There are many challenges associated with identifying potentially cancerous pancreatic cysts. Here, Dr. Annabelle L. Fonseca et al explain
Doctors and patients usually do not know that a problem was even there. It is estimated that millions of people have pancreatic cysts (2% to 13% of the general population in the United States undergoing imaging). Because of the prevalence of these cysts, physicians often see them in patients undergoing diagnostic imaging, but the patients commonly do not have any symptoms from the cyst itself. This usually represents a conundrum for the doctor and patient because the cysts were not expected. The imaging is usually ordered for reasons unrelated to the pancreas (like gallbladder stones or other benign or malignant conditions). The challenge lies with the fact that the vast majority of pancreatic cysts are benign, but a small proportion of cysts can turn into pancreatic cancer, one of the deadliest diseases that afflicts humans.
The common initial reaction: How do I get rid of it?
Currently, the only way to cure pancreatic cysts is with major surgery that may involve removal of part of the stomach and bowel, along with the pancreatic cyst(s). The surgery can be life-altering, and the procedure carries a small risk of death. Even after considering the morbidity and mortality of the surgery, many patients receive too much treatment (also described as over diagnosis) for an otherwise benign condition, largely out of fear that a cancer might be lurking.
Refocusing the question: What are the needles in the haystack?
Techniques to characterise these pancreatic cysts are urgently needed to spare patients with benign cysts from unnecessary surgery and to identify the patients with potentially malignant cysts who need surgery. In our analogy, the haystack represents all the patients with pancreatic cysts. The needles represent the small number of patients who have cysts that may turn into cancer.
There are multiple forms of pancreatic cysts. The most common types that can turn into pancreatic cancer are intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs). Studies have shown that surgical removal of IPMNs or MCNs when they have not yet turned into cancer results in 5-year survival rates of 90-100%. Conversely, if any cancer component is found in the cyst after surgery, the survival rate is reduced by half. The current thinking by experts is that benign cysts exhibit a cellular pattern known as low grade dysplasia, and that cysts with a higher likelihood of becoming cancer have high grade dysplasia. Currently, the only reliable method to get the correct diagnosis involves major surgery so that a pathologist can see the entire tissue specimen; a small biopsy is not usually sufficient for an accurate diagnosis. So how do we select patients with pancreatic cysts for surgery?
The current approach: More hay than needles
The current approach to deciding which patients should receive surgery involves the use of consensus guidelines: If a patient meets the criteria, which a group of experts decide on, then the patient is recommended to undergo surgery. This approach does not involve evidence based clinical trials, unfortunately. Although the consensus guidelines have a relatively high sensitivity of around 90% or more (it can detect most cysts with cancer), there is a relatively low specificity of 50-60% (it incorrectly classifies benign cysts as high risk), feeding the over diagnosis problem. How can we accurately identify the high risk pancreatic cysts non-invasively?
A multi-faceted, biophysical approach to the problem
In the next few articles, we will explore the approaches to better identify high risk pancreatic cysts. Our approach involves the use of genetics, proteomics, physics, and math to overcome the current challenges that pancreatic cysts pose to physicians, patients, and the general healthcare system.
“This work was sponsored by the MD Anderson Cancer Moonshots program, Sheikh Ahmed Center for Pancreatic Cancer Research, and National Institutes of Health grant U01CA196403.”
Center for Precision Biomedicine
Brown Foundation Institute of Molecular Medicine
University of Texas Health Science Center at Houston (UTHealth) McGovern Medical School
Eugene J. Koay
Department of Radiation Oncology
Sheikh Ahmed Center for Pancreatic Cancer Research, MD Anderson Cancer Center
Annabelle L. Fonseca – Department of Surgical Oncology, MD Anderson Cancer Center
Anirban Maitra – Departments of Pathology and Translational Molecular Pathology, Sheikh Ahmed
Center for Pancreatic Cancer Research, MD Anderson Cancer Center
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