Chindo Hicks

Cardiac extracellular proteome profiling and membrane topology analysis using glycoproteomics

Extracellular proteins are easily accessible, which presents a subproteome of molecular targets that have high diagnostic and therapeutic potential. Efforts have been made to catalog the cardiac extracellular matridome and analyze the topology of identified proteins for the design of therapeutic targets. Although many bioinformatics tools have been developed to predict protein topology, topology has been experimentally validated for only a very small portion of membrane proteins. The aim of this study was to use a glycoproteomics and MS approach to identify glycoproteins in the extracellular matridome of the infarcted left ventricle (LV) and provide experimental evidence for topological determination.

An Integrative Genomics Approach to Biomarker Discovery in Breast Cancer

Genome-wide association studies (GWAS) have successfully identified genetic variants associated with risk for breast cancer. However, the molecular mechanisms through which the identified variants confer risk or influence phenotypic expression remains poorly understood. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to assess the combined contribution of multiple genetic variants acting within genes and putative biological pathways, and to identify novel genes and biological pathways that could not be identified using traditional GWAS. The results show that genes containing SNPs associated with risk for breast cancer are functionally related and interact with each other in biological pathways relevant to breast cancer. Additionally, we identified novel genes that are co-expressed and interact with genes containing SNPs associated with breast cancer. Integrative analysis combining GWAS information with gene expression data provides functional bridges between GWAS findings and biological pathways involved in breast cancer.

An Integrative Genomics Approach for Associating GWAS Information with Triple-Negative Breast Cancer

Genome-wide association studies (GWAS) have identified genetic variants associated with an increased risk of developing breast cancer. However, the association of genetic variants and their associated genes with the most aggressive subset of breast cancer, the triple-negative breast cancer (TNBC), remains a central puzzle in molecular epidemiology. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs) associated with an increased risk of developing breast cancer are connected to and could stratify different subtypes of TNBC. Additionally, we sought to identify molecular pathways and networks involved in TNBC. We performed integrative genomics analysis, combining information from GWAS studies involving over 400,000 cases and over 400,000 controls, with gene expression data derived from 124 breast cancer patients classified as TNBC (at the time of diagnosis) and 142 cancer-free controls. Analysis of GWAS reports produced 500 SNPs mapped to 188 genes. We identified a signature of 159 functionally related SNP-containing genes which were significantly (P < 10−5) associated with and stratified TNBC. Additionally, we identified 97 genes which were functionally related to, and had similar patterns of expression profiles, SNP-containing genes. Network modeling and pathway prediction revealed multi-gene pathways including p53, NFkB, BRCA, apoptosis, DNA repair, DNA mismatch, and excision repair pathways enriched for SNPs mapped to genes significantly associated with TNBC. The results provide convincing evidence that integrating GWAS information with gene expression data provides a unified and powerful approach for biomarker discovery in TNBC.

Integrative Analysis of Response to Tamoxifen Treatment in ER-Positive Breast Cancer Using GWAS Information and Transcription Profiling

Variable response and resistance to tamoxifen treatment in breast cancer patients remains a major clinical problem. To determine whether genes and biological pathways containing SNPs associated with risk for breast cancer are dysregulated in response to tamoxifen treatment, we performed analysis combining information from 43 genome-wide association studies with gene expression data from 298 ER+ breast cancer patients treated with tamoxifen and 125 ER+ controls. We identified 95 genes which distinguished tamoxifen treated patients from controls. Additionally, we identified 54 genes which stratified tamoxifen treated patients into two distinct groups. We identified biological pathways containing SNPs associated with risk for breast cancer, which were dysregulated in response to tamoxifen treatment. Key pathways identified included the apoptosis, P53, NFkB, DNA repair and cell cycle pathways. Combining GWAS with transcription profiling provides a unified approach for associating GWAS findings with response to drug treatment and identification of potential drug targets.

Integrative Genomic Analysis for the Discovery of Biomarkers in Prostate Cancer

Genome-wide association studies (GWAS) have achieved great success in identifying single nucleotide polymorphisms (SNPs, herein called genetic variants) and genes associated with risk of developing prostate cancer. However, GWAS do not typically link the genetic variants to the disease state or inform the broader context in which the genetic variants operate. Here, we present a novel integrative genomics approach that combines GWAS information with gene expression data to infer the causal association between gene expression and the disease and to identify the network states and biological pathways enriched for genetic variants. We identified gene regulatory networks and biological pathways enriched for genetic variants, including the prostate cancer, IGF-1, JAK2, androgen, and prolactin signaling pathways. The integration of GWAS information with gene expression data provides insights about the broader context in which genetic variants associated with an increased risk of developing prostate cancer operate.

Comprehensive Assessment and Network Analysis of the Emerging Genetic Susceptibility Landscape of Prostate Cancer

Background Recent advances in high-throughput genotyping have made possible identification of genetic variants associated with increased risk of developing prostate cancer using genome-wide associations studies (GWAS). However, the broader context in which the identified genetic variants operate is poorly understood. Here we present a comprehensive assessment, network, and pathway analysis of the emerging genetic susceptibility landscape of prostate cancer. Methods We created a comprehensive catalog of genetic variants and associated genes by mining published reports and accompanying websites hosting supplementary data on GWAS. We then performed network and pathway analysis using single nucleotide polymorphism (SNP)-containing genes to identify gene regulatory networks and pathways enriched for genetic variants. Results We identified multiple gene networks and pathways enriched for genetic variants including IGF-1, androgen biosynthesis and androgen signaling pathways, and the molecular mechanisms of cancer. The results provide putative functional bridges between GWAS findings and gene regulatory networks and biological pathways.

Associating GWAS Information with the Notch Signaling Pathway Using Transcription Profiling

Genome-wide association studies (GWAS) have identified SNPs associated with breast cancer. However, they offer limited insights about the biological mechanisms by which SNPs confer risk. We investigated the association of GWAS information with a major oncogenic pathway in breast cancer, the Notch signaling pathway. We first identified 385 SNPs and 150 genes associated with risk for breast cancer by mining data from 41 GWAS. We then investigated their expression, along with 32 genes involved in the Notch signaling pathway using two publicly available gene expression data sets from the Caucasian (42 cases and 143 controls) and Asian (43 cases and 43 controls) populations. Pathway prediction and network modeling confirmed that Notch receptors and genes involved in the Notch signaling pathway interact with genes containing SNPs associated with risk for breast cancer. Additionally, we identified other SNP-associated biological pathways relevant to breast cancer, including the P53, apoptosis and MAP kinase pathways.

Molecular Analysis of Central Nervous System Disease Spectrum in Childhood Acute Lymphoblastic Leukemia

Treatment of the central nervous system (CNS) is an essential therapeutic component in childhood acute lymphoblastic leukemia (ALL). The goal of this study was to identify molecular signatures distinguishing patients with CNS disease from those without the disease in pediatric patients with ALL. We analyzed gene expression data from 207 pediatric patients with ALL. Patients without CNS were classified as CNS1, while those with mild and advanced CNS disease were classified as CNS2 and CNS3, respectively. We compared gene expression levels among the three disease classes. We identified gene signatures distinguishing the three disease classes. Pathway analysis revealed molecular networks and biological pathways dysregulated in response to CNS disease involvement. The identified pathways included the ILK, WNT, B-cell receptor, AMPK, ERK5, and JAK signaling pathways. The results demonstrate that transcription profiling could be used to stratify patients to guide therapeutic decision-making in pediatric ALL.

Multimodality Imaging in Pediatric Osteosarcoma in the Era of Image Gently and Image Wisely Campaign With a Close Look at the CT Scan Radiation Dose.

The increasing use of serial multimodality imaging in the management of pediatric osteosarcoma raises concern of over exposure to ionizing radiation in children, especially from repeated computed tomographic (CT) scans. This study reviews the utilization of multimodality imaging in patients with osteosarcoma at our institution and analyzes any potential radiation-related complications. Twenty-eight patients were identified. Three patients developed late complications—acute myeloid leukemia, myelodysplastic syndrome, and early menopause. Using the patient’s age and body part imaged, CT dose length product and effective dose was estimated with the use of a conversion factor for 19 patients. The effective doses were higher in the 3 patients with late complications than the other patients in the cohort (P=0.018). These results suggest an increased risk for adverse effects with higher CT exposures and effective doses. On the basis of our data and published data, methods to decrease the doses of radiation from medical imaging need to be explored. The number of CT scans may be limited. Implementing the Image Gently concept to decrease radiation exposure can be beneficial in modification of CT acquisition parameters.

Transcriptome Analysis of Minimal Residual Disease in Subtypes of Pediatric B Cell Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer and the leading cause of cancer-related death in children and adolescents. Minimal residual disease (MRD) is a strong, independent prognostic factor. The objective of this study was to identify molecular signatures distinguishing patients with positive MRD from those with negative MRD in different subtypes of ALL, and to identify molecular networks and biological pathways deregulated in response to positive MRD at day 46. We compared gene expression levels between patients with positive MRD and negative MRD in each subtype to identify differentially expressed genes. Hierarchical clustering was applied to determine their functional relationships. We identified subtype-specific gene signatures distinguishing patients with positive MRD from those with negative MRD. We identified the genes involved in cell cycle, apoptosis, transport, and DNA repair. We also identified molecular networks and biological pathways dysregulated in response to positive MRD, including Granzyme B, B-cell receptor, and PI3K signaling pathways.