Researchers investigate gene network to identify “cancer driver genes”

 

Drug Target Review (December 14th, 2021)

A team at the Georgia Institute of Technology, US, have found that an important class of genetic changes in cancer patients may be happening in places where scientists do not normally look: the network of gene-gene interactions associated with cancer onset and progression. Their discovery may uncover new targets for gene therapies.

Cancer chemotherapy has undergone a paradigm shift in recent years with traditional treatments such as broad-spectrum cytotoxic agents being complemented or replaced by drugs that target specific genes believed to drive the onset and progression of the disease. This more personalised approach to chemotherapy became possible when genomic profiling of individual patient tumours led researchers to identify specific “cancer driver genes” that led to the onset and development of cancer.

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Top Opportunities for Artificial Intelligence to Improve Cancer Care

 

Health IT Analytics (November 29th, 2021)

As artificial intelligence (AI) continues to grow in the healthcare field, researchers are findings new ways to utilize its capabilities. In chronic disease management and prevention, especially in cancer research, AI has been critical in the diagnosis, decision-making, and treatment process.

According to the National Cancer Institute, AI, machine learning, and deep learning can all be used to improve cancer care and patient outcomes.

“Integration of AI technology in cancer care could improve the accuracy and speed of diagnosis, aid clinical decision-making, and lead to better health outcomes. AI-guided clinical care has the potential to play an important role in reducing health disparities, particularly in low-resource settings,” NCI wrote on Cancer Detection & Diagnosis Research.

With the use of AI, researchers can create the next stage of precision oncology.

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Machine Learning Predicts Cancer Treatment Response

 

machine learning algorithm

Health IT Analytics (October 29th, 2021)

The Georgia Institute of Technology and Ovarian Cancer Institute researchers are using machine learning algorithms to predict how patients will respond to cancer-fighting drugs.

Advances in machine learning and artificial intelligence are allowing researchers to create more targeted precision medicine-based treatment using predictive analytics. By analyzing large amounts of complex data, clinicians can provide individualized treatments, improving patient outcomes.

“In medicine, we need to be able to make predictions,” professor at 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, John F. McDonald, said in a press release.

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Multi-Algorithm Approach Helps Deliver Personalized Medicine for Cancer Patients

 

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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Atlanta’s Ovarian Cancer Institute breaking new ground on early detection, treatment

Ovarian Cancer Institute

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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Chemotherapy and Cancer Gang up to Cause a Neurological Side Effect, Study Says

NCI stock image of cancer patient

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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