SNP microarray cases:	Prostate cancer	Pharmacogenomics	Cardiac disease	Resistance to HIV infection
Expression microarray cases:	Breast cancer	Melanoma	Herpes

Background:  Microarrays perform the simultaneous detection of thousands of DNA sequences.  Single-stranded DNA probes are spotted onto a small chip, and a labeled DNA sample is added. Matching sequences will hybridize, and the label (e.g. fluorescence) will be detected on the spots corresponding to probes that match the sample’s sequences. The Case It software displays a representative 64-spot section from a microarray chip, so that students can view the fluorescence data used to analyze the samples.

The Case It software simulates two types of microarrays, SNP microarrays detect single nucleotide polymorphisms in DNA samples.  SNP chips contain pairs of probes containing a single nucleotide difference between them.  DNA samples are tested for their ability to bind to one or both probes, as measured by the amount of fluorescence detected on each probe spot.  The genotype of each sample is determined by the relative amount of fluorescence bound to each probe in a SNP pair.  Genotypes may be homozygous for one or the other SNP, or they may be heterozygous. SNPs are associated with a variety of conditions, including disease susceptibility or resistance, and can be used for diagnosis or for research into understanding disease mechanisms.  The SNPs in these cases are identified by the dbSNP ID names, beginning with the designation “rs” followed by a number.

Expression microarrays measure levels of gene expression in cells and tissues under specific conditions, based on the amount of RNA transcribed from the genes.  RNA isolated from the samples is copied into cDNA, incorporating a fluorescent label.  DNA from control is typically labeled with a green dye, while DNA from experimental samples is labeled red.  A control and an experimental sample are mixed and added to a chip containing probes corresponding to genes of interest.   The relative amount of green-labeled DNA that binds to each probe, compared to the amount of red-labeled DNA that binds, is an indication of whether the expression of that gene increased or decreased (or did not change) under the experimental conditions, relative to the control.  A computer program displays the relative red and green fluorescence on each spot on the chip, where equal amounts of green and red are displayed as yellow.

Expression microarrays typically include probes for genes that should not change expression regardless of conditions, as controls for variability. These control genes include beta-actin, GAPDH, GUS, RPLPO, and TFRC.

Tutorial links

Quick start instructions provide a quick summary of procedures used to run both SNP and expression microarrays with Case It v7.0.4.

Video tutorials for SNP microarrays and for expression microarrays provide considerably more detail on microarray principles, software use, interpretation of results, and construction of data files.

SNP MICROARRAYS

Case A: Prostate cancer. Greg just celebrated his 50th birthday.  He does not feel “old” and thought he was in very good health.  However, his physician recommended that, because of his age, he undergo screening for various diseases that are more common in men over 50.  One of these is the PSA (prostate-specific antigen) test, used to detect potential prostate diseases.  Although Greg has not had any of the symptoms associated with prostate disease, he has his blood tested for PSA.  His result of 8 ng/ml is outside of the normal range of 0-4 ng/ml.   Greg’s physician suggests that they perform a needle biopsy to look for abnormal cells in Greg’s prostate that might indicate inflammation or even cancer.  Greg does not want any unnecessary tests, especially any involving needles, and he discusses his concerns with his physician.  Greg’s physician just read an article describing men with higher than normal PSA levels in the absence of any prostate disease, and suggests the possibility that higher PSA blood levels may be normal for Greg due to his genetics.  The physician arranges for Greg’s DNA to be tested for the SNPs associated with high PSA levels.

According to this study, two SNPs (rs10788160 near the FGFR gene, and rs17632542 in the KLK3 gene) were associated with higher blood PSA levels in the absence of prostate cancer.  One SNP (rs10993994 in the MSMB gene) was linked to higher PSA levels but also to higher risk for prostate cancer.

Procedure: To analyze this case, open the file SNP PSA levels.csv and run the microarray.  Compare Greg’s DNA with the sample from a patient with genetically high PSA levels and the sample from someone with normal PSA levels to determine whether Greg’s DNA contains SNP alleles that would explain his higher blood PSA levels.

1. Does Greg’s DNA contain the SNP alleles associated with high PSA levels?
2. Should Greg get the needle biopsy? Why or why not?
3. How do these results affect the interpretation of Greg’s PSA test results?
4. What role might these gene products play in prostate function?
5. Should routine PSA testing continue to be recommended if It is not completely accurate?

Case B: Pharmacogenomics. Each year, thousands of people die from drug complications, and millions have adverse side effects. There is significant genetic variability in how patients will respond to certain drugs. For example, Warfarin is an oral anticoagulant drug that is widely used to prevent and treat thromboembolic disease in patients with deep-vein thrombosis, pulmonary embolism, mechanical heart valves, and atrial fibrillation.  It inhibits the vitamin K epoxide reductase complex subunit 1 (VKORC1), which results in decreased formation of vitamin K–dependent clotting factors and provides the therapeutic effect of anticoagulation. It is associated with a substantial risk of major bleeding, which can be fatal, and patients taking Warfarin must be monitored closely. SNPs have been identified in genes encoding enzymes that metabolize Warfarin, that are associated with increased risk for bleeding. Additional SNPs in the VKORC1 gene are associated with resistance to Warfarin, rendering it ineffective at protecting against blood clots.

Sally is a 55-year-old woman with a recent history of atrial fibrillation who requires long-term anticoagulation therapy. She and her daughter are quite concerned about the potential for bleeding and ask the pharmacist about their concerns. The pharmacist suggests that Sally undergo genetic testing to avoid this adverse event. Sally’s DNA is tested for SNPs associated with higher risk of excessive bleeding due to Warfarin.

Procedure: To analyze this case, open the file “SNP pharmacogenomics warfarin.csv” and run the SNP microarray. A DNA sample from an individual known to have a SNP associated with risk for Warfarin-induced bleeding is included, as well as DNA from someone who has a SNP associated with resistance to Warfarin.

1. Based on the results of these tests, should Sally be prescribed Warfarin to treat her atrial fibrillation?
2. What other recommendations do you have for Sally to help her manage her health?
3. What are the functions of the SNP-associated genes and how are they involved in modulating the effect of Warfarin?

Case C: Cardiac disease. Jonathan is a 44-year old male who is in good health, although he is about 30 pounds overweight.  It has been a difficult year for Jonathan. His marriage ended, and after a bitter custody fight he has full custody of his two daughters, ages 7 and 9. Soon after, he lost his full time job. He quickly found work again in a position that pays a lower salary. but he feels lucky, though, to have found a job that provides health insurance. He blames the stress of the past year for the fact that he has gained weight. It has been hard to find time to exercise with his new job and taking care of his daughters. So he was relieved when his recent physical exam indicated that his overall health was reasonably good. His cholesterol levels were slightly elevated since his last exam, but his blood pressure was in the normal range.

Jonathan has been concerned about heart disease ever since a former classmate, who had seemed in perfect health, died of a sudden heart attack while running a 10K race. Jonathan does not know very much about his own family history of heart disease since his father died in a car accident when Jonathan was very young, and he has few other male relatives. When he mentioned his concerns to his physician, he tells Jonathan that there is a genetic test that can determine whether his DNA contains certain SNPs associated with sudden cardiac disease. Having one of these SNPs may be associated with a 2-5 times greater chance of sudden myocardial infarction (heart attack). Having more than one of the associated SNPs can increase the risk significantly. Since this clinic is involved in researching the role of these SNPs in sudden cardiac disease (SCD), Jonathan can get his DNA tested for no cost. He decides to go ahead with the test and submits a blood sample.

Procedure: To analyze this case, open the SNP Cardiac disease.csv file and run the SNP microarray. For comparison, this file also contains samples from a man who had a sudden myocardial infarction (SCD) at age 40 with no prior symptoms, and from a man with is in his 70’s and has had no heart problems nor does he have any family history of heart disease. Determine the genotype for these SNPs associated with increased risk for sudden cardiac disease:

SNP	Risk allele
rs4687718	A
rs4665058	A
rs3918242	T
rs11970286	T

1. Does Jonathan’s DNA contain any of the SNPs associated with risk for sudden cardiac disease? How would you explain the results of the test to him?
2. What would you recommend to Jonathan in terms of managing his health and reducing his risk of cardiac disease?
3. Should Jonathan be concerned about the results of his DNA testing being used in a research study, or being shared with anyone else?
4. Are there SNPs other than those mentioned in the tables whose genotype pattern indicate they might be associated with increased risk for cardiac disease?
5. Are these SNPs located in or near genes? If so, what are the functions of these genes in cardiac function?

Case D: Resistance to HIV infection. Researchers have been studying a population of Kenyan sex workers who appear to be resistant to HIV infection despite repeated exposure to the virus.  Identifying the mechanism for HIV resistance could lead to treatments that would protect individuals at risk for HIV exposure. To determine whether there are genetic factors that contribute to this resistance, the researchers obtained blood samples from HIV-resistant sex workers as well as from individuals who became infected with HIV upon exposure, and isolated DNA from these samples.  A SNP microarray was performed to identify any SNPs consistently associated with HIV resistance.

Procedure: To analyze these samples, open the file “SNP HIV resistance.csv” and run the microarray.  Compare the resistant and susceptible samples against each other to identify SNPs genotypes that correlate with resistance.

1. Are there SNPs that appear distinguish the resistant vs. susceptible individuals?
2. Do any of these SNPs appear to be in or near genes that you would expect to be involved in HIV resistance?  What is the gene function?
3. How might a change in one nucleotide affect the ability of a cell to be infected by HIV?

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EXPRESSION MICROARRAYS

Expression microarray quick start instructions

Video tutorial for expression microarrays – for more in-depth information

Case A: Breast cancer. Sarah was devastated when she received a diagnosis of breast cancer. It did not seem to run in her family, so she assumed she did not have to worry about it. She is grateful for the support of her friends, especially Molly, who is a clinical lab pathologist. Molly is helping her think about the difficult decisions about how aggressive her treatment should be, in terms of surgery, chemotherapy, etc. She explained that the oncologist recommended running a lab test that uses a microarray to measure the expression of specific genes. The pattern of gene expression can predict how quickly the tumor cells will grow and whether they will respond to treatments. Sarah is meeting with the oncologist to review the results, and she has asked Molly to go with her.

Researchers have identified genes whose increased expression is associated with increased proliferation, or rapid growth in breast cancer tumors: Ki-67, STK15, Survivin, Cyclin B1, MYLB2. Other genes are associated with increased tumor cell invasion if their expression is increased: Stomelysin 3 and Cathepsin L2. Some breast cancers cells respond to the hormone estrogen by proliferating, which provides a possible mechanism for treatment since estrogen receptors can be blocked. Increases in the expression of estrogen receptor genes might indicate these cells are responsive to the hormone.

Procedure: To analyze this case, open the file “Expr breast cancer.csv” and run the microarray. Compare the levels of gene expression, indicated by fluorescence intensity, in the sample from Sarah’s normal breast epithelium to a sample of the tumor tissue.

1. What genes are elevated in the tumor tissue? What genes are decreased?
2. What are the function of the genes with the most significant difference in expression between normal and tumor tissue?
3. Does that pattern of gene expression provide any information about Sarah’s prognosis?

Case B: Melanoma

Background: Melanoma accounts for about 3% of human cancers, and it is one of the most lethal. If caught early, it can be treated successfully with surgical excision. However, once it has spread it does not respond well to chemotherapy or other treatments. The cure rate is less than 5% and average survival times are 6-9 months from diagnosis. Melanoma arises from melanocytes, the pigment-producing cells in skin. These cells also produce benign skin growths such as moles (nevi). One of the challenges in detecting melanomas is to determine when an apparently benign nevi may have developed into a cancerous growth. Patients are advised to seek medical advice if a mole changes shape, size, or color. If the physician thinks that further evaluation is necessary, a surgical biopsy is performed and a pathologist will determine microscopically whether there are abnormal cells, with the potential to invade other tissues, spreading from the tissue. Diagnosis via standard histological criteria can be very difficult with these samples, and cases of invasive melanoma can be missed. Recently, molecular methods have been developed to support the microscopic pathology. Genes that are expressed at increased levels in invasive melanoma tissue relative to benign nevi can be used to identify tumor cells. Furthermore, identification of these genes provides a possible strategy for developing therapies that target invasive melanoma cells. Genes associated with increased expression in melanoma cells include OPN (a secreted phosphoprotein involved in cell adhesion and migration), PHACTR1 (phosphatase inhibitor), STAT1 (signal transduction and transcription activator), and FABP7 (fatty acid binding protein).

Scenario: Catherine usually did not spend much time looking closely at her skin. At 23, she was not yet worried about the signs of aging. Growing up on the gulf coast of Texas, she had spent most of her summers on the beach without worrying very much about excessive sun exposure. Her college roommate and best friend, who was from Minnesota, constantly commented on how attractive Catherine’s tanned skin was, and what a “healthy glow” she had. So when her physician questioned her about a large mole on her shoulder, she could not really tell her whether it had changed in appearance recently. She had many moles and did not pay much attention to them. But once it had been pointed out to her, and after doing some internet searching on how to identify potential skin cancers, she became anxious enough to seek the advice of a dermatologist. After examining the mole, the dermatologist recommended a biopsy, since it appeared to be abnormal. The pathologist report came back as “uninterpretable”, because there was some trauma to the tissue during the excision and processing that made it difficult to characterize the cells. A second biopsy with wider margins was planned, but in the meantime the original tissue sample was submitted for an experimental evaluation that involved extracting RNA for purposes of gene expression studies that might provide more information about whether the tissue contained cancerous cells. A biopsy of a mole with a normal benign appearance was taken for comparison.

Procedure: To analyze this case, open the file “Expr melanoma.csv” and run the microarray. Compare the levels of gene expression, indicated by fluorescence intensity, in the sample from Catherine’s questionable tissue (possible melanoma) to that in the normal, benign mole.

1. Is the expression of any of the gene associated with invasive melanoma elevated in the questionable mole sample relative to the benign mole?
2. Are there any other differences in gene expression between the two samples? If so, what are the functions of the genes showing differential expression?
3. What would you recommend to Catherine based on the results of this analysis?
4. What else could Catherine do to reduce her risk for melanoma?

Case C: Herpes simplex virus multiplication. Microarrays can be used to determine a time course of virus gene expression during the infection of cells in culture.  Virus multiplication cycles include attachment to the cell and penetration of the cell membrane, replication of the virus genome synthesis of virus proteins, and assembly and release of new virus particles. Virus gene expression is regulated temporally, with some genes expressed early in the multiplication process, while other genes are not expressed until later in the process. In this experiment, HSV-1 was used to infect HeLa cells.  Samples of infected cells were taken at 3 and 8 hours, and total RNA was extracted.  The RNA was copied into cDNA, incorporating Cy5 (red) fluorescent dye into the cDNA.  RNA was also extracted from the uninfected HeLa cells, and cDNA was copied incorporating Cy3 (green) dye.

Procedure: To analyze the results of this experiment, open the file “Expr HSV 3hr.csv” and run the microarray. Compare the levels of gene expression, indicated by fluorescence intensity, in the sample from uninfected and HSV-infected cells.   Note which genes appear to be elevated in the virus-infected cells at that time point, relative to uninfected cells.  Then repeat this procedure with the file “Expr HSV 8hr.csv”. Genes that were not elevated at 3 hr but appear at 8 hr would be considered “late genes”. Click here for background information about HSV microarray experiments and to identify the virus genes (HSV gene names include the letter U followed by a number). Probe sequences can also be submitted to BLAST analysis to gain more information about the genes.

1. Which HSV genes would be designated “early” genes based on these results?  What are their functions in virus multiplication?
2. Which HSV genes would be designated “late” genes based on these results?  What are their functions in virus multiplication?
3. Which cellular genes show increased expression in HSV-infected cells relative to uninfected cells?  What role would these genes have in virus multiplication?