Cancer
affects people all around the world and has been a leading cause of death for
many years. Whether your diagnosed with it or someone you know suffers from it
cancer is a terrible disease no one should have to deal with. Scientist and researchers
have been trying to come up with a cure for cancer for a while but none have
been successful.
In the article “The Use of Ovarian
Cancer Cells from Patients Undergoing Surgery to Generate Primary
Cultures Capable of Undergoing Functional Analysis” by O’Donnell et al studies are
being done using ascites and tumor tissue from patients with ovarian cancer
during surgery to culture for diagnostic testing and research.
“Ovarian cancer is the leading cause of gynecological
cancer mortality worldwide” (O’Donnell et
al). Doctors treat ovarian
cancer as a single disease with surgery and chemotherapy but really ovarian
cancer is a combination of different diseases. Researchers are now constructing
a heterogeneous model to study. To be most accurate cells are used from the primary
source. There are so many advantages to culturing from the primary source than any other model like cell lines or animal models.
Samples
were collected from patients at the Queen Elizabeth hospital in Gateshead U.K.
They were then transported to the lab and there some of the samples were added
directly onto coverslips for analysis. In the case of the ascites cultures were
91% successful. “Establishment of
cell cultures from tissue explants was achieved in 100% of cases” (O’Donnell
et al).
Any research
being done to better treat cancer patients is a step in the right direction.
People shouldn’t have to suffer from such a horrible and body deteriorating
disease any longer. I hope and believe one day there will be a cure with the
right research and experimenting I think it is very possible.
Citation
O′Donnell RL, McCormick A, Mukhopadhyay A, Woodhouse LC, Moat M, Grundy A, et al. (2014) The Use of Ovarian Cancer Cells from Patients Undergoing Surgery to Generate Primary Cultures Capable of Undergoing Functional Analysis. PLoS ONE 9(3): e90604. doi:10.1371/journal.pone.0090604 Read about it here
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