Metabolomic biomarkers of pancreatic cancer: a meta-analysis study

Abstract

Pancreatic cancer (PC) is an aggressive disease with high mortality rates, however, there is no blood test for early detection and diagnosis of this disease. Several research groups have reported on metabolomics based clinical investigations to identify biomarkers of PC, however there is a lack of a centralized metabolite biomarker repository that can be used for meta-analysis and biomarker validation. Furthermore, since the incidence of PC is associated with metabolic syndrome and Type 2 diabetes mellitus (T2DM), there is a need to uncouple these common metabolic dysregulations that may otherwise diminish the clinical utility of metabolomic biosignatures. Here, we attempted to externally replicate proposed metabolite biomarkers of PC reported by several other groups in an independent group of PC subjects. Our study design included a T2DM cohort that was used as a non-cancer control and a separate cohort diagnosed with colorectal cancer (CRC), as a cancer disease control to eliminate possible generic biomarkers of cancer. We used targeted mass spectrometry for quantitation of literature-curated metabolite markers and identified a biomarker panel that discriminates between normal controls (NC) and PC patients with high accuracy. Further evaluation of our model with CRC, however, showed a drop in specificity for the PC biomarker panel. Taken together, our study underscores the need for a more robust study design for cancer biomarker studies so as to maximize the translational value and clinical implementation.

NMR‐based metabolomics of biofluids in cancer

“…Further, Bathe et al demonstrated the possibility to distinguish pancreatic cancer from benign hepatobiliary disease by NMR metabolic profiling of serum from 99 participants with high accuracy . A recent meta‐analysis has been performed to assess the diagnostic potential of literature‐curated NMR and MS metabolite markers using MS profiling of serum samples from pancreatic cancer patients ( n = 59) and three clinically relevant control groups (colorectal cancer (CRC) patients, type 2 diabetes patients, and healthy controls) . The resulting panel of 10 metabolites (increased lactate, lyso‐PC, alanine, choline, threonine, asparginine, tyrosine, lysine, and decreased palmitate and 3‐hydroxybutyrate in cancer) showed high classification accuracy (AUC = 0.99) for separating pancreatic cancer patients from non‐cancers.…”

Trait and state biomarkers for psychiatric disorders: Importance of infrastructure to bridge the gap between basic and clinical research and industry

“…Application of the appropriate research frameworks, as well as education in the key links among basic research, clinical applications, and industry, will form a fundamental base for success in such collaborative works . In particular, sharing patient neuronal samples and establishing common protocols to prepare and analyze these samples are crucial: indeed, many efforts have been made to standardize biobanking and analytical methods, such as by the College of American Pathologists and the International Organization for Standardization, to overcome irreproducibility in biomedical research and facilitate meta‐analyses . Importantly, both parties must follow IRB guidance, and carefully consider intellectual property rights among all parties.…”

“…11 In particular, sharing patient neuronal samples and establishing common protocols to prepare and analyze these samples are crucial: indeed, many efforts have been made to standardize biobanking and analytical methods, such as by the College of American Pathologists and the International Organization for Standardization, to overcome irreproducibility in biomedical research and facilitate metaanalyses. [33][34][35][36][37][38] Importantly, both parties must follow IRB guidance, and carefully consider intellectual property rights among all parties. Finally, a comprehensive data-management system designed specifically for translational research is a key tool to facilitate extensive collaborations between different groups, institutions, and even between academia and industry.…”

A Prospective Targeted Serum Metabolomics Study of Pancreatic Cancer in Postmenopausal Women

“…Several studies have used the metabolomics tool in pancreatic cancer early detection (22). One study found that the metabolite profiles are distinct among 50 patients with pancreatic cancer, 50 diabetic patients, and 50 healthy controls (23).…”