Biomedical subjects

Rajiv Raja

Publications and source records attributed to Rajiv Raja.

6 recordsLinked to original sources

PubMed2006

Molecular classification of human cancers using a 92-gene real-time quantitative polymerase chain reaction assay.

CONTEXT: Correct diagnosis of the tissue origin of a metastatic cancer is the first step in disease management, but it is frequently difficult using standard pathologic methods. Microarray-based gene expression profiling has shown great promise as a new tool to address this challenge. OBJECTIVE: Adoption of microarray technologies in the clinic remains limited. We aimed to bridge this technological gap by developing a real-time quantitative polymerase chain reaction (RT-PCR) assay. DESIGN: We constructed a microarray database of 466 frozen and 112 formalin-fixed, paraffin-embedded (FFPE) samples of both primary and metastatic tumors, measuring expression of 22,000 genes. From the microarray database, we used a genetic algorithm to search for gene combinations optimal for multitumor classification. A 92-gene RT-PCR assay was then designed and used to generate a database for 481 frozen and 119 FFPE tumor samples. RESULTS: The microarray-based K-nearest neighbor classifier demonstrated 84% accuracy in classifying 39 tumor types via cross-validation and 82% accuracy in predicting 112 independent FFPE samples. We successfully translated the microarray database to the RT-PCR platform, which allowed an overall success rate of 87% in classifying 32 different tumor classes in the validation set of 119 FFPE tumor samples. CONCLUSIONS: The RT-PCR-based expression assay involving 92 genes represents a powerful tool for accurately and objectively identifying the site of origin for metastatic tumors, especially in the cases of cancer of unknown primary. The assay uses RT-PCR and routine FFPE samples, making it suitable for rapid clinical adoption.

Algorithms↗

PubMed2004

Genetic signatures of high- and low-risk aberrant crypt foci in a mouse model of sporadic colon cancer.

To determine whether cancer risk is related to histopathological features of preneoplastic aberrant crypt foci (ACF), gene expression analysis was performed on ACF from two mouse strains with differing tumor sensitivity to the colonotropic carcinogen, azoxymethane. ACF from sensitive A/J mice were considered at high risk, whereas ACF from resistant AKR/J mice were considered at low risk for tumorigenesis. A/J and AKR/J mice received weekly injections of azoxymethane (10 mg/kg body weight), and frozen colon sections were prepared 6 weeks later. Immunohistochemistry was performed using biomarkers associated with colon cancer, including adenomatous polyposis coli, beta-catenin, p53, c-myc, cyclin D1, and proliferating cell nuclear antigen. Hyperplastic ACF, dysplastic ACF, microadenomas, adjacent normal-appearing epithelium, and vehicle-treated colons were laser captured, and RNA was linearly amplified (LCM-LA) and subjected to cDNA microarray-based expression analysis. Patterns of gene expression were identified using adaptive centroid algorithm. ACF from low- and high-risk colons were not discriminated by immunohistochemistry, with the exception of membrane staining of beta-catenin. To develop genetic signatures that predict cancer risk, LCM-LA RNA from ACF was hybridized to cDNA arrays. Of 4896 interrogated genes, 220 clustered into six broad clusters. A total of 226 and 202 genes was consistently altered in lesions from A/J and AKR/J mice, respectively. Although many alterations were common to both strains, expression profiles stratified high- and low- risk lesions. These data demonstrate that ACF with distinct tumorigenic potential have distinguishing molecular features. In addition to providing insight into colon cancer promotion, our data identify potential biomarkers for determining colon cancer risk in humans.

Animals↗

PubMed2004

The unique transcriptome through day 3 of human preimplantation development.

Successful human development is dependent upon a cascade of events following fertilization. Unfortunately, knowledge of these critical events in humans is remarkably incomplete. Although hundreds of thousands of human embryos are cultured yearly at infertility centers worldwide, the vast majority fail to develop in culture or following transfer to the uterus. In this study, we sought to characterize global patterns of gene expression in individual, normal embryos during the first three days of embryonic life using microarrays; we then compared gene expression between normally growing and growth-arrested embryos using quantitative PCR. Our results documented several novel findings. First, we found that a complex pattern of gene expression exists; most genes that are transcriptionally modulated during the first three days following fertilization are not upregulated, as was previously thought, but are downregulated. Second, we observed that the majority of genes exhibiting differential expression during preimplantation development are of unknown identity and/or function. Third, we show that embryonic transcriptional programs are clearly established by day 3 following fertilization, even in embryos that arrested prematurely with 2-, 3- or 4-cells. This indicates that failure to activate transcription is not associated with the majority of human preimplantation embryo loss. Finally, taken together, these results provide the first global analysis of the human preimplantation embryo transcriptome, and demonstrate that RNA can be amplified from single oocytes and embryos for analysis by cDNA microarray technology, thus lending credence to additional studies of genetic regulation in these cell types, as well as in other small biological samples.

Blastocyst↗

PubMed2004

Microgenomics: Identification of new expression profiles via small and single-cell sample analyses.

BACKGROUND: Since the sequencing of the human genome has been finished, microgenomics has been booming, employing highly sophisticated, high-throughput platforms. But these mainly chip-based methods can only generate biologically relevant data if the samples investigated consist of homogeneous cell populations, in which no unwanted cells of different specificity and/or developmental stage obscure the results. METHODS: Different sampling methods have been routinely applied to overcome the problem presented by heterogeneous samples, e.g., global surveys, cell cultures, and microdissection. Various methods of laser-assisted microdissection, employing either positive or negative selection of tissue areas or even single cells, are available. RESULTS: These laser-assisted microdissection methods allow for fast and precise procurement of extremely small samples. Through subsequent application of recently developed methods of linear mRNA amplification in a pool of isolated total RNA, it has now become possible to perform complex high-throughput RNA expression profiling by microdissecting and processing even single-cell samples. CONCLUSIONS: Studies using the tools and methods of microgenomics have shed light on how those new approaches will eventually aid in the development of a new generation of diagnostics, e.g., leading to new patient-specific drugs tailored to the requirements assessed by assaying only a few biopsy cells.

Cell Separation↗

PubMed2003

Accurate and reproducible gene expression profiles from laser capture microdissection, transcript amplification, and high density oligonucleotide microarray analysis.

Gene expression profiling using high density oligonucleotide arrays is a powerful method to generate an unbiased survey of a cell's transcriptional landscape. Increasingly complex biological questions require that this approach be applicable to the small numbers of cells that are obtained from sources such as laser capture microdissection (LCM) of solid tissues. In this report, we demonstrate that two rounds of transcript amplification can generate accurate and reproducible gene expression profiles using high density oligonucleotide microarrays, starting with as little as 10 ng of total RNA. Biased amplification of the 3' end of transcripts does not have a major impact on the overall transcript profile due to the 3' bias of probe sets incorporated in the array design. Furthermore, greater than 95% of all genes detected demonstrate less than a twofold difference in expression when independent tissue dissections of identical cell populations are compared. The accuracy and technical reproducibility of the method suggests that expression profiling using transcript amplification and high density oligonucleotide microarrays can be used on a routine basis.

Breast Neoplasms↗

PubMed2002

Role of the alternating reading frame (P19)-p53 pathway in an in vivo murine colon tumor model.

Considering the importance of the oncogene checkpoint function of the alternating reading frame(ARF)-p53 pathway, studies were undertaken to evaluate the status of this pathway in azoxymethane (AOM)-induced mouse colon tumors. A PCR-based analysis of ARF and p53 cDNAs in normal colon tissues and AOM-induced colon tumors failed to detect mutations in either of these two critical tumor suppressor genes. In addition, laser capture microdissection of tumors followed by PCR-based sequencing of exons 5-7 of genomic p53 showed that even the most pleomorphic cancer cells were p53 normal. A marked increase in ARF mRNA and protein levels was observed in colon tumors, indicating activation of the ARF-p53 pathway in these tumors. High levels of ARF protein stabilized p53 protein in the tumors, but the p53 protein showed little biochemical activity. Compared with a mouse colonocyte cell line that expresses high levels of wild-type p53 (YAMC), the p53 protein in tumors had no detectable DNA binding activity nor did it activate p21 expression. In fact, p21 levels were lower in tumor tissue relative to normal mucosa, even though p53 levels were approximately 30-fold higher in tumors relative to control. Within the A/J tumors, we also used a cDNA microarray approach to screen a panel of genes that are transcriptionally up- or down-regulated by functional p53. The expression patterns of these p53-regulated genes were consistent with a lack of functional p53. This work demonstrates that the ARF-p53 oncogene checkpoint can be overcome without p53 mutations and that the mechanism used to overcome this checkpoint involves the suppression of p53 transcriptional activating activity. The AOM colon cancer model may be well suited for studying tumor promotion events that precede p53 disruption.

Adenocarcinoma↗