC.

Bivariate logistic Bayesian LASSO for detecting rare haplotype association with two correlated phenotypes.

In genetic association studies, joint modeling of related traits/phenotypes can utilize the correlation between them and thereby provide more power and uncover additional information about genetic etiology. Moreover, detecting rare genetic variants are of current scientific interest as a key to missing heritability. Logistic Bayesian LASSO (LBL) has been proposed recently to detect rare haplotype variants using case-control data, that is, a single binary phenotype. As there is currently no haplotype association method that can handle multiple binary phenotypes, we extend LBL to fill this gap. We develop a bivariate model by using a latent variable to induce correlation between the two outcomes. We carry out extensive simulations to investigate the bivariate LBL and compare with the univariate LBL. The bivariate LBL performs better or similar to the univariate LBL in most settings. It has the highest gain in power when a haplotype is associated with both traits and it affects at least one trait in a direction opposite to the direction of the correlation between the traits. We analyze two data sets-Genetic Analysis Workshop 19 sequence data on systolic and diastolic blood pressures and a genome-wide association data set on lung cancer and smoking and detect several associated rare haplotypes.

Chlorin e6 Conjugated Methoxy-Poly(Ethylene Glycol)-Poly(D,L-Lactide) Glutathione Sensitive Micelles for Photodynamic Therapy.

PURPOSE: In this study, we developed a polymeric micellar system for glutathione-mediated intracellular delivery of a photosensitizer, chlorin e6 (Ce6) by synthesizing an amphiphilic polymer, methoxy-poly(ethylene glycol)-poly(D,L-lactide)-disulfide-Ce6 (mPEG-PLA-S-S-Ce6), which self-assembled in aqueous environment to form micelles. METHODS: The polymer-drug conjugate was characterized by NMR. The singlet oxygen (2O1) generation and in vitro release of Ce6 micelles were evaluated. Further, glutathione-mediated intracellular drug delivery was assessed in human alveolar adenocarcinoma cells (A549), mouse mammary carcinoma cells (4 T1) and 3D A549 spheroids. RESULTS: The micellar system protected Ce6 from aggregation leading to improved 2O1 generation compared to free Ce6. Due to the availability of glutathione, the disulfide bonds in the micelles were cleaved resulting in rapid release of Ce6 evident from the in vitro study. The Ce6 micelles displayed quicker drug release in presence of glutathione monoester (GSH-OEt) pre-treated A549 and 4 T1 cells compared to without pre-treated cells. In vitro phototoxicity of micelles displayed enhanced toxicity in 10 mM GSH-OEt pre-treated A549 and 4 T1 cells compared to untreated cells. As anticipated, Ce6 micelles showed lower drug release in presence of 0.1 mM of buthionine sulfoximine (BSO) pretreated A549 and 4 T1 cells exhibiting lower phototoxicity. Further, A549 3D spheroids treated with Ce6 micelles showed significant inhibition in growth, enhanced phototoxicity, and cellular apoptosis in comparison to free Ce6. CONCLUSION: The above results showed that the developed strategy could be effective in improving the PDT efficacy of Ce6, and the developed polymeric micellar system could be utilized as a PDT regimen for cancer.

A Bayesian Hierarchical Framework for Pathway Analysis in Genome-Wide Association Studies.

BACKGROUND: Pathway analysis allows joint consideration of multiple SNPs belonging to multiple genes, which in turn belong to a biologically defined pathway. This type of analysis is usually more powerful than single-SNP analyses for detecting joint effects of variants in a pathway. METHODS: We develop a Bayesian hierarchical model by fully modeling the 3-level hierarchy, namely, SNP-gene-pathway that is naturally inherent in the structure of the pathways, unlike the currently used ad hoc ways of combining such information. We model the effects at each level conditional on the effects of the levels preceding them within the generalized linear model framework. To deal with the high dimensionality, we regularize the regression coefficients through an appropriate choice of priors. The model is fit using a combination of iteratively weighted least squares and expectation-maximization algorithms to estimate the posterior modes and their standard errors. A normal approximation is used for inference. RESULTS: We conduct simulations to study the proposed method and find that our method has higher power than some standard approaches in several settings for identifying pathways with multiple modest-sized variants. We illustrate the method by analyzing data from two genome-wide association studies on breast and renal cancers. CONCLUSION: Our method can be helpful in detecting pathway association.

α-Tocopherol Succinate-Anchored PEGylated Poly(amidoamine) Dendrimer for the Delivery of Paclitaxel: Assessment of in Vitro and in Vivo Therapeutic Efficacy.

This study involves development of a dendrimer-based nanoconstruct by conjugating α-tocopheryl succinate (α-TOS) and polyethylene glycol (PEG) on a poly(amidoamine) dendrimer (G4 PAMAM) to improve intracellular delivery of a poorly water-soluble chemotherapeutic drug, paclitaxel (PTX). The conjugates were characterized by NMR, and PTX-loaded nanocarriers (G4-TOS-PEG-PTX) were evaluated for hydrodynamic diameter, polydispersity index (PDI), zeta potential, percentage encapsulation efficiency (%EE), and percentage drug loading (%DL). A hemolysis study was performed, which indicated that the synthesized dendrimer conjugates were not toxic to red blood cells; hence, they were biocompatible. A cellular uptake study in (B16F10 and MDA MB231) monolayer cells and 3D spheroids showed that α-TOS conjugation improved the time dependent uptake of nanosized dendrimer conjugates. The cell viability assay revealed that G4-TOS-PEG-PTX enhanced the cytotoxicity of PTX as compared to free PTX and PTX-loaded G4-PEG (G4-PEG-PTX) at tested concentrations. Correspondingly, the α-TOS-anchored dendrimer induced more apoptosis as compared to free PTX and G4-PEG-PTX. Moreover, the fluorescently labeled G4-TOS-PEG penetrated deeper into MDA MB231 3D spheroids as visualized by confocal microscopy. G4-TOS-PEG-PTX showed significant growth inhibition in 3D spheroids as compared to free PTX and G4-PEG-PTX. Further, the in vivo efficacy study using B16F10 xenografted C57Bl6/J mice indicated that the G4-TOS-PEG localized in tumor sections. G4-TOS-PEG-PTX reduced the tumor growth significantly compared to free PTX and G4-PEG-PTX. G4-TOS-PEG-PTX had more apoptotic potential in tumor sections as analyzed by TUNEL assay. Hence, the newly developed dendrimer conjugate, G4-TOS-PEG, has the potential to target loaded drug to the tumor, and G4-TOS-PEG-PTX has the potential to be utilized successfully in cancer treatment.

A Family-Based Rare Haplotype Association Method for Quantitative Traits.

BACKGROUND: The variants identified in genome-wide association studies account for only a small fraction of disease heritability. A key to this "missing heritability" is believed to be rare variants. Specifically, we focus on rare haplotype variant (rHTV). The existing methods for detecting rHTV are mostly population-based, and as such, are susceptible to population stratification and admixture, leading to an inflated false-positive rate. Family-based methods are more robust in this respect. METHODS: We propose a method for detecting rHTVs associated with quantitative traits called family-based quantitative Bayesian LASSO (famQBL). FamQBL can analyze any type of pedigree and is based on a mixed model framework. We regularize the haplotype effects using Bayesian LASSO and estimate the posterior distributions using Markov chain Monte Carlo methods. RESULTS: We conduct simulation studies, including analyses of Genetic Analysis Workshop 18 simulated data, to study the properties of famQBL and compare with a standard family-based haplotype association test implemented in FBAT (family-based association test) software. We find famQBL to be more powerful than FBAT with well-controlled false-positive rates. We also apply famQBL to the Framingham Heart Study data and detect an rHTV associated with diastolic blood pressure. CONCLUSION: FamQBL can help uncover rHTVs associated with quantitative traits.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

PURPOSE: Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer. METHODS: The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009. Each case of contralateral breast cancer was matched with three controls based on year of first breast cancer diagnosis, race, and length of follow-up. A total of 847 cases and 2541 controls were included. The risk factors included in the study were mammographic breast density, age of first breast cancer diagnosis, family history of breast cancer, anti-estrogen treatment, hormone replacement therapy, menopausal status, and estrogen receptor status, all from the time of first breast cancer diagnosis. Both univariate analysis and multivariate conditional logistic regression analysis were performed. RESULTS: In the final multivariate model, breast density, family history of breast cancer, and anti-estrogen treatment remained significant with p values less than 0.01. Increasing breast density had a dose-dependent effect on the risk of contralateral breast cancer. Relative to 'almost entirely fat' category of breast density, the adjusted odds ratios (and p values) in the multivariate analysis for 'scattered density,' 'heterogeneously dense,' and 'extremely dense' categories were 1.65 (0.036), 2.10 (0.002), and 2.32 (0.001), respectively. CONCLUSION: Breast density is an independent and significant risk factor for development of contralateral breast cancer. This risk factor should contribute to clinical decision making.