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Keith Baggerly

Publications and source records attributed to Keith Baggerly.

8 recordsLinked to original sources
PubMed2005

Gene expression signature of estrogen receptor alpha status in breast cancer.

BACKGROUND: Estrogens are known to regulate the proliferation of breast cancer cells and to modify their phenotypic properties. Identification of estrogen-regulated genes in human breast tumors is an essential step toward understanding the molecular mechanisms of estrogen action in cancer. To this end we generated and compared the Serial Analysis of Gene Expression (SAGE) profiles of 26 human breast carcinomas based on their estrogen receptor alpha (ER) status. Thus, producing a breast cancer SAGE database of almost 2.5 million tags, representing over 50,000 transcripts. RESULTS: We identified 520 transcripts differentially expressed between ERalpha-positive (+) and ERalpha-negative (-) primary breast tumors (Fold change >or= 2; p < 0.05). Furthermore, we identified 220 high-affinity Estrogen Responsive Elements (EREs) distributed on the promoter regions of 163 out of the 473 up-modulated genes in ERalpha (+) breast tumors. In brief, we observed predominantly up-regulation of cell growth related genes, DNA binding and transcription factor activity related genes based on Gene Ontology (GO) biological functional annotation. GO terms over-representation analysis showed a statistically significant enrichment of various transcript families including: metal ion binding related transcripts (p = 0.011), calcium ion binding related transcripts (p = 0.033) and steroid hormone receptor activity related transcripts (p = 0.031). SAGE data associated with ERalpha status was compared with reported information from breast cancer DNA microarrays studies. A significant proportion of ERalpha associated gene expression changes was validated by this cross-platform comparison. However, our SAGE study also identified novel sets of genes as highly expressed in ERalpha (+) invasive breast tumors not previously reported. These observations were further validated in an independent set of human breast tumors by means of real time RT-PCR. CONCLUSION: The integration of the breast cancer comparative transcriptome analysis based on ERalpha status coupled to the genome-wide identification of high-affinity EREs and GO over-representation analysis, provide useful information for validation and discovery of signaling networks related to estrogen response in this malignancy.

Biomarkers, Tumor↗
PubMed2005

Alterations in transcription clusters underlie development of bladder cancer along papillary and nonpapillary pathways.

Bladder cancer develops in the urothelial lining from intraurothelial preneoplasia via two pathways, papillary and nonpapillary, which correspond to nonaggressive and aggressive forms of the disease. Because these two forms of cancer may develop via distinct molecular events, we examined the gene expression patterns in the development of bladder cancer from preneoplasia along papillary and nonpapillary pathways. The expression profiles of 19 pairs of RNA samples from adjacent urothelium and tumors were analyzed using cDNA microarrays. For selected genes their expressions were verified on a cohort of 251 bladder cancer patients using tissue microarray and immunohistochemistry and were related to clinicopathological parameters including follow-up data. We identified alterations in seven gene clusters controlling proliferation, differentiation, and programmed cell death that were common for papillary and nonpapillary cancer. In contrast, genes controlling cellular and stromal interactions were altered in the nonpapillary cancer. The expression levels of only two genes from this group could be used to define an aggressive form of the disease. Tumors characterized by the low expression of e-cadherin and the high expression of DNA alpha-topoisomerase II had a high propensity for distant metastasis and were associated with poor survival.

DNA, Complementary↗
PubMed2005

High-resolution whole-organ mapping with SNPs and its significance to early events of carcinogenesis.

We attempted to identify deleted segments in two model tumor suppressor gene loci on chromosomes 13q14 and 17p13 that were associated with clonal expansion of in situ bladder preneoplasia using single nucleotide polymorphisms (SNPs)-based whole-organ histologic and genetic mapping. For mapping with SNPs, the sequence-based maps spanning approximately 27 and 5 Mb centered around RB1 and p53, respectively, were assembled. The integrated gene and SNP maps of the regions were used to select 661 and 960 SNPs, which were genotyped by pyrosequencing. Genotyping of SNPs was performed on DNA samples corresponding to histologic maps of the entire bladder mucosa in human cystectomy specimens with invasive urothelial carcinoma. By using this approach, we have identified deleted regions associated with clonal expansion of intraurothelial neoplasia; which ranged from 0.001 to 4.3 Mb (average 0.67 Mb) and formed clusters of discontinuous deleted segments. The high resolution of such maps is a prerequisite for future positional targeting of genes involved in early phases of bladder neoplasia. This approach also permits analysis of the overall genomic landscape of the involved region and discloses that a unique composition of noncoding DNA characterized by a high concentration of repetitive sequences may predispose to deletions.

Carcinoma in Situ↗
PubMed2004

From mice to humans: identification of commonly deregulated genes in mammary cancer via comparative SAGE studies.

Genetically engineered mouse mammary cancer models have been used over the years as systems to study human breast cancer. However, much controversy exists on the utility of such models as valid equivalents to the human cancer condition. To perform an interspecies gene expression comparative study in breast cancer we used a mouse model that most closely resembles human breast carcinogenesis. This system relies on the transplant of p53 null mouse mammary epithelial cells into the cleared mammary fat pads of syngeneic hosts. Serial analysis of gene expression (SAGE) was used to obtain gene expression profiles of normal and tumor samples from this mouse mammary cancer model (>300,000 mouse mammary-specific tags). The resulting mouse data were compared with 25 of our human breast cancer SAGE libraries (>2.5 million human breast-specific tags). We observed significant similarities in the deregulation of specific genes and gene families when comparing mouse with human breast cancer SAGE data. A total of 72 transcripts were identified as commonly deregulated in both species. We observed a systematic and significant down-regulation in all of the tumors from both species of various cytokines, including CXCL1 (GRO1), LIF, interleukin 6, and CCL2. All of the mouse and most human mammary tumors also displayed decreased expression of genes known to inhibit cell proliferation, including NFKBIA (IKBalpha), GADD45B, and CDKN1A (p21); transcription-related genes such as CEBP, JUN, JUNB, and ELF1; and apoptosis-related transcripts such as IER3 and GADD34/PPP1R15A. Examples of overexpressed transcripts in tumors from both species include proliferation-related genes such as CCND1, CKS1B, and STMN1 (oncoprotein 18); and genes related to other functions such as SEPW1, SDFR1, DNCI2, and SP110. Importantly, abnormal expression of several of these genes has not been associated previously with breast cancer. The consistency of these observations was validated in independent mouse and human mammary cancer sets. This is the first interspecies comparison of mammary cancer gene expression profiles. The comparative analysis of mouse and human SAGE mammary cancer data validates this p53 null mouse tumor model as a useful system closely resembling human breast cancer development and progression. More importantly, these studies are allowing us to identify relevant biomarkers of potential use in human studies while leading to a better understanding of specific mechanisms of human breast carcinogenesis.

Animals↗
PubMed2004

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression.

INTRODUCTION: Genomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution. METHODS: In the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed. RESULTS: We accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01). CONCLUSION: A major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions with fully invasive lesions, a much more heterogeneous group, clearly identified as the most importantly deregulated group of transcripts those encoding for various families of proteins in charge of extracellular matrix remodeling, invasion and cell motility functions.

Apoptosis↗
PubMed2004

Diagnostic protein discovery using proteolytic peptide targeting and identification.

Plasma protein profiling with mass spectrometry is currently being evaluated as a diagnostic tool for cancer and other diseases. These experiments consist of three steps: plasma protein fractionation, analysis with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS), and comparisons of the MALDI profiles to develop diagnostic fingerprints using bioinformatic techniques. While preliminary results appear promising in small sample groups, the method is limited by the sensitivity of MALDI-MS for intact proteins, the limited mass range of MALDI-MS, and difficulties associated with isolating individual proteins for identification to validate the diagnostic fingerprint. Here we present an alternative and improved method directed toward diagnostic protein discovery, which incorporates proteolytic peptide profiling, bioinformatic targeting of ion signals, and MALDI tandem mass spectrometry (MS/MS) peptide sequencing, rather than fingerprinting. Pancreatic cancer patients, pancreatitis patients, and controls are used as the model system. Profiling peptides after enzymatic digestion improves sensitivity and extends the accessible protein molecular weight range when compared to intact protein profiling. The first step is to extract and fractionate the proteins from plasma. Each fraction is digested with trypsin and subsequently analyzed by MALDI-MS. Rather than using bioinformatic analysis as a pattern-matching technique, peptides are targeted based on the disease to control peak intensity ratios measured in the averages of all mass spectra in each group and t-tests of the intensity of each individual peak. The targeted peptide ion signals are subsequently identified using MALDI-MS/MS in quadrupole-TOF and tandem-TOF instruments. This study found not only the proteins targeted and identified by a previous protein profiling experiment, but also detected additional proteins. These initial results are consistent with the known biology of pancreatic cancer or pancreatitis, but are not specific to those diseases.

Adult↗
PubMed2002

Obtaining reliable information from minute amounts of RNA using cDNA microarrays.

BACKGROUND: High density cDNA microarray technology provides a powerful tool to survey the activity of thousands of genes in normal and diseased cells, which helps us both to understand the molecular basis of the disease and to identify potential targets for therapeutic intervention. The promise of this technology has been hampered by the large amount of biological material required for the experiments (more than 50 microg of total RNA per array). We have modified an amplification procedure that requires only 1 microg of total RNA. Analyses of the results showed that most genes that were detected as expressed or differentially expressed using the regular protocol were also detected using the amplification protocol. In addition, many genes that were undetected or weakly detected using the regular protocol were clearly detected using the amplification protocol. We have carried out a series of confirmation studies by northern blotting, western blotting, and immunohistochemistry assays. RESULTS: Our results showed that most of the new information revealed by the amplification protocol represents real gene activity in the cells. CONCLUSION: We have confirmed a powerful and consistent cDNA microarray procedure that can be used to study minute amounts of biological tissue.

Journal Article↗