Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data
Programmed cell death (PCD), or cell suicide, encompasses multiple pathways including apoptosis and autophagy and is essential for development, cellular homeostasis, and prevention of cancer cell growth. I describe here the development and use of bioinformatic methods to identify and analyze gene...
Main Author: | |
---|---|
Language: | English |
Published: |
2010
|
Online Access: | http://hdl.handle.net/2429/18261 |
id |
ndltd-UBC-oai-circle.library.ubc.ca-2429-18261 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-UBC-oai-circle.library.ubc.ca-2429-182612018-01-05T17:39:21Z Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data Pleasance, Erin Dael Programmed cell death (PCD), or cell suicide, encompasses multiple pathways including apoptosis and autophagy and is essential for development, cellular homeostasis, and prevention of cancer cell growth. I describe here the development and use of bioinformatic methods to identify and analyze genes involved in PCD, both in the model organism Drosophila melanogaster and in human cancer, by analysis of large-scale gene expression data. An approach was developed to correctly identify genes from serial analysis of gene expression (SAGE) data, distinguish the set of genes not accessible to the SAGE method, and determine the optimal set of enzymes for Drosophila, C. elegans, and human SAGE library construction. In Drosophila metamorphosis the salivary gland undergoes autophagic PCD, whereby cellular components are engulfed and degraded by cytoplasmic vacuoles, with additional hallmarks of apoptosis. This is an excellent model in which to study the genes involved in PCD. Transcriptional profiling of this tissue by expressed sequence tags (ESTs) and serial analysis of gene expression (SAGE) identified many genes differentially regulated prior to cell death, including genes known to be death regulators, genes in related pathways, genes of no known function, and potentially novel unannotated genes. The PCD-associated genes found in this analysis were then used to identify similar genes in the human genome that are differentially expressed in cancer, which have the potential to be involved in PCD and in oncogenesis. The pattern of genes expressed suggests a role for autophagy-associated processes in cancer progression. To examine this further, expression of the autophagy gene LC3 was examined in multiple cancer types, subtypes, and stages. LC3 expression is decreased significantly in several cancer types and also during cancer progression, suggesting a tissue- and stage-specific role for autophagy in regulating oncogenesis. Medicine, Faculty of Medical Genetics, Department of Graduate 2010-01-16T17:29:54Z 2010-01-16T17:29:54Z 2006 2006-05 Text Thesis/Dissertation http://hdl.handle.net/2429/18261 eng For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
collection |
NDLTD |
language |
English |
sources |
NDLTD |
description |
Programmed cell death (PCD), or cell suicide, encompasses multiple pathways including
apoptosis and autophagy and is essential for development, cellular homeostasis, and prevention
of cancer cell growth. I describe here the development and use of bioinformatic methods to
identify and analyze genes involved in PCD, both in the model organism Drosophila
melanogaster and in human cancer, by analysis of large-scale gene expression data. An approach
was developed to correctly identify genes from serial analysis of gene expression (SAGE) data,
distinguish the set of genes not accessible to the SAGE method, and determine the optimal set of
enzymes for Drosophila, C. elegans, and human SAGE library construction. In Drosophila
metamorphosis the salivary gland undergoes autophagic PCD, whereby cellular components are
engulfed and degraded by cytoplasmic vacuoles, with additional hallmarks of apoptosis. This is
an excellent model in which to study the genes involved in PCD. Transcriptional profiling of this
tissue by expressed sequence tags (ESTs) and serial analysis of gene expression (SAGE)
identified many genes differentially regulated prior to cell death, including genes known to be
death regulators, genes in related pathways, genes of no known function, and potentially novel
unannotated genes. The PCD-associated genes found in this analysis were then used to identify
similar genes in the human genome that are differentially expressed in cancer, which have the
potential to be involved in PCD and in oncogenesis. The pattern of genes expressed suggests a
role for autophagy-associated processes in cancer progression. To examine this further,
expression of the autophagy gene LC3 was examined in multiple cancer types, subtypes, and
stages. LC3 expression is decreased significantly in several cancer types and also during cancer
progression, suggesting a tissue- and stage-specific role for autophagy in regulating oncogenesis. === Medicine, Faculty of === Medical Genetics, Department of === Graduate |
author |
Pleasance, Erin Dael |
spellingShingle |
Pleasance, Erin Dael Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
author_facet |
Pleasance, Erin Dael |
author_sort |
Pleasance, Erin Dael |
title |
Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
title_short |
Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
title_full |
Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
title_fullStr |
Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
title_full_unstemmed |
Identification and analysis of programmed cell death genes in Drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
title_sort |
identification and analysis of programmed cell death genes in drosophila melanogaster and human cancer using bioinformatic analysis of gene expression data |
publishDate |
2010 |
url |
http://hdl.handle.net/2429/18261 |
work_keys_str_mv |
AT pleasanceerindael identificationandanalysisofprogrammedcelldeathgenesindrosophilamelanogasterandhumancancerusingbioinformaticanalysisofgeneexpressiondata |
_version_ |
1718590777618071552 |