The Role of p53 Mutations and Cancer Day - Nursing Assignment Help

Assignment Task

Introduction 
In Practicals 2 and 3 you separated out proteins from two human cancer cell lines to identify how protein  localisation can differ for the same protein and how that relates to cancer type and progression. In this set of  Workshops you will study the vast array of mutations that can occur to the tumour suppressor gene p53 (TP53  gene symbol) that lead to cancer. You will mine information on these mutations of p53 from the World Health  Organization International Agency for Research on Cancer (IARC) database which compiles “TP53 mutation  data that have been reported in the published literature since 1989 or are available in other public databases.” 
Each Workshop you will answer a set of questions about the data mining and analysis activities within that  Workshop. Together these question sets form Lab Report #4: p53 Analysis - (10%). 
In preparation for Workshop 2: 
• Read pg. 1115-1126 in your textbook Molecular Biology of the Cell for more information on p53 and cancer. 
• Watch Cancer Part I and II lectures by Prof. Mark Molloy (U Syd, Lawrence Penn Chair of Bowel Cancer  Research) and look at associated PDFs. 
• Skim (read lightly and quickly, don’t get bogged down in details) a slideshow describing the p53 gene and  protein. Go to https://p53.iarc.fr/ and navigate to the ‘RESOURCES AND LINKS’ tab and select the ‘Slide show’  link. I have also uploaded the slideshow PDF to iLearn: ‘TP53-SlideShow2019.pdf’. Caution: this is a LOT of  information! Please do not get overwhelmed, but it contains very useful info that we will slowly learn over the  next three workshops.
Part 1: Introduction 
Today we will be searching a p53 mutation database to study the distribution of p53 mutations in a certain  type of cancer and upon exposure to a particular carcinogen. In addition, we will look at the cancers with the  highest incidence of p53 mutation in the United States, as well as the overall mutation distribution in all  somatic mutations reported in the database. 
The database that we are using today is officially called The International Agency for Research on Cancer TP53  mutation database (http://www-p53.iarc.fr/). Currently, the IARC website has information on over 28,000  somatic mutations in p53. Somatic mutations are acquired during the lifetime of an organism, in cells of the  body not including eggs and sperm, so this type of mutation is not passed on to the next generation [2].  
We will be examining p53 because of the high frequency of p53 mutation in cancer. P53, which is named for  the size of the protein at 53,000 Da, controls the DNA damage response in mammalian cells, among other  roles. It is a tumour suppressor gene, and functions as a transcription factor. 
As with other data mining exercises, we will be looking through the large datasets of the p53 database for  particular patterns. Specifically, we will be looking for mutation patterns in p53. Remember that with any  data mining experiment, the database search is limited by the quality of the information in the database.  
One of our data mining activities will involve searching for mutation patterns in cancer patients exposed to the  carcinogen, aflatoxin. Aflatoxin is produced by a certain type of mould found growing on improperly stored  peanuts and grains. Exposure to aflatoxin is linked to a three-fold increase in the chance of developing liver  carcinoma. In the next Workshop session, you will have the opportunity to search for mutations in patients  exposed to other types of carcinogens. 

Part 2: Data Mining Activity #1 
Analysis of somatic mutations associated with p53 in liver cancer 
Step 1: Go to the p53 mutation database homepage (https://p53.iarc.fr/). NOTE: (1) Firefox and Chrome  browsers work best on this website, (2) your computer may ask you whether you want to block Flash on this  website. Please feel free to allow Flash blocking as the website can function without Flash enabled. 
Hover your cursor on “DATA ANALYSIS AND DOWNLOADS” in the menu bar at the top of the homepage. 
Step 2: On the dropdown menu click on “Somatic Mutations” 
Step 3: Select the “Search Somatic Mutation Data” heading/section. Scroll down to the “Sample”  heading/section and select “Liver” under “Topography” category. 
Hit the “X” button on the far right of the “Morphology” box heading to clear all selections. Then check the box  next to two listings under morphology: “Hepatocellular adenoma (C22.0)” and “Hepatocellular carcinoma,  NOS”.
Step 4: Scroll up to the top to the “Search Somatic Mutation Data” heading. Click on the box labelled  “Mutation distribution” with a pie chart in red, green, and blue. Please note that the Java Applet is not necessary to view content for the exercise. 
Step 5: Examine the mutation type (right hand side graphic). How many mutations come up under this  particular query? (n= ?) What is the most common mutation type? 
Step 6: Examine the codon distribution graph in the lower left corner of the page. Roll over the codon  distribution title and click the square in the upper left corner to enlarge the graph. What codon number has  the highest percentage of the codon distribution? What percent of the total distribution? 
Step 7: For the codon most often changed as recorded in Step 6, what p53 protein domain is affected by this  change? (Use the p53 database slideshow and this lab handout to look at the protein domains of p53.)  
Step 8: Click on the “Mutation effect” tab. What is the most common mutation effect? 
Step 9: Click the “Previous” button. To the right of the “Criteria to include” heading click the “Reset include”  button. 
Part 3: Data mining activity #2 
Analysis of somatic p53 mutations associated with exposure to aflatoxin 
Step 1: Go to the p53 mutation database homepage (https://p53.iarc.fr/). Hover your cursor on “DATA  ANALYSIS AND DOWNLOADS” in the menu bar at the top of the homepage. 
Step 2: On the dropdown menu click on “Somatic Mutations” 
Step 3: Select the “Search Somatic Mutation Data” heading/section. Scroll down to the “Sample”  heading/section and select “LIVER” under “Topography” category. 
Hit the “X” button on the far right of the “Morphology” box heading to clear all selections. Then check the box  next to two listings under “Morphology” heading: “Hepatocellular adenoma (C22.0)” and “Hepatocellular  carcinoma, NOS (C22.0)”. 
Step 4: Now, select the “Individual” section (just below the Sample section) and under the search category of  “Exposure” select “AFB1 (aflatoxin)”.  
Step 5: Scroll up to the top of the on “Search Somatic Mutation Data” section. Click on the box labelled  “Mutation distribution” with a pie chart in red, green, and blue. Please note that the Java Applet is not necessary to view content for the exercise. 
Step 6: Examine the mutation type. How many mutations come up under this particular query? (n= ?)  What is the most common mutation type? 
Step 7: Examine the codon distribution graph in the lower left corner of the page. Roll over the codon  distribution title and click the square in the upper left corner to enlarge the graph. What codon has the  highest percentage of the codon distribution? What percent of the total distribution? Were mutations in  liver cancer patients with known exposure to aflatoxins concentrated in one particular area as compared to  all liver cancers? 
Step 8: Click on the “Mutation effect” tab. What is the most common mutation effect? 
Step 9: Click the “Previous” button. To the right of the “Criteria to include” heading click the “Reset include”  button.
Part 4: Data mining activity #3 
Cancers in the USA population most commonly found to have p53 mutations 
Step 1: Go to the p53 mutation database homepage (https://p53.iarc.fr/). Hover your cursor on “DATA  ANALYSIS AND DOWNLOADS” in the menu bar at the top of the homepage. On the dropdown menu click on  “Somatic Mutations” 
Step 2: Select the “Search Mutation Prevalence Data” heading/section. 
Step 3: Do not designate a “Topography”. Under “Morphology” category select “Cancer, NOS”. Then select  “USA” under “Country/Region” category, and finally select “DNA” under “Start material”.  
Step 4: On the bottom right click on “Topography graph” (button with blue arrow). What are the top three  types of cancers (found in the USA) in terms of p53 mutation prevalence? What is the prevalence for those  three types listed?  
Step 5: Click the “Previous” button. Scroll down to the bottom of the page and click the “Reset” button. 
Part 5: Data mining activity #4 
Comparison to statistics for entire database 
Step 1: Go to the p53 mutation database homepage (https://p53.iarc.fr/). Hover your cursor on “DATA  ANALYSIS AND DOWNLOADS” in the menu bar at the top of the homepage. On the dropdown menu click on  “Somatic Mutations” 
Step 2: Under the heading “Selected Statistics on Somatic Mutations” choose “Mutation distribution” button.  
Step 3: Click on the “Mutation effect” heading and look at the pie chart for “Mutation effect”. How do the  mutation effects listed for all somatic mutations in the database compare to those found for activities #1  and #2?  
Step 4: Click on the “Mutation type” heading and look at the pie chart for “Mutation Type”. How does the  mutation pattern listed for the entire database of somatic mutations compare to the mutation type seen in  activities #1 and #2? 
Step 5: Look at the “Codon distribution” chart. How does the codon distribution listed for the entire  database of somatic mutations compare to those found for activities #1 and #2?  

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