A New Treatment Paradigm Suggested for Pancreatic Cancer

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Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma, which may be highly prognostic.
Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma, which may be highly prognostic.

A new study suggests that treatment decisions for pancreatic cancer should be based on both a patient's stroma and tumor subtype.1 In the largest gene expression analysis of the disease to date, researchers have identified specific subtypes that may be highly prognostic.

“We believe that our findings of different tumor and stroma subtypes will change the landscape of clinical trials for pancreatic cancer and how to approach its treatment,” said the study's senior author Jen Jen Yeh, MD, who is the vice chair for research in the University of North Carolina School of Medicine Department of Surgery in Chapel Hill, NC.

“Pancreatic cancer is more challenging to study because of its low tumor cell content and dense surrounding stroma. What we have found is there are subtypes that may explain why the stroma may both constrain and promote tumor spread.”

The findings from the study, which were published in Nature Genetics, pave the way for potential personalized medicine approaches and hopefully improved outcomes.

Dr. Yeh said the current 5-year survival rate for patients with pancreatic cancer is only about 7% and that is because clinicians still treat pancreatic cancers as one entity. She said these new study findings should set the groundwork for future clinical trials, allowing treatments to be assigned based on specific subtypes.

A hallmark of pancreatic ductal adenocarcinoma (PDAC) is extensive stromal involvement. This makes it difficult to capture precise tumor-specific molecular information. In this current study, the researchers were able to marry the right data analysis technique to the right problem.

RELATED: Ruxolitinib Plus Capecitabine May Improve Survival in Pancreatic Cancer

Dr. Yeh and her colleagues were able to overcome this problem by applying blind source separation to a diverse collection of PDAC gene expression microarray data.

The researchers were able to collect specific data on primary tumor, metastatic, and normal samples. By digitally separating tumor, stromal and normal gene expression, the investigators identified and validated two tumor subtypes. One of the subtypes is a “basal-like” subtype that appears to be associated with a worse outcome.

The researchers have defined “normal” and “activated” stromal subtypes, which are independently prognostic. Patients with the activated subtype had worse survival outcomes.

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