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Immune Responses
 

Abnormal immune responses can trigger a range of autoimmune diseases, in which an individual’s immune system is attacking normal tissues in the body. Well-known examples of autoimmune diseases are type 1 diabetes mellitus, lupus, and multiple sclerosis.
 

Ideally, one would like to harness the immune system to attack abnormal substances or tissues like cancer, while sparing the normal (unaffected) tissue. Many tumor cells produce antigens (proteins) that theoretically ought to trigger an immune response: that is, one’s immune system ought to recognize cancer cells as somehow foreign or abnormal, and thereafter eliminate these cells from the body. The field of cancer immunotherapy is actively pursuing this study.
 

Tumor antigens may also be useful for diagnostic tests; high levels of tumor antigens could be taken as markers or indicators of cancer. In this assignment, you will be examining levels of tumor-associated antigens (TAAs) as determined from immunoassays (i.e., biochemical tests that measure the concentrations of the tumor-associated antigens in serum samples).

• Download the Excel file MHA610_assignment_3_data.xls, and open it.
• The spreadsheet contains data      on 250 individuals: 90 normal individuals from San Diego (the controls),      and 160 individuals from Korea and China, all of whom were diagnosed with      hepatocellular carcinoma (HCC).
  • Serum samples       were taken from the controls and from the cases at time of diagnosis of       HCC. Levels of a panel of 12 tumor-associated antigens (TAAs) were       assessed via immunoassays in all individuals;
    • The levels        are given in the columns with headings Ab14, HCC1, IMP1, KOC, MDM2,        NPM1, P16, P53, P90, RaIA, and Survivin. (These are the designations of        the 12 TAAs, all of which were thought to be potentially predictive of        cancer.)
• The underlying question is      whether we can effectively discriminate between the cases and controls on      the basis of the levels of these TAAs. This is sometimes termed a      classification problem in the statistics and biostatistics literature: we      wish to classify individuals as normal or cancer patients on the basis of      their TAA levels.
• We will examine these data in      Statdisk. Use the MHA610_Week 3_Assignment_Data.CSV file to upload this information into      Statdisk.
  • If you choose       the latter option, Start Statdisk, then choose File>Open and select       the .csv file you created (unless you changed the name, it ought to be       MHA610_assignment_3_data.csv)
  • Check the box       that specifies the data contains column titles or headers, select Comma       separated for how the data are delimited, click finish, and the dataset       will have been successfully imported into Statdisk.
  • NOTE: you may       want to read through the remainder of the assignment first, before       proceeding with this step. This may save you some work afterwards!
• Note that Statdisk operates on      columns of data, and that both cases and controls are contained in each      column of TAA levels. It will be necessary to separate the cases and      controls for further analyses. This can be accomplished either by copying      within Statdisk or by reverting to the original Excel workbook, copying in      Excel, exporting as a .csv file, and then importing into Statdisk. (Don’t      say you weren’t warned!)
• Explain if you would      characterize any or all of the TAA levels as approximately normally      distributed for the controls and for the cases.
  • Provide plots       and statistics in support of your conclusions.
• Explain if any of the TAAs are      useful for discriminating between the cases and controls.
  • Provide plots       and statistics in support of your conclusions.
• All writing assignments should      be at least 250-500 words in APA format supported by scholarly sources.

BONUS. In the above, we pooled all cases together.  Summarize whether you think this is legitimate or whether the levels of any of the TAAs appear to differ significantly between the cases from China and the cases from Korea. Provide evidence in support of your conclusion.