Limits...
Proteogenomic convergence for understanding cancer pathways and networks.

Boja ES, Rodriguez H - Clin Proteomics (2014)

Bottom Line: However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems.It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years.However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, 31 Center Drive, MSC 2580, 20892 Bethesda, MD, USA.

ABSTRACT
During the past several decades, the understanding of cancer at the molecular level has been primarily focused on mechanisms on how signaling molecules transform homeostatically balanced cells into malignant ones within an individual pathway. However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems. Recent technological advances in high throughput, deep sequencing for the human genomes and proteomic technologies to comprehensively characterize the human proteomes in conjunction with multiplexed targeted proteomic assays to measure panels of proteins involved in biologically relevant pathways have made significant progress in understanding cancer at the molecular level. It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years. However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks. With a critical link to genotypes (i.e., high throughput genomics and transcriptomics data), new and complementary information can be gleaned from multi-dimensional omics data to (1) assess the effect of genomic and transcriptomic aberrations on such complex molecular machinery in the context of cell signaling architectures associated with pathological diseases such as cancer (i.e., from genotype to proteotype to phenotype); and (2) target pathway- and network-driven changes and map the fluctuations of these functional units (proteins) responsible for cellular activities in response to perturbation in a spatiotemporal fashion to better understand cancer biology as a whole system.

No MeSH data available.


Related in: MedlinePlus

Linking cancer genotypes to cancer phenotypes. The comprehensive molecular level analysis at the DNA, RNA, protein and dynamic protein pathways and networks through proteogenomics and network modeling can greatly enhance our understanding of cancer systems biology (i.e., linking genotype to proteotype to cell/tissue phenotype).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4067069&req=5

Figure 1: Linking cancer genotypes to cancer phenotypes. The comprehensive molecular level analysis at the DNA, RNA, protein and dynamic protein pathways and networks through proteogenomics and network modeling can greatly enhance our understanding of cancer systems biology (i.e., linking genotype to proteotype to cell/tissue phenotype).

Mentions: What does this entail for proteomics and integrative biology? These rich datasets present an unprecedented opportunity for the research community to study cancer systems biology by linking cancer genotype to cancer phenotype through the understanding of cancer proteotype and the complex dysregulated signaling pathways and interaction networks. An example of the importance of such integrative analysis is shown by Wang, et al. where the corroboration of genomic aberrations at the protein level has been demonstrated with KRAS in pancreatic cancer in which targeted MRM-MS approach coupled with immunoprecipitation of intact RAS protein isoforms detected a single point mutation at the peptide level in KRAS oncogenes from a cell line, tumor sample and pancreatic cyst fluid at sensitivity of <25 fmol/mL [78]. While peptide-level mutation confirmation is crucial, the impact of such activating mutations on pancreatic cancer proteome was not evaluated. This requires a comprehensive characterization of wild-type and mutant KRAS proteomes including PTMs and subsequent integrative analysis of omics data superimposed on genes/proteins and their regulatory networks, signaling pathways and dynamics of operation. As illustrated in FigureĀ 1, a systematic and comprehensive molecular-level characterization (DNA, RNA and protein) could provide a specific context for important biological processes responsible for cell and tissue function, thereby shedding new light on how genomic instabilities and aberrations result in changes in dynamic protein signaling pathways and networks to give rise to its ultimate phenotypic behaviors.


Proteogenomic convergence for understanding cancer pathways and networks.

Boja ES, Rodriguez H - Clin Proteomics (2014)

Linking cancer genotypes to cancer phenotypes. The comprehensive molecular level analysis at the DNA, RNA, protein and dynamic protein pathways and networks through proteogenomics and network modeling can greatly enhance our understanding of cancer systems biology (i.e., linking genotype to proteotype to cell/tissue phenotype).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4067069&req=5

Figure 1: Linking cancer genotypes to cancer phenotypes. The comprehensive molecular level analysis at the DNA, RNA, protein and dynamic protein pathways and networks through proteogenomics and network modeling can greatly enhance our understanding of cancer systems biology (i.e., linking genotype to proteotype to cell/tissue phenotype).
Mentions: What does this entail for proteomics and integrative biology? These rich datasets present an unprecedented opportunity for the research community to study cancer systems biology by linking cancer genotype to cancer phenotype through the understanding of cancer proteotype and the complex dysregulated signaling pathways and interaction networks. An example of the importance of such integrative analysis is shown by Wang, et al. where the corroboration of genomic aberrations at the protein level has been demonstrated with KRAS in pancreatic cancer in which targeted MRM-MS approach coupled with immunoprecipitation of intact RAS protein isoforms detected a single point mutation at the peptide level in KRAS oncogenes from a cell line, tumor sample and pancreatic cyst fluid at sensitivity of <25 fmol/mL [78]. While peptide-level mutation confirmation is crucial, the impact of such activating mutations on pancreatic cancer proteome was not evaluated. This requires a comprehensive characterization of wild-type and mutant KRAS proteomes including PTMs and subsequent integrative analysis of omics data superimposed on genes/proteins and their regulatory networks, signaling pathways and dynamics of operation. As illustrated in FigureĀ 1, a systematic and comprehensive molecular-level characterization (DNA, RNA and protein) could provide a specific context for important biological processes responsible for cell and tissue function, thereby shedding new light on how genomic instabilities and aberrations result in changes in dynamic protein signaling pathways and networks to give rise to its ultimate phenotypic behaviors.

Bottom Line: However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems.It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years.However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks.

View Article: PubMed Central - HTML - PubMed

Affiliation: Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, 31 Center Drive, MSC 2580, 20892 Bethesda, MD, USA.

ABSTRACT
During the past several decades, the understanding of cancer at the molecular level has been primarily focused on mechanisms on how signaling molecules transform homeostatically balanced cells into malignant ones within an individual pathway. However, it is becoming more apparent that pathways are dynamic and crosstalk at different control points of the signaling cascades, making the traditional linear signaling models inadequate to interpret complex biological systems. Recent technological advances in high throughput, deep sequencing for the human genomes and proteomic technologies to comprehensively characterize the human proteomes in conjunction with multiplexed targeted proteomic assays to measure panels of proteins involved in biologically relevant pathways have made significant progress in understanding cancer at the molecular level. It is undeniable that proteomic profiling of differentially expressed proteins under many perturbation conditions, or between normal and "diseased" states is important to capture a first glance at the overall proteomic landscape, which has been a main focus of proteomics research during the past 15-20 years. However, the research community is gradually shifting its heavy focus from that initial discovery step to protein target verification using multiplexed quantitative proteomic assays, capable of measuring changes in proteins and their interacting partners, isoforms, and post-translational modifications (PTMs) in response to stimuli in the context of signaling pathways and protein networks. With a critical link to genotypes (i.e., high throughput genomics and transcriptomics data), new and complementary information can be gleaned from multi-dimensional omics data to (1) assess the effect of genomic and transcriptomic aberrations on such complex molecular machinery in the context of cell signaling architectures associated with pathological diseases such as cancer (i.e., from genotype to proteotype to phenotype); and (2) target pathway- and network-driven changes and map the fluctuations of these functional units (proteins) responsible for cellular activities in response to perturbation in a spatiotemporal fashion to better understand cancer biology as a whole system.

No MeSH data available.


Related in: MedlinePlus