The Gene Expression Resource (GER) was established with the successful recruitment of Lesleyann Hawthorn, PhD in 2001. The Resource has flourished since that time with a broad base of satisfied users whose continued patronage is derived from a unique approach to microarray experimentation. Its success is largely due to a commitment to provide researchers with high-quality microarray data with the added advantage of data analysis so that the results provided to the individual researchers are in a usable format, unlike most array-based facilities. Dr Hawthorn and the GER staff keep abreast of emerging technologies to provide users with a broad range of expertise and options. This success is substantiated by a large user base, publications and awarded grants. The Resource is functionally divided into Gene Expression, Genotyping, and Copy Number Analysis at the genomics level. At the level of individual chromosomal regions or specific genes, it offers mutation/polymorphism analysis, SNP validation and discovery, expression level quantification and analysis of methylation status. Most importantly, the Resource offers data analysis for all the platforms that it supports and provides expertise, time and funding for the development of novel technologies. For example, Exon array analysis has been developed which allows simultaneous detection of gene expression and alternative splicing events. Furthermore, the Resource is now able to run Whole-Genome Tiling arrays, which permit the highest-resolution Chip-on-Chip analysis as well as the detection of novel transcripts in genomic DNA. During the last few years, the Resource has been working on innovative approaches to the analysis of genomics data. One of these centers on the high-density SNP arrays that offer the highest density genotyping, as well as simultaneous CGH analysis with accompanying LOH analysis. Gene Expression has been using these arrays to look for gains and losses of chromosomal regions (CGH). The ability of the SNP Mapping arrays to detect standard cytogenetic abnormalities represents a major advancement over conventional karyotyping. The GER has collaborated with Dr Cowell's group (GN) to develop statistical analysis tools that permit the overlay of gene expression data with aCGH data, thus enhancing the power of both these technologies. Members of the six CCSG programs utilized this Resource over the last project period. The Resource was instrumental in enhanced peer-reviewed funding, publications and recruitment efforts. It is anticipated that with the new recruitment into the CSBT Program (Dr Gudkov), MTET Program (Dr Adjei), and Til (Dr Lee) the utilization of the Resource will expand. The Resource is used by all six Programs and 98% of users are CCSG members. $80,355 in CCSG support is requested, representing 11% of the total operating budget.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
3P30CA016056-36S4
Application #
8637140
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2013-05-01
Budget End
2014-04-30
Support Year
36
Fiscal Year
2013
Total Cost
$3,763,390
Indirect Cost
$1,467,341
Name
Roswell Park Cancer Institute Corp
Department
Type
DUNS #
824771034
City
Buffalo
State
NY
Country
United States
Zip Code
14263
Liu, Chunhong; Yu, Tao; Xing, Zhuo et al. (2018) Triplications of human chromosome 21 orthologous regions in mice result in expansion of megakaryocyte-erythroid progenitors and reduction of granulocyte-macrophage progenitors. Oncotarget 9:4773-4786
Muramatsu, Masashi; Akakura, Shin; Gao, Lingqiu et al. (2018) SSeCKS/Akap12 suppresses metastatic melanoma lung colonization by attenuating Src-mediated pre-metastatic niche crosstalk. Oncotarget 9:33515-33527
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Ramakrishnan, Swathi; Huss, Wendy; Foster, Barbara et al. (2018) Transcriptional changes associated with in vivo growth of muscle-invasive bladder cancer cell lines in nude mice. Am J Clin Exp Urol 6:138-148
Chang, Han-Wen; Valieva, Maria E; Safina, Alfiya et al. (2018) Mechanism of FACT removal from transcribed genes by anticancer drugs curaxins. Sci Adv 4:eaav2131
Dong, Jing; Buas, Matthew F; Gharahkhani, Puya et al. (2018) Determining Risk of Barrett's Esophagus and Esophageal Adenocarcinoma Based on Epidemiologic Factors and Genetic Variants. Gastroenterology 154:1273-1281.e3

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