Janelle N. Ruiz Assignment 11: Difference between revisions
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==Outline== | ==Outline== | ||
===Introduction=== | |||
*Prostate cancer is the most common cancer in the United States affecting over 198,000 individuals in 2001 | |||
*Recently, increase in proportion of patients diagnosed with tumors confined to the prostate gland alone | |||
#Results of increased public awareness and early detection and measurement of PSA levels in blood | |||
#Early disease is genetically heterogeneous because many patients have a slow-moving cancer (more likely to survive) | |||
*Once metastatic disease develops, majority of patients die | |||
*Prostate cancer now considered in a series of stages of disease: metastasized and localized tumors | |||
#Understanding biological basis of differences in stages is crucial to assess prognosis, therapy, and treatment. | |||
*Tumor metastasis = most clinically significant (i.e. deadly) event in prostate cancer development | |||
#Requires that cancer cell participate in specific interactions between itself and host | |||
#Cells from primary tumors must detach, invade stromal tissue, and penetrate vessels in order to spread themselves throughout the body | |||
#Must survive this circulation step in order to reach next site in which they stop or bind to tissue | |||
#To form tumors outside prostate, cancer cells must multiply in the new tissue and obtain a blood supply | |||
#The tumor cells that are selected for those which are most "fit" -- this process involves many genes and transcriptional programs | |||
*Purpose of study: Identification of genes, gene expression profiles, and biological pathways which contribute to metastasis | |||
#This is important to improve tumor identification and therapy | |||
#To do this, authors performed genome-wide expression analysis and identified differences in gene expression between primary and metastatic prostate cancers | |||
===Materials and Methods=== | |||
- Samples: | |||
○ Tissues from | |||
§ 3 non-cancerous prostates (controls) | |||
§ 23 primary prostate cancers | |||
§ 9 metastatic prostate cancers | |||
○ Each tissue examined histologically using H&E-stained cryostat sections | |||
- Gene Expression Analysis: | |||
○ RNA was extracted from tissues | |||
○ Complimentary DNA synthesized from total RNA labeled with biotinylated nucleotides | |||
○ Gene expression analysis carried out using Affymetrix U95 gene arrays with 63,175 features for individual gene/EST clusters | |||
§ Five distinct microarrays, each containing probes for ~12,000 unique genes/EST transcripts | |||
§ Two response measures: Average Difference (primary measure of expression levels) and Absolute Call (secondary measure of expression level) extracted fro each gene on every sample | |||
§ Expression values on each array scaled to have avg expression of 2500 | |||
- Data Analysis: | |||
○ Scanned image files analyzed using Microarray Suite v4.0 | |||
○ Differential expression (DE) filtered to include only those with mean expression values that differed at least 3-fold between groups. DE evaluated using: | |||
§ First probed were ranked based on magnitude of difference b/w means of two sample sets | |||
§ Second, datasets normalized by standardizing each gene to mean = 0 and variance = 1 | |||
§ Clustering and result display performed using Cluster and TreeView software | |||
§ Specific genes corresponding to Unigene clusters identified using GenBank of the clone used to produce probe set | |||
- Immunohistochemistry: | |||
○ Tissue prepared using tissue arrayer | |||
○ Immunohistochemical detection carried out using standard methods | |||
- Quantitative Reverse Transcriptase-PCR: | |||
○ Q RT-PCR: | |||
§ Utilized SYBR Green system | |||
○ Measured mRNA expression levels quantitatively | |||
- Results: | |||
○ Gene Expression Analysis Using Oligonucleotide Arrays: | |||
§ Analyzed gene expression using hybridization of RNA target to oligonucleotide microarrays with 63,175 features for gene/EST clusters | |||
§ Highest proportion of expressed genes represented by probe sets on U95A microarray corresponding to genes with near full-length cDNAs | |||
○ Identification of Differentially Expressed Genes: | |||
§ Compared 14 tumors from patients that did not recur with 9 metastatic prostate cancer to see differences | |||
§ Expression data first filtered to include only probe sets detecting genes with mean expression levels that differed by at least three-fold between two groups -- a total of 3,436 probe sets were found to contain differences of this magnitude | |||
§ Probes then ranked based on relative magnitude of different (t test) between the means | |||
§ Of the probe sets for full-length genes, 132 were over-expressed in primary tumors and 360 in metastatic tumors (100 most highly ranked tumor genes based on t test listed in Table 2) | |||
○ Functional Attributes of Differentially Expressed Genes: | |||
§ Based on review of literature, assigned general molecular or biological function to each gene (Table 2) | |||
§ These reflect biological differences between primary and metastatic tumors | |||
§ 26 of 100 high ranked genes play some role in cell cycle regulation, DNA replication and repair, or mitosis | |||
□ Examples: RFC5, TOP2A, etc - known to be up-regulated in highly proliferative cells | |||
§ 15 of 100 corresponded to genes known to be involved in signaling an signal transduction | |||
§ 9 of 100 may contribute to cell adhesion, migration, or extracellular matrix | |||
□ Ex: HMMR -- encodes extracellular matrix binding protein which pays a role in cell motility through RAS-ERK signaling pathway | |||
§ Large proportion of 100 believed to be involved in regulation of gene expression and gene product function | |||
□ 13 encode trxn factors, components of transcriptional complex, or other protein contributing to regulation of trxn | |||
□ 3 encode products which participate in RNA splicing or metabolism | |||
□ 3 encode products which participate in chromatin modifications - may also impact trxn regulation | |||
□ 5 contribute to post-trxn regulation of protein function | |||
□ Findings suggest that progression of metastatic prostate cancer associated with changes in gene expression levels related to cell proliferation, interaction with micro-environment, cell motility, activated signal transduction pathways, and regulation of gene product synthesis and function | |||
§ Validation: | |||
□ Gene expression values validated by: | |||
® Some gene transcripts represented by more than one probe set (each detected similar levels of expression) | |||
® Cancer Genome Anatoy Project verified expression of many genes | |||
® Q-RT-PCR -- some of 100 genes selected and measured for transcript levels using Q-RT-PCR --results in agreement with relative levels of microarray gene expression | |||
® Immunohisotchemical analysis of tumor samples: established protein expression levels of select 100 correlated with mRNA levels from microarray | |||
® Several genes identified have already been previously shown to be differentially expressed in metastatic prostate cancer | |||
○ Table 1: Clinical and Pathological Features of Prostate Carcinomas | |||
○ Figure 1: Representative gene expression clusters enriched for genes differentially expressed between primary (blue boxes) and metastatic (orange boxes) prostate carcinomas | |||
○ Table 2: 100 highest ranked differentially expressed genes and functional classification | |||
○ Figure 2: Proliferation indices for prostate carcinoma samples | |||
§ A: Dendrogram showing overall similarity of gene expression profiles. Blue boxes represent primary tumors and orange boxes represent metastatic tumors | |||
§ B: Bar graph representing proliferation indices based on Ki67 immunohistochemistry | |||
§ C: Section of multitissue block of primary prostate carcinomas immunostained for Ki67 | |||
○ Figure 3: Comparison of relative expression values for selected differentially expressed genes based on Q-RT-PCR and microarray analysis | |||
Discussion | |||
- Few prior studies have used high-throughput gene expression analysis to study prostate cancer metastasis and differences in gene expression between non-progressive and progressive tumors | |||
§ Why? | |||
§ Well-preserved surgical samples are rare -- limiting availability | |||
- Previous studies with high-throughput analysis have revealed similar differentially expressed gene expression levels: Partial agreement despite different methodology= encouraging and helps validate results | |||
§ One study (comparing fewer samples): 5 of 9 genes found to be commonly differentially expressed agreed with data here | |||
§ Another study: two of genes over-expressed in metastatic cancer as compared with primary prostate cancer agreed with data presented here | |||
§ Another study: two of five genes identified as differentially over-expressed in aggressive cancer agreed with findings here | |||
- Predicted function of differentially expressed genes gives insight into biology of prostate cancer progression | |||
§ Differentially expressed genes reflect biological distinctions and functional pathways previously implicated in aggressive disease | |||
- Some of genes differentially expressed may identity critical functional pathways: | |||
§ Ex: MYBL2 -- over expressed in many metastatic tumors -- activate CDC2 gene expression in proliferating fibroblasts --> catalytic subunit of protein kinase complex that induces entry into mitosis (cyclin E modulates functional activity of these genes) | |||
§ This pathway may be critical component of cell cycle regulation in metastatic prostate cancer because all elements of pathway over-expressed in metastatic cells | |||
§ This may serve as therapeutic target | |||
- Analysis reveled hundreds of poorly characterized EST clusters that likely represent novel genes of unknown function | |||
§ Biological activity of these genes can be inferred from other known genes with shared expression patterns | |||
§ Many are likely to play important roles to those predicted for known gene products (described above) | |||
- Next Steps: determine function of unknown genes will provide new insights into biology of prostate cancer |
Revision as of 15:38, 10 April 2010
Vocabulary
- Heterogeneous: consisting of elements that are not of the same kind or nature http://www.google.com/search?rlz=1C1SNNT_enUS360US361&sourceid=chrome&ie=UTF-8&q=define%3A+heterogeneous
- Prostate-specific antigen (PSA) is a protein produced by cells of the prostate gland. The PSA test measures the level of PSA in the blood. The higher a man’s PSA level, the more likely it is that cancer is present, but there are other possible reasons for an elevated PSA level http://www.cancer.gov/cancertopics/factsheet/Detection/PSA
- Indolent: sluggish, slow to develop www.sfaf.org/custom/glossary.aspx
- Stroma - The supportive framework of an organ (or gland or other structure), usually composed of connective tissue http://www.google.com/search?rlz=1C1SNNT_enUS360US361&sourceid=chrome&ie=UTF-8&q=define%3Astromal
- Dissemination - the property of being diffused or dispersed http://www.google.com/search?hl=en&rlz=1C1SNNT_enUS360US361&q=define%3Adisseminate.&btnG=Search
- Fibroblast: - a cell from which connective tissue develop http://www.google.com/search?hl=en&rlz=1C1SNNT_enUS360US361&q=define%3Afibroblasts&btnG=Search
- Metastasis - the spreading of a disease (especially cancer) to another part of the body wordnetweb.princeton.edu/perl/webwn
- Prostatectomy: surgical removal of part or all of the prostate gland wordnetweb.princeton.edu/perl/webwn
- Transduction: the transformation of sensory stimulus energy into a cellular signal, such as a receptor potential www.macalester.edu/psychology/whathap/ubnrp/smell/definitions.html
- Immunohistochemistry - an assay that shows specific antigens in tissues by the use of markers that are either fluorescent dyes or enzymes (such as horseradish peroxidase) wordnetweb.princeton.edu/perl/webwn
Outline
Introduction
- Prostate cancer is the most common cancer in the United States affecting over 198,000 individuals in 2001
- Recently, increase in proportion of patients diagnosed with tumors confined to the prostate gland alone
- Results of increased public awareness and early detection and measurement of PSA levels in blood
- Early disease is genetically heterogeneous because many patients have a slow-moving cancer (more likely to survive)
- Once metastatic disease develops, majority of patients die
- Prostate cancer now considered in a series of stages of disease: metastasized and localized tumors
- Understanding biological basis of differences in stages is crucial to assess prognosis, therapy, and treatment.
- Tumor metastasis = most clinically significant (i.e. deadly) event in prostate cancer development
- Requires that cancer cell participate in specific interactions between itself and host
- Cells from primary tumors must detach, invade stromal tissue, and penetrate vessels in order to spread themselves throughout the body
- Must survive this circulation step in order to reach next site in which they stop or bind to tissue
- To form tumors outside prostate, cancer cells must multiply in the new tissue and obtain a blood supply
- The tumor cells that are selected for those which are most "fit" -- this process involves many genes and transcriptional programs
- Purpose of study: Identification of genes, gene expression profiles, and biological pathways which contribute to metastasis
- This is important to improve tumor identification and therapy
- To do this, authors performed genome-wide expression analysis and identified differences in gene expression between primary and metastatic prostate cancers
Materials and Methods
- Samples: ○ Tissues from § 3 non-cancerous prostates (controls) § 23 primary prostate cancers § 9 metastatic prostate cancers ○ Each tissue examined histologically using H&E-stained cryostat sections - Gene Expression Analysis: ○ RNA was extracted from tissues ○ Complimentary DNA synthesized from total RNA labeled with biotinylated nucleotides ○ Gene expression analysis carried out using Affymetrix U95 gene arrays with 63,175 features for individual gene/EST clusters § Five distinct microarrays, each containing probes for ~12,000 unique genes/EST transcripts § Two response measures: Average Difference (primary measure of expression levels) and Absolute Call (secondary measure of expression level) extracted fro each gene on every sample § Expression values on each array scaled to have avg expression of 2500 - Data Analysis: ○ Scanned image files analyzed using Microarray Suite v4.0 ○ Differential expression (DE) filtered to include only those with mean expression values that differed at least 3-fold between groups. DE evaluated using: § First probed were ranked based on magnitude of difference b/w means of two sample sets § Second, datasets normalized by standardizing each gene to mean = 0 and variance = 1 § Clustering and result display performed using Cluster and TreeView software § Specific genes corresponding to Unigene clusters identified using GenBank of the clone used to produce probe set - Immunohistochemistry: ○ Tissue prepared using tissue arrayer ○ Immunohistochemical detection carried out using standard methods - Quantitative Reverse Transcriptase-PCR: ○ Q RT-PCR: § Utilized SYBR Green system ○ Measured mRNA expression levels quantitatively
- Results: ○ Gene Expression Analysis Using Oligonucleotide Arrays: § Analyzed gene expression using hybridization of RNA target to oligonucleotide microarrays with 63,175 features for gene/EST clusters § Highest proportion of expressed genes represented by probe sets on U95A microarray corresponding to genes with near full-length cDNAs ○ Identification of Differentially Expressed Genes: § Compared 14 tumors from patients that did not recur with 9 metastatic prostate cancer to see differences § Expression data first filtered to include only probe sets detecting genes with mean expression levels that differed by at least three-fold between two groups -- a total of 3,436 probe sets were found to contain differences of this magnitude § Probes then ranked based on relative magnitude of different (t test) between the means § Of the probe sets for full-length genes, 132 were over-expressed in primary tumors and 360 in metastatic tumors (100 most highly ranked tumor genes based on t test listed in Table 2) ○ Functional Attributes of Differentially Expressed Genes: § Based on review of literature, assigned general molecular or biological function to each gene (Table 2) § These reflect biological differences between primary and metastatic tumors § 26 of 100 high ranked genes play some role in cell cycle regulation, DNA replication and repair, or mitosis □ Examples: RFC5, TOP2A, etc - known to be up-regulated in highly proliferative cells § 15 of 100 corresponded to genes known to be involved in signaling an signal transduction § 9 of 100 may contribute to cell adhesion, migration, or extracellular matrix □ Ex: HMMR -- encodes extracellular matrix binding protein which pays a role in cell motility through RAS-ERK signaling pathway § Large proportion of 100 believed to be involved in regulation of gene expression and gene product function □ 13 encode trxn factors, components of transcriptional complex, or other protein contributing to regulation of trxn □ 3 encode products which participate in RNA splicing or metabolism □ 3 encode products which participate in chromatin modifications - may also impact trxn regulation □ 5 contribute to post-trxn regulation of protein function □ Findings suggest that progression of metastatic prostate cancer associated with changes in gene expression levels related to cell proliferation, interaction with micro-environment, cell motility, activated signal transduction pathways, and regulation of gene product synthesis and function § Validation: □ Gene expression values validated by: ® Some gene transcripts represented by more than one probe set (each detected similar levels of expression) ® Cancer Genome Anatoy Project verified expression of many genes ® Q-RT-PCR -- some of 100 genes selected and measured for transcript levels using Q-RT-PCR --results in agreement with relative levels of microarray gene expression ® Immunohisotchemical analysis of tumor samples: established protein expression levels of select 100 correlated with mRNA levels from microarray ® Several genes identified have already been previously shown to be differentially expressed in metastatic prostate cancer ○ Table 1: Clinical and Pathological Features of Prostate Carcinomas ○ Figure 1: Representative gene expression clusters enriched for genes differentially expressed between primary (blue boxes) and metastatic (orange boxes) prostate carcinomas ○ Table 2: 100 highest ranked differentially expressed genes and functional classification ○ Figure 2: Proliferation indices for prostate carcinoma samples § A: Dendrogram showing overall similarity of gene expression profiles. Blue boxes represent primary tumors and orange boxes represent metastatic tumors § B: Bar graph representing proliferation indices based on Ki67 immunohistochemistry § C: Section of multitissue block of primary prostate carcinomas immunostained for Ki67 ○ Figure 3: Comparison of relative expression values for selected differentially expressed genes based on Q-RT-PCR and microarray analysis
Discussion
- Few prior studies have used high-throughput gene expression analysis to study prostate cancer metastasis and differences in gene expression between non-progressive and progressive tumors § Why? § Well-preserved surgical samples are rare -- limiting availability - Previous studies with high-throughput analysis have revealed similar differentially expressed gene expression levels: Partial agreement despite different methodology= encouraging and helps validate results § One study (comparing fewer samples): 5 of 9 genes found to be commonly differentially expressed agreed with data here § Another study: two of genes over-expressed in metastatic cancer as compared with primary prostate cancer agreed with data presented here § Another study: two of five genes identified as differentially over-expressed in aggressive cancer agreed with findings here - Predicted function of differentially expressed genes gives insight into biology of prostate cancer progression § Differentially expressed genes reflect biological distinctions and functional pathways previously implicated in aggressive disease - Some of genes differentially expressed may identity critical functional pathways: § Ex: MYBL2 -- over expressed in many metastatic tumors -- activate CDC2 gene expression in proliferating fibroblasts --> catalytic subunit of protein kinase complex that induces entry into mitosis (cyclin E modulates functional activity of these genes) § This pathway may be critical component of cell cycle regulation in metastatic prostate cancer because all elements of pathway over-expressed in metastatic cells § This may serve as therapeutic target - Analysis reveled hundreds of poorly characterized EST clusters that likely represent novel genes of unknown function § Biological activity of these genes can be inferred from other known genes with shared expression patterns § Many are likely to play important roles to those predicted for known gene products (described above) - Next Steps: determine function of unknown genes will provide new insights into biology of prostate cancer