The Best for Breast Cancer Studies -Fatima R.

Before reading chapter five of Rigor Mortis, “Trusting the Untrustworthy”, I had no idea that inaccuracies in cell lines and antibodies was a real issue faced in the world of research and study. Although it was easy to wrap my head around the idea of these type of mistakes as a possibility during experiments, I never fully thought about how they came into place and how significant they were.

One thing that surprised me about cell lines was the big misidentification of melanoma cells as breast cancer cells in the 1970s:

Image result for melanoma cells
Melanoma cells under a microscope.

“Melanoma cancers had their own unique gene-expression fingerprint. And so did breast cancer cells- well, almost all of the breast cancer cells. MDA-MB-435 didn’t come out looking like a breast cancer cell. Its gene pattern matched the melanoma cells and “really had nothing to do with the breast cancer cell lines,” Ross told me. ” So we repeated the experiment to make sure we didn’t screw it up”- and got the same melanoma pattern. Ross borrowed a different sample of MDA-MB-435 from colleagues at Stanford. Same thing. It was looking a lot like melanoma. “We just mentioned in the paper the possibility its tissue of origin was misidentified,” he said.” (pg. 101).



Misidentifying the melanoma cells for breast cancer was understandable as supported by the scientists’ finds, which showed that the cells in fact were very similar to a series of each others’ lines.  However, the book also shared that in the 1980s it became one of the National Cancer Institute’s 60 key lines and it became essential to the experimentation and testing of new cancer drugs. What was the most surprising to me was that from 1980s to the 2000s everyone simply trusted this acclaimed cell line, rather than challenging what came before them, and resulted in almost two decades worth of inaccurate information.

I was interested in learning more about breast cancer within this timeline to see how the findings played out with cancer rates, so I found a statistic page that stated decreases in breast cancer incidences began in 2000, which was around the same time this discovery was made.

Related image
Analyzing a mammogram.

Although it wasn’t clearly stated, I thought maybe the correct identification of the cells and cautioning led to more helpful cancer treatment in these years. Of course it wasn’t the only factor that affected these rates, but a big breakthrough like that must’ve been helpful.


Why are we afraid to question something that’s been “proven” right or accurate? It may seem redundant, but I see it as a way to fully eliminate all the possible variables that could cause the experiment to shift. It’s like taking a test. You would obviously go back and double-check your answers. An experiment in the field of biomedical research is the same in the sense that one of the things you’re focused on is being as successful as possible, and being careful is the key to that. As the chapter comes to a conclusion, a solution is also offered to help experiment results: “Improving experimental design would further reduce these unforced errors in science.” (pg. 122).


One thought on “The Best for Breast Cancer Studies -Fatima R.

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  1. I was really impressed by how well all of your information was organized in this post, I was able to comprehend the idea that melanoma cells were not connected to breast cancer cells. I also appreciate that you had a link that had much information about breast cancer so I could better understand this article. – Alicia L.

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