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Big Data Can Reveal Why Cancer Therapies Fail Posted on : Sep 10 - 2019

The use of big data can reveal why targeted cancer therapies fail, according to new research from IBM and the Broad Institute.

Since 2016, both organisations have been using technology to explore what genetics can tell us about how cancer evolves and can be treated.

On Tuesday, in Nature Medicine, the researchers published the first in a series of discoveries that could spearhead cancer research and treatments.

Using data mining algorithms, they were able to untangle genetic mutations in the blood samples of patients with gastrointestinal diseases such as pancreatic, liver, colon and stomach cancer.

After performing an analysis of these samples, the scientists found genetic alterations linked to drug abstinence in almost 80% of cases. These didn’t show up in standard tissue biopsies.

These results, according to the researchers, could “give clues into two of the most pressing questions surrounding cancer treatment”.

First, why do targeted therapies fail? The researchers claim that, during the experiment, nearly every patient developed multiple forms of drug resistance. They’re confident that this could explain why targeted therapies often fail and change how clinicians treat metastatic cancers.

Second, could a blood sample tell us more than tissue biopsies? This experiment shows that it’s certainly possible. By analyzing patterns in the data of these samples, the researchers were given a clearer picture of the genetic makeup of tumors and how it can cause drug resistance at the molecular level. 

Both organizations take the view that these findings could lead to “effective combination therapies for cancers that have developed resistance” and spur “further analysis of simple, fast blood biopsies vs. invasive biopsy procedures”.

Laxmi Parida, IBM fellow of computational genomics, said: “A challenging obstacle to cancer treatment is our limited knowledge of how and why tumors develop resistance to drugs - including even the most advanced therapies.

“With Broad, we used unique data mining to untangle genetic mutations found in patients' blood samples - uncovering the reason why current therapies may fail for some patients, and that could be because of multiple resistance mechanisms." Source