Unlocking the Secrets in Our Genes
INTRODUCTION
In Activity 3.1.4, you investigated five genes potentially involved in the development of
lung cancer. To complete this investigation, you performed a simulated DNA
mic
...
Unlocking the Secrets in Our Genes
INTRODUCTION
In Activity 3.1.4, you investigated five genes potentially involved in the development of
lung cancer. To complete this investigation, you performed a simulated DNA
microarrayusing healthy and cancerous lung tissue from different patients. You were able to
analyze the results and identify basic trends to determine if, and how, the gene expression was
different in the cancerous lung tissue from the healthy lung tissue.
This information can help scientists determine the potential role these genes might play in the
development of lung cancer. DNA microarrays are helping researchers learn more about the
genetic mutations associated with different types of cancer; however, DNA microarrays can also
be used to look at the gene expression profiles of groups of patients in order to personalize
medical treatments.
Mike Smith’s oncologist wants to determine the best treatment plan for Mike. He has enrolled
Mike in a research study to compare Mike's gene expression profile to those of
other osteosarcoma patients known to have had success with various chemotherapy
medications. By taking samples from each known patient, scientists can perform DNA
microarrays to determine their gene expression patterns.
They can then calculate the similarities between Mike’s gene expression pattern and the gene
expression pattern of each patient. If Mike has a similar gene expression pattern to one of these
patients, it is likely that Mike would have a similar clinical outcome as that patient. This means
that if that patient responded well to a particular type of chemotherapy medication, it is likely
that Mike would also respond well.
One popular method to calculate the similarities between gene expression profiles is called
the Pearson correlation coefficient, also known as the Pearson product-moment
correlation coefficient. This method statistically measures the correlation, or relationship,
between two sets of data. In this activity, you will use the Pearson correlation coefficient method
to determine which patient’s gene expression profile is the most similar to Mike Smith. You will
use this information to help Mike’s oncologist make an informed decision as to which
chemotherapy medication should be prescribed to Mike
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