DNA Microarrays in Clinical Oncology

2002 ◽  
Vol 20 (7) ◽  
pp. 1932-1941 ◽  
Author(s):  
Sridhar Ramaswamy ◽  
Todd R. Golub
Keyword(s):  
Gene Expression ◽  
Clinical Oncology ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Human Cancer ◽  
Clinical Applications ◽  
Cancer Gene ◽  
Comprehensive Understanding ◽  
Aberrant Gene Expression ◽  
Aberrant Gene

ABSTRACT: Aberrant gene expression is critical for tumor initiation and progression. However, we lack a comprehensive understanding of all genes that are aberrantly expressed in human cancer. Recently, DNA microarrays have been used to obtain global views of human cancer gene expression and to identify genetic markers that might be important for diagnosis and therapy. We review clinical applications of these novel tools, discuss some important recent studies, identify promising avenues of research in this emerging field of study, and discuss the likely impact that expression profiling will have on clinical oncology.

scholarly journals Differentially Methylated Super-Enhancers Regulate Target Gene Expression in Human Cancer

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Emily L. Flam ◽  
Ludmila Danilova ◽  
Dylan Z. Kelley ◽  
Elena Stavrovskaya ◽  
Theresa Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Target Genes ◽  
Human Cancer ◽  
Genetic Alterations ◽  
Tumor Type ◽  
Gene Pairs ◽  
Aberrant Gene Expression ◽  
Tumor Types ◽  
Aberrant Gene

Abstract Current literature suggests that epigenetically regulated super-enhancers (SEs) are drivers of aberrant gene expression in cancers. Many tumor types are still missing chromatin data to define cancer-specific SEs and their role in carcinogenesis. In this work, we develop a simple pipeline, which can utilize chromatin data from etiologically similar tumors to discover tissue-specific SEs and their target genes using gene expression and DNA methylation data. As an example, we applied our pipeline to human papillomavirus-related oropharyngeal squamous cell carcinoma (HPV + OPSCC). This tumor type is characterized by abundant gene expression changes, which cannot be explained by genetic alterations alone. Chromatin data are still limited for this disease, so we used 3627 SE elements from public domain data for closely related tissues, including normal and tumor lung, and cervical cancer cell lines. We integrated the available DNA methylation and gene expression data for HPV + OPSCC samples to filter the candidate SEs to identify functional SEs and their affected targets, which are essential for cancer development. Overall, we found 159 differentially methylated SEs, including 87 SEs that actively regulate expression of 150 nearby genes (211 SE-gene pairs) in HPV + OPSCC. Of these, 132 SE-gene pairs were validated in a related TCGA cohort. Pathway analysis revealed that the SE-regulated genes were associated with pathways known to regulate nasopharyngeal, breast, melanoma, and bladder carcinogenesis and are regulated by the epigenetic landscape in those cancers. Thus, we propose that gene expression in HPV + OPSCC may be controlled by epigenetic alterations in SE elements, which are common between related tissues. Our pipeline can utilize a diversity of data inputs and can be further adapted to SE analysis of diseased and non-diseased tissues from different organisms.

scholarly journals 78 Novel RNA-seq platform improve patient outcome in clinical oncology and enable implementation of AI in the clinic

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A87-A87
Author(s):  
Vy Nguyen ◽  
Gitte Pedersen ◽  
Morten Pedersen
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Clinical Oncology ◽  
Individualized Treatment ◽  
Tissue Type ◽  
Clinical Samples ◽  
Aberrant Gene Expression ◽  
Approved Drugs ◽  
Aberrant Gene ◽  
Insight Into

BackgroundOnly 1 out of 4 cancer treatments prolongs life while expenditure for cancer treatment is greater than $100 billion/year. RNA-sequencing has allowed researchers to gain insight into the transcriptome of human cancers. However, RNA-sequencing remains widely unused in clinical oncology. We address this issue through the development and CLIA validation of OneRNA—an RNA-sequencing platform for cancer diagnostics and the design of new treatments. The development of OneRNA had to overcome the two main hurdles for implementation of RNA sequencing in the clinic: 1) clinical samples are typically embedded in FFPE which results in highly fragmented RNA making sequencing of these samples difficult. 2) how to interpret aberrant gene expression events and translate these results into clinical action. We demonstrate how OneRNA® would enable the design of sophisticated combinatorial clinical studies. An example is combining immune targeting agents such as checkpoint inhibitors with mRNA vaccines. OneRNA also supports the integration of gene expression algorithms because of its ability to interrogate the entire sample transcriptome. OneRNA® has been CLIA certified using FFPE, FF, blood, and saliva samples. Furthermore, the sample preparation method has demonstrated >95% concordance between FF and FFPE and 5–10X the sensitivity compared to Truseq.MethodsThis study aims to demonstrate the clinical utility of OneRNA in detecting aberrant gene expression events and connecting these to already approved drugs that targets these events to offer truly individualized treatment options.ResultsWe show that OneRNA has the ability to predict results for not only validated biomarkers used in standard of care such as ER, PR and HER2 in breast cancer, but also provide insight into biomarkers for response to already approved drugs independent of tissue type and with no standard test. Finally, we demonstrate the reproducibility of OneRNA in predicting IHC status in ER, PR and HER2.ConclusionsThese results demonstrate that OneRNA has applications in both cancer research, drug discovery and development, development of companion diagnostic algorithms and implementation of truly individualized treatment.

scholarly journals A decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects

Blood ◽  
2009 ◽  
Vol 113 (2) ◽  
pp. 291-298 ◽  
Author(s):  
Bas J. Wouters ◽  
Bob Löwenberg ◽  
Ruud Delwel
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Myeloid Leukemia ◽  
Dna Microarrays ◽  
Human Cancer ◽  
Genome Wide ◽  
Genome Wide Gene Expression ◽  
Acute Myeloid

Abstract The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues

Looking Beyond Morphology: Cancer Gene Expression Profiling Using DNA Microarrays

2003 ◽  
Vol 21 (6) ◽  
pp. 937-949 ◽  
Author(s):  
Jun Luo ◽  
William B. Isaacs ◽  
Jeffrey M. Trent ◽  
David J. Duggan
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Cancer Gene

Hepatocellular cancer gene expression profiling by DNA microarrays: development of new diagnostic markers

2002 ◽  
Vol 36 ◽  
pp. 170-171
Author(s):  
Stephan Kaiser ◽  
Holger Hass ◽  
Juergen Jobst ◽  
Sabine Debuschewitz ◽  
Michael Gregor
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Hepatocellular Cancer ◽  
Diagnostic Markers ◽  
Cancer Gene

scholarly journals Microarray expression technology in clinical research of non-Hodgkin lymphoma

2007 ◽  
Vol 15 (1-2) ◽  
pp. 28-35 ◽  
Author(s):  
Vladimir Baltic ◽  
Milan Baltic
Keyword(s):  
Gene Expression ◽  
Hodgkin Lymphoma ◽  
Clinical Oncology ◽  
Expression Profiling ◽  
Dna Microarrays ◽  
Prognostic Models ◽  
Current Therapy ◽  
Non Hodgkin Lymphoma ◽  
Oncology Research ◽  
Oncology Practice

Nowadays, in genomocentric era accelerated research of the human genome coupled with advances is enabling the comprehensive molecular profiling of human tissue. Particularly, DNA microarrays are powerful tools for obtaining global view of human non-Hodgkin lymphomas gene expression. Complex information from lymphomas "expression profiling" studies can, in turn, be used to create molecular markers that have diagnostic or prognostic implications. The gene "expression profiling" is not of routine clinical oncology practice, but is used in genomic classification of clinically relevant subgroups of non-Hodgkin lymphoma. The genomics biomarkers have been incorporated into current prognostic models which are based on IPI, R-IPI, and FLIPI. Molecular or pharmacogenomic profiling can be used as new therapeutic targets for patients who are refractory to current therapy. We discus the utility of DNA microarray-based lymphoma profiling in clinical oncology research, and identify future of research in lymphoma evolving fields.

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