To operate or not to operate?
New research from the David Geffen School of Medicine at UCLA may give oncologists and surgeons a more informed answer to this question for liver cancer patients.
A team of student researchers, led by Senior Scholarship Day award recipient, Sudeep Banerjee, has discovered a biomarker that accurately predicts the outcome of surgical procedures for patients with hepatocellular carcinoma (HCC), a form of liver cancer.
Treating MVI
Microvascular invasion (MVI) suggests a patient's cancer is entering the arteries or veins surrounding the tumor, meaning there's a good chance the disease has started to spread. This is a well-known predictor that liver patients won't respond well to surgical resection or liver transplantation, but it can only be detected after surgery when pathologists examine tissues cells. Against this backdrop, oncologists have traditionally made surgical decisions based on tumor size and blood protein levels, both of which can be determined before surgery but don't offer the full picture of a patient's chances for survival.
"Our goal was to find a surrogate biomarker for MVI that could be seen preoperatively using contrast CT imaging," explains Banerjee. "This information would help doctors better identify surgical candidates and give patients with MVI more aggressive medical treatment."
To find a scannable surrogate for MVI, he turned to radiogenomics — an emerging field that compares tissue samples and images from cancer patients — in search of a relationship between the two.
The RVI biomarker
Banerjee's team examined data collected on 157 HCC patients who underwent surgery at three different institutions between 2000 and 2009. "The hope was that we would find stable relationships between the gene variation in these tissue samples and what we could see in the images, so we could use imaging to infer information about the genetic composition of tumor tissue," he explains.
His team did more than hope; they discovered radiogenomic venous invasion (RVI), a noninvasive biomarker that predicts MVI with 80 to 90 percent accuracy. "RVI is a combination of three imaging traits that can be detected by a radiologist," says Banerjee. "It's when you look at a tumor on a CT scan and see it has internal arteries within the tumor itself, a dense halo around the tumor and the absence of another trait — which we're calling 'tumor liver difference.'"
Prediction through collaboration
This medical breakthrough, according to Banerjee, wouldn't have been possible without "the effortless collaboration" of medical experts associated with DGSOM — including pathologists who provided the patient data, radiologists who read images and hepatologists who answered questions for the team about how treatment decisions are typically made. "My mentor brought together all these different people from different institutions," he acknowledges. "Research is only benefited by collaboration. Always being able to get experts to chime in really enriched the project."
Banerjee will soon enter a general surgery residency, after which he hopes to complete a surgical oncology fellowship. "In the next several decades, the strides that will be achieved in treating cancer are going to be tremendous," he says. "We're really at a turning point where the use of targeted therapy and the availability of treatment modalities is continuously expanding. And I think being part of that revolution and effectively treating cancer would be an extremely gratifying use of a career."
