Molecular subtypes of pancreatic cancer based on miRNA expression profiles have independent prognostic value

BACKGROUND AND AIM

Altered microRNAs (miRNA) expression, a typical feature of many cancers, is reportedly associated with prognosis according to several studies. Although numerous studies on miRNAs in pancreatic ductal adenocarcinoma have also attempted to identify prognostic biomarkers, more large-scale clinical studies are needed to establish the clinical significance of the results. Present study aimed to identify prognosis-related molecular subtypes of primary pancreas tumors using miRNA expression profiling.

METHODS

Expression profiles of 1733 miRNAs were obtained by using microarray analysis of 104 pancreatic tumors of Korean patients. To detect subgroups informative in predicting the patient's prognosis, we applied unsupervised clustering methods and then analyzed the association of the molecular subgroups with survival time. Then, we constructed a classifier to predict the subgroup using penalized regression models.

RESULTS

We have determined three pancreatic ductal adenocarcinoma tumor subtypes associated with prognosis based on miRNA expression profiles. These subtypes showed significantly different survival time for patients with the same clinical conditions. This demonstrates that our prognostic molecular subgroup has independent prognostic utility. The molecular subtypes can be predicted with a classifier of 19 miRNAs. Of the 19 signature miRNAs, miR-106b-star, miR-324-3p, and miR-615 were related to a p53 canonical pathway, and miR-324, miR-145-5p, miR-26b-5p, and miR-574-3p were related to a Cox-2 centered pathway.

CONCLUSIONS

Our prognostic molecular subtypes demonstrated that miRNA profiles could be used as prognostic markers. Additionally, we have constructed a classifier that may be used to determine the molecular subgroup of new patient sample data. Further studies are needed for validation.

Overall survival: a gold standard in search of a surrogate: the value of progression-free survival and time to progression as end points of drug efficacy

Overall survival (OS) has been the gold standard for demonstrating clinical benefit for cancer drugs. It is 100% accurate for the event and time, it is assessed daily, its importance is unquestioned, and it addresses both safety and efficacy. However, OS as the primary efficacy end point requires large studies, long periods of follow-up, and it is potentially confounded by effective crossover, subsequent therapies, and noncancer death. Progression-free survival (PFS) or time to progression (TTP) directly measures the treatment effects of drugs on cancer growth, and they are not confounded by subsequent or crossover therapy. Although PFS and TTP benefits do not translate into OS benefits in all clinical settings examined so far, PFS or TTP improvement with a sufficient magnitude and in the context of favorable benefit-risk ratio should also be considered an important clinical benefit. Acceptance of PFS and TTP improvement demonstrated by well designed and conducted studies as direct evidence of clinical benefit will accelerate cancer drug development and make effective therapy available to patients with cancer sooner. The availability of sequential therapies, each delivers incremental progress in tumor control and PFS, may collectively lead to transformation of cancer to a curable or controllable chronic disease.