University of Cincinnati (UC) researchers played a pivotal role in two recent cancer studies in which he used bioinformatics—specifically, public domain genomics data—to help identify a tumor suppressor gene’s role in human cancers. The approach took the work out of animal models and moved it into computer analysis.
Bioinformatics is a relatively new field of science which incorporates biology, statistics, computer science and information technology. By using large data sets and new statistical models, scientists can make discoveries or learn new insights into human disease.
Mario Medvedovic, PhD, an associate professor in the department of environmental health at the UC College of Medicine, and Jing Chen, PhD, research scientist in Medvedovic’s group, co-authored two recent National Institutes of Health-supported studies appearing in Cell and Proceedings of the National Academy of Sciences. Both studies relied on bioinformatics analysis of genomics data.
"An interesting aspect from our angle is that in both papers we used public domain genomics data to connect experimental genomics data from in vivo and in vitro models to human diseases,” says Medvedovic, whose lab has been actively gathering and processing public domain genomics data and developing bioinformatics to analyze these data. It has created web servers where anyone can go and mine these data. (http://GenomicsPortals.org and http://LincsGenomics.org)
"Re-use of public domain genomics datasets is a pretty hot topic locally and nationally.” (The U.S. Supreme Court recently heard arguments for and against patenting of human genome data. A decision is expected in June.)
Tumor Suppressors and Cancer
Much of our understanding of cancer comes from research that uncovers the molecular interactions underlying this disease. The discovery of tumor suppressor genes that control cell division and growth provides great insight into how cancer develops.
Tumor suppressors are viewed as protective genes that prevent the uncontrollable division of cells, a hallmark of cancer development. A disruption in the function of these genes can catapult cancer progression. Protein Kinase C zeta (PKC zeta) is a tumor suppressor known to play a role in different human cancers. A mutated form of PKC zeta found in people is associated with tumor development.
The exact mechanism by which PKC zeta (or lack of) affects the progression of cancer is not well understood. Recently, a team of researchers led by scientists at Sanford-Burnham Medical Research Institute identified PKC zeta’s role in prostate cancer and its mechanism of action. The same authors previously published a paper demonstrating PKC zeta to be a tumor suppressor in human and mouse intestinal cancer.
This Research: Before Bioinformatics
Prior to utilizing public domain genomics data and bioinformatics, the researchers used a mouse model deficient in tumor suppressor PTEN, which predisposes the mouse to cancer, to determine PKC zeta’s role in prostate cancer. Using this model, the researchers found that the loss of PKC zeta resulted in prostate cancer. These results directed them to establish PKC zeta’s role in human prostate cancer in the context of PTEN deficiency.
They also analyzed protein expression of PTEN and PKC zeta in human prostate cancer tissue samples and saw that there was a positive correlation between the expression of two tumor suppressors.
Using Public Domain Datasets
The researchers wanted to further assess the PTEN-dependent role of PKC zeta in normal prostate tissues, primary cancer and metastatic primary cancer tissue. With the help of Medvedovic and Chen, the team was able to establish PKC zeta’s role in human prostate cancer through bioinformatics analysis.
By mining their collection of genomics datasets, Medvedovic and Chen determined the appropriate human prostate cancer dataset to use, which provided information about gene-level changes in prostate cancer. The results of this analysis showed that reduction in expression levels of PKC zeta in metastatic cancers is dependent on a decrease in PTEN expression levels. This supported previous findings on PKC zeta’s role in colorectal cancer, and from there, the researchers were able to explore even deeper the cellular mechanism of PKC zeta in prostate cancer.
To investigate the molecular mechanisms by which PKC zeta restrains prostate cancer, researchers performed a genome-wide transcriptome analysis and identified genes that are differentially expressed between cells without PKC zeta and cells with PKC zeta. Expression levels of these genes were then used to cluster samples in the human prostate cancer datasets.
The researchers found similarities among the altered genes in cells and tumors without PKC zeta when compared with normal tissue. Bioinformatics analysis of the altered genes showed that they are involved in proliferation, growth, movement and cell death, suggesting that, when present, PKC zeta plays a role in preventing progression of prostate cancer, invasion and metastasis.
Further analysis of these differentially expressed gene signatures led to the identification of another gene
(c-Myc) as a relevant target of PKC zeta. Levels of c-Myc increase when PKC zeta is absent, and this was confirmed in the prostates of the PTEN mouse model deficient in PKC zeta. These data suggest that the loss of PKC zeta results in increased levels of c-Myc, subsequently affecting cell proliferation and growth.
Medvedovic and Chen then used a public domain ChIP-seq dataset and their own bioinformatics technique for analysis of transcription factor DNA-binding patterns to identify c-Myc targets. They found that genes upregulated in cells without PKC zeta tend to be targets of c-Myc, further underscoring the idea that PKC zeta negatively regulates c-Myc to prevent cancer. The researchers hypothesized that PKC zeta not only repressed the gene levels of c-Myc but also repressed by directly acting on c-Myc.
The application of bioinformatics tools allowed the researchers to:
• Correlate the PTEN-dependent role of PKC zeta to human prostate cancer.
• Identify and categorize genes regulated by PKC zeta.
• Identify the clinically relevant target of PKC zeta, c-Myc.
• Provide supporting evidence that PKC zeta regulates cell division and growth by negatively regulating c-Myc, thereby preventing the development of cancer.
"Prostate cancer is the most common malignancy among men in Western countries,” the authors write. "Our observations that PKC zeta is a tumor suppressor in this type of neoplasia, and that it acts by repressing c-Myc expression and function, are likely to be highly relevant in the design of new therapeutic approaches, which are sorely needed.”
Adds Medvedovic: "The vast amount of diverse public domain genomics datasets provide a tremendous opportunity to test and postulate new hypotheses by simply re-analyzing other people’s data. Such data can also be used to better interpret results of laboratory experiments and increase their impact by making a connection with human disease.”
Medvedovic is a member of the UC Cancer Institute. Both Medvedovic and Chen work with UC’s Center for Clinical and Translational Science and Training (CCTST) to assist investigators with bioinformatics analyses. The CCTST is the academic home of UC’s institutional Clinical and Translational Science Award (CTSA) from the National Institutes of Health.
Jessica Dade is a fourth-year graduate student in molecular genetics, biochemistry and microbiology with an interest in science writing. She participated in UC’s summer research program in 2008 and began her graduate work at the university the following year. She is working in a lab at the Cincinnati Department of Veterans Affairs under the direction of George Deepe, MD, and George Smulian, MD, both of UC’s infectious diseases division.
Mario Medvedovic, PhD, an associate professor in the department of environmental health at the UC College of Medicine, and Jing Chen, PhD, research scientist in Medvedovic’s group, co-authored two recent National Institutes of Health-supported studies appearing in Cell and Proceedings of the National Academy of Sciences. Both studies relied on bioinformatics analysis of genomics data.
"An interesting aspect from our angle is that in both papers we used public domain genomics data to connect experimental genomics data from in vivo and in vitro models to human diseases,” says Medvedovic, whose lab has been actively gathering and processing public domain genomics data and developing bioinformatics to analyze these data. It has created web servers where anyone can go and mine these data. (http://GenomicsPortals.org and http://LincsGenomics.org)
"Re-use of public domain genomics datasets is a pretty hot topic locally and nationally.” (The U.S. Supreme Court recently heard arguments for and against patenting of human genome data. A decision is expected in June.)
Tumor Suppressors and Cancer
Much of our understanding of cancer comes from research that uncovers the molecular interactions underlying this disease. The discovery of tumor suppressor genes that control cell division and growth provides great insight into how cancer develops.
Tumor suppressors are viewed as protective genes that prevent the uncontrollable division of cells, a hallmark of cancer development. A disruption in the function of these genes can catapult cancer progression. Protein Kinase C zeta (PKC zeta) is a tumor suppressor known to play a role in different human cancers. A mutated form of PKC zeta found in people is associated with tumor development.
The exact mechanism by which PKC zeta (or lack of) affects the progression of cancer is not well understood. Recently, a team of researchers led by scientists at Sanford-Burnham Medical Research Institute identified PKC zeta’s role in prostate cancer and its mechanism of action. The same authors previously published a paper demonstrating PKC zeta to be a tumor suppressor in human and mouse intestinal cancer.
This Research: Before Bioinformatics
Prior to utilizing public domain genomics data and bioinformatics, the researchers used a mouse model deficient in tumor suppressor PTEN, which predisposes the mouse to cancer, to determine PKC zeta’s role in prostate cancer. Using this model, the researchers found that the loss of PKC zeta resulted in prostate cancer. These results directed them to establish PKC zeta’s role in human prostate cancer in the context of PTEN deficiency.
They also analyzed protein expression of PTEN and PKC zeta in human prostate cancer tissue samples and saw that there was a positive correlation between the expression of two tumor suppressors.
Using Public Domain Datasets
The researchers wanted to further assess the PTEN-dependent role of PKC zeta in normal prostate tissues, primary cancer and metastatic primary cancer tissue. With the help of Medvedovic and Chen, the team was able to establish PKC zeta’s role in human prostate cancer through bioinformatics analysis.
By mining their collection of genomics datasets, Medvedovic and Chen determined the appropriate human prostate cancer dataset to use, which provided information about gene-level changes in prostate cancer. The results of this analysis showed that reduction in expression levels of PKC zeta in metastatic cancers is dependent on a decrease in PTEN expression levels. This supported previous findings on PKC zeta’s role in colorectal cancer, and from there, the researchers were able to explore even deeper the cellular mechanism of PKC zeta in prostate cancer.
To investigate the molecular mechanisms by which PKC zeta restrains prostate cancer, researchers performed a genome-wide transcriptome analysis and identified genes that are differentially expressed between cells without PKC zeta and cells with PKC zeta. Expression levels of these genes were then used to cluster samples in the human prostate cancer datasets.
The researchers found similarities among the altered genes in cells and tumors without PKC zeta when compared with normal tissue. Bioinformatics analysis of the altered genes showed that they are involved in proliferation, growth, movement and cell death, suggesting that, when present, PKC zeta plays a role in preventing progression of prostate cancer, invasion and metastasis.
Further analysis of these differentially expressed gene signatures led to the identification of another gene
(c-Myc) as a relevant target of PKC zeta. Levels of c-Myc increase when PKC zeta is absent, and this was confirmed in the prostates of the PTEN mouse model deficient in PKC zeta. These data suggest that the loss of PKC zeta results in increased levels of c-Myc, subsequently affecting cell proliferation and growth.
Medvedovic and Chen then used a public domain ChIP-seq dataset and their own bioinformatics technique for analysis of transcription factor DNA-binding patterns to identify c-Myc targets. They found that genes upregulated in cells without PKC zeta tend to be targets of c-Myc, further underscoring the idea that PKC zeta negatively regulates c-Myc to prevent cancer. The researchers hypothesized that PKC zeta not only repressed the gene levels of c-Myc but also repressed by directly acting on c-Myc.
The application of bioinformatics tools allowed the researchers to:
• Correlate the PTEN-dependent role of PKC zeta to human prostate cancer.
• Identify and categorize genes regulated by PKC zeta.
• Identify the clinically relevant target of PKC zeta, c-Myc.
• Provide supporting evidence that PKC zeta regulates cell division and growth by negatively regulating c-Myc, thereby preventing the development of cancer.
"Prostate cancer is the most common malignancy among men in Western countries,” the authors write. "Our observations that PKC zeta is a tumor suppressor in this type of neoplasia, and that it acts by repressing c-Myc expression and function, are likely to be highly relevant in the design of new therapeutic approaches, which are sorely needed.”
Adds Medvedovic: "The vast amount of diverse public domain genomics datasets provide a tremendous opportunity to test and postulate new hypotheses by simply re-analyzing other people’s data. Such data can also be used to better interpret results of laboratory experiments and increase their impact by making a connection with human disease.”
Medvedovic is a member of the UC Cancer Institute. Both Medvedovic and Chen work with UC’s Center for Clinical and Translational Science and Training (CCTST) to assist investigators with bioinformatics analyses. The CCTST is the academic home of UC’s institutional Clinical and Translational Science Award (CTSA) from the National Institutes of Health.
Jessica Dade is a fourth-year graduate student in molecular genetics, biochemistry and microbiology with an interest in science writing. She participated in UC’s summer research program in 2008 and began her graduate work at the university the following year. She is working in a lab at the Cincinnati Department of Veterans Affairs under the direction of George Deepe, MD, and George Smulian, MD, both of UC’s infectious diseases division.
Media Contact: AHC Public Relations, (513) 558-4553
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