6039BMS Cancer Biology | Coventry University

Assignment Task

You are required to produce a summary of analysis and interpretation of genomic data and links to diagnosis and therapy. You can keep the case study that was originally assigned to you in workshop 1 and make substantial approvements based on the feedback.  If you miss workshop 1, you should contact the module leader to receive the case study.

• You will be provided a patient case study and a list of genetic variants that has been created after the secondary genomic analysis using next generation sequencing.

• Based on this genomic data, you will need to identify pathogenic mutation/s in the driver gene/s likely to be associated with the type of cancer specified in the case study.

• You are required to use a publicly available databases such as  My Cancer Genome https://www.mycancergenome.org/  and Catalogue of Somatic Mutations in Cancer https://cancer.sanger.ac.uk/cosmic for data interpretation.

• The report should include a background to the topic area followed by a critical discussion on how next generation sequencing data would inform patient diagnosis and therapeutic decision making or screening of at-risk family members. There will be questions included in the case study to guide students in report writing.

• You will need to research your topic in suitable journal review articles, original scientific research papers and appropriate web-based sources. 

• Your report should conclude with a summary to evaluate the information that you have presented.

The following are included in your word allowance:

1. The text of your written work

2. Reference citations and reference to Figures and Tables within the text

3. Descriptive paragraphs as Figure or Table legends 

4. Text that is incorporated into a table format or into a text box format e.g. “Key points” summaries etc

The following are excluded from your word allowance:

1. The title

2. Your name, course etc

3. Figure and Table headings 

4. Words associated with Figures and Tables if these are data based

5. Reference list

6. The word count details

7. Contents page (if used)

Assessed Module Learning Outcomes

The Learning Outcomes for this module align to the marking criteria which can be found at the end of this brief. Ensure you understand the marking criteria to ensure successful achievement of the assessment task. The following module learning outcomes are assessed in this task:

• Apply an analytical approach to big data in cancer biology and evaluate the value of such information in future medical approaches to cancer.