Sambasivarao Damaraju

Nucleoside anticancer drugs: the role of nucleoside transporters in resistance to cancer chemotherapy.

The clinical efficacy of anticancer nucleoside drugs depends on a complex interplay of transporters mediating entry of nucleoside drugs into cells, efflux mechanisms that remove drugs from intracellular compartments and cellular metabolism to active metabolites. Nucleoside transporters (NTs) are important determinants for salvage of preformed nucleosides and mediated uptake of antimetabolite nucleoside drugs into target cells. The focus of this review is the two families of human nucleoside transporters (hENTs, hCNTs) and their role in transport of cytotoxic chemotherapeutic nucleoside drugs. Resistance to anticancer nucleoside drugs is a major clinical problem in which NTs have been implicated. Single nucleotide polymorphisms (SNPs) in drug transporters may contribute to interindividual variation in response to nucleoside drugs. In this review, we give an overview of the functional and molecular characteristics of human NTs and their potential role in resistance to nucleoside drugs and discuss the potential use of genetic polymorphism analyses for NTs to address drug resistance.

Predictive Models for Breast Cancer Susceptibility from Multiple Single Nucleotide Polymorphisms

Hereditary predisposition and causative environmental exposures have long been recognized in human malignancies. In most instances, cancer cases occur sporadically, suggesting that environmental influences are critical in determining cancer risk. To test the influence of genetic polymorphisms on breast cancer risk, we have measured 98 single nucleotide polymorphisms (SNPs) distributed over 45 genes of potential relevance to breast cancer etiology in 174 patients and have compared these with matched normal controls. Using machine learning techniques such as support vector machines (SVMs), decision trees, and naïve Bayes, we identified a subset of three SNPs as key discriminators between breast cancer and controls. The SVMs performed maximally among predictive models, achieving 69% predictive power in distinguishing between the two groups, compared with a 50% baseline predictive power obtained from the data after repeated random permutation of class labels (individuals with cancer or controls). However, the simpler naïve Bayes model as well as the decision tree model performed quite similarly to the SVM. The three SNP sites most useful in this model were (a) the +4536T/C site of the aldosterone synthase gene CYP11B2 at amino acid residue 386 Val/Ala (T/C) (rs4541); (b) the +4328C/G site of the aryl hydrocarbon hydroxylase CYP1B1 at amino acid residue 293 Leu/Val (C/G) (rs5292); and (c) the +4449C/T site of the transcription factor BCL6 at amino acid 387 Asp/Asp (rs1056932). No single SNP site on its own could achieve more than 60% in predictive accuracy. We have shown that multiple SNP sites from different genes over distant parts of the genome are better at identifying breast cancer patients than any one SNP alone. As high-throughput technology for SNPs improves and as more SNPs are identified, it is likely that much higher predictive accuracy will be achieved and a useful clinical tool developed.

Association of DNA Repair and Steroid Metabolism Gene Polymorphisms with Clinical Late Toxicity in Patients Treated with Conformal Radiotherapy for Prostate Cancer

Objective: To explore the possible relationship between single nucleotide polymorphisms (SNP) in candidate genes encoding DNA damage recognition/repair/response and steroid metabolism proteins with respect to clinical radiation toxicity in a retrospective cohort of patients previously treated with three-dimensional conformal radiotherapy (3-DCRT) for prostate cancer. Experimental Design: One hundred twenty-four patients with prostate cancer underwent 3-DCRT at our institution between September 1996 and December 2000. Of these, 83 consented for follow-up of blood sampling and SNP analysis. Twenty-eight patients were documented as having experienced grade ≥2 late bladder or rectal toxicity (scoring system of Radiation Therapy Oncology Group) on at least one follow-up visit. We analyzed 49 SNPs in BRCA1, BRCA2, ESR1, XRCC1, XRCC2, XRCC3, NBN, RAD51, RAD52, LIG4, ATM, BCL2, TGFB1, MSH6, ERCC2, XPF, NR3C1, CYP1A1, CYP2C9, CYP2C19, CYP3A5, CYP2D6, CYP11B2, and CYP17A1 genes using the Pyrosequencing technique. Results: Significant univariate associations with late rectal or bladder toxicity (grade ≥2) were found for XRCC3 (A>G 5′ untranslated region NT 4541), LIG4 (T>C Asp568Asp), MLH1 (C>T, Val219Ile), CYP2D6*4 (G>A splicing defect), mean rectal and bladder dose, dose to 30% of rectum or bladder, and age <60 years. On Cox multivariate analysis, significant associations with toxicity were found for LIG4 (T>C, Asp568Asp), ERCC2 (G>A, Asp711Asp), CYP2D6*4 (G>A, splicing defect), mean bladder dose >60 Gy, and dose to 30% of rectal volume >75 Gy. Conclusions: In this study, we identified SNPs in LIG4, ERCC2, and CYP2D6 genes as putative markers to predict individuals at risk for complications arising from radiation therapy in prostate cancer.

Lymphovascular Invasion Is Associated With Poor Survival in Gastric Cancer: An Application of Gene-Expression and Tissue Array Techniques

Objectives:To examine a population-based cohort for the association between clinicopathologic predictors of survival and immunohistochemical markers (IHC), and to assess changes in gene expression that are associated with lymphovascular invasion (LVI). Summary Background Data:LVI has been associated with poor survival and aggressive tumor behavior. The molecular changes responsible for the behavior of gastric cancer have yet to be determined. Characterization of IHC markers and gene expression profiles may identify molecular alterations governing tumor behavior. Methods:Clinicopathologic and survival data of 114 patients were reviewed. Archival specimens were used to construct a multitumor tissue array that was subjected to IHC of selected protein targets. Correlation of IHC with tumor thickness (T status), LVI and prognosis was studied. Microarray analysis of fresh gastric cancer tissue was conducted to examine the gene expression profile with respect to LVI. Results:In a multivariate analysis, nodal status (N), metastasis (M), and LVI were independent predictors of survival. LVI was associated with a 5-year survival of 13.9% versus 55.9% in patients in whom it was absent. LVI correlated with advancing T status (P = 0.001) and N status (P < 0.001). IHC staining of cyclooxygenase-2 (COX-2) correlated with T status, tumor grade, lymph node positivity, and IHC staining of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9). Microarray analyses suggested differential expression of oligophrenin-1 (OPHN1) and ribophorin-II (RPNII) with respect to LVI. Conclusion:LVI was an independent predictor of survival in gastric cancer. Expression of COX-2 may facilitate tumor invasion through MMP-2 and MMP-9 activation. OPHN1 and RPN II appeared to be differentially expressed in gastric cancers exhibiting LVI. The reported function of OPHN1 and RPN II makes these gene products promising candidates for future studies involving LVI in gastric cancer.

Central nervous system inflammation induces muscle atrophy via activation of the hypothalamic–pituitary–adrenal axis

Systemic and CNS-delimited inflammation triggers skeletal muscle catabolism in a manner dependent on glucocorticoid signaling.

Analysis of Fcγ Receptor IIIa and IIa Polymorphisms: Lack of Correlation with Outcome in Trastuzumab-Treated Breast Cancer Patients

Purpose: The mechanisms by which trastuzumab imparts clinical benefit remain incompletely understood. Antibody-dependent cellular cytotoxicity via interactions with Fcγ receptors (FcγR) on leukocytes may contribute to its antitumor effects. Single-nucleotide polymorphisms (SNP) in FCGR3A and FCGR2A genes lead to amino acid substitutions at positions 158 and 131, respectively, and affect binding of antibodies to FcγR such that 158V/V and 131H/H bind with highest affinity. This study aimed to determine whether high-affinity SNPs are associated with disease-free survival (DFS) among patients with HER2-positive nonmetastatic breast cancer. Experimental Design: Genomic DNA was isolated from 1,286 patients enrolled in a trial of adjuvant trastuzumab-based chemotherapy. Genotyping was conducted using Sanger sequencing and Sequenom mass spectrometry. Results: Patient samples (N = 1,189) were successfully genotyped for FCGR3A and 1,218 for FCGR2A. Compared with the overall results of the BCIRG006 study, in the subset of patients genotyped in this analysis, a less robust improvement in DFS was observed for the trastuzumab arms than control arm (HR, 0.842; P = 0.1925). When stratified for prognostic features, the HR in favor of trastuzumab was consistent with that of the overall study (HR, 0.74; P = 0.036). No correlation between DFS and FCGR3A/2A genotypes was seen for trastuzumab-treated patients (158V/V vs. V/F vs. F/F, P = 0.98; 131H/H vs. H/R vs. R/R, P = 0.76; 158V/V and/or 131H/H vs. others, P = 0.67). Conclusion: This analysis evaluating the association between FCGR3A/2A genotypes and trastuzumab efficacy in HER2-positive breast cancer did not show a correlation between FCGR3A-V/F and FCGR2A-H/R SNPs and DFS in patients treated with trastuzumab. Clin Cancer Res; 18(12); 3478–86. ©2012 AACR.

Computational Predictions of Volatile Anesthetic Interactions with the Microtubule Cytoskeleton: Implications for Side Effects of General Anesthesia

The cytoskeleton is essential to cell morphology, cargo trafficking, and cell division. As the neuronal cytoskeleton is extremely complex, it is no wonder that a startling number of neurodegenerative disorders (including but not limited to Alzheimer’s disease, Parkinson’s disease and Huntington’s disease) share the common feature of a dysfunctional neuronal cytoskeleton. Recently, concern has been raised about a possible link between anesthesia, post-operative cognitive dysfunction, and the exacerbation of neurodegenerative disorders. Experimental investigations suggest that anesthetics bind to and affect cytoskeletal microtubules, and that anesthesia-related cognitive dysfunction involves microtubule instability, hyper-phosphorylation of the microtubule-associated protein tau, and tau separation from microtubules. However, exact mechanisms are yet to be identified. In this paper the interaction of anesthetics with the microtubule subunit protein tubulin is investigated using computer-modeling methods. Homology modeling, molecular dynamics simulations and surface geometry techniques were used to determine putative binding sites for volatile anesthetics on tubulin. This was followed by free energy based docking calculations for halothane (2-bromo-2-chloro-1,1,1-trifluoroethane) on the tubulin body, and C-terminal regions for specific tubulin isotypes. Locations of the putative binding sites, halothane binding energies and the relation to cytoskeleton function are reported in this paper.

Next generation sequencing profiling identifies miR-574-3p and miR-660-5p as potential novel prognostic markers for breast cancer

BackgroundPrognostication of Breast Cancer (BC) relies largely on traditional clinical factors and biomarkers such as hormone or growth factor receptors. Due to their suboptimal specificities, it is challenging to accurately identify the subset of patients who are likely to undergo recurrence and there remains a major need for markers of higher utility to guide therapeutic decisions. MicroRNAs (miRNAs) are small non-coding RNAs that function as post-transcriptional regulators of gene expression and have shown promise as potential prognostic markers in several cancer types including BC.ResultsIn our study, we sequenced miRNAs from 104 BC samples and 11 apparently healthy normal (reduction mammoplasty) breast tissues. We used Case–control (CC) and Case-only (CO) statistical paradigm to identify prognostic markers. Cox-proportional hazards regression model was employed and risk score analysis was performed to identify miRNA signature independent of potential confounders. Representative miRNAs were validated using qRT-PCR. Gene targets for prognostic miRNAs were identified using in silico predictions and in-house BC transcriptome dataset. Gene ontology terms were identified using DAVID bioinformatics v6.7. A total of 1,423 miRNAs were captured. In the CC approach, 126 miRNAs were retained with predetermined criteria for good read counts, from which 80 miRNAs were differentially expressed. Of these, four and two miRNAs were significant for Overall Survival (OS) and Recurrence Free Survival (RFS), respectively. In the CO approach, from 147 miRNAs retained after filtering, 11 and 4 miRNAs were significant for OS and RFS, respectively. In both the approaches, the risk scores were significant after adjusting for potential confounders. The miRNAs associated with OS identified in our cohort were validated using an external dataset from The Cancer Genome Atlas (TCGA) project. Targets for the identified miRNAs were enriched for cell proliferation, invasion and migration.ConclusionsThe study identified twelve non-redundant miRNAs associated with OS and/or RFS. These signatures include those that were reported by others in BC or other cancers. Importantly we report for the first time two new candidate miRNAs (miR-574-3p and miR-660-5p) as promising prognostic markers. Independent validation of signatures (for OS) using an external dataset from TCGA further strengthened the study findings.

Assessing SNP-SNP Interactions among DNA Repair, Modification and Metabolism Related Pathway Genes in Breast Cancer Susceptibility

Genome-wide association studies (GWASs) have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs) associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis) are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based) weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i) to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii) to replicate these SNPs in an independent set of breast cancer cases and controls; and iii) to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls) from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412) in logistic regression that conferred elevated risks for breast cancer (P interaction<7.3×10−3). Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943) (P permutation = 2.4×10−3). SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P correlation/trend = 3.2×10−4) than the others. These single-locus effects were independent of body mass index. Our results provide a framework for evaluating SNPs showing statistically weak but reproducible single-locus effects for epistatic effects contributing to disease susceptibility.

Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility.

Previous genome-wide association studies (GWAS) have shown several risk alleles to be associated with breast cancer. However, the variants identified so far contribute to only a small proportion of disease risk. The objective of our GWAS was to identify additional novel breast cancer susceptibility variants and to replicate these findings in an independent cohort. We performed a two-stage association study in a cohort of 3,064 women from Alberta, Canada. In Stage I, we interrogated 906,600 single nucleotide polymorphisms (SNPs) on Affymetrix SNP 6.0 arrays using 348 breast cancer cases and 348 controls. We used single-locus association tests to determine statistical significance for the observed differences in allele frequencies between cases and controls. In Stage II, we attempted to replicate 35 significant markers identified in Stage I in an independent study of 1,153 cases and 1,215 controls. Genotyping of Stage II samples was done using Sequenom Mass-ARRAY iPlex platform. Six loci from four different gene regions (chromosomes 4, 5, 16 and 19) showed statistically significant differences between cases and controls in both Stage I and Stage II testing, and also in joint analysis. The identified variants were from EDNRA, ROPN1L, C16orf61 and ZNF577 gene regions. The presented joint analyses from the two-stage study design were not significant after genome-wide correction. The SNPs identified in this study may serve as potential candidate loci for breast cancer risk in a further replication study in Stage III from Alberta population or independent validation in Caucasian cohorts elsewhere.