the Patterns: Data Analysis of Cancer Patients o will be working with data from
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the Patterns: Data Analysis of Cancer Patients o will be working with data from REAL cancer cases. For each patient e contributing to their specific cancer. You'll be Introduction In this vou be ctvity you e this data in several diferent ways that will reveal the similarities, nts. It has been this sort of analysis that has cancer, finally allowing us to turn the tide on this deadly asked to analyze differences, and tren change our approach to treating condition. a understand how large data sets are distilled in Goal The primary order to see underlying patterns al of this lab is to help you in the biology. It may be somewhat tedious, but the biol essence of scientific discovery is in the details. Often times, arrangin different ways helps investigators see important trends and features of the data in In the Case Study Cards there are 32 cases with 8 different types of c ncer ( breast, colorectal, pancreatic, leukemia, glioma, melanoma, and hepatlung, those cancer types and analyze the genet cancerous growth in each patient. ic mutations that are contributing to the Cancers you are analyzing: 1) Lung 2) Breost ota Concer 4)Legen d Part I- The Multiple Hit Hypothesis Fill in the table below calculating the average number of mutations in your cancer patients. First, do this by cancer type, then calculate an overall average. Cancer Typ Average number of Overal Mutations per patientAverage LunT5 2. 1. Is there any patient in your set that has a single mutation? What does that tell you about cancer? Can we ever "blame" a single gene?Explanation / Answer
2. in lung cancer, we see 5 oncogenes and 8 tumor suppressors. in breast cancer, we see 2 oncogenes and 6 tumor suppressors. in colorectal cancer, we see 6 oncogenes and 8 tumor suppressors. in leukemia, we see 4 oncogenes and 6 tumor suppressor genes. overall the four cancer types, we see more tumor suppressor genes than the oncogenes.
3. the genes associated with specific cancer are scattered on various chromosomes
4. more men get cancer than women. the study is mostly connected to carcinogenic exposures and lifestyle factors like smoking, drinking etc. the genetics also play a mojor role but studies related are ongoing.
5.
the overall most common gene is TP53.
6. genetic variations in tumor suppressor gene TP53 cause various cancers. the TP53 inactivation occurs by substitution or loss of alleles causing specific cancers. inheritance of TP53 mutation causes early onset of various cancers. the TP53 is highly polymorphic in coding and noncoding regions and these polymorphism increase cancer susceptibility.
cancer type most common gene lung cancer TP53 breast cancer TP53 colorectal cancer TP53, APC, SMAD4 leukemia NOTCH1Related Questions
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