News Release

Blood test could detect kidney cancer up to five years prior to clinical diagnosis

Earlier detection could improve outcomes for patients with renal cell carcinoma

Peer-Reviewed Publication

Beth Israel Deaconess Medical Center

Rupal Bhatt, M.D., Ph.D., Beth Israel Deaconess Medical Center

image: This is Rupal Bhatt, M.D., Ph.D., corresponding author and medical oncologist at Beth Israel Deaconess Medical Center. view more 

Credit: Beth Israel Deaconess Medical Center

BOSTON - Every year, more than 330,000 people are diagnosed with kidney cancer worldwide. More than 80 percent of those new cases are renal cell carcinomas (RCC). When caught early, the five-year survival rate is more than 90 percent. Patients diagnosed with more invasive tumors, however, have dramatically poorer prognoses, with five-year survival rates of 50 percent and 10 percent for patients diagnosed at stages III and IV respectively. Early detection could improve the overall survival rate in patients at high risk for death from RCC.

Now, a team of investigators led by Beth Israel Deaconess Medical Center (BIDMC) medical oncologist Rupal Bhatt, MD, PhD, has demonstrated that a molecule called KIM-1, a protein present in the blood of some patients with renal cell carcinoma is present at elevated levels at the time of diagnosis, can also serve as a tool to predict the disease's onset up to five years prior to diagnosis. The team's findings were published in the journal Clinical Cancer Research.

"Our study found a significant association between plasma KIM-1 concentrations and the risk of renal cell carcinomas," said Bhatt, corresponding author of the study and an Associate Professor of Medicine at Harvard Medical School. "The team also found that KIM-1 concentrations were associated with poorer survival. Further studies are needed, but a sensitive and specific tumor marker that can detect early stage RCC would have strong potential to improve overall survival."

Bhatt and colleagues, including co-first author David Muller, PhD, a research fellow in Epidemiology and Biostatistics at Imperial College London, analyzed data from the European Prospective Investigation into Cancer and nutrition (EPIC), one of the world's largest cohort studies investigating the link between diet, lifestyle and environment and chronic diseases including cancer.

When the team compared KIM-1 concentrations in samples from EPIC participants who developed RCC within five years with participants who remained healthy, they found the average concentration of KIM-1 was double in those eventually diagnosed with RCC. What's more, including KIM-1 concentrations into a model for predicting kidney cancer risk approximately doubled the model's accuracy.

"This work is a big step forward, because KIM-1 is the only blood biomarker shown prospectively to distinguish between people at high and low risk of kidney cancer," said Muller. "But more work will be necessary before we could see this in the clinic."

"It will be important to understand more about the settings in which KIM-1 might be incorporated into patient care," added Bhatt. "We don't expect that KIM-1 will be useful as a screening test, as risk of RCC in the general population is low. KIM-1 is more likely to be relevant in high-risk populations or as an adjunct to other diagnostic procedures."

###

In addition to Bhatt and Muller, co-authors include co-first author Ghislaine Scelo of the International Agency for Research on Cancer (IARC), and Venkata Sabbisetti and Joseph V. Bonventre of Brigham and Women's Hospital.

For a complete list of contributors, please visit: http://clincancerres.aacrjournals.org/content/early/2018/07/21/1078-0432.CCR-18-1496

This work was supported by grants from the National Institutes of Health Funding (R01 CA196996 and P50 CA101942-12) and a Cancer Research UK Population Research Fellowship.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.