Survival and Pervention of Breast Cancer

Abstract

Breast cancer is something that affects women on a daily basis. Breast Cancer is a disease caused by many different biological factors. It forms through cells that form together and become malignant. Different things can play into women getting breast cancer. Genes, age, race, and many other things can contribute to the spread or survival of those with breast cancer. Many studies have come out looking into the prevention of breast cancer and increasing the survival of those diagnosed.

Key Words: Breast cancer, spread and survival, prevention

Surviving and Preventing Breast Cancer

Breast cancer is the leading diagnosed cancer in women and the second leading cause of malignancy death, next to lung cancer(Bevers 2015). Around 234,190 cases of invasive breast cancer have been diagnosed with around 40,290 deaths from this cancer in 2015(Bevers 2015).

As women age, the risk for breast cancer increases which means they should start doing more preventative measures to stop the possibilities of getting cancer at an early age. Researchers suggest preventative measures such as risk reduction and risk reduction surgery(Bevers 2015). These however need to be carefully thought about and discussed with doctors to decide if this is the best option and if you are at a risk for psychological or physical damage(Bevers 2015).

Preventative Measures

Many Doctors and researchers have done multiple types of test to have these preventative measures in place to begin in women who are at a higher risk for breast cancer or who have lower staged cancer. In one case, immunotherapy doctors use checkpoint inhibitors, chimeric antigen-receptor T cells, and tumor infiltrating T cells are all used a have a positive impact on cancer patients(University of Connecticut School of Medicine 2017). Although this seems like a promising idea, the amount of people in complete remission is less than 25%(UCSM 2017). Limitations also are a factor in this such as it is challenging to identify the cancer antigens in a rapid fashion.(UCSM 2017). The most effective way to look into preventative measures is through genome sequencing and to do a personalized immune system assessment(UCSM 2017). There are reports of 149 tumor antigens in human breast cancer patients which is caused by insertions and deletions in DNA which result in frameshift mutations. Researchers suggest using a model of anti-cancer immunity and a GDI platform to identify patient-specific tumor antigens(UCSM 2017)

Most Likely to be Affected

In cancer cases, there are higher risks for certain women. Breast Cancer is 39% more prominent in pre-menopausal African American women. Around 14% of postmenopausal African American women are diagnosed with breast cancer and around 16% of women diagnosed by cancer are non-African American women of all ages(Carey 2006). African american women may be affected more by this disease due to genetics, lifestyle differences, nutritional and environmental differences or other factors such as socioeconomic level and less access to screenings and treatment(Carey 2006)

Survival Rates

When breast cancer was first discovered, there was very little known about the disease. As time went on and technology reinvented medicine, more studies showed possibilities for cancer patients. Thanks to biomedical technologies, better measurement and recording techniques, low computer cost, better quality data, and analytic methods; people with breast cancer have a higher chance for survival(Delen 2005). Using popular data mining algorithms and other types of datasets, we can indicate that the decision tree(C5) is the best predictor with a 93.6% accuracy rate(Delen 2005). Multiple prediction models for Breast Cancer provides us with the ability to use the data collected to help the research of breast cancer(Delen 2005).

Results

Although Breast cancer is the most common cancer in the US for women, it is discovered that the minority of breast cancer cells in rats had the ability to form new tumors. This led to the seclusion of the tumorigenic cells from the non tumorigenic ones based off of the cells surface marker(Muhammad 2003). The cells were discovered as lineage cells in eight out of nine patients. Only around 100 cells that had that genetic makeup were able to form tumors where the other cells failed to.(Muhammed 2003). With this data researchers can regulate the growth of the cancerous cells and help the survival rate in cancer patients.

Conclusion

In conclusion, Breast Cancer is a very common cancer in women and affect a large variety of all types of women. Although there is no set cure for Breast Cancer, researchers get closer and closer every day to the possibility that they can slow down the progression of the disease and further help prevent women everywhere from getting breast cancer to begin with. Although researchers are getting closer to helping decrease the chances of breast cancer, it is still the most common cancer in women and one of leading causes of death especially when it comes to deaths from cancer.

References

Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J., & Clarke, M. F. (2003, April 01). Prospective identification of tumorigenic breast cancer cells. Retrieved from https://www.pnas.org/content/100/7/3983 Bevers, B., Ward, J. H., Arun, B. K., Colditz, G. A., Cowan, K. H., Daly, M. B., . . . Sofia D. Merajver. (n.d.). Breast Cancer Risk Reduction, Version 2.2015. Retrieved from https://www.jnccn.org/content/13/7/880.full.pdf html Carey, L. A. (2006, June 07). Race, Breast Cancer Subtypes, and Survival in the Carolina Breast Cancer Study. Retrieved from https://jamanetwork.com/journals/jama/fullarticle/202952 Predicting breast cancer survivability: A comparison of three data mining methods. (2004, September 09). Retrieved from https://www.sciencedirect.com/science/article/pii/S0933365704001010 Qendro, V., Lundgren, D. H., Palczewski, S., Hegde, P., Stevenson, C., Perpetua, L., . . . Han, D. K. (2017, August). Discovery of putative breast cancer antigens using an integrative platform of genomics-driven immunoproteomics. Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/28665052

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