Liver cancer is in the top 3 of most difficult cancers to cure and detect for early treatment. The incidence of liver cancer has tripled since 1980. In 2019, estimates say that 42,030 adults in the United States will be diagnosed with primary liver cancer and 31,780 deaths will occur. The five year survival rate is 18% and liver cancer is more common in Sub-Saharan Africa and Southeast Asia. We referenced the research article, “Tumor-Derived Exosomal miR-1247-3p Induces Cancer-Associated Fibroblast Activation to Foster Lung Metastasis in Liver Cancer”. Using NCBI 's Nucleotide Database, we found 3 nucleotide sequences using a connected search query, ‘Hepatocellular Carcinoma Cells AND Lung Metastasis AND Cancer Associated Fibroblasts’.
The three sequences were connected to the proteins NPTN, B4GALT3, and TMEM88. TMEM88 and B4GALT3 are prognostic markers that evaluate and predict the liver cancer growth and therapeutic intervention. DNA Deletion is a genetic mutation where part of a chromosome or a DNA sequence is removed during DNA replication. Non-coding DNA is any sequence component of an organism’s DNA that doesn't code for any proteins and can increase the chances of fatal diseases. Quartiles are statistical cut points that divide the range of observations in a sample. We used the Tukey Hinges Method for calculating the quartile nucleotides for every sequence. Using Python & MATLAB, we simulated coordinated DNA deletion or “Quartile Deletion” to see how removing the quartile nucleotides would change the amount and position of amino acids that were cancer promoters or cancer suppressors. We tracked the number and placement of non-coding RNAs to how their presence and position affected what amino acids were generated. These preliminary research results could continue to validate computational simulation for Precision Medicine, but most importantly create a new way to discover therapeutic markers to cure or prevent liver cancer.