Uncategorized, Page 2 Category

Georgia Tech Research (October 26th, 2021)

Today, machine learning, artificial intelligence, and algorithmic advancements made by research scientists and engineers are driving more targeted medical therapies through the power of prediction. The ability to rapidly analyze large amounts of complex data has clinicians closer to providing individualized treatments for patients, with an aim to create better outcomes through more proactive, personalized medicine and care.

“In medicine, we need to be able to make predictions,” said John F. McDonald, professor in the School of Biological Sciences and director of the Integrated Cancer Research Center in the Petit Institute for Bioengineering and Bioscience at the Georgia Institute of Technology. One way is through understanding cause and reflect relationships, like a cancer patient’s response to drugs, he explained. The other way is through correlation.

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Saporta Report (September 13th, 2021)

It’s one of those cruel realities. By the time most women are diagnosed with ovarian cancer, it’s often too late to cure.

But an Atlanta gynecological oncologist and his team of scientists and researchers are trying to change that reality.

Dr. Benedict Benigno, founder and CEO of the Ovarian Cancer Institute, feels he is close to reaching the “Holy Grail” – developing an accurate test for the early diagnosis of ovarian cancer. The Institute is about six to eight weeks away from getting the results of how effective its early detection test has been on a trial of 800 women.

“If the early diagnostic test is as successful as I think it will be, it will be a monumental contribution,” Dr. Benigno said in an interview. “It is one of oncology’s Holy Grails. There’s a 92 percent chance of survival if ovarian cancer is diagnosed at Stage 1.”

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Georgia Tech Research (June 8th, 2020)

Contrary to common medical guidance, chemotherapy does not appear to be the only culprit in neuropathy, a neurological side effect of cancer treatment, a new study says. Cancer itself contributes heavily, too, and the stresses on neurons appear far worse than the sum of the two causes.

“There was some distress caused by cancer alone and some distress from chemo alone, but when you put the two things together, it was off the charts, seven times the trauma to neurons of the two things added together,” said Nick Housley, first author of the study performed in rats at the Georgia Institute of Technology. “It turned out to be the first-ever evidence that there is this exacerbation going on.”

Every year in the U.S., there are 1.8 million new cancer diagnoses, and about half of patients receive platinum-based drugs, which are very effective. About 40 percent of patients receiving platinum chemotherapy come down with neuropathy, suffering strange sensations, pain, fatigue, or loss of muscle coordination that impedes day-to-day life. Neuropathy can persist for years after chemotherapy ends.

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Oncotarget (January 28th, 2020)

A new study by researchers in the School of Biological Sciences raises new questions about a decades-old, award-winning theory regarding how many genetic mutations are necessary for cancer to develop in human cells.

That theory, called the Knudson Hypothesis, argued that two mutations in the type of genes that suppress tumors are needed to lead to changes that could cause cancer. However, John McDonald, a School of Biological Sciences professor and the director of Georgia Tech’s Integrated Cancer Research Center, says the research, published in Oncotarget, “shows, for the first time, that nearly all normal healthy individuals carry at least one potentially cancer-causing tumor suppressor gene mutation. The implication is that a majority of the human population is, to a greater or lesser extent, predisposed to develop cancer.”

 (full story…)

Targeted Oncology (January, 10th, 2019)

The use of big data is revolutionizing many industries, allowing greater insights by drilling into evidence with more detail. Pair that with personalized medicine, where clinicians can tailor a patient’s cancer treatment based on biomarkers, genetic aberrations, or other individual characteristics, and oncologists gain powerful insight that can help predict the best course of treatment for each patient that is based on individual disease characteristics, not just cancer type and stage. Medical centers are also taking unique approaches, but they all have 2 things in common: technology and data. (full story..)

MedPage Today (June, 2018)

Machine learning, which helps find correlations in large data sets, is gaining ground in cancer treatment. John F. McDonald, PhD, explains why and shares his vision for the future of this technology in oncology. (full story..)