Cancer

Prof. Regina Barzilay speaks with Nicole Estephan of WCVB-TV’s Chronicle about her work developing new AI systems that could be used to help diagnose breast and lung cancer before the cancers are detectable to the human eye.

A study by researchers from the Broad Institute and others have found that cancer in humans and dogs share genomic similarities, reports Nicole Karlis for Salon. “Specifically, the study identified 18 genetic mutations that are likely a primary driver of the cancer in canine patients, eight of which overlapped with so-called "hotspots" in human cancers,” writes Karlis.

Soledad O’Brien spotlights how researchers from MIT and Massachusetts General Hospital developed a new artificial intelligence tool, called Sybil, that an accurately predict a patient’s risk of developing lung cancer. “Sybil predicted with 86 to 94 percent accuracy whether a patient would develop lung cancer within a year,” says O’Brien.

Researchers at MIT have developed a new nanoparticle sensor that can detect cancerous proteins through a simple urine test. “The researchers designed the tests to be done on a strip of paper, similar to the at-home COVID tests everyone became familiar with during the pandemic,” writes Lambert. “They hope to make it as affordable and accessible to as many patients as possible.”

NBC News highlights how researchers from MIT and MGH have developed a new AI tool, called Sybil, that can “accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time.” NBC News notes that according to experts, the tool "could be a leap forward in the early detection of lung cancer.”

Researchers at MIT developed a system that uses artificial intelligence to help predict future risk of developing breast cancer, reports Poppy Harlow for CNN. What this work does “is identifies risk. It can tell a woman that you’re at high risk for developing breast cancer before you develop breast cancer,” says Larry Norton, medical director of the Lauder Breast Center at the Memorial Sloan Kettering Cancer Center.

Researchers at MIT and Massachusetts General Hospital have developed “Sybil” – an artificial intelligence tool that can predict the risk of a patient developing lung cancer within six years, reports Mallika Marshall for CBS Boston. 

MIT researchers have developed a new AI tool called Sybil that could help predict whether a patient will get lung cancer up to six years in advance, reports Pranshu Verma for The Washington Post.  “Much of the technology involves analyzing large troves of medical scans, data sets or images, then feeding them into complex artificial intelligence software,” Verma explains. “From there, computers are trained to spot images of tumors or other abnormalities.”

MIT researchers are developing targeted drug delivery through the use of nanoparticles to aid in cancer treatment, reports Simone Migliori for Boston Magazine. “Designed to circulate through the bloodstream, these small but mighty travelers [nanoparticles] can deliver a chemotherapy drug directly to a target cancer cell without disturbing any healthy cells along the way,” writes Migliori. “In doing so, patients may be able to avoid some of the worst side effects of chemotherapy drugs while still effectively treating their cancer.”

Researchers from MIT and Mass General Hospital have developed “a deep learning model named ‘Sybil’ that can be used to predict lung cancer risk, using data from just a single CT scan,” writes Sai Balasubramanian for Forbes. “Sybil is able to predict a patient’s future lung cancer risk to a certain extent of accuracy, using the data from just one LDCT [low-dose computed tomography scan],” writes Balasubramanian.

Jake Becraft PhD ’19 and former postdoctoral associate Tasuku Kitada co-founded Strand Therapeutics, a biotech firm developing mRNA therapies for cancer, reports Ryan Cross for The Boston Globe. They created “a way to activate mRNA in the presence of particular microRNAs – a much more useful application for therapies,” writes Cross. 

A study co-authored by researchers from MIT found that a person’s ancestry can impact CRISPR’s ability to edit genomes as intended, “particularly in people of African descent, whose genomes are most likely to differ from those used to steer CRISPR to a specific gene,” reports Jocelyn Kaiser for Science.

Prof. Richard Hynes is one of the winners of this year’s Lasker Award, reports Benjamin Mueller for The New York Times, for his work describing how “cells bind to their surrounding networks of proteins and other molecules — findings that pointed the way toward treatments for a number of diseases.”

Prof. Richard Hynes is one of three honorees for the Albert Lasker Basic Medical Research Award, reports Maddie Burakoff for the AP. Hynes and his fellow awardees “helped launch the field of integrin research, which has since led to new strategies for treating diseases,” writes Burakoff.

Prof. Richard Hynes is one of the three recipients of the 2022 Albert Lasker Basic Medical Research Award for his contributions to the field of integrin research, reports Martin Finucane for The Boston Globe. Hynes and his colleagues “provided a greater understanding of the diseases that can result when integrin function is perturbed.”